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a r X i v :c o n d -m a t /0201141v 1 [c o n d -m a t .m t r l -s c i ] 9 J a n 2002First-Principles-Based Thermodynamic Description of SolidCopper Using the Tight-Binding ApproachSven P.Rudin,1M.D.Jones,2C.W.Greeff,1and R.C.Albers 11Los Alamos National Laboratory,Los Alamos,NM 875452Department of Physics and Center for Computational Research,University at Buffalo,The State University of New York,Buffalo,NY 14260(February 1,2008)Abstract A tight-binding model is fit to first-principles calculations for copper that include structures distorted according to elastic constants and high-symmetry phonon modes.With the resulting model the first-principles-based phonon dispersion and the free energy are calculated in the quasi-harmonic approximation.The resulting thermal expansion,the temperature-and volume-dependence of the elastic constants,the Debye temperature,and the Gr¨u neisen parameter are compared with available experimental data.PACS numbers:63.20.Dj,64.30.+t,65.40.De,65.40.GrTypeset using REVT E XI.INTRODUCTIONDensity-functional theory(DFT)first-principles electronic-structure methods describe anomaly-free solids such as elemental copper successfully.They achieve high accuracy for quantities such as bulk properties,1surface relaxation and lattice dynamics of the surface,2 as well as the epitaxial Bain path and elastic constants.3DFT methods are routinely used to compute the zero-temperature internal energy,Φ0(V),but also can be used to calculate the free energy contributions from the ions,F I(V,T),and the electrons,F E(V,T),resulting in a complete equation of state,F(V,T)=Φ0(V)+F I(V,T)+F E(V,T).(1)However,the required computational effort is expensive,and an alternative efficient evalu-ation at all volumes and temperatures would be desirable.In this paper we use the computationally less demanding tight-binding(TB)total energy model in conjunction with well chosenfirst-principles calculations.In particular,we use the functionalfitting forms developed at the U.S.Naval Research Laboratory(NRL)for com-puting the total energy within the TB formalism,i.e.,without an external potential.4The model isfit to and accurately reproduces a set offirst-principles calculations with a speed-up of many orders of magnitude.In addition,transferability(i.e.,a TB parameterization that is accurate for a wide variety of crystal structures and atomic arrangements)has been successfully demonstrated for semiconductors as well as for simple and transition metals.4 We believe that the TB method can be used as a highly accurate,but computationally more efficient,surrogate for a fullfirst-principles-based approach to calculate the equation of state for solids.Copper is frequently used as a test material for theoretical methods.5In this paper we have(1)developed an improvedfit for copper that is accurate for phonons,and(2)used this model to calculate a wide range of temperature-and volume-dependent thermodynamic quantities.Copper is furthermore widely employed as a pressure standard in high-pressure research.7 This use is based on correcting P(V)data taken along the shock Hugoniot8to room tem-perature.Such corrections employ model assumptions about the volume dependence of the Gr¨u neisen parameterγ(V),which is difficult to measure independently.Shock heating increases with pressure,making the corrections more significant at high pressure.It is there-fore important to develop theoretical techniques for accurate prediction ofγfor copper at high pressure.Phonons play a major role in the calculations of thermodynamic quantities,and the TBfits are adjusted to more accurately calculate them.Structures corresponding to high-symmetry phonon modes are shown here to aid in refining the model;the resulting phonon density of states can then be used to determine the free energy and hence all thermodynamic quantities of interest.The precision required to calculate phonon frequencies is an order of magnitude higher than that for the lattice constant or bulk modulus,9making this a stringent test for the validity of the tight-binding approach in general and the copper model in particular.The ion–ion free energy of Eq.1is often separated into harmonic and anharmonic parts,F I(V,T)=F H(V,T)+F A(V,T).(2)Normally,the harmonic component is not a function of volume,but is calculated from the effect of small displacements about the zero-temperature equilibrium lattice.In our calcula-tions,we use the quasi-harmonic approximation,which considers small displacements at any fixed volume(lattice constant)within the harmonic approximation,and hence our phonon frequencies become volume dependent.However,our phonon frequencies are calculated at zero temperature for any given volume,and are not temperature dependent.The anharmonic part of the free energy involves terms that arise from the potential energy of the lattice when it is expanded beyond the harmonic part to higher than second order. Such terms are needed at high temperatures,when the phonon amplitudes are large,and ultimately lead to melting.They are also needed to explain thermal expansion effects whenthe harmonic part is based on the equilibrium volume.The quasi-harmonic approximation can handle thermal expansion and the Gr¨u neisen parameter accurately through the volume dependence of the phonons at low temperature.At sufficiently high temperatures,the quasi-harmonic approximation breaks down when the phonon amplitudes become large,and additional anharmonic phonon-phonon corrections are necessary(as indicated in Eq.2).We have not included these anharmonic types of effects in our calculations.Hence we always set F A(V,T)=0,and our calculations will become less reliable at very high temperatures (near melting).In the following section we introduce the basic ideas of the tight-binding method and the first-principles method used to generate thefitting database,and then describe our TBfitting procedures.In the subsequent section we present calculated results for the thermodynamic properties and compare them with experiment.II.FITTING THE MODELA.Tight-binding electronic structureThe tight-binding approach is essentially a parameterized version of thefirst-principles calculations and hence is orders of magnitude more computationally efficient.In DFT meth-ods the secular equation,Hψi,v=ǫi,v Sψi,v,(3)is constructed directly from approximate solutions to the full many-body Hamiltonian,and involves a self-consistent potential that is solved iteratively;whereas in the TB approach the elements of the Hamiltonian(and the overlap matrix)themselves have been parameter-ized.Only two-center terms are considered.10For the non-orthogonal tight-binding model described here this requires73fitted parameters.Of those parameters,thirty each are used to describe the inter-site matrix elements of the Hamiltonian and of the overlap matrix.For each combination of symmetries(ll′m)theform11ish ll′m(r)=(a ll′m+b ll′m r)e−c2ll′m r f c(r),(4)s ll′m(r)= ¯a ll′m+¯b ll′m r e−¯c2ll′m r f c(r),(5) where f c=1/(1+e2(r−r0))is a multiplicative factor included to ensure a smooth cutoffwithincreasing distance.In our calculations we have set r0=16.0Bohr radii.The remaining13parameters determine the on-site terms,which allows the parameter-ization to be applied to structures not included in thefitting database.A measure of thevalence electron density,ρ= i=j e−λ2r ij f c(r ij),(6) where r ij is the interatomic distance,serves to describe the on-site energy,eα=e0α+e1αρ2/3+e2αρ4/3+e3αρ2,(7)for the three orbital typesα,i.e.,s,p,and d.These terms are somewhat similar to an embedded-atom-like form in that the energy changes depending on the nearby arrangements of atoms,and may approximately account for self-consistency effects as the atoms move around.B.Full potential LAPW methodThefirst-principles quality of the tight-binding model results fromfitting to full potential linear augmented plane wave(LAPW)calculations using the reliable WIEN97program suite.12The parameters for thefirst-principles calculations are listed in Table I.The LAPW method divides space into spherical regions centered on the atoms and the remaining interstitial region.The radius of the spheres,the muffin-tin radius R m,must be chosen such that the spheres do not overlap.The basis functions used to represent the wave function are adapted to the regions:radial solutions to the Schr¨o dinger equation in thespheres,plane waves in the interstitial region.The wave functions then are found iteratively within density-functional theory,constrained to match at the boundaries of the different regions.C.Initial Fitting ProcedureWefirstfit the TB method to predict energy differences between the ground-state and non-equilibrium structures.Thefitting database includedfirst-principles energies calculated for the cubic structures.In addition to the total energies of these structures,it proved to be crucial tofit the energy bands at high-symmetry points in reciprocal space.15,16By decom-posing the electronic wave function in terms of the symmetry character of the eigenvalues17 the bands are guided to the correct ordering.The total energies and the band energies can be calculated by starting with a very crude initial tight-binding model that ignores intersite terms;15the errors are then minimized utilizing standard nonlinear least squares algorithms.18Figure1shows the T=0phonon dispersion for fcc copper calculated with the initial model.15The long-wavelength modes nearΓare well described,the short-wavelength modes near the zone boundary display somewhat high frequencies,in particular the longitudinal modes.The reasonable agreement for phonons near the zone centerΓcan be understood by considering the elements of thefitting database.The bulk modulus,i.e.,a linear combination of the elastic constants,is implicitly included in thefit.While this does not guarantee accurate elastic constants,i.e.,good agreement for the slopes of the dispersion nearΓ,it does set the right scale.Furthermore,thefit includes the bcc structure,which is related to the fcc crystal by a tetragonal strain corresponding to the long-wave-vector limit of the longitudinal mode in the[00ξ]direction.The database lacks any information related to the short-wave-vector modes.D.Fitting procedure with distorted structuresIn order to construct a model with an improved phonon dispersion the database was expanded to include additional information on the phonons,in particular,structures that are snapshots of the crystal deformed by particular phonon modes,i.e.,frozen phonons. The undistorted and distorted crystal structures are treated on the same footing in the first-principles calculations and thefitting procedure,implicitly including the differences in energy and hence the frequencies of the phonon modes.The longitudinal and the transverse mode at the high-symmetry point X(q=(0,0,1)) were chosen because of the large discrepancy in frequency(see Fig.1)and because the distorted structures require only a doubling of the unit cell.These distorted structures are considered as additional,distinct structures in the database,to befit to over a range of volumes.The initialfit for copper already contains some of the character of distortions related to the elastic constants:the bulk modulus is explicitly included in the energy as a function of volume,and the tetragonal distortion of the fcc crystal is somewhat reflected byfitting to the bcc structure.For completeness,tetragonally-and trigonally-distorted fcc crystals were added to thefit as distinct structures.These additional structures barely influence the model resulting from thefit;however,thefitting process converges much more quickly when they are included.The cubic structures that were included in the initialfit differ from each other by an energy scale of fractions of electron volts.Phonons require a model tuned to discern energies on a scale that is approximately an order of magnitude smaller.This could be a problem since the minimization procedure tends to ignore small energy differences.For frozen phonons at the zone boundary,where neighboring atoms move against each other,it turns out that amplitudes which are still within the harmonic regime can produce energies that differ from the undistorted structure by fractions of electron volts.The distortions corresponding to elastic constants,however,need to be exaggerated for them to give large enough energydifferences.The trigonal distortion used here compresses the base angle from90◦to75◦, while the tetragonal distortion changes the c/a ratio from unity to1.9.Figure2shows the energy values in thefitting database alongside those of the initial and improved tight-binding models.The volumes of thefirst-principles calculations are limited to structures where the muffin-tin radius R m is smaller than the nearest-neighbor distance, particularly for the strongly-distorted fcc structures the choice of R m=2.0a.u.prohibits strong compression.No such limitations exist for the tight-binding approach;the volumes for which the model is appropriate will become clear in the next section.Figure3shows the errors in the improved model’sfipared to the initialfit,errors for the simple,cubic structures remain about the same.The errors for the tetragonally-distorted structures are small around the equilibrium volume(11.93˚A3),but show a ten-dency to increase as the crystal is compressed.The form of the matrix elements(Eq.4) cannot be expected to allow a high-qualityfit at all volumes;indeed when only a subset of data points are included in thefit the errors show no radical change.Including the distorted structures in thefit improves the transferability of the model. Figure4shows the improved agreement between tight-binding andfirst-principles energies for the diamond structure,which is not included in thefit.The transferability to a structure of such a different coordination is not guaranteed,and our initial model did not reproduce the diamond energies well,nor did the model of the NRL group.5Figure5shows the phonon dispersion calculated with the improved model.Including the distorted fcc structures clearly refines the agreement with the measured values,though the curves do not overlap perfectly:the dispersion of the low-lying transverse modes in the[0ξ1] direction shows a different character,and the high-frequency longitudinal modes remain somewhat large.The discrepancy of the longitudinal frequency at L suggests including this data point in thefit.However,afirst-principles,frozen-phonon calculation of this mode shows better agreement with the tight-binding model than with experiment and was therefore not added to the database.Figure6shows the phonon density of states calculated with the improved model.Thegeneral shape agrees with the data calculated from the Born-von K´a rm´a n force constants fitted to the experimental phonon dispersion along high-symmetry directions.19,20The differ-ence in maximum frequencies and the peak near7THz can be attributed to the discrepancy in the dispersion of the longitudinal mode near L in the[ξξξ]direction.The tight-binding density of states displays more structure around4THz,which may be due to modes in low-symmetry directions that are not part of the experimental force-constant model.The distorted structures added to thefit indeed make for a model that is better suited for phonon calculations.However,while the additional constraints improve the total energies described by the model,the electronic band structure deteriorates.Figure7shows the electronic band structure along two sample high-symmetry directions of fcc copper at the experimental volume.While the initial model agrees well with thefirst-principles band structure,the model improved for thermodynamic quantities loses the good agreement. The resulting electronic density of states,shown in Fig.8,shows the same discrepancy; however,the density of states at the Fermi energy is quite similar,which is important for the temperature-dependent influence of the electrons(see below).It is possible that a better or moreflexible functional form for the distance dependence of the intersite Hamiltonian and overlap matrices are necessary to keep the good transferability and the good agreement with the individual energy bands.III.CALCULATIONS WITH THE TB MODELA.Force ConstantsThe force constants are calculated from the tight-binding model by the direct-force method,21–24which relies on evaluating the forces on all atoms in a simulation cell in which a reference atom(0,i)has been displaced.The large simulation cell consists of primitive cells transposed by vectorsℓ.Due to periodic boundary conditions on the simulation cell, the force on an atom(ℓ,j)is in response to the displaced reference atom(0,i)as well as itsimages transposed by vectors L,F(ℓ,j)=− LφC(ℓ,j;0,i)= Lφ∂uα(0,i)≈−Fβ(ℓ,j)(q),which in turn is the Fourier transform of the system’s force constants,Dαβ(q)=1that break the inversion symmetry with respect to the reference atom have to be duplicated (with adjusted weight)and transposed with a basis vector of the simulation cell to reinstate the symmetry.The cubic symmetry of the fcc crystal allows the calculation of the force constants at a particular volume with a single displacement of the basis atom.Distorted fcc structures no longer have the cubic symmetry,the calculation of the force constants therefore requires the forces to be evaluated for the basis atom displaced in all three Cartesian directions separately. For all calculations the simulation cell contained108atoms and a mesh of4×4×4k-points was used.B.ThermodynamicsAs indicated by Eq.1,the free energy is the internal energy from the tight-binding calculation with entropic terms added from the electrons and the ions.In both terms the relevant physical quantity is the density of states(DOS).The electronic DOS,n(E),the occupation of which is given by the Fermi distribution f(E,T)=[e(E−E f)/(k B T)+1]−1, determines the electrons’contribution to the entropy,S el(T)=−k B [f ln f+(1−f)ln(1−f)]n(E)dE.(12) The phonon DOS,g(ω),contributes through the zero-point energy,1U zero=the phonons,although at low temperatures(where both contributions are very small)and small volumes the percentage rises to about10%.Figure9shows the resulting free-energy as a function of volume for temperatures between 0K to1400K(at ambient pressure copper melts at1356K;melting is an anharmonic effect that lies outside the scope of the quasi-harmonic treatment)in100K increments.A comparison with the free energy for the bcc phase shows the fcc structure at lower free energy for all temperatures and volumes,indicating that the model agrees with experiment in that respect.The free energy as a function of volume and temperature determines the thermal ex-pansion.The temperature-dependent lattice constant derived from the tight-binding model is shown in the inset of Fig.9along with the experimental values.As is typical for GGA-calculations,the tight-binding model overestimates the equilibrium volume by1.4%.The calculated linear expansion coefficient is compared to experimental data in Fig.10and shows good agreement,in particular the characteristic temperature,which is determined by the phonon characteristic temperatures(see below).The shape of the free energy as a function of volume and temperature directly provides the temperature-dependence of the bulk modulus,B(T),which is calculated byfitting a second order Birch equation of state.26The bulk modulus is related to two of the elastic constants by B(T)=1accounted for byfinding the equilibrium volume for each temperature and then calculating the effect of the strain on the free energy of that volume.Figure12shows the calculated T=0elastic constants as a function of volume.The phonon characteristic temperatures,which are defined as moments of the phonon density of states,28ln(k Bθ0)= ln(¯hω) BZ,(15)k Bθ1=43(¯hω)2 BZ 1/2,(17) are shown in Fig.13.The approximate rule of thumbθ2≈θ1≈e1/3θ0holds nicely for the calculated values(inset).At temperatures below the phonon characteristic temperatures individual phonon modes must be considered separately,because they contribute to the crystal’s thermal properties with weights depending on their frequency relative to the temperature.The weight of a mode of branch s with wave vector q is determined by the heat capacity for that mode,c s(q)=∂eβ¯hωs(q)−1.(18)The sum of these individual heat capacities as a function of temperature agrees well with calorimetric data;the comparison is plotted in Fig.14in terms of the Debye temperature θD,which is found such that the Debye model’s heat capacityc V=9k B T(e x−1)2dx(19) is the same as the heat capacity calculated for the tight-binding model at the same temper-ature.The shape of the Debye temperature plotted against temperature remains very similar with compression;the curve itself is shifted upwards with the same volume-dependence as the characteristic phonon temperatures.The heat capacity of each individual phonon mode,combined with the Gr¨u neisen Pa-rameter of that mode,d lnωs(q)γq,s=−q,s c v,s(q).(21) At high temperatures(T>θ2),where all phonon modes contribute equally,γ≈γ0= d lnθ0/d lnρ.At low temperatures only the acoustic phonon modes contribute.Figure15compares the tight-binding results for the Gr¨u neisen parameter with available data.For densities up to near13g/cm3the results roughly agree with the rule of thumb thatγ·ρ=constant.Our values are slightly below the experimental values,indicating that the phonon frequencies do not increase with compression as rapidly as they should.Figure15also shows the calculated temperature-dependence of the Gr¨u neisen parameter. At low temperatures(T<40K)the plot shows a fair amount of structure relative to the high-∼temperature curve.This can be understood from the phonon dispersion shown in Fig.5, where the lowest branch is in the[ξξξ]direction and becomesflat around3THz,frequencies that become relevant in their contribution to the specific heat at temperatures around a third of their energy,i.e.,around50K.This branch is the lowest and hence appearsfirst with increasing temperature,furthermore it appears with a lot of weight as there are eight spatial directions corresponding to these modes.At low temperatures the phonon contribution to the heat capacity is proportional to T3 and vanishes more rapidly than the electronic contribution,which is linear in temperature. Figure16shows the calculated coefficient of the electronic contribution to the heat capacity,π2γel=which is proportional to the density of states at the Fermi energy,n(E F).Compression of the crystal reduces n(E F),i.e.,γel decreases monotonically.IV.SUMMARYThe work presented here is aimed at(1)improving the tight-bindingfit of copper specif-ically for the calculation of thermodynamic properties,and(2)investigating the transfer-ability and range of applicability of the improved model.For the model to be reliable in calculating thermodynamic properties,it must produce a phonon dispersion in good agreement with experiment.The initial model wasfit to first-principles calculations of the total energy at a series of different volumes for the cubic crystal structures.The database offirst-principles calculations was extended here to include fcc structures distorted to reflect high-symmetry phonon modes and the elastic constants;fitting to the extended database yields the improved model which indeed delivers phonon frequencies significantly closer to the experimental values.From the phonon density of states the free energy was calculated,in the quasi-harmonic approximation,as a function of volume and temperature.The temperature-dependence of the minimum of the free energy directly yields the thermal expansion and the linear expansion coefficient,both in good agreement with experiment.The elastic constants are somewhat improved over the initial model,though discrepancies with experiment remain evident.The quantities in the previous paragraph depend on volumes only in the vicinity of the T=0equilibrium volume.The volumes used for the cubic and the distorted fcc structures in thefit extend over a wide range;the equilibrium volume is not treated any differently than other values(down to9.7˚A3,the smallest volume for which distorted structures were fit).This gives some confidence that the model applies to a range beyond the equilibrium volume and its immediate vicinity.Within the quasi-harmonic approximation the volume dependence of the phonon fre-quencies gives a non-zero Gr¨u neisen parameter;the results calculated from the TB model roughly agrees with the empiricalγ·ρ=constant.The magnitude is somewhat low,i.e., the compression-induced stiffening of the crystal remains somewhat weaker than is experi-mentally measured.The compression at which the model clearly fails can be seen from the Gr¨u neisen param-eter as well as the volume dependences of the elastic constants,the electronic contribution to the heat capacity,and the characteristic phonon temperatures.All of these entities vary monotonically with compression until the volume reaches approximately8˚A3,i.e.,a density of roughly13g/cm3,at which point unphysical behavior appears.The unphysical behavior points to the limitations of the model.The Hamiltonian and overlap matrix elements are described by a functional form which can at best approximate the actual behavior within a limited range.For an extended range either the functional form must be modified,e.g.by including higher-order terms in Eq.4,as has been done in a more recent NRL TB copper potential used in Ref.5.The need for modification can also be seen in the electronic band structure,which is degraded by thefitting to distorted fcc structures.V.ACKNOWLEDGMENTWe thank Jon Boettger,Matthias Graf,David Schiferl,and Duane Wallace for helpful and encouraging discussions.This research is supported by the Department of Energy un-der contract W-7405-ENG-36.All FLAPW calculations were performed using the Wien97 package.12Some of the calculations were performed at the National Energy Research Scien-tific Computing Center(NERSC),which is supported by the Office of Science of the U.S. Department of Energy under Contract No.DE-AC03-76SF00098REFERENCES1N.Troullier,J.L.Martins,Phys.Rev.B43,1993(1991).2C.Y.Wei,S.P.Lewis,E.J.Mele,and A.M.Rappe,Phys.Rev.B57,10062(1998).3F.Jona and P.M.Marcus,Phys.Rev.B63,094113/1(2001).4R.E.Cohen,M.J.Mehl,and D.A.Papaconstantopoulos,Phys.Rev.B50,14694(1994); M.J.Mehl and D.A.Papaconstantopoulos,Phys.Rev.B54,4519(1996);S.H.Yang, M.J.Mehl,and D.A.Papaconstantopoulos,Phys.Rev.B57,R2013(1998).5Y.Mishin,M.J.Mehl,D.A.Papaconstantopoulos,A.F.Voter,and J.D.Kress,Phys. 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Global Model-Checking of Infinite-State SystemsNir Piterman and Moshe Y.VardiWeizmann Institute of Science,Department of Computer Science,Rehovot76100,Israel Email:nir.piterman@wisdom.weizmann.ac.il,URL:http://www.wisdom.weizmann.ac.il/nirp Rice University,Department of Computer Science,Houston,TX77251-1892,U.S.A.Email:vardi@,URL:/vardiAbstract.We extend the automata-theoretic framework for reasoning about infinite-state sequential systems to handle also the global model-checking problem.Our frame-work is based on the observation that states of such systems,which carry afinite butunbounded amount of information,can be viewed as nodes in an infinite tree,andtransitions between states can be simulated byfinite-state automata.Checking thatthe system satisfies a temporal property can then be done by a two-way automatonthat navigates through the tree.The framework is known for local model checking.For branching time properties,the framework uses two-way alternating automata.Forlinear time properties,the framework uses two-way path automata.In order to solvethe global model-checking problem we show that for both types of automata,given aregular tree,we can construct a nondeterministic word automaton that accepts all thenodes in the tree from which an accepting run of the automaton can start.1IntroductionAn important research topic over the past decade has been the application of model check-ing to infinite-state systems.A major thrust of research in this area is the application of model checking to infinite-state sequential systems.These are systems in which a state carries afinite,but unbounded,amount of information,e.g.,a pushdown store.The ori-gin of this thrust is the important result by M¨u ller and Schupp that the monadic second-order theory of context-free graphs is decidable[MS85].As the complexity involved in that decidability result is nonelementary,researchers sought decidability results of elemen-tary complexity.This started with Burkart and Steffen,who developed an exponential-time algorithm for model-checking formulas in the alternation-free-calculus with re-spect to context-free graphs[BS92].Researchers then went on to extend this result to the -calculus,on one hand,and to more general graphs on the other hand,such as pushdowngraphs[BS95,Wal96],regular graphs[BQ96],and prefix-recognizable graphs[Cau96]. One of the most powerful results so far is an exponential-time algorithm by Burkart for model checking formulas of the-calculus with respect to prefix-recognizable graphs [Bur97b].See also[BE96,BEM97,Bur97a,FWW97,BS99,BCMS00].3Some of this the-ory has also been reduced to practice.Pushdown model-checkers such as Mops[CW02], Moped[ES01,Sch02],and Bebop[BR00](to name a few)have been developed.Success-ful applications of these model-checkers to the verification of software are reported,for example,in[BR01,CW02].We usually distinguish between local and global model-checking.In thefirst setting we are given a specific state of the system and determine whether it satisfies a given property. In the second setting we compute(afinite representation)of the set of states that satisfy a given property.For many years global model-checking algorithms were the standard;inparticular,CTL model checkers[CES86],and symbolic model-checkers[BCM92]per-form global model-checking.While local model checking holds the promise of reduced computational complexity[SW91]and is more natural for explicit LTL model-checking[CVWY92],global model-checking is especially important where the model-checking is only part of the verification process.For example,in[CKV01,CKKV01]global model-checking is used to supply coverage information,which informs us what parts of the designunder verification are relevant to the specified properties.In[Sha00,LBBO01]an infinite-state system is abstracted into afinite-state system.Global model-checking is performedover thefinite-state system and the result is then used to compute invariants for the infinite-state system.In[PRZ01]results of global model-checking over small instances of a param-eterized system are generalized to invariants for every value of the system’s parameter.An automata-theoretic framework for reasoning about infinite-state sequential systemswas developed in[KV00,KPV02](see exposition in[Cac02a]).The automata-theoretic approach uses the theory of automata as a unifying paradigm for system specification,ver-ification,and synthesis[WVS83,EJ91,Kur94,VW94,KVW00].Automata enable the sep-aration of the logical and the algorithmic aspects of reasoning about systems,yielding clean and asymptotically optimal algorithms.Traditionally automata-theoretic techniquesprovide algorithms only for local model-checking[CVWY92,KV00,KPV02].As model-checking in the automata-theoretic approach is reduced to the emptiness of an automaton, it seems that this limitation to local model checking is inherent to the approach.Forfinite-state systems we can reduce global model-checking to local model-checking by iterating over all the states of the system,which is essentially what happens in symbolic model checking of LTL[BCM92].For infinite-state systems,however,such a reduction can-not be applied.In this paper we remove this limitation of automata-theoretic techniques. We show that the automata-theoretic approach to infinite-state sequential systems general-izes nicely to global model-checking.Thus,all the advantages of using automata-theoretic methods,e.g.,the ability to handle regular labeling and regular fairness constraints,the ability to handle-calculus with backward modalities,and the ability to check realizability [KV00,ATM03],apply also to the more general problem of global model checking.We use two-way tree alternating automata to reason about properties of infinite-state sequential systems.The idea is based on the observation that states of such systems can be viewed as nodes in an infinite tree,and transitions between states can be simulated byfinite-state automata.Checking that the system satisfies a temporal property can then be done by a two-way alternating automaton.Local model checking is then reduced to emptiness or membership problems for two-way tree automataIn this work,we give a solution to the global model-checking problem.The set of con-figurations of a prefix-recognizable system satisfying a-calculus property can be infinite, but it is regular,so it isfinitely represented.We show how to construct a nondeterminis-tic word automaton that accepts all the configurations of the system that satisfy(resp.,do not satisfy)a branching-time(resp.,linear-time)property.In order to do that,we study the global membership problem for two-way alternating parity tree automata and two-way path automata.Given a regular tree,the global membership problem is tofind the set of states of the automaton and locations on the tree from which the automaton accepts the tree.We show that in both cases the question is not harder than the simple membership problem(is the tree accepted from the root and the initial state).Our result matches the upper bounds for global model checking established in[BEM97,EHRS00,EKS01,KPV02,Cac02b].Our contribution is in showing how this can be done uniformly in an automata-theoretic frame-work rather than via an eclectic collection of techniques.2Preliminaries2.1Labeled Rewrite SystemsA labeled transition graph is,where is afinite set of labels,is a (possibly infinite)set of states,is a labeling function,is a transition relation,and is an initial state.When,we say that is a successor of,and is a predecessor of.For a state,we denote by,the graph with as its initial state.An-computation is an infinite sequence of statessuch that and for all,we have.An-computationinduces the-trace.Let be the set of all-traces.A rewrite system is,where is afinite set of labels,is afinite alphabet,is afinite set of states,is a labeling function that depends only on thefirst letter of(Thus,we may write.Note that the label is defined also for the case that is the empty word).Thefinite set of rewrite rules is defined below.The set of configurations of the system is.Intuitively,the system hasfinitely many control states and an unbounded store.Thus,in a configuration we refer to as the control state and to as the store.We consider here two types of rewrite systems.In a pushdown system,each rewrite rule is.Thus,.In a prefix-recognizable system,each rewrite rule is reg reg reg,where reg is the set of regular expressions over.Thus,reg reg reg. For a word and a regular expression reg we write to denote that is in the language of the regular expression.We note that the standard definition of prefix-recognizable systems does not include control states.Indeed,a prefix-recognizable system without states can simulate a prefix-recognizable system with states by having the state as thefirst letter of the unbounded store.We use prefix-recognizable systems with control states for the sake of uniform notation.The rewrite system starting in configuration induces the labeled transition graph.The states of are the configurations of and if there is a rewrite rule leading from configurationto configuration.Formally,if is a pushdown system,thenif;and if is a prefix-recognizable system,thenif there are regular expressions,,and such that,,,and .Note that in order to apply a rewrite rule in stateof a pushdown graph,we only need to match the state and thefirst letter of with the second element of a rule.On the other hand,in an application of a rewrite rule in a prefix-recognizable graph,we have to match the state and we shouldfind a partition of to a prefix that belongs to the second element of the rule and a suffix that belongs to the third element.A labeled transition graph that is induced by a pushdown system is called a pushdown graph.A labeled transition system that is induced by a prefix-recognizable system is called a prefix-recognizable graph.Example1.The pushdown system,,with,,,,,,,,,,,,and,,andwhen starting from in-duces the labeled transition graph on the right.Consider a prefix-recognizable system.For a rewrite rule ,,,,,let,for,be the non-deterministic automaton for the language of the regular expression.We assume that all initial states have no incoming edges and that all accepting states have no outgoing edges. We collect all the states of all the automata for,,and regular expressions.Formally, ,,and.We define the size of as the space required in order to encode the rewrite rules in and the labeling function.Thus,in a pushdown system,,and in a prefix-recognizable system,.We are interested in specifications expressed in the-calculus[Koz83]and in LTL [Pnu77].For introduction to these logics we refer the reader to[Eme97].We want to model check pushdown and prefix-recognizable systems with respect to specifications in these logics.We differentiate between local and global model-checking.In local model-checking, given a graph and a specification,one has to determine whether satisfies.In global model-checking we are interested in the set of configurations such that satisfies.As is infinite,we hope tofind afinite representation for this set.It is known that the set of states of a prefix-recognizable system satisfying a monadic second-order formula is regular [Cau96,Rab72],which implies that this also holds for pushdown systems and for-calculus and LTL specifications.In this paper,we extend the automata-theoretic approach to model-checking of sequen-tial infinite state systems[KV00,KPV02]to global model-checking.Our model-checking algorithm returns a nondeterministicfinite automaton on words(NFW,for short)recogniz-ing the set of configurations that satisfy(not satisfy,in the case of LTL)the specification. Our results match the previously known upper bounds[EHRS00,EKS01,Cac02b].4 Theorem1.Global model-checking for a system and a specification is solvable–in time and space,where is a pushdown system and is an LTL formula.–in time and space,where is a prefix-recognizable system and is an LTL formula.–in time,where is a prefix-recognizable system and is a-calculus formula of alternation depth.2.2Alternating Two-way AutomataGiven afinite set of directions,an-tree is a set such that if,where and,then also.The elements of are called nodes,and the empty word is the root of.For every and,the node is the parent of.Each node of has a direction in.The direction of the root is the symbol(we assume that).The direction of a node is.We denote by the direction of node .An-tree is a full infinite tree if.A path of a tree is a set such that and for every there exists a unique such that.Note that our definitions here dualize the standard definitions(e.g.,when,the successors of the node are and,rather than and)5.Given twofinite sets and,a-labeled-tree is a pair where is an-tree and maps each node of to a letter in.When and are not important or clear from the context,we call a labeled tree.We say that an-labeled -tree is-exhaustive if for every node,we have.A tree is regular if it is the unwinding of somefinite labeled graph.More formally,a transducer is a tuple,where is afinite set of directions,is afinite alphabet,is afinite set of states,is a start state,is a deterministic transition function,and is a labeling function.We definein the standard way:and.Intuitively,a transducer is a labeledfinite graph with a designated start node,where the edges are labeled by and the nodes are labeled by.A-labeled-tree is regular if there exists a transducer,such that for every,we have.We then say that the size of,denoted,is,the number of states of.Alternating automata on infinite trees generalize nondeterministic tree automata and werefirst introduced in[MS87].Here we describe alternating two-way tree automata.For afinite set,let be the set of positive Boolean formulas over(i.e.,boolean formulas built from elements in using and),where we also allow the formulas and,and,as usual,has precedence over.For a set and a formula ,we say that satisfies iff assigning to elements in and assigning to elements in makes true.For a set of directions,the extension of is the set(we assume that).An alternating two-way automaton over-labeled-trees is a tuple,where is the input alphabet,is afinite set of states,is an initial state,is the transition function,and specifies the acceptance condition.A run of an alternating automaton over a labeled tree is a labeled treein which every node is labeled by an element of.A node in,labeled by, describes a copy of the automaton that is in the state and reads the node of.Many nodes of can correspond to the same node of;there is no one-to-one correspondence between the nodes of the run and the nodes of the tree.The labels of a node and its succes-sors have to satisfy the transition function.Formally,a run is a-labeled-tree, for some set of directions,where and satisfies the following:1.and.2.Consider with and.Then there is a(possiblyempty)set,such that satisfies,and for all,there is such that and the following hold:–If,then.–If,then.–If,then,for some and,and. Thus,-transitions leave the automaton on the same node of the input tree,and-transitions take it up to the parent node.Note that the automaton cannot go up the root of the input tree,as whenever,we require that.A run is accepting if all its infinite paths satisfy the acceptance condition.We consider here parity acceptance conditions[EJ91].A parity condition over a state set is a finite sequence of subsets of,where. The number of sets is called the index of.Given a run and an infinite path ,let be such that if and only if there are infinitely many for which.That is,is the set of states that appear infinitely often in.A path satisfies the condition if there is an even for whichand.An automaton accepts a labeled tree if and only if there exists a run that accepts it.We denote by the set of all-labeled trees that accepts.The automaton is nonempty iff.The B¨u chi acceptance condition[B¨u c62]is a private case of parity of index3.The B¨u chi condition is equivalent to the parity condition.A path satisfies the B¨u chi condition iff.We say that is one-way if is restricted to formulas in.We say that is nondeterministic if its transitions are of the form),in such cases we write.In the case that,is a word automaton.Theorem2.Given an alternating two-way parity tree automaton with states and in-dex,we can construct an equivalent nondeterministic one-way parity tree automaton whose number of states is exponential in and whose index is linear in[Var98],and we can check the nonemptiness of in time exponential in[EJS93].The membership problem of an automaton and a regular tree is to determine whether accepts;or equivalently whether.For and,we say that accepts from if there exists an accepting run of that starts from state reading node(i.e.a run satisfying Condition2above where the root of the run tree is labeled by).The global membership problem of and regular tree is to determine the set accepts from.We use acronyms in to denote the different types of automata.Thefirst symbol stands for the type of movement of the automaton:1for1-way automata(we often omit the1)and2for2-way automata.The second symbol stands for the branching mode of the automaton:for alternating and for nondeterministic. The third symbol stands for the type of acceptance used by the automaton:for B¨u chi and for parity,and the last symbol stands for the object the automaton is reading:for words and for trees.For example,a2APT is a2-way alternating parity tree automaton and an NBW is a1-way nondeterministic B¨u chi word automaton.2.3Alternating Automata on Labeled Transition GraphsConsider a labeled transition graph.Let.An alter-nating automaton on labeled transition graphs(graph automaton,for short)[Wil99]6is a tuple,where,,,and are as in alternating two-way automata, and is the transition function.Intuitively,when is in state and it reads a state of,fulfilling an atom(or,for short)requires to send a copy in state to some successor of.Similarly,fulfilling an atom requires to send copies in state to all the successors of.Thus,graph automata cannot distinguish between the various successors of a state and treat them in an existential or universal way.Like runs of alternating two-way automata,a run of a graph automaton over a labeled transition graph is a labeled tree in which every node is labeled by an element of.A node labeled by,describes a copy of the automaton that is in the state of and reads the state of.Formally,a run is a-labeled-tree, where is some set of directions,,and satisfies the following:1.and.2.Consider with and.Then there is a(possiblyempty)set,such that satisfies,and for all,we have:–If,then there is such that and.–If,then for every successor of,there is such that and.–If,then there is a successor of and such that and.Acceptance is defined as in2APT runs.The graph is accepted by if there is an ac-cepting run on it.We denote by the set of all graphs that accepts and by the automaton with as its initial state.We use graph automata as our branching time specification language.We say that a labeled transition graph satisfies a graph automaton,denoted,if accepts. Graph automata have the same expressive power as the-calculus.Formally, Theorem3.[Wil99]Given a-calculus formula,of length and alternation depth, we can construct a graph parity automaton such that is exactly the set of graphs satisfying.The automaton has states and index.We use NBW as our linear time specification language.We say that a labeled transition graph satisfies an NBW,denoted,if(where is the initial state of)7.We are especially interested in cases where,for some set ofatomic propositions,and in languages definable by NBW or formulas of the linear temporal logic LTL[Pnu77].For an LTL formula,the language of,denoted ,is the set of infinite words that satisfy.Theorem4.[VW94]For every LTL formula,there exists an NBW with states such that.Given a graph and a specification,the global model-checking problem is to com-pute the set of configurations of such that.Whether we are interested in branching or linear time model-checking is determined by the type of automaton used.3Global Membership for2APTIn this section we solve the global membership problem for2APT.Consider a2APT and a regular tree.Our construction consists of two stages. First,we modify into a2APT that starts its run from the root of the tree in an idle state.In this idle state it goes to a node in the tree that is marked with a state of.From that node,the new automaton starts a fresh run of from the marked state.We convert into an NPT[Var98].Second,we combine with an NBT that accepts only trees that have exactly one node marked by some state of.We check now the emptiness of this automaton.From the emptiness information we derive an NFW that accepts a word in state(i.e.the run ends in state of;state is an accepting state of) iff accepts from.Theorem5.Consider a2APT and a regular tree.We can construct an NFW that accepts the word in stateiff accepts from.Let be the number of states of and its index;the NFW is constructible in time exponential in.Proof.Let and.Consider the2APTwhere,is a new initial state and is defined as follows.andandClearly,accepts a-labeled tree iff there is a node in labeled byfor some and accepts the projection of on when it starts its run from node in state.Let be the NPT that accepts exactly those trees accepted by[Var98].If has states and index then hasstates and index.Let be the transducer inducing the labeling of.We con-struct an NBT that accepts-labeled trees whose projection on is and have exactly one node marked by a state in.Consider the NBTwhere is defined as follows.For letbe the tuple where the-th element is the-successor of and all elements are marked by except for the-th element,which is marked by.Intuitively,a state accepts a subtree all of whose nodes are marked by.A state means that is still searching for the unique node labeled by a state in.The transition to means that is looking for that node in direction.andandandOtherwiseClearly,accepts a-labeled tree iff the projection of on is exactly and all nodes of are labeled by except one node labeled by some state.Let be the product of and where,,is defined below and is obtained from by setting and for we have.Thus,states are visitedfinitely often,and otherwise only the state of is important for acceptance.For every stateand letter the transition function is defined by:andEvery tree accepted by has a unique node labeled by a state of and all other nodes are labeled by,and if is the projection of on then accepts from.The number of states of is and its index is.We can check whether accepts the empty language in time exponential in.The emptiness algorithm returns the set of states of whose language is not empty[EJS93].From now on we remove from the state space of all states whose language is empty.Thus,transitions of contain only tuples such that all states in the tuple have non empty language.We are ready to construct the NFW.The states of are the states of in in addition to(the set of states of).Every state in is an accepting sink of .For the transition of we follow transitions of-states.Once we can transition into a tuple where the is removed,we transition into the appropriate accepting states.Let,where,is the initial state of,is the set of states of(accepting sinks in),and is defined below.Consider a state.Its transition in is of the formandandFor every tuple,we add to .For every tuple,we add the letter used in the transition to.Lemma1.A word is accepted by in a state iff accepts from. The proof of the Lemma is in Appendix A.4Global Model Checking of Branching Time PropertiesIn this section we solve the global model-checking for branching time specifications by a reduction to the global membership problem for2APT.The construction is somewhat dif-ferent from the construction in[KV00]as we use the global-membership of2APT instead of the emptiness of2APT.Consider a rewrite system.Recall that a configuration of is a pair.Thus,the store corresponds to a node in the full infinite-tree.An automaton that reads the tree can memorize in its state space the state component of the configuration and refer to the location of its reading head in as the store.We would like the automaton to“know”the location of its reading head in.A straightforward way to do so is to label a node by.This,however,involves an infinite alphabet.We show that labeling every node in by its direction is sufficiently informative to provide the2APT with the information it needs in order to simulate transitions of the rewrite system. Let be the tree where.Theorem6.Given a pushdown system and a graph automaton,there is a2APT on-trees and a function that associates states of with states of such that accepts from iff.The automaton has states,and has the same index as.States of the automaton have three components:a state of,a state of,and navi-gation information.States are partitioned into action states and navigation states.An action state that includes state of and state of and reads node(in an accepting run of )means that starting in accepts.A navigation state,contains the informa-tion on how to navigate to a new node in the tree.From an action state,in order to check that the requirements imposed by state of on the graph,the transition is simulated by by sending a copy that navigates to some successor of configurationand from there applies new actions.A transition is simulated by by sending copies that navigate to all the successors of configuration.The full proof of Theorem6is in Appendix B.1.We extend the above construction to prefix-recognizable systems.Again the two-way automaton navigates through the full-tree and simulates transitions of the rewrite system. In order to apply a rewrite rule,the automaton goes up the tree along a word in,it checks that the suffix is in by sending a separate copy to the root,and moves downwards along a word in.Theorem7.Given a prefix-recognizable system and a graph au-tomaton,there is a2APT on-trees and a function that asso-ciates states of with states of such that accepts from iff.The automaton has states,and has the same index as.As in the case of pushdown systems,states of the automaton contain a state of, a state of,and navigation information.The navigation information,relating to a rewrite rule,is a state of an automaton for.Again,states are partitioned into action and navigation states,this time navigation states are either universal or existential(indicating whether they are part of a transition of or a transition of).In order to simulate a transition,existential navigation states are used.The automaton guesses a transition,it spawns an existential navigation state that contains the initial state of.The navigation phase continues by emulating the run of while going up the tree(towards the root).Once an accepting state ofis reached,spawns an extra navigation process that is in charge of going to the root and ensuring that the current location is a member in(that is,spawn a navigation state with a state of).Simultaneously,proceeds with a navigation state that contains a state of.It emulates a run of backwards and guesses a word in.In order to simulate a transition,universal navigation states are used.In order to check all possible successors of the configuration,the behavior of universal navigation states is dual. The full proof of Theorem7is in Appendix B.2.The constructions in Theorems6and7reduce the global model-checking problem to the global membership problem of a2APT.By Theorem5,we then have the following. Theorem8.Global model-checking for a pushdown or a prefix-recognizable system and a graph automaton,can be solved in time exponential in,where and is the index of.Together with Theorem3,we can conclude with an EXPTIME bound also for the global model-checking problem of-calculus formulas,matching the lower bound in[Wal96]. Note that the fact the same complexity bound holds for pushdown and prefix-recognizable rewrite systems stems from the different definition of in the two cases.。
系统研发与应用System Research and Application生物样本库信息管理系统的设计和实现System Research and Application系统研发与应用2 系统设计生物样本库信息管理系统是以图1 临床资源库网络信息管理系统图2 LIS系统图3 HIS系统 2.1 系统分析生物样本库信息管理系统是技术难点和科技含量较高的生物样本库信息系统。
生物样本库信息技术是与高效运行的医院信息系统（HIS）、电子病历系统（EMR）、检验信息系统（LIS）、放射医疗学管理系统（RIS）对接的医疗结构的基础设施和基础结构的集成，围绕卫生部“基于电子病历的医院信息平台建设技术方案”为宗旨，探索生物样本库平台建设以及无线临床应用，探索建立生物样本库样本的标准化采集，保存流程和生物样本库信息整合，分析及检索查询和尝试移动终端为社区流调数据归档和建立的可行性研究和分析。
本系统是基于SOAP模式的数据采集，采用Broswer/Server（B/S）和Client/Server（C/S）混合架构。
考虑到系统的可扩展性及跨平台性，数据库系统选择采用SQL Severs 2005，实高，系统设计分为表现层，业务逻辑层和数据访问层系统。
系统设有不同图4 EMR系统图5 统一医学语言系统80第8卷第10期System Research and Application系统研发与应用本信息，优化流程，探索开发一套服务于国内转化医学研究的生物样本库信息管理和决策支持系统。
2.3.2 管理权限的设置 优化流程、集中控制采集、分级权限管理解决了物理访问控制的矛盾，避免了数据泄露。
网络边界管理，数据访问限制和数字签名，完善的密码验证和分级权限登录验证机制，及时的数据备份可以从容应对紧急情况下发生的灾难事件，将数据损失降低到最低，加强对接医院端生物样本库的临床信息管理系统的安全管理。
在有限元要素的建立下，确保生物样本患者个人隐私安全进行设计架构。
国家科研论文和科技信息高端交流平台的战略定位与核心特征*李广建，罗立群*本文系国家社会科学基金重大项目“大数据时代知识融合的体系架构、实现模式及实证研究”（项目编号：15ZDB129）研究成果。
摘要建设高端交流平台是对国家科技信息和科技情报体系的顶层设计，也是新时期科技情报研究和工作的指导思想，为科技情报的未来指明了发展方向。
在国家“十四五”规划中，高端交流平台的构建上升到了国家战略高度，是加强我国科学战略力量的重要任务之一，相较于一般意义的平台具有更丰富的内涵和更高的定位。
文章站在全球科技格局和创新生态的高度，从国家科技安全、国家重大需求、科技创新范式等三个维度系统思考高端交流平台的战略定位。
基于对高端交流平台的三个定位、中国国家科技战略发展的根本需要以及对全球科技创新态势的正确认知，结合中国国情，从三个维度阐释高端交流平台构建的核心特征：一是开放，从单向被动不对等开放走向双向主动对等开放交流；二是融合，从成果发布走向知识融合；三是计算，从辅助科学发现的工具走向自主科学发现的主体。
关键词高端交流平台知识融合情报计算科学发现开放科学引用本文格式李广建，罗立群.国家科研论文和科技信息高端交流平台的战略定位与核心特征[J].图书馆论坛，2022，42（1）：13-20.On the Positioning and Core Features of the National High-end Exchange Platform for Scientific and Technological Papers and InformationLI Guangjian &LUO LiqunAbstract The construction of the national high-end exchange platform for scientific and technological papers and information is among the top-level designs of the national scientific and technological information and intelligence system ，and it is vital for the strengthening of China ’s scientific strategic forces.With a view of global scientific andtechnological pattern and innovation ecology ，this paper discusses the positioning of such a national high-end exchange platform ，focusing on national scientific and technological security ，major national needs ，and scientific and technological innovation paradigms.It then makes an analysis of its three core features ，i.e.，openness ，fusion ，and computing.As for openness ，it should transfer from the one-way passive non-equivalent openness to the two-way active reciprocal open communication.As for fusion ，it should transfer from the singlerelease of scientific and technological findings to the fusion of such findings.As for computing ，it should not onlyact as a tool to assist scientific discovery ，but also become a main body of autonomous independent scientific discoveries.Keywords high-end exchange platform ；knowledge fusion ；intelligence computing ；scientific discovery ；open science0引言国家科研论文和科技信息高端交流平台(以下简称“高端交流平台”)已经被正式列入《中华人民共和国国民经济和社会发展第十四个五年规划和2035年远景目标纲要》，这是党和国家在“百年未有之大变局”时代对我国国家科技创新体系的高瞻远瞩，是对国家科技信息和科技情报体系的顶层设计，也是新时期科技情报研究和工作的指导思想，为科技情报的未来指明了发展方向。
（1）阅读下列说明和图，完成问题1至问题4,并在答题纸上自行列表写出答案。
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西北工业大学智慧树知到“信息管理与信息系统”《管理信息系统》网课测试题答案（图片大小可自由调整）第1卷一.综合考核(共15题)1.结构化系统开发方法的每一个阶段都有明确的工作目标。
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A.系统吞吐量B.系统响应时间C.系统处理方式D.系统的输出方式6.大规模集成电路的出现是在计算机硬件发展的()。
A.第二代B.第三代C.第四代D.第五代7.把管理信息系统划分成生产、计划、财务、供销、劳资等子系统，是()。
A、按物理结构进行划分的B、按整体结构进行划分的C、按职能进行划分的D、按层次结构进行划分的8.管理信息系统的技术基础包括()。
A、计算机技术B、网络技术C、数据库技术D、管理技术9.系统总体结构设计是否合理，对提高系统的各项指标至关重要，这些指标包括系统的()等。
A、可行性B、可用性C、可维护性D、易读性和效率10.系统开发是系统建设中工作任务最为繁重的阶段。
()A.错误B.正确11.所谓管理信息系统的结构，指的是()。
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A.数据库B.计算机系统C.数据库管理系统D.DBA14.生命周期法通常是在系统需求比较确定的情况下采用的。
()A.错误B.正确15.数据一般会影响人们的决定，而信息不会。
()A.错误B.正确第2卷一.综合考核(共15题)1.对于经济管理方面的信息来说，传递速度愈快、使用愈及时，那么其()。
A type-A-choking-oriented uni fied model for fast fluidization dynamicsMing-Chuan Zhang ⁎,Chu ZhangSchool of Mechanical Engineering,Shanghai Jiao Tong University,Shanghai 200240,Chinaa b s t r a c ta r t i c l e i n f o Article history:Received 9October 2012Received in revised form 24January 2013Accepted 26January 2013Available online 13March 2013Keywords:Fast fluidizationSeparate-phase model Type A choking Solids holdupHigh-density fast-bedStarting from analysis to Yang's formula for type A choking,a uni fied and self-consistent model for fast flu-idization dynamics,named the separate-phase-coexistence model,was proposed in this paper.The basic assumptions used in the model are that all the gas from outside enters the solid-saturated upward dilute phase,to which the Yang's formula is still applied,yet revised with an effective velocity factor F (β);while the clusters fall down freely at a velocity consistent with their voidage.The impact of falling clusters on the upward dilute phase was considered with the equivalent wall friction,from which the method to predict the apparent solids holdup of upper dilute region was obtained.The force balance for falling clusters was also an-alyzed,from which the cluster voidage was determined.When the cluster viodage reaches its minimum value,a small part of outside gas will invade the cluster,resulting in the so-called “secondary fluidization of clusters ”.It well predicted that the solids holdups of upper dilute region and bottom dense region did not change obviously with further increase of the solid circulation rate,the most impressive feature of high-density fast beds.Further-more,by analogy to bubbling beds,the phenomena of clusters in risers of fast beds were analyzed in a meso-scale mechanism,from which the effective velocity factors of dilute phase F (β)were theoretically determined.And the solid-wall friction factors in Yang's formula and the Harris's correlation for cluster size were also reconstructed based on the experimental data available in the literatures.Without any model parameters adjusted,the uni fied model predicted successfully the type C choking,the solids holdups for both upper dilute region and bottom dense region,and the transitions to high-density fast bed and dense suspension up-flow.The predictions were compared with several hundreds of experimental data available in the literatures,which veri fied well the model's uni fication and acceptable accuracy.©2013Elsevier B.V.All rights reserved.1.IntroductionFast fluidization or circulating fluidized bed (CFB)has attracted people more and more attention in chemical,metallurgy,energy en-gineering and other applied fields as an ef ficient gas-solid contacting technology [1–3].With certain rate of particle circulation,fast fluid-ization provides the possibility that small particles could be operat-ed under quite high gas velocity due to agglomeration of particles in the CFB riser.Under this condition,the fast fluidized bed is charac-terized by a non-uniform axial distribution of particle concentration,where the solids holdup is small in the top,and large in the bottom.The basic requirements to form a fast fluidized bed are generally de-scribed as [4]:i)the circulating solid flux G s is greater than the min-imum value of that G sm ;and ii)for a given solid flux G s >G sm ,the super ficial gas velocity u f is kept within the range of velocities for type A choking and type C choking,i.e.u ch,C b u f b u ch,A .A large number of studies have been done to find how these char-acteristic parameters change with properties of the gas and the solid,the system geometry,and operating conditions.Empirical correla-tions were usually given in the form of non-dimensional criteria.For example,correlations for different types of choking were given by Yang [5,6],Yous fiand Gau [7],and other researchers [8–10].There were also quite a lot empirical correlations of solids holdups for both the upper dilute region and the bottom dense region [11–15].However,most of these studies were carried out separately;there were little physical relations among them.In some cases,incompatible results would be predicted from these empirical correlations,for in-stance u ch,A b u ch,C .On the other hand,the recently recognized “high density fast fluidization (HDFF)”[16]and “dense suspension up-flow (DSU)”[17]have shown some different two-phase-flow behaviors.How these flow regimes relate with the traditional one are also not clear.The present work tried to establish a self-consistent model for fast fluidization dynamics,in which all the characteristic parameters mentioned above can be easily deduced from a same origin;and the uni fied model can be applied for both traditional fast fluidized bed and high density fast fluidized bed.2.Theoretical considerations 2.1.Start point of the modelConcepts of choking in vertical upward co-current gas –solid systems have been used for a long time to describe some critical conditions,atPowder Technology 241(2013)126–141⁎Corresponding author.E-mail address:mczhang@ (M.-C.Zhang).0032-5910/$–see front matter ©2013Elsevier B.V.All rights reserved./10.1016/j.powtec.2013.01.070Contents lists available at SciVerse ScienceDirectPowder Technologyj o u r na l h o me p a g e :ww w.e l s e v i e r.c o m /l o c a t e /p o w t e cwhich the two-phase flow system cannot run properly or ef ficiently.For systems with different application purposes,the de finitions may also be different.In a pneumatic conveying system,the choking is usually de-fined as the onset of particle precipitation downward,which makes the transportation less ef ficient.However,it doesn't breach the system operation as a whole.On the opposite,in a CFB riser the choking is usu-ally de fined as a critical condition,at which a small decrease of operat-ing gas velocity or increase of circulating solid flux will cause signi ficant increase of bed pressure drop,leading to collapse,to some extents,of the whole system.Differences of the two types of choking did not get enough attention until Bi and Grace [18],where the former was de fined as the accumulative choking or type A choking,and the latter as the classical choking or type C choking.Predictions to type A choking and type C choking are obviously im-portant for fast fluidization,since they will determine the allowable ranges for gas velocity or solid circulation flux.There were quite a lot of formulas developed in the past to correlate the gas velocities and the solid fluxes at the two types of choking.However,only one of them can be chosen as the start point of the uni fied model,while the other should be deducted from the chosen one.Considering the re-search history for pneumatic conveying system is much longer than that for fast fluidized bed,and the two-phase flow structure in the for-mer is much simpler than that in the latter,it is believed that the theo-retical and experimental bases for type A choking are more reliable and universal.Among the numerous formulas existed in the literatures for type A choking,the form of Yang's formula [5,6]looks the best,since deriva-tion of the formula involves only two theoretical deductions.The first one is that the terminal velocity of particles for a uniform suspension of voidage εin a riser of diameter D t can be calculated from Eq.(1).u 0t ¼u t ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi1þf p u 2pt!Âε4:7v u u t ð1ÞWhere,u p =G s /[ρs (1−ε)]is the particle velocity,while f p stands for the solid-wall friction factor.This is a theoretically logical formula,and detailed derivation and discussion on that can be found in Yang's series work from 1973to1975[5,19,20].The second deduction is when type A choking happens,the slip velocity between gas and solid,i.e.the terminal velocity of a particlesuspension in a finite diameter riser u t',is just equal to the terminal velocity of a single particle in the in finity u t [5,6].u 0t ¼u tð2ÞThis deduction was actually used in the derivation of Yang's pre-dictive equation [5,6](Eq.(3)),but was not clearly declared and explained in his work.2D t g ε−4:7ch −1 u ch −u t ðÞ2¼f p ð3ÞThe followings are the present authors'try to explain “what does the deduction really mean?”It can be seen from Eq.(1),the first item withsquare root sign ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi1þf pu 2p2gD tr represents the in fluence of wall friction onu t',since it will always be unity in an in finitely wide riser.When D t gets smaller,the wall friction gets greater,then u t'gets greater.The second item with square root sign ffiffiffiffiffiffiffiffiε4:7p represents the in fluence of bed voidage,i.e.the in fluence of surrounding particles.When the particleconcentration (1−ε)gets greater,εgets smaller,then u t 'gets smaller.The reason is that the surrounding particles will cause both increase ofreal gas velocity ffiffiffiffiffiε2pand more flexuous flow-pass of gas around theparticle,then increase of the drag force coef ficient ffiffiffiffiffiffiffiffiε2:7p[21].There-fore,the amendment of u t 'is on the basis of super ficial gas velocity.If we resolve the increased fluid drag on one particle in a uniform suspension into the basal fluid drag on a single particle F f and the sur-plus F s due to the surrounding particles,the overall force balance for the suspension,or a single particle in a long time duration,can be expressed asF f þF s ¼G þW ð4Þwhere,G stands for the gravity of particle or particle suspension,whileW for the wall friction.Comparing the values of F s and W ,two different situations can be distinguished.For a relatively dilute suspension,the drag force caused by the surrounding particles is relatively small,resulting in F s b W ,and then F f >G .The fluid drag given by the gas solely F f is greater than the gravity of the particle,which means that besides supporting the particle there will be something rest to balance the wall friction,simply shown as F f −G =W −F s .This will be a relatively simple dy-namic system centered on each single particles;the relatively indepen-dent movement of these particles will lead to a uniformly dispersed gas-solid two phase flow,i.e.the custom dilute suspension transporta-tion.On the opposite,if we have F s >W and F f b G ,the fluid drag given by the gas F f will no longer be able to support the particle gravity solely,but needs something else from the surrounding particles,simply shown as F f +(F s −W )=G .Then the force balance for any particle will depend more on the others,making the dynamic system more complex and easier to lose its uniformity.For instance,an occasionally local condensation of particles will result in less gas flowing through them and decrease of F f ,which will make these particles to move close further to increase F s as the overall force balance needs.This may probably be the physical reason of cluster formation for the case of F s >W .Therefore,what can be used to separate the two different types of flows mentioned above is just the criteria of F s =W or F f =G ,i.e.u t'=u t from their de finitions.It means that the in fluence of finite riser diameter D t on u t'is just compensated by the in fluence of bed voidage εat the type A choking.At this unique condition,the moving particle looks as if there is neither wall nor surrounding particles.The authors suggest that this is the real meaning of the deduction,and then can be seen as the physical essence of type A choking.Just because of its sound physical meaning,the relationship given by Eq.(3)for the super ficial gas velocity and the bed voidage under solid-saturated conditions (type A choking)can be considered as “inherent ”,then the equation as “constitutive equation ”.However,it should also be pointed out here,the functional relation of u ch and εch is the most important in Eq.(3),but not the value of f p at this moment.Actually,the solid friction factor f p =0.01was taken originally by Yang in 1975[5],and changed later to the present form in 1983[6]f p ¼6:81Â105ρgρs2:2:ð5ÞThe rationality or accuracy of above mentioned values for f p will bediscussed in detail and re-correlation of f p with more experimental data will be made later in Section 3.3.For the time being,the solid fric-tion factor used in the calculations before Section 3.3was f p =0.01,the value given in 1975[5],since it was better than the other according to the accuracy evaluation of Xu et al.[10].2.2.Physical description of the modelAs we discussed above,Eq.(3)shows the relationship of super ficial gas velocity u ch and bed voidage εch under solid-saturated conditions,127M.-C.Zhang,C.Zhang /Powder Technology 241(2013)126–141i.e.type A choking.For a given fluidizing system,when u ch increases,εch will decrease;then the particle concentration (or solids hold-up)(1−εch )increases,and the saturation carrying capacity of gas G s ⁎will increase even faster.G Ãs ¼ρs u ch −u t ðÞ1−εchεchð6ÞThe equation derived here is a little bit different from what was used in Yang's articles [5,6]by 1/εch ,since the modi fication of ffiffiffiffiffiffiffiffiε4:7p includes also the in fluence of the gas velocity ffiffiffiffiffiε2p ,then the real par-ticle velocity is (u ch −u t )/εch .As an example,Fig.1shows the cal-culated results of (1−εch )and G s ⁎varied with u ch for a FCC-air fluidizing system.It can be seen from the figure that the saturation carrying capacity G s ⁎varies with the super ficial gas velocity u ch in an exponential form with power >1.Just because of this special relationship between G s ⁎and u ch ,one can imagine when the circulating solid flux is greater than G s ⁎at a given gas velocity,the system will not completely collapse but run in a more complicated separate-phase-coexistence mode.Some par-ticles will segregate from the gas stream and get agglomerated to form a free-falling dense phase (clusters),which occupies a part of the riser cross-sectional area,but without outer gas getting in;while in the rest of the riser,more concentrated gas with higher ve-locity could carry even more particles upward in the form of dilute phase.Without outer gas getting in clusters is a logical deduction from two-way stability analysis,and is coincident with Mueller and Reh's investigation [22],i.e.“the acceleration of particle inside the strand (cluster)is equal to the acceleration of free fall,which implies that no drag force acts on the particle within the strand ”[21].Let βbe the cross-sectional area fraction occupied by the falling dense phase or clusters,which is also the volume fraction of randomlydistributed clusters;m s−as the corresponding solid flux downward,and m s +as the solid flux upward in solid-saturated dilute phase.Both m s+and m s −are de fined on the basis of the total cross-sectional area,but not their own occupied.Then,the solid flux circulating into the riser G s can be expressed as G s ¼m þs −m −s :ð7ÞThe sketch map for m s +and m s −varied with βat a constant gas velocity is shown in Fig.2.It can be seen from the figure,if we haved m þs d βj β¼0>d m −sd βj β¼0;ð8Þthe separate-phase-coexistence mode can really transport more par-ticles upward in the riser than the saturation carrying capacity ofgas at type A choking,i.e.G s =m s +−m s −>G s ⁎.This will be trueuntil a critical point β=βch is reached,where d m þs d βj β¼βch ¼d m −sd βj β¼βch;ð9Þand the transportable solid flux at the given gas velocity takes its max-imum value G s,max .Beyond this point the separate-phase-coexistence mode has no more ability to balance the excess solid flux,leading to the system being totally “collapsed ”,i.e.the type C choking.The analysis above indicates also that the critical requirement for separate-phase-coexistence mode is d m þs d βj β¼0¼d m −sd βj β¼0:ð10ÞThis criterion can be used for determination of G sm ,which will bediscussed later elsewhere.As a sum,the key points af firmed or the basic assumptions to be used in the uni fied model are as follows:i)the relationship between bed voidage εch and gas velocity u ch given by Yang's formula for type A chok-ing can be seen as “inherent ”or “constitutive ”for solid-saturated dilute phase,which provides the theoretical basis of the model;ii)with neces-sary amendment,this relationship can also be applied for the solid-saturated upward dilute phase when coexisted separate-phases appear;and iii)in the separate-phase-coexistence mode,all the gas from outside enters the solid-saturated upward dilute phase,while the clusters fall down freely at a velocity consistent with their voidage (ex-cept for HDFF or DSU).3.Mathematical model kernels3.1.Model kernels3.1.1.Dilute phase modelAs discussed above,at type A choking,the very beginning of the separate-phase-coexistence mode (β=0),the gas –solid slip velocity can take the value of terminal velocity of a single particle u t .When separate phases visibly appear,due to the impact of falling clusters,it is expected that the saturation carrying capacity per unit gas in the dilute phase will be less than that for β=0.It means that the gas –solid slip velocity in this case has increased.However,this im-pact can also be expressed by decrease of the effective gas velocity in dilute phase,while keeping the slip velocity unchanged.This can123456G *s (k g /m 2s )u ch (m/s)1-c hεFig.1.Saturated carryings G s ⁎and solid concentration (1−εch )at different gas velocity u ch (FCC –air system,ρs =1620kg/m 3,d p =100μm,D t =0.1m).G s ,m sG *schββFig.2.Sketch map for m s +and m s −varied with βat constant gas velocity.128M.-C.Zhang,C.Zhang /Powder Technology 241(2013)126–141be easily done by using an effective velocity factor of dilute phase F (β)b 1in the calculation.Thus,the upward solid flux based on unit dilute phase area can be expressed as G þs ¼ρsu f F βðÞ−u t !1−εch εch ;ð11Þand the relationship between the calculation velocityu Ãch¼u f F βðÞ1−βand the solid-saturated dilute phase viodage εch still fits the revised Yang's formula,as we discussed above.Therefore,the super ficial up-ward solid flux de fined on the basis of the total cross-sectional area of the riser will be m þs ¼ρs u f F βðÞ−u t 1−βðÞ½1−εchεch:ð12ÞFrom the analysis above,the function F (β)chosen should meet the requirements of F βðÞj β¼0¼1;andd F βðÞd βjβ¼0¼0:ð13ÞThe simplest form of that is F βðÞ¼1−c βn:ð14ÞAs βincreases,the impact of falling clusters gets greater andgreater.The upward solids flux of dilute phase m s+will reach its max-imum,then decrease gradually until slugging occurs at β=1.Sincethe solid flux m s+at slugging is still finite but not zero,it can be roughly estimated that m s +|β=1=G s ⁎,i.e.the saturation carryingcapacity of gas at type A choking G s ⁎(see Fig.2).From that,we haveρs u f F 1ðÞ½ 1−εslεsl ¼ρs u f −u t ½ 1−εch ;A εch ;Að15Þwhere F (1)is the value of F (β)at β=1;εsl and εch,A are the bedvoidages for slugging (β=1)and type A choking (β=0),respec-tively.Therefore,F 1ðÞ¼1−u t f1−εch ;A εch ;A εslsl:ð16ÞSuppose the solid span equals to the gas span when slugging occurs,and the voidage equals εmf in the solid span,then we have the average asεsl ¼1−1−εmf ðÞ=2:ð17ÞFinally,the effective velocity factor of dilute phase F (β)can be calcu-lated asF βðÞ¼1−1−F 1ðÞ½ βn:ð18Þ3.1.2.Dense phase modelThe sub-model for dense-phase or falling clusters is relatively simple in form,i.e.m −s ¼ρs βu cl 1−εcl ðÞ:ð19ÞAs we mentioned above,the falling velocity of clusters u cl should be in consistence with their voidage εcl to keep the outside gas flow within the cluster being zero.Therefore,the modi fied Richardson –Zaki'sequation [23]must be satis fied for the force balance of gas-particles in-side of clusters,i.e.u cl ¼u tεcl1m¼u t εm cl :ð20ÞHere,m ¼lg u mfu t=lg εmf ;ð21Þand εmf =0.45was used in the following calculations.However,to determine both εcl and u cl ,a supplementary condi-tion is needed.This will be discussed later in Section 5.1,i.e.the weight of clusters should be balanced by the inter-phase drag,which can be solved with other parameters together through itera-tions.Nevertheless,for the initial value of εcl with iteration or a sim-pli fied calculation (no iteration)a rough estimation is still needed.According to the experimental data collected by Harris and Davidson [24],the solid concentration in clusters can be seen approximately twice of that in the dilute phase.Then,we have εcl ;0¼1−21−εch ðÞ¼2εch −1:ð22Þ3.1.3.Empirical estimation of model parameter nAccording to the derivations above,the model equations can be used in following procedures.i)The type A choking velocity u ch,A is calculated for a given solids flux G s (>G sm ).ii)Decrease super ficialgas velocity to make u f b u ch,A ;then,m s+and m s −are calculated by using different βuntil G s =m s +−m s −is satis fied;the voidage of upward dilute phase εch at the operating velocity u f is then deter-mined.iii)Repeat the steps above until type C choking occur;the type C choking velocity u ch,C is finally ing a different model parameter n ,the variations of dilute phase voidage εch with operating gas velocity u f for a FCC –air system (D t =0.1m,the typ-ical diameter of laboratory scale risers)are shown in Fig.3.It can be seen from the figure,when the operating gas velocity u f is close to u ch,C ,a small reduction of gas velocity will cause a great increase of bed concentration (1−ε).That is the characteristic feature of type C choking.It can also be seen from the figure,as n gets greater,the type C chok-ing velocity calculated gets smaller.Then,the empirical correlation0.920.930.940.950.960.970.980.991.00u f (m/s)u ch,CεFig.3.Variations of dilute phase voidage εch with gas velocity u f calculated from different n for a FCC –air system (D t =0.1m,ρs =1620kg/m 3,d p =100μm,G s =100kg/(m 2s)).129M.-C.Zhang,C.Zhang /Powder Technology 241(2013)126–141given by Yous fiand Gau [7](Eq.(23)),which was veri fied to be the best for type C choking [10],can be used to estimate the proper value of n .u ch ;C ffiffiffiffiffiffiffiffigd pq ¼32Re −0:06tG s g u ch ;C!0:28ð23ÞFrom this kind of “calibration ”,the model parameter n =4.5can be chosen for a simpli fied version of the model without iteration.More fundamental determination of the model parameter n will be given in detail in Section 3.2later.Fig.4shows the comparison be-tween the model predictions with n =4.5and those given by Eq.(23),for both FCC –air and sand –air systems with different parti-cle sizes (50,100,150and 200μm)and solid fluxes (50,100and 200kg/(m 2s)).The result looks quite satisfactory.3.2.Mechanistic determination of F(β)and nThe wake effect was used quite often in the literature to explain how the cluster was formed in a CFB riser.For example,Basu et al.stated in their Book [25],“For a given velocity,the feed rate may be increased to a level where the solid concentration will be so high that one particle will enter the wake of the other.When that hap-pens,the fluid drag on the first particle will decrease,and it will fall under gravity to drop on the trailing particle.The effective surface area of the pair just formed is low,and so the fluid drag will be lower than their combined weight,making the pair fall further to collide with other particles.Thus an increasing number of particles combine together to form particle agglomerates known as clusters.These clusters are,however,not permanent.They are continuously torn apart by the up-flowing gas.Thus,the formation of clusters and their disintegration continue.”Though most of these words were actually from analytical consequence only,the description was quite reasonable.Recently,He et al.carried out an excellent PIV measurement for particle movement in a CFB riser [26]showing clearly the details of this phenomenon as in Fig.5(a)and (b).They described in their arti-cle,“it can be easily seen that a cluster is followed by a wake,in which particles move downward quickly ”,and “when a cluster is passing by,the particles are dragged down at a higher velocity ”.Be-sides a very clear veri fication of the wake effect,the measurement showed that those particles moved towards the cluster at velocitiesof the same order for up-flowing ones,which will result in a notable deposition on the back side of the cluster.And due to the size limitation for a stable cluster,there must be the same quantities of particles pouring out the cluster from its nose.The continuous deposition and pour out of those particles will cause the downward displacement of particles inside the cluster,too.The particles moving towards the clus-ter in the wake,the inside displacement,and the front pour out can then be viewed as an integrated penetration of these particles through the cluster.From this point of view,the phenomenon can be analogous to what happens around a rising bubble in a bubbling bed as shown in Fig.1(c)[27].It can be seen that except the directions are opposite-down,the flow patterns of the two are quite similar.Furthermore,through phase reversal the following correspondences could be easily af-firmed.(1)A falling cluster with concentrated particles vs.a rising bubble with null or few particles;(2)the upward dilute flow around the cluster vs.the downward dense particle flow around the bubble;(3)the downward penetrating particle flow through the cluster vs.the upward penetrating gas flow through the bubble.The scenarios in CFB risers described above are quite in consistent with the results from detailed numerical simulations by combining the two-fluid model with the EMMS approach [21],i.e.“the particles tend to enter into clusters instead of suspending in dilute broth (phase),whereas the gas tends to pass around,instead of penetrating through,the dense cluster phase.”[21]Then,some results obtained for bubbling beds may also be used to estimate the in fluence of fall-ing clusters on the upward dilute phase,as explained below.Suppose that a spherical cluster of voidage εcl falls down in a di-lute suspension with a constant pressure gradient d p /dz =−J ,i.e.the pressure drop per unit riser height which can be calculated in the way described in Section 4.1below.If we put the cluster in a sur-rounding bed with the same voidage εcl ,the through flow penetrat-ing the cluster u fu under the pressure gradient −J would be the same as that in the surroundings.On the other hand,the cluster is also penetrated by a particle flow from the opposite direction,which results in a downward displacement of particles at u sd inside the cluster,as we discussed above.To keep the gas flow inside the cluster being null,which is a primer assumption for the model estab-lishment,there must be u sd =u fu .Just because the null flows inside of cluster,the pressures everywhere inside are constant.Therefore,the isobars above and below the cluster will get condensed,which will then suck more gas flowing through the cluster.Though the cluster is full of particles,it functions as an empty bubble.According to the well-known Davidson's model for a single bubble immerged in an incipiently fluidized bed [27],the total volume flow-rate through the cluster is q ¼3u pen πR 2clð24Þwhere R cl stands for the radius of the cluster,and u pen stands for the super ficial percolation velocity in a packed bed of voidage εcl under the pressure gradient −J .It can be easily calculated by the Ergun's equation or the extended Ergun's equations [21,28],i.e.Ergun's for εb 0.8and Wen's for ε≥0.8.Then the interstitial gas velocity through the cluster,which will be counteracted finally by the down-ward displacement of particles inside,can be written asu sd ¼u fu ¼3u pen =εcl :ð25ÞIn bubbling fluidized beds [27],rising bubbles can be classi fied as the fast bubble or the slow bubble,according to the ratio of the bub-ble rising velocity u br to the interstitial gas velocity far away from the bubble u f,∞.For a fast bubble [27],i.e.u br >u f,∞,the gas leaves at the top of the bubble will be sucked in again from the bottom;the1.01.52.02.53.03.54.0u c h ,C (m /s ,t h i s m o d e l )u ch,C (m/s,Yousfi & Gau)parison of model predictions for type C choking (n =4.5,D t =0.1m)and those from Yous fiand Gau [7].130M.-C.Zhang,C.Zhang /Powder Technology 241(2013)126–141。
企业管理信息系统的发展历程0940408206 赵学连一. 管理信息系统的发展经历了六个时期：（1） 订货点法 OPM（2） 物料需求计划 MRP（3） 闭环MRP（4） 制造资源计划MRPII（5） 企业资源计划 ERP（6） 计算机集成制造系统 CIMS二．分析各阶段的内容，产生原因，特点，适用等A 订货点法 ：①基本原理:对生产中需要的各种物料，根据生产需要量及其供应和存储条件，规定一个安全库存量和订货点库存量。
各种物料的库存量在日常消耗中不得低于它的安全库存量，随着物料的逐渐耗用，当库存量降到某一库存水平时（订货点量），就要下达订单以补充库存。
如下图所示订货点法②特点：根据历史记录来推测未来的需求，假定订货提前期是不变的，每次订货的批量是相等的，订购时间是随着物资库存量降到订货点的时间的不同而变化的。
因此，在生产对物资的消耗速度不均匀的情况下，可以利用订货点派人订货来适应物资消耗速度的变化，保持物资储备的合理性。
③适用范围：它不仅适用于原辅材料的采购供应，还可应用于企业自制零部件的生产制造。
适用于需求或消费量比较稳定的物料，因此，适合于大批量的生产组织方式。
④不足：（1）订货点法能够为企业正常生产提供足够的原料，但会有库存积压现象(2)订货点法对原料的需求相对较高，要求原料具有以下特点：A 对各种物料的需求是相对独立的B 物料需求是连续发生的C 提前期是已知的和固定的数量D库存消耗之后应立即补充E无法解决何时订货的问题B物料需求计划 MRP：①产生的原因：A 20世纪60年代中期，人们发现传统的订货点法不能适应新的情况：（1）新产品，新材料的不断涌现（2）客户越来越挑剔B 由于传统的订货点法并不需要了解也不提供以下情况：销售计划或客户订单情况；现有库存数量；各种产品的组成结构；各种部件的组成结构；材料消耗定额；采购订货周期（从外部采购的原材料等）；生产加工周期（自制零部件）。
因此需要有新的计划数据和计划方法。
Toward a Glucose Biosensor Based on Surface-EnhancedRaman ScatteringKaren E.Shafer-Peltier,†,‡Christy L.Haynes,‡Matthew R.Glucksberg,†andRichard P.Van Duyne*,‡Contribution from the Department of Biomedical Engineering and Department of Chemistry,Northwestern Uni V ersity E V anston,Illinois60208-3113Received August22,2002;E-mail:vanduyne@Abstract:This work presents the first step toward a glucose biosensor using surface-enhanced Raman spectroscopy(SERS).Historically,glucose has been extremely difficult to detect by SERS because it has a small normal Raman cross section and adsorbs weakly or not at all to bare silver surfaces.In this paper, we report the first systematic study of the direct detection of glucose using SERS.Glucose is partitioned into an alkanethiol monolayer adsorbed on a silver film over nanosphere(AgFON)surface and thereby,it is preconcentrated within the0-4nm thick zone of electromagnetic field enhancement.The experiments presented herein utilize leave-one-out partial least-squares(LOO-PLS)analysis to demonstrate quantitative glucose detection both over a large(0-250mM)and clinically relevant(0-25mM)concentration range. The root-mean-squared error of prediction(RMSEP)of1.8mM(33.1mg/dL)in the clinical study is near that desired for medical applications(1mM,18mg/dL).Future studies will advance toward true in vivo, real time,minimally invasive sensing.IntroductionAccording to the National Institutes of Health,an estimated 17million people have diabetes mellitus(type I and II)in the United States today,including151000juvenile cases.In1997, a total of$44billion was spent diagnosing,monitoring,and treating diabetes.1In diabetes mellitus,the body either fails to produce or to respond to insulin,which regulates glucose metabolism,resulting in large fluctuations in glucose levels. These fluctuations can cause a range of secondary complications, including kidney disease,heart disease,blindness,nerve damage, and gangrene.Current treatment of diabetes consists of self-regulation of blood glucose levels through frequent monitoring and a combination of diet,medication,and insulin injection, depending on the type of diabetes.Most patients measure their glucose levels by withdrawing small samples of blood using a “finger-stick”apparatus,followed by indirect electrochemical detection of hydrogen peroxide produced by enzymatic oxidation of glucose with glucose oxidase.Sampling in this manner is both painful and inconvenient;however,the electrochemical detection is currently the best technology available for frequent use.As a result,many patients fail to adequately monitor their glucose levels,risking secondary complications.A faster,easier, and less painful method for frequently measuring glucose levels would be of great individual,clinical,and societal benefit. Continuous monitoring of blood glucose would open the door to feedback control of implanted insulin pumps.In fact,the development of a reliable and robust sensor technology is the single stumbling block to the realization of an artificial pancreas. Because of the importance of this issue,many groups are researching methods for minimally invasive,biologically com-patible,quantitative glucose detection.2,3Mid-infrared absorp-tion,one of the more promising techniques,is sensitive to temperature,pH,and competing absorption by water.Current mid-infrared absorption studies utilize an indwelling probe to minimize complicating factors.4In laser polarimetry,another approach being developed,polarized light is rotated by chiral molecules,such as glucose,while passing through the aqueous humor of the eye.This technique is capable of detecting glucose concentrations as low as20mg/dL(∼1.0mM)in vitro; however,the optical activity of the other constituents of the aqueous humor,such as ascorbate and albumin,as well as the birefringence of the cornea,make this approach extremely difficult.5Indirect detection of glucose is also done using fluorescence or other optical techniques.6,7These techniques rely on the enzymatic reaction of glucose to produce the detected byproduct.Biomolecules similar to the analyte can interfere with this multistep process,giving false positives.One technique capable of addressing the major weaknesses of the aforementioned methods(interfering water absorption, overlapping signals from competing analytes,and indirect†Department of Biomedical Engineering.‡Department of Chemistry.(1)In National Institute of Diabetes and Digesti V e and Kidney Diseases;Department of Health and Human Services,Nation Institutes of Health: Bethesda,2002.(2)McNichols,R.J.;Cote,G.L.J.Biomed.Opt.2000,5,5-16.(3)Steffes,P.G.Diabetes Technol.Ther.1999,1,129-133.(4)Klonoff,D.C.;Braig,J.;Sterling,B.;Kramer,C.;Goldberger,D.;Trebino,R.IEEE LEOS Newsletter1998,12,13-14.(5)Cameron,B.D.;Gorde,H.W.;Satheesan,B.;Cote,G.L.Diabetes Technol.Ther.1999,1,125-143.(6)Russell,R.J.;Pishko,M.V.;Gefrides,C.C.;McShane,M.J.;Cote,G.L.Anal.Chem.1999,71,3126-3132.(7)Jin,Z.;Chen,R.;Colon,L.A.Anal.Chem.1997,69,1326-1331.Published on Web12/11/20025889J.AM.CHEM.SOC.2003,125,588-59310.1021/ja028255v CCC:$25.00©2003American Chemical Societymeasurement complications)is vibrational Raman spectroscopy. It has been shown that normal Raman spectroscopy(NRS)can readily detect physiological concentrations of glucose in vitro from a simulated aqueous humor solution.8Using partial-least squares(PLS),Lambert et al.were able to predict glucose levels ranging from50mg/dL(2.8mM,hypoglycemic)to1300mg/ dL(72.2mM,severe diabetic)with a standard error of24.7 mg/dL(1.4mM).Berger et al.were able to detect glucose concentrations with an accuracy of26mg/dL(1.4mM)in serum and79mg/dL(4.4mM)in whole blood using PLS.9Although these are promising results,the laser exposure in both experi-ments is significantly higher than is biologically permissible.10 The high laser powers and long acquisition times are required due to the inherently small normal Raman scattering cross section of glucose,5.6×10-30cm2molecule-1sr-1according to McCreery and co-workers.11To establish the proper context, consider that benzene,a strong Raman scatterer,has a cross section of2.8×10-29cm2molecule-1sr-1and water,a weak Raman scatterer,has a cross section of 1.1×10-31cm2 molecule-1sr-1.11Note that the reported Raman cross section for glucose is only five times smaller than that of benzene and 50times larger than that of water.From the one reported glucose Raman cross section,it is clear that normal Raman scattering should produce sufficiently large signals for effective quantita-tive analysis.Any approach that produces a stronger optical signal from glucose will only improve the feasibility of clinical measurements.Raman optical activity spectroscopy and Raman difference spectroscopy are both examples of highly sensitive Raman techniques capable of detecting small differences in Raman cross section.In both of these techniques,however,the resultant difference signals are very small and long data acquisition times are required.12,13Such an approach is not desirable for a rapid, robust,clinical analysis method.One way to increase the Raman cross section is to exploit resonance Raman spectroscopy.14In the case of glucose,this would require excitation in the deep ultraviolet region(λ∼200nm)of the spectrum.Ultraviolet excitation is unlikely to be appropriate for in vivo sensing due to photodamage of DNA.Alternatively,the Raman cross section can be amplified by surface-enhanced Raman spectroscopy (SERS).Using SERS should retain all of the advantages of normal Raman spectroscopy while achieving significantly stronger signal intensity.SERS is a process whereby the Raman scattering signal is increased when a Raman-active molecule is spatially confined within range of the electromagnetic fields generated upon excitation of the localized surface plasmon resonance of nanostructured noble metal surfaces.The ensemble-averaged Raman signal increases by up to8orders of magnitude,15 whereas the nonensemble-averaged Raman signal can increase by14or15orders of magnitude in special cases.16,17Both chemical and conformational information can be elucidated from SERS.Theoretical analysis suggests that molecules confined within the decay length of the electromagnetic fields,viz.0-4 nm,will exhibit SER spectra even if they are not chemisorbed.18 SERS possesses many desirable characteristics as a tool for the chemical analysis of in vivo molecular species including high specificity,attomole to high zeptomole mass sensitivity,mi-cromolar to picomolar concentration sensitivity,and interfacial generality.19The work presented in this paper represents the first step toward the development of a glucose biosensor using SERS. Silver film over nanospheres(AgFON)substrates are used in this investigation since they have been successfully used in electrochemical,ultrahigh vacuum,and ambient SERS experi-ments.20-22Previously,SERS has been used to detect a wide variety of analytes present at low concentrations,including,but not limited to,pollutants,23explosives,24,25chemical warfare agents,26and DNA.27However,only a few of the existing studies present quantitative results.28,29The success of chemo-metric techniques in the analysis of normal Raman data30 suggests that this same approach may also benefit the quantita-tive analysis of SERS data.This work is an initial effort to explore the systematic response characteristics of this glucose biosensor by combining the strengths of SERS and PLS within a clinically relevant glucose concentration range. Chemometric methods,such as PLS,are used when the spectrum of an analyte of interest is embedded within a complex background spectrum.Long data acquisition times,like those needed in Raman optical activity and Raman difference spectroscopy,are not required when PLS is used to analyze the SERS data.PLS was chosen for data analysis because it is a time efficient technique that requires only knowledge of analyte concentrations in order to verify predictions.The derived calibration vectors show the vibrational features of the analytes found,making it easy to verify that the desired analyte(glucose) is,in fact,the analyte recognized and analyzed by the PLS algorithm.Furthermore,the results presented here demonstrate the utility of a stationary phase or partition layer in preconcentrating(8)Lambert,J.;Storrie-Lombardi,M.;Borchert,M.IEEE LEOS Newsletter1998,12,19-22.(9)Berger,A.J.;Koo,T.-W.;Itzkan,I.;Horowitz,G.;Feld,M.S.Appl.Opt.1999,38,2916-2926.(10)American National Standards Institute,Laser Institute of America(LaserInstitute of America),/PRES/policies/vi1600a.html (11)McCreery,R.L.Raman Spectroscopy for Chemical Analysis;John Wiley&Sons:New York,2000;Vol.157.(12)Bell,A.F.;Barron,L.D.;Hecht,L.Carbohydr.Res.1994,257,11-24.(13)Chaiken,J.;Finney,W.F.;Yang,X.;Knudson,P.E.;Peterson,K.P.;Peterson,C.M.;Weinstock,R.S.;Hagrman,D.Proc.SPIE2001,4254, 216-227.(14)Asher,S.A.Anal.Chem.1993,65,201A-210A.(15)Haynes,C.L.;Van Duyne,R.P.J.Phys.Chem.B2002,submitted.(16)Nie,S.;Emory,S.R.Science1997,275,1102-1106.(17)Kneipp,K.;Wang,Y.;Kneipp,H.;Perelman,L.T.;Itzkan,I.;Dasari,R.R.;Feld,M.S.Phys.Re V.Lett.1997,78,1667-1670.(18)Schatz,G.C.;Van Duyne,R.P.In Handbook of Vibrational Spectroscopy;Chalmers,J.M.,Griffiths,P.R.,Eds.;Wiley:New York,2002;Vol.1, pp759-774.(19)Smith,W.E.;Rodger,C.In Handbook of Vibrational Spectroscopy;Chalmers,J.M.,Griffiths,P.R.,Eds.;John Wiley&Sons:Chichester, U.K.,2002;Vol.1,pp775-784.(20)Dick,L.A.;McFarland,A.D.;Haynes,C.L.;Van Duyne,R.P.J.Phys.Chem.B2002,106,853-860.(21)Litorja,M.;Haynes,C.L.;Haes,A.J.;Jensen,T.R.;Van Duyne,R.P.J.Phys.Chem.B2001,105,6907-6915.(22)Freunscht,P.;Van Duyne,R.P.;Schneider,S.Chem.Phys.Lett.1997,281,372-378.(23)Weissenbacher,N.;Lendl,B.;Frank,J.;Wanzenboeck,H.D.;Mizaikoff,B.;Kellner,R.J.Mol.Struct.1997,410-411,539-542.(24)McHugh,C.J.;Keir,R.;Graham,D.;Smith,mun.2002,580-581.(25)Sylvia,J.M.;Janni,J.A.;Klein,J.D.;Spencer,K.M.Anal.Chem.2000,72,5834-5840.(26)Taranenko,N.;Alarie,J.-P.;Stokes,D.L.;Vo-Dinh,T.J.Raman Spec.1996,27,379-384.(27)Vo Dinh,T.;Stokes,D.L.;Griffin,G.D.;Volkan,M.;Kim,U.J.;Simon,M.I.J.Raman Spec.1999,30,785-793.(28)Loren,A.;Eliasson,C.;Josefson,M.;Murty,K.;Kall,M.;Abrahamsson,J.;Abrahamsson,K.J.Raman Spec.2001,32,971-974.(29)Sulk,R.;Chan,C.;Guicheteau,J.;Gomez,C.;Heyns,J.B.B.;Corcoran,R.;Carron,K.J.Raman Spec.1999,30,853-859.(30)Hanlon,E.B.;Manoharan,R.;Koo,T.-W.;Shafer,K.E.;Motz,J.T.;Fitzmaurice,M.;Kramer,J.R.;Itzkan,I.;Dasari,R.R.;Feld,M.S.Phys.Med.Bio.2000,45,R1-R59.Glucose Biosensor Based on SERS A R T I C L E SJ.AM.CHEM.SOC.9VOL.125,NO.2,2003589glucose within the zone of enhanced electromagnetic fields,enabling SERS detection and quantitation of glucose.A cross-validated PLS algorithm is used to predict glucose concentra-tions both within and outside of the physiologically relevantrange.The achieved prediction error is near the desired accuracyfor biomedical application.We have identified seven milestones to be achieved on thepath to continuous,minimally invasive,quantitative,in vivosensing of glucose in aqueous humor and interstitial fluid.Thefirst,and most critical in terms of scientific feasibility,is thedemonstration of quantitative sensing of glucose using SERS.This work accomplishes exactly that goal.The remaining sixmilestones require(1)optimization of the partition layer,(2)glucose sensing in mixtures,(3)study of nonspecific partition-ing,(4)fabrication of a AgFON substrate on the tip of a fiberoptic probe and in vivo testing of the SERS-active probe,(5)miniaturization of the implanted AgFON surface to micro/nanoscale dimensions,and(6)miniaturization of the detectionapparatus.Experimental SectionMaterials.Ag(99.99%,0.04"diameter)was purchased from D.F.Goldsmith(Evanston,IL).Glass substrates were18mm diameter,No.2coverslips from Fisher Scientific(Fairlawn,VA).Pretreatment ofsubstrates required H2SO4,H2O2,and NH4OH,all purchased from FisherScientific(Fairlawn,VA).Surfactant-free white carboxyl-substitutedpolystyrene latex nanospheres with diameters of390(19.5nm wereobtained from Duke Scientific Corporation(Palo Alto,CA).Tungstenvapor deposition boats were purchased from R.D.Mathis(Long Beach,CA).4-aminothiophenol(90%),L-cystein(97%),3-mercaptoproprionicacid(99+%),11-mercaptoundecanoic acid(95%),1-hexanethiol(95%),1-octanethiol(98%),1-decanethiol(96%),1-hexadecanethiol(92%),3-mercapto-1-propanesufonic acid(Na+salt,90%),benzenethiol(99+%),cyclohexylmercaptan(97%),R-D-Glucose(ACS Reagent Grade)werepurchased from Aldrich(Milwaukee,WI)and used as received.Poly-DL-lysine hydrobromide was purchased from Sigma(St.Louis,MO). Ethanol was purchased from Pharmco(Brookfield,CT).For all stepsof substrate and solution preparation,ultrapure water(18.2MΩcm-1)from a Millipore academic system(Marlborough,MA)was used.AgFON Fabrication and Incubation Procedure.Borosilicate glasssubstrates were pretreated in two steps(1)piranha etch,3:1H2SO4:30%H2O2at80°C for1h,was used to clean the substrate,and(2)base treatment,5:1:1H2O:NH4OH:30%H2O2with sonication for1h,was used to render the surface hydrophilic.Approximately2µL ofundiluted nanosphere solution(4%solids)were drop coated onto eachsubstrate and allowed to dry in ambient conditions.The metal filmswere deposited in a modified Consolidated Vacuum Corporation vapordeposition system31with a base pressure of10-7Torr.The massthickness of Ag in all cases was200nm and deposition rates for eachfilm(1nm/sec)were measured using a Leybold Inficon XTM/2quartz-crystal microbalance(QCM)(East Syracuse,NY).Fresh AgFONsamples were incubated in1mM solutions of the partition layer self-assembled monolayers(SAMs)in ethanol for>12h before beingexposed to glucose solutions of the desired concentration.Each samplewas dosed in a separate vial.The glucose incubation time was arbitrarilychosen to be between10min and1h.The effectiveness of the partitionlayer determines the required incubation time.Glucose solutions rangedin concentration from0to250mM in80%ethanol:20%water.Micro-SERS Apparatus.Spatially resolved SER spectra weremeasured using a modified Nikon Optiphot(Frier Company,Huntley,IL)confocal microscope with a20x objective in backscatteringgeometry.The laser light from a Coherent(Santa Clara,CA)model 590dye laser operating atλex)632.8nm or a Spectra-Physics (Moutainview,CA)model Millenia Vs laser operating atλex)532.0 nm was coupled into a200µm core diameter fiber using a Thorlabs (Newton,NJ)fiber launch.Appropriate Edmund Scientific(Barrington, NJ)interference filters and Kaiser(Ann Arbor,MI)holographic notch filters were placed in the beam path.The backscattered light was collected by an output fiber optic coupled to an Acton(Acton,MA) VM-505monochromator(entrance slit set at250µm)with a Roper Scientific(Trenton,NJ)Spec-10:400B liquid N2-cooled CCD detector.Chemometrics Method.All data processing was performed using MATLAB(MathWorks,Inc.,Natick,MA)and PLS_Toolbox(Eigen-vector Research,Inc.,Manson,WA).Prior to analysis,cosmic rays were removed from the spectra using a derivative filter and the slowly varying background,commonly seen in SERS experiments,was removed by subtracting a fourth-order polynomial.The data were then mean-centered.Data analysis was performed using partial least-squares (PLS)leave-one-out(LOO)analysis.PLS was chosen from among the many chemometric techniques available because it only requires knowledge of the concentrations of the analyte of interest during calibration.32,33Other techniques,such as classical least-squares require knowledge of all of the chemicals present in the sample.Although the precise amount of glucose added to each sample is known in the presented experiments,the knowledge of the other chemicals in the background(e.g.,polystyrene from substrate preparation or impurities in the partition layers)was less certain.PLS has previously been used to analyze data for similar studies.9 Whenever a chemometric technique is used,proper validation is essential to obtain meaningful ually,two separate data sets are used,one for calibration and one for validation.Because of the limited number of samples in the data set,LOO was chosen as the cross-validation technique.34In LOO analysis,one sample at a time is left out of the calibration set.The PLS model is developed using the remaining data and then applied to the lone sample.The predicted concentration of this sample is then compared to the actual concentration and used to evaluate the quality of the model.The process is then repeated,leaving each sample out,one at a time,to build up a set of validation results.LOO cross-validation enables evaluation of a new technique despite a relatively small data set.Prediction error in the calibration and validation sets was determined by calculating the root-mean-squared error of prediction(RMSEP) In this equation,conc represents the actual concentration of a sample, pred represents the predicted concentration for that sample,and n is the total number of samples.The choice of the number of loading vectors to use in the PLS results discussed here was determined by the number of loading vectors needed for the root-mean-squared error of calibration(RMSEC)to stabilize at a minimum value.Results and DiscussionAll attempts to observe glucose on AgFON surfaces using SERS without a partition layer were unsuccessful.This result is in agreement with all previous attempts to measure glucose using SERS that are known to us,except one.The only published SER spectrum of glucose we are aware of uses a two-step surface preparation technique using electrochemically roughened electrodes and colloidal nanoparticles.35Although(31)Hulteen,J.C.;Van Duyne,R.P.J.Vac.Sci.Technol.A1995,13,1553-1558.(32)Geladi,P.;Kowalski,B.R.Anal.Chim.Acta1986,185,1-17.(33)Haaland,D.M.;Thomas,E.V.Anal.Chem.1988,60,1193-1202.(34)Martens,J.;Naes,T.Multi V ariate Calibration;Wiley:Chichester,1989.(35)Mrozek,M.F.;Weaver,M.J.Anal.Chem.2002,74,4069-4075. RMSEP)(conc1-pred1)2+(conc2-pred2)2+...+(conc n-pred n)2n(1)A R T I C L E S Shafer-Peltier et al. 590J.AM.CHEM.SOC.9VOL.125,NO.2,2003this substrate has potential for future work in glucose detection,substrate stability remains to be demonstrated.Electrochemically roughened electrodes are known to have metastable nanostruc-tures;their enhancement factors are strongly potential dependent and,at sufficiently negative potentials,experience irreversible loss of SERS-activity.Also,colloidal nanoparticles aggregate when exposed to media with high ionic strength such as would be encountered in glucose sensing.Excellent stability of SERS-activity has been unambiguously demonstrated for bare AgFON surfaces over potential ranging from Ag oxidation to H 2evolution 20and at high temperatures (<T s )500K)in ultrahigh vacuum.21Similarly,the self-assembled monolayers (SAMs)36used in this work are known to be extremely stable by themselves and as adsorbates on AgFON surfaces.22,37The historic difficulty of SERS detection of glucose must be attributable to its weak or nonexistent binding to bare silver surfaces since its normal Raman cross section should provide sufficient signal.In the experiment performed by Weaver and co-workers,the glucose,apparently,must be trapped in the junction between the roughened electrode and the colloidal nanoparticle.To increase glucose interaction with the AgFON surface,a SAM can be formed on its surface to preconcentrate the analyte of interest (Figure 1),in a manner analogous to that used to create the stationary phase in high performance liquid chromatography (HPLC).22,36,38-40Implementing a partition layer has three advantages:(1)the SAM stabilizes the Ag surface against oxidation;(2)the SAM is exceedingly stable;and (3)preconcentration functionality is built in and tailorable by synthetic control of the partition layer.It is instructive to consider two limiting cases that provide useful estimates of the time response that is potentially achievable.Consider the following kinetic scheme for the SERS-based glucose sensorIn general,glucose must diffuse from bulk solution,G bulk ,tothe solution/alkanethiol SAM,S ,interface where it is adsorbed,G ads ,and then partitioned,G part ,into the SAM.D is the glucose diffusion coefficient,k ads is the bimolecular rate constant for adsorption of glucose at the solution/SAM interface,k des is the unimolecular rate constant for desorption of glucose from the solution/SAM interface,k p is the rate constant for partitioning of glucose into the SAM,and k -p is the rate constant for departitioning of glucose.If diffusion is the rate-limiting step,one can calculate the time,τ,for 1/2monolayer of glucose to accumulate at the solution/SAM interface 41where Γmax is the packing density for a full monolayer and C is the bulk concentration of glucose.Substituting D )6.8×10-6cm 2s -1,Γmax )4.1×10-10mole cm -2,and C )1mM )1.0×10-6mole cm -3,the value of τis 4.8×10-3s.Under these conditions,the SERS-based glucose sensor would be expected to achieve ∼10millisecond time response.Now consider the case where the kinetics of adsorption/desorption and partitioning/departitioning are rate determining.This situation has been examined by Harris and co-workers 42,43in their study of solute retention kinetics at reversed-phase chromatographic surfaces.From a detailed analysis of a temperature-jump relaxation experiment,Harris determined that k ads )(12.7(3)×108M -1s -1,k des )(1.07(0.15)×106s -1,k p )1.8×105s -1,and k -p )1.3×105s -1for the system in which 1-anilino-8-naphthalene sulfonate (ANS)is the solute,C4-silica is the chromatographic surface,and 0.4M NaCl in 50/50CH 3OH/H 2O is the solution.The rate constants measured for other systems including ANS/C18-silica and a neutral solute,N-phen-yl-1-naphthylamine (1-NPN),at C4silica were of similar magnitude.Harris’results allow us to conclude,at least qualitatively,that the rate limiting step in the transport of glucose from bulk solution to the interior of the alkanethiol SAM partition layer where it is detected at the AgFON surface by SERS is diffusion,rather than adsorption/desorption or parti-tioning/departioning.Consequently,we anticipate the future development of SERS-based glucose sensors with real-time response.Several SAMs were tested to determine their effectiveness as a partition layer.The twelve SAMs tested in this work were 4-aminothiophenol,L-cystein,3-mercaptopropionic acid,11-mercaptoundecanoic acid,1-hexanethiol,1-octanethiol,1-de-canethiol (1-DT),1-hexadecanethiol,poly-DL -lysine,3-mercapto-1-propanesufonic acid,benzenethiol,and cyclohexylmercaptan.Of these,only the straight chain alkanethiols were found to be effective partition layers,especially 1-decanethiol (which forms a monolayer on silver ∼1.9nm thick).44It is interesting to note that 1-decanethiol almost completely fills the theoretical first decay length of the electromagnetic fields from the SERS substrate.18The decay length has been estimated at ∼1.5nm in multiple studies as well.45-47Figure 2shows example spectra from the different stages of assembly of the glucose/1-DT/(36)Deschaines,T.O.;Carron,K.T.Appl.Spectrosc.1997,51,1355-1359.(37)Dick,L.A.;Haes,A.J.;Van Duyne,R.P.J.Phys.Chem.B 2000,104,11752-11762.(38)Blanco Gomis,D.;Muro Tamayo,J.;Mangas Alonso,J.Anal.Chim.Acta2001,436,173-180.(39)Yang,L.;Janle,E.;Huang,T.;Gitzen,J.;Kissinger,P.T.;Vreeke,M.;Heller,A.Anal.Chem.1995,34,1326-1331.(40)Carron,K.T.;Kennedy,B.J.Anal.Chem.1995,67,3353-3356.(41)Jung,L.S.;Nelson,K.E.;Stayton,P.S.;Campbell,ngmuir 2000,16,9421-9432.(42)Harris,J.M.;Marshall,D.B.J.Microcolumn Sep.1997,9,185-191.(43)Ren,F.Y.;Harris,J.M.Anal.Chem.1996,68,1651-1657.(44)Walczak,M.M.;Chung,C.;Stole,S.M.;Widrig,C.A.;Porter,M.D.J.Am.Chem.Soc.1991,113,2370-2378.Figure 1.Schematic showing hypothetical glucose concentration gradient created by 1-decanethiol partition layer.G bulk +S y \z k ads k desG ads y \z k pk-pG part(2)τ)πΓmax 216C 2D(3)Glucose Biosensor Based on SERS A R T I C L E SJ.AM.CHEM.SOC.9VOL.125,NO.2,2003591AgFON surface.Figure 2A shows the SER spectrum of 1-DT on a AgFON surface.After 10min incubation in 100mM glucose solution,the SER spectrum in Figure 2B was observed.This spectrum is the superposition of the SER spectra for the partition layer and glucose.Figure 2B clearly shows vibrational features from both the analyte glucose (1123and 1064cm -1)and 1-DT (1099,864,and 681cm -1)constituents.The SERS difference spectrum resulting from subtraction of spectrum 2A from spectrum 2B is shown in Figure 2C.The difference spectrum can be compared directly to the normal Raman spectrum of crystalline glucose shown in Figure 2D.The vibrational bands seen at 914and 840cm -1in the crystalline glucose spectrum (Figure 2D)are not observed in the spectra shown in Figure 2B and 2C because these bands are strongest in crystalline glucose;this phenomenon has been previously observed.35In the initial quantitative experiment,AgFON surfaces with a monolayer of 1-DT were incubated for 10min in a solution containing glucose concentrations ranging from 0to 250mM.SER spectra were then measured from each sample using λex )632.8nm (P laser ) 4.7mW,90s).In all 36cases,the measurements were made on samples in dry,ambient conditions.Upon performing LOO -PLS analysis,21loading vectors were found to minimize the root-mean-squared error of calibration (RMSEC),see inset of Figure 3.The resulting cross-validated glucose concentration predictions,using 21loading vectors,can be seen in Figure 3.The corresponding error of prediction is 3.3mM.This result has been repeated with multiple,similar data sets.Although it is important that quantitative SERS detection is demonstrated in the aforementioned data set,a clinically relevant concentration range is of the highest priority.Accordingly,AgFONs with a monolayer of 1-DT were incubated for an hour in glucose solutions diluted by a factor of 10(0-25mM,0-450mg/dL).SER spectra were then measured from each sample using λex )632.8nm (P laser )3.25mW,30s).In all 13cases,the measurements were made on samples in a simple environ-mentally controlled cell,bathed in the corresponding glucose solution.Upon performing LOO -PLS analysis,10loading vectors were found to minimize the root-mean-squared error of calibration (RMSEC),see inset of Figure 4.The resulting cross-validated glucose concentration predictions,using 10loading vectors,can be seen in Figure 4.The corresponding error of prediction is 1.8mM.Fewer loading vectors and a lower RMSEP in the smaller concentration range experiment may be attributable to the onset of a nonlinear signal versus glucose concentration relationship (i.e.,the nonlinear portion of the(45)Murray,C.A.;Allara,D.L.;Hebard,A.F.;Padden,F.J.Surf.Sci.1982,119,449-478.(46)Kennedy,B.J.;Spaeth,S.;Dickey,M.;Carron,K.T.J.Phys.Chem.B1999,103,3640-3646.(47)Jianxin,Q.Y.;Sun,L.J.Phys.Chem.B 1997,101,8221-8224.Figure 2.Spectra used in quantitative analysis.(A)1-DT monolayer on AgFON substrate,λex )532nm,P )1.25mW,acquisition time )30s.(B)Mixture of 1-DT monolayer and glucose partitioned from a 100mM solution,λex )532nm,P )1.25mW,acquisition time )30s.(C)Residual glucose spectrum produced by subtracting (A)from (B).(D)Normal Raman spectrum of crystalline glucose for comparison,λex )632.8nm,P )5mW,acquisition time )30s.Figure 3.Plot of PLS predicted glucose concentrations versus actual glucose concentrations using leave-one-out cross-validation (21loading vectors).Ag FON samples were made (D )390nm,dm )200nm),incubated for 17h in 1mM 1-DT solution,and dosed in glucose solution (range:0-250mM)for 10min.Each micro-SERS measurement was made under ambient conditions,using λex )632.8nm (4.7mW,90s).Dashed line is not a fit,but rather represents perfect prediction.Inset shows the root-mean-squared error of calibration as a function of number of loading vectors used in the PLSalgorithm.Figure 4.Plot of PLS predicted physiologically relevant glucose concentra-tions versus actual glucose concentrations using leave-one-out cross-validation (10loading vectors).AgFON samples were made (D )390nm,d m )200nm),incubated for 19h in 1mM 1-DT solution,and dosed in glucose solution (range:0-25mM)for 1h.Each micro-SERS measurement was made,whereas samples were in an environmental control cell filled with glucose solution,using λex )632.8nm (3.25mW,30s).Dashed line is not a fit,but rather represents perfect prediction.Inset shows the root-mean-squared error of calibration as a function of number of loading vectors used in the PLS algorithm.A R T I C L E S Shafer-Peltier et al.592J.AM.CHEM.SOC.9VOL.125,NO.2,2003。
1.用二维表数据来表示实体及实体之间联系的数据模型称为（ A ）A. 实体 -联系模型B.层次模型C.网状模型D.关系模型2.一般认为，管理信息系统是一个复杂的社会系统，它是以( B )A. 计算机硬件为主导的系统B.人员为主导的系统C.机构为主导的系统D.计算机网络为主导的系统3．下列选项中属于关键成功因素法内容的是（ C ）A ．了解组织结构B ．识别职能部门的功能和关系C．分析信息需求D．制定组织目标4．信息系统规划的准备工作包括进行人员培训，培训的对象包括（C）．高层管理人员、分析员和规划领导小组成员B．高层和中层管理人员、规划领导小组成员C．分析员、程序员和操作员D．高层、中层和低层管理人员5．下列选项中，对初步调查叙述正确的是（B）．调查目的是从总体上了解系统的结构B．调查内容主要包括有关组织的整体信息、有关人员的信息及有关工作的信息C．调查分析内容主要为人员状况、组织人员对系统开发的态度D．初步调查是在可行性分析的基础上进行的6.改进风险对策的关键是(D )A. 风险识别B.风险分析C.风险规划D.风险监控7.原型法的主要优点之一是( A)A. 便于满足用户需求B.开发过程管理规范C.适于开发规模大、结构复杂的系统D.开发文档齐全8.在数据流程图中，系统输出结果的抵达对象是( A )A. 外部实体B.数据处理C.数据存储D.输出设备9.系统详细调查需要弄清现行系统的基本逻辑功能和( B )A. 组织机构B.外部环境C.信息流程D.基础设施lO. 关系到信息系统能否最大程度发挥作用的关键问题是确定新系统的( A) A. 外部环境 B.管理模式C.业务流程D.数据流程图U/C 矩阵中， C 代表 (D)A 、使用B、完成C、功能 D 、创建12.如果数据流程图呈束状结构，则称它为(B)A. 变换型数据流程图B.事务型数据流程图C.顶层数据流程图D.分层数据流程图13.某学生的代码(学号 )为 2009001，这个代码属于(D)A 、数字码B 、字符码C、混合码D、助记码14.数据库设计的起点是(A)A. 用户需求分析B.概念结构设计C.存储结构设计D.物理结构设计15.系统测试的主要目的是 ( C )A. 提高程序效率B.证明程序正确C.发现程序错误D.改正程序错误16．在进行技术可行性分析中，人员方面主要指的是（ C ）A ．人员的学历层次B ．人员的职称结构C．人员的技术水平和知识结构D．人员的年龄结构17．下列选项中属于间接经济效益的是（ D ）A ．节省人员B ．压缩库存C．产量增加D．改进服务18．下列选项中，对系统开发的必要性叙述正确的是（ C ）A ．必要性是系统分析的基础B ．必要性是可行性分析的前提C．必要性是总体战略规划的基础D．必要性是系统设计的前提19．提高模块独立性的原则是（ B ）A ．高耦合、高内聚B ．低耦合、高内聚C．低耦合、低内聚D．高耦合、低内聚20．下列设计工作中，不属于系统设计阶段工作的是（ B ）A ．代码设计B ．程序设计C．输出设计D．数据库设计21.在公路运输管理中，若车辆通过道路时是免费的，公路的建设、维护费用依靠税收和财政拨款，这种管理控制称（B）A 、反馈控制B、前馈控制C、输入控制D、运行控制22．信息系统开发过程包括的阶段是(B)．系统规划、可行性研究、详细调查、系统设计、系统实施B．系统规划、系统分析、系统设计、系统实施、系统运行与维护C．系统分析、系统设计、系统实施、系统运行与维护、系统评价D．系统分析、系统设计、系统实施、系统转换、系统运行与维护23．软件产品的 ISO 标准是 ( D )A ． ISO9002B ．ISO9003C． ISO9000-2 D． ISO9000-324.决策支持系统是（ D ）A 、数据驱动的B、知识驱动的C、语言驱动的D、模型驱动的25.决策支持系统支持（ B ）A 、结构化和半结构化决策B、结构化和非结构化决策C、半结构化非结构化决策D、半结构化与风险型决策26.信息资源包括（C）A 、信息、物资、货币B、信息、信息生产者、设备C、信息、信息生产者、信息技术D、信息技术、信息生产者、货币27．关于系统设计中的输入设计和输出设计，我们一般做法或看法是（ D ）A 、先做输入设计，再做输出设计B、两者的先后顺序无关紧要C、两者的先后顺序视具体情况决定D、先做输出设计，再做输入设计28．在系统构成上，与一般的决策支持系统相比，智能决策支持系统包括（ D ）A 、数据库B 、模型库C、方法库D、知识库29.除了进行决策分析外，还要着重于决策参与者之间的沟通，这是（ B ）A 、决策支持系统B、群决策支持系统C、智能决策支持系统 D 、主管信息系统30.信息系统能使中层管理人员能做更多的工作，可以减少对基层人员的需求，是组织结构变为（ D）A 、职能化结构B 、直线式结构C、扁平化结构D、菱形式结构31.下列哪项不是事务处理系统的特点（`A ）A 、支持每天的运作B 、逻辑关系简单C、重复性强D、为各管理层提供信息32.计算机集成制造系统主要组成部分是（ A ）。
南开大学智慧树知到“物流管理”《系统工程》网课测试题答案（图片大小可自由调整）第1卷一.综合考核(共15题)1.决策分析的过程包括()A.信息活动阶段B.设计活动阶段C.抉择活动阶段D.实施活动阶段2.系统动力学的特点包括()A.多变量B.定性分析和定量分析相结合C.以仿真实验为基本手段D.可处理高阶次、多回路、非线性的动态复杂系统问题3.模型方法是系统工程的基本方法。
研究系统一般都要通过它的模型来研究，甚至有些系统只能通过模型来研究。
()A.错误B.正确4.系统的可达矩阵可以由邻接矩阵通过布尔代数运算得到。
()A.错误B.正确5.明确问题的重点就是收集资料(考察、测量、调研、需求分析、市场预测)。
了解系统的环境、目的、系统的各组成部分及其联系等。
()A.错误B.正确6.以下关于硬系统方法论和软系统方法论的说法正确的是()A.HSM以工程系统为研究对象，SSM更适合于解决社会经济问题B.HSM的核心是优化分析，SSM的核心是比较学习C.HSM更多的关注定量分析方法，SSM更强调定性与定量相结合的方法D.软系统方法论要优于硬系统方法论7.聚类分析将样本或变量按照亲疏的程度，把性质相近的归为一类，使得同一类中的个体都具有高度的同质性，不同类之间的个体具有高度的异质性。
()A.错误B.正确8.系统仿真的优点在于()A.对于带有随机因素的现实世界系统，仿真经常是唯一的可行的研究方式B.仿真与现实实验相比具有经济性和安全性C.仿真使人们能在较短的时间内研究长时间范围的系统D.系统仿真可以不用去考察现实系统9.Hall三维结构时间维中的运行阶段是指()。
A.生产出系统的构件和整个系统B.对系统进行安装和调试C.系统按照预期目标运作和服务D.以新系统代替或改进旧系统10.AHP方法中求相对权重的计算方法主要有()A.求和法B.方根法C.特征根法D.最小二乘法11.结构模型是指应用有向连接图描述系统各要素间的关系，以表示一个作为要素集合体的系统的模型，是一种以定量分析为主的模型。
运用面向对象的方法对智能集成网络管理系统进行建模(英文)费翔;罗军舟;顾冠群;吴介一
【期刊名称】《东南大学学报：英文版》
【年(卷),期】1998(000)001
【摘要】本文首先介绍了智能集成网络管理（ＩＩＮＭ）的基本概念．为了有效地分析、设计和实现ＩＩＮＭ，本文采用面向对象的方法对ＩＮＭ系统进行建模，其中，域对象类和管理单元对象类用于表示管理器和被管资源，特别地，引入了具有智能行为的特殊对象类—网络管理智能代理（ＮＭＩＡ）用于对网络资源进行有效地管理．
【总页数】5页(P3-7)
【关键词】面向对象方法;计算机通信网络;网络管理
【作者】费翔;罗军舟;顾冠群;吴介一
【作者单位】东南大学计算机科学与工程系;东南大学ＣＩＭＳ研究中心
【正文语种】中文
【中图分类】TP393,
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第一届（2013）复杂管理系统建模与仿真国际研讨会征文通知仿真建模、分析与优化，已经成为解决复杂管理系统的重要手段，正日益受到理论界和实践界的广泛关注。
本会议的目标，旨在为国内外从事复杂管理系统建模与仿真的研究及实践人员提供一个高水平的、专业的论坛，通过思想碰撞与信息交流，探讨系统仿真领域的最新理论和实践，促进相互合作，进而推动仿真建模、分析与优化技术在复杂管理系统中的研究与应用。
本会议邀请了国内外在仿真领域卓有建树的知名学者参加，如美国建模与仿真学会（SCS ）主席J. Fowler 教授，美国冬季仿真会议（WSC ）主任委员会委员J. Smith 教授，2012年WSC 会务主席美国亚利桑那大学Y .J. Son 教授等；以及中国系统仿真学会、广东省系统工程学会推荐的众多专家学者。
会议将请各位专家学者就仿真理论、技术及其应用的最新进展做主题报告，大会还将组织针对性强的分组专题报告与研讨。
第一届（2013）复杂管理系统建模与仿真国际研讨会期待您的参与和交流。
主办单位：中国系统仿真学会离散仿真专业委员会 广东省系统工程学会 深圳大学承办单位：深圳大学（管理学院） 赞助单位：深圳本斯集团 会议地点：中国·广东·深圳会议网站：/ismscs13/ 会议时间：2013年6月1日至2日 会议主席：李凤亮教授，深圳大学副校长 大会执行主席：陈智民教授，深圳大学管理学院院长周泓教授，北京航空航天大学张光宇教授，广东省系统工程学会Dr. J. Fowler ，Arizona StateUniv . (USA) Dr. J. Smith ，Auburn Univ . (USA) Dr. Y .J. Son ，Univ . of Arizona (U SA) 学术委员会主席：周泓教授，北京航空航天大学 学术委员会委员：Dr. J. Fowler ，Arizona StateUniv . (USA) Dr. J. Smith ，Auburn Univ . (USA) Dr. Y .J. Son ，Univ . of Arizona (U SA)Dr. P. Ahrweiler, Univ . of Dublin (Ireland) 范文慧教授，清华大学何世伟教授，北京交通大学 胡斌教授，华中科技大学 隽志才教授，上海交通大学 任佩瑜教授，四川大学卫军胡教授，西安交通大学 魏新教授，广东工业大学徐哲教授，北京航空航天大学 徐宗昌教授，装甲兵工程学院 张光宇教授，广东工业大学 周明教授，深圳大学朱一凡教授，国防科技大学 戈鹏副教授，四川大学刘蕾副教授，电子科技大学 龚晓光副教授，华中科技大学 潘燕春副教授，深圳大学赵晗萍副教授，北京师范大学会议主题：复杂管理系统建模、仿真与分析---理论研究与应用实践。
议题范围（会议议题包括但不限于以下方面）：1. 复杂管理系统建模：基于系统科学/系统工程的方法；2. 仿真建模与分析的理论和方法，如离散事件仿真、系统动力学仿真、多智能体仿真、嵌入式仿真等； 3. 仿真技术与工具；4. 基于仿真的复杂系统优化；5. 基于仿真的风险决策与分析；6. 面向可持续发展的绿色生产与服务：基于仿真的研究；7. 系统仿真与信息系统整合：决策支持与智能化管理； 8. 仿真在复杂管理系统中的应用，包括生产制造系统、供应链与物流系统、交通运输系统、计算机/通讯网络管理系统、医疗服务管理系统、旅游与智慧景区管理系统、作战与综合保障系统，以及循环经济、项目管理、流程再造、工程或技术管理、战略管理、信息管理与电子商务等各大领域。
会议出版物：会议拟将录用的论文以光盘形式出版，并申请国际权威检索机构（EI/ISTP ）审查收录。
论文投递：论文请用英文撰写，MS W ord 编辑，采用电子投稿方式，投递至大会邮箱ismscs2013@ ，论文格式规范详见会议网站/ismscs13/。
最佳论文奖：大会将评选最佳论文奖（最多3篇），并颁发获奖证书。
重要时间：2013年3月1日，论文扩展摘要或全文（最多6页）投稿截止；2013年4月1日，论文录用与否通知；2013年5月15日，大会注册截止；2013年6月1日-2日，会议召开。
费用：版面费800元（5页内），每超一页加100元；会务费700元每位。
版面费和会务费学生减半，详见会议网站。
International Symposium on Modeling and Simulation ofComplex Management Systems (ISMSCS-2013)Topics of Keynote Speeches（1）JOHN FOWLER（USA）Professor and Chair, Arizona State University; Former President, SCSTitle: SIMULATION OF HEALTHCARE SYSTEMSModern industrial engineering, systems engineering, operations management, and operations research methods hold significant p romise for healthcare systems and quality of care research. Among the most promising methods are queuing theory, simulation, and optimiz ation. This presentation will focus on the use of simulation to analyze and improve health care systems. We will discuss some of t he most common uses of simulation in healthcare and will point out some unique challenges in applying simulation to these complex systems.（2）JEFF SMITH（USA）Joe W. Forehand Jr. Professor, Auburn UniversityTitle: SIMULATION-BASED PLANNING AND SCHEDULING IN DISCRETE-PARTS MANUFACTURING ENVIRONMENTSThis talk will focus on the use of discrete-event simulation as a planning and scheduling tool for discrete parts manufacturing environments. Simulation has long been used for design and analysis of these types of manufacturing systems and recent advances in computer hardware, networking, and simulation software have expanded the usefulness of simu lation into the planning and scheduling domains. The talk will present a brief history of this technology and applications and will continue with a concrete example. Finally, an outlook for the future of this technology will be presented.（3）YOUNG-JUN SON（U SA）Professor, University of Arizona; Arizona Engineering FellowTitle:DISTRIBUTED FEDERA TION OF MUL TI-P ARADIGM SIMULA TIONS AND DECISION MODELS FOR PLANNING AND CONTROL: FROM SHOP FLOOR TO TOP FLOORIn this talk, we first discuss simulation-based shop floor planning and control, where 1) on-line simulation is used to evaluate decision alternatives at the planning stage, 2) the same simulation model (executing in the fast mode) used at the planning stage is used as a real-time task generator (real-time simulation) during the control stage, and 3) the real-time simulation drives the manufacturing system by sending and receiving messages to an executor. We then discuss how simulation-based shop floor planning and control can be extended to enterprise level activities (top floor). （4）PETRA AHRWEILER（IRELAND）Professor, University of Dublin; Director, UCD Innovation Research Union (IRU)Title: MODELLING RESEARCH AND INNOV ATION NETWORKS IN COMPLEX SOCIAL SYSTEMSInnovation policymakers, business managers and the public often expect that the current investments in R&D, universities, science-industry networks etc. will immediately produce a flow of products and processes with high commercial returns. The disappointments and legitimatory problems arising from missing outputs are considerable and show the limits of steering, control and policy functions… This presentatio n is about research on innovation in complex social systems. It introduces an agent-based model called SKIN (acronym for Simulating Knowledge Dynamics in innovation Networks) to simulate the effects and impacts of policy making on the structure, composition and outputs of research and innovation networks. The model will be discussed with two examples of its many policy-relevant contributions, (i) simulating the effects of different innovation management strategies of firms in the biotechnology-based pharmaceutical industry, and (ii) impact assessment and e-ante evaluation of European funding schemes in the ICT sector. Using real-world datasets and in close response to questions put forward by stakeholders, the model can provide precise, detailed information on the effects of specific policy instruments, on how/how well research and innovat ion networks operate, and how to understand and manage the relationship between research funding and policy goals. Importantly, the model allows for experimenters to change policy parameters in the simulations. This allows using the system as a tool for modeling and evaluating the results of specific interactions between policies, funding strategies and agents.（5）HONG ZHOU（CHINA）Professor, Beihang University; Chair, Chinese Society of Systems Simulation-Discrete Event Simulation CommitteeTitle: THE STA TE-OF-THE-AR T OF SIMULA TION RESEARCH AND EDUCA TION IN CHINASimulation in China is relatively new compared with that in most developed countries. However, it received significant concerns since it was introduced and keeps almost the same pace in many aspects. In the simulation modeling areas, some research results of the theories and methods for complex system modeling and simulation are even slightly higher than the international level. In simulation system development, the research on simulation system theory is generally consistent with the current frontier, however the software engineering philosophy, methods and techniques in systems development still haven’t got sufficient attention and affected the progress of the simulation industry. This paper provided a comprehensive overview on simulation in China from different aspects, including main achievements, hot research areas, education institutions, disciplines and degree systems, academic organizations, etc., with the purpose or intention of giving a general picture of the state-of-the-art of simulation in China today. Some potential fields for future investigations are also proposed.（6）MING ZHOU（CHINA）Professor, Shenzhen University; Former director, Center for Systems Modeling & Simulation at Indiana State UniversityTitle: GREEN PRODUCTION STRA TEGIES: A SIMULATION BASED ANALYSISGreen production has become a requirement for low-carbon economy and sustainable development of modern production/service systems. The objectives and new conditions (or constraints, such as Cape-&-Trade) have caused a number of issues that significantly affect enterprises’decisions and systems’ performance. This talk presents an analysis on these issues through different simulation paradigms, in cluding discrete-event, system dynamics, and multi-agent models. It shows how simulation models, alone or integrated with other computational mechanisms, can achieve critical tasks such as characterization, evaluation and optimization of complex sustainable systems.。
