Simulation of Dynamic Recrystallization in 7075 Aluminum Alloy Using Cellular Automaton

The evolution of microstructure during hot deformation is key to achieving good mechanical properties in aluminum alloys.We have developed a cellular automaton(CA) based model to simulate the microstructural evolution in 7075 aluminum alloy during hot deformation.Isothermal compression tests were conducted to obtain material parameters for 7075 aluminum alloy,leading to the establishment of models for dislocation density,nucleation of recrystallized grains,and grain growth.Integrating these aspects with grain topological deformation,our CA model effectively predicts flow stress,dynamic recrystallization(DRX) volume fraction,and average grain size under diverse deformation conditions.A systematic comparison was made between electron back scattered diffraction(EBSD) maps and CA model simulated under different deformation temperatures(573 to 723 K),strain rates(0.001 to 1 s^(-1)),and strain amounts(30% to 70%).These analyses indicate that large strain,high temperature,and low strain rate facilitate dynamic recrystallization and grain refinement.The results from the CA model show good accuracy and predictive capability,with experimental error within 10%.

Dynamics of Land Use/Land Cover Considering Ecosystem Services for a Dense-Population Watershed Based on a Hybrid Dual-Subject Agent and Cellular Automaton Modeling Approach

Land use/land cover represents the interactive and comprehensive influences between human activities and natural conditions,leading to potential conflicts among natural and human-related issues as well as among stakeholders.This study introduced economic standards for farmers.A hybrid approach(CA-ABM)of cellular automaton(CA)and an agent-based model(ABM)was developed to effectively deal with social and land-use synergic issues to examine human–environment interactions and projections of land-use conversions for a humid basin in south China.Natural attributes and socioeconomic data were used to analyze land use/land cover and its drivers of change.The major modules of the CA-ABM are initialization,migration,assets,land suitability,and land-use change decisions.Empirical estimates of the factors influencing the urban land-use conversion probability were captured using parameters based on a spatial logistic regression(SLR)model.Simultaneously,multicriteria evaluation(MCE)and Markov models were introduced to obtain empirical estimates of the factors affecting the probability of ecological land conversion.An agent-based CA-SLR-MCE-Markov(ABCSMM)land-use conversion model was proposed to explore the impacts of policies on land-use conversion.This model can reproduce observed land-use patterns and provide links for forest transition and urban expansion to land-use decisions and ecosystem services.The results demonstrated land-use simulations under multi-policy scenarios,revealing the usefulness of the model for normative research on land-use management.

Visualization of Vapor Film Collapse Behavior with Complexity on Quenching Process by Cellular Automaton

The vapor film collapse that occurs in the quenching process is complicated and affects the heat treatment quality and its distortion.In order to incorporate it into the MBD(Model Based Development)technology required these days,it is necessary to predict the quality of heat treatment by CAE(Computer Added Engineering),shorten the product development period.The calculation of the vapor film collapses in a simple and practical time in order to improve the product performance.However,in the past,in order to formulate the vapor film collapse on a simulation,it was necessary to perform a very large amount of computational calculation CFD(computational fluid dynamics),which was a problem in terms of computer resources and the model of vapor film collapse.In addition,this phenomenon has a complexity behavior of the phenomenon in iterative processing,which also complicates the calculation.In this study,the vapor film collapse phenomenon is easily visualized using self-organized cellular automaton simulation which includes the phenomena of“vapor film thickness and its fluctuation”,“flow disturbance”,“surface step of workpiece”,and“decrease of cooling due to r shape of surface”.The average cooling state and repeated fluctuations of the cooling state were reproduced by this method.

采用Cellular Automaton法模拟铝合金的微观组织

采用 Cellular Automaton微观模型 ,并与宏观的传热计算相结合 ,对砂型铸造铝合金铸件的凝固组织形成进行了模拟。在模拟过程中 ,采用连续形核的方法处理液态金属的异质形核现象。通过高斯分布函数描述形核质点密度随温度的分布关系 ,在给定过冷度时对分布函数求积分可得该时刻的形核密度。晶粒生长模型则考虑枝晶尖端生长动力学和择优生长方向〈1 0 0〉晶向。模拟计算结果表明 ,在冷却速度不变的情况下 ,随着形核分布参数ΔTN 增加 ,所得到的晶粒尺寸增大。

用Cellular Automaton模型方法模拟二元合金多晶粒枝晶生长

研究并针对CellularAutomaton凝固组织模拟方法的物理本质、数值计算方法以及在凝固微观组织模拟中的应用进行了探索。并利用CellularAutomaton凝固组织模拟方法,求解了Al4.5Cu等轴晶多个枝晶同时生长过程。模拟结果和试验结果吻合很好。

用Cellular Automaton方法模拟压铸镁合金AM50的微观组织

基于Cellular Automaton(CA)方法的基本原理,建立了压铸镁合金AM50形核和等轴晶粒生长的二维数学物理模型,能够对任意晶向的等轴晶晶粒生长进行模拟。模型耦合了宏观传热与微观组织模拟计算,镁合金AM50阶梯块压铸件的温度场通过热传导反算法计算求得。对阶梯块压铸件不同阶梯表面的微观组织进行了模拟,并与金相试验结果进行了对比,它们在晶粒尺寸上吻合较好。

用Cellular Automaton模型方法模拟二元合金枝晶生长

研究并针对CellularAutomaton凝固组织模拟方法模型的物理本质、数值计算方法以及在凝固微观组织模拟中的应用进行了探索。并利用CellularAutomaton凝固组织模拟方法,求解了Al-4.5%Cu等轴晶枝晶生长。

金属成形过程组织演变的Cellular Automaton模拟技术

结合金属凝固过程和热成形过程的温度场、浓度场、应力应变场等的数值模拟和金属结晶、再结晶过程中的热力学、动力学条件，建立了金属成形过程组织演变的宏－微观耦合模型．利用ＣｅｌｌｕｌａｒＡｕｔｏｍａｔｏｎ方法，依据建立的模型对Ｋ４１７Ｎｉ基合金叶片的凝固组织形成过程和热加工过程的再结晶组织进行了模拟．

基于热力学函数的纳米晶粒长大Cellular Automaton仿真研究

基于纳米晶热力学特性表征函数,将纳米晶热力学性质对晶界迁移的影响引入Cellular Automaton算法,对纳米晶粒长大行为进行了定量化和可视化的仿真研究.模拟结果表明,纳米晶粒长大的动力学与传统粗晶材料不同,在恒温条件下,纳米晶粒的长大指数n不是常数(传统粗晶材料的晶粒长大指数n=2为常数),随纳米晶粒长大过程的进行,n值从1.70至6.59发生变化.作为纳米晶粒长大的驱动力,纳米晶界的过剩自由能与纳米晶粒尺寸的变化直接相关.由于纳米晶材料强烈的小尺寸效应,纳米晶组织的热力学性质较大地影响纳米晶界的结构和能量状态,从而影响纳米晶粒长大的动力学特征.因此,只有结合纳米晶热力学特性的仿真研究才能获得对纳米晶粒长大行为本质性的认识.

采用Cellular automaton法模拟动态再结晶过程的研究

结合金属塑性成形过程的冶金学原理,给出了一种新的模拟动态再结晶过程的元胞自动机(Cellular automaton,CA)模型,用来模拟塑性变形过程中动态再结晶过程。再结晶晶粒的生长速度与再结晶驱动力成正比, 再结晶驱动力取决于晶界能和位错密度。在一个增量步内,根据动态再结晶晶粒生长速度确定与其相邻原胞转变 概率。采用本模型对不同温度、应变速度、应变条件下的动态再结晶过程进行了模拟,模拟结果与试验结果以及 经验公式得到的结果相一致。本模型也可用于再结晶动力学、微观组织和织构变化过程的模拟。

Optimization of deformation parameters of dynamic recrystallization for 7055 aluminum alloy by cellular automaton

In order to simulate the microstructure evolution during hot compressive deformation,models of dynamic recrystallization(DRX)by cellular automaton(CA)method for7055aluminum alloy were established.The hot compression tests were conducted toobtain material constants,and models of dislocation density,nucleation rate and recrystallized grain growth were fitted by leastsquare method.The effects of strain,strain rate,deformation temperature and initial grain size on microstructure variation werestudied.The results show that the DRX plays a vital role in grain refinement in hot deformation.Large strain,high temperature andsmall strain rate are beneficial to grain refinement.The stable size of recrystallized grain is not concerned with initial grain size,butdepends on strain rate and temperature.Kinetic characteristic of DRX process was analyzed.By comparison of simulated andexperimental flow stress–strain curves and metallographs,it is found that the established CA models can accurately predict themicrostructure evolution of7055aluminum alloy during hot compressive deformation.

An improved cellular automaton model considering the effect of traffic lights and driving behaviour

This paper proposes an improved cellular automaton model to describe the urban traffic flow with the consideration of traffic light and driving behaviour effects. Based on the model, the characteristics of the urban traffic flow on a single- lane road are investigated under three different control strategies, i.e., the synchronized, the green wave and the random strategies. The fundamental diagrams and time-space patterns of the traffic flows are provided for these strategies respectively. It finds that the dynamical transition to the congested flow appears when the vehicle density is higher than a critical level. The saturated flow is less dependent on the cycle time and the strategies of the traffic light control, while the critical vehicle density varies with the cycle time and the strategies. Simulated results indicate that the green wave strategy is proven to be the most effective one among the above three control strategies.

Simulation of Dynamic Recrystallization Using Cellular Automaton Method

A new modeling approach that couples fundamental metallurgical principles of dynamical recrystallization with the cellular automaton method was developed to simulate the microstructural evolution linking with the plastic flow behavior during thermomechanical processing.The driving force for the nucleation and growth of dynamically recrystallized grain is the volume free energy due to the stored dislocation density of a deformation matrix.The growth terminates the impingement.The model is capable of simulating kinetics,microstructure and texture evolution during recrystallization.The predictions of microstructural evolution agree with the experimental results.

EVOLUTION COMPL EXITY OF THE ELEMENTARY CELLULAR AUTOMATON OF RUL E 2 2

Cellular automata are the discrete dynamical systems of simple construction but with complex and varied behaviors.In this paper,the elementary cellular automaton of rule 22 is studied by the tools of formal language theory and symbolic dynamics.Its temporal evolution orbits are coarse grained into evolution sequences and the evolution languages are defined.It is proved that for every n ≥2 its width n evolution language is not regular.

Identification of nucleation parameter for cellular automaton model of dynamic recrystallization

The accuracy of nucleation parameter is a critical factor in the simulation of microstructural evolution during dynamic recrystallization(DRX).Based on the flow stress curve under hot deformation conditions,a new approach is proposed to identify the nucleation parameter during DRX.In this approach,a cellular automaton(CA) model is applied to quantitatively simulate the microstructural evolution and flow stress during hot deformation;and adaptive response surface method(ARSM) is applied as optimization model to provide input parameters to CA model and evaluate the outputs of the latter.By taking an oxygen-free high-conductivity(OFHC) copper as an example,the good agreement between the simulation results and the experimental observations demonstrates the availability of the proposed method.

Effect of acceleration threshold on the phase transition in a cellular automaton traffic flow model

In this paper, we incorporate new parameters into a cellular automaton traffic flow model proposed in our previous paper [Jin et al. 2010 J. Stat. Mech. 2010 P03018]. Through these parameters, we adjust the anticipated velocity and the acceleration threshold separately. It turns out that the flow rate of synchronized flow mainly changes with the anticipated velocity, and the F →S phase transition feature mainly changes with the acceleration threshold. Therefore, we conclude that the acceleration threshold is the major factor affecting the F → S phase transition.

Numerical simulation of solidification morphologies of Cu-0.6Cr casting alloy using modified cellular automaton model

The purpose of this study is to predict the morphologies in the solidification process for Cu-0.6Cr(mass fraction,%)alloy by vacuum continuous casting(VCC)and verify its accuracy by the observed experimental results.In numerical simulation aspect, finite difference(FD)method and modified cellular automaton(MCA)model were used to simulate the macro-temperature field, micro-concentration field,nucleation and grain growth of Cu-0.6Cr alloy using real data from actual casting operations.From the observed casting experiment,the preliminary grain morphologies are the directional columnar grains by the VCC process.The solidification morphologies by MCAFD model are in agreement with the result of actual casting experiment well.

A new cellular automaton model accounting for stochasticity in traffic flow induced by heterogeneity in driving behavior

A new reliable cellular automaon(CA) model designed to account for stochasticity in traffic flow induced by heterogeneity in driving behavior is presented.The proposed model differs from most existing CA models in that this new model focuses on describing traffic phenomena by coding into its rules the key idea that a vehicle's moving state is directly determined by a driver stepping on the accelerator or on the brake(the vehicle's acceleration).Acceleration obeys a deformed continuous distribution function when considering the heterogeneity in driving behavior and the safe distance, rather than equaling a fixed acceleration value with a probability, as is the rule in many existing CA models.Simulation results show that the new proposed model is capable of reproducing empirical findings in real traffic system.Moreover, this new model makes it possible to implement in-depth analysis of correlations between a vehicle's state parameters.

Modeling on dynamic recrystallization of aluminium alloy 7050 during hot compression based on cellular automaton

The dynamic recrystallization(DRX) process of hot compressed aluminium alloy 7050 was predicted using cellular automaton(CA) combined with topology deformation. The hot deformatation characteristics of aluminium alloy 7050 were investigated by hot uniaxial compression tests in order to obtain the material parameters used in the CA model. The influences of process parameters(strain, strain rate and temperature) on the fraction of DRX and the average recrystallization grain(R-grain) size were investigated and discussed. It is found that larger stain, higher temperature and lower strain rate(less than 0.1 s^(–1)) are beneficial to the increasing fraction of DRX. And the deformation temperature affects the mean R-grain size much more greatly than other parameters. It is also noted that there is a critical strain for the occurrence of DRX which is related to strain rate and temperature. In addition, it is shown that the CA model with topology deformation is able to simulate the microstructural evolution and the flow behavior of aluminium alloy 7050 material under various deformation conditions.

Cellular automaton modeling of pedestrian movement behavior on an escalator

As a convenient passenger transit facility between floors with different heights, escalators have been extensively used in shopping malls, metro stations, airport terminals, etc. Compared with other vertical transit facilities including stairs and elevators, escalators usually have large transit capacity. It is expected to reduce pedestrian traveling time and thus improve the quality of pedestrian’s experiences especially in jamming conditions. However, it is noticed that pedestrians may present different movement patterns, e.g., queuing on each step of the escalator, walking on the left-side and meanwhile standing on the right-side of the escalator. These different patterns affect the actual escalator traffic volume and finally the passenger spatiotemporal distribution in different built environments. Thus, in the present study, a microscopic cellular automaton(CA) simulation model considering pedestrian movement behavior on escalators is built. Simulations are performed considering different pedestrian movement speeds, queuing modes, and segregation on escalators with different escalator speeds.The actual escalator capacities under different pedestrian movement patterns are investigated. It is found that walking on escalators will not always benefit escalator transit volume improvement, especially in jamming conditions.