Numericalsimulationontheinfluenceofurbandevelopmentonthelocalatmosphericenvironment

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强地震作用引起的近断层地表破裂分

2006.3
CONTENT
• • • • • • • • OVERVIEW METHODOLOGY ONSET OF STRAIN LOCALIZATION EVOLUTION OF SLIPPAGE LINE CONSTITUTIVE MODEL INPUT OF THE PROBLEM EXAMPLES AND DISCUSSIONS SOME PROBLEMS
• Thickness of soil layer 30 meters
Figure 8 Deformations distribution on Z=0~90m of soil under dislocation of bedrock
Figure 9 Slippage line and extensive deformation
强断层
断层
AN APPROACH TO EVALUATE GROUND SURFACE RUPTURE CAUSED BY REVERSAL FAULT MOVEMENT
赵纪
1,2
³®L·s
1,3
师
静1
1. ¤ 国学 2. ¤ 国学国冻 3. «¢ 尔滨业学
(Institute of Engineering Mechanics, China Earthquake Administration) 点试验 (State Key Laboratory of Frozen Soil Engineering, CAREERI, CAS) 学 (School of civil Engineering, Harbin Institute of Technology)
• Assumed m and n are known

Numerical modeling of the microstructure of carbon-carbon composites on different length scales

ineering Mechanics, University of Karlsruhe (TH), Kaiserstraße 10, D-76131 Karlsruhe (Germany) Department of Mechanical Engineering, University of New Hampshire, Durham, NH 03824 (USA) 3 Institute of Chemical Technology and Polymer Chemistry, University of Karlsruhe (TH), Engesserstraße 20, D-76131 Karlsruhe (Germany) 4 Nuclear Research Centre Negev, P.O. Box 9001, Beer-Sheva, 84190 (Israel)
2
* Corresponding author. E-mail: romana.piat@ Abstract. Carbon/carbon composites produced by chemical vapour infiltration consist of carbon fibers embedded in a matrix of pyrolytic carbon with anisotropic mechanical properties. Microscopic studies show that the production process facilitates formation of a matrix consisting of cylindrically shaped pyrolytic carbon layers. The matrix layers may have different textures, which induce different mechanical properties in the axial, radial and circumferential directions. By modifying the production process parameters, it is possible to control the order, approximate width and degree of texture of the layers. Depending on the infiltration conditions pores with different geometry, size and orientations are formed between fibers with pyrolytic carbon coating. One of the goals of the present study is the microstructure characterization and the statistical description of the matrix texture, the fibers orientation distribution and the porosity. Furthermore, a micromechanical modeling using homogenization methods of the material on different length scales is performed. Correlation between calculated and experimentally obtained material properties is also discussed.

基于MCS和改进遗传算法的进气消声器优化分析

doi：10．3969/j．issn．1671－5446．2020．02．002基于MCS和改进遗传算法的进气消声器优化分析*朱传峰，毕嵘，韦静思，袁懋荣，李波，朱亚亚（广汽集团广汽研究院，广东广州511434）摘要：综合考虑发动机进气消声器声学性能和阻力特性，采用蒙特卡洛模拟（MCS），分别对基于传递矩阵和神经网络建立的进气消声器传递损失和压力损失数值模型进行参数贡献度分析，结合改进遗传算法（GA）对进气消声器进行单目标和多目标优化。

研究结果表明：MCS方法有效辨识出参数L2，L4，L6，D2，D3，D4对传递损失和压力损失贡献都较大，简化了优化分析模型。

基于神经网络建立的消声器压力损失数值模型精度较高，消声器压力损失大小的限制对进气消声器的优化结果影响较大。

在满足压力损失的情况下，单目标优化能使进气消声器的传递损失在单个共振带中心频率处传递损失达到最大值，而多目标优化得到的进气消声器比原始进气消声器控制进气噪声最多降低5．31dB，在整个工况范围，进气噪声基本都有所降低，性能优于单目标优化的结果。

关键词：蒙特卡洛模拟；神经网络；遗传算法；传递损失；压力损失中图分类号：TB535．2文献标志码：A文章编号：1671－5446（2020）02－0006－06Optimization Analysis of Acoustic and Resistance Characteristics of Intake Muffler Basedon Monte Carlo SimulationZHU Chuanfeng，BI Rong，WEI Jingsi，YUAN Maorong，LI Bo，ZHU Yaya（GAC Automotive Engineering Institute，Guangzhou511434，China）Abstract：Considering the acoustic and resistance characteristics of intake muffler，the transfer matrix and neural network were used to construct the numerical calculation model of intake muffler transmission loss and pressure loss．The contribution of intake muffler pa-rameters were analyzed based on Monte Carlo Simulation（MCS），combined with improved genetic algorithm（GA），the single objective and multiple objective optimization model were established respectively．The result shows that MCS can effective identification of pa-rameters L2，L4，L6，D2，D3，D4have great contribution to transmission loss and pressure loss，and simplify the optimization model．Theprecision of the intake muffler pressure loss model based on neural network is accurate and the limitation of pressure loss of intake muf-fler has great influence on the optimization．Under the condition of considering pressure loss，the transmission loss of intake muffler cor-responding to the center frequency of single resonant band through single objective optimization can reach maximum，however，the multi-objective optimization is better than that of the original intake muffler to control the intake noise maximum reduction is5．31dB，and the performance of the intake muffler is better than that of single target optimization．Key words：Monte Carlo Simulation；neural network；genetic algorithm；transmission loss；pressure loss引言发动机进气消声器的优劣将直接影响车辆的性能，在保证进气充足的情况下，如何高效率的设计出声学及阻力特性都满足性能要求的进气消声器是工程师面临的一个技术难题，而传递损失和压力损失是用来评价进气消声器声学性能和阻力特性的重要指标［1-3］。

üèDòáò×ù für Mathematik in den Naturwissenschaften Leipzig

f¨u r Mathematikin den NaturwissenschaftenLeipzigRandom perturbations of spiking activity in apair of coupled neuronsbyBoris Gutkin,J¨u rgen Jost,and Henry TuckwellPreprint no.:492007Random perturbations of spiking activity in apair of coupled neuronsBoris Gutkin∗,J¨u rgen Jost and Henry C.Tuckwell†May14,2007AbstractWe examine the eﬀects of stochastic input currents on theﬁring be-haviour of two coupled Type1or Type2neurons.In Hodgkin-Huxleymodel neurons with standard parameters,which are Type2,in the bistableregime,synaptic transmission can initiate oscillatory joint spiking,butwhite noise can terminate it.In Type1cells(models),typiﬁed by aquadratic integrate andﬁre model,synaptic coupling can cause oscilla-tory behaviour in excitatory cells,but Gaussian white noise can againterminate it.We locally determine an approximate basin of attraction,A,of the periodic orbit and explain theﬁring behaviour in terms of theeﬀects of noise on the probability of escape of trajectories from A.1IntroductionHodgkin(1948)found that various squid axon preparations responded in quali-tatively diﬀerent ways to applied currents.Some preparations gave a frequency ofﬁring which rose smoothly from zero as the current increased whereas oth-ers manifested the sudden appearance of a train of spikes at a particular input current.Cells that responded in theﬁrst manner were called Class1(which we refer to as Type1)whereas cells with a discontinuous frequency-current curve were called Class2(Type2).Mathematical explanations for the two types are found in the bifurcation which accompanies the transition from rest state to a periodicﬁring mode.For Type1behaviour,a resting potential vanishes via a saddle-node bifurcation whereas for Type2behaviour the instability of the rest point is due to an Andronov-Hopf bifurcation,see Rinzel and Ermentrout (1989).Stochastic eﬀects in theﬁring behaviour of neurons have been widely reported, discussed and analyzed since their discovery in the1940’s.One of theﬁrst reports for the central nervous system was by Frank and Fuortes(1955)for catX1X3X2X4X1X2TIMEFigure1:On the left are shown the solutions of(1)-(4)for two coupled QIF model neurons with the standard parameters.X1and X2are the potential variables of neurons1and2and X3and X4are the inputs to neurons1and2, respectively.On the right is shown the periodic orbit in the(x1,x2)-plane.The square marked P was explored in detail in reference to the extent of the basin of attraction of the periodic orbit.spinal neurons.Although there have been many single neuron studies,the eﬀect of noise on systems of coupled neurons have not been extensively investigated. Some preliminary studies are those of Gutkin,Hely and Jost(2004)and Casado and Baltan´a s(2003).2The quadratic integrate andﬁre modelA relatively simple neural model which exhibits Type1ﬁring behaviour is the quadratic integrate andﬁre(QIF)model.We couple two model neurons in the following manner(Gutkin,Hely and Jost,2004).Let{X1(t),X2(t),t≥0}be the depolarizations of neurons1and2,where t is the time index.Then the model equations are,for subthreshold states of two identical neurons,dX1=[(X1−x R)2+β+g s X3]dt+σdW1(1)dX2=[(X2−x R)2+β+g s X4]dt+σdW2(2)dX3=−X3τ+F(X1)(4)2where X3is the synaptic input to neuron1from neuron2and X4is the synaptic input to neuron2from neuron1.The quantity x R is a resting value.g s is the coupling strength.βis the mean background input.W1and W2are independent standard Wiener processes which enter with strengthσ.This term may model variations in nonspeciﬁc inputs to the circuit as well as possibly intrinsic membrane and channel noise.By construction,we take this term to be much weaker than the mutual coupling between the cells in our circuit.The function F is given byF(x)=1+tanh(α(x−θ))whereθcharacterizes the threshold eﬀect of synaptic activation.Since when a QIF neuron is excited and it receives no inhibition,its potential reaches an inﬁnite value in aﬁnite time,for numerical simulations a cutoﬀvalue x max is introduced so that the above model equations for the potential apply only if X1 or X2are below x max.To complete a“spike”in any neuron,taken as occurring when its potential reaches x max,its potential is instantaneously reset to some value x reset which may be taken as−x max.At the bifurcation point g s=g∗s, two heteroclinic orbits between unstable rest points turn into a periodic orbit of antiphase oscillations.3Results and theoryIn the numerical work,the following constants are employed throughout.x R= 0,x max=20,θ=10,α=1,β=−1,g s=100andτ=0.25.The initial values of the neural potentials are X1(0)=1.1,X2(0)=0and the initial values of the synaptic variables are X3(0)=X4(0)=0.When there is no noise,σ=0,the results of Figure1are obtained.The spike trains of the two coupled neurons and their synaptic inputs are shown on the left.Theﬁring settles down to be quite regular and the periodic orbit,S,is shown on the right.The patch marked P is the location of the region explored in detail below.The eﬀects of a small amount of noise are shown in Figure2.The neural excitation variables are shown on the left and the corresponding trajectories in the(x1,x2)-plane are shown on the right.In the top portion an example of the trajectory forσ=0.1is shown.Here three spikes arise in neuron1and two in neuron2,but the time between spikes increases and eventually the orbit collapses away from the periodic orbit.In the example(lower part)forσ=0.2 there are no spikes in either neuron.In10trials,the average numbers of spikes obtained for the pair of neurons were(2.5,2.2)forσ=0.1,(1.4,1.1)forσ=0.2 and(1.3,0.9)forσ=0.3;these may be compared with(5,5)for zero noise. 3.1Exit-time and orbit stabilityIf a basin of attraction for a periodic orbit can be found,then the probabil-ity that the process with noise escapes from the region of attraction gives the probability,in the present context,that spiking will cease.Since the system3TIMEX1X21 X2Figure2:On the left are shown examples of the neuronal potentials for neurons 1and2(QIF model)for two values of the noise,σ=0.1andσ=0.2.On the right are shown the trajectories corresponding to the results on the left,showing how noise pushes or keeps the trajectories out of the basin of attraction of the periodic orbit.(1)-(4)is Markovian,we may apply standardﬁrst-exit time theory(Tuckwell, 1989).Letting A be a set in R4and letting x=(x1,x2,x3,x4)∈A be a values of X1,X2,X3,X4)at some given time,the probability p(x1,x2,x3,x4)that the process ever escapes from A is given byL p≡σ2∂x21+σ2∂x22(5)+[(x1−x R)2+β+g s x3]∂p∂x2+ F(x2)−x3∂x3+ F(x1)−x4∂x4=0,x∈Awith boundary condition that p=1on the boundary of A(since the process is continuous).If one also adds an arbitrarily small amount of noise for X3and X4(or considers those solutions of(5)that arise from the limit of vanishing noise for X3,X4),the solution of the linear elliptic partial diﬀerential equation (5)is unique and≡1,that is,the process will eventually excape from A with probability1.Hence,the expected time f(x)of exit of the process from A satisﬁes L f=−1,x∈A with boundary condition f=0on the boundary of A.In fact,for small noise,the logarithm of the expected exit time from A,that4is,the time at whichﬁring stops,behaves like the inverse of the square of the noise amplitude(Freidlin and Wentzell,1998).These linear partial diﬀerential equations can be solved numerically,for example by Monte-Carlo techniques.The basin of attraction A must be found in order to identify the domain of(5).We have done this approximately for the square P in Figure1.The eﬀects of perturbations of the periodic orbit S within P on the spiking activity were found by solving(1)-(4)with various initial conditions in the absence of noise.The values of x1were from−0.43to1.57in steps of0.2and the values of x2were from-4to2also in steps of0.2.For this particular region, as expected from geometrical considerations,the system responded sensitively to to variations in x1but not x2.For example,to the left of S there tended to be no spiking activity whereas just to the right there was a full complement of spikes and further to the right(but still inside P)one spike.4Coupled Hodgkin-Huxley neuronsAs an example of a Type2neuron,we use the standard Hodgkin-Huxley(HH) model augmented with synaptic input variables as in the model for coupled QIF neurons given by equations(3)and(4),but with diﬀerent parameter values. It has been long known that additive noise has a facilitative eﬀect on single HH neurons(Yu and Lewis,1989).Coupled pairs of HH neurons have been employed with a diﬀerent approach using conductance noise in order to analyze synchronization properties(e.g.Casado and Balt´a nas,2003).For the present approach,with X1and X2as the depolarizations of the two cells,we putdX1=1g K n4(V K−X1)+it was found that transient synchronization can terminate sustained activity. For Type2neurons,we have investigated coupled Hodgkin-Huxley neurons and found that in the bistable regime,noise can again terminate sustained spiking activity initiated by synaptic connections.We have investigated a minimal cir-cuit model of sustained neural activity.Such sustained activity in the prefrontal cortex has been proposed as a neural correlate of working memory(Fuster and Alexander,1973).ReferencesCasado,J.M.,Balt´a nas,J.P.(2003).Phase switching in a system of two noisy Hodgkin-Huxley neurons coupled by a diﬀusive interaction.Phys.Rev.E68,061917,Frank,K.,Fuortes,M.G.(1955).Potentials recorded from the spinal cord with microelectrodes,J.Physiol.130,625-654.Freidlin,M.I.,Wentzell,A.D.(1998),Random Perturbations of Dynamical Sys-tems,2nd ed.,Springer,New York Fuster,J.M.and Alexander,G.E.(1971),Neuron activity related to short-term memory.Science652-654 Gutkin,B.,Ermentrout,G.B.(1998).Dynamics of membrane excitability de-termine interval variability:a link between spike generation mechanismsand cortical spike train statistics.Neural Comp.10,1047-1065. Gutkin,B.S.et al.(2001)Turning on and oﬀwith p.Neurosc.11:2,121-134Gutkin,B.,Hely,T.,Jost,J.(2004).Noise delays onset of sustainedﬁring in a minimal model of persistent activity.Neurocomputing58-60,753-760. Hodgkin,A.L.(1948).The local changes associated with repetitive action in a non-medullated axon.J.Physiol.107,165-181.Rinzel,J.,Ermentrout,G.B.(1989).Analysis of neural excitability and oscilla-tions;in:Koch C.&Segev I.,eds.MIT Press.Tateno,T.,Harsch,A.,Robinson,H.P.C.(2004).Thresholdﬁring frequency-current relationships of neurons in rat somatosensory cortex:Type1and Type2dynamics.J.Neurophysiol.92,2283-2294.Tuckwell,H.C.(1989).Stochastic Processes in the Neurosciences.SIAM,Philadel-phia.Yu,X.,Lewis,E.R.(1989).Studies with spike initiators:linearization by noise allows continuous signal modulation in neural networks.IEEE Trans.Biomed.Eng.36,36-43.6。

包钢长材厂蓄热式加热炉数值模拟

包钢长材厂蓄热式加热炉数值模拟！刘中兴1冯猛1伍永福1张鹏1!2戈春刚2(1.内蒙古科技大学内蒙古自治区白云鄂博矿多金属资源综合利用重点实验室，2.包钢长材厂)摘要以包钢长材厂蓄热式加热炉为研究对象，利用A n sy s软件采用湍流模型、P- 1辐射模型等，模拟了采用交错燃烧组织方式加热炉内各物理场分布情况。

发现该种燃烧方式下，炉内流动涡流运动明显加强，有利于燃烧的混合和组织。

但出口附近的回流造成燃烧短路，高温烟气不易达到炉膛中心，易造成炉内温度不均匀，氧气浓度相对较高不利于钢坯生产，因此该平顶、平底炉型采用交错换向燃烧有待于进一步实践验证。

关键词蓄热式加热炉数值模拟物理场高温空气燃烧技术Numerical simulation on the long materitil factoryof Baogangd regenerative furnaceLiu Zhongxing1Feng Meng1Wu Yongfu1Zhang Peng1，2Ge Chungang2(1. Inner Mongolia University of Science and Technology，2.Long Material Factory of Baogang)Abstract The regenerative heating furnace of tlie long material factory was taken as the research obje c t，used the m odel of '- $ turbulence model and P -1radiation model using Ansys software，andsimulated the distribution of the physical field in the furnace with staggered combust is found that the flow vortex motion in the furnace is obviously enhanced under And it is also conducive to the mixing and organization of the combustion. But the reflow caused bycombustion short circuit near the exit. High temperature f lue gas is not easy to reach the center of thefurnace and cause t he furnace t uneven temperature distribution. Oxygen concentration is relativelyhigh，which is unfavorable to billet production. Therefore，the flat roof and flat hearth type adoptedstaggered reversing combustion need to be further verified.Keywords regenerative furnace numerical simulation physical field high temperature air combustion加热炉是工业加热的关键设备，广泛应用于国民经济的各行各业。

Numerical simulation of pulverized coal MILD combustion considering advanced heterogeneous

Turbulence,Heat and Mass Transfer7c 2012Begell House,Inc.Numerical simulation of pulverized coal MILD combustion considering advanced heterogeneous combustion modelM.Vascellari1,2,S.Schulze1,D.Safronov1,P.Nikrytyuk1,C.Hasse11ZIK Virtuhcon,Dep.of Energy Process Enginnering and Chemical Engineering,University of Technology Freiberg,Fuchsmhlenweg9,09599Freiberg,Germany2Michele.Vascellari@vtc.tu-freiberg.deAbstract—A new advanced subgrid scale(SGS)model for coal particle combustion and gasiﬁcation was devel-oped.The new model considers a detailed representation of the diffusion and convection phenomena in the direct proximity of the coal particle,which are generally neglected by standard models available in literature.This paper shows the coupling of the new model with the commercial CFD code Ansys-Fluent and its validation consider-ing a full-scale furnace.In particular the IFRF pulverized coal MILD combustion experiments are considered for validating the results of the new model,showing a better agreement with experiments with respect to a standard model.1.IntroductionNew“clean coal technologies”for reducing pollutants from coal power plants require new advanced design tools,able to accurately predict the performances and the emission of such systems.CFD simulations represent a very important tool for designing advanced coal conversion system.However,coal combustion and gasiﬁcation require several mathematical submodels to represent the several chemical physical phenomena involved.Subgrid scale models are gener-ally developed and validated considering small scale experimental test,focusing the attention on only one ually,it is diffult to extrapolate the results of small scale laboratory tests to large scale system because of the complex nature of turbulent,reacting and multiphase ﬂows in such systems.Eaton et al.[1]presented an overview of the main submodels required for modelling solid fuels systems and their application to comprehensive CFD models.This work presents the coupling of a new subgrid scale(SGS)model for coal char com-bustion with a CFD code and its validation considering a semi-industrial scale pulverized coal MILD test-case[2].The new models was previously developed and validated considering sin-gle coal particle direct numerical simulations(DNS)[3].The new model showed excellent agreement with single particle DNS,predicting enhanced char conversion rates with respect to standard Baum and Street[4]model.2.Numerical ModelsDuring coal combustion several chemical-physical phenomena take place.They require spe-ciﬁc mathematical models implemented in a comprehensive CFD code[1].The main models considered concern the following phenomena:turbulence,multiphaseﬂow and interphase in-teractions,homogeneous and heterogeneous chemical reactions,radiation,etc..Simulations of MILD coal combustion were performed considering the commercial CFD code Ansys-Fluent,version13.0.The Reynolds Average Navier Stokes(RANS)equations are2Turbulence,Heat and Mass Transfer7Table1:Experimental conditions of IFRF furnace[2]Massﬂowrate,kg/hTemp.,K Composition(%vol)PrimaryAir130313.15O221%,N279%Secondary air 6751623.15CO28.1%,O219.7%,N257.2%,H2O15.1%solved on an unstructured hybrid mesh using aﬁnite volume discretization approach.The three-dimensional version of the pressure-based solver is considered.The SIMPLE[5]algorithm is used for velocity-pressure coupling.Convectiveﬂuxes in all transport equations are discretized with a second-order accurate upwind scheme and the pressure gradient with a second-order accurate scheme.The realizable k− turbulence model[6]is considered for RANS equations closure.The P-1radiation model[7]is considered for radiation heat transfer.The coal discrete phase is modelled considering a Eulerian-Lagrangian approach.The main gas phase is solved considering transport equations for continuous phase in the Eulerian frame of reference,while the secondary discrete solid coal phase is solved considering a Lagrangian frame.The trajectories of the particles are evaluated by integrating the force balance on them with respect to time.The continuous phaseﬂow pattern is impacted by the discrete phase(and vice versa)and the calculation of the main phase is alternated with the discrete phase until a converged coupled solution is achieved.As the trajectory of a particle is computed,the heat, mass and momentum gained or lost by the particle are evaluated,and these interactions are taken into account in the Eulerian equations of the primary phase by means of source terms. The dispersion of particles due to turbulence is taken into account by considering the stochastic tracking model,including the effect of instantaneous turbulent velocityﬂuctuations on particle trajectories.The interaction between turbulentﬂow and chemical reaction plays a fundamental rule in MILD combustion modeling,whether considering solid or liquid and gaseous fuels.Indeed,ﬂuid dynamic behaviour of MILD combustion strongly differs from conventional combustion, because gradients of temperature and chemical species concentrations are generally lower[8]. In this way,a well-deﬁnedﬂame front can no longer be observed.In particular,it was demon-strated[9]that better prediction of temperature and chemical speciesﬁeld were obtained consid-ering advanced turbulence-chemistry interaction model,such as EDC[10]with detailed kinetic mechanisms.The DRM mechanism[11]with103reactions among22chemical species is chosen here.Coal combustion is modelled according to the following sequence of phenomena:drying, pyrolysis,volatile combustion and char burnout.Moisture drying is governed by the difference of water concentrations between the parti-cle surface and the bulk phase.The water concentration on the particle surface is evaluated by assuming that the partial pressure of vapor at the interface is equal to the saturated vapor pressure at the particle temperature.The mass transfer coefﬁcient used for evaluating moisture evaporation is calculated by means of correlation of Ranz and Marshall[12].Pyrolysis can be regarded as a two-stage process[13].During primary pyrolysis,coal par-ticles decompose and release volatile matter(devolatilization),composed by TAR,light hy-drocarbons and gas.During secondary pyrolysis,TAR decomposes and produces soot,lightM.Vascellari et al.3Table2:Proximate and ultimate analysis of Guasare coal[2]Proximate analysis Ultimate analysis(%daf)V olatile matter37.1C78.41Fixed carbon56.7H 5.22Moisture 2.9O10.90Ash 3.3N 1.49LHV31.74MJ/kgTable3:V olatile yield predicted by CPD modelVolatile yield,%dafChar61.69TAR26.91H2O 5.51CO2 1.31CH4 2.26CO0.77N2 1.55hydrocarbons and gas.The devolatilization rate is modelled based on an empirical single ki-netic rate law[14].dY=A v exp(−E v/RT p)·(Y0−Y)(1)dtwhere T p is the particle temperature and Y and Y0are the instantaneous and the overall volatile yield on a dry ash-free(daf)basis,respectively.The model parameters A v and E v are the pre-exponential factor and the activation energy,which need to be adjusted for the given coal and the operating conditions.The CPD model[15]is used to determine the rate constants for single rate model.It requires chemical structure data from13C Nuclear Magnetic Resonance (13C NMR)spectroscopy on the speciﬁc coal.Since these detailed analysis data are usually not available,Genetti et al.[16]developed a non-linear correlation based on existing13C NMR data for30coals to determine the required(coal-structure-dependent)input data for the CPD model using the available proximate and ultimate analysis.This correlation is applied here. The volatile matter composition and the overall yield at high temperature were also estimated by means of the CPD model.V olatile matter is composed by light gases and hydrocarbons (CO,CO2,H2O,CH4,etc.)and heavy hydrocarbons(tar).Tar is approximated as an equivalent molecule C n H m,reacting with O2in the gas phase and producing CO and H2[13].2.1.Char Combustion ModelOnce volatile matter is completely released during primary pyrolysis,the char remaining in the coal particles reacts with the surrounding gas phase.The following four heterogeneous reactions were considered:4Turbulence,Heat and Mass Transfer7Figure1:Geometry of the IFRF furnaceC(s)+O2−→CO2(2)2C(s)+O2−→2CO(3)C(s)+CO2−→2CO(4)C(s)+H2O−→CO+H2O(5)Boudouard(Eq.(4))and gasiﬁcation(Eq.(5))reactions play an important role in MILD combustion[9,17]and they can not be neglected as usually is done for conventional coal com-bustion with atmospheric air.Char burnout is governed by the diffusion of the oxidant species from the bulk phase to the particle surface and by the heterogeneous reactions on the particle surface.Reaction rates are calculated considering global kinetic rates from[18,19].The diffusion of each chemical species from the bulk phase(∞)to the particle surface(s)is given by:β(c∞,i−c s,i)+4j=1νj,iˆR j=0(6)WhereˆR j is the rate of the reaction j,νj,i is the stoichiometric coefﬁcient of species i in reaction j andβis the mass transport coefﬁcient,calculated from the Ranz and Marshall[12] correlation,assuming unitary Lewis number.Generally,standard models[4]neglect the in-ﬂuence of the convection assuming stagnantﬂow around the particle.The diffusion of each species(Eq.(6))is equal to its production due to the heterogeneous reactions.The mass bal-ance of Eq.(6)account for the interactions between different surface reactions.In fact,CO2, produced on the particle surface from the char oxidization reaction(Eq.(2)),can react directly according to the Boudouard reaction(Eq.(4))increasing the overall char consumption.Gener-ally,standard models,such as[4]model,neglect any interaction between the different surface reactions.Further information about the model can beﬁnd in the paper of Schulze et al.[3].User Deﬁned Function(UDF)capability of Ansys-Fluent were used for coupling the SGS model,coded in C language,with the CFD solver,replacing the standard models for char com-bustion.5(a)(b)Figure 2:Comparison of temperature considering Baum and Street [4](BS)and SGS models respectively:(a)axial section contour plot;(b)radial proﬁles at 0.15,0.44,0.735,and 1.32m from the burner and comparison with experimental results [2].(a)(b)Figure 3:Comparison of CO dry volume fraction considering Baum and Street [4](BS)and SGS models respectively:(a)axial section contour plot;(b)radial proﬁles at 0.15,0.44,0.735,and 1.32m from the burner and comparison with experimental results [2].3.Validation of the SGS Char Combustion ModelValidation of SGS model was performed considering the experimental pulverized coal MILD test-case at the International Flame Research Fundation (IFRF)[2].MILD or ﬂameless com-bustion is a new technology developed for reducing pollutant emissions [8].Reactants are in-troduced at temperature generally higher than ignition temperature and the mixture is strongly diluted in order to reduce the temperature increase during reactions.The IFRF furnace is char-acterized by a square section of 2m ×2m and by a length of 6.25m,as shown in Fig.1.Primary air enters from the two lateral inlets,transporting pulverized coal particles.Secondary air is preheated by means of combustion with natural gas up to levels of 1350◦C before entering the furnace from the central inlet.Vitiated air is enriched with pure O 2in order to maintain the same concentration as atmospheric air.The furnace is ﬁred with 66kg h −1,130kg h −1and 675kg h −1respectively of coal,primary and secondary air,corresponding to a stoichiometric ratio of 1.2,as reported in Tab.1.The wall of the furnace is considered at the constant temper-Transfer7Figure4:Char consumption rate(kg/s m2)for65µm particles at0.44,0.735,1.32and2.05m from the burner.Results of Baum and Street(BS)model are reported on the left(triangles)and results of SGS on the right(circles)for each sectionsature of about1000◦C.The furnace isﬁred with Guasare coal,which proximate and ultimate analyisis are reported in Tab.2.Coal isﬁnely pulverized to give a particle size distribution with80%less than90µm[2].Particle size distribution is covered considering six classes[20]. V olatile yields are calculated by means of the CPD model,as reported in Tab.3.The single rate devolatilization model(Eq.(1))is calibrated by means of the CPD model,obtaining a pre-exponential factor of26353.9s−1and an activation energy of45.424kJ/mol.Considering recirculation of exhaust gas,the furnace is characterized by high concentrations of CO2and H2O and consequently a large fraction of char is converted through the gasiﬁcation (Eq.(4))and Boudoard(Eq.(5))reactions[17],representing an optimal test-case for validating the new char combustion model.The performances of the SGS model are therefore compared to the standard Baum and Street (BS)model andﬁnally validated against the experiments[2].Reactions Eq.(3)-(5)are consid-ered for Baum and Street model considering the same kinetic rates[18,19]used for the SGS model.Figure2(a)shows the comparison between the Baum and Street[4]and SGS models consid-ering the temperatureﬁeld.As expected,temperature gradients are very small and no clear front ofﬂame can be observed.Similar temperature proﬁles were predicted considering both models. The comparison with experiments is reported in Fig.2(b),considering four radial traverses at 0.15,0.44,0.735and1.32m from the burner.The SGS model predicts a lower temperature level in the inner jet zone,because of the increased conversion of char due to the endothermic reactions.Indeed,in this region,O2is almost completely consumed(see[9])and therefore only the endothermic gasiﬁcation(Eq.(5))and Boudouard reactions(Eq.(4))take place,absorbing heat from the gas phase.Figure3(a)shows the comparison of dry CO molar fraction on the axial section between the Baum and Street[4]and SGS models.Lower levels of CO are predicted by SGS model withrespect to Baum and Street model.Indeed,considering SGS model,the char reacting with O2 produces either CO either CO2,reducing the overall production of CO from the discrete phase. Dry CO molar fraction from numerical simulations is compared to experiments[2]considering four radial traverses at0.15,0.44,0.735and1.32m from the burner,as shown in Fig.3(b).SGS models shows a better agreement with respect to experiments.Figure4shows the char consumption rate at four cross sections for Baum and Street and SGS models considering65µm particles.As already observed for single particle simulations [3],SGS model predicts an enhanced char consumption rate with respect to Baum and Street model,nevertheless the same kinetic rates are used.In fact,the SGS model takes in account the inﬂuence of the heat and mass transport from the bulk phase to the particle surface and the interaction between the heterogeneous reaction in the particle boundary layer,enhancing the overall char consumption rate.4.ConclusionsIn this paper a new SGS model for char combustion,previously developed and validated for a single particle combustion by Schulze et al.[3],has been coupled to the commercial CFD code Ansys-Fluent and validated considering a pulverized coal MILD combustion test-case. The results have been compared to the standard Baum and Street model,used as default char combustion model by Ansys-Fluent.The comparison shows an improved prediction of the chemical species concentrations for the new SGS model with respect to the standard model. References[1]Eaton,A.et al.“Components,formulations,solutions,evaluation,and application ofcomprehensive combustion models”.In:Prog Energ Combust25.4(1999),pp.387–436.[2]Orsino,S.et al.Excess Enthalpy Combustion of Coal(Results of High Temperature AirCombustion Trials).Tech.rep.IFRF Doc.No.F46/y/3.International Flame Research Foundation,2000.[3]Schulze,S.et al.“Sub-model for a spherical char particle moving in a hot air/steamatmosphere”.In:Flow Turbul Combust(2012).(submitted).[4]Baum,M.et al.“Predicting the Combustion Behaviour of Coal Particles”.In:CombustSci Technol3.5(1971),pp.231–243.[5]Patankar,S.et al.“A calculation procedure for heat,mass and momentum transfer inthree-dimensional parabolicﬂows”.In:International Journal of Heat and Mass Transfer15.10(1972),pp.1787–1806.[6]Shih,T.et al.“A new k-epsilon eddy viscosity model for high reynolds number turbulentﬂows”.In:Computers and Fluids24.3(1995),pp.227–238.[7]Cheng,P.“Two-dimensional radiating gasﬂow by a moment method”.In:AIAA Journal2.9(1964),pp.1662–1664.[8]Cavaliere,A.et al.“Mild Combustion”.In:Prog Energ Combust30.4(2004),pp.329–366.[9]Vascellari,M.et al.“Inﬂuence of turbulence and chemical interaction on CFD pulverizedcoal MILD combustion modeling”.In:Fuel(2012).doi:10.1016/j.fuel.2011.07.042.[10]Gran I.,R.et al.“A numerical study of a bluff-body stabilized diffusionﬂame.Part1.Inﬂuence of turbulence modeling and boundary conditions”.In:Combust Sci Technol 119.1-6(1996),pp.171–190.[11]Kazakov,A.et al.Reduced Reaction Sets based on GRI-Mech1.2.http://me.berk/drm/.1994.[12]Ranz,M.et al.“Evaporation from drops:Part I”.In:Chem Eng Prog48(1952),pp.141–146.[13]F¨o rtsch,D.et al.“A kinetic model for the prediction of NO emissions from staged com-bustion of pulverized coal”.In:Proceedings of the27th Symposium(Intl.)on Combus-tion,The Combustion Institute,Pittsburgh27.2(1998),pp.3037–3044.[14]Badzioch,S.et al.“Kinetics of Thermal Decomposition of Pulverized Coal Particles”.In:Ind.Eng.Chem.Proc.Des.Dev.9.4(1970),pp.521–530.[15]Grant D.,M.et al.“Chemical model of coal devolatilization using percolation latticestatistics”.In:Energy&Fuels3.2(1989),pp.175–186.[16]Genetti,D.et al.“Development and Application of a Correlation of13C NMR Chem-ical Structural Analyses of Coal Based on Elemental Composition and V olatile Matter Content”.In:Energy&Fuels13.1(1999),pp.60–68.[17]Stadler,H.et al.“On the inﬂuence of the char gasiﬁcation reactions on NO formation inﬂameless coal combustion”.In:Combustion and Flame156.9(2009),pp.1755–1763.[18]Libby P.,A.et al.“Burning carbon particles in the presence of water vapor”.In:Com-bustion and Flame41.0(1981),pp.123–147.[19]Caram H.,S.et al.“Diffusion and Reaction in a Stagnant Boundary Layer about a CarbonParticle”.In:Industrial&Engineering Chemistry Fundamentals16.2(1977),pp.171–181.[20]Kim,J.et al.“Numerical modelling of MILD combustion for coal”.In:Progress in Com-putational Fluid Dynamics(2007).。

TiB_2_Al复合材料喷丸后微区残余应力的有限元模拟

TiB 2/Al 复合材料喷丸后微区残余应力的有限元模拟卞凯,姜传海,栾卫志(上海交通大学材料科学与工程学院高温材料及高温测试教育部重点实验室,上海200240)摘要:采用ANSYS/LS DYNA 有限元分析软件建立了颗粒增强T iB 2/Al 复合材料的喷丸模型,并对喷丸后残余应力分布进行了预测;然后对复合材料进行了喷丸试验,对残余应力进行了检测;将试验结果与模拟结果进行了对比。

结果表明:该复合材料喷丸后残余应力分布的试验结果与模拟结果基本相符;喷丸后最表层部分增强体呈拉应力状态,在材料残余压应力场内,由于增强体和基体材料力学性能的差异,增强体的残余应力值普遍大于基体中的。

关键词:复合材料;有限元模拟;喷丸;残余应力中图分类号:T B333 文献标志码:A 文章编号:1000 3738(2011)01 0086 03Finite Element Simulation of Micro region Residual Stress of ShotPeened TiB 2 / Al CompositeBIAN Kai,JIANG C huan hai,LUAN Wei zhi(K ey L abor ator y for H igh T emperatur e M ateria ls and T ests of M inist ry of Educatio n,Schoo l o f M aterials Science andEng ineering ,Shang hai Jiaot ong U niv ersity ,Shang hai 200240,China)Abstract:A model o f sho t peening of the part icle reinfo rced T iB 2/A l composites w as built w ith AN SY S/L S DYN A finite element simulat ion so ftwa re,then the residua l stress distr ibut ion after shot peening was predict ed.T he shot peening tests wer e perfor med on the co mpo sites,and the r esidual stresses w ere measured,then t he test results wer e co mpar ed with the simulatio n r esult s.It is show n that the ex perimetal results of residual st ress distr ibut ion of the composites after shot peening w ere in ag reement w ith the simulated one.T he r einfo rcement at the outmest layer after shot peening sho wed tensile stress state.In the residual pressure stress field,r esidual str ess in the r einfor cement was generally g reater than that in the substr ate,which was resulted fr om the differ ence of the mechanical pro per ties of the tw o mater ials.Key words:composite;finite element simulation;shot peening ;r esidual str ess0 引言喷丸是一种广泛应用的材料表面强化手段,可显著提高材料的疲劳强度、表面强度、抗应力腐蚀性能等[1]。

《建筑结构》稿件录制视(音)频倡议书

[13] CALVI GM,PAVESE A,RASULO A ,et al. Experimental and numerical studies on the seismic response of RC hollow bridge piers [ J ]. Bulletin of Earthquake Engineering, 2 0 0 5 ,3 (3 ) ：267-297.
《建筑结构》稿件录制视（音）频倡议书
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清晰、多维度地了解论文成果，丰富论文的呈现形
[10] AN Y F,HAN L H ，ZHAO X L. Experimental behavior of box concrete-encased CFST eccentrically loaded column [ J ] . Mag. Magazine of Concrete Research, 2013, 65 (20) ：1219-1235.
[ 8 ] Bridge design specifications：AASHTO LRFD SI-2007 [S ]. Washington, D. C. ：American Association of State Highway and Transportation Officials ,2007.
[11] CHENG C T, YANG J C, YEH Y K, et al. Seismic performance of repaired hollow bridge piers [ J ]. Journal of Construction and Building Material,2003,17(5) ：339-351.

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引言
城镇人口的急剧增长和城市规模的不断扩大，改变了城市区域土地利用结构和大气层下垫面特性，使得原有自然植被或裸露土地被各种建筑物以及大量的沥青、水泥马路所代替。人们的生产和生活极大地改变了城市大气的热力和动力状况，工业排放的大量烟尘、气溶胶、颗粒物以及汽车尾气和扬尘等对于城市气温、湿度、能见度、风和降水等都有１－４］影响，并进一步影响到人们生活的舒适程度［。鄂尔多斯市东胜区地处鄂尔多斯高原腹地，属于毛乌素沙地的延伸地带，风蚀沙化严重，海拔高度为１５００ｍ左右。自然条件较为严酷，但资源丰富，是国家新兴能源重化工基地之一。近年来，东胜区经济发展明显加快，国民生产总值从２０世纪７０年代的４５１９０万元，增到２００５年的１２７１１１４０万元，增加了２８０多倍。尤其是近５ａ东胜区经济发展迅速，大型工矿企业明显增多，与此同时东胜区人口也从２０世纪８０年代的１０１３万人，增到２００５年的２３０６万人，呈现出快速增长趋势。工业发展以及人口增多，改变了城区大气的热力和动力结构，加上地处干旱地区的东胜区自然植被差，自净能力弱，给城市发展带来了一系列的问题。为了探索城区建设对局地及周边大气环境的影响，本文采用典型气象条件，以
根据区域边界层模式模拟运算所需，初始场中规划数据为遥感影像和规划图扫描后以土地利用／ＩＤＬ语言为平台，采用图像智能分类法，对城市规划、现状等下垫面信息进行了智能化提取。气象资料为２００２ —２００６年东胜站４个时次包括温度、气压、相对８时和２０湿度、地温、地面风速和地面风向资料和０时９个标准层包括逐层高度、温度、露点温度、风向、００２ —２００６年１月（代风速等资料。模式中运行了２表冬季）、７月（代表夏季）的气象要素的平均值。地形为模拟范围１ ∶ ５万地形高度数据。污染源资料包０个点污染括二氧化硫一种污染物，污染源资料为１源排污数据。运行设置从００点开始模拟，运行时长为８６４００ｓ（即２４ｈ）；时间步长为０５ｓ。输出时间间隔为３６００ｓ（即每隔１ｈ输出１次结果）。１４模式检验以东胜地面自动气象站２００５年７月５日００ — ２３时逐时气温和风速观测数据对模拟结果进行检验。将２００５年７月４日２０时地面观测资料及探空资料作为模式初始场，共模拟３０ｈ。将观测数据与相应时段的模拟结果比较（图２），模式模拟性能较好，模拟的地面气温与实测趋势基本吻合。地面风速的模拟结果基本反映了日变化规律，模式对地面气温的模拟效果好于地面风速的模拟效果。说明利ＢＬＭ模式对城市现状和规划方案进行模拟可信用Ｒ度是比较高的。
００２年城区建设现状与２００３ —２０２０年东胜东胜区２区总体建设规划为例，进行数值模拟，通过地气相互作用，分析东胜区经济快速发展对局地大气环境产生的影响，以期为城区发展决策提供参考。东胜区城市总体规划的内容涵盖了城乡发展目标与战略，城镇体系规划（人口与城镇化、城镇体系布局、产业选择与布局、旅游规划、空间管制规划、社会服务设施规划和市政工程设施与防灾规划），城市性质与城市规模，城区用地布局规划，城区近期建设规模与目标，城乡统筹规划，综合交通规划，绿地系统及水系规划，市政基础设施规划，综合防灾规划和环境及资源与风貌保护规划和远景发展设想等主要方面。其特点：从城市的实际出发，以构建社会主义和谐社会为基本目标，坚持五个统筹，坚持节约和集约利用资源，坚持因地制宜确定城市发展目标，保护生态环境，保护人文资源，尊重历史文化，促进城市全面协调可持续发展。有关城区规划对大气环境影响评价方面，取得［５－１８］，如北京五棵松体育场规划、珠了大量研究成果江三角洲城市群的建设规划等都充分考虑了发展规划对周边地区大气环境的影响，增强了城市建设规划的科学性等。但这些研究成果主要针对经济较为发达的大城市，而东胜区作为中国重化工能源基地，是近几年来快速发展起来的中小城市，城区发展对
６２
气象与环境பைடு நூலகம்报
第２７卷
大气环境影响很大，因此，在经济快速发展的同时，开展东胜城区建设对大气环境影响的定量化评估非常必要。
气流特征，模拟中心经度为１１００１０７ ° Ｅ，纬度为３９８０８２ ° Ｎ，水平格距为５００ｍ × ５００ｍ，平均垂直格距为２００ｍ，最小底层垂直格距为２０ｍ，垂直方向共３３层（图１）。
第２７卷第３期２０１１年６月
气象与环境学报ＪＯＵＲＮＡＬＯＦＭＥＴＥＯＲＯＬＯＧＹＡＮＤＥＮＶＩＲＯＮＭＥＮＴ
Ｖｏｌ．２７Ｎｏ．３Ｊｕｎｅ２０１１
李喜仓，白美兰，马玉峰，等．鄂尔多斯市城区发展对局地大气环境影响的数值模拟［Ｊ］．气象与环境学报，２０１１，２７（３）：６１－６６．ＬＩＸｉｃａｎｇ，ＢＡＩＭｅｉｌａｎ，ＭＡＹｕｆｅｎｇ，ｅｔａｌ．ＮｕｍｅｒｉｃａｌｓｉｍｕｌａｔｉｏｎｏｎｔｈｅｉｎｆｌｕｅｎｃｅｏｆｕｒｂａｎｄｅｖｅｌｏｐｍｅｎｔｏｎｔｈｅｌｏｃａｌａｔｍｏｓｐｈｅｒｉｃｅｎｖｉｒｏｎｍｅｎｔｉｎＤｏｎｇｓｈｅｎｇｄｉｓｔｒｉｃｔｏｆＥｒｄｏｓ，ＩｎｎｅｒＭｏｎｇｏｌｉａａｕｔｏｎｏｍｏｕｓｒｅｇｉｏｎ［Ｊ］．ＪｏｕｒｎａｌｏｆＭｅｔｅｏｒｏｌｏｇｙａｎｄＥｎｖｉｒｏｎｍｅｎｔ，２０１１，２７（３）：６１－６６．
１９］。模式采用Ｒｅｙｎｏｌｄｓ平均的大气运值模拟系统［
动控制方程组，包括动量方程、热流量方程、标量方程和完全弹性连续方程。模式的控制方程组由水平和垂直运动方程、连［１９］续方程、位温方程和水汽方程组成。取湍流动能Ｅ（ＴＫＥ）闭合方案和湍流能量Ｅ引 ε闭合方案可选，入湍流动能Ｅ（ＴＫＥ）方程和Ｅ ε方程。模式输入由ＧＩＳ）生成的数据库给出，并经模式预地理信息系统（处理以提供气象模式和扩散模式所需信息和参数作本模式输入。主要包括模拟区域范围内的地理网络及基本地理特征、地形高度、地面覆盖状况、地面与高空气象要素、地面污染物排放源址及源量等。模式输出主要包括以下３项：（１）大气边界层气象要素和湍流变量的分布；（２）近地面层空气污染物浓度分布；（３）利用Ｇｒａｄｓ给出的图像显示并输出。１３模拟范围及参数设置东胜区模拟范围包括２０ｋｍ× ２０ｋｍ范围内的
［１９］模式），以２００２年东胜城区现状及其２００３ —２０２０
方框为东胜区位置；模式分辨率为０５ｋｍ；数字为海拔高度（ｍ）
图１模拟区域地形
城区规划发展过程为例，模拟研究随着城区规模扩大、不同下垫面布局对大气环境的影响。ＲＢＬＭ模式考虑了下垫面特征对边界层结构的影响，采用先进实用的湍能１５阶的湍流闭合方案。是由一个三维非静力、细网格高分辨、精细ＰＢＬ模拟和一个区域中 β 尺度气象模式及空气污染物输送扩散模式组成，是一个具有诊断和预报功能的城市数
收稿日期：２０１０－１２－０２；修订日期：２０１１－０３－２９。基金项目：科研院所社会公益专项资金项目“ 沙尘气溶胶辐射模型及气候环境效益” （２００５ＤＩＢ３Ｊ１０８）和中国气象局２００７年多轨道建设项目“ 城市规划气候可行性论证业务系统” 共同资助。作者简介：李喜仓，男，１９６２年生，高级工程师，主要从事气候资源开发利用和气候变化影响研究，Ｅｍａｉｌ：ｑｋｓｌｘｃ＠１６３．ｃｏｍ。通讯作者：白美兰，Ｅｍａｉｌ：ｎｍｇｈｒｑ＠ｓｉｎａ．ｃｏｍ。
鄂尔多斯市城区发展对局地大气环境影响的数值模拟
李喜仓１白美兰１马玉峰１刘克利２冯晓晶１杨晶１
（１内蒙古自治区气候中心，内蒙古呼和浩特０１００５１；２内蒙古自治区气象科技服务中心，内蒙古呼和浩特０１００５１）摘要：选取鄂尔多斯市东胜区为代表区域。基于该区域１９６１ —２００６年定时地面气象观测资料和２００２ —２００６年０８时、２０时各标准层探空以及２００１ —２００６年主要污染源源强、１９６１ —２００６年社会经济数据、２００２年卫星遥感反演资料、２００３ —２０２０年城市总体规划资料等，利用区域边界层模式模拟方法，分析鄂尔多斯市城市化进程对局地大气环境的影响。结果表明：东胜区发展后（２０２０年）气温低于现状（２００２年），使城区中心气温与周边地区气温差异变小，对城区大气环境的改善较为有利。东胜城区扩展后，在污染严重的冬季，气流辐合区域减少，辐散能力增强，对减轻城区污染和改善大气环境有利。城区拓展后由于下垫面等布局发生变化，气流场变化较大，但从污染物的扩散能力来看，按规划发展后城区污染轻于现状。关键词：大气环境；模拟分析；影响评价；鄂尔多斯市中图分类号：Ｘ８２３文献标识码：Ａ文章编号：１６７３－５０３Ｘ（２０１１）０３－００６１－０６