译文Simulation-based optimization for housekeeping in a container transshipment terminal

The growing diversity of disciplines, participants, tasks, tools and events associated with project management at the design and construction stages, the increasing pressure of costing competition and tighter production deadlines, as well as continually increasing quality requirements and the need for technological enhancements, are the driving force of information modeling and numerical simulation in the construction industry. When choosing the most effective investment project in construction, a major problem associated with the actual demand for resources is underestimated. In order to solve this problem in the most effective way, the application programs, covering virtually every phase of the specific construction product development, e.g. planning, design, cost estimation, scheduling, fabrication, construction, maintenance and facility management were developed and supplemented with the calculation of the demand for resources, comparison of alternatives and determination of the duration of all the stages of the project life. Theoretical principles and practical innovative applications of building information modeling and construction process simulation technique, used to determine the most effective alternative of the project by applying the appropriate multiple criteria evaluation methods, are considered in the article.Article Outline1. Introduction2. New concept in design and construction3. BIM as an approach to building design and management4. Computer-aided evaluation system in design and construction5. The development of virtual construction project6. Determining the most effective project variant7. ConclusionReferencesVariability in production is one of the largest factors that negatively impacts construction project performance. A common construction practice to protect production systems from variability is the use ofbuffers (Bf). Construction practitioners and researchers have proposed buffering approaches for different production situations, but these approaches have faced practical limitations in their application. A multiobjective analytic model (MAM) is proposed to develop a graphical solution for the design ofWork-In-Process (WIP) Bf in order to overcome these practical limitations to Bf application, being demonstrated through the scheduling of repetitive building projects. Multiobjective analytic modeling is based on Simulation–Optimization (SO) modeling and Pareto Fronts concepts. Simulation–Optimization framework uses Evolutionary Strategies (ES) as the optimization search approach, which allows for the design of optimum WIP Bf sizes by optimizing different project objectives (e.g., project cost, time and productivity). The framework is tested and validated on two repetitive building projects. The SO framework is then generalized through Pareto Front concepts, allowing for the development of the MAM as nomographs for practical use. The application advantages of the MAM are shown through a project scheduling example. Results demonstrate project performance improvements and a more efficient and practical design of WIP Bf. Additionally, production strategies based on WIP Bf and lean production principles in construction are discussed.Article Outline1. Introduction2. Research objective3. Research methodology4. Describing WIP Bf in repetitive construction processes5. WIP Bf design approach using Simulation–Optimization5.1. Simulation architecture and modeling assumptions5.2. General Simulation–Optimization approach to design WIP Bf5.3. Evolutionary Strategies in optimization problems5.4. WIP Bf optimization using Evolutionary Strategies in simulation approach6. Multiobjective model to design WIP Bf7. Testing and validation of the Simulation–Optimization approach7.1. Project description7.2. Project A7.3. Project B7.4. Discussion of SO testing and validation8. MAM application9. Conclusions10. NotationReferencesEvaluation and use of the standards in of the technical drawings in the final year project Original Research ArticleProcedia - Social and Behavioral SciencesThe use of a virtual building design and construction model for developing an effective project concept in 5D environment Original Research ArticleAutomation in ConstructionSimulation model incorporating genetic algorithms for optimal temporary hoist planning in high-rise building construction Original Research ArticleAutomation in ConstructionResearch highlightsWe propose a model for temporary hoist planning in high-rise building construction. >The model isconstructed with a discrete-event simulation and genetic algorithms. This model uses a simulation toverify various scenarios for vertical transportation. The GAs assists the planner to search for anoptimal scenario in the solution space. It will support hoist planners while preparing optimal plans with minimal time and effort.建筑/建材/工程环境艺术园林设计规划设计方案、景观设计方案绿植施工图选样及定板工作技术问题5,243 articles found for: pub-date > 2000 and tak(((Construction building materials) or (environmental art) or project or planning or design or (garden design) or (landscape design)) and (Plants or construction or drawings sampling or work or technical or problems or fixed or plate)) Edit this search | Save this search | Save as search alert | RSS FeedConstruction / building materials / environmental art project planning and design garden design, landscape designPlants and construction drawings sampling the work of technical problems fixed plateThe economics of native plants in residential landscape designs Original Research Article Landscape and Urban PlanningMultiobjective design of Work-In-Process buffer for scheduling repetitive building projects Original Research ArticleAutomation in ConstructionYard-scale landscape designs can influence environmental quality through effects on habitat, stormwater runoff, and water quality. Native plant gardens may have ecological benefits, and previous research has shown that yards using these plants can be designed in ways that people find attractive. This study examines whether people are willing to pay more for more ecologically benign designs than for a lawn. A contingent choice survey was conducted in southeast Michigan in which people were presented with four different yard designs (three of which included native plants) in three different settings, with different monthly maintenance costs for each design. Respondents were asked to rank their choices of the yards while considering the maintenance costs they were presented. Results suggest that people are willing to pay more for well-designed yards including native plants than for lawns, and that their increased willingness to pay exceeds any increase in costs associated with the native plantings. These results should encourage homeowners, landscape designers, and the landscape plant industry to work with native plants. In this study, people were willing to pay more for designs that present gains for the environment, without government intervention and without social cost.Article Outline1. Introduction2. Measurement of willingness to pay in theory and practice3. Survey design4. Results5. ConclusionAcknowledgementsAppendix A. Calculation of willingness to pay (WTP)ReferencesVitaeStudy of a historical garden soil at the Grand-Pressigny site (Indre-et-Loire, France): evidence of landscape management Original Research ArticleJournal of Cultural HeritageGarden archaeology is a new discipline in France, which mainly focuses on technical aspects of garden creation. Excavations reveal complex stratigraphic sequences and show that soils are strongly influenced by human activities linked to cultivation, including for aesthetic purposes. The objective of the research was firstly to better understand and explain the complex archaeological deposits of a historical garden, using various techniques such as soil micromorphology, image analysis and soil chemistry. The second objective was to show the composition of remains from one garden. Samples were taken from LeGrand-Pressigny site in Touraine, a French garden dating from the XVIth–XIXth centuries. The analyses of different anthropogenic levels in thin sections, the measurements of carbonate, phosphorus, carbon organic contents and soil porosity (image analysis) provided accurate information about the presence of an earlier garden made up of imported soil. The results also identified spatial changes over time. This study suggests an interesting approach to understanding soil care by early human communities and cancontribute to garden restoration projects considering the technical construction of these sites and historical techniques.Article Outline1. Introduction2. Study site and methods2.1. Study area2.2. Field data and sampling2.2.1. The natural soil2.2.2. The anthropic deposits2.3. Methods3. Results3.1. Micromorphological descriptions3.2. Analytical data3.2.1. Particle size distribution and chemical analyses3.3. Image analysis4. Interpretation and discussion4.1. Interpretation of the characteristics of natural subsoil4.2. Interpretation of the characteristics of anthropic deposits4.3. Imported soil as garden remains5. ConclusionAcknowledgementsReferencesRisk analysis in fixed-price design–build construction projects Original Research Article Building and EnvironmentA case study on the management of the development of a large-scale power plant project in East Asia based on design-build arrangement Original Research Article International Journal of Project ManagementTeaching construction project management with BIM support: Experience and lessons learned Original Research ArticleAutomation in ConstructionEnvironmental factors and work performance of project managers in the construction industry Original Research ArticleInternational Journal of Project Management。

使用MOEA的城市设计物理环境多目标寻优方法袁磊;冯锦滔;许雪松【摘要】This paper focuses on solving the ubiquitous disjunction between the performance evaluation and morphological design optimization for urban design with multi-physical criteria, and proposes an integrated and optimized design method for this purpose. The article explains the basic principles of this method, which is for both the design optimization and environmental performance optimization to be managed between regional planning and urban design via a two-stage workflow. The core of the method is a simulation-based optimizing engine using the multi-objective evolutionary algorithm (MOEA) to drive the optimization process and thereby achieve integrated prediction and optimization processes at the process level and multi-objective performance optimization simultaneously at the factor level. Using some examples, the article shows how the method works in two aspects of regional planning and urban design, and validates the effectiveness of the method and its efficiency in optimizing designs.%文章聚焦于解决城市设计中多种物理环境性能评价和形态优化设计之间普遍存在的脱节问题,提出了一种整合优化的设计方法.文章讲解了该方法的基本原理,是通过两阶段型的工作框架将环境性能优化的目标和数据在区域规划与城市设计的上下层次间实现传递.该方法的核心是基于模拟的优化引擎,使用多目标进化算法(MOEA)驱动多目标寻优过程,在过程层面实现了预测与优化的过程合一,在要素层面实现了多种性能共同优化的效果.文章通过案例展示了该方法在区域规划和城市设计两个层次的设计工作实验,验证了该方法的有效性和优化设计的效率.【期刊名称】《南方建筑》【年(卷),期】2018(000)002【总页数】5页(P41-45)【关键词】城市设计;环境性能;多目标优化算法;数值模拟;自动优化设计【作者】袁磊;冯锦滔;许雪松【作者单位】深圳大学建筑与城市规划学院;深圳大学建筑设计研究院有限公司;深圳大学建筑设计研究院有限公司【正文语种】中文【中图分类】TU11;TU-023引言城市作为人类建成环境的密集区域，其对人类生活环境和全球范围自然生态的影响殊为重大。

基于模型参考自适应的永磁同步电机速度观测器中PI参数调节方法刘小俊;张广明;梅磊;王德明【摘要】永磁同步电机(PMSM)在有感控制方案中需安装编码器或霍尔传感器,增加了系统的设计成本,因此,研究PMSM的无感控制方案就显得有必要性.随着现代控制理论的发展,无传感器技术也日益发展.以磁场定向控制为控制策略,以模型参考自适应理论为基础,设计了一种速度观测器.侧重用现代控制理论知识分析了观测器的稳定性,并用传统控制理论知识分析了一种新的观测器中PI调节器参数整定方法.这种方法具有很强的适应性和移植性.最后,验证了这种方法的准确性和可行性.【期刊名称】《电机与控制应用》【年(卷),期】2016(043)007【总页数】6页(P1-6)【关键词】永磁同步电机;无感控制;模型参考自适应系统;稳定性;参数整定【作者】刘小俊;张广明;梅磊;王德明【作者单位】南京工业大学电气工程与控制科学学院,江苏南京210009;南京工业大学电气工程与控制科学学院,江苏南京210009;南京工业大学电气工程与控制科学学院,江苏南京210009;南京工业大学电气工程与控制科学学院,江苏南京210009【正文语种】中文【中图分类】TM341近年来，随着电力电子技术的发展，交流伺服系统越来越受到人们的关注。

其中永磁同步电机(Permanent Magnet Synchronous Motor， PMSM)具有体积小、效率高、功率密度高等特点，在交流伺服系统中占据着重要的地位，在高性能驱动系统中得到了广泛的应用[1-3]。

目前，PMSM的驱动通常使用磁场定向控制(Field Oriented Control， FOC)或者直接转矩控制(Direct Torque Control，DTC)。

但是，无论是针对哪种控制策略，都需要用到转速和转子位置角信息。

当然，这两个参数知道其中一个即可。

目前，对于这两个参数的获取有两种方案，即有传感器和无传感器。

A realistic approach for reduction of energy losses in low voltage distribution networkabstractThis paper proposes reduction of energy losses in low voltage distribution network using Lab VIEW as simulation tool. It suggests a methodology for balancing load in all three phases by predicting and controlling current unbalance in three phase distribution systems by node reconfiguration solution for typical Indian scenario. A fuzzy logic based load balancing technique along with optimization oriented expert system for implementing the load changing decision is proposed. The input is the total phase current for each of the three phases. The average unbalance per phase is calculated and checked against threshold value. If the average unbalance per phase is below threshold value, the system is balanced. Otherwise, it goes for the fuzzy logic based load balancing. The output from the fuzzy logic based load balancing is the value of load to be changed for each phase. A negative value indicates that the specific phase is less loaded and should receive the load, while a positive value indicates that the specific phase is surplus load and should release that amount of load. The load change configuration is the input to the expert system which suggests optimal shifting of the specific number of load points, i.e., the consumers.1. IntroductionAmong three functional areas of electrical utility namely, generation, transmission and distribution, the distribution sector needs more attention as it is very difficult to standardize due to its complexity. Transmission and distribution losses in India have been consistently on the higher side in the range of 21–23%. Out of these losses, 19% is at distribution level in which 14% is contributed by technical losses. This is due to inadequate investments for system improvement work. To reduce technical losses, the important parameters are inadequate reactive compensation, unbalance of current and voltage drops in the system. There are two main distribution network lines namely, primary distribution lines (33 kV/22 kV/11 kV) and secondary distribution lines (415 V line voltage). Primary distribution lines are feeding HT consumers and are regularized by insisting the consumers to maintain power factor of 0.9 and above and their loads in all three phases is mostly balanced. The energy loss control becomes a critical task in secondary distribution network due to the very complex nature of the network.Distribution Transformer caters to the needs of varying consumers namely Domestic, Commercial, Industrial, Public lighting, Agricultural, etc. Nature of load also varies as single phase load and three phase load. The system is dynamic and ever expanding. It requires fast response to changes in load demand, component failures and supply outages. Successful analysis of load data at the distribution level requiresprocedures different from those typically in use at the transmission system level. Several researchers have proposed methods for node reconfiguration in primary distribution network [1–11]. Two types of switches used in primary distribution systems are normally closed switches (sectionalizing switches) and normally open switches (tie switches). Those two types of switches are designed for both protection and configuration management and by altering the open/ closed status of switches loss reduction and optimization of primary distribution network can be achieved. Siti et al. [12] discussed reconfiguration algorithms in secondary distribution network with load connections done via a switching matrix with triacs and hence costly alternative for developing countries. Much work needs to be done in the secondary distribution network where lack of information is an inherent characteristic. For example in most of the developing countries (India, China, Brazil, etc.) the utilities charge the consumers based on their monthly electric energy consumption. It does not reflect the day behaviour of energy consumption and such data are insufficient for distribution system analysis.Conventionally, to reduce the unbalance current in a feeder the load connections are changed manually after field measurement and software analysis. Although this process can improve the phase current unbalance, this strategy is more time consuming and erroneous. The more scientific process of node reconfiguration of LV network which involves thearrangement of loads or transfer of load from heavily loaded area to the less loaded area is needed. This paper focuses on this objective. In the first stage, the energy meter reading from secondary of Distribution Transformer is downloaded and is applied as input to Lab-VIEW based distribution simulation package to study the effects of daily load patterns of a typical low voltage network (secondary distribution network). The next stage is to develop an intelligent model capable of estimating the load unbalance on a low voltage network in any hour of day and suggesting node reconfiguration to balance the currents in all three phases.Objectives are to:Study the daily load pattern of low voltage network of Distribution Transformer by using Lab VIEW.Study the unbalance of current in all three phases and power factor compensation in individual phases.Develop distribution simulation package.The distribution simulation package contains fuzzy logic based load balancing technique and fuzzy expert system to shift the number of consumers from over loaded phase to under loaded phase.2. Existing systemIn the existing system of distribution network, the energymeters are provided for energy accounting, but there is no means of sensingunbalance currents, voltage unbalance and power factor correction requirement for continuous 24 h in three phases of LT feeder. In other words, instantaneous load curves, voltage curves, energy curves and power factor curves for individual three phases are not available for monitoring, analyzing and controlling the LV network. The individual phase of Distribution Transformer could be monitored only by taking reading whenever required and if there is unequal distribution of load in three phases, the consumer loads are shifted from overloaded phase to under loaded phase of distribution LT feeder by the field staff in charge of the Distribution Transformer. There is no scientific methodology at present.3. Proposed systemIn the proposed system, Lab VIEW is used as software simulation tool [13]. In the existing system of distribution network, the Distribution Transformers are fixed with energy meters in the Secondary of the Distribution Transformer and energy meter readings can be downloaded with Common Meter Reading Instrument (CMRI instrument). The energy meter reading includes VI profile and it can be used for the power measurement.4. Monitoring parametersThe phase voltages and the line currents of all three phases are available every half an hour and the voltage curve and load curve are obtained fromthese values. The active, the reactive and the apparent power are computed from these quantities after the phase angle is determined. The following parameters are plotted:1. Individual phase voltage.2. Individual phase current.3. Individual phase active power.4. Individual phase reactive power.5. Individual phase apparent power.6. Individual phase power factor.With the above concepts, the front panel and block diagram are developed for unbalanced three phase loads by downloading the VI profile from energy meter installed in the Distribution Transformer and simulating the setup using practical values. From the actual values obtained load unbalance is predicted using fuzzy logic and node reconfiguration is suggested using expert system.The Lab VIEW front panel displays the VI profile on a particular date with power and energy measurement as in Table 1. The Lab VIEW reads the VI profile and computes the real power, reactive power, apparent power and energy, kWh.4.1. Prediction of current unbalanceThe maximum current consumption in each phase is IRmax, IYmax, and IBmax. The optimum current (Iopt) is given in the following equation:()3max max max B Y R opt I I I I ++=The difference between opt I and m ax R I is then determined. Similarly thedifference between opt I and max Y I , opt I and max B I is computed. If thedifference is positive then that phase is considered as overloaded and if the difference is negative then that phase is considered to be under loaded. If the difference is within the threshold value, then that load is perfectly balanced.To balance the current in three phases, if the difference between opt I and m ax R I is less than threshold value then that phase is left as such.Otherwise, if the difference is greater than threshold value, some of the consumers are suggested reconfiguration from overloaded phase to under loaded phase using expert system.5. Fuzzy based load balancingA fuzzy logic based load balancing technique is proposed along with combinatorial optimization oriented expert system for implementing the load changing decision. The flowchart of the proposed system is shown in Fig. 1. Here the input is the total phase current for each of the three phases. Typical loads on low voltage networks are stochastic by nature. However it has been ensured that there is similarity in stochastic nature throughout the day as seen from load graph of Distribution Transformer as shown in Fig. 6. It has been verified that if R phase is overloaded followed by Y phase and thenB phase the same load pattern continuesthroughout the day.The average unbalance per phase is calculated as (IRmax _ Iopt) for R phase, (IYmax _ Iopt) for Y phase and (IBmax _ Iopt) for B phase and is checked against a threshold value (allowed unbalance current) of 10 A. If the average unbalance per phase is below 10 A, it can be assumed that the system is more or less balanced and discard any further load balancing. Otherwise, it goes for the fuzzy logic based load balancing. The output from the fuzzy logic based load-balancing step is the load change values for each phase.This load change configuration is the input to the expert system, which tries to optimally suggest shifting of specific number of load points. However, sometimes the expert system may not be able to execute the exact amount of load change as directed by the fuzzy step. This is because the actual load points for any phase might not result in a combination which sums up to the exact change value indicated by the fuzzy controller however optimization is achieved because of balancing attempted during peak hours of the day of the load graph.5.1. Fuzzy controller: input and outputTo design the fuzzy controller, at first the input and output variables are to be designed. For the load balancing purpose, the inputs selected are ‘phase current’ i.e., the individual phase current for each of the three phases and optimum current required and the output as ‘change’, i.e., thechange of load (positive or negative) to be made for each phase. For the input variable, Table 2 and Fig. 2 show the fuzzy nomenclature and the triangular fuzzy membership functions. And for the output variable, Table 3 shows the fuzzy nomenclature and Fig. 3 the corresponding triangular fuzzy membership functions.The IF-THEN fuzzy rule set governing the input and output variable is described in Table 4.5.2. Fuzzy expert systemA fuzzy expert system is an expert system that uses a collection of fuzzy membership functions and rules, instead of Boolean logic, to reason out data. The rules in a fuzzy expert system are usually of a form similar to the following:If x is low and y is high then z = mediumwhere x and y are input variables (names for known data values), z is an output variable (a name for a data value to be computed), low is a membership function (fuzzy subset) defined on x, high is a membership function defined on y, and medium is a membership function defined on z .The antecedent (the rule’s premise) describes to what degree the rule applies, while the conclusion (the rule’s consequent) assigns a membership function to each of one or more output variables. Most tools for working with fuzzy expert systems allow more than one conclusion per rule. The set of rules in a fuzzy expert system is known as the rulebase or knowledge base.The load change configuration is the input to the expert system which tries to optimally shift the specific number of load points. The following are the objectives of the expert system:_ Minimum switching._ Minimum losses._ Satisfying the voltage and current constraints.Fg. 4 shows the block diagram of the expert system. The inputs to the expert system are the value added or subtracted to that particular phase from the fuzzy controller and the current consumption of the individual consumers on that particular phase. The expert system should display which of the consumers are to be shifted from the overloaded phase to under loaded phase and also displays the message NO CHANGE if that phase is balanced.6. Simulation resultsTable 1 shows the display of output of Lab-VIEW based power and energy measurement [14]. It asks for the Distribution Transformer secondary reading, date, tolerance value (threshold value), and fuzzy conditioner of three phases for load balancing. It then displays the date, time, voltage, current, power factor, real power, reactive power, apparent power.Fig. 5 shows the line voltage curve for R, Y and B phases. It alsoindicates the voltage drop during peak hours of the day. The current curve for R, Y and B phases is shown in Fig. 6. It indicates the current unbalance in the existing supply network. The load graph from typical Distribution Transformer for entire day indicates interesting similarity in load patterns of consumers. Hence load balancing attempted during peak load band yielded fruitful result for the entire day.Fig. 7 displays the results of fuzzy logic based load balancing technique. Fuzzy toolkit in Lab VIEW is used for simulation. Mamdani fuzzy inference technique is applied and centroid based defuzzication technique is employed in the load balancing system. The output from the fuzzy controller is the value that is to be subtracted or added to a particular phase. The positive value indicates that the specific phase is overloaded and it should release the amount of load. The negative value indicates that the specific phase is under loaded and it should receive the amount of load. The value less than 10 A indicate that phase is perfectly loaded. Fig. 8 show the expert system output for all three phases. It gives the Service connection number (SC No.) and current consumption of individual consumer. The output of the fuzzy controller is applied as the input to the expert system. If the output of the fuzzy controller is a positive value then the expert system should inform which of the consumers are to be shifted from that phase.From Fig. 8, the R phase is overloaded, so the expert system informs thatthe SC No.’s 56 and 23 should be shifted. The output of the fuzzy controller for the Y phase is less than threshold value 10 A so that phase is perfectly loaded. The output of the fuzzy controller for B phase is a negative value; hence it receives the load from R-phase. There is no shifting of consumer in Y phase and B phase therefore the entries are indicated by zero values. There is no switching arrangement in secondary low voltage distribution network in Indian scenario and hence shifting to be done manually.The suggested approach has been tested practically on 70 nodes (70 consumers) low voltage distribution network and results are as shown in Fig. 9 (before balancing) and Fig. 10 (after balancing). Single phase customers physically reconfigured from overloaded phase into under loaded phase and then test results studied. Unbalancing has been observed for 10 days and then balancing attempted. Balanced network was studied and then results obtained. There is a percentage reduction in Energy loss from 9.695% to 8.82% though there is increase in cumulative kWh from 1058.95 to 1065.9. This Distribution Transformer belongs to urban area of a typical Indian city and has 41 single phase consumers and 29 three-phase consumers and three-phase consumers have balanced loads. In rural areas where number of single phase consumers are predominant and scattered around lengthy distribution lines this balancing technique will be much more beneficial than the tested study indicates.This research is significant to the Indian scenario considering the fact that there are 180,763 Distribution Transformers (www.tneb.in) and 2,07,00,000 consumers and length of secondary distribution network 5,17,604 km in one state, Tamil Nadu alone, 1% saving in energy loss per transformer per day will save few crores of rupees for a month to electrical utility.7. ConclusionIn this paper, the complete online monitoring of low voltage distribution network is done by using Lab VIEW and the fuzzy logic based load balancing technique is presented. With the results obtained from Lab VIEW, currents in individual phases are predicted and unbalance pattern is studied without actually measuring instantaneous values from consumer premise.A fuzzy logic based load balancing is implemented to balance the current in three phases and expert system to reconfigure some of the consumers from over loaded phase to under loaded phase. The input to the fuzzy controller is the individual phase current. The output of the fuzzy controller is the load change value, negative value for load receiving and positive value for load releasing. Expert system performs the optimal interchanging of the load points between the releasing and receiving phases.The proposed phase balancing system using fuzzy logic and expertsystem is effective for reducing the phase unbalance in the low voltage secondary distribution network. The energy losses are reduced and efficiency of the distribution network is improved and has been practically studied in typical Distribution Transformer of electrical utility.图一图2图3 图4图5图6图7图8图9图10。

CHEMICAL INDUSTRY AND ENGINEERING PROGRESS 2017年第36卷第7期·2724·化 工 进展惠州石化有限公司连续重整装置工艺流程模拟与优化孟凡辉，纪传佳，杨纪（中海油惠州石化有限公司，广东 惠州 516086）摘要：以惠州石化有限公司200×104t/a 连续重整装置为研究对象，采用英国先进技术公司KBC 的流程模拟软件Petro-SIM ，建立了预加氢部分、重整反应部分以及重整全流程模型，以期优化装置操作条件，改善装置的生产瓶颈。

应用该模型分别对重整加权平均反应入口温度以及重整装置的3条分馏塔进行了优化分析。

模拟结果得出，重整加权平均反应入口温度在520.7～521.7℃时，重整操作条件最优；预加氢产物汽提塔底温度在235℃、塔压在1.01MPa 、进料温度在171℃时达到最佳的分离效果；重整脱戊烷塔塔压在1.02MPa 、重整脱丁烷塔塔压在1.0MPa 时塔的操作最优。

通过实施优化措施，将重整加权平均反应入口温度由517.7℃提高至521℃，可增产芳烃2.7×104t/a ，氢气1.126×107m 3/a ；分别将汽提塔塔压、脱戊烷塔塔压以及脱丁烷塔塔压由1.1MPa 降至1.0MPa ，共节约燃料气3.528×106m 3，多回收C 6环烷烃2.306×104t/a 。

核算装置效益，全年可实现节能效益197.9万元，提升装置经济效益3128.8万元。

关键词：连续重整装置；模拟；模型；优化；节能中图分类号：TQ021.8 文献标志码：A 文章编号：1000–6613（2017）07–2724–06 DOI ：10.16085/j.issn.1000-6613.2016-2078Process simulation and optimization for CNOOC Huizhou company’scontinuous reforming unitMENG Fanhui ，JI Chuanjia ，YANG Ji（CNOOC Huizhou Petrochemical Limited Company ，Huizhou 516086，Guangdong ，China ）Abstract ：Using the Petro-SIM software ，technicians established the pretreatment model ，the catalytic reforming reaction model and the complete continuous catalytic reforming （CCR ）process model which reflecting the actual operating conditions of 200×104t/a reforming unit in Huizhou company of China national offshore oil corporation （CNOOC ）．The results showed that the reforming conditions are optimal when the inlet temperature at 520.7—521.7℃. The hydrogenation product stripper’s bottom temperature at 235℃，the pressure at 1.01MPa and the feed temperature at 171℃. The best separation effect was obtained. The operation of the column is optimal when the reforming depentanizer’s pressure is at 1.02MPa and the reforming butane tower’s pressure at 1.0MPa. The models were applied to the analysis of reactor temperature and three fractionation columns ，such as increasing the average weighted temperature from 517.7℃ to 521℃，the aromatics increased by 2.7×104t/a and hydrogen increased by 1.126×107m 3/a. The pressures at the top of stripper tower ，depentanizer and the butane tower were reduced from 1.1MPa to 1.0MPa respectively. The flue gas was decreased by 3.528×106m 3 and C 6 naphthenic increased by 2.306×104t/a. Effective measures have been adopted to improve the operation of reforming unit ，energy savings for the unit totaled 1.979 million yuan and annual economic benefits totaled 31.288 million yuan. Key words ：continuous reforming unit ；simulation ；model ；optimization ；energy saving 中海油惠州石化有限公司连续重整装置采用美国环球油品公司第三代超低压连续重整专利技收稿日期：2016-11-14；修改稿日期：2017-01-04。

1、个人简介张煜，1974年，男，工学博士，博士后出站，教授，博士生导师，武汉理工大学教学名师。

主持国家自然科学基金面上项目、科技部国际合作项目、湖北省自然科学基金、中国博士后基金、教育部高校专项基金、企业项目等。

主要参与国家自然科学基金、河南省重大科技攻关项目、十二五国家科技支撑计划、十一五国家科技支撑计划、交通部西部专项、重庆市科技攻关计划项目、湖北省自然科学基金（重点）等。

在国内外发表论文40多篇。

中国系统工程学会会员，国家自然科学基金评审专家，湖北省科技项目评审专家库成员。

获得教育部、湖北省、中国物流采购联合会、中国港口协会等科技进步奖4项（1等奖1项，2等奖4项）。

2、所在单位及职称武汉理工大学，物流工程学院&港口装卸技术交通部重点实验室，教授。

中国远洋海运-武汉理工大学技术中心，兼职教师。

3、受教育经历2001/09－2007/05，武汉理工大学，物流工程学院，机械设计及理论专业，工学博士。

1998/09－2001/06，武汉理工大学，物流工程学院，机械设计及理论专业，工学硕士。

1992/09－1996/06，武汉水运工程学院，港机系，流体传动及控制专业，工学学士。

4、工作经历2017/06－至今，武汉理工大学，物流工程学院&港口装卸技术交通部重点实验室，教授,博士生导师。

2013/11－至今，武汉理工大学，物流工程学院&港口装卸技术交通部重点实验室，教授,硕士生导师。

2008/10－2013.10，武汉理工大学，物流工程学院&港口装卸技术交通部重点实验室，副教授,硕士生导师。

2008/10－2011/09，武汉理工大学，水路公路交通安全与装备教育部工程研究中心，博士后(交通运输与规划专业)。

2010/09－2011/09，美国Lehigh大学，Department of Industrial and System Engineering（ISE），访问学者。

智能停车场系统中英文对照外文翻译文献(文档含英文原文和中文翻译)原文：Intelligent parking systemAbstractThe basic concepts of the parking reservation system and parking revenue management system are discussed in this paper. The proposed intelligent’’ parking space inventory control system that is based on a combination of fuzzy logic and integer programming techniques makes ‘‘on line’’ decisions whether to accept or reject a new driver's request for parking. In the first step of the proposed model, the best parking strategies are developed for many different patterns of vehicle arrivals. These parking strategies are developed using integer programming approach. In the second step, learn-ing from the best strategies, specific rules are defined. The uniqueness of the proposed approach is that the rules arederived from the set of chosen examples assuming that the future traffic arrival patterns are known. The results were found to be close to the best solution assuming that the future arrival pattern is known.Keywords: Traffic; Uncertainty modeling; Control; Parking; Fuzzy logic 1.IntroductionEvery day a significant percentage of drivers in single-occupancy vehicles search for a parking space. Additionally, less experienced drivers or out-of-towners further contribute to the increase of traffic congestion. Search for a vacant parking space is a typical example of a search process. Every parking search strategy is composed of a set of vague rules. It is usually difficult to describe these rules explicitly. The type of the planned activity, time of a day, day of the week, current congestion on particular routes, knowledge of city streets, and potentially available parking places have significant influence on a chosen parking search strategy. During the last four decades numerous parking search models have been developed (Vander Goot, 1982; Axhausen and Polak, 1991; Polak and Axhausen, 1990; Young et al., 1991a,b; saltzman, 1997; Shoup, 1997; Steiner, 1998; Thompson and Richardson, 1998; Arnott and Rowse, 1999; Tam and Lam, 2000; Wong et al., 2000; Waterson et al., 2001). In many decision-making situations in transportation (modal split, choice of air carrier, choice of airport, etc.) the competitive alternatives and their characteristics are reasonably well known in advance to the decision maker (passenger, driver). On the other hand, the drivers usually discover diffierent parking alternatives one by one in a temporal sequence. Clearly, this temporal sequence has a very strong influence on the driver's final decision about the parking placeDuring the past two decades, traffic authorities in many cities (Helsinki, Cologne, Mainz, Stuttgart, Wiesbaden, Aalborg, Hague) havestarted to inform and guide drivers to parking facilities with real-time var-iable message signs [directional arrows, names of the parking facilities, status (full, not full, number of available parking spaces, etc.)]. Information about the number of available parking spaces could be displayed on the major roads, streets and intersections, or it could be distributed through the Internet.It is logical to ask the question about the benefits of the parking guidance systems. Current practice shows that parking guidance systems usually do not change the occupancy rate or average parking duration. Drivers easily become familiar with the parking guidance systems, and majority of them use, thrust and appreciate the help of the systems. Guidance systems significantly increase the probability of finding vacant parking space, mitigate frustration of the drivers–visitors unfamiliar with the city center, decrease the queues in front of parking garages, decrease the total amount of vehicle-miles traveled (particularly in the city centers), decrease the average trip time, energy consumption, and air pollution. Parking guidance system is a part of comprehensive parking policy and traffic management system, whose other elements are street parking control (including sanctions for the illegally parked vehicles), parking fare structure, and parking revenue management system.Parking guidance systems help drivers to find vacant parking spaces when they are already on the network, and approaching their final destination. Throughout this research the concepts of the parking reservation system and parking revenue management system are proposed. Such systems would help drivers to find a vacant parking space even before beginning their trip. The proposed ‘‘intelligent’’parking space inventory control system that is based on the combination of simulation, optimization techniques, and fuzzy logic makes ‘‘real-time’’ decisions as to whether to reject or accept a new request for parking. The proposedmethodology could be applied for parking lots and parking garages in cities and at the big international airports.The paper is organized as follows:1. Parking-pricing problems are presented in Section 2. Analogies between parking problems and some other industries are presented in Section 3. The parking revenue management system is introduced in Section 4, and the Intelligent parking space inventory control system is introduced in Section 5. The algorithm to create intelligent parking spaces inventory control system is presented in Section 6. Results obtained with the ‘‘intelligent’’ parking system are given in Section 7, and Sec-tion 8 presents the concluding remarks and further research orientations.2.parking pricingIn majority of cities throughout the world drivers pay for using different parking facilities. In some instances, traffic congestion can be significantly reduced as a result of parking price. The parking revenue is usually used to cover parking facility costs (access gates, ticket printers, parking meters, parking signs, attendants), or to improve some other traffic and transportation activities. Different parking pricing strategies should be a part of the comprehensive solution approach to the complex traffic congestion problems. There is no doubt that parking pricing represents one of the important demand management strategies. For example, traffic authorities, local governments and private sector could introduce higher parking tariffs for solo drivers or for long-term parkers in congested city areas. They could provide special parking discounts to vanpoolers. Obviously parking pricing should be carefully studied in the context of the considered city area (down-town, residential, commercial, retail use areas).In some cities (Madison, Wisconsin) there are already time dependent parking fees that force commuters to switch to diffierent alternativesof public transportation . Trying to promote public transit San Francisco traffic authorities increased parking tariffs at public and commercial garages. The Chicago authorities raised parking rates few times. As a consequence, the total number of cars parked significantly decreased, as well as parking duration time. The greatest decrease was in the number of all day parkers. Authorities in Seattle significantly reduced parking tariffs for carpool at two Seattle parking facilities in downtown . Active role in parking pricing strategies could also have employers paying for employees' parking. Employers who remove parking subsidies for the employees could significantly decrease the total number of solo drivers. The main role of any parking pricing strategy should be reducing the total number of vehicle trips during certain time periods, shifting commuters to alternative transportation modes, and to different parking locations. At the same time, when trying to implement any parking strategy, it is very important to provide enough parking space for shoppers, to provide preferential parking for residents in considered city area, to provide preferential parking for different parking locations, to consider low income families, and to protect streets in the neighborhood from illegal parking.The basic economic concepts of supply and demand should be more utilized when solving complex traffic congestion and parking problems (Vickrey, 1969, 1994; Verhoef et al., 1995). So-called value pricing is also known as congestion pricing, or variable tolling. The basic idea behind the concept of congestion pricing is to force drivers to travel and use transportation facilities more during off-peak hours and less during peak hours. The idea of congestion pricing is primarily connected with the road (drivers pay for using private, faster roads, drivers with lower vehicle occupancy pay for using High Occupancy Vehicle lanes, drivers pay more to enter city's downtown on weekdays) or airportoperators (more expensive landing fees during peak hours). In the context of parking problems, this means: (a) that different parking tariffs should exist for different users; (b) that the parking fees should increase and/or decrease few times during a day.3.Parking problems and revenue management systems: Analogies with some other industriesAirline industry, hotels, car rental, rail, cruise, healthcare, broadcast industry, energy industry, golf,equipment rental, restaurant, and other industries are utilizing revenue management concepts when selling their products (Cross, 1997). Revenue management could be described as a group of different scientific techniques of managing the company revenue when trying to deliver the right product to the right client at the right price at the right time. The roots of the revenue management are in the airline industry. The basic characteristics of the industries to which different revenue management concepts were successfully applied are: (a) variable demand over time; (b) variable asset utilization; (c) perishable assets; (d) limited resources; (e) market segmentation; (f) adding new capacity is expensive, difficult or impossible; (g) direct cost per client is negligible part of the total cost of making service available; (h) selling products in advance. The main characteristics of the parking space inventory control problems are the following:· Parking demand is variable over time.· Like hotel rooms, or restaurant chairs, parking spaces also have daily opportunity to be ‘‘sold’’ (used by clients).·Any parking lot or garage has limited number of parking spaces that can be used by drivers· Market segmentation means that different customers are willing to pay different prices for the same asset (hotel room, airline seat, seat ina rented car). Businessman wanting to park a car near a meeting point 15 minutes before the meeting would be ready to pay much higher parking fee than a pensioner planning to walk with his wife through the downtown, who made parking reservation four day in advance.· Building new garages and parking lots could be very expensive and sometimes very difficult.· Parking places can be easily reserved in advance.Introducing and developing parking reservation system (created in an Internet and cell phone environ-ment) would present further improvement in modern parking technologies. Drivers would be advised and guided before beginning of the trip, as well as during the trip. Parking reservation system should be coupled with the parking revenue management system. In this way, parking operators and traffic authorities would be able to implement different parking strategies. Once the driver is allowed to park, it is possible to implement internal garage guidance system that guides the driver to an empty parking place.4.Introducing parking revenue management systemLet us assume that we have parking reservation system. Drivers make their requests for parking at random moments of time (by phone from home, by cell phone while driving, through the Internet, etc.).A certain number of drivers would maybe cancel their reservations before beginning of the parking.These cancellations would also be made at random moments of time. Like in some other industries, a certain number of drivers would not appear in parking garage for which they have a con-firmed reservation and purchased ticket. Would these drivers be penalized for their behavior? Depending on ration between parking demand and parking supply, the answer could be ‘‘Yes’’ or ‘‘No’’.Reservation system should be flexible enough allowing some drivers to appear right before wished beginning of parking, looking for an emptyspace in a garage, even though they do not have a confirmed reservation. Would it be good to have few different parking tariffs? The answer is obviously ‘‘Yes’’. Drivers paying lower parking tariffs could be disabled and senior citizens, people who reserve parking space few days in advance, or HOV drivers. Drivers paying higher tariffs could be solo drivers, long term parking drivers, or drivers showing up and asking for parking without making reservation in advance. Obviously, there is a lot of possible parking pricing strategies.The stochastic nature of reservation generation and cancellation, the stochastic nature of driver show-up during reserved time slot, variety of parking tariffs, and the need to respond to drivers' requests in real time, indicate that the management of parking garage revenues represents a complex problem.In the past 30 years a relatively large number of papers have been devoted to different aspects of the air-line seat inventory control problem (Littlewood, 1972; Belobaba, 1987; Brumelle and McGill, 1993; Teodorovic et al., 2002). The model proposed in this paper is highly inspired by the developed airline yield management stochastic and/or deterministic models.Let us assume that we have few different parking tariffs. The simplest reservation system (similar to some airline reservation systems in the past) could be ‘‘distinct tariff class parking space inventories’’ (Fig. 1(a)),indicating separate parking spaces in the garage for each tariff class. In this case, once the parking space is assigned to a tariff class, it may be booked only in that tariff class or else remains unsold. There are certain advantages, as well as certain disadvantages in the case of distinct parking space inventories. In this case users paying lower tariffs would be relatively well ‘‘protected’’. In other words, this system would pay a lot of attention to the disabled person, senior citizens,people who reserve parking space few days in advance, and HOV drivers. Obvious disadvantage of the distinct parking space inventories is the fact that very often some parking spaces assigned to lower tariff users would be empty even the higher tariff users demand is very high. In other words, it would be possible to reject some drivers even all parking spaces in garage are not occupied.In case of a ‘‘nested reservation system ’’, the high tariff request will not be rejected as long as any parking spaces are available in lower tariff classes. For example, if we have four tariff classes, then there is no booking limit for class 1, but there are booking limits (BLi, i = 2, 3, . . ., m) for each of the remaining three classes (Fig. 1(b)). As we can see from Fig. 1(b), all parking spaces are always available to class1. There are always a certain number of parking spaces protected for class 1, certain number of parking spaces protected for classes 1 and 2, and certain number of parking spaces protected for classes 1, 2 and 3. If we make a request-by-request revision of booking limits, there is no longer a difference between distinct and nested reservation system.In this research (like in the paper of Teodorovic ´ et al., 2002) an attempt was made to make reservation decisions on theBL1BL2BLmCBL1=CBL2BLm (a)(b)Fig.1‘‘request-by-request’’ basis. In the scenario that we consider, we assume that there are more than two types of tariffs. The basic characteristic of the parking space inventory control model that we propose is ‘‘real-time’’ decision making about each driver request. The developed model is called an ‘‘intelligent’’ parking space inventory control system.译文：智能停车场系统摘要：本文讨论停车预订系统和停车收入管理系统的基本概念.拟议的智能停车空间的库存控制系统，基于模糊逻辑和整数规划技术相结合，使“上线”决定是否接受或拒绝新的驱动程序的停车要求。

英文原文The simulation and the realization of the digital filterWith the information age and the advent of the digital world, digital signal processing has become one of today's most important disciplines and door technology. Digital signal processing in communications, voice, images, automatic control, radar, military, aerospace, medical and household appliances, and many other fields widely applied. In the digital signal processing applications, the digital filter is important and has been widely applied.1、figures Unit on :Analog and digital filtersIn signal processing, the function of a filter is to remove unwanted parts of the signal, such as random noise, or to extract useful parts of the signal, such as the components lying within a certain frequency range.The following block diagram illustrates the basic idea.There are two main kinds of filter, analog and digital. They are quite different in their physical makeup and in how they work. An analog filter uses analog electronic circuits made up from components such as resistors, capacitors and op amps to produce the required filtering effect. Such filter circuits are widely used in such applications as noise reduction, video signal enhancement, graphic equalisers in hi-fi systems, and many other areas. There are well-established standard techniques for designing an analog filter circuit for a given requirement. At all stages, the signal being filtered is an electrical voltage or current which is the direct analogue of the physical quantity (e.g. a sound or video signal or transducer output) involved. A digital filter uses a digital processor to perform numerical calculations on sampled values of the signal. The processor may be a general-purpose computer such as a PC, or a specialised DSP (Digital Signal Processor) chip. The analog input signal must first be sampled and digitised using an ADC (analog to digital converter). The resulting binary numbers, representing successive sampled values of the input signal, are transferred to the processor,which carries out numerical calculations on them. These calculations typically involve multiplying the input values by constants and adding the products together. If necessary, the results of these calculations, which now represent sampled values of the filtered signal, are output through a DAC (digital to analog converter) to convert the signal back to analog form.Note that in a digital filter, the signal is represented by a sequence of numbers, rather than a voltage or current.The following diagram shows the basic setup of such a system.Unit refers to the input signals used to filter hardware or software. If the filter input, output signals are separated, they are bound to respond to the impact of the Unit is separated, such as digital filters filter definition. Digital filter function, which was to import sequences X transformation into export operations through a series Y.According to figures filter function 24-hour live response characteristics, digital filters can be divided into two, namely, unlimited long live long live the corresponding IIR filter and the limited response to FIR filters. IIR filters have the advantage of the digital filter design can use simulation results, and simulation filter design of a large number of tables may facilitate simple. It is the shortcomings of the nonlinear phase; Linear phase if required, will use the entire network phase-correction. Image processing and transmission of data collection is required with linear phase filters identity. And FIR linear phase digital filter to achieve, but an arbitrary margin characteristics. Impact from the digital filter response of the units can be divided into two broad categories : the impact of the limited response (FIR) filters, and unlimited number of shocks to (IIR) digital filters.FIR filters can be strictly linear phase, but because the system FIR filter function extremity fixed at the original point, it can only use the higher number of bands to achieve their high selectivity for the same filter design indicators FIR filter called band than a few high-IIR 5-10 times, the cost is higher, Signal delay is also larger. But if the same linear phase, IIR filters must be network-wide calibration phase, the same section also increase the number of filters and network complexity. FIR filters can be used to achieve non-Digui way, not in a limited precision of a shock, and into the homes and quantitative factors of uncertainty arising from the impact of errors than IIR filter small number, and FIR filter can be used FFT algorithms, the computational speed. But unlike IIR filter can filter through the simulation results, there is no ready-made formula FIR filter must use computer-aided design software (such as MATLAB) to calculate. So, a broader application of FIR filters, and IIR filters are not very strict requirements on occasions.Unit from sub-functions can be divided into the following four categories :(1) Low-filter (LPF);(2) high-filter (HPF);(3) belt-filter (BPF);(4) to prevent filter (BSF).The following chart dotted line for the ideals of the filter frequency characteristics :A1(f) A2(f)10 f2cf 0 f2cf(a) (b)A3(f) A4(f)0 f1c f2cf 0 f1cf2cf(c) (d)(a)LPF (b)HPF (c)BPF (d)BSF2、MATLAB introducedMATLAB is a matrix laboratory (Matrix Laboratory) is intended. In addition to an excellent value calculation capability, it also provides professional symbols terms, word processing, visualization modeling, simulation and real-time control functions. MATLAB as the world's top mathematical software applications, with a strong engineering computing, algorithms research, engineering drawings, applications development, data analysis and dynamic simulation, and other functions, in aerospace, mechanical manufacturing and construction fields playing an increasingly important role. And the C language function rich, the use of flexibility, high-efficiency goals procedures. High language both advantages as well as low level language features. Therefore, C language is the most widely used programming language. Although MATLAB is a complete, fully functional programming environment, but in some cases, data and procedures with the external environment of the world is very necessary and useful. Filter design using Matlab, could be adjusted with the design requirements and filter characteristics of the parameters, visual simple, greatly reducing the workload for the filter design optimization.In the electricity system protection and secondary computer control, many signal processing and analysis are based on are certain types Yeroskipou and the second harmonics of the system voltage and current signals (especially at D process), are mixed with a variety of complex components, the filter has been installed power system during the critical components. Current computer protection and the introduction of two digital signal processing software main filter. Digital filter design using traditional cumbersome formula, the need to change the parameters after recalculation, especially in high filters, filter design workload. Uses MATLAB signal processing boxes can achieve rapid and effective digital filter design and simulation.MATLAB is the basic unit of data matrix, with its directives Biaodashi mathematics, engineering, commonly used form is very similar, it is used to solve a problem than in MATLAB C, Fortran and other languages End precision much the same thing. The popular MATLAB 5.3/Simulink3.0 including hundreds of internal function with the main pack and 30types of tool kits (Toolbox). kits can be divided into functional tool kits and disciplines toolkit. MATLAB tool kit used to expand the functional symbols terms, visualization simulation modelling, word processing and real-time control functions. professional disciplines toolkit is a stronger tool kits, tool kits control, signal processing tool kit, tool kits, etc. belonging to such communicationsMATLAB users to open widely welcomed. In addition to the internal function, all the packages MATLAB tool kits are readable document and the document could be amended, modified or users through Yuanchengxu the construction of new procedures to prepare themselves for kits.3、Digital filter designDigital filter design of the basic requirementsDigital filter design must go through three steps :(1) Identification of indicators : In the design of a filter, there must be some indicators. These indicators should be determined on the basis of the application. In many practical applications, digital filters are often used to achieve the frequency operation. Therefore, indicators in the form of general jurisdiction given frequency range and phase response. Margins key indicators given in two ways. The first is absolute indicators. It provides a function to respond to the demands of the general application of FIR filter design. The second indicator is the relative indicators. Its value in the form of answers to decibels. In engineering practice, the most popular of such indicators. For phase response indicators forms, usually in the hope that the system with a linear phase frequency bands human. Using linear phase filter design with the following response to the indicators strengths：①it only contains a few algorithms, no plural operations；②there is delay distortion, only a fixed amount of delay; ③the filter length N (number of bands for N-1), the volume calculation for N/2 magnitude.(2) Model approach : Once identified indicators can use a previous study of the basic principles and relationships, a filter model to be closer to the target system.(3) Achieved : the results of the above two filters, usually by differential equations, system function or pulse response to describe. According to this description of hardware or software used to achieve it.4、Introduced FPGAProgrammable logic device is a generic logic can use a variety of chips, which is to achieve ASIC ASIC (Application Specific Integrated Circuit) semi-customized device, Its emergence and development of electronic systems designers use CAD tools to design their own laboratory in the ASIC device. Especially FPGA (Field Programmable Gate Array) generated and development, as a microprocessor, memory, the figures for electronic system design and set a new industry standard (that is based on standard product sales catalogue in the market to buy). Is a digital system for microprocessors, memories, FPGA or three standard building blocks constitute their integration direction.Digital circuit design using FPGA devices, can not only simplify the design process and can reduce the size and cost of the entire system, increasing system reliability. They do not need to spend the traditional sense a lot of time and effort required to create integrated circuits, to avoid the investment risk and become the fastest-growing industries of electronic devices group. Digital circuit design system FPGA devices using the following main advantages(1)Design flexibleUse FPGA devices may not in the standard series device logic functional limitations. And changes in system design and the use of logic in any one stage of the process, and only through the use of re-programming the FPGA device can be completed, the system design provides for great flexibility.(2) Increased functional densityFunctional density in a given space refers to the number of functional integration logic. Programmable logic chip components doors several high, a FPGA can replace several films, film scores or even hundreds of small-scale digital IC chip illustrated in the film. FPGA devices using the chip to use digital systems in small numbers, thus reducing the number of chips used to reduce the number of printed size and printed, and will ultimately lead to a reduction in the overall size of the system.(3) Improve reliabilityPrinting plates and reduce the number of chips, not only can reduce system size, but it greatly enhanced system reliability. A higher degree of integration than systems in many low-standard integration components for the design of the same system, with much higher reliability. FPGA device used to reduce the number of chips required to achieve the system in the number printed on the cord and joints are reduced, the reliability of the system can beimproved.(4) Shortening the design cycleAs FPGA devices and the programmable flexibility, use it to design a system for longer than traditional methods greatly shortened. FPGA device master degrees high, use printed circuit layout wiring simple. At the same time, success in the prototype design, the development of advanced tools, a high degree of automation, their logic is very simple changes quickly. Therefore, the use of FPGA devices can significantly shorten the design cycle system, and speed up the pace of product into the market, improving product competitiveness.(5) Work fastFPGA/CPLD devices work fast, generally can reach several original Hertz, far larger than the DSP device. At the same time, the use of FPGA devices, the system needed to achieve circuitclasses and small, and thus the pace of work of the entire system will be improved.(6) Increased system performance confidentialityMany FPGA devices have encryption functions in the system widely used FPGA devices can effectively prevent illegal copying products were others(7) To reduce costsFPGA device used to achieve digital system design, if only device itself into the price, sometimes you would not know it advantages, but there are many factors affecting the cost of the system, taken together, the cost advantages of using FPGA is obvious. First, the use of FPGA devices designed to facilitate change, shorten design cycles, reduce development costs for system development; Secondly, the size and FPGA devices allow automation needs plug-ins, reducing the manufacturing system to lower costs; Again, the use of FPGA devices can enhance system reliability, reduced maintenance workload, thereby lowering the cost of maintenance services for the system. In short, the use of FPGA devices for system design to save costs.FPGA design principles :FPGA design an important guiding principles : the balance and size and speed of exchange, the principles behind the design of the filter expression of a large number of certification.Here, "area" means a design exertion FPGA/CPLD logic resources of the FPGA can be used to the typical consumption (FF) and the search table (IUT) to measure more general measure can be used to design logic equivalence occupied by the door is measured. "pace"means stability operations in the chip design can achieve the highest frequency, the frequency of the time series design situation, and design to meet the clock cycle -- PADto pad, Clock Setup Time, Clock Hold Beijing, Clock-to-Output Delay, and other characteristics of many time series closely related. Area (area) and speed (speed) runs through the two targets FPGA design always is the ultimate design quality evaluation criteria. On the size and speed of the two basic concepts : balance of size and speed and size and speed of swap.One pair of size and speed is the unity of opposites contradictions body. Requirements for the design of a design while the smallest, highest frequency of operation is unrealistic. More scientific goal should be to meet the design requirements of the design time series (includes requirements for the design frequency) premise, the smallest chip area occupied. Or in the specified area, the design time series cushion greater frequency run higher. This fully embodies the goals of both size and speed balanced thinking. On the size and speed requirements should not be simply interpreted as raising the level and design engineers perfect sexual pursuit, and should recognize that they are products and the quality and cost of direct relevance. If time series cushion larger design, running relatively high frequency, that the design Jianzhuangxing stronger, more quality assurance system as a whole; On the other hand, the smaller size of consumption design is meant to achieve in chip unit more functional modules, the chip needs fewer, the entire system has been significantly reduced cost. As a contradiction of the two components, the size and speed is not the same status. In contrast, meet the timetables and work is more important for some frequency when both conflicts, the use of priority guidelines.Area and the exchange rate is an important FPGA design ideas. Theoretically, if a design time series cushion larger, can run much higher than the frequency design requirements, then we can through the use of functional modules to reduce the consumption of the entire chip design area, which is used for space savings advantages of speed; Conversely, if the design of a time series demanding, less than ordinary methods of design frequency then generally flow through the string and data conversion, parallel reproduction of operational module, designed to take on the whole "string and conversion" and operate in the export module to chip in the data "and string conversion" from the macro point of view the whole chip meets the requirements of processing speed, which is equivalent to the area of reproduction - rate increase.For example. Assuming that the digital signal processing system is 350Mb/s input data flow rate, and in FPGA design, data processing modules for maximum processing speed of150Mb/s, because the data throughput processing module failed to meet requirements, it is impossible to achieve directly in the FPGA. Such circumstances, they should use "area-velocity" thinking, at least three processing modules from the first data sets will be imported and converted, and then use these three modules parallel processing of data distribution, then the results "and string conversion," we have complete data rate requirements. We look at both ends of the processing modules, data rate is 350Mb/s, and in view of the internal FPGA, each sub-module handles the data rate is 150Mb/s, in fact, all the data throughput is dependent on three security modules parallel processing subsidiary completed, that is used by more chip area achieve high-speed processing through "the area of reproduction for processing speed enhancement" and achieved design.FPGA is the English abbreviation Field of Programmable Gate Array for the site programmable gate array, which is in Pal, Gal, Epld, programmable device basis to further develop the product. It is as ASIC (ASIC) in the field of a semi-customized circuit and the emergence of both a customized solution to the shortage circuit, but overcome the original programmable devices doors circuit few limited shortcomings.FPGA logic module array adopted home (Logic Cell Array), a new concept of internal logic modules may include CLB (Configurable Logic Block), export import module IOB (Input Output Block) and internal links (Interconnect) 3. FPGA basic features are :(1) Using FPGA ASIC design ASIC using FPGA circuits, the chip can be used,while users do not need to vote films production.(2) FPGA do other customized or semi-customized ASIC circuits throughout the Chinese specimen films.3) FPGA internal capability and rich I/O Yinjue.4) FPGA is the ASIC design cycle, the shortest circuit, the lowest development costs, risks among the smallest device5) FPGA using high-speed Chmos crafts, low consumption, with CMOS, TTL low-power compatibleIt can be said that the FPGA chip is for small-scale systems to improve system integration, reliability one of the bestCurrently FPGA many varieties, the Revenue software series, TI companies TPC series, the fiex ALTERA company seriesFPGA is stored in films from the internal RAM procedures for the establishment of the state of its work, therefore, need to programmed the internal Ram. Depending on the different configuration, users can use a different programming methodsPlus electricity, FPGA, EPROM chips will be read into the film, programming RAM中data, configuration is completed, FPGA into working order. Diaodian, FPGA resume into white films, the internal logic of relations disappear, FPGA to repeated use. FPGA's programming is dedicated FPGA programming tool, using generic EPROM, prom programming device can. When the need to modify functional FPGA, EPROM can only change is. Thus, with a FPGA, different programming data to produce different circuit functions. Therefore, the use of FPGA very flexible.There are a variety of FPGA model : the main model for a parallel FPGA plus a EPROM manner; From the model can support a number of films FPGA; serial prom programming model could be used serial prom FPGA programming FPGA; The external model can be engineered as microprocessors from its programming microprocessors.Verilog HDL is a hardware description language for the algorithm level, doors at the level of abstract level to switch-level digital system design modelling. Modelling of the target figure by the complexity of the system can be something simple doors and integrity of electronic digital systems. Digital system to the levels described, and in the same manner described in Hin-time series modelling.Verilog HDL language with the following description of capacity : design behaviour characteristics, design data flow characteristics, composition and structure designed to control and contain the transmission and waveform design a certification mechanism. All this with the use of a modelling language. In addition, Verilog HDL language programming language interface provided by the interface in simulation, design certification from the external design of the visit, including specific simulation control and operation.Verilog HDL language grammar is not only a definition, but the definition of each grammar structure are clear simulation, simulation exercises. Therefore, the use of such language to use Verilog simulation models prepared by a certification. From the C programming language, the language inherited multiple operating sites and structures. Verilog HDL provides modelling capacity expansion, many of the initial expansion would be difficult to understand. However, the core subsets of Verilog HDL language very easy to learn and use, which is sufficient formost modelling applications. Of course, the integrity of the hardware description language is the most complex chips from the integrity of the electronic systems described.historyVerilog HDL language initially in 1983 by Gateway Design Automation companies for product development simulator hardware modelling language. Then it is only a dedicated language. Since their simulation, simulation devices widely used products, Verilog HDL as a user-friendly and practical language for many designers gradually accepted. In an effort to increase the popularity of the language activities, Verilog HDL language in 1990 was a public area. Open Verilog International (OVI) is to promote the development of Verilog international organizations. 1992, decided to promote OVI OVI standards as IEEE Verilog standards. The effort will ultimately succeed, a IEEE1995 Verilog language standard, known as IEEE Std 1364-1995. Integrity standards in Verilog hardware description language reference manual contains a detailed description.Main capacity：Listed below are the main Verilog hardware description language ability*Basic logic gate, and, for example, or have embedded in the language and nand* Users of the original definition of the term (UDP), the flexibility. Users can be defined in the original language combinations logic original language, the original language of logic could also be time series* Switches class infrastructure models, such as the nmos and pmos also be embedded in the language* Hin-language structure designated for the cost of printing the design and trails Shi Shi and design time series checks.* Available three different ways to design or mixed mode modelling. These methods include : acts described ways - use process of structural modelling; Data flow approach - use of a modelling approach Fuzhi expression; Structured way - using examples of words to describe modular doors and modelling.* Verilog HDL has two types of data : data types and sequence data line network types. Line network types that the physical links between components and sequence types that abstract data storage components.* To describe the level design, the structure can be used to describe any level module example* Design size can be arbitrary; Language is design size (size) impose any restrictions* Verilog HDL is no longer the exclusive language of certain companies but IEEE standards.* And the machine can read Verilog language, it may as EDA tools and languages of the world between the designers* Verilog HDL language to describe capacity through the use of programming language interface (PLI) mechanism further expansion. PLI is to allow external functions of the visit Verilog module information, allowing designers and simulator world Licheng assembly* Design to be described at a number of levels, from the switch level, doors level, register transfer level (RTL) to the algorithm level, including the level of process and content* To use embedded switching level of the original language in class switch design integrity modelling* Same language can be used to generate simulated incentive and certification by the designated testing conditions, such as the value of imports of the designated*Verilog HDL simulation to monitor the implementation of certification, the certification process of implementing the simulation can be designed to monitor and demonstrate value. These values can be used to compare with the expectations that are not matched in the case of print news reports.* Acts described in the class, not only in the RTL level Verilog HDL design description, and to describe their level architecture design algorithm level behavioural description* Examples can use doors and modular structure of language in a class structure described* Verilog HDL mixed mode modelling capabilities in the design of a different design in each module can level modelling* Verilog HDL has built-in logic function, such as*Structure of high-level programming languages, such as conditions of expression, and the cycle of expression language, language can be used* To it and can display regular modelling* Provide a powerful document literacy* Language in the specific circumstances of non-certainty that in the simulator, different models can produce different results; For example, describing events in the standard sequence of events is not defined.5、In troduction of DSPToday, DSP is w idely used in the modern techno logy and it has been the key part of many p roducts and p layed more and mo re impo rtant ro le in our daily life.Recent ly, Northw estern Po lytechnica lUniversity Aviation Microelect ronic Center has comp leted the design of digital signal signal p rocesso r co re NDSP25, w h ich is aim ing at TM S320C25 digital signal p rocesso r of Texas Inst rument TM S320 series. By using top 2dow n design flow , NDSP25 is compat ible w ith inst ruct ion and interface t im ing of TM S320C25.Digital signal processors (DSP) is a fit for real-time digital signal processing for high-speed dedicated processors, the main variety used for real-time digital signal processing to achieve rapid algorithms. In today's digital age background, the DSP has become the communications, computer, and consumer electronics products, and other fields based device.Digital signal processors and digital signal processing is inseparably, we usually say "DSP" can also mean the digital signal processing (Digital Signal Processing), is that in this digital signal processors Lane. Digital signal processing is a cover many disciplines applied to many areas and disciplines, refers to the use of computers or specialized processing equipment, the signals in digital form for the collection, conversion, recovery, valuation, enhancement, compression, identification, processing, the signals are compliant form. Digital signal processors for digital signal processing devices, it is accompanied by a digital signal processing to produce. DSP development process is broadly divided into three phases : the 20th century to the 1970s theory that the 1980s and 1990s for the development of products. Before the emergence of the digital signal processing in the DSP can only rely on microprocessors (MPU) to complete. However, the advantage of lower high-speed real-time processing can not meet the requirements. Therefore, until the 1970s, a talent made based DSP theory and algorithms. With LSI technology development in 1982 was the first recipient of the world gave birth to the DSP chip. Years later, the second generation based on CMOS工艺DSP chips have emerged. The late 1980s, the advent of the third generation of DSP chips. DSP is the fastest-growing 1990s, there have been four successive five-generation and the generation DSP devices. After 20 years of development, the application of DSP products has been extended to people's learning, work and all aspects of life and gradually become electronics products determinants.。

School of Electronic and Computer EngineeringPeking UniversityWang WenminArtificial IntelligenceReinforcement Learning Paradigm11. Paradigms in Machine Learning Contents:☐11.1. Supervised Learning Paradigm☐11.2. Unsupervised Learning Paradigm☐11.3. Reinforcement Learning Paradigm☐11.4. Relations and Other Paradigms11.3. Reinforcement Learning Paradigm Contents:☐11.3.1. Overview of Reinforcement Learning☐11.3.2. Types of Reinforcement Learning☐11.3.3. New Algorithms of Reinforcement Learning☐11.3.4. Applications of Reinforcement Learning☐In reinforcement learning (RL), the learner is a decision-making agent,that takes actions in an environment and receives rewards for its actions.在强化学习中，其学习器是一个决策制定智能体，在环境下采取行动并获得这些动作的回报。

☐After a set of trial-and-error runs, the agent should learn the best policy.经过一系列试错运行之后，该智能体能够学到最优策略。

CFD simulation and optimization ofthe ventilation for subway side-platformFeng-Dong Yuan *, Shi-Jun YouAbstractTo obtain the velocity and temperature field of subway station and the optimized ventilation mode of subway side-platform station, this paper takes the evaluation and optimization of the ventilation for subway side-platform station as main line, builds three dimensional models of original and optimization design of the existed and rebuilt station. And using the two-equation turbulence model as its physics model, the thesis makes computational fluid dynamics (CFD) simulation to subwayside-platform station with the boundary conditions collected for simulation computation through field measurement. It is found that the two-equation turbulence model can be used to predict velocity field and temperature field at the station under some reasonable presumptions in the investigation and study. At last, an optimization ventilation mode of subway side-platform station was put forward.1. IntroductionComputational fluid dynamics (CFD) software is commonly used to simulate fluid flows, particularly in complex environments (Chow and Li, 1999; Zhang et al., 2006;Moureh and Flick, 2003). CFD is capable of simulating a wide variety of fluid problems (Gan and Riffat, 2004;Somarathne et al., 2005; Papakonstantinou et al., 2000;Karimipanah and Awbi, 2002). CFD models can be realistically modeled without investing in more costly experimental method (Betta et al., 2004; Allocca et al., 2003;Moureh and Flick, 2003). So CFD is now a popular design tool for engineers from different disciplines for pursuing an optimum design due to the high cost, complexity, and limited information obtained from experimental methods (Li and Chow, 2003; Vardy et al., 2003; Katolidoy and Jicha,2003). Tunnel ventilation system design can be developed in depth from the predictions of various parameters, such as vehicle emission dispersion, visibility, air velocity, etc. (Li and Chow, 2003; Yau et al., 2003; Gehrke et al., 2003).Earlier CFD simulations of tunnel ventilation system mainly focus on emergency situation as fire condition (Modic, 2003; Carvel et al., 2001; Casale, 2003). Many scientists and research workers (Waterson and Lavedrine,2003; Sigl and Rieker, 2000; Gao et al., 2004; Tajadura et al., 2006) have done much work on this. This paper studied the performance of CFD simulation on subway environment control system which has not been studied by other paper or research report. It is essential to calculate and simulate the different designs before the construction begins, since the investment in subway’s construction is huge and the subway should run up for a few decade years. The ventilation of subway is crucial that the passengers should have fresh and high quality air (Lowndes et al.,2004; Luo and Roux, 2004). Then if emergency occurred that the well-designed ventilation system can save many people’s life and belongings (Chow and Li, 1999; Modic,2003; Carvel et al., 2001). The characteristics of emergency situation have been well investigated, but there have been few studies in air distribution of side-platform in normal conditions.The development of large capacity and high speed computer and computational fluid dynamics technology makes it possible to use CFD technology to predict the air distribution and optimize the design project of subway ventilation system. Based on the human-oriented design intention in subway ventilation system, this study simulated and analyzed the ventilation system of existent station and original design of rebuilt stations of Tianjin subway in China with the professional software AIRPAK, and then found the optimum ventilation project for the ventilation and structure of rebuilt stations.2. Ventilation systemTianjin Metro, the secondly-built subway in China, will be rebuilt to meet the demand of urban development and expected to be available for Beijing 2008 Olympic Games. The existent subway has eight stations, with a total length of km and a km average interval. For sake of saving the cost of engineering, the existent subway will continue to run and the stations will be rebuilt in the rebuilding Line 1 of Tianjin subway. Although different existent stations of Tianjin Metro have differentstructures and geometries, the Southwest Station is the most typical one. So the Southwest Station model was used to simulate and analyze in the study. Its geometry model is shown in Fig. 1.. The structure and original ventilation mode of existent stationT he subway has two run-lines. The structure of Southwest Station is, length width height = m(L) m(W) m(H), which is a typical side-platform station. Each side has only one passageway (length height = m(L) m(H)). The middle of station is the space for passengers to wait for the vehicle. The platform mechanical ventilation is realized with two jet openings located at each end of station and the supply air jets towards train and track. There is no mechanical exhaust system at the station and air is removed mechanically by tunnel fans and naturally by the exits of the station.. The design structure and ventilation of rebuilt stationThe predicted passenger flow volume increase greatly and the dimension of the original station is too small, so in the rebuilding design, the structure of subway station is changed to, (length width height = 132 m(L) m(W) m(H)), and each side has two passageways. The design volume flow of Southwest Station is 400000 m3/h. For most existent stations, the platform height is only m, which is too low to set ceiling ducts.So in the original design, there are two grille vents at each end of the platform to supply fresh air along the platform length direction and two grille vents to jet air breadthways towards trains. The design velocity of each lengthways grille vent ism/s. For each breadthways vent, it is m/s. Under the platform, 80 grille vents of the same velocity m/s, 40 for each platform of the station) are responsible for exhaust.3. CFD simulation and optimizationThe application of CFD simulation in the indoor environment is based on conversation equations of energy, mass and momentum of incompressible air. The study adopted a turbulence energy model that is the two-equation turbulence model advanced by Launder and Spalding. And it integrated the governing equation on the capital control volumes and discretized in the definite grids, at last simulated andcomputed with the AIRPAK software.. Preceding simplifications and presumptionsBecause of mechanical ventilation and the existence of train-driven piston wind, the turbulence on platform is transient and complex. Unless some simplifications and presumptions are made, the mathematics model of three-dimensional flow is not expressed and the result is divergent. While ensuring the reliability of the computation results, some preceding simplifications and presumptions have to be taken.(1)The period of maximum air velocity is paid attention to in the transient process.Apparently the maximum air velocity is reached at the period when train stops at or starts away from the station (Yau et al., 2003;Gehrke et al., 2003), so theperiod the simulation concerns about the best period of time for simulation is from the point when at the section of ‘x = m’ (Fig. 1) and the air velocity begin to change under piston-effect to the point when train totally stops at the station (defined as a ‘pulling-in cycle’).(2) Though the pulling-in cycle is a transient process, it is simplified to a steady process.(3) Because the process is presumed to a steady process, the transient velocity of test sections, which was tested in Southwest Station in pulling-in cycle, is presumed to the time-averaged velocity of test sections.(4) The volume flow driven into the station by pulling-in train is determined by such factors as BR (blocking ratio, the ratio of train cross-section area to tunnelcross-section area), the length of the train and the resistance of station etc. For existent and new stations, BRs are almost the same. Although the length of the lattertrain doubles that of the former which may increase the piston flow volume, the resistance of latter is greater than that of the former which may counteract thisincrease. So it is presumed that the piston flow volume is same for both existent and new station and that the volume flow through the passenger exits is also same. Based on this presumption, the results of the field measurements at the existent station can be used as velocity boundary conditions to predict velocity filed of new station .. Original conditionsTo obtain the boundary conditions for computation and simulation, such as the air velocity and temperature of enclosure, measures were done by times at Southwest Station.All data are recorded during a complete pulling-in cycle. The air velocities were measured by the multichannel anemone-master hotwire anemoscope and infrared thermometer is used to measure the temperature of the walls of the station which are taken as the constant temperature thermal conditions in the simulation.Temperatures of enclosureDivide the platform into five segments and select some typical test positions. The distributing temperature of enclosure is shown in Table 1. It can be seen from Table 1 that all temperatures of enclosure are between 23 _C and 25 _C, there is littledifference in all test positions, and the average temperature is 24 _C. So alltemperatures of subway station’s walls is 24 _C in CFD computation and simulation.Time-averaged air velocity above the platformFig. 1 is the location of test section and the layout of measuring points. The data measured include 12 transient velocities in each section (A –H in Fig. 1), which were deal with section’s time -averaged velocities in the period, 12 point’s velocities ofpassageway, which is used to acquire the average flow, and the velocities of each end of station, which is used to acquire the average piston flow volume.Fig. 2 is the lengthways velocities measured of platform sections, max V is themaximum air velocity, min V is the minimum air velocity and avc V is the average air velocity. Fig. 2 shows that the maximum air velocity is at the passageway. At thepassageway the change of air velocity is about m/s, which is the maximum and indicates that the passageway is the position effected most by the piston wind effect, and the air velocity of section D and E after the passageway is almost the same, which indicates that the piston wind can hardly effect the air velocity after the passageway.CFD模拟和地铁站台的优化通风Feng-Dong Yuan *, Shi-Jun You摘要获得车站的速度和温度领域同时地铁站台的最优方式。