Early maturation processes in coal. Part 2
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ReaxFF方法研究的褐煤热解过程中硫的迁移机理王凤;李光跃;卢金荣;李莹莹;梁英华【摘要】采用ReaxFF(reactive force field,活性反应力场)分子动力学方法模拟了褐煤在1000 K~2 000 K下的热解过程,分析了热解温度对热解产物分布的影响,搜寻到了噻吩、硫酚和硫醚中硫元素迁移的基元反应以及热解产物中硫原子的存在形式.结果表明,热解温度是影响热解产物中硫元素分布的一个重要因素,高温会抑制硫从褐煤中逸出.在热解过程中,噻吩、硫酚和硫醚中的硫原子会通过硫自由基中间体进行相互转化.在热解结束时大多数硫原子以噻吩和硫醚的形式存在.【期刊名称】《煤炭转化》【年(卷),期】2016(039)001【总页数】5页(P21-25)【关键词】褐煤模型;ReaxFF;热解;硫迁移【作者】王凤;李光跃;卢金荣;李莹莹;梁英华【作者单位】华北理工大学化学工程学院,063009 河北唐山;华北理工大学化学工程学院,063009 河北唐山;华北理工大学化学工程学院,063009 河北唐山;华北理工大学化学工程学院,063009 河北唐山;华北理工大学化学工程学院,063009 河北唐山【正文语种】中文【中图分类】TQ530.2褐煤在我国储量丰富,具有广泛的利用方式,如燃烧、热解、炼焦、液化、气化和提取褐煤蜡等.[1]为避免褐煤中硫元素在其处理过程中产生的SO2和H2S等气体对环境产生污染,研究褐煤的脱硫技术日益迫切.煤的热解除了能提高煤综合利用效率,还能解决煤中污染物特别是硫的脱除问题.因此,煤的热解可作为褐煤脱硫技术的一种重要方法.研究硫原子在褐煤中的迁移规律有利于设计脱硫工艺,但在此过程中硫原子迁移速度很快,很难用当前的实验设备或手段检测其反应中间体,从而获得硫原子迁移的反应机理.随着计算机技术的发展,动力学模拟(molecular dynamics)方法开始应用到研究煤的一系列反应中.[23]活性反应力场(reactive force field,ReaxFF)是由美国宾州大学van Duin[45]开发的一种动力学模拟方法,可以处理包括褐煤在内的复杂体系的化学反应.Zheng et al[2]利用ReaxFF方法模拟了烟煤成熟过程中的热解过程,获得具体反应和产物等动力学信息,进而解释了烟煤初始的热解机理.本课题组[6]用ReaxFF方法对离子交换褐煤热解机理进行了研究,观察了金属化合物在褐煤热解中的作用.结果显示,加入的金属化合物不仅会大大降低其中的脱羧反应与C—O桥键断裂的势垒,同时也使最终产物变得稳定.基于此,本工作利用ReaxFF方法模拟褐煤热解过程中硫原子的迁移过程,希望为研究褐煤的热解脱硫工艺提供参考.1.1三维模型的构建选用Wofrum[7]提出的褐煤分子模型作为褐煤结构的基本单元.由于计算方法所限,对其进行了修改(见图1)(分子式为C220H195O38N4S3,简写为W,其结构见图1a).该模型由多组分交联而成,官能团种类比较多,符合褐煤的实际结构特点.在W中硫分别以硫醇、硫醚和噻吩形式存在,为研究褐煤热解过程中硫原子的迁移规律提供了有利条件.首先用LAMMPS软件[8]中的Dreiding力场[9]对W分子进行优化.两相模型理论[10]指出煤的大分子网络结构中会镶嵌着一些小分子结构.为了表达煤的这种结构特点,将W分子拆分成小的分子片段,然后利用Packmol软件[11]将9个优化后的W模型分子和5组W模型的小分子碎片模型放在5.5nm×5.5nm×5.5nm的周期性边界势箱中,并进行优化,构建成密度为0.498 9g/cm3的褐煤模型(见图1b).1.2 ReaxFF方法模拟根据文献[12-13],温度只影响反应速率,而不是反应途径.由于化学反应通常在高温下更易发生,为了减少模拟时间,设定的模拟反应温度远远高于实验温度.本工作中模拟温度分别设定为1 000K,1 200K,1 400K,1 600K,1 800K和2 000K.ReaxFF分子力学模拟时间步长为0.25fs,阻尼常数为100fs,模拟中使用Castro-marcano[14]提出的参数,此参数适用于含H,C,O,N和S的分子,压力为0.1MPa,模拟时间为300ps.为了与实际的热解过程相符,设定0ps~50ps为升温过程,构建的褐煤系统由298K以恒定速率在50ps时间内升到设定温度;50ps~250ps为恒温过程,褐煤系统在设定温度下恒温反应200ps;250ps~300ps为降温过程,褐煤系统由设定温度以恒定速率在50ps内降到298K.在模拟中,对褐煤系统包括硫原子在内的所有原子都进行了标记和追踪.利用编写的C++程序[15],分析系统中发生的键的生成和键的断裂反应.2.1热解产物的分布参照文献[2],定义热解产物中碳原子个数大于40的结构碎片为C40+组分;碳原子个数在5~40的结构碎片为C5~C40组分.表1为用ReaxFF方法模拟褐煤热解过程中,不同热解温度下C40+组分和C5~C40组分的分布以及C40+组分中硫的分布.由表1可以看出,褐煤模型的C40+组分的产率随热解温度的升高而降低,当热解温度高于1 400K时,C40+组分的产率降低速率变小;C5~C40组分的产率随热解温度的升高先增大后减小,热解温度在1 400K时达到最大,且在该温度下C5~C40组分产率的增加幅度最大,热解温度高于1 400K后,C5~C40组分的产率变化减小. C40+组分和C5~C40组分产率的变化表明,热解温度是影响热解产物分布的一个重要因素,热解温度在1 200K~1 400K时,褐煤模型的有机大分子的裂解反应占优势,大于1 400K以后,褐煤模型的有机大分子的聚合反应占优势.硫在C40+组分的含量随着热解温度的升高逐渐增大,高温会抑制硫从褐煤中逸出.为了控制硫在C40+组分的含量,热解温度不宜过高.2.2含硫官能团中硫的迁移煤在热解过程中,伴随着分子间桥键的断裂,分解成小的分子片段.Attar[16]认为在热解过程中C—S键断裂形成含硫的自由基碎片是硫迁移反应的决定性步骤.煤中的有机硫化合物的热稳定性差异很大,脂肪硫最不稳定,很容易分解成H2S和不饱和烃类化合物;芳香硫相对稳定,在H2气氛下易生成不饱和化合物;噻吩型硫参与了环的共振,使C—S键更加稳定,而难以分解.为了研究在褐煤热解过程中硫原子的迁移规律,用ReaxFF方法分别跟踪了W模型中噻吩型硫、硫酚型硫和硫醚型硫的迁移情况,下面以2 000K下的热解反应为例.2.2.1 噻吩型硫的迁移以褐煤模型中含噻吩的结构片段A(见第23页图2)中键的断裂与生成反应为例,观察噻吩型硫的迁移变化.片段A包含一个芳香环和一个噻吩环.噻吩型硫的结构比较稳定,在热解过程中比其他非噻吩型硫复杂.在热解反应中随着时间的延长,结构片段A中的噻吩环扭曲,S—C1键逐渐被拉长.键长被拉长时,键能变小,键容易断裂.在40.5ps时,S—C1键的键长大于0.193nm,S—C1键断裂,说明S—C1键是片段A中的弱键,热解时会优先断裂,是热解过程中硫脱除的引发键;在91ps时,与S相连的六元环的C2~C3键断裂,六元环经环的重排后变为五元环,形成C—S·自由基,其构象如110.5ps时所示;在254.5ps时,C—S·自由基中的S原子与体系中的其他烃类化合物中的C5原子逐渐靠近,当距离小于0.169nm时,发生交联反应,形成含有硫醚键的大分子结构,即255ps所示构象.2.2.2 硫酚型硫的迁移褐煤模型中以含硫酚的结构片段B(见图3)为例,观察硫酚中硫原子的迁移变化.片段B是一个多元环化合物,包含两个芳香环和一个呋喃环,B中的硫为硫酚.对于硫酚而言,在煤热解过程中,其中的苯环结构比较稳定,很难发生键的断裂,因此,硫酚中键的断裂基本发生在C—S键处.结构片段B在热解反应中随着时间的延长,硫酚中的S—H键逐渐被拉长,褐煤系统中的其他烃类化合物中的C1原子逐渐向S原子靠近,在50.5ps时,C1原子和S原子间的距离达到0.266nm;53.5ps时,硫酚中的S—H键进一步被拉长而断裂,C1原子与S原子的距离也进一步靠近,为0.265 nm;55.5ps时,S—C1键的键长达到0.130nm,便发生交联反应,此时芳香环上的S—C2键被逐渐拉长,距离为0.184nm;60ps时,S—C2键被拉长至0.198nm而断裂,芳香环上的C2原子与体系中烃类化合物中的C1原子正逐渐靠近;73ps时,C2原子与C1原子距离为0.153nm,C2原子与C1原子发生键合反应;75.5ps时,S原子和另一芳香环上的C3原子逐步靠近,当距离小于0.178nm时发生交联反应,形成含有噻吩型有机硫的大分子网络化合物.噻吩型硫在热解过程中会进一步发生一系列的迁移变化,与结构片段A所经历的过程类似.2.2.3 硫醚型硫的迁移褐煤模型中以含硫醚的结构片段C(见图4)为例,观察硫醚中硫的迁移变化,片段C为芳香硫醚.在热解反应中随着时间的延长,结构片段C中的S—C1键被拉长,10.5ps时,S—C1键的键长超过0.181nm而断裂,形成C—S·自由基;15.5ps时,C—S·自由基夺取H·自由基形成硫酚.整个过程经历的时间很短,说明硫醚键在热解过程中比较容易断裂.形成的硫酚会经历与结构片段B类似的过程.由图2、图3和图4可以看出,在热解过程中会产生硫自由基,可以想办法将其中的硫自由基与其他自由基反应(如在体系中加入H2),减少与含碳的自由基反应进而可以减少煤的大分子网络结构中的硫原子,这对于研究褐煤的热解脱硫工艺具有重要意义.2.3模型中硫原子在热解结束时的存在形式褐煤热解时硫原子会存在各种形态间的转化,可能是因为设置的褐煤体系是一个密封的体系,在热解过程中产生的H2S等气体没有逸出体系,和活性硫等一起与一些固相中的小分子烃或芳构化的自由基发生键合反应,再次形成噻吩和硫醚等结构固定在大分子网络结构中.在本研究中,褐煤模型中噻吩型硫、硫酚型硫和硫醚型硫经过300ps热解(热解温度为2 000K)反应后,其中的硫原子主要以噻吩型硫和硫醚型硫两种形式存在(见图5).其中噻吩型硫占总硫个数的42.86%,硫醚型硫占总硫个数的40.18%,其他的含硫化合物中硫仅占总硫个数的16.96%(见图6).与在实际热解产物半焦中大部分的硫原子以噻吩型硫和硫醚型硫存在于大分子网络结构中这一事实相符.1)热解温度是影响热解产物分布的一个重要因素,高温会抑制硫从褐煤中逸出.为了控制硫在C40+组分的含量,热解温度不宜过高.2)用ReaxFF方法分别跟踪了褐煤模型中噻吩、硫酚和硫醚中的硫原子在热解过程中的迁移情况,得到不同时间点硫原子与其他原子发生的键的断裂与键的生成反应,搜寻到了噻吩、硫酚和硫醚中的硫原子迁移的基元反应.3)在热解过程中,噻吩、硫酚和硫醚中的硫原子会通过硫自由基中间体进行相互转化.在热解结束时硫原子主要以噻吩型硫和硫醚型硫存在于煤的大分子网络结构中,与实际热解情况相符.【相关文献】[1]董洪峰,云增杰,曹勇飞.我国褐煤的综合利用途径及前景展望[J].煤炭技术,2008,27(9):122-124.[2] ZHENG Mo,LI Xiaoxia,LIU Jian,etal.Initial Chemical Reaction Simulation of Coal Pyrolysis via ReaxFF Molecular Dynamics[J].Energy and Fuels,2013,27(6):2942-2951.[3] ZHAN Jinhui,WU Rongcheng,LIU Xiaoxing,etal.Preliminary Understanding of Initial Reaction Process for Subbituminous Coal Pyrolysis with Molecular Dynamics Simulation[J].Fuel,2014,134:283-292.[4] AGRAWALLA S,van DUIN A C T.Development and Application of a ReaxFF Reactive Force Field for Hydrogen Combustion[J].The Journal of Physical Chemistry A,2011,115(6):960-972.[5] NOMRUA K I,KALIA R K,NAKANO A,etal.A Scalable Parallel Algorithm for Large-scale Reactive Force-field Molecular Dynamics Simulations[J].Computer Physics Communications,2008,178(2):73-87.[6] LI Guangyue,XIE Quanan,ZHANG Hang,etal.Pyrolysis Mechanism of Metal-ion-exchanged Lignite:a Combined Reactive Force Field and Density Functional Theory Study[J].Energy and Fuels,2014,28(8):5373-5381.[7] WOLFRUM E A.Correlation Between Petrographic Properties,Chemical Structure,and Technological Behavior of Rhenish Brown Coal[C]∥The Chemistry of Low-rank Coals.ACS Symposium Series.Washington D C:American Chemical Society,1983:15-37. 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MODERNOPERATINGSYSTEMSTHIRD EDITION PROBLEM SOLUTIONSANDREW S.TANENBAUMVrije UniversiteitAmsterdam,The NetherlandsPRENTICE HALLUPPER SADDLE RIVER,NJ07458Copyright Pearson Education,Inc.2008SOLUTIONS TO CHAPTER1PROBLEMS1.Multiprogramming is the rapid switching of the CPU between multiple proc-esses in memory.It is commonly used to keep the CPU busy while one or more processes are doing I/O.2.Input spooling is the technique of reading in jobs,for example,from cards,onto the disk,so that when the currently executing processes arefinished, there will be work waiting for the CPU.Output spooling consists offirst copying printablefiles to disk before printing them,rather than printing di-rectly as the output is generated.Input spooling on a personal computer is not very likely,but output spooling is.3.The prime reason for multiprogramming is to give the CPU something to dowhile waiting for I/O to complete.If there is no DMA,the CPU is fully occu-pied doing I/O,so there is nothing to be gained(at least in terms of CPU utili-zation)by multiprogramming.No matter how much I/O a program does,the CPU will be100%busy.This of course assumes the major delay is the wait while data are copied.A CPU could do other work if the I/O were slow for other reasons(arriving on a serial line,for instance).4.It is still alive.For example,Intel makes Pentium I,II,and III,and4CPUswith a variety of different properties including speed and power consumption.All of these machines are architecturally compatible.They differ only in price and performance,which is the essence of the family idea.5.A25×80character monochrome text screen requires a2000-byte buffer.The1024×768pixel24-bit color bitmap requires2,359,296bytes.In1980these two options would have cost$10and$11,520,respectively.For current prices,check on how much RAM currently costs,probably less than$1/MB.6.Consider fairness and real time.Fairness requires that each process be allo-cated its resources in a fair way,with no process getting more than its fair share.On the other hand,real time requires that resources be allocated based on the times when different processes must complete their execution.A real-time process may get a disproportionate share of the resources.7.Choices(a),(c),and(d)should be restricted to kernel mode.8.It may take20,25or30msec to complete the execution of these programsdepending on how the operating system schedules them.If P0and P1are scheduled on the same CPU and P2is scheduled on the other CPU,it will take20mses.If P0and P2are scheduled on the same CPU and P1is scheduled on the other CPU,it will take25msec.If P1and P2are scheduled on the same CPU and P0is scheduled on the other CPU,it will take30msec.If all three are on the same CPU,it will take35msec.2PROBLEM SOLUTIONS FOR CHAPTER19.Every nanosecond one instruction emerges from the pipeline.This means themachine is executing1billion instructions per second.It does not matter at all how many stages the pipeline has.A10-stage pipeline with1nsec per stage would also execute1billion instructions per second.All that matters is how often afinished instruction pops out the end of the pipeline.10.Average access time=0.95×2nsec(word is cache)+0.05×0.99×10nsec(word is in RAM,but not in cache)+0.05×0.01×10,000,000nsec(word on disk only)=5002.395nsec=5.002395μsec11.The manuscript contains80×50×700=2.8million characters.This is,ofcourse,impossible tofit into the registers of any currently available CPU and is too big for a1-MB cache,but if such hardware were available,the manuscript could be scanned in2.8msec from the registers or5.8msec from the cache.There are approximately27001024-byte blocks of data,so scan-ning from the disk would require about27seconds,and from tape2minutes7 seconds.Of course,these times are just to read the data.Processing and rewriting the data would increase the time.12.Maybe.If the caller gets control back and immediately overwrites the data,when the writefinally occurs,the wrong data will be written.However,if the driverfirst copies the data to a private buffer before returning,then the caller can be allowed to continue immediately.Another possibility is to allow the caller to continue and give it a signal when the buffer may be reused,but this is tricky and error prone.13.A trap instruction switches the execution mode of a CPU from the user modeto the kernel mode.This instruction allows a user program to invoke func-tions in the operating system kernel.14.A trap is caused by the program and is synchronous with it.If the program isrun again and again,the trap will always occur at exactly the same position in the instruction stream.An interrupt is caused by an external event and its timing is not reproducible.15.The process table is needed to store the state of a process that is currentlysuspended,either ready or blocked.It is not needed in a single process sys-tem because the single process is never suspended.16.Mounting afile system makes anyfiles already in the mount point directoryinaccessible,so mount points are normally empty.However,a system admin-istrator might want to copy some of the most importantfiles normally located in the mounted directory to the mount point so they could be found in their normal path in an emergency when the mounted device was being repaired.PROBLEM SOLUTIONS FOR CHAPTER13 17.A system call allows a user process to access and execute operating systemfunctions inside the er programs use system calls to invoke operat-ing system services.18.Fork can fail if there are no free slots left in the process table(and possibly ifthere is no memory or swap space left).Exec can fail if thefile name given does not exist or is not a valid executablefile.Unlink can fail if thefile to be unlinked does not exist or the calling process does not have the authority to unlink it.19.If the call fails,for example because fd is incorrect,it can return−1.It canalso fail because the disk is full and it is not possible to write the number of bytes requested.On a correct termination,it always returns nbytes.20.It contains the bytes:1,5,9,2.21.Time to retrieve thefile=1*50ms(Time to move the arm over track#50)+5ms(Time for thefirst sector to rotate under the head)+10/100*1000ms(Read10MB)=155ms22.Block specialfiles consist of numbered blocks,each of which can be read orwritten independently of all the other ones.It is possible to seek to any block and start reading or writing.This is not possible with character specialfiles.23.System calls do not really have names,other than in a documentation sense.When the library procedure read traps to the kernel,it puts the number of the system call in a register or on the stack.This number is used to index into a table.There is really no name used anywhere.On the other hand,the name of the library procedure is very important,since that is what appears in the program.24.Yes it can,especially if the kernel is a message-passing system.25.As far as program logic is concerned it does not matter whether a call to a li-brary procedure results in a system call.But if performance is an issue,if a task can be accomplished without a system call the program will run faster.Every system call involves overhead time in switching from the user context to the kernel context.Furthermore,on a multiuser system the operating sys-tem may schedule another process to run when a system call completes, further slowing the progress in real time of a calling process.26.Several UNIX calls have no counterpart in the Win32API:Link:a Win32program cannot refer to afile by an alternative name or see it in more than one directory.Also,attempting to create a link is a convenient way to test for and create a lock on afile.4PROBLEM SOLUTIONS FOR CHAPTER1Mount and umount:a Windows program cannot make assumptions about standard path names because on systems with multiple disk drives the drive name part of the path may be different.Chmod:Windows uses access control listsKill:Windows programmers cannot kill a misbehaving program that is not cooperating.27.Every system architecture has its own set of instructions that it can execute.Thus a Pentium cannot execute SPARC programs and a SPARC cannot exe-cute Pentium programs.Also,different architectures differ in bus architecture used(such as VME,ISA,PCI,MCA,SBus,...)as well as the word size of the CPU(usually32or64bit).Because of these differences in hardware,it is not feasible to build an operating system that is completely portable.A highly portable operating system will consist of two high-level layers---a machine-dependent layer and a machine independent layer.The machine-dependent layer addresses the specifics of the hardware,and must be implemented sepa-rately for every architecture.This layer provides a uniform interface on which the machine-independent layer is built.The machine-independent layer has to be implemented only once.To be highly portable,the size of the machine-dependent layer must be kept as small as possible.28.Separation of policy and mechanism allows OS designers to implement asmall number of basic primitives in the kernel.These primitives are sim-plified,because they are not dependent of any specific policy.They can then be used to implement more complex mechanisms and policies at the user level.29.The conversions are straightforward:(a)A micro year is10−6×365×24×3600=31.536sec.(b)1000meters or1km.(c)There are240bytes,which is1,099,511,627,776bytes.(d)It is6×1024kg.SOLUTIONS TO CHAPTER2PROBLEMS1.The transition from blocked to running is conceivable.Suppose that a processis blocked on I/O and the I/Ofinishes.If the CPU is otherwise idle,the proc-ess could go directly from blocked to running.The other missing transition, from ready to blocked,is impossible.A ready process cannot do I/O or any-thing else that might block it.Only a running process can block.PROBLEM SOLUTIONS FOR CHAPTER25 2.You could have a register containing a pointer to the current process tableentry.When I/O completed,the CPU would store the current machine state in the current process table entry.Then it would go to the interrupt vector for the interrupting device and fetch a pointer to another process table entry(the ser-vice procedure).This process would then be started up.3.Generally,high-level languages do not allow the kind of access to CPU hard-ware that is required.For instance,an interrupt handler may be required to enable and disable the interrupt servicing a particular device,or to manipulate data within a process’stack area.Also,interrupt service routines must exe-cute as rapidly as possible.4.There are several reasons for using a separate stack for the kernel.Two ofthem are as follows.First,you do not want the operating system to crash be-cause a poorly written user program does not allow for enough stack space.Second,if the kernel leaves stack data in a user program’s memory space upon return from a system call,a malicious user might be able to use this data tofind out information about other processes.5.If each job has50%I/O wait,then it will take20minutes to complete in theabsence of competition.If run sequentially,the second one willfinish40 minutes after thefirst one starts.With two jobs,the approximate CPU utiliza-tion is1−0.52.Thus each one gets0.375CPU minute per minute of real time.To accumulate10minutes of CPU time,a job must run for10/0.375 minutes,or about26.67minutes.Thus running sequentially the jobsfinish after40minutes,but running in parallel theyfinish after26.67minutes.6.It would be difficult,if not impossible,to keep thefile system consistent.Sup-pose that a client process sends a request to server process1to update afile.This process updates the cache entry in its memory.Shortly thereafter,anoth-er client process sends a request to server2to read thatfile.Unfortunately,if thefile is also cached there,server2,in its innocence,will return obsolete data.If thefirst process writes thefile through to the disk after caching it, and server2checks the disk on every read to see if its cached copy is up-to-date,the system can be made to work,but it is precisely all these disk ac-cesses that the caching system is trying to avoid.7.No.If a single-threaded process is blocked on the keyboard,it cannot fork.8.A worker thread will block when it has to read a Web page from the disk.Ifuser-level threads are being used,this action will block the entire process, destroying the value of multithreading.Thus it is essential that kernel threads are used to permit some threads to block without affecting the others.9.Yes.If the server is entirely CPU bound,there is no need to have multiplethreads.It just adds unnecessary complexity.As an example,consider a tele-phone directory assistance number(like555-1212)for an area with1million6PROBLEM SOLUTIONS FOR CHAPTER2people.If each(name,telephone number)record is,say,64characters,the entire database takes64megabytes,and can easily be kept in the server’s memory to provide fast lookup.10.When a thread is stopped,it has values in the registers.They must be saved,just as when the process is stopped the registers must be saved.Multipro-gramming threads is no different than multiprogramming processes,so each thread needs its own register save area.11.Threads in a process cooperate.They are not hostile to one another.If yield-ing is needed for the good of the application,then a thread will yield.After all,it is usually the same programmer who writes the code for all of them. er-level threads cannot be preempted by the clock unless the whole proc-ess’quantum has been used up.Kernel-level threads can be preempted indivi-dually.In the latter case,if a thread runs too long,the clock will interrupt the current process and thus the current thread.The kernel is free to pick a dif-ferent thread from the same process to run next if it so desires.13.In the single-threaded case,the cache hits take15msec and cache misses take90msec.The weighted average is2/3×15+1/3×90.Thus the mean re-quest takes40msec and the server can do25per second.For a multithreaded server,all the waiting for the disk is overlapped,so every request takes15 msec,and the server can handle662/3requests per second.14.The biggest advantage is the efficiency.No traps to the kernel are needed toswitch threads.The biggest disadvantage is that if one thread blocks,the en-tire process blocks.15.Yes,it can be done.After each call to pthread create,the main programcould do a pthread join to wait until the thread just created has exited before creating the next thread.16.The pointers are really necessary because the size of the global variable isunknown.It could be anything from a character to an array offloating-point numbers.If the value were stored,one would have to give the size to create global,which is all right,but what type should the second parameter of set global be,and what type should the value of read global be?17.It could happen that the runtime system is precisely at the point of blocking orunblocking a thread,and is busy manipulating the scheduling queues.This would be a very inopportune moment for the clock interrupt handler to begin inspecting those queues to see if it was time to do thread switching,since they might be in an inconsistent state.One solution is to set aflag when the run-time system is entered.The clock handler would see this and set its ownflag, then return.When the runtime systemfinished,it would check the clockflag, see that a clock interrupt occurred,and now run the clock handler.PROBLEM SOLUTIONS FOR CHAPTER27 18.Yes it is possible,but inefficient.A thread wanting to do a system callfirstsets an alarm timer,then does the call.If the call blocks,the timer returns control to the threads package.Of course,most of the time the call will not block,and the timer has to be cleared.Thus each system call that might block has to be executed as three system calls.If timers go off prematurely,all kinds of problems can develop.This is not an attractive way to build a threads package.19.The priority inversion problem occurs when a low-priority process is in itscritical region and suddenly a high-priority process becomes ready and is scheduled.If it uses busy waiting,it will run forever.With user-level threads,it cannot happen that a low-priority thread is suddenly preempted to allow a high-priority thread run.There is no preemption.With kernel-level threads this problem can arise.20.With round-robin scheduling it works.Sooner or later L will run,and eventu-ally it will leave its critical region.The point is,with priority scheduling,L never gets to run at all;with round robin,it gets a normal time slice periodi-cally,so it has the chance to leave its critical region.21.Each thread calls procedures on its own,so it must have its own stack for thelocal variables,return addresses,and so on.This is equally true for user-level threads as for kernel-level threads.22.Yes.The simulated computer could be multiprogrammed.For example,while process A is running,it reads out some shared variable.Then a simula-ted clock tick happens and process B runs.It also reads out the same vari-able.Then it adds1to the variable.When process A runs,if it also adds one to the variable,we have a race condition.23.Yes,it still works,but it still is busy waiting,of course.24.It certainly works with preemptive scheduling.In fact,it was designed forthat case.When scheduling is nonpreemptive,it might fail.Consider the case in which turn is initially0but process1runsfirst.It will just loop forever and never release the CPU.25.To do a semaphore operation,the operating systemfirst disables interrupts.Then it reads the value of the semaphore.If it is doing a down and the sema-phore is equal to zero,it puts the calling process on a list of blocked processes associated with the semaphore.If it is doing an up,it must check to see if any processes are blocked on the semaphore.If one or more processes are block-ed,one of them is removed from the list of blocked processes and made run-nable.When all these operations have been completed,interrupts can be enabled again.8PROBLEM SOLUTIONS FOR CHAPTER226.Associated with each counting semaphore are two binary semaphores,M,used for mutual exclusion,and B,used for blocking.Also associated with each counting semaphore is a counter that holds the number of up s minus the number of down s,and a list of processes blocked on that semaphore.To im-plement down,a processfirst gains exclusive access to the semaphores, counter,and list by doing a down on M.It then decrements the counter.If it is zero or more,it just does an up on M and exits.If M is negative,the proc-ess is put on the list of blocked processes.Then an up is done on M and a down is done on B to block the process.To implement up,first M is down ed to get mutual exclusion,and then the counter is incremented.If it is more than zero,no one was blocked,so all that needs to be done is to up M.If, however,the counter is now negative or zero,some process must be removed from the list.Finally,an up is done on B and M in that order.27.If the program operates in phases and neither process may enter the nextphase until both arefinished with the current phase,it makes perfect sense to use a barrier.28.With kernel threads,a thread can block on a semaphore and the kernel canrun some other thread in the same process.Consequently,there is no problem using semaphores.With user-level threads,when one thread blocks on a semaphore,the kernel thinks the entire process is blocked and does not run it ever again.Consequently,the process fails.29.It is very expensive to implement.Each time any variable that appears in apredicate on which some process is waiting changes,the run-time system must re-evaluate the predicate to see if the process can be unblocked.With the Hoare and Brinch Hansen monitors,processes can only be awakened on a signal primitive.30.The employees communicate by passing messages:orders,food,and bags inthis case.In UNIX terms,the four processes are connected by pipes.31.It does not lead to race conditions(nothing is ever lost),but it is effectivelybusy waiting.32.It will take nT sec.33.In simple cases it may be possible to determine whether I/O will be limitingby looking at source code.For instance a program that reads all its inputfiles into buffers at the start will probably not be I/O bound,but a problem that reads and writes incrementally to a number of differentfiles(such as a compi-ler)is likely to be I/O bound.If the operating system provides a facility such as the UNIX ps command that can tell you the amount of CPU time used by a program,you can compare this with the total time to complete execution of the program.This is,of course,most meaningful on a system where you are the only user.34.For multiple processes in a pipeline,the common parent could pass to the op-erating system information about the flow of data.With this information the OS could,for instance,determine which process could supply output to a process blocking on a call for input.35.The CPU efficiency is the useful CPU time divided by the total CPU time.When Q ≥T ,the basic cycle is for the process to run for T and undergo a process switch for S .Thus (a)and (b)have an efficiency of T /(S +T ).When the quantum is shorter than T ,each run of T will require T /Q process switches,wasting a time ST /Q .The efficiency here is thenT +ST /QT which reduces to Q /(Q +S ),which is the answer to (c).For (d),we just sub-stitute Q for S and find that the efficiency is 50%.Finally,for (e),as Q →0the efficiency goes to 0.36.Shortest job first is the way to minimize average response time.0<X ≤3:X ,3,5,6,9.3<X ≤5:3,X ,5,6,9.5<X ≤6:3,5,X ,6,9.6<X ≤9:3,5,6,X ,9.X >9:3,5,6,9,X.37.For round robin,during the first 10minutes each job gets 1/5of the CPU.Atthe end of 10minutes,C finishes.During the next 8minutes,each job gets 1/4of the CPU,after which time D finishes.Then each of the three remaining jobs gets 1/3of the CPU for 6minutes,until B finishes,and so on.The fin-ishing times for the five jobs are 10,18,24,28,and 30,for an average of 22minutes.For priority scheduling,B is run first.After 6minutes it is finished.The other jobs finish at 14,24,26,and 30,for an average of 18.8minutes.If the jobs run in the order A through E ,they finish at 10,16,18,22,and 30,for an average of 19.2minutes.Finally,shortest job first yields finishing times of 2,6,12,20,and 30,for an average of 14minutes.38.The first time it gets 1quantum.On succeeding runs it gets 2,4,8,and 15,soit must be swapped in 5times.39.A check could be made to see if the program was expecting input and didanything with it.A program that was not expecting input and did not process it would not get any special priority boost.40.The sequence of predictions is 40,30,35,and now 25.41.The fraction of the CPU used is35/50+20/100+10/200+x/250.To beschedulable,this must be less than1.Thus x must be less than12.5msec. 42.Two-level scheduling is needed when memory is too small to hold all theready processes.Some set of them is put into memory,and a choice is made from that set.From time to time,the set of in-core processes is adjusted.This algorithm is easy to implement and reasonably efficient,certainly a lot better than,say,round robin without regard to whether a process was in memory or not.43.Each voice call runs200times/second and uses up1msec per burst,so eachvoice call needs200msec per second or400msec for the two of them.The video runs25times a second and uses up20msec each time,for a total of 500msec per second.Together they consume900msec per second,so there is time left over and the system is schedulable.44.The kernel could schedule processes by any means it wishes,but within eachprocess it runs threads strictly in priority order.By letting the user process set the priority of its own threads,the user controls the policy but the kernel handles the mechanism.45.The change would mean that after a philosopher stopped eating,neither of hisneighbors could be chosen next.In fact,they would never be chosen.Sup-pose that philosopher2finished eating.He would run test for philosophers1 and3,and neither would be started,even though both were hungry and both forks were available.Similarly,if philosopher4finished eating,philosopher3 would not be started.Nothing would start him.46.If a philosopher blocks,neighbors can later see that she is hungry by checkinghis state,in test,so he can be awakened when the forks are available.47.Variation1:readers have priority.No writer may start when a reader is ac-tive.When a new reader appears,it may start immediately unless a writer is currently active.When a writerfinishes,if readers are waiting,they are all started,regardless of the presence of waiting writers.Variation2:Writers have priority.No reader may start when a writer is waiting.When the last ac-tive processfinishes,a writer is started,if there is one;otherwise,all the readers(if any)are started.Variation3:symmetric version.When a reader is active,new readers may start immediately.When a writerfinishes,a new writer has priority,if one is waiting.In other words,once we have started reading,we keep reading until there are no readers left.Similarly,once we have started writing,all pending writers are allowed to run.48.A possible shell script might beif[!–f numbers];then echo0>numbers;ficount=0while(test$count!=200)docount=‘expr$count+1‘n=‘tail–1numbers‘expr$n+1>>numbersdoneRun the script twice simultaneously,by starting it once in the background (using&)and again in the foreground.Then examine thefile numbers.It will probably start out looking like an orderly list of numbers,but at some point it will lose its orderliness,due to the race condition created by running two cop-ies of the script.The race can be avoided by having each copy of the script test for and set a lock on thefile before entering the critical area,and unlock-ing it upon leaving the critical area.This can be done like this:if ln numbers numbers.lockthenn=‘tail–1numbers‘expr$n+1>>numbersrm numbers.lockfiThis version will just skip a turn when thefile is inaccessible,variant solu-tions could put the process to sleep,do busy waiting,or count only loops in which the operation is successful.SOLUTIONS TO CHAPTER3PROBLEMS1.It is an accident.The base register is16,384because the program happened tobe loaded at address16,384.It could have been loaded anywhere.The limit register is16,384because the program contains16,384bytes.It could have been any length.That the load address happens to exactly match the program length is pure coincidence.2.Almost the entire memory has to be copied,which requires each word to beread and then rewritten at a different location.Reading4bytes takes10nsec, so reading1byte takes2.5nsec and writing it takes another2.5nsec,for a total of5nsec per byte compacted.This is a rate of200,000,000bytes/sec.To copy128MB(227bytes,which is about1.34×108bytes),the computer needs227/200,000,000sec,which is about671msec.This number is slightly pessimistic because if the initial hole at the bottom of memory is k bytes, those k bytes do not need to be copied.However,if there are many holes andmany data segments,the holes will be small,so k will be small and the error in the calculation will also be small.3.The bitmap needs1bit per allocation unit.With227/n allocation units,this is224/n bytes.The linked list has227/216or211nodes,each of8bytes,for a total of214bytes.For small n,the linked list is better.For large n,the bitmap is better.The crossover point can be calculated by equating these two formu-las and solving for n.The result is1KB.For n smaller than1KB,a linked list is better.For n larger than1KB,a bitmap is better.Of course,the assumption of segments and holes alternating every64KB is very unrealistic.Also,we need n<=64KB if the segments and holes are64KB.4.Firstfit takes20KB,10KB,18KB.Bestfit takes12KB,10KB,and9KB.Worstfit takes20KB,18KB,and15KB.Nextfit takes20KB,18KB,and9 KB.5.For a4-KB page size the(page,offset)pairs are(4,3616),(8,0),and(14,2656).For an8-KB page size they are(2,3616),(4,0),and(7,2656).6.They built an MMU and inserted it between the8086and the bus.Thus all8086physical addresses went into the MMU as virtual addresses.The MMU then mapped them onto physical addresses,which went to the bus.7.(a)M has to be at least4,096to ensure a TLB miss for every access to an ele-ment of X.Since N only affects how many times X is accessed,any value of N will do.(b)M should still be atleast4,096to ensure a TLB miss for every access to anelement of X.But now N should be greater than64K to thrash the TLB, that is,X should exceed256KB.8.The total virtual address space for all the processes combined is nv,so thismuch storage is needed for pages.However,an amount r can be in RAM,so the amount of disk storage required is only nv−r.This amount is far more than is ever needed in practice because rarely will there be n processes ac-tually running and even more rarely will all of them need the maximum al-lowed virtual memory.9.The page table contains232/213entries,which is524,288.Loading the pagetable takes52msec.If a process gets100msec,this consists of52msec for loading the page table and48msec for running.Thus52%of the time is spent loading page tables.10.(a)We need one entry for each page,or224=16×1024×1024entries,sincethere are36=48−12bits in the page numberfield.。
强化学习的马尔可夫决策过程与值函数强化学习是一种机器学习领域中的方法,旨在使机器能够通过与环境互动来学习最佳行动策略。
马尔可夫决策过程(MDP)和值函数是强化学习中的两个核心概念。
在本文中,我们将详细介绍马尔可夫决策过程和值函数,并讨论它们在强化学习中的作用。
一、马尔可夫决策过程(MDP)马尔可夫决策过程是强化学习中用于建模决策问题的数学框架。
它是一种序列决策问题,其中智能体根据环境的状态进行决策,并接收激励信号来调整自己的行为。
MDP主要由以下几个要素组成:1. 状态空间(State Space):状态空间是指环境可能处于的所有状态的集合。
每个状态都代表了环境的一个特定配置。
在MDP中,状态可以是离散的(如棋盘上的位置)或连续的(如机器人的位置和速度)。
2. 动作空间(Action Space):动作空间是指智能体可以选择的所有可能动作的集合。
每个动作都会导致环境从一个状态转移到另一个状态。
3. 转移概率(Transition Probability):转移概率定义了在给定当前状态和动作的情况下,环境转移到下一个状态的概率。
这可以用一个转移函数来表示,即P(s'|s, a),其中s'代表下一个状态,s代表当前状态,a代表当前动作。
4. 奖励函数(Reward Function):奖励函数定义了智能体在不同状态和采取不同动作时获得的即时奖励。
奖励可以是正值、负值或零,用来评估智能体的行为。
5. 折扣因子(Discount Factor):折扣因子(通常用γ表示)被引入到MDP中,用于表示未来奖励的重要性相对于即时奖励的衰减程度。
如果折扣因子接近于0,智能体将更关注即时奖励;如果折扣因子接近于1,智能体将更关注未来的奖励。
基于上述要素,马尔可夫决策过程可以通过一个状态-动作-奖励的序列表示,即{<s_0, a_0, r_0>, <s_1, a_1, r_1>, <s_2, a_2,r_2>, ...}。
选煤专业英语词汇汇总选煤一般术语选煤Coal preparation毛煤Run of mine;原煤Raw coal原料煤Raw coal feed中煤middlings选煤Coal cleaning精煤Cleaned coal ; clean coal纯中煤True middlings; bone假中煤False middlings; Interbanded middlings矸石Reject; refuse废矸Diacard; dirt stone再循环Recirculation外来煤Foreign coal进口煤Imported coal低级煤Low-grade coal析离segregation分选特性Cleaning characteristics可选性曲线Wash ability curve可选性Wash ability; separability浮物累计曲线Cumulative floats curve浮物累计曲线累计曲线Cumulative sinks curve; Cumulative curve密度曲线Densimetric curve; relative density curve灰分特性曲线Characteristic ash curve邻近密度曲线Near-density curve; difficulty curve性能曲线浮沉试验Performance curve; Float-and-sink ;Analysis; Float-and-sink test 实际性能曲线Actual performance curve预期性能曲线expected performance curve迈尔曲线M-curve ;Mayer curve灰分/相对密度曲线Ash/relative density curve能力与处理量Capacity and throughput额定能力Nominal capacity生产能力Operational capacities设计能力Design capacity最大设计能力Peak design capacity 设备最大能力Mechanical maximum capacity 原料Feed原则流程图Basic flow sheet工艺流程图Process flow sheet设备流程图equipment flow sheet物料流程图Materials flow sheet液体流程图Liquids flow sheet能力流程图Weighted flow Sheet ; capacity flow sheet可浮性3)float ability矿井选煤厂Pithead coal preparation plant群矿选煤厂Group mine’s coal preparation plant矿区选煤厂Mine coal preparation plant中心选煤厂central coal preparation plant用户洗煤厂User’s coal preparation plant分选作业Separation process辅助作业Auxiliary process粒度size入料上限Top size入了下限Lower size分选粒级Size range of separation密度级Densimetric fractions; density fraction 密度组成Densimetric consist; density consist 分选密度±0.1含量法Classification of wash ability based onδ±0.1 near-density material中间煤含量法Classification of wash ability based on middling泥化Degradation in water煤泥(粉)浮沉试验Fine coal float- and sink test; fine coal float and-sink analysis水煤浆Coal water mixture;CWM;CWF;CWS洁净煤技术Clean coal technology可见矸石Vision refuse手选矸石Hand picked refuse粒级煤Sized coal块煤Lump coal大块煤Large sized coal中块煤Medium sized coal小块煤Small sized coal混煤Mixed coal混末煤Mixed small coal一般术语general分级1)sizing分级2)classification筛分试验Size analysis小筛分Sieve analysis平均粒度Mean size额定粒度Nominal size; limiting size筛上粒oversize筛下粒undersize粉尘dust粉煤fines末煤smalls筛分screening筛分Screening筛分机Screen振幅amplitude行程Stroke;throw孔径Aperture size干法筛分Dry screening湿法筛分Wet screening概率筛分Probability screening脱泥desliming脱粉Fines removal脱尘dedusting筛上物Screen overflow错配筛下粒Misplaced undersize筛下物Screen underflow错配筛上粒Misplaced oversize(筛分)错配物Misplaced material邻近筛孔物Near-mesh ma- terial; near-size material(筛子)额定面积Nominal area(筛子)有效面积effective area开孔率open area标准筛Sieve; test sieve筛分机的部件Parts screens筛面Screen deck; Screening surface筛板Screen plate筛网Screen cloth; Screen mesh楔条筛面Wedge-wire deck; wedge-wire sieve 活动棒条筛面Loose-rod deck缓冲筛面Dry screening按用途分类的筛分机Screens according to purpose毛煤筛Run-of-mine screen 预先分级筛Primary screen; Raw coal screen 脱水筛Dewatering screen脱泥筛Stroke;throw煤泥筛Slurry screen喷洗筛Rinsing screen; Spray screen分级筛(组)Sizing screen(s)Grading screen(s); classifying Screen(s)超粒控制筛Guard screen; Oversize control screen细粒控制筛Undersize control screen breakage screen按结构原理分类的筛分机Screens according to principle of construction单层筛Single-deck screen多层筛multi-deck screen摇动筛Jigging screen; Reciprocating screen 共振筛Resonance screen振动筛Vibrating screen旋转概率筛Rotating probability screen圆筒筛Trammel screen; Revolving screen滚轴筛Roll screen棒条筛Bar screen格筛grizzly弧形筛Sieve bend在气流或水流中分级Sizing in a current of air or water风力分级Air classification分级机classifier分级旋流器Cyclone classifier水力分级3)Hydraulic classification水析Vibrating screen沉降末速Terminal velocity等沉粒Equal falling particles等沉比Equal falling tatio自由沉降Free falling干扰沉降Hindered falling水力旋流器Hydro-cyclone准备筛分Preliminary screening检查筛分Control screening最终筛分Final screening等厚筛分banana screening气流筛分Air flow screening筛孔Screen aperture筛序Sieve scale筛比Sieve ratio粒度组成Size consist粒级Size fraction粒级上限Upper size粒级下限Lower size自然级Size fractions of raw coal破碎级Size fractions of crushed coal条缝筛Wedge-wire screen旋流筛V ortex sieve圆振动筛Circular vibrating screen直线振动筛Linear vibrating screen电磁振动筛Electro-magnetic vibrating screen振动概率筛Probability screen驰张筛Flip-flow screening machine等厚筛Banana vibrating screen电热筛Electric heated screen琴弦筛Piano wire screen高频振动筛High frequency vibrating screen振动棒条筛Loose-rod vibrating screen高频电磁细筛High frequency electromagnetic节肢振动筛Node-and-limb vibratory screen筛网旋流器cyclone screen cloth一般术语general干法选煤Dry cleaning湿法选煤Wet cleaning选煤厂Washery; coal preparation plant Reclean; rewash选煤产品Washery products矸石提升机Reject elevator; refuse elevator (deprecated)中煤提升机Middings elevator定压水箱Head tank溜槽launder泵池Pump sump悬浮体suspension流态化悬浮体Teeter; fluidized suspension 洗水系统Water circuit洗水闭路循环Closed water circuit循环水Circulating water 补充水Make-up water喷水Rinsing water; spray water废水Waste water; surplus water; bleed water井下水Pit water; mine water细泥slimes煤泥水slurry泡沫浮选Froth floatation重力选煤1)Gravity concentration; gravity separation跳汰选煤Water circuit重介质选煤Dense medium separation流槽选煤Coal laundering Trough washing 斜槽选煤Inclined-trough washing摇床选煤Table cleaning浮游选煤Coal floatation离心选煤Centrifugal cleaning摩擦选煤Friction cleaning主选Primary cleaning中间产物Intermediate product回选Recirculation cleaning配煤入洗Preparation of blended raw coal 分组入选Preparation of grouped raw coal 不分级入选Preparation of unsized raw coal分级入选Preparation of sized raw coal脱泥入选Preparation of deslimed raw coal 筛选厂Sizing plant干法选煤Dry cleaning手选Hand cleaning人工拣选Hand selection手选带Picking belt; picking table环形手选台Picking table circular风选Pneumatic cleaning风力摇床Dry cleaning table风力跳汰机Air jig风力跳汰2)Air jigging; pneumatic jigging 空气重介流化床干法选煤Dry beneficiation with air-dense medium fluidized bed检查性手选Control hand picking跳汰选煤jigging跳汰机Jig;washbox主选跳汰机Primary jig再选跳汰机Re-wash jig空气脉动跳汰机Air pulsating jig长石床层跳汰机feldspar jig动筛跳汰机Moving sieve jig活塞跳汰机plunger jig; piston jig隔膜跳汰机Diaphragm jigging跳汰筛板Jig screen plate; Bed plate跳汰床层Jig bed跳汰分室Jig cell跳汰分段Jig compartments跳汰机筛下室hutch跳汰机入料堰Jig feed sill跳汰机中间堰Jig center weir跳汰机溢流堰Jig discharge sill风阀Air valve滑动风阀Jig slide valve旋转风阀Rotary air valve跳汰机风阀周期Jig air cycle排矸装置Reject extractor浮标float床层传感器Bed depth transducer排矸室Reject extraction chamber排矸闸门Reject gate; discharger shutter排矸轮Reject rotor; star wheel extractor排矸螺旋Air valve排矸管Reject discharge pipes一段排矸提升机Primary reject elevator二段排矸提升机Secondary reject elevator 冲水Top water; transport water输送水flushing water顶水Under screen water; back water跳汰周期Jigging cycle跳汰周期特性曲线Characteristic curve of jigging cycle风阀特性曲线Characteristic curve of air valve跳汰频率Jig frequency跳汰振幅Jig amplitude水力跳汰Hydraulic jigging人工床层Artificial bed; feldspar bed床层松散度Mobility of the jig bed分层stratification透筛排料Discharge of heavy material through screen plate 正排矸Discharge of heavy dirt at the discharge end倒排矸Discharge of heavy dirt at the feed end跳汰室Jigging chamber空气室Air chamber跳汰面积Jig area电控气动风阀Electro-pneumatic valve筛侧空气室跳汰机Baum jig筛下空气室跳汰机Batac jig; tacub jig复合脉动跳汰机Compound pulsating jig 重介质选煤Dense medium cleaning重液Dense liquid重介质Dense medium; heavy medium重介质工艺Dense medium process重介质分选机Dense medium separator加重质Medium solids分选介质Separating medium; correct medium循环悬浮液Circulating medium补充悬浮液Make-up medium; make-up medium solids重介质回收Electro-pneumatic valve磁选机Magnetic separator磁性物Magnetics非磁性物Non-magnetics再生悬浮液Regenerated dense medium; recovered dense medium稀悬浮液Dilute medium浓悬浮液Over-dense medium重介车间Dense medium plant密度控制装置Density control device脱介筛Medium draining screen悬浮物Suspended matter介质回收筛Medium recovery screen喷水装置Shower box加重质制备Medium solids preparation悬浮液4)suspension悬浮液稳定性Stability of suspension分流Spilt flow预磁Pre-magnetization退磁de-magnetization磁性物含量Magnetic material content水平流Horizontal current上升流Upward current下降流Downward current斜轮重介质分选机Inclined lifting wheel separator; drew boy separator立轮重介质分选机vertical lifting wheel separator;刮板重介质分选机H.M vessel重介质旋流器Dense-medium cyclone筒式磁选机Drum magnetic separator圆筒带式磁选机Drum-belt magnetic separator磁力脱水槽magnetic dewatering风力提升器Air lifter分流量Spilt flow quantity非磁性物含量Non-magnetic material content高梯度磁选High-intensity magnetic separation介质桶Medium tank混料桶Blending tank悬浮液粘度Suspension viscosity其它分选设备Cleaning equipment (miscellaneous)槽选机Trough washer; launder washer摇床Concentrating table; shaking table格条Riffles清洗水Dressing water; cross water上升流分选机Upward current washer斜板分选机Plate cleaner滚筒分选机Barrel washer; drum wahser旋流器cyclone阻沉选煤机Hindered settling cleaner斜槽分选机5)Counterflow steeply inclined separator螺旋分选机spiral离心摇床Centrifugal table水介质旋流器Hydrocyclone; wateronly cyclone; autogenous cyclone化学选煤Chemical coal cleaning选择性絮凝法Selective flocculation method泡沫浮选Forth flotation活化剂Trough washer; launder washer捕收剂Collecting agent; collector 起泡剂Frothing agent; frother润湿剂Wetting agent抑制剂depressant矿浆pulp优先浮选Selective flotation; differential flotation; prefer- entail flotation充气aeration调和conditioning调和槽conditioner给药机Reagent feeder浮选机Flotation cell搅拌桶Agitator主选槽Primary cells粗选槽Rougher cells再选槽Secondary cells精选槽Cleaner cells; recleaner cells扫选槽Scavenger cells浮选精煤Flotation concentrate浮选尾煤Flotation tailings浮选中煤Flotation middlings接触角Contact angle消泡器Froth breaker分段试验Release analysis疏水性矿物6)Hydrophobic mineral亲水性矿物Hydrophilic mineral矿化泡沫Mineralized froth浮选时间Flotation time浮选剂Flotation agent调整剂Modifying agent; regulator分散剂Dispersing agent; dispersant乳化剂emulsifier药剂制度Regime of agent直接浮选Direct flotation浓缩浮选Thickening flotation微泡浮选Hydrophilic mineral粗选roughing扫选scavenging精选cleaning浮选试验Flotation test单元浮选试验Batch-flotation test分步释放浮选试验Timed-release analysis 连续性浮选试验Continuous flotation test 单位充气量Aeration quantity充气均匀系数Aeration uniformitycoefficient机械搅拌式浮选机Subaeration flotation machine; agitation froth machine喷射式浮选机Jet flotation machine充气式浮选机Pneumatic flotation machine 浮选柱Flotation column矿浆准备器Pulp preprocessor一般术语general脱水dewatering干燥drying泄水draining过滤filtration离心脱水centrifuging絮凝flocculation澄清clarification浓缩thickening溢流effluent选煤厂排放水Plant effluent煤泥池Slurry pond分散体dispersion脱水dewatering干燥机dryer固定筛Fixed screen过滤式离心脱水机Basket centrifuge沉降式离心脱水机Solid-bowl centrifuge 沉降过滤式离心脱水机Screen-bowl centrifuge离心液centrate过滤槽Filter bowl; filter tank滤布thickening滤饼Filter cake滤液filtrate压力过滤机Pressure filter压滤机Filter press真空压滤机Vacuum filter埋刮板输送机Dredging conveyor捞坑Dredging sump; drag tank; smudge tank澄清和浓缩Clarification and thickening絮凝剂Flocculating agent; flocculant絮团flocs浓缩漏斗Settling cone; conical settling tank 沉淀池Settling pond耙式浓缩机Rake thickener浓缩旋流器Cyclone thickener给料箱Head box; feed box固气分离Separation of solid from air除尘Dust extraction集尘Dust recovery除尘器Dust collector; dust extractor; deduster旋风除尘器Cyclone dust collector袋式除尘器Bag filter; fabric filter静电除尘器Electrostatic precipitator预先脱水1)Preliminary dewatering最终脱水Final dewatering脱水时间Dewatering time过滤介质Filter media脱落率Percentage of cake discharge助滤剂Filter aid离心强度Centrifugal intensity脱水仓Drainage bin脱水斗式提升机Dewatering basket; dewatering elevator离心脱水机centrifuge惯性卸料离心脱水机Inertial discharge centrifuge刮刀卸料离心脱水机Scraper discharge centrifuge振动卸料离心脱水机Vibrational discharge centrifuge过滤机Filter圆盘式真空过滤机Disc-type filter圆筒式真空过滤机Drum-type filter折带式真空过滤机Feinc vacuum filter; feinc filter水平带式真空过滤机Belt vacuum filter加压过滤机hyperbaric filter箱式压滤机Chamber pressure filter; recessed plate filter press充气式压滤机Hyperbaric pressure filter管式压滤机Tubular pressure filter; tube filter带式压滤机Belt filter press筒式压滤机Drum-type filter press管式干燥机Tubular dryer; flash dryer滚筒式干燥机Drum-type dryer井筒式干燥机Shaft dryer; cascade type dryer沸腾层干燥机fluid-bed dryer;fluidized bed dryer螺旋干燥机Helicoids screw dryer煤粉Coal fines煤泥slime粗煤泥Coarse slime原生煤泥Primary slime次生煤泥Secondary slime浮沉煤泥Slime from float- and-sink analysis; slime from float- and-sink test澄清水Clarified water洗水Wash water底流underflow浓度concentration凝聚剂coagulating agent; coagulant角锥沉淀池Spitzkasten沉淀塔Settling tower带式沉淀塔Dredging tank倾斜板沉淀槽Lamella; inclined plate depositing tank深锥浓缩机Deep cone thickener高效浓缩机High-capacity thickener沉淀仓Settling bunker尾煤场Tailing site水膜除尘器Water-film dedustor泡沫除尘器Froth dedustor一般术语general破碎1)Breaking; cracking破碎2)crashing磨碎Grinding; pulverizing破碎比Reduction ratio解离Liberation(of inter grown constituents) 破碎breakage裂解degradation碎解Disintegration; dissociation可碎性crushability可磨性grindability选择性破碎Selective crushing选择性磨碎Selective grinding破碎流程Crushing circuit 磨碎流程grinding circuit破碎设备Size reduction machines劈碎机Pick breaker滚筒碎选机Rotary breaker; bradford breaker颚式破碎机Jaw crusher辊式破碎机Roll crusher; toothed roll crusher固定锤式破碎机Rigid-hammer crusher摆动锤式破碎机Swing-hammer crusher; swing- hammer mill; swing-hammer pulverizer球磨机Ball mill; rod mill旋转(圆锥)形破碎机Gyratory crusher ; cone crusher准备破碎3)Auxiliary breaking preliminary breaking; auxiliary crushing; preliminary crushing最终破碎Finished breaking; finished crushing; final breaking; final crushing开路破碎Open-circuit crushing闭路破碎closed-circuit crushing一段破碎Single-stage crushing二段破碎Two-stage crushing总破碎比Total reduction ratio超粒oversize过粉碎Over crushing; over breaking破碎机Crusher; breaker单齿辊破碎机Single roll crusher反击破碎机Impact crusher双齿辊破碎机double roll crusher四齿辊破碎机Four roll crusher一般术语general效率efficiency性能描述Statement of performance产率Yield recovery计算入料Calculated feed; reconstituted feed分配曲线Partition curve; distribution curve 分配率Partition coeffici- ents; distribution coefficients分割点Cut-point错配物Misplaced material错配物总量Total misplaced material正配物Correctly placed material正配物总量Total correctly placed material 分级作业Sizing operations规定粒度Designated size分离粒度Separation szie分配粒度Partition size等误粒度Equal errors size控制粒度control size; checking size; testing size参考粒度Reference size额定筛分粒度Nominal screening size (粒度)错配物Misplaced material (sizing) (粒度)正配物Correctly placed material (sizing)有效筛孔Effective screen aperture额定筛孔Nominal screen aperture分级效率Efficiency of sizing; yield of sizing筛分效率Efficiency of screening粒度特性曲线Size distribution curve分选作业Cleaning operations数量效率Organic efficiency理论产率Theoretical yield误差曲线Error curve; tromp error curve分选密度Separation density分配密度partition density; tromp cut-point 等误密度Equal error cut- point (density); wolf cut-point (deprecated)可能偏差Ecart probable moyen; Epm ; E 不完善度Imperfection; I灰分误差Ash error产率损失Yield loss浮物floats沉物sinks邻近密度物Neat-density material(分选)错配物Misplaced material (cleaning)(分选)正配物Correctly placed material (cleaning)回收率1)recovery错配率Miscellany rate处理能力capacity单位处理能力Unit capacity 单位消耗量Specific consumption加工费Preparation cost分级粒度Sizing size理论分级粒度Theoretical sizing size实际分级粒度Separation size; practical sizing size通过粒度Through size限下率Undersize fraction限上率oversize fraction理论灰分Theoretical ash理论分选密度Theoretical separation density等灰密度Equal ash density当量密度Equal yield density实际分选密度Practical separation density 质量效率Quality efficiency污染指标Contamination index浮煤Float coal中间煤Middle coal沉矸Sink refuse含矸率Percentage of refuse content拣矸效率Efficiency of hand picking含煤率Percentage of coal content分选下限Lower limit of separation基元灰分Elementary ash分界灰分Cut-point ash最高产率原则Rule of maximum yield灰分批合格率Ash content qualification ratio灰分批稳定率Ash content stabilization ratio降硫率Percentage of desulfurization脱硫率Percentage of desulfurization脱硫完善指标Perfect index desulfurization 比滤阻Relative filter resistance破碎效率Crushing efficiency粉碎率Degradation rate细粒增量Increment of fines脱水效率Dewatering efficiency浓缩效率Thickening efficiency浮选完善指标Perfect index flotation一般术语general仓配Bunker blending; bin blending给料机feeder不均匀性heterogeneity均质性Homogeneity均质化homogenization混料mixing混料机mixer均匀性uniformity不均匀性Non-uniformity取料机reclaimer堆料机stacker堆料stockpiling料堆stockpile整体流动(在仓内)Mass flow (in bunkers) 管状流动Core flow; funnel flow堆取料机1)Stocker-reclaimer储煤场stockpile配煤仓Blending bunker装车仓Loading bunker; loading bin多点装车Multipoint loading单点装车Single-point loading矸石场Refuse pile定量装车Quantitative loading防尘Dust-proofing防冻Freeze-proofing安息角Angle of repose抑尘Dust suppression配料Blending料仓Bunker; bin漏斗Hopper缓冲仓Surge hopper; surge bunker粘结agglomeration堆密度Bulk density叶片式混料机Paddle mixer防冻剂1)Antifreeze; anti-freezing agent 计量水分Metrological moisture团煤briquetting型煤Coal briquette一般术语general控制系统Control system自动控制Automatic control手动控制Manual control集中控制Central control就地控制Local control 遥控指示Remote indications遥控Remote control过程控制系统Process control system自适应控制系统Adaptive control system 信息管理系统Management information system; MIS监测Monitor(to)数据资料data工序控制sequence control报警alarm故障保护Fail safe控制设备Control equipment传感器sensor监测器detector变换器transducer流量计flow meter控制器controller制动器actuator伺服机构Servo-mechanism放大器amplifier转换器converter灰分监测器Ash monitor堆密度计Bulk density meter水分计Moisture meter密度计Density meter接近开关Proximity switch预启动报警Pre-start warning模拟图Mimic diagram打印机printer打印输出printout光学显示器Visual display unit; VDU状态显示Status display静态显示Static display动态显示dynamic display微型计算机Microcomputer; microprocessor数字计算机Digital computer模拟计算机Analogue computer混合计算机Hybrid computer前端处理器Front end processor程序控制器Programmed controller可编程序控制器Programmable controller 专用控制器Dedicated controller限位开关Limit switch限位转换器Limit transducer锁定系统Lock-out circuit控制术语Control terminology开路控制(系统)Open loop control (system)闭路控制(系统)closed loop control (system)比例控制(系统)ratio control (system) 可控装置Controlled device可控条件Controlled condition预定值Desired value输入信号Input signal指令信号Command signal给定值Set point偏差deviation误差信号Error signal控制信号Control signal控制作用Control action比例作用Proportional action微分作用Derivative action积分作用Integral action反馈feedback稳定性stability衰减damping寻找平衡hunting校定calibration接口interface入机接口Man-machine interface硬件hardware软件software硬连线Hardwire(to)机器语言Machine language程序programme传递pass诊断diagnostic字word存储器memory配置configuration液位计hardware料位计software皮带秤Belt weigher核子秤Nuclear weigh scale在线灰分仪On line coal ash monitor 在线水分仪On line moisture monitor在线煤质分析仪On line coal analyzer 汽车衡Underground weigher轨道衡Frack scale矿物加工工艺常用词汇(一)1选矿-Mineral separation (ore dressing) 2设计-Design3工艺-Technics (craftwork)4初步设计-Initiative(preliminary) design 5流程-Flow(circuit)6流程图-flowchart7施工设计-working design8设计方案-design project9粉碎-comminution10 磨矿-grinding11浮选-flotation12脱水-dehydration13干燥车间-drying shop14尾矿-tailing15精矿-concentrate16中矿-middles17精选-concentration18粗选-first concentration20选矿机-concentrator21矿浆ore pulp22分级-classification22磨矿-grinding23磨矿机-grinding mills24筛分-screen25粉碎-crush26筛分机-screener27粉碎机-crusher28颚式粉碎机-jaw crusher29圆锥粉碎机-cone crusher30冲击式粉碎机impact crusher31辊式粉碎机-crusher rolls32球磨机-ball mill33棒磨机-rod mill34自磨机-autogenous mills35震动筛-vibratory screener36分级机-classification equipment37浮选-flotation38浮选机-flotation equipment39重选-reelect40特殊选-special selection41 浮选柱-flotation ploe42脱水机-spin-drier43干燥机-drier44总图-general chart45配置-deploy46运输-transport47环境保护-environment protect 48场址-field location(site)49布置-lay50设计资料-design information 51粉碎流程-comminution flow 52磨矿流程-grinding flow(circuit) 53浮选流程-flotation flow54金属矿-metallic mines55非金属矿-non-metallic mines 56闭路-close circuit(loop)57闭路流程-close flow58开路-cut circuit(loop)59开路流程-cut flow60废水-liquid waste61粉尘-powder62噪声-yawp63污染-contamination64沉淀-form sediment65净化-decontaminate66输送-transportation67矿石-ore68物料-material69给矿-feed ores70给料-feed stuff71设备-equipment72方案-project73标高-elevation74通道-passage75维修-maintain76检查-check77操作-operation78化验-test、assay79检测-examine80坡度-gradient81起重机-crane 82堆积-accumulation83细粒-granule、fine84粗粒-coarse85尾矿坝-tailing dam86矿仓-feed bin(storehouse)87粉矿仓-crushing pocket88产品仓-product bin(storehouse) 89砂泵-pump90立式泵-stand pump91卧式泵-horizontal pump92耐酸泵-acid-proof pump93耐碱泵-alkali-resistant pump94勘察-reconnaissance95地形-landform96工程-engineering97设计步骤design process98规模-scale99选矿厂-concentrating mill100设计内容design content(二)1 comminution-粉碎2 comminution engineering-粉碎工程3粉碎机-comminuter4粉碎动力学-comminution kinetics 5筛分曲线图-screen analysis chart 6筛孔-screen aperture7筛面-screen area8筛条screen bar9筛框-screen box10筛选厂-screen building11筛分机生产能力screen capacity 12筛分槽-screen cell13筛布-screen cloth14筛分screen classification15筛孔-screen hole16筛分车间-screenhouse17筛分分析-screen analysis18滚筒筛-screening-drum19筛分效率-screening efficiency20筛分速率-screening rate21筛网-screen mesh22筛制、筛比、筛序-screen scale 23筛孔尺寸-screen size24套筛-screen set25筛序-screen size gradation26筛余物screen tailings27筛下产品-screen throughs (underflow undersize)28可碎性crushability29可碎性系数-crushability factor30碎矿仓-crushed ore pocket31粉碎产品-crushed product32粉碎粒度-crusher size33粉碎腔-crushing cavity34粉碎厂-crushing plant35粉碎系数-crushing coefficient36粉碎工段-crushiong section37助磨剂-grinding aid38磨球-grinding ball39 磨矿负荷-grinding charge40磨矿效率-grinding efficiency41磨矿-grinding ore42磨砾-grinding pebble43磨碎能力-grinding property44研磨试验grinding test45磨矿设备-grinding unit46磨矿速度-grinding rate47磨矿功率-grinding power48磨矿车间-grinding plant49可磨性-grindability50可磨性指数-grindability index51可磨性指标-grindability rating52可磨性试验-grindability test53研磨工-grinder54磨工车间-grindery55磨矿动力学-grinding kinetics56粉碎能-crushing energy57粉碎机给矿口-crushing mouth58粉碎面-crushing face59粉碎力-crushing force60粉碎机进料口-crusher throat61筛分动力学-screen kinetics62选厂矿仓-mill bin63 选厂中矿mill chats64选厂配置mill configuration65磨过的矿石-milled ore66磨机给料-mill feeder67选厂给矿-mill-head 68研磨作用-milling action69磨机衬里mill liner70入选品位milling grade71入选品位矿石milling-grade ore 72磨矿机milling-grinder73细碎、精磨-milling grinding74磨矿介质-milling medium75磨矿法-milling method76选矿作业-milling operation77选矿厂-milling plant78选厂矿泥-milling slime79选厂厂址-mill site80磨机负荷-mill load81选矿工(工长)millan82磨机需用功率-mill power draft 83选矿质量控制mill puality control 84选矿取样-mill sampling85磨机外壳-mill shell86磨机矿浆-mill slurries87磨石-millstone88选矿厂储矿仓mill-storage89选厂尾矿-mill tail90选矿用水-mill water91磨矿机溶液-mill solution92选矿厂建筑师-millwright93分级沉淀-class setting94矿粉-mineral fine95分级-classification96分级溢流-classifier overflow97分级返砂-classifier sand98分级机-classifier99分级筛-classifying screen100分级箱-classifying box(三)1品位-grade2精矿品位-concentrate grade3尾矿品位-tailing grade4尾矿场-tail area(pile)5尾矿仓-tailing bin6尾矿滤饼-tailing cake7尾矿坝-tailing dam8尾矿池-tailing pond(pit)9取样-taking cut(sampling)10滑石talc11蓝晶石-talc blue12 试样缩分-sample division13 分样器-sample divider14精矿取样-concentrate sampling15中矿取样-middles sampling16尾矿取样-tailing sampling17浓缩-thickening18精矿浓缩-concentrate thickening19选矿流程-concentrating circuit20精选机-concentrating mcching21试样缩分-sample reduction (splitting) 22矿物组成-mineralcomposition23矿物组分-mineral constituent24矿床-mineral depost25矿物-mineral26选矿方法mineral dressing method27选矿厂-concentrating mill28选矿ore dressing,mineral separation29矿物分析-mineral analysis30矿物组合-mineral association31 试样袋-sample sack32矿床-deposit33矿物岩相facies34矿物纤维-mineral fiber35固、气界面-mineral-air interface36固、液界面-mineral-water interface37固、气、液接触mineral-air-water contact 38矿物颗粒-grain39矿物鉴定-mineral identification40矿物资源-interest41矿物解离-mineralliberation42矿物特性mineral character43矿物储量-mineral reserve44矿物(成分)检验mineral logical examination45扑收剂-Minerec,flotigan,46精矿回收率concentrate recovery47中矿回收率middles recovery48精选concentration49附着精矿气泡concentratr-loaded bubble 50精选机-concentrating maching51分选判据-concentration criterion52富集比-concentration factor53选矿摇床-concentration table 54选厂流程concentrator flow5选厂流程图concentrator flow sheet56试样品位-sample grade57絮凝剂-flocculant58絮凝-floculate59絮凝物-flocs60絮凝浮选floc flotation61絮凝作用flocculation62浮选机flotation unit63浮选剂- flotation agent64整排浮选机flotation bank65浮选槽- flotation cell66浮选能力flotation capacity67浮选精矿- flotation concentrate68浮选尾矿flotation rejects69浮选中矿- flotation middles70浮选设备flotation equipment71浮选泡沫-flotation froth72浮选动力学flotation kinetics73浮选浸出法- flotation leaching method 74浮选厂flotation mill75浮选油-flotation oil76浮选矿浆- flotation pulp77浮选速度-flotation rate78浮选试验flotation test79单槽浮选机- flotation unit cell80浮选摇床- flotation table81摇床浮选- flotation tabling82起泡剂Flotol83流程图-flow line84工艺流程图-flow process chart (flow sheet)85可选(洗)性-washability86可选性特性- washability characteristic 87可选性曲线- washability curve88可选性指数- washability number89可选性试验- washability test90可浮性-flotability91可浮性曲线-flotability curve92粒度特性-granularity93粒度分级试验grading test94结构-texture95构造-tectonic(structural)96致密结构-compact texture97斑状结构porphyritic texture98 粒度分析-granularmetric analysis99采样-sample collecting100分样器-sample divider采矿mining地下采矿underground mining露天采矿open cut mining, open pit mining, surface mining采矿工程mining engineering选矿(学)mineral dressing, ore beneficiation, mineral processing矿物工程mineral engineering矿物资源综合利用engineering of comprehensive utilization of mineral resources中国金属学会The Chinese Society for Metals中国有色金属学会The Nonferrous Metals Society of China采矿工艺mining technology有用矿物valuable mineral冶金矿产原料metallurgical mineral raw materials矿床mineral deposit特殊采矿specialized mining海洋采矿oceanic mining, marine mining 矿田mine field矿山mine露天矿山surface mine地下矿山underground mine矿井shaft矿床勘探mineral deposit exploration矿山可行性研究mine feasibility study矿山规模mine capacity矿山生产能力mine production capacity矿山年产量annual mine output矿山服务年限mine life矿山基本建设mine construction矿山建设期限mine construction period矿山达产arrival at mine full capacity开采强度mining intensity矿石回收率ore recovery ratio 矿石损失率ore loss ratio工业矿石industrial ore采出矿石extracted ore矿体ore body矿脉vein海洋矿产资源oceanic mineral resources 矿石ore矿石品位ore grade岩石力学rock mechanics岩体力学rock mass mechanics选矿厂concentrator, mineral processing plant工艺矿物学process mineralogy开路open circuit闭路closed circuit流程flowsheet方框流程block flowsheet产率yield回收率recovery矿物mineral粒度particle size粗颗粒coarse particle细颗粒fine particle超微颗粒ultrafine particle粗粒级coarse fraction细粒级fine fraction网目mesh原矿run of mine, crude精矿concentrate粗精矿rough concentrate混合精矿bulk concentrate最终精矿final concentrate尾矿tailings粉碎comminution破碎crushing磨碎grinding团聚agglomeration筛分screening, sieving分级classification富集concentration分选separation手选hand sorting重选gravity separation, gravity concentration。
刘新杰,宋高峰,蒋斌斌.煤炭行业发展历程及展望[J ].矿业安全与环保,2019,46(3):100-103.文章编号:1008-4495(2019)03-0100-04煤炭行业发展历程及展望刘新杰1,宋高峰2,蒋斌斌1(1.煤炭开采水资源保护与利用国家重点实验室,北京102209;2.北方工业大学土木工程学院,北京100144)摘要:中国煤炭产量处于不断优化调整期,煤炭价格日趋平稳,煤炭开采逐步进入绿色㊁安全㊁高效和有序状态,煤炭利用步入清洁㊁低碳的发展轨道㊂通过分析近10年中国能源生产结构㊁电煤价格指数㊁采矿行业工资及科研方向,表明煤炭所占国家能源比重将会进一步降低,但仍是主要能源,能源结构将呈现煤㊁油㊁天然气㊁无碳能源(水电㊁风电㊁核电等)四足鼎立的格局㊂煤炭开发过程更加注重绿色开采和社会责任,煤炭行业待遇偏低,理应尽快建立竞争有序的煤炭市场体系,促使煤炭行业成为人才向往的行业㊂关键词:煤炭;绿色开采;低碳;电煤价格指数;能源生产结构中图分类号:TD82 文献标志码:C收稿日期:2018-10-24;2019-05-27修订基金项目:国家重点研发计划项目(2016YFC0501100-09)作者简介:刘新杰(1986 ),男,山东菏泽人,博士,工程师,主要从事煤矿开采生态减损方面的研究工作㊂E-mail :liuxinjie@ ㊂The Development Course and Prospect of Coal IndustryLIU Xinjie 1,SONG Gaofeng 2,JIANG Binbin 1(1.State Key Laboratory of Water Resource Protection and Utilization in Coal Mining ,Beijing 102209,China ;2.School of Civil Engineering ,North China University of Technology ,Beijing 100144,China )Abstract :The Chinese coal production is in a period of continuous optimization and adjustment,the coal price becomesmore and more stable,coal mining has gradually entered a green,safe,efficient and orderly state,and coal utilization is also turning to a clean and low-carbon direction.Through the analysis of domestic energy production structure,thermal coal price index,mining industry wages and scientific research direction in recent 10years,it is shown that the proportion of coal innational energy will be further reduced,but it will still be the main energy,while the oil,natural gas and other carbon-free energies including hydroelectric,wind power,nuclear power become equally important.The coal development process pays more attention to green mining and social responsibility,and the coal industry has low treatment.Therefore,it is reasonable to establish a competitive and orderly coal market as soon as possible,so as to make the coal industry become an industry desiredby talents.Keywords :coal;green mining;low-carbon;thermal coal price index;energy production structure 当今世界主要产煤国可分为3种类型:一是以印度为代表的产量快速增长型;二是以中国为代表的产量优化调整型;三是以美国为代表的产量有序型㊂中国煤炭行业经过多年来的自我改革和优化,产业结构和开发布局不断提升,煤炭开采由产量向质量转变,优势产能比重提高,开采理念从安全高效逐渐过渡到绿色㊁安全㊁高效㊁生态和智能㊂煤炭长期作为我国的主体能源,在保障国家能源安全的同时,深部岩体探测㊁开采装备研发(首台矿用全断面硬岩快速掘进机㊁首套煤矿大型护盾式快速掘锚装备研制成功,上湾煤矿8.8m 大采高综采设备投产),以及开采后采煤塌陷区整治,土地功能构建,湿地㊁生态建设等技术迅猛发展,开始引领世界煤炭行业的发展㊂1 中国能源生产结构现状‘2018年能源工作指导意见“[1]指出全国能源消费总量控制在45.5亿t 标准煤左右㊂非化石能源消费比重提高到14.3%左右,天然气消费比重提高到7.5%左右,煤炭消费比重下降到59.0%左右㊂㊃001㊃全国能源生产总量36.6亿t标准煤左右㊂煤炭产量为37.0亿t左右,原油产量为1.9亿t左右,天然气产量为1600亿m3左右,非化石能源发电装机达到7.4亿kW左右㊁发电量达到2万亿kW㊃h左右㊂2007 2016年中国能源生产结构如图1所示[2]㊂图1 2007 2016年中国能源生产结构组成(来源:中华人民共和国国家统计局)由图1可知,2007 2015年煤炭资源一直占据我国能源比重的70%以上,2016年煤炭比重首次降低至69%㊂未来随着清洁能源的发展,煤炭比重仍会持续下降,预计到2050年煤炭比重会降至50%,最终稳定在45%~50%,依然是中国的主要能源㊂全球石油已迈入稳定期[3],中国原油产量近10a间变化不明显,原油比重一直稳定在8%~ 10%,约为煤炭比重的1/8,未来或许有上升趋势,但短时间内难以实现㊂天然气2007 2016年间产量迅速增加,平均以5.0%的速率递增,天然气比重由2007年的3.5%上升至2016年的5.3%㊂国家发展和改革委员会等十三部门印发了‘加快推进天然气利用的意见“[4],明确提出逐步将天然气培育成为我国现代清洁能源体系的主体能源的目标㊂到2020年,天然气在我国一次能源消费结构中的占比力争达到10%左右,到2030年,力争将天然气在一次能源消费结构中的占比提高到15%左右㊂但天然气介于化石能源和可再生能源之间,发展正步入鼎盛期,属于化石能源向低碳新能源过渡的能源,预计天然气比重稳定在15%~20%㊂水电㊁核电㊁风电㊁太阳能㊁氢能㊁生物质发电等无碳能源[5]正处于发展黄金期,是未来主要发展的绿色能源产业㊂水电㊁核电和风电平均每年以8%的速率递增,2016年能源占比已超过16%,成为中国第二大能源㊂随着水电开发利用的统筹优化,核电发展的稳妥推进,稳步发展风电和太阳能发电措施的落实,无碳能源的开发利用比重将越来越大㊂随着人类对绿色生态环境需求的提升和低碳社会的到来,国家对生态环境㊁气候变化及未来能源消费方式的要求越来越高,煤炭绿色㊁安全㊁高效㊁清洁㊁低碳开发利用已成为共识,相对富煤㊁贫油㊁少气的国情决定了我国未来30a煤炭所占能源结构比重不断降低,但煤炭仍是中国最经济㊁可靠且不可替代的主要能源,未来会形成煤㊁油㊁天然气㊁无碳能源(水电㊁风电㊁核电等)四足鼎立的格局㊂2摇中国电煤价格指数电煤价格指数是中国煤炭行业发展行情的风向标,煤炭价格与供需关系有着明显的关联㊂中国主要产煤省(自治区)有山西㊁陕西㊁贵州㊁山东㊁河南㊁安徽㊁宁夏㊁河北㊁内蒙古㊁新疆㊂亿吨级的省(自治区)有8个,按产量排名依次为内蒙古㊁山西㊁陕西㊁新疆㊁贵州㊁山东㊁河南㊁安徽㊂截至2018年12月底,安全生产许可证等证照齐全的生产煤矿有3373个,产能为35.3亿t/a;已核准(审批)㊁开工建设的煤矿有1010个(含同步改建㊁改造项目的生产煤矿有64个),产能为10.3亿t/a,其中已建成㊁进入联合试运转的煤矿有203个,产能为3.7亿t/a[6]㊂8个亿吨级省(自治区)原煤产量为30.00亿t,占全国煤炭产量(34.88亿t)的86%,其中晋陕蒙3省区煤炭产量为23.00亿t,占全国产量的66%㊂8个主要产煤省区电煤价格及全国煤炭月产量和电煤均价如图2所示[7]㊂图2 2014 2018年中国电煤价格指数(来源:中华人民共和国国家发展和改革委员会价格监测中心)由图2可知,中国电煤价格在2014 2018年间经历了大起大落,2015 2016年煤炭价格跌至谷底,特别是2015年5月,全国电煤均价为315元/t,安徽省的价格最高为376元/t,生产成本远大于销售价格,造成全国大量煤矿企业亏损负债㊂随后国家实㊃101㊃施煤炭产能减量置换政策,调整供需关系,煤炭产量控制在37.00亿t左右,2014㊁2015和2016年3a煤炭总产量为104.30亿t,平均年产量为34.80亿t,全国煤炭月产量维持在2.10亿~3.25亿t,平均月产量为2.90亿t,实现煤炭供需动态平衡㊂随后在2016年12月(全国电煤均价为535元/t)和2018年2月(全国电煤均价为567元/t)分别达到电煤价格局部峰值,2018年全国电煤均价维持在520~ 570元/t,逐步走向动态平衡㊂2018年全国煤炭产量已完成36.50亿t,全年电煤均价约为531元/t㊂中国煤炭资源分布和消费差异性极大,山东㊁安徽和河南3省电煤价格处于高位,长期高于全国电煤均价,贵州和陕西省基本和全国电煤均价持平,而新疆㊁内蒙古自治区和山西省长期低于全国电煤均价㊂2014 2018年主要产煤省(区)平均煤价与全国电煤均价比值排序依次为山东省(1.188)>安徽省(1.186)>河南省(1.084)>贵州省(0.995)>陕西省(0.893)>山西省(0.691)>内蒙古自治区(0.550)>新疆自治区(0.434)㊂显然山东煤价最高㊁新疆煤价最低,因此推动煤炭生产向大型煤炭基地集中,积极发展先进产能,向陕北㊁神东㊁黄陇㊁新疆等价格具备竞争优势的大型煤炭基地转移是未来的发展趋势㊂3 采矿行业工资现状2007年全国煤炭产量为26.90亿t,采矿行业(含金属矿和非金属矿)国有企业就业人员有232.8万人,年平均工资为29177元;2016年煤炭产量为34.10亿t,采矿行业国有企业就业人员有44.6万人,年平均工资为61638元㊂2007 2016年间煤炭产量增长了27%,采矿业国有企业人员减少了80%,工资增长了111%㊂相较于制造㊁电力㊁建筑㊁交通㊁金融和房地产行业,采矿行业工资增速是最低的㊂国有企业就业人员平均工资变化如图3所示㊂图3 2007 2016年国有企业就业人员平均工资统计(来源:中华人民共和国国家统计局)由图3对比可知,行业平均工资逐年递增的有制造㊁电力㊁建筑交通和金融行业㊂房地产行业受楼市调控政策影响,2012年平均工资出现略微下降,采矿行业因煤炭市场供大于求的原因分别在2014和2015年平均工资出现下降调整㊂2007 2016年间行业平均工资按增速水平排名依次是制造行业(200%)>交通行业(175%)>电力行业(152%)>建筑行业(151%)>房地产行业(150%)>金融行业(135%)>采矿行业(111%)㊂可见采矿行业平均工资增速最低,平均工资水平由第3位(2007年)降低到第6位(2016年),仅高于建筑行业㊂采矿工程作为一级学科矿业工程下属的二级学科,属于工学照顾专业㊂因井下工作条件恶劣的特殊性,从事该领域的员工主要为男性,工作环境培养了采矿人特别能吃苦㊁特别能战斗的特性㊂煤炭工作者为国家提供了充足的 工业粮食”,煤炭产量㊁技术和装备有了极大的提升,相对应的工资待遇水平并未得到有效改善㊂煤炭行业理应提升行业待遇,并朝向绿色㊁低碳㊁清洁㊁有序的方向发展,使之成为人才向往的高新技术行业[8]㊂4 煤炭行业科研发展方向中国煤炭开采已由追求产量增长向绿色开采㊁低碳利用转变,煤炭产量在2013年达到峰值后开始稳定,煤炭开采技术研究也由单纯采矿向生态㊁深地㊁深海攻关[9-12]㊂根据已批复的 十三五”国家重点研发计划可知,煤炭行业分别在典型脆弱生态修复与保护㊁深地资源勘查开采㊁深海关键技术与装备㊁公共安全风险防控等领域承担众多重要的研究任务㊂中国煤炭行业发展方向路线如图4所示㊂图4 中国煤炭行业发展方向路线图2016年国家能源集团(原神华集团有限责任公司)牵头承担的 东部草原区大型煤电基地生态修复与综合整治技术及示范”项目,更加注重煤矿开采生态,通过本底调查和动态监测㊁理论与试验研究,揭示东部草原区煤电开发生态退化的影响机理和累积效应,研究土地整治㊁植被恢复㊁土壤重构和景观的生态恢复等关键技术,提出生态修复与综合整治的技术体系;在东部草原区大型煤电基地的胜利㊁宝日㊃201㊃希勒和大雁矿区开展技术集成与工程示范,形成东部草原区大型煤电基地生态修复与综合整治的技术体系和调控模式[13]㊂2016年四川大学在深地资源勘查开采领域牵头承担的 深部岩体力学与开采理论”项目,针对浅部岩石力学理论没有考虑深部真实应力环境和工程扰动状态的现状,深入研究深部岩体原位力学状态和地应力环境及工程扰动效应㊂实施深部原位条件下微观到宏观,二维到三维的理论建模 实验研究 现场监测结合的研究方案,建立深部岩体力学和深部资源开采的新理论㊁新方法㊁新技术,全面提升我国深部资源的获取能力[14]㊂2017年天地科技股份有限公司牵头承担的 煤矿千米深井围岩控制及智能开采技术”项目,开展千米深井强采动巷道围岩大变形与破坏机理㊁350m 以上工作面覆岩结构演化及智能开采模式㊁巷道锚杆支护 卸压协同控制技术㊁巷道围岩改性关键材料与技术㊁超长工作面围岩自适应智能控制开采技术的研究,同时进行千米深井围岩控制及智能开采技术的工程示范[15]㊂2017年大连理工大学在深海关键技术与装备领域牵头的 南海多类型天然气水合物成藏原理与开采基础研究”项目,拟研究南海多类型天然气水合物成藏 源 汇”地质过程与富集的规律;研究天然气水合物开采过程气㊁水产出的机制;研究天然气水合物开采过程沉积层骨架结构变化规律等多项关键科学与技术问题,将建立我国南海多类型天然气水合物成藏地质演化与富集等相关理论,提出南海多类型天然气水合物成藏预测方法,突破水合物高效安全开采的技术瓶颈,为南海天然气水合物试采与工程实施奠定坚实基础[16]㊂2018年8月29日,由天地科技股份有限公司在深地资源勘查开采领域牵头承担的国家重点研发计划项目 千万吨级特厚煤层智能化综放开采关键技术及示范(2018YFC0604500)项目”,以千万吨级特厚煤层智能化综放开采为核心,以 智能群组放煤机理 智能放煤方法 煤矸精准识别技术 智能放煤控制技术及装备―工程示范”为主线,开发千万吨级特厚煤层智能化综放开采关键技术及装备,并进行工程示范,最终实现煤炭智能化综放开采,为我国特厚煤层的安全㊁高效开采提供技术支撑㊂2016年中国矿业大学(北京)在公共安全风险防控与应急技术装备领域牵头的 煤矿典型动力灾害风险判识及监控预警技术研究”和 煤矿重特大事故应急处置与救援技术研究”项目,以及2017年中国矿业大学在国家质量基础的共性技术研究与应用领域牵头的 矿山新型甲烷通风防尘安全仪器计量技术研究” 严酷条件下矿用设备性能检测及质量评价技术研究项目”和煤炭科学技术研究院有限公司牵头的 煤的热稳定性等4项指标测定方法国际标准研究”项目,标志着煤炭行业正在承担着越来越多的社会责任[17]㊂5摇结论1)中国煤炭产量由优化调整进入产量有序,煤炭在未来30a仍是主要能源,能源结构将呈现煤㊁石油㊁天然气㊁无碳能源(水电㊁风电㊁核电等)四足鼎立的能源格局㊂2)煤炭开采更加安全㊁高效㊁绿色㊁智能,煤炭利用向更加清洁㊁低碳发展,煤炭开采正在形成煤㊁瓦斯㊁水㊁热等能源协同开发模式㊂3)中国煤炭行业目前待遇偏低,赋予的社会责任较高,承担着越来越多的国家重点研发任务,在技术和装备领域已逐步引领世界,成为煤炭行业的研发中心㊂参考文献:[1]国家能源局.2018年能源工作指导意见[EB/OL].(2018-03-09)[2018-06-14]./ xinwen/2018-03/09/content_5272569.htm.[2]中华人民共和国国家统计局.国家数据[EB/OL].(2018-03-12)[2018-05-14]./ easyquery.htm?cn=C01.[3]邹才能.新能源[M].北京:石油工业出版社,2019.[4]中华人民共和国国家发展和改革委员会.关于印发‘加快推进天然气利用的意见“的通知[EB/OL].(2017-07-04)[2018-06-14]./xinwen/2017-07/04/content_5207958.htm.[5]王韶华.基于低碳经济的我国能源结构优化研究[D].哈尔滨:哈尔滨工程大学,2013.[6]国家能源局公告2019年第2号[EB/OL].(2019-03-26)[2019-04-15]./auto85/ 201903/t20190326_3637.htm.[7]中华人民共和国国家发展和改革委员会价格监测中心.中国电煤价格指数[EB/OL].(2018-06-12)[2018-06-14]./zgdmjgzs.aspx?clmId= syjgzs6.[8]谢和平,王金华,王国法,等.煤炭革命新理念与煤炭科技发展构想[J].煤炭学报,2018,43(5):1187-1197. [9]姚成林,熊云威,宋春香.煤层气地面开发及利用趋势探讨[J].矿业安全与环保,2017,44(6):79-82.(下转第112页)㊃301㊃系初探[J ].职业卫生与应急救援,2012,30(3):127-130.[3]李戬,陈建武,孙庆云,等.职业危害监管信息系统(政府版)的设计与开发[J ].中国安全生产科学技术,2010,6(1):40-43.[4]柳静献,常德强,林秀丽,等.作业场所职业危害监管信息管理系统开发[J ].中国安全科学学报,2008,3(3):118-122.[5]杭一平,熊敏如,陈小春.职业病防治法律法规与控制职业病危害效果的影响因素[J ].实用预防医学,2005,12(2):371-376.[6]王海青,白杰,刘继倩,等.农民工职业危害防护需求意愿调查分析[J ].中国安全生产科学技术,2011,7(9):130-134.[7]盖梅,童玲,李济超,等.武汉市不同行业职业病危害与职业卫生服务现状分析[J ].公共卫生与预防医学,2012,23(3):39-43.[8]李强,蒋承林,翟果红.我国煤炭行业尘肺病现状分析及防治对策[J ].中国安全生产科学技术,2011,7(4):148-151.[9]曲婵.HACCP 在火力发电厂职业病危害控制效果评价中的应用[D ].长春:吉林大学,2012.[10]熊立新,罗周全,吴超,等.深井受限空间职业危害程度辨析方法[J ].金属矿山,2014(11):132-137.[11]赵同辉,赵蕊,蒋莉.电焊条生产行业职业危害监测评价模型研究[J ].林业劳动安全,2015,28(1):37-41.[12]张忠彬,陈刚,张圆媛.我国职业病危害防治现状㊁问题与对策探讨[J ].中国安全生产科学技术,2014,10(增刊1):51-54.[13]GUNNAR F.NORDBERG ,KATARINA VICTORIAN.Mixed exposures :assessment and evaluation of some carcinogenic and non -carcinogenic effects [J ].Methods for Assessing the Effects of Mixtures of Chemicals ,1987(6):590-610.[14]何川,刘功智,任智刚,等.职业危害因素混合接触综合评价方法概述[J ].中国安全生产科学技术,2009,5(5):176-180.[15]梁秀波.基于 主体 对象 客体”关系模型的公安学基础理论体系构建研究[J ].武警学院学报,2014,30(7):49-52.[16]田水承,薛明月,李广利,等.基于因子分析法的矿工不安全行为影响因素权重确定[J ].矿业安全与环保,2013,40(5):113-116.[17]田彦清,杨振宏,李华,等.作业场所风险影响因素分析及评估模型研究[J ].安全与环境学报,2011,11(5):222-226.[18]周琳,栗继祖.关于煤矿安全评价中危险源辨识的研究[J ].矿业安全与环保,2014,41(5):116-119.[19]谢乃明.灰色系统建模技术研究[D ].南京:南京航空航天大学,2008.(责任编辑:逄锦伦 )(上接第103页)[10]姚韦靖,庞建勇.我国深部矿井热环境研究现状与进展[J ].矿业安全与环保,2018,45(1):107-111.[11]康红普,王国法,姜鹏飞,等.煤矿千米深井围岩控制及智能开采技术构想[J ].煤炭学报,2018,43(7):1789-1800.[12]徐亮.新时期煤炭建设行业转型发展战略研究[J ].煤炭工程,2018,50(6):1-3.[13]李全生.东部草原区煤电基地开发生态修复技术研究[J ].生态学报,2016,36(22):7049-7053.[14]谢和平. 深部岩体力学与开采理论”研究构想与预期成果展望[J ].工程科学与技术,2017,49(2):1-16.[15]王中伟,杨建威.千米深井项目启动[EB /OL ].(2017-10-30)[2018-06-14].http :// /content /c45184.html.[16]大连理工大学.面向未来能源:南海多类型天然气水合物成藏原理与开采基础研究[EB /OL ].(2017-08-16)[2018-06-14].http :// /info /4528/15544.html.[17]中国21世纪议程管理中心.国家重点研发计划 国家质量基础的共性技术研究与应用”[EB /OL ].(2018-03-12)[2018-16-14].http :// /.(责任编辑:逄锦伦)㊃211㊃。
1、检索课题名称:.煤矿绿色开采技术的基础理论与应用2、课题分析:“绿色开采技术”是属于本课题中的主体,其应用目标是“煤炭”的开采,涉及到绿色开采的“基本理论”及其“应用”,由此得出如下检索词(按其对课题影响程度排序):中文关键词:1绿色开采 2煤炭 3基本原理 4应用英文关键词:(1)Green mining(2)Coal(3)The basic principle(4)Application3、选择检索工具:Elsevier 数据库4、构建检索策略:Coal green mining AND The basic principle and Application5、简述检索过程:选定在 Elsevier 中期刊、图书、文摘数据库等全部文献资源中检索 1996 年以后的关于煤矿绿色开采技术的基础理论与应用的相关文献。
利用确定的检索策略(Coal green mining AND The basic principle and Application),文献全文(含文献题目、摘要、关键词)中检索,检到 2530 篇相关文献;在文献题目、摘要和关键词中检索,检索到 1010 篇相关文献;在文献关键词中检索到 95 篇相关文献;在文献题目中检索到 142 篇相关文献。
6、整理检索结果:从以上文献中选择出3 条切题文献1. Study on incentive mechanisms of coal green miningLu Ming-yin a, b, Zhang Zhen-fang a, Meng Xing a, Li Dai aa School of Mines, China University of Mining & Technology, Xuzhou 221116, Chinab State Key Laboratory of Coal Resources and Safe Mining, Xuzhou 221116, ChinaAvailable online 12 October 2009.AbstractThrough summing up the research situation of green mining incentive mechanism home and abroad, the obstacles which cumber the implementation of green mining from market, organization and technology in our country are analyzed. The result of the analytical model, which analyzes market obstacles, indicates that the profit margin of traditional mining is higher than that of greenmining which results in the shortage of the gr een mining. Finally, the green mining incentive mechanism is constructed from three aspects including market incentive, governmental incentive and technical incentive. Specially, the governmental incentive is analyzed by game theory.Keywords: green mining; incentive mechanism; analytical model; game theory2、Waste-filling in fully-mechanized coal mining and its applicationXie-xing MIAO a, b, Ji-xiong ZHANG a, c, Mei-mei FENG a, b,a State Key Laboratory for Geomechanics & Deep Underground Engineering, China University of Mining& Technology, Xuzhou, Jiangsu 221008, Chinab School of Sciences, China University of Mining & Technology, Xuzhou, Jiangsu 221008, Chinac School of Mines, China University of Mining & Technology, Xuzhou, Jiangsu 221008, China Received 25 April 2008; Accepted 10 July 2008. Available online 21 December 2008.AbstractA fully-mechanized coal mining (FMCM) technology capable of filling up the goaf with wastes (including solid wastes) is described. Industrial tests have proved that by using this technology not only can waste be re-used but also coal resources can be exploited with a higher recovery rate without removing buildings located over the working faces. Two special devices, a hydraulic support and a scraper conveyor, run side-by-side on the same working face to simultaneously realize mining and filling. These are described in detail. The tests allow analysis of rock pressure and ground subsidence when backfilling techniques are employed. These values are compared to those from mining without using backfilling techniques, under the same geological conditions. The concept of equivalentmining height is proposed based on theoretical analysis of rock pressure and ground subsidence. The upper limits of the rock pressure and ground subsidence can be estimated in backfilling mining using this concept along with traditional engineering formulae.Key words: fully-mechanized coal mining; coal mining with gangue backfilling; mining under buildings; railways and water bodies; rock pressure around coal face; control of ground subsidence3、Waste-filling in fully-mechanized coal mining and its applicationXie-xing MIAO a, b, Ji-xiong ZHANG a, c, Mei-mei FENG a, b,a State Key Laboratory for Geomechanics & Deep Underground Engineering, China University of Mining& Technology, Xuzhou, Jiangsu 221008, Chinab School of Sciences, China University of Mining & Technology, Xuzhou, Jiangsu 221008, Chinac School of Mines, China University of Mining & Technology, Xuzhou, Jiangsu 221008, China Received 25 April 2008; Accepted 10 July 2008. Available online 21 December 2008.AbstractA fully-mechanized coal mining (FMCM) technology capable of filling up the goaf with wastes (including solid wastes) is described. Industrial tests have proved that by using this technology not only can waste be re-used but also coal resources can be exploited with a higher recovery rate without removing buildings located over the working faces. Two special devices, a hydraulic support and a scraper conveyor, run side-by-side on the same working face to simultaneously realize mining and filling. These are described in detail. The tests allow analysis of rock pressure and ground subsidence when backfilling techniques are employed. These values are compared to those from mining without using backfilling techniques, under the same geological conditions. The concept of equivalentmining height is proposed based on theoretical analysis of rock pressure and ground subsidence. Theupper limits of the rock pressure and ground subsidence can be estimated in backfilling mining using this concept along with traditional engineering formulae.Key words: fully-mechanized coal mining; coal mining with gangue backfilling; mining under buildings; railways and water bodies; rock pressure around coal face; control of ground subsidenceReferences1 MG Qian, JL Xu and XX Miao, Green technique in coal mining, . Journal of China University of Mining & Technology, 32 4 (2003), pp. 343–348 (In Chinese)..2 MG Qian and TC Liu, Ground Pressure and Its Control, China University of Mining and Technology Press, Xuzhou (1991), (In Chinese)..3 GQ He, L Yang and GD Ling et al., Mining Subsidence, China University of Mining and Technology Press, Xuzhou (1991), (In Chinese)..4 XX Miao, XB Mao and GW Hu, et al. Research on broken expand and press solid characteristics of rocks and coals, . Journal of Experimental Mechanics, 12 3 (1997), pp. 394–399 (In Chinese)6、全文摘录选择一篇:1. Waste-filling in fully-mechanized coal mining and its application一、篇名Waste-filling in fully-mechanized coal mining and its application二、著者A. Xie-xing MIAO a, b, Ji-xiong ZHANG a, c, Mei-mei FENG a, b,三、著者机构:A、State Key Laboratory for Geomechanics & Deep Underground Engineering, China University of Mining& Technology, Xuzhou, Jiangsu 221008, ChinaB、School of Sciences, China University of Mining & Technology, Xuzhou, Jiangsu 221008, ChinaC、School of Mines, China University of Mining & Technology, Xuzhou, Jiangsu 221008, China四、文摘AbstractA fully-mechanized coal mining (FMCM) technology capable of filling up the goaf with wastes (including solid wastes) is described. Industrial tests have proved that by using this technology not only can waste be re-used but also coal resources can be exploited with a higher recovery rate without removing buildings located over the working faces. Two special devices, a hydraulic support and a scraper conveyor, run side-by-side on the same working face to simultaneously realize mining and filling. These are described in detail. The tests allow analysis of rock pressure and ground subsidence when backfilling techniques are employed. These values are compared to those from mining without using backfilling techniques, under the same geological conditions. The concept of equivalentmining height is proposed based on theoretical analysis of rock pressure and ground subsidence. The upper limits of the rock pressure and ground subsidence can be estimated in backfilling mining using this concept along with traditional engineering formulae.五、关键词Keywords: fully-mechanized coal mining; coal mining with gangue backfilling;mining under buildings; railways and water bodies; rock pressure around coal face; control of ground subsidence六、正文1. 1 IntroductionThere are numerous coal reserves located under village buildings, railways and water bodies in China. These are called the three-underground coal reserves. Based on statistical data, the three-underground coal reserves amountto 13.7 billion tons. Backfilling mining is a preferable technological measure used toresolve this problem of the three-underground coal reserves[1–4]. However, some conventional backfilling mining technologies such as paste filling, hydraulic filling or pneumatic filling are not widely used due to high costs and limits arising from high rock pressures[ 5–6]. An integrated technology of fully-mechanized coal mining and backfilling is introduced here. This technology allows directly filling up the goaf area with waste. A case study employing this technology and a description of the subsequentcontrol of rock strata movement are also described5 ConclusionsCoal resources are becoming exhausted in China inmore and more coal mining areas. A large amount ofcoal isunder buildings, or under complicated geologicalconditions. In addition, the output of waste isgetting larger and larger. So a new waste-filling miningtechnology was developed. This technology directlyuses the waste to replace coal that cannot bemined out using traditional mining methods. Thisnew technology not only makes effective use of thesolid waste but also protects the surface buildings andenvironment. Therefore, it is one of the importanttechnologies in the green mining system. FMCM with waste backfilling can achieve high productivity and efficiency assuming continuous waste feeding.Of course, continuous waste feeding can be achieved as long as the solid waste is transported into the goaf. Waste-filling has obviously economic benefits consideringthe cost of removing buildings, which is required when the backfilling technology is not used. The concept equivalent mining height allows us to regard coal mining with waste-filling as mining of a thinner coal seam. Then, traditional methods of rock pressure theory and ground subsidence prediction can be used to analyze the strata behavior and ground subsidence. This is a limit analysis: Some parameters obtained are upper limits, such as the support load, the roadway deformation, the support pressure and the ground deformation. Theoretical analysis and measured data show that, when coal mining with waste-filling is used, the degree and absolute values of strata deformation are obviously reduced at the working face. For example, the maximum convergence deformation of roadways, the incidence of support pressure and the peak value are obviously lower for roadways compared to when backfilling is not used. This makes periodic weighting unseen in practice and ground subsidence can be strictly controlled. What is more, coal resources located under villages or industrial sites, which can not be exploited by conventional mining methods, now can be safely and effectively mined out without removingthe buildings on the surface.17(3): 316–320七、参考文献References1 MG Qian, JL Xu and XX Miao, Green technique in coal mining, . Journal of China University of Mining & Technology, 32 4 (2003), pp. 343–348 (In Chinese)..2 MG Qian and TC Liu, Ground Pressure and Its Control, China University of Mining and Technology Press, Xuzhou (1991), (In Chinese)..3 GQ He, L Yang and GD Ling et al., Mining Subsidence, China University of Mining and Technology Press, Xuzhou (1991), (In Chinese)..4 XX Miao, XB Mao and GW Hu, et al. Research on broken expand and press solid characteristics of rocks and coals, . Journal of Experimental Mechanics, 12 3 (1997), pp. 394–399 (In Chinese)。
机器学习技术中的时间序列预测方法应用案例时间序列预测是机器学习技术中的重要应用领域之一,它能够帮助我们对未来的趋势进行预测与分析。
在许多实际应用中,时间序列预测方法被广泛应用于股票市场预测、天气预报、经济指标预测等领域。
本文将介绍几个时间序列预测方法的应用案例,帮助读者更好地理解其在实际环境中的应用。
首先,我们来介绍一种常用的时间序列预测方法,即自回归移动平均模型(ARMA)。
ARMA模型是一种线性模型,它结合了自回归模型(AR)和移动平均模型(MA)的特点,可以用来描述时间序列数据的自相关性和滞后效应。
在许多经济领域的数据分析中,ARMA模型被广泛应用于经济指标的预测。
例如,利用ARMA模型可以对股票市场的波动进行预测与分析,帮助投资者做出更准确的决策。
其次,我们来介绍一种更为复杂的时间序列预测方法,即长短期记忆网络(LSTM)。
LSTM是一种递归神经网络模型,它可以有效地捕捉时间序列数据中的长期依赖关系,并具有较强的预测能力。
LSTM在语音识别、自然语言处理等领域得到了广泛应用,同时在股票市场预测、天气预报等时间序列预测任务中也有着良好的表现。
例如,利用LSTM模型可以对股票的收盘价进行预测,帮助投资者做出买入或卖出的决策。
另外,我们来介绍一种时间序列预测方法的组合应用,即ARIMA模型与外部变量的集成模型。
ARIMA模型是一种广义自回归移动平均模型,具有对非平稳时间序列数据建模的能力。
通过引入外部变量,可以进一步提高ARIMA模型的预测精度。
这种集成模型在交通流量预测、电力负荷预测等领域得到了广泛应用。
例如,利用ARIMA模型与天气、节假日等外部变量相结合,可以对城市的交通流量进行准确的预测,帮助交通管理部门优化交通流量管控。
最后,我们来介绍一种应用于短期负荷预测的时间序列预测方法,即小波神经网络模型(WNN)。
WNN模型是一种基于小波变换与神经网络的联合模型,可以有效地捕捉短期负荷的波动特征。
Probability and Stochastic ProcessesProbability and stochastic processes are important concepts in the field of mathematics and have applications in various areas such as engineering, finance, and computer science. In this response, I will discuss the significance of probability and stochastic processes from multiple perspectives, highlightingtheir practical applications, theoretical foundations, and potential limitations. From a practical perspective, probability and stochastic processes play a crucial role in decision-making under uncertainty. Whether it is predicting the weather, estimating the risk of a financial investment, or designing a reliable communication system, the ability to quantify and analyze uncertainty is essential. Probability theory provides a framework for modeling and analyzing random events, enabling us to make informed decisions based on the likelihood of different outcomes. Stochastic processes, on the other hand, allow us to model systems that evolve over time in a probabilistic manner, providing valuable insights into the behavior of complex systems. In the field of engineering, probability and stochastic processes are used extensively in reliability analysis and system design. By modeling the failure rates of components and the interactions between them, engineers can evaluate the reliability of a system and identify potential weaknesses. This information is crucial for designing robust systems that can withstand uncertainties and minimize the risk of failure. Stochastic processes, such as Markov chains and queuing theory, are also used to model and analyze various engineering systems, including communication networks, manufacturing processes, and transportation systems. From a financial perspective, probability and stochastic processes are essential tools for risk management and investment analysis. Financial markets are inherently uncertain, and understanding the probabilistic nature of asset prices and returns is crucial for making informed investment decisions. By modeling the behavior of financial variables using stochastic processes, such as geometric Brownian motion or jump-diffusion processes, analysts can estimate the probabilities of different market scenarios and assess the risk associated with different investment strategies. This information is invaluable for portfolio management, option pricing, and hedging strategies. From a theoretical perspective, probability theory and stochasticprocesses provide a rigorous mathematical foundation for understanding randomness and uncertainty. Probability theory, with its axioms and theorems, allows us to reason logically about uncertain events and make precise statements about their probabilities. Stochastic processes, as mathematical models for random phenomena, provide a framework for studying the long-term behavior of systems and analyzing their statistical properties. This theoretical understanding is not only important for practical applications but also for advancing our knowledge in various scientific disciplines, including physics, biology, and social sciences. However, it is important to acknowledge the limitations of probability and stochastic processes. Firstly, these concepts are based on assumptions and simplifications that may not always hold in real-world situations. For example, many stochastic models assume that the underlying processes are stationary and independent, which may not be true in practice. Secondly, probability and stochastic processes can only provide probabilistic predictions and estimates, rather than deterministic outcomes. This inherent uncertainty means that even with the best models and data, there will always be a degree of unpredictability. Lastly, the accuracy of probability and stochastic models heavily relies on the availability and quality of data. In situations where data is limited or unreliable, the predictions and estimates obtained from these models may be less accurate or even misleading. In conclusion, probability and stochastic processes are fundamental concepts with wide-ranging applications and theoretical significance. They provide a powerful framework for quantifying and analyzing uncertainty, enabling us to make informed decisions and understand the behavior of complex systems. From practical applications in engineering and finance to theoretical foundations in mathematics and science, probability and stochastic processes play a crucial role in our understanding of the world. However, it is important to recognize theirlimitations and the inherent uncertainties they entail. By embracing uncertainty and using probability and stochastic processes as tools for reasoning anddecision-making, we can navigate the complexities of the world with greater confidence and understanding.。
李雅普诺夫指数迁移率边【原创实用版】目录一、李雅普诺夫指数的概念和背景二、李雅普诺夫指数与混沌运动的关系三、李雅普诺夫指数的应用案例四、李雅普诺夫指数的意义和影响正文一、李雅普诺夫指数的概念和背景李雅普诺夫指数(Lyapunov Exponent)是一种用于描述非线性系统动力学行为的数学指标,由俄国数学家亚历克谢·李雅普诺夫于 19 世纪末提出。
李雅普诺夫指数可以用来衡量一个系统在给定初始条件下,经过一定时间后,其状态变量偏离初始值的速度。
在数学上,李雅普诺夫指数可以表示为系统状态变量的对数增量与相应时间间隔的比值。
二、李雅普诺夫指数与混沌运动的关系混沌运动是指在确定性非线性系统中,系统的演化行为表现出极度敏感依赖于初始条件的现象。
在混沌运动中,系统的状态变量在经过一定时间后,会与初始条件相差甚远,呈现出无规律、不可预测的特征。
李雅普诺夫指数是判断一个非线性系统是否具有混沌行为的重要依据。
当李雅普诺夫指数大于零时,可以断定系统处于混沌状态;当李雅普诺夫指数小于零时,系统则趋于稳定或周期解。
三、李雅普诺夫指数的应用案例李雅普诺夫指数在许多领域都有广泛应用,例如气象学、生态学、经济学等。
其中,最为著名的应用案例是洛伦兹提出的天气预报模型。
在1961 年的一个冬季,洛伦兹通过计算机模拟天气模式,发现从几乎相同的初始条件出发,经过一段时间后,天气模式的预测结果却出现了巨大的差异。
这一发现揭示了混沌现象在气象学中的重要作用,并为后来的气象预报研究提供了重要的理论依据。
四、李雅普诺夫指数的意义和影响李雅普诺夫指数的提出和应用,对于理解和预测非线性系统的动力学行为具有重要意义。
它为我们提供了一种定量的方法来分析系统的稳定性和混沌现象,从而帮助我们更好地掌握系统的演化规律。
The discovery of coal marked a significant turning point in human history, particularly in the realm of energy production and industrial development.Coal,a fossil fuel formed from the remains of ancient plants,has been used by humans for thousands of years,but its widespread use as an energy source began during the Industrial Revolution.Early Uses of CoalInitially,coal was used for a variety of purposes.In ancient China,for instance,coal was discovered and utilized for its heatproducing properties as early as the4th century BCE. It was used for heating and cooking,but its potential as a fuel for largescale industrial processes was not fully realized until much later.The Industrial RevolutionThe18th and19th centuries saw the coal industry boom,especially in Britain,where vast deposits of coal were discovered.This period,known as the Industrial Revolution,was characterized by rapid industrialization and the development of machinery.Coal became the primary fuel for steam engines,which powered factories,mines,and eventually, locomotives.Environmental ImpactThe increased use of coal had profound environmental implications.The burning of coal releases carbon dioxide and other pollutants into the atmosphere,contributing to air pollution and climate change.Despite these concerns,the demand for coal continued to grow as it was cheaper and more abundant than other energy sources at the time. Technological AdvancementsOver time,technologies were developed to mitigate the environmental impact of coal use. For example,the invention of the steam turbine improved the efficiency of coalfired power plants,while scrubbers and filters were introduced to reduce emissions.Modern ChallengesIn the21st century,the world faces the challenge of reducing reliance on coal due to its environmental impact.There is a global push towards cleaner energy sources,such as solar,wind,and hydroelectric power.However,coal remains a significant part of the energy mix in many countries,particularly those with limited access to alternative energysources.Future ProspectsThe future of coal is uncertain.On one hand,advancements in clean coal technologies and carbon capture and storage offer hope for a more sustainable use of this resource.On the other hand,the increasing focus on renewable energy and the global commitment to reducing greenhouse gas emissions suggest a gradual decline in the role of coal in the worlds energy supply.In conclusion,the discovery and utilization of coal have had a lasting impact on human society,driving industrialization and economic growth,but also posing significant environmental challenges.As we move forward,the balance between energy needs and environmental sustainability will continue to be a critical issue in the global conversation about energy sources.。
Ž.International Journal of Coal Geology351998175–207Characteristics and origins of coal cleat:A review ubach a,),R.A.Marrett b,J.E.Olson c,A.R.Scott aa The UniÕersity of Texas at Austin Bureau of Economic Geology,10100Burnet Road,Austin,TX78758-4497,USAb The UniÕersity of Texas at Austin Department of Geological Sciences,Austin,TX78758-4497,USAc The UniÕersity of Texas at Austin Department of Petroleum and Geosystems Engineering,Austin,TX78758-4497,USAReceived18December1996;accepted16April1997AbstractCleats are natural opening-mode fractures in coal beds.They account for most of the permeability and much of the porosity of coalbed gas reservoirs and can have a significant effect on the success of engineering procedures such as cavity stimulations.Because permeability and stimulation success are commonly limiting factors in gas well performance,knowledge of cleat characteristics and origins is essential for successful exploration and production.Although the coal–cleat literature spans at least160years,mining issues have been the principal focus,and quantitative data are almost exclusively limited to orientation and spacing information.Few data are available on apertures,heights,lengths,connectivity,and the relation of cleat formation to diagenesis,characteristics that are critical to permeability.Moreover,recent studies of cleat orientation patterns and fracture style suggest that new investigations of even these well-studied parameters can yield insight into coal permeability.More effective predictions of cleat patterns will come from advances in understanding cleat origins.Although cleat formation has been speculatively attributed to diagenetic and r or tectonic processes,a viable mechanical process for creating cleats has yet to be demonstrated.Progress in this area may come from recent developments in fracture mechanics and in coal geochemistry.q1998Elsevier Science B.V. Keywords:coal;fractures;brittle deformation;statistical analysis;mechanics;natural gas1.IntroductionFractures occur in nearly all coal beds,and can exert fundamental control on coal stability,minability,and fluid flow.It is therefore not surprising that coal fractures have)Corresponding author.Fax:q1-512-4710140;E-mail:laubachs@0166-5162r98r$19.00q1998Elsevier Science B.V.All rights reserved.Ž.PII S0166-51629700012-8()176ubach et al.r International Journal of Coal Geology351998175–207Ž.Ž. Fig. 1.Schematic illustration of coal cleat geometries.a Cleat-trace patterns in plan view.b CleatŽ.hierarchies in cross-section view adapted from Laubach and Tremain,1991.These conventions are used for cleat:length is dimension parallel to cleat surface and parallel to bedding;height is parallel to cleat surface and perpendicular to bedding;aperture is dimension perpendicular to fracture surface.Spacing between two cleats Ž.of same set is a distance between them at right angles to cleat surface.been investigated since the early days of coal mining,and that published descriptionsŽand speculation on fracture origins date from early in the nineteenth century Mammatt,.1834;Milne,1839;cited in Kendall and Briggs,1933.Although various miner’s terms for systematic fractures in coal have been used over the years,they are still generallyŽ.referred to by the ancient mining term:cleat Dron,1925.Cleats are fractures that usually occur in two sets that are,in most instances,mutually perpendicular and also perpendicular to bedding.Although pre-1990geologic literature and current mining usage distinguishes these sets on the basis of factors such as ‘prominence’that are difficult to quantify,abutting relations between cleats generallyŽ.show that one set pre-dates the other Fig.1.This is a readily quantifiable distinction between sets in most outcrops and cores.Through-going cleats formed first and are referred to as face cleats;cleats that end at intersections with through-going cleatsŽformed later and are called butt cleats Laubach and Tremain,1991;Kulander and Dean, .1993.These fracture sets,and partings along bedding planes,impart a blocky character Ž.to coal Fig.2.A hierarchy—or perhaps a continuum—of cleat sizes typify theŽ.Ž.population of cleats in a coal bed Laubach and Tremain,1991Fig.1.This is most easily recognized in cleat heights,but size variations are also evident in cleat lengths, apertures,and spacings.Although fractures in coal are relatively unimportant in strip mining,their signifi-cance in efficient design and safety of underground coal mines has continued toŽcommand the attention of the mining industry Hanes and Shepherd,1981;Esterhuizen,.1995;Molinda and Mark,1996.In contrast,the characteristics and origin of fractures inŽ.coal have been relatively neglected in recent1966–1996geological literature.For example,only two AAPG Bulletin papers specifically on coal fractures have been()ubach et al.r International Journal of Coal Geology351998175–207177Fig.2.Cleats in coal outcrop of Cretaceous Fruitland Formation.Photograph,view to northwest.Rock hammer for scale.published in that time,and the leading journal on coal geology,the International Journal of Coal Geology,has only published one article that focused on cleat in the last10 years.Other journals and geology textbooks have also paid little heed to cleat in recent times.This neglect partly reflects a historic impasse in the scientific understanding of certain types of fractures such as those in coal.Cleats most commonly occur without any observable shear offset,and are thus properly termed opening-mode fractures.Studies of the origins of opening-mode fractures,such as cleats and joints,are plagued by the problem of equifinality—the situation where several processes may lead to the same result—rendering unique causes difficult to deduce from products.This arises because Ž.coals and other rocks have low tensile strength,and a wide range of loading paths canŽlead to propagation of opening-mode fractures Engelder,1985;Engelder and Fischer, .1996.Yet such fractures preserve little evidence of the loading conditions that caused them.A symptom of this is the variety of plausible scenarios that have been advanced()178ubach et al.r International Journal of Coal Geology351998175–207Žfor the origins of cleats Kendall and Briggs,1933;McCulloch et al.,1974;Ting,1977;.Close,1993and the lack of explicit,testable predictions that can be used to identify the best interpretations.Owing to the increasing importance of coal beds as gas reservoirs,geologists are again becoming concerned with the characteristics and origins of cleat.For coalbed methane extraction,knowledge of the properties of natural fractures is essential for planning exploration and development because of their influence on recovery of methane,and the local and regional flow of hydrocarbons and water.New mapping of cleat patterns,guided by recent conceptual advances in the description and theoretical understanding of fracture processes,is beginning to bring these patterns into focus.This, together with more rigorous study of the petrology of cleat development,may resolve uncertainties about causes of cleat that now hinder predictions of interwell-scale patterns of fractures in coal beds.This paper highlights recent studies with emphasis on our research in United States coalbed methane basins,and points to areas of potential future advancement.2.Cleat attributesAs many observers have noted,the attributes of cleats closely resemble those ofŽfractures termed‘joints’in other rock types Dron,1925;Kendall and Briggs,1933; Williamson,1967;McCulloch et al.,1974,1976;Ting,1977;Campbell,1979;Laubach .et al.,1992.Cleats are opening-mode fractures rather than faults;typically there is no appreciable offset parallel to cleat walls.At surface conditions they generally have apertures less than0.1mm,and these scarcely visible apertures caused some early workers to mistakenly conclude that no opening had occurred normal to cleat walls. They also have surface structures such as arrest lines and hackles characteristic ofŽ.opening-mode propagation Kulander and Dean,1990.Many of the prominent attributes of cleats and cleat patterns have been known since the1930’s.Individual fractures are generally planar but sometimes are locally curved in plan view.Cleats are subvertical in flat-lying beds and are typically oriented at right angles to stratification even where beds are folded.In many cases cleats are confined to individual coal beds,or to layers composed of a particular maceral monly they are uniform in strike within an outcrop or core and arranged in subparallel sets that haveŽ.uniform regional trends Kendall and Briggs,1933.Yet they locally show abrupt lateralŽ.and vertical shifts in strike Dron,1925.Coals containing closely spaced faults rather than opening-mode fractures are apparently rare.This reflects either proximity to large faults,reactivation by slip on pre-existing cleats,or anomalous burial conditions Ž.Ammosov and Eremin,1963;Laubach et al.,1993.One remarkable attribute of cleat formation is the extent to which they are developed in many coal beds of nearly all ranks in maturity.Cleats are typically much more intensely developed than fractures in adjacent non-coal rocks.The great intensity of cleat development,in comparison to fractures in other rock types,is an important clue to cleat origins.()ubach et al.r International Journal of Coal Geology351998175–207179 2.1.Cleat sizeThere are little quantitative data on the size of cleats.Because many cleats are only centimeters in length and height and typically have nearly indiscernible aperture, modeling studies usually assume cleats are small in terms of length,height,and aperture. In San Juan Basin,New Mexico,Fruitland Formation coal beds cleat lengths and heightsŽ.are reported to range from microns to meters Tremain et al.,1991.Yet these cleats areŽarranged in a hierarchy of sizes that includes fractures of decimeter size‘master cleats’, .Fig.1.Ž.Estimates of in situ cleat widths range from0.001to20mm Gamson et al.,1993. However,most information on cleat width is based on outcrop studies and r or micro-scopic examination of coal samples not under confining pressure.Little reliable informa-tion is available on cleat apertures in the subsurface.The parallel-plate fracture permeability model can be used to estimate that cleat apertures range from3to40m m Ž.Fig.3.Where diagenetic minerals have filled cleats,considerably wider fractures are locally preserved,including fractures with widths as much as0.5cm in Cretaceous coal beds in the western United States.These fossilized cleat apertures show that fractures much wider than most outcrop-and core-based estimates are locally present in the subsurface.Because cleat apertures may change as effective stress is altered in coalbed methane reservoirs,lack of reliable information on in situ cleat apertures is a potential barrier to effective reservoir management.Fig.3.Relation among face-cleat spacing,permeability,and aperture assuming parallel-plate ing measured cleat spacing and permeability for highly productive coalbed methane wells in San Juan and Black Warrior Basins,shaded area shows range of inferred aperture size.()180ubach et al.r International Journal of Coal Geology351998175–207Fig.4.Cleat aperture size distribution for combined face and butt cleats in cores from San Juan Basin.Data Ž.represent volumetric3D sampling.Least squares fit made to data in open symbols.Size distribution of opening-mode fracture apertures have been studied quantitativelyŽ.in a variety of rock types Marrett,1997,but there is little published data for cleats to permit such an analysis.One set of observations,summarized by Close and Mavor Ž.1991,was collected from six wells in the San Juan Basin.Aperture of a typical cleat in each lithotype layer was measured microscopically without confining stress.From thisŽ.we calculate cumulative volumetric3D frequency of cleats as a function of each core Ž.Fig.4.This presupposes that all cleats in a specific lithotype layer have the same aperture,probably a poor assumption.Apertures observed in three coal cores range from0.01to0.2mm,although cleatsŽ. with smaller apertures were not measured.In each core,cumulative frequency f of cleats having apertures of e or larger follows a power law:f s be y c1Ž.Žwhere b is a general measure of the cleat intensity and c is a constant referred to as the .fractal dimension.A power law forms a line on a log–log plot of f versus e,and the slope of the line is the negative of the fractal dimension.Values of c determined fromŽ.volumetric sampling of cleat apertures 2.74–2.82are larger by;2than valuesŽ.Ž. determined from scanline1D sampling of apertures in non-coal rocks Marrett,1997.()ubach et al.r International Journal of Coal Geology351998175–207181Ž.This is expected assuming aperture,length,and height are linearly proportional due toŽ.Ž.Žthe difference between volumetric3D and scanline1D sampling Marrett and.Allmendinger,1991;Marrett,1996.Thus,size distribution of cleat apertures is consis-tent with size distribution of fracture apertures in non-coal rocks.Ž.Reports summarized by Close and Mavor1991provide the only systematic core data available on cleat heights.Among cleats with a specific aperture value,heights vary significantly.However,cleats with large apertures tend to have large heights.Average Ž.height h of all cleats having a specific aperture value increases approximately linearly with aperture:h s ae2Ž. where a is about1000for cleats in one well.This linear aperture r height relationship is consistent with linear elastic fracture mechanics predictions for opening-mode fracturesŽ. where fracture height is shorter than fracture length Pollard and Segall,1987.Ž.Ž.Combining results of Eqs.1and2implies that cleat heights follow a power law size distribution.No systematically collected data on cleat lengths are known.Butt cleats are limited in length by spacing of face cleats,so butt cleat lengths should depend on face cleat spacings.We might anticipate that face cleat lengths will follow power law size distributions,by analogy with size distribution of fracture lengths in non-coal rocks Ž.extension fracture data in Marrett,1997and references therein.Positive interference between wells shows that interconnected pathways in cleated rocks can be as long as1 km.2.2.Cleat spacingŽ.Cleat spacing is sufficiently close on the order of centimeters that numerous visible fractures are typically present in coal cores.However,core observations rarely distin-guish the hierarchy of fracture sizes that are present,so published cleat spacing information is difficult to compare.Spacing measurements reported from core may count all visible fractures,whereas outcrop and mine studies typically choose fractures of a given size to measure,but this choice is rarely explicitly stated.Recognizing the wide range of cleat sizes present in coal,quantitative statements of spacing are onlyŽ. meaningful with reference to the sizes of cleats included in an analysis Fig.5.AnŽ. example where a size criteria was specified is the study of Tremain et al.1991.In thisŽ.study,fractures of equivalent height defined by layer thickness were compared. Measurements on long mine highwalls show that spacing between individual cleats ofŽ.similar size ranges from microns to more than a meter Fig.6.Yet within a given bed, average spacing of fractures of similar size is remarkably uniform over distances of Ž.Ž.hundreds of meters Fig.7Tremain et al.,1991.Sampling procedure needs to be specified in order to obtain meaningful fracture spacing measurements.Ž.Variability in spacing or intensity of fracture development of cleats in coal beds hasŽ.long been recognized Kendall and Briggs,1933;Macrae and Lawson,1954.Contrasts in coalbed methane well production also may reflect variable development of cleats,as several operators have speculated.Methods for identifying and mapping such variability Ž.Esterhuizen,1995are important in mining conditions because of implications for()182ubach et al.r International Journal of Coal Geology351998175–207Fig.5.Cleat spacing and aperture data from Northeast Blanco Unit No.403,San Juan Basin.Plotted spacings represent averages of all measured spacings having a specific aperture measurement.Least squares fit made to average spacings of face cleats.ŽFig.6.Cleat spacing versus bed thickness of medium-brightness coals,northern San Juan Basin adapted from.Laubach and Tremain,1991.()ubach et al.r International Journal of Coal Geology351998175–207183Fig.7.Cleat spacing versus traverse distance in a bed of uniform dip,thickness,and composition,San Juan Basin,New Mexico.Center half of data at each station is shown by box,and median by bar.Dashed line and shaded area are mean and one standard deviation of measurements from all stations.Ž.quality of mined coal and mine stability Brady and Haramy,1994.These methods typically rely on visual estimates of fracture intensity,but recent advances in automated imaging methods and image analysis promise to make these approaches more quantita-Ž.tive Djahanguiri et al.,1994.Some of these mapping methods possibly could be adapted for use in describing core from coal-gas reservoirs or from outcrop analogs.A variety of factors have been cited as affecting cleat development.These factors include coal rank,coal composition,and layer thickness.To the extent that the impact of these factors on cleating has been explored quantitatively,average cleat spacing has been used to characterize the cleats.Other factors,such as mineral fill,degree of tectonic and compactional deformation,and coal age,have received little to no attention.Researchers have observed that cleat spacing varies with coal rank,decreasing fromŽlignite through medium volatile bituminous coal Ammosov and Eremin,1963;Ting, .1977;Law,1993,and increasing through anthracite coals,forming a bell-shaped distribution of cleat spacing.Based on outcrop and core data from North American coal,Ž.Law1993found that face cleat spacing ranges from approximately22cm in lignites ŽŽ..ŽR vitrinite reflectance values of0.25–0.38%to0.2cm in anthracites R values o o.more than2.6%.The best fit to the data is an inverse exponential equation: s s0.473P100.398r R o3Ž.Ž.where s is cleat spacing in centimeters.Eq.3predicts a similar decrease in cleat spacing with increasing rank from the lignite to medium volatile bituminous,but alsoŽindicates that spacing remains constant at vitrinite reflectance values above1.5%Fig. .8.However,only two data points from low-volatile bituminous and higher-rank coalsdefine the trend,so rank-dependence of cleat spacing remains uncertain.Variation in cleat spacing with rank may reflect competing processes of fractureŽ.formation and annealing Levine,1993.Bedding-parallel compaction fabrics and deformation or flow of coal around rigid grains shows that flattening predates fracturing()184ubach et al.r International Journal of Coal Geology351998175–207Fig.8.Cross-plot of vitrinite reflectance versus cleat spacing for coals ranging from lignite to anthracite Ž.Ž.vitrinite reflectance of0.25to2.6q%.Mean face-cleat spacing.Adapted from Law1993.Data were collected only from bright coal lithotype layers.Ash content varies among coals and affects cleat spacing, however ash content was not reported.in most coals.Highly strained coals at high rank deform predominantly by flow rather than fracture.Because tectonism commonly accompanies high thermal maturation,it is reasonable that tectonism may obliterate previously formed cleats in many anthracites apparently barren of cleats.It is an open question whether annealing processes are an unrecognized but important process modifying fracture patterns in low-rank coal.If so, regular variation in cleat spacing with rank within the lignite to high-rank bituminous range might not be expected.Many authors have noted that cleat spacing varies with coal type and ash content Ž.Spears and Caswell,1986;Tremain et al.,1991;Law,1993.Bright coal lithotypes Ž.Ž. vitrain generally have smaller cleat spacings than do dull coal lithotypes durain Ž.Kendall and Briggs,1933;Stach et al.,1982.Coals with low ash content tend to have smaller cleat spacings than do coals with high ash anic-rich shales also commonly have closely spaced fractures that resemble cleats.This suggests that geochemical processes such as shrinkage related to coal composition are key to intense development of fractures.The effect of compositional layering on fracture spacing has received much attention. Examples where average spacing is linearly proportional to coal lithotype-layer thick-Žness have been found Spears and Caswell,1986;Grout,1991;Tremain et al.,1991;.Ž.Close and Mavor,1991;Law,1993.Daniels et al.1996,in contrast,found no pattern of cleat spacing with bed thickness.If we interpret cleat height as equal to lithotype Ž.layer thickness t,and assume a linear aperture-spacing relation the result is a linear proportionality between cleat spacing and lithotype layer thickness.Equating cleatŽ.Ž. height and lithotype layer thickness again,the combination of Eqs.1and2implies that lithotype layer thicknesses follow a power law size distribution:N s qt y r4Ž. where N is cumulative number of lithotype layers having a thickness of t or larger,q is a measure of the total sequence thickness,and r is fractal dimension.Coal lithotypeŽ.layer thickness data collected by Smyth and Buckley1993follow a power law size distribution.The empirical fit to these data has a fractal dimension significantly greater than one,implying that thin layers account for more coal volume than thick layers.Comparisons of cleat spacings versus bed thickness have typically not accounted for the range of cleat sizes present.For example,Upper Cretaceous Fruitland coal beds haveŽ.numerous interbedded ash layers tonsteins that define coal bed thicknesses.A cleat spacing-bed thickness relation is apparent if cleats that span the coal layer are used and shorter cleats are neglected,and then only for beds that are thinner than10to20cm.ForŽ.these,cleat spacing is slightly less than layer thickness Tremain et al.,1991.Other coalŽbeds in the western United States for example,Upper Cretaceous Adaville Formation.coal beds at the Elkol mine,Wyoming have a spectrum of cleat sizes and spacings that resemble those of Fruitland coal beds,but these coal seams lack thin interbeds.SimilarŽhierarchies of fractures in massive beds have been observed in non-coal rocks Nelson, .Ž1985and in cooling cracks in glass Nemat-Nasser and Oranratnachai,1979;DeGraff .and Aydin,1993.This implies that the apparent fracture spacing r bed thickness relationship in Fruitland coals may be an illusion.Such observations suggest that,except perhaps for the thinnest beds,interbed-layer thickness is not a primary control on cleat intensity.However,a possible explanation for hierarchical spacing without obvious layer boundaries may be found in the mechanical similarity of cooling,contracting lava flows and dehydrating,contracting coals.DeGraff Ž.and Aydin1993show that cooling rate strongly affects fracture propagation,resulting in closer spaced fractures for higher cooling rates.Possibly variations in contraction rate Ž.of coal controlled by chemical processes may govern the spacing of cleats of a given size.Even cleat spacing is apparent in many coal beds.Although they have been reported by mine operators,few distinct cleat swarms—zones of anomalously closely spaced fractures—have been described.This may partly result from lack of coal exposuresŽ.where intense localized fracture development can be seen Fig.9.Some swarms areŽ.associated with faults Shepherd et al.,1981;Laubach et al.,1991and locally these features are evident in seismic records.This is an area where more information is needed,since these structures potentially are a cause of highly productive areas within coal beds.Finally,indirect quantification of cleat spacing comes from data on sizes of mined Ž.coal fragments Bennett,1936;Turcotte,1992.Mass fractions of mined coal fragmentsŽ.as a function of fragment size determined by sieve analysis are consistent among theŽseams and collieries analyzed19data sets,from United Kingdom coals of unknown.Ž.rank,composition,and age,and form lines on a log–log plot Fig.10.If we assume that coal fragments in a data set have statistically similar shapes and mass densities,thenFig.9.Cleat patterns and potential sources of anomalous cleat attributes:fracture swarms and differential compaction zones.Diagram shows schematic fracture patterns in coal.Žwe can convert mass fraction data into cumulative numbers R.Marrett,1994,unpubl..rept.and characterize the size distribution of fragments.The spacing of bounding cleatsprobably define the size of an individual fragment,so we can interpret the convertedFig.10.Coal fragment size distribution from sieve analysis of coals in‘Colliery B’Bennett,1936.Data Ž.represent volumetric3D sampling of mass fraction having linear dimension less than plotted value.For clarity,0.5was added to log mass fraction r number values for coal seam1and0.5was subtracted from logmass fraction r number values for coal seam5.data as a volumetric sample of the cleat spacing size distribution.This interpretationsuggests that cleat spacing follows a power law of the form:N s ms y d5Ž. where N is volumetric cumulative number of spacings of s or larger,m is a measure ofcoal volume and cleat frequency,and d is the fractal dimension.Best fit values of dŽ.range from2.31to2.34.Eq.5plus a linear aperture-spacing relation suggests thatc s d;however this is not true of the values determined.Although there are a variety ofpossible explanations,the most likely is that the assumption involved in averagingobserved average spacings is incorrect.2.3.Cleat network geometry and connectiÕityŽIf all fractures in a coal bed were isolated,then flow rates observed after draining.those fractures directly intersected by the wellbore would be limited by matrix Ž.permeability i.e.,no fracture enhancement of work geometry and connectivity of fractures in a system clearly are important to the permeability enhance-Ž.ment that fractures can provide Fig.9.For example,coal-bed permeability may be3toŽ10times greater in the face cleat direction than in other directions McCulloch et al., .1974,reflecting the strong preferred orientation and greater length of interconnectedfractures in that direction.On a local scale,cleat connectivity results from cross cuttingand abutting relations.Maps of cleat patterns show that connections within the networkŽmay be accomplished by fractures of vastly different size Tremain et al.,1991;Chen .and Harpalani,1995.Vertical connectivity of cleat networks is commonly limited bythe termination of small cleats at interfaces between coal types,and large cleats atcoal-non-coal bed interfaces.One approach to cleat network characterization is to count the various types of Ž.Ž. fracture ends i.e.,connected,constricted,or dead-end Laubach et al.,1991.Con-stricted and dead-end terminations render fractures insignificant to permeability en-hancement,although they might assist flow from the matrix into the fracture network.Analysis of relative frequencies of different fracture-end types was done for twoŽ. exposed bedding surfaces of coals in the San Juan Basin Laubach et al.,1991.One coal-bed surface showed the expected result that cleat systems are well connected,due to systematic development of butt cleats extending from one face cleat to another.The other bedding surface indicated poor connectivity among cleats,possibly because onlyŽlarge cleats were considered.Uncertainty about timing and origin of butt cleats which.may in some case be restricted to near-surface locations clearly will impact interpreta-tion of fracture connectivity in coal beds at depth.Cross-cutting relations and contrastsin orientation suggest that not all cleats in a given bed formed simultaneously.2.4.Cleat petrologyŽCleat apertures may or may not contain authigenic minerals commonly clays,quartz, .Žand calcite or organic material and resin Spears and Caswell,1986;Daniels and .Altaner,1990.In coal mining,such minerals have an impact on coal quality,but forcoalbed methane,diagenetic alteration of the cleat network due to precipitation of。
时序预测算法python时序预测算法概述时序预测算法旨在预测未来序列的值,基于以往观测到的数据序列。
它们广泛应用于各种领域,例如股票市场预测、天气预报和医疗诊断。
时间序列数据时间序列数据是一系列按时间顺序排列的数据点。
例如,股票价格序列是一组按时间顺序记录的股票价格。
时间序列数据通常具有时间依赖性,即序列中的当前值与之前的值相关。
时序预测算法类型自回归移动平均 (ARMA) 模型:ARMA 模型是一种线性时序预测算法,将过去的值(自回归项)与过去误差的加权和(移动平均项)结合起来预测未来值。
季节性自回归移动平均 (SARIMA) 模型:SARIMA 模型是 ARMA模型的扩展,专门用于处理具有季节性模式的时间序列数据。
它包括季节性自回归和季节性移动平均项。
滑窗法:滑窗法是对历史数据窗口进行预测,然后随着新数据的出现滑动窗口。
常见的滑窗法包括移动平均法和指数平滑法。
机器学习模型:诸如递归神经网络 (RNN) 和长短期记忆 (LSTM) 等机器学习模型也用于时序预测。
它们可以学习复杂的时间依赖关系,并对非线性数据进行建模。
评价指标时序预测算法的性能通常使用以下指标进行评估:均方根误差 (RMSE):度量预测值与实际值之间的平均差值的平方根。
平均绝对误差 (MAE):度量预测值与实际值之间的平均绝对差值。
马洛斯距离:度量预测值与实际值之间的平均距离。
应用时序预测算法在以下领域具有广泛的应用:金融预测:预测股票价格、汇率和商品价格。
天气预报:预测温度、降水和风力。
医疗诊断:预测疾病风险和患者预后。
工业监控:预测机器故障和生产效率。
交通预测:预测交通流量和道路拥堵。
选择算法选择合适的时序预测算法取决于数据的性质、预测范围和预测精度要求。
对于线性数据,ARMA 或 SARIMA 模型可能是合适的。
对于非线性数据,机器学习模型如 RNN 或 LSTM 可能更有效。
数据预处理在应用时序预测算法之前,可能需要对数据进行预处理,包括:归一化:将数据缩放至特定范围,以提高模型的稳定性。
Do not distribute.Is there a role for trihelix transcription factorsin embryo maturation?Melissa S.Barr,1Matthew R.Willmann 2and Pablo D.Jenik 3,*1Kennard-Dale High School;Fawn Grove,PA USA;2Department of Biology;University of Pennsylvania;Philadelphia,PA USA;3Department of Biology;Franklin &Marshall College;Lancaster,PA USAKeywords:Arabidopsis,embryogenesis,maturation,trihelix transcription factor,microRNAThe development of the angiosperm seed includes the accumulation of storage products,the loss of most of its water and the establishment of dormancy.While much is known about the pathways that initiate maturation during mid-embryogenesis or repress it after germination,only recently has it been shown that other mechanisms repress the program during early embryogenesis.Two recent reports have shown that microRNAs are critical regulators of maturation in Arabidopsis early embryogenesis.Two closely related trihelix transcription factors,ASIL1and ASIL2,were identified as probable partially redundant repressors of early maturation downstream of the microRNA-synthesizing enzyme DICER-LIKE1.An overlap between the genes upregulated in asil1-1and dcl1-15mutants support this conclusion.ASIL2orthologs are found across seed plants,indicating that their role in maturation might be conserved.ASIL1arose from the ancestral ASIL2clade by a gene duplication event in the Brassicaceae,although it is not clear whether its function has diverged.Seed maturation encompasses a set of processes that lead to the accumulation of storage products,desiccation tolerance and dormancy.1The onset of the seed maturation program in Arabidopsis occurs around the heart stage of embryogenesis.A number of transcriptional regulators have been identified that promote maturation.Central to the process appear to be the B3domain transcription factors ABA INSENSITIVE3(ABI3),LEAFY-COTYLEDON2(LEC2)and FUSCA3(FUS3),as well as two proteins that are B subunits of the NF-Y family of trimeric transcription factors [LEC1(also called NF-YB9)]and LEC1-LIKE (L1L ,NF-YB6).Other transcriptions factors from the bZIP,MYB and AGL families,and the hormone ABA have also been implicated,directly or indirectly,in positively regulating the process.2It is known that the expression and accumulation of storage products and other embryonic traits are actively repressed after germination.Most of the repressors that have been described so far involve proteins that downregulate transcription by acting at the chromatin level:histone deacetylases (HDA6/SIL1and HDA19)3,SWI/SNF2chromatin remodelers (BRAHMA,BUSHY GROWTH and ATSWI3c )4,Polycomb group proteins (SWINGER,CURLY LEAF,EMBRYONIC FLOWER2and FERTILIZATION INDEPENDENT ENDOSPERM )5,6and Trithorax group proteins (PICKLE and PICKLE-RELATED )7.Only a handful of transcription factors that repress the expression of maturation genes have been described so far:the B3domain proteins VP1/ABI3-LIKE1(VAL1,also called HIGH-LEVEL EXPRESSION OF SUGAR-INDUCIBLE GENE2or HSI2)and VAL2/HSL1,and the trihelix protein ARABIDOPSIS 6B-INTERACTING PROTEIN1-LIKE1(ASIL1).8-10Because maturation does not start until mid-embryogenesis,it was natural to assume that there were also unknown factors preventing its premature onset.We and David Bartel ’s lab recently showed that microRNAs (miRNAs)are key repressors of maturation during early embryogenesis.11,12As early as the early globular stage,embryos homozygous for loss-of-function mutations in DICER-LIKE1(DCL1)that significantly reduce or eliminate the synthesis of miRNAs also show the development of chloroplasts,accumulation of chlorophyll,and the synthesis of storage products.Nodine and Bartel 11showed that the upregulation of the miR156targets SQUAMOSA PROMOTER-BINDING PROTEIN-LIKE10(SPL10)and SPL11in dcl1is partly responsible for this effect.Willmann et al.12demonstrated that ASIL1,its closest homolog ASIL2,and HDA6/SIL1redundantly repress maturation during early embryonic devel-opment.Early accumulation of chlorophyll is seen in asil1and asil2single mutants and is further enhanced in all three double mutant combinations of asil1,asil2,and sil1.The normal timing of maturation might be explained by the ability of these genes to repress maturation combined with the significantly decreasing expression of ASIL2and SIL1during embryonic development,as shown in a developmental time series microarray experiment from the Goldberg and Harada labs.12The expression levels of these genes are likely indirectly controlled at least in part by*Correspondence to:Pablo D.Jenik;Email:****************Submitted:11/09/11;Revised:11/28/11;Accepted:11/29/11/10.4161/psb.18893SHORT COMMUNICATIONPlant Signaling &Behavior 7:2,205–209;February 2012;G2012Landes BioscienceDo not distribute.miRNAs,because their expression is decreased in dcl1embryos. Thus,it is likely that their expression is repressed directly or indirectly by a miRNA target;whether SPL10and/or SPL11 could be this miRNA target remains unknown.The phenotypes of the double mutants of asil1,asil2and sil1are still weaker than that of dcl1,however,indicating that there are other factors downstream of miRNAs involved in this process,as well. Interestingly,the involvement of ASIL1,ASIL2and SIL1in repressing early maturation shows that at least some of the pathways involved in the post-embryonic repression of maturation function similarly during early embryogenesis.To further explore the connections between DCL1and these genes,we compared microarray data sets generated for dcl1-15 (a strong allele)and asil1-1(probably a null allele).9,12If miRNAs and ASIL1regulate the same processes,we expect to see a significant overlap between them,particularly between the sets of upregulated genes.We expected the comparisons to be noisy, though,as we are comparing microarrays generated from torpedo stage embryos(dcl1-15)and two-week-old seedlings treated with ABA(asil1-1)(Fig.1).In spite of that,we saw a highly significant overlap between the sets of genes that are upregulated in both mutants.This analysis strengthens the argument that miRNAs and ASIL1both repress maturation.The trihelix family of transcription factors,to which ASIL1and ASIL2belong,is specific to the land plant lineage.There are33 members in Arabidopsis.9To better understand the relationships of ASIL1and ASIL2with the rest of the trihelix family,we performed a BLAST search within the Plant Transcription Factors Database(PlantTFDB)(/)13using their protein sequences.We picked all the sequences matching the full-length protein with high scores(.200,e-value,10-15).A phylogenetic tree derived from the alignment of the full-length proteins shows four distinct,well-supported clades:one each for the orthologs of the Arabidopsis genes At3g24490,At3g58630and At3g11100/At5g05550and one that includes both ASIL1 and ASIL2(ASIL1/2)(not shown).These four clades were also found,with various levels of support,by previous analyses of Arabidopsis and rice trihelix family transcription factors.9,14To increase the support of the nodes,we re-built our tree using just the sister clades ASIL1/2and At3g24490(Fig.2).The tree shows that there are ASIL2orthologs in dicots,monocots,gymnos-perms,and lycophytes.The PlantTFDB contains41trihelix transcription factors from the bryophyte Physcomitrella patens, but none of them fall into these clades.ASIL1orthologs,however, are only present in the Brassicaceae,suggesting a gene duplication event in the earliest ancestor of this family.Although nothing is known yet about the function of the ASIL1/2orthologs in other plants,it is possible that they are involved in maturation as well.Interestingly,there are orthologs of the other regulators of maturation(VAL genes,FUS3/LEC2and LEC1)in all lineages of land plants,including seedless plants.15One wonders what their ancestral role was,before they were co-opted for the regulation of seed maturation.Protection against abiotic stress is an intriguing possibility because ABA and ABI3,which are important for seed maturation in Arabidopsis,are involved in desiccation tolerance in the moss Physcomitrella patens.16We selected representatives of the ASIL1/2clade and aligned their full-length protein sequences to see whether there are lineage-specific differences.We found that there are several positions in the N-terminal proline-rich domain(not shown)and in the trihelix domain(specifically in helices1and2)(Fig.3)that consistently differ between the dicot representatives of ASIL1 and ASIL2.This suggests that the ASIL1orthologs have signi-ficantly diverged from their ASIL2counterparts since their dupli-cation.There are also some positions in the trihelix domain that appear to be different in rice.Overall,the trihelix domains of the dicot ASIL2proteins are more similar to those of rice and pine than to ASIL1proteins.Because the trihelix domain is a DNA binding domain,these changes may result in changes in the DNA sequence recognized.However,the only known structure of a trihelix domain,that of the GT-1protein of Arabidopsis,suggests that helix3interacts with the major groove of DNA and deter-mines binding specificity.17None of the observed ASIL1and dicot ASIL2lineage differences affect this particular helix.Further work will be needed to see whether these differences affect DNA binding properties or function.Additional evidence of functional divergence of ASIL1and ASIL2comes from the Arabidopsis protein interactome recently built using a yeast two-hybrid system,which shows that they have largely different potential interactors.18Although the biological significance of all the resulting interactions needs to be validated in planta,it is interesting to note that out of63putativeparison of microarray data for dcl1-15and asil1-1.Theoverlaps were generated using Partek Genomics Suite6.5.The statisticaltest used to show significance of the overlap was a Fisher’s exact test.Figure2(See opposite page).Neighbor-joining phylogenetic tree for the ASIL1/2and At3g24490clades.Full-length protein sequences were aligned using ClustalW,and the tree was built using MEGA4.For each protein,the first number is the one assigned by the PlantTFDB,while the second number is the one assigned by the corresponding sequencing project.Arabidopsis genes are highlighted in gray boxes.Species are identified as follow:Aan, Artemisia annua;Ahy,Arachis hypogaea;Ath,Arabidopsis thaliana;Aly,Arabidopsis lyrata;Bdi,Brachypodium distachyon;Bna,Brassica napus;Bra,Brassica rapa;Cpa,Carica papaya;Csg,Cucumis sativus;Csi,Citrus sinensis;Ghi,Gossypium hirsutum;Ppe,Prunus persica;Lja,Lotus japonicas;Mes,Manihot esculenta;Mtr,Medicago truncatula;Osj,Oryza sativa subsp Japonica;Pta,Pinus taeda;Pgl,Picea glauca;Pth,Populus trichocarpa;Sbi,Sorghum bicolor; Sly,Solanum lycopersicon;Smo,Selaginella moellendorffii;Stu,Solanum tuberosum;Vvi,Vitis vinifera;Zma,Zea mays.Do not distribute.Figure2.For figure legend,see page206.Do not distribute.interactors(48for ASIL1and15for ASIL2),only three proteins interacted with both of them:the protein kinase AKIN11/ SnRK1.2(At3g29160),the60S ribosomal subunit RPL4A (At3g09630)and a transposase(At3g19120).There is also a provocative connection to maturation:an antisense line for an AKIN11/SnRK1.2ortholog in pea showed defects in seed maturation.19While we have yet no data to support a connection, it is tempting to speculate that SnRK1kinase might act in part by negatively regulating ASIL1or ASIL2activity.The available data so far indicate that the trihelix transcription factors ASIL1and ASIL2repress at least certain aspects of the maturation program:the accumulation of storage products(in embryos and seedlings),the development of chloroplasts(embryos), and the expression of regulators of the pathway(seedlings).Our data also support the idea that they mediate some of the effects of miRNAs in the embryos.The conservation of ASIL2hints at the conservation of this repressive pathway across seed plants. Further experiments will help clarify their respective contribu-tions and any divergences in roles between ASIL1and ASIL2.Disclosure of Potential Conflicts of InterestNo potential conflicts of interest were disclosed.AcknowledgmentsThis project was funded by Franklin and Marshall College.M.L.B.was supported by an award to Franklin and Marshall College from the Howard Hughes Medical Institute's Undergraduate Science Education Program.M.R.W.was supported by an NIH NRSA postdoctoral fellowship.We would like to thank Jaime Blair(Franklin and Marshall College)for help with phylogenetic analyses and Jinpu Jin(PlantTFDB)for collating the trihelix protein sequences.Figure3.Alignment of the trihelix domains of selected proteins of the ASIL1/2clade.The trihelix domains were aligned using ClustalW.The position of the helices is based on.9The numbers identifying the proteins correspond to those on Figure2.Differences present in only one lineage(dicot,rice or pine)are boxed in red.Arabidopsis genes are highlighted in gray boxes.References1.Holdsworth MJ,Bentsink L,Soppe WJ.Molecularnetworks regulating Arabidopsis seed maturation,after-ripening,dormancy and germination.New Phytol 2008;179:33-54;PMID:18422904;/10.1111/j.1469-8137.2008.02437.x2.Vicente-Carbajosa J,Carbonero P.Seed maturation:developing an intrusive phase to accomplish a quiescent state.Int J Dev Biol2005;49:645-51;PMID:16096971;/10.1387/ijdb.052046jc3.Tanaka M,Kikuchi A,Kamada H.The Arabidopsishistone deacetylases HDA6and HDA19contribute to the repression of embryonic properties after germination.Plant Physiol2008;146:149-61;PMID:18024558;/10.1104/pp.107.1116744.Tang X,Hou A,Babu M,Nguyen V,Hurtado L,LuQ,et al.The Arabidopsis BRAHMA chromatin-remodeling ATPase is involved in repression of seed maturation genes in leaves.Plant Physiol2008;147:1143-57;PMID:18508955;/10.1104/pp.108.1219965.Bouyer D,Roudier F,Heese M,Andersen ED,Gey D,Nowack MK,et al.Polycomb repressive complex2controls the embryo-to-seedling phase transition.PLoSGenet2011;7:e1002014;PMID:21423668;http://dx./10.1371/journal.pgen.10020146.Makarevich G,Leroy O,Akinci U,Schubert D,ClarenzO,Goodrich J,et al.Different Polycomb group complexesregulate common target genes in Arabidopsis.EMBO Rep2006;7:947-52;PMID:16878125;/10.1038/sj.embor.74007607.Aichinger E,Villar CBR,Farrona S,Reyes JC,Hennig L,Köhler C.CHD3proteins and polycomb group proteinsantagonistically determine cell identity in Arabidopsis.PLoS Genet2009;5:e1000605;PMID:19680533;/10.1371/journal.pgen.10006058.Tsukagoshi H,Morikami A,Nakamura K.Two B3domain transcriptional repressors prevent sugar-inducible expression of seed maturation genes inArabidopsis seedlings.Proc Natl Acad Sci U S A2007;104:2543-7;PMID:17267611;http://dx.doi.org/10.1073/pnas.06079401049.Gao M-J,Lydiate DJ,Li X,Lui H,Gjetvaj B,HegedusDD,et al.Repression of seed maturation genes by atrihelix transcriptional repressor in Arabidopsis seed-lings.Plant Cell2009;21:54-71;PMID:19155348;/10.1105/tpc.108.06130910.Suzuki M,Wang HHY,McCarty DR.Repression ofthe LEAFY COTYLEDON1/B3regulatory network inplant embryo development by VP1/ABSCISIC ACIDINSENSITIVE3-LIKE B3genes.Plant Physiol2007;143:902-11;PMID:17158584;/10.1104/pp.106.09232011.Nodine MD,Bartel DP.MicroRNAs prevent pre-cocious gene expression and enable pattern formationduring plant embryogenesis.Genes Dev2010;24:2678-92;PMID:21123653;/10.1101/gad.198671012.Willmann MR,Mehalick AJ,Packer RL,Jenik PD.MicroRNAs regulate the timing of embryo maturationin Arabidopsis.Plant Physiol2011;155:1871-84;PMID:21330492;/10.1104/pp.110.17135513.Zhang H,Jin J,Tang L,Zhao Y,Gu X,Gao G,et al.PlantTFDB 2.0:update and improvement of the comprehensive plant transcription factor database.Nucleic Acids Res2011;39(Database issue):D1114-7;PMID:21097470;/10.1093/nar/ gkq114114.Fang Y,Xie K,Hou X,Hu H,Xiong L.Systematicanalysis of GT factor family of rice reveals a novel subfamily involved in stress 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euler ancestral sampling 解析-回复Euler ancestral sampling 解析Euler ancestral sampling 是一种基于欧拉遗传算法的采样方法,可以用于从给定的目标分布中生成样本。
它基于马尔可夫链蒙特卡洛(MCMC)方法,在概率图模型中得到了广泛应用。
本文将逐步解析Euler ancestral sampling 的原理及应用,并探讨其优缺点。
1. 欧拉遗传算法欧拉遗传算法是一种基于遗传算法的优化方法,其灵感来源于生物学中的遗传进化。
该算法主要通过模拟生物个体遗传和变异过程来寻找最优解。
而Euler ancestral sampling 是将欧拉遗传算法与概率图模型相结合的一种技术。
2. 概率图模型概率图模型是一种用于描述随机变量之间依赖关系的图模型。
它将概率分布表示为一个图,其中节点代表随机变量,边表示变量之间的依赖关系。
常见的概率图模型有贝叶斯网络和马尔可夫随机场等。
利用概率图模型可以对复杂的概率分布进行建模,并进行各种推断和预测。
3. Euler ancestral sampling 的原理Euler ancestral sampling 是一种基于概率图模型的采样方法,在给定概率图模型的条件下,生成符合目标分布的样本。
它通过构建马尔可夫链蒙特卡洛采样算法,在模型中进行状态转移,最终生成样本。
具体而言,Euler ancestral sampling 的过程如下:- 初始化:随机选择一个初始状态,作为当前样本。
- 遗传变异:根据概率图模型中的条件概率,对当前样本进行变异,得到新的样本。
- 选择操作:根据变异后的样本与目标概率分布之间的距离评估,选择保留样本或丢弃样本。
- 迭代操作:通过遗传变异和选择操作,循环进行,直到满足采样需求的样本数量。
4. Euler ancestral sampling 的应用Euler ancestral sampling 在许多领域都得到了广泛的应用:- 受限玻尔兹曼机(RBM)的采样:RBM 是一种无向概率图模型,常用于降维、特征选择和生成模型。
Early maturation processes in coal.Part 2:Reactive dynamics simulations using the ReaxFF reactive force field on Morwell Brown coal structuresElodie Salmon a ,Adri C.T.van Duin b ,François Lorant a ,Paul-Marie Marquaire c ,William A.Goddard III d,*aInstitut Français du Pétrole,BP 311,92506Rueil-Malmaison Cedex,FrancebDepartment of Mechanical and Nuclear Engineering,Penn State University,University Park,PA 16802,USA cDépartement de Chimie Physique des Réactions (DCPR),Nancy-Université,CNRS 1rue Grandville,BP 20451,F-54001Nancy,France dMaterials and Process Simulation Center (MC 139-74),California Institute of Technology,Pasadena,CA 91125,USAa r t i c l e i n f o Article history:Received 20April 2009Received in revised form 31August 2009Accepted 2September 2009Available online 6September 2009a b s t r a c tThis paper reports reactive dynamics (RD)simulations of a macro-model of Morwell Brown coal using the ReaxFF reactive force field.We find that these reactive MD simulations successfully reproduce thermal decomposition processes of defunctionalization,depolymerization and rearrangement of the residual structure observed in various experimental studies.For example,our simulations indicate that the decar-boxylation and dehydroxylation of the lignin side chain of the Morwell model involves the formation of double bonds conjugated with the aromatic rings.The process of defunctionalization of the methoxy functions involving the formation of phenolic structures in the residue has been confirmed.We also observe that gaseous hydrocarbons are generated by cleavage of C–C bonds of the lignin side chain.The success in using ReaxFF RD to describe the molecular processes underlying the kinetics in pyrolysis of this model of coal plus the success of a similar previous study on the algaenan of Botryococcus braunii race L biopolymer model of kerogens suggests that such computation can be useful in providing molec-ular based kinetic models for other pyrolysis processes underlying the organic transformations in sedi-mentary materials.Ó2009Elsevier Ltd.All rights reserved.1.IntroductionThere is great interest in determining a kinetic model to de-scribe oil and gas generation from the thermal decomposition of fossil organic matter and of shale and coal.Such information can be invaluable in assessing migration pathways of these precursors evolving to produce oil and gas that would help to locate the opti-mum locations for extraction.This has led to a number of experi-mental studies (Huck and Karweil,1955;Karweil,1955;Vassoevich et al.,1969;Lopatin,1971;Waples,1980)to under-stand and estimate the chemical processes and the kinetics of oil and gas generation.However,it is difficult to reproduce the low temperature,high pressure conditions in practical laboratory experiments.This has made it imperative to derive computational models to predict oil generation.One of the earliest such model by Pitt (1962)consists of a set of global reactions assumed to occur simultaneously and assumed to be independent of each other.Ki-netic equations of all prototypical reactions were then definedexperimentally for each source rock.This allowed the bulk rate of oil and gas generation for a source rock to be accounted -ter,experimental thermal decomposition studies of model com-pounds and structural models of kerogen and coal were used to obtain a molecular level description of the formation of petroleum (Solomon et al.,1988;Savage and Klein,1989;Freund,1992;Payne and Ortoleva,2002;Kelemen et al.,2004;Freund et al.,2007).In addition,Solomon et al.(1988)used a structural model of coal to reproduce the devolatilization of coal observed in pyrolysis exper-iments.Other approaches have simulated the defunctionalization processes generating gas compounds and the bond breaking/cross linking processes involved in tar formation.These molecular mod-els explain defunctionalization of coal by combining the functional group composition of the coal with kinetic coefficients of each gas generated.Alternatively,the formation of the tar has been de-scribed using a statistical distribution of kinetically constrained,one step ter,statistical models of the transformation time for thermal decomposition and pyrolysis and natural evolu-tion of sedimentary organic matter were proposed for asphalthene (Savage and Klein,1989),lignite (Payne and Ortoleva,2002)and kerogen (Freund,1992;Kelemen et al.,2004;Freund et al.,2007).These previous approaches to developing chemical models have necessarily used a limited number of chemical steps involved in such pyrolysis processes,which necessarily limits the accuracy of0146-6380/$-see front matter Ó2009Elsevier Ltd.All rights reserved.doi:10.1016/geochem.2009.09.001*Corresponding author.Address:Materials and Process Simulation Center (MC 139-74),California Institute of Technology,1200East California Blvd.,Pasadena,CA 91125,USA.Tel.:+16263952731;fax:+16265850918.E-mail addresses:wag@ ,shirley@ (W.A.God-dard).Organic Geochemistry 40(2009)1195–1209Contents lists available at ScienceDirectOrganic Geochemistryjournal homepage:www.elsevie r.c o m /l o c a te /o r g g e o c h emthe predictions from these models.For this reason,we embarked on a collaborative experimental and theory-computational program to provide a more accurate molecular based model of the processes.Thefirst phase of this program reported the results of both experiment(Salmon et al.,2009a)and ReaxFF reactive dynamics computational modeling(Salmon et al.,2009b)on ther-mal decomposition process in algaenan of Botryococcus braunii race L.This current paper is the theory part of a second series of similar experimental and theory-computational studies,but now on lig-nite,a model system for coal.As in Salmon et al.(2009b)we use the ReaxFF reactive force field(van Duin et al.,2001)in reactive dynamics(RD)simulations for realistic models of lignite.[For other reactive forcefield ap-proaches to organic geochemical polymers see Stoliarov et al. (2004)and Yin et al.(2006).]The ReaxFF(van Duin et al.,2001) reactive forcefield has been demonstrated to retain nearly the accuracy of the QM calculations from which it is derived while en-abling RD at computational costs nearly as low as for ordinary non-reactive forcefields.The accuracy and efficacy of ReaxFF RD has been demonstrated for a wide variety of materials including tran-sition metal oxides and alloys,homogenous and heterogeneous molecular catalysts,and semiconductor oxides interactions(e.g., van Duin and Sinninghe Damsté,2003;Strachan et al.,2003; Chenoweth et al.,2005,2008;Chen et al.,2005;van Duin et al., 2005;Han et al.,2005;Buehler et al.,2006;Goddard et al., 2006a,b;Ludwig et al.,2006;Leininger et al.,2008).ReaxFF RD has been applied to simulations of105–106million atoms(using massively parallel computers)and with a single CPU is quite prac-tical for simulations with up to4000atoms per periodic cell(Nom-ura et al.,2007;Nakano et al.,2008).The results presented here used just a single CPU.Our previous ReaxFF RD study of the ther-mal decomposition of an aliphatic biopolymer of algaenan of B. braunii race L led to excellent comparison with experiment(Sal-mon et al.,2009a)as does the current application to lignite.The present paper uses ReaxFF RD to describe the initial steps of the thermal decomposition of the kerogen aromatic geopolymer. These simulations aim to predict the molecular decomposition of the Morwell brown coal model defined in parallel experimental study by Salmon et al.(2009c).Thefirst section describes the sim-ulation system,a molecular structure containing500atoms made up from representatives of the structural units of the coal model (e.g.,guaiacyl,syringyl and p-hydroxyl units).This allows the ther-mal decomposition processes of these specific structures and func-tional groups to be described simultaneously.Based on these results we analyze the reproducibility of the thermal decomposi-tion mechanism as a function of the initial spatial positions of the molecules.Then we present the ReaxFF RD results for a macro-model containing2692atoms of Morwell coal.Wefind that the results agree qualitatively with experimental data from the lit-erature,validating the methodology.2.Modeling method2.1.Selection of initial molecular modelsThe Morwell coal is lignite enriched in aromatic chemical struc-tures.This structure,which is similar to kerogen,is selected for the present study.A molecular model of the immature lignite samples was proposed in Salmon et al.(2009c).This model,displayed in Fig.1,was con-strained by(1)experimental characterization(elemental analysis,1196 E.Salmon et al./Organic Geochemistry40(2009)1195–1209Infrared spectra,modern1-and2-D Nuclear Magnetic Resonance)of the brown coal sample from Morwell Open Cut(Gippsland Forma-tion,Australia)and(2)the theoretical transformation of an angio-spermous lignin structure found in the literature(Nimz,1974).To set up the simulation procedure for this type of complex organic matter,wefirst selected small molecular models of 24–33atoms to represent specific substructures of the lignite macro-model(Fig.1).The lignite structure is composed of various aromatic units containing a p-hydroxyl aromatic ring substituted by a C1–C6aliphatic side chain and oxygenated functional groups (methoxy,carboxyl or carbonyl functional groups).Hence,the structural models selected were representative of the different aro-matic units observed in the macro-models of lignite(Fig.2B–F).2.2.Molecular dynamics modeling using the reactive forcefield, ReaxFFA brief description of the ReaxFF reactive forcefield and of the simulation procedure(Fig.3)is presented below;a more detailed description is available in Salmon et al.(2009b).E.Salmon et al./Organic Geochemistry40(2009)1195–12091197For the present study,the simulations aimed at reproducing the experimental results of off line pyrolysis of the Morwell lignite per-formed by Salmon et al.(2009c).To initiate the simulations a peri-odic cubic box was built containing the molecular models described in the previous section.Each box contained up to 15identical functional models,initially at a low density of 0.1kg/dm 3,resulting in system sizes of around 500atoms.We also built one macro-model of lignite containing 2692atoms at low density.Subsequently,a low temperature reactive dynamics (for functional models at 2K and the macro-model at 50K)was performed on these initial low density configurations.Thereafter,the system was equilibrated at 300K using NVT-dynamics (2.5ps =picosec-onds)and a Berendsen thermostat (Berendsen et al.,1984).This system was then compressed to the experimental solid density at room temperature of d =1.4g dm À3by means of re-scaling the cell parameters during a 1.25ps,MD-simulation at T =300K.Then the system was equilibrated at a pressure of 1bar and a temperature of 750K using NPT-dynamics (25ps)with the Berendsen thermostat and barostat.This causes an expansion of the box size to a density of about 0.7–0.8kg/dm 3for the functional models and of 0.68kg/dm 3for the macro-model (Table 1).Finally,we performed heat up simulations from 300–2500K at rates of 88,44and 22K/ps for the functional models (Fig.4)to determine the onset tempera-ture of thermal decomposition at the picosecond time scale of our simulations.For the macro-model A the onset temperature of ther-mal decomposition was determined by heat up simulation per-formed from 700–3100K for 40ps corresponding to a rate of 60K/ps.We observed that the thermal decomposition of functional models began between 1700and 2500K and that of the macro-model at around 1200K.To assess the kinetics of the thermal decomposition reactions,we also performed constant temperature molecular dynamics simulations on each functional models for 50ps at T =2000,2100and 2200K.The macro-model was isother-mally heated as well,for 40ps at 1000,1200,1400,1600,1800and 2000K.The time scale of the simulation (50picoseconds)is many mag-nitudes lower than that employed in the experiments (9hours in Salmon et al.,2009c ).Thus,for the numerical simulations we arti-ficially increased the temperature to be in the range 500–2200K,allowing the chemical reactions to occur within a few picoseconds,but hopefully with similar mechanism to laboratory experiments which take hours at much lower temperature (i.e.,473–573K).We previously demonstrated that despite these time and temper-ature differences between simulation and experiment,we obtained good qualitative agreement between the initial reaction products on aliphatic structure (Salmon et al.,2009b ).3.Simulations on the thermal decomposition of the lignite geopolymer3.1.Thermal decomposition of functional models of ligniteFig.5gives an overview of the kinetics of degradation of each functional model for NVT-dynamic simulations at 2000,2100and 2200K for 50ps.As expected the chemical systems tend to be more reactive at higher temperature.We do reversible reactions (noted R in Fig.5)involving either addition reactions or reverse dismutations involving hydrogen exchanges.For example:ðB ÞC 12H 16O 2þC 8H 8O 2¢C 12H 17O 12þC 8H 7O 2ðC ÞC 10H 13O 5þC 10H 11O 5¢2C 10H 12O 5ðD ÞC 11H 16O 3þCH 3¢C 11H 15O 3þCH 4ðE Þ2C 9H 10O 2¢C 18H 20O 4¢C 9H 11O 2þC 9H 9O 2ðF Þ2C 10H 12O 2¢C 20H 24O 4The aliphatic cycle (F),methoxy (D)and acid (C)functional models decompose faster than the hydroxyl (B)and the ketone (E)models.The acid (C)model leads to earlier initiation reactions compared to the aliphatic cycle (F)than the methoxy (D)models.Table 1Simulation conditions for constant temperature NVT RD simulations and the final results.Models Numbers Volume (Å3)Pressure (Mpa)Initial density (kg/dm 3)Final density (kg/dm 3)Nature Structures Number atoms Number cases Macro-model A Lignite 269215536010 1.430.68Functional modelB Hydroxyl 3315655010 1.430.80C Acid2718900910 1.430.70D Methoxy 3017703710 1.430.79E Ketone2124698510 1.430.86FAliphatic cycle24217159101.430.801198 E.Salmon et al./Organic Geochemistry 40(2009)1195–1209In Tables 2and 3,the products of decomposition are partitioned into four classes of compounds.The aromatic compounds contain aromatic rings and larger struc-tures that have no more carbons than their respective initial function models.Those compounds represent residual struc-tures that are resistant to thermal stress.The alkyl compounds are structural moieties with less than four carbons and derived from the decomposition of the aliphatic side chains.This fraction is composed of oxygenated compounds like formaldehyde,ethanol,propanol and small hydrocarbons like butane,propene,ethene,methyl radical and methane.Other compounds represent inorganic compounds like water,carbon dioxide or H 2.Condensed compounds in Table 3,contain more than the ten car-bons of the initial acid (C 10H 12O 5)and aliphatic cycle functional models (C 10H 12O 2).The first main steps deduced from the reaction products are dis-played in Figs.6–8.Those reactions begin with an initiation reac-tion followed by beta-scission decomposition and/or methathesis (H transfer)with the reactant.For each initiation the bond dissoci-ation energy (BDE)proposed by Luo (2003)is given indicating the strength of the bond that is cleaved and so giving an idea of the occurrence of each reaction.For all the functional models we ob-serve decomposition of the aliphatic side chain and of other func-tional groups,but no aromatic ring is degradated,as expected.The specific decomposition of the aliphatic cycle functional model,dis-played as reaction F in Fig.8,shows that depolymerization and condensation reactions may evolve simultaneously.The generation of unstable biradicals led to the strong rearrangements in the car-bon skeleton structure like those displayed in Fig.9.The occur-rence of high molecular weight compounds resulted from addition or termination reactions.However those reactions are less likely to occur when the aliphatic cycle is substituted by functional groups or connected to other aromatic units or side chains,as is common in lignite macro-structures.For all functional models,we observed radicals generated via a depolymerization of the ali-phatic side chain.In terms of defunctionalization,we observed dehydroxylation of both alkyl and aryl hydroxyl,i.e.,reaction B3and C (Figs.6and 7),releasing both hydroxyl radicals and water.Sometimes,b -hydroxyl functions were decomposed into such oxy-genated compounds as formaldehyde,ethanol and propanol.Decarboxylations releasing carbon dioxide were obtained by the decomposition of the acid functional model C (Fig.7).It is notice-able that the ketone group (reaction E in Fig.7)exhibits a high resistance to thermal stress.This stability is increased by the ben-zyl position of the ketone group in the functional model.Reaction D reports the demethoxylation process generating methyl and phenolic radicals.Thereafter,hydrogenation reactions were at the origin of methane and of the formation of catechol moieties.3.2.Reproducibility of functional model resultsFor each functional model,as defined in Fig.2,we constructed periodic boxes containing 15–24duplicates,depending on the510152025102030405060O H OH O H OOH C H 32100K 8/182000K 3/182200K 10/185101520250102030405060O HOC H 3C H 32100K 7/242000K 0/242200K 4/240510152025102030405060OH O HC H 3O HC H 32100K 0/152000K 1/152200K 7/15510152025O HOH H 3COCH 3C H 32100K 7/172000K 2/172200K 15/175101520250102030405060102030405060Time (ps)Time (ps)OH OH 2100K 15/212000K 8/212200K 18/21CDBEFRRRRRRRRRRRRN u m b e r o f m o l e c u l e sN u m b e r o f m o l e c u l e sN u m b e r o f m o l e c u l e sN u m b e r o f m o l e c u l e sN u m b e r o f m o l e c u l e sFig.5.Thermal of decomposition of functional models for NVT RD simulations at 2000,2100and 2200K.E.Salmon et al./Organic Geochemistry 40(2009)1195–12091199model size(Table1).For each of these boxes thermal decomposi-tion simulations were performed starting fromfive independent initial configurations,thus allowing us to evaluate the reproduc-ibility of the observed chemical events.Results of these reproduc-ibility experiments are displayed in Fig.10for the decomposition and the total production of the hydroxyl functional model at three temperatures(2000,2100and2200K).Similar trends were observed for both the decomposition and the products generation at2000and2100K.At these tempera-tures,respectively up to4and7initial models are decomposed generating up to10and11new molecules.At2200K,the reaction rate is higher than at lower temperature.About5to10hydroxyl functional units are decomposed into11–21new molecules.A de-tailed list of compounds generated after50ps at2000,2100and 2200K,also displayed in Fig.8,indicates that the overall reaction always creates the same products whatever the temperature.At 2000and2100K,some compounds are formed by recombination or addition reactions,either between two initial reactantsTable2Table3List of compounds obtained from thermal decomposition of functional models bearing carboxyl group and an aliphatic cycle at2000,2100and2200K during50ps of NVT RD1200 E.Salmon et al./Organic Geochemistry40(2009)1195–1209(C24H36O6),or between an initial reactant and an intermediate product,or between two intermediate products(C24H35O5, C18H20O4,C14H22O2,C13H21O4).These MD results establish molecu-lar balances for the early decomposition of the hydroxyl structure (Table4).We found thatfive bonds are especially weak in this structure,generating butyl,methyl,hydroxyl,methylhydroxyl rad-icals and propene molecules.This means that the dispersion of products observed previously in Fig.10,is controlled by the prob-ability of occurrence of the reaction as a function of the initial spa-tial conformation of the system.Detailed analysis of products formed after50ps shows that similar early reactions occur,irre-spective of the initial spatial conformation.From these reproducibility experiments,we conclude that the RD simulations performed here provide qualitative descriptions of the thermal decomposition of the organic structures studied. Quantitative results would require statistical analysis of reactions, which requires larger systems or many independent simulations for small systems.Results provided hereafter were all obtained using one spatial conformation and multiple temperatures,so they are restricted to qualitative analysis.3.3.Thermal decomposition of the macro-models of ligniteWe simulated the decomposition of the lignite macro-model A with a heat up ramp of60K/ps.Fig.11displays the formation of the main products generated during this simulation.Thefirst products formed are carbon dioxide and concomitant higher molecular weight compounds having more than three carbon atoms.Formation of CO2starts at700K after only$.10ps and higher molecular weight compounds are generated starting from 1500K at12.5ps.Carbon monoxide is observed at t=18ps corre-sponding to a temperature of$1800K.At about2200K,low molecular weight hydrocarbons,C1–C2oxygenated compounds and water appear.At the end of the simulation,4molecules of water,29molecules of C1–C3hydrocarbons and29molecules of C1–C3oxygenated compounds were generated.Thefirst hydrocar-bon molecules(methane and ethylene)appear after14ps ($1500K)followed by acetylene(C2H2)at33ps($3000K)due to the high temperature.Di-hydrogen(H2)is generated at tem-peratures higher than2500K.Molecular C1–C4oxygenated com-pounds formed at3209K/40ps contain methanol(CH4O)and formaldehyde(CH2O).Analysis of the molecular compounds formed at different time steps,listed in Table5,indicates that high molecular weight spe-cies at lower temperature(61947K)are mainly composed of C30+aromatic structures.Beyond2000K the proportion of C40Àcompounds increases.Since high temperatures favor decomposi-tion rather than addition and recombination,no additional C100+ high molecular weigh structures are observed beyond3000K.Un-der our MD simulation conditions,oxygenated compounds inE.Salmon et al./Organic Geochemistry40(2009)1195–12091201C1–C6are formed before C1–C4hydrocarbons.More CO2and methyl radicals are generated compared to CO and methane.We observe the formation of hydroxyl radicals at1947K -ter on(24ps),water appears in the system.In addition to ramped heating runs,we performed constant temperature RD simulations between500and2000K for79ps.It seemed that no reaction happened during the simulation at 500K/79ps.But closer analysis of the chemical system during the simulation shows some structural rearrangement does occur at this temperature.Indeed,two molecules of CO2are released in the system and then reincorporated into the main structure by an addition process.A few kerogen decomposition reactions gener-ate CO at1600,1800and2000K.Fig.12displays the overall forma-tion of CO2as a function of time and temperature.We observe that the defunctionalization process is dominant compared to the reac-tions of CO2.The compound classes observed at50ps in the simulations at 500,1000,1200,1400,1600,1800and2000K are displayed in pounds are lumped according to mass fractions fre-quently used in experimental petroleum studies.We observed that C100+compounds are dominant in the system.At1800K,these compounds represent62wt%of the mass of the initial structure but at2000K only29wt%of C100+compounds remain in the system.The main products formed during RD simulation are C14–C100 compounds that may be ascribed to heavy oxygenated compounds1202 E.Salmon et al./Organic Geochemistry40(2009)1195–1209E.Salmon et al./Organic Geochemistry40(2009)1195–12091203experimentally observed in the C 14+fraction extracted from the pyrolysis residue.At 1600K about as many C 6–C 14as C 1–C 6com-pounds are formed,$3–5wt%.At 2000K,C 1–C 6oxygenated com-pounds make up 3wt%of the mass of the structure,but only 0.5wt%of light hydrocarbons are generated.Formation of inorganic compounds such as CO 2,CO and water,increases with temperature to about 9wt%at 2000K.Predicted chemical structures at the end of the RD simulations at 1600,1800and 2000K show an increase in aromaticity.We also observed an increase in double bonds on the side chains conjugated with aromatic rings.Most of those dou-ble bonds are in the trans conformation.Additional ring structures are also observed in the final system configurations.Fig.14gives an overview of these ring structures.3.4.Discussion:comparison of experimental and reactive dynamics resultsOur RD simulations on small systems (<500atoms)reproduce the processes related to the formation of low molecular weight products.As observed in experiments,the RD finds that CO 2is gen-erated by defunctionalization of carboxylic groups.Initially,we thought that ketone functional groups might be responsible for CO or CO 2release;however the RD do not show any thermal decomposition of ketone functional groups.Instead we find that methyl radicals are generated by cleavage of C–C bonds on the ali-phatic side chain or by cleavage of C–O bonds of methoxy groups.Defunctionalization of the methoxy group by release of methyl radical has been proposed by Hatcher and Clifford (1997)based on observations of natural samples and pyrolysis experiments.Subsequently,the methyl radicals may convert into heavier mole-cules by addition to other molecules or radicals or by metathesis and methyl radicals can be transformed into methane.This mech-anism was strongly suggested though artificial maturation studies of Behar and Hatcher (1995)and Salmon et al.(2009c).We find that the RD confirms this mechanism for functional model D bear-ing methoxy groups.Our simulations also showed ethylene to be formed by cleavage of C–C bonds on the aliphatic side chain of the aromatic units.For example,we observe that the naphtheno-aromatic units unsubstituted present in functional models F,are able to generate a large amount of ethylene.However in lignite macro-structures it is likely that those naphtheno-aromatic units are connected to other aromatic units or side chains,which would lower the rate of ethylene generation.RD simulations of the thermal decomposition of functional model B bearing a hydroxyl group by MD show that C–C bonds in a ,b or c position of the hydroxyl group are weaker than C–O bonds involving the hydroxyl groups.Cleavage of the C–C bonds results in the formation of oxygenated compounds such as formal-dehyde,ethanol or propanol.During pyrolysis experiments (Sal-mon et al.,2009c ),these compounds would appear in the NSO fraction,which contain high molecular weight compounds.How-ever the chemical structure of the NSO fraction was not identified by Salmon et al.(2009c)for two reasons:first,the amount NSO fraction recovered by extraction was too low;and second this frac-tion was dried before quantification in order to remove any trace of solvent,which would evaporate low molecular weight compounds associated to this fraction.As such,we cannot directly link the sim-ulations to the experiments for these small oxygenated compounds.Table 4Major reactions found in RD of thermal decomposition of functional models hydroxyl (B)based on the balance of structures recorded during dynamic simulations at 2000,2100and 2200K,50ps.2000K/50ps 2100K/50ps 2200K/50ps Reactant ProductsReactant ProductsReactant Products C 12H 18O 3?C 11H 15O 2+CH 3O C 12H 18O 3?C 12H 18O 3?C 12H 17O 3+HC 11H 15O 2+CH 2O +HC 11H 15O 2+CH 2O +H C 11H 14O 2+CH 2OC 10H 12O 2+CH 3+CH 3O C 10H 12O 2+CH 3+CH 3O C 9H 10O 2+C 3H 6+H 2O C 9H 10O 2+C 3H 6+H 2O C 9H 11O 2+C 3H 6+HO C 8H 10O 2+C 4H 8C 8H 9O 3+C 4H 9C 8H 9O 3+C 4H 9C 8H 9O 3+C 3H 6+CH 3C 8H 9O 3+C 3H 6+CH 3C 8H 8O 2+C 4H 9+OHC 8H 8O 2+C 4H 9+OHC 8H 8O 2+C 4H 9+OHC 8H 6O 2+C 3H 6+CH 4+H 2O0204060801001201401601802000510152025303540Time (ps)510152025303540Time (ps)N u m b e r o f m o l e u c l e s .500100015002000250030003500TotalproductionCO 2H 2O (C 1-C 2) oxygenated compounds H 2(C 1-C 2) hydrocarbons CO Heavy compoundsTemperature (K)T (K)05101520253035404550N u m b e r o f m o l e c u l e s .500100015002000250030003500Temperature (K).H 2CH 4C 2H 4TotalproductionFig.11.Products generated during the thermal decomposition of the macro-model A by NVT simulation under heat up temperature of 60K/ps.1204 E.Salmon et al./Organic Geochemistry 40(2009)1195–1209。