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.

Mathematical model for flood routing based on cellular automaton

Increasing frequency and severity of flooding have caused tremendous damage in China, requiring more essential countermeasures to alleviate the damage. In this study, the dynamic simulation property of a cellular automaton was used to make further progress in flood routing. In consideration of terrain＇s influence on flood routing, we regarded the terrain elevation as an auxiliary attribute of a two-dimensional cellular automaton in path selection for flood routing and developed a mathematical model based on a cellular automaton. A numerical case of propagation of an outburst flood in an area of the lower Yangtze River was analyzed with both the fixed-step and variable-step models. The results show that the flood does not spread simultaneously in all directions, but flows into the lower place first, and that the submerged area grows quickly at the beginning, but slowly later on. The final submerged areas obtained from the two different models are consistent, and the flood volume balance test shows that the flood volume meets the requirement of the total volume balance. The analysis of the case shows that the proposed model can be a valuable tool for flood routing.

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.

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.

Two-dimensional cellular automaton model for simulating structural evolution of binary alloys during solidification

Two-dimensional cellular automaton(CA)simulations of phase transformations of binary alloys during solidification were reported.The modelling incorporates local concentration and heat changes into a nucleation or growth function,which is utilized by the automaton in a probabilistic fashion.These simulations may provide an efficient method of discovering how the physical processes involved in solidification processes dynamically progress and how they interact with each other during solidification.The simulated results show that the final morphology during solidification is related with the cooling conditions.The established model can be used to evaluate the phase transformation of binary alloys during solidification.

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%.

Simulation of α-Al grain formation in high vacuum die-casting Al-Si-Mg alloys with multi-component quantitative cellular automaton method

Al-Si-Mg alloys are the most commonly used material in high vacuum die-casting(HVDC),in which the morphology and distribution ofα-Al grains have important effect on mechanical properties.A multi-component quantitative cellular automaton(CA)model was developed to simulate the microstructure and microsegregation of HVDC Al-Si-Mg alloys with different Si contents(7%and 10%)and cooling rates during solidification.The grain number and average grain size with electron backscatter diffraction(EBSD)analysis were used to verify the simulation.The relationship between grain size and nucleation order as well as nuclei density was investigated and discussed.It is found that the growth of grains will be restrained in the location with higher nuclei density.The influence of composition and cooling rate on the solute transport reveals that for AlSi7Mg0.3 alloy the concentration of solute Mg in liquid is higher at the beginning of eutectic solidification.The comparison between simulation and experiment results shows that externally solidified crystals(ESCs)have a significant effect for samples with high cooling rate and narrow solidification interval.

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.

A cellular automaton model for the ventricular myocardium considering the layer structure

A cellular automaton model for the ventricular myocardium considering the layer structure has been established. The three types of cells in this model differ principally in the repolarization characteristics. For the normal travelling waves in this model, the computer simulation results show the R, S, and T waves and they are qualitatively in agreement with the standard electrocardiograph. Phenomena such as the potential decline of point J and segment ST and the rise of the potential line after the T wave appear when the ischemia occurs in the endocardium. The spiral wave has also been simulated, and the corresponding potential has a lower amplitude, higher frequency, and wider R wave, which accords with the distinguishing feature of the clinical electrocardiograph. Mechanisms underlying the above phenomena are analyzed briefly.

Urban rail departure capacity analysis based on a cellular automaton model

As an important traffic mode, urban rail transit is constantly developing toward improvement in service capacity and quality. When an urban rail transit system is evaluated in terms of its service capacity, the train departure capacity is an important index that can objectively reflect the service level of an urban rail transit facility. In light of the existing cellular automaton models, this paper proposes a suitable cellular automaton model to analyze the train departure capacity of urban rail transit under different variable factors and conditions. The established model can demonstrate the train operating processes by implementing the proposed sound rules, including the rules of train departure at the origin and intermediate stations, and the velocity and position updating rules. The properties of train traffic are analyzed via numerical experiments. The numerical results show that the departure capacity is negatively affected by the train departure control manner. In addition, （i） the real-time signal control can offer a higher train service frequency; （ii） the departure capacity gradually rises with the decrease in the line design speed to a limited extent; （iii） the departure capacity decreases with extension in the train length; （iv） the number of departed trains decreases as the train stop time increases; （v） the departure capacity is not affected by the section length. However, the longer the length, the worse the service quality of the urban rail transit line. The experiments show that the proposed cellular automaton model can be used to analyze the train service capacity of an urban rail transit system by performing quantitative analysis under various considered factors, conditions, and management modes.

Modeling the dendritic evolution and micro-segregation of cast alloy with cellular automaton

In order to precisely describe the dendritic morphology and micro-segregationduring solidification process, a novel continuous model concerning the different physicalproperties in the solid phase, liquid phase and interface is developed. Coupling the heat and solutediffusion with the transition rales, the dendrite evolution is simulated by cellular automatonmethod. Then, the solidification microstructure evolution of a small ingot is simulated by usingthis method. The simulated results indicate that this model can simulate the dendrite growth, showthe second dendrite arm and tertiary dendrite arm, and reveal the micro-segregation in theinter-dendritic zones. Furthermore, the columnar-to-equiaxed transition (CET) is predicted.

Numerical simulation on dendritic growth of Al-Cu alloy under convection based on the cellular automaton lattice Boltzmann method

A numerical model is developed by coupling the cellular automaton(CA)method and the lattice Boltzmann method(LBM)to simulate the dendritic growth of Al-Cu alloy in both two and three dimensions.An improved decentered square algorithm is proposed to overcome the artificial anisotropy induced by the CA cells and to realize simulation of dendritic growth with arbitrary orientations.Based on the established CA-LBM model,effects of forced convection and gravity-driven natural convection on dendritic growth are studied.The simulation results show that the blocking effect of dendrites on melt flow is advanced with a larger number of seeds.The competitive growth of the converging columnar dendrites is determined by the interaction between heat flow and forced convection.Gravity-driven natural convection leads to highly asymmetric growth of equiaxed dendrites.With sinking downwards of the heavy solute,chimney-like or mushroom-like solute plumes are formed in the melt in front of the columnar dendrites when they grow along the gravitational direction.More details on dendritic growth of Al-Cu alloy under convection are revealed by 3D simulations.

Cellular automaton simulation of peritectic solidification of a C-Mn steel

A cellular automaton model has been developed to simulate the microstructure evolution of a C-Mn steel during the peritectic solidification. In the model, the thermodynamics and solute diffusion of multi-component systems were taken into account by using Thermo-Calc and Dictra software package. Scheil model was used to predict the relationship between the solid fraction and the temperature, which was used to calculate the movement velocity of the L/δ and the L/y interfaces. A mixed-mode model in multi-component systems was adopted to calculate the movement velocity of the 6/7 interface. To validate the cellular automaton model, the variation of manganese distribution was studied. The simulated results showed a good agreement with experimental results reported in literatures. Meanwhile, the simulated growth kinetics of peritectic solidification agreed well with the experimental results obtained using confocal scanning laser microscopy （CSLM）. The model can simulate the growth kinetics of the peritectic solidification and the distribution of concentrations of all components in grains.

Simulation of microstructural evolution in directional solidification of Ti-45at.%Al alloy using cellular automaton method

The microstructural evolution of Ti-45 at.%Al alloy during directional solidification was simulated by applying a solute diffusion controlled solidification model.The obtained results have shown that under high thermal gradients the stable primary spacing can be adjusted via branching or competitive growth.For dendritic structures formed under a high thermal gradient,the secondary dendrite arms are developed not very well in many cases due to the branching mechanism under a constrained dendritic growth condition.Furthermore,it has been observed that,with increasing pulling velocity,there exists a cell/dendrite transition region consisting of cells and dendrites,which varies with the thermal gradient in a contradicting way,i.e.increase of the thermal gradient leading to the decrease of the range of the transition region.The simulations agree reasonably well with experiment results.

ONE-DIMENSIONAL CELLULAR AUTOMATON MODEL OFTRAFFIC FLOW BASED ON CAR-FOLLOWING IDEA

An improved one-dimensional CA ( Cellular Automaton) traffic model was proposed to describe the highway traffic under the periodic boundary conditions. This model was based on the idea of the car-following model, which claims that the motion of a vehicle at one time step depends on both its headway and the synchronous motion of the front vehicle, thus including indirectly the influence of its sub-neighboring vehicle. It? addition, the so-called safety distance was introduced to consider the deceleration behavior of vehicles and the stochastic factor was taken into account by introducing the deceleration probability. Meanwhile, the conditional deceleration in the model gives a better description of the phenomena observed on highways. It is found that there exists the metastability and hysteresis effect of traffic flow in the neighborhood of critical density under different initial conditions. Since this model gives a reasonable depiction of the motion of a single vehicle, it is easy to be extended to the case of traffic flow tinder the control of traffic lights in cities.

Combined Cellular Automaton Model for Dynamic Recrystallization Evolution of 42CrMo Cast Steel

The dynamic recrystallization(DRX) simulation performance largely depends on simulated grain topological struc?tures. However, currently solutions used di erent models for describing two?dimensional(2 D) and three?dimensional(3 D) grain size distributions. Therefore, it is necessary to develop a more universal simulation technique. A cellular automaton(CA) model combined with an optimized topology deformation technology is proposed to simulate the microstructural evolution of 42 CrMo cast steel during DRX. In order to obtain values of material constants adopted in the CA model, hot deformation characteristics of 42 CrMo cast steel are investigated by hot compression metal?lographic testing. The proposed CA model deviates in two important aspects from the regular CA model. First, an optimized grain topology deformation technology is utilized for studying the hot compression e ect on the topology of grain deformation. Second, the overlapping grain topological structures are optimized by using an independent component analysis method, and the influence of various thermomechanical parameters on the nucleation process, grain growth kinetics, and mean grain sizes observed during DRX are explored. Experimental study shows that the average relative root mean square error(RRMSE) of the mean grain diameter obtained by the regular CA model is equal to 0.173, while the magnitude calculated using the proposed optimized CA model is only 0.11. This paper pro?poses a novel combined CA model for simulating the microstructural evolution of 42 CrMo cast steel, which notably uses a ICA?based grain topology deformation method to optimize the overlapping grain topological structures in simulation.

A High-Performance Cellular Automaton Model of Tumor Growth with Dynamically Growing Domains

Tumor growth from a single transformed cancer cell up to a clinically apparent mass spans many spatial and temporal orders of magnitude. Implementation of cellular automata simulations of such tumor growth can be straightforward but computing performance often counterbalances simplicity. Computationally convenient simulation times can be achieved by choosing appropriate data structures, memory and cell handling as well as domain setup. We propose a cellular automaton model of tumor growth with a domain that expands dynamically as the tumor population increases. We discuss memory access, data structures and implementation techniques that yield high-performance multi-scale Monte Carlo simulations of tumor growth. We discuss tumor properties that favor the proposed high-performance design and present simulation results of the tumor growth model. We estimate to which parameters the model is the most sensitive, and show that tumor volume depends on a number of parameters in a non-monotonic manner.

Simulation of Spin-3/2 Blume-Capel Model on a Cellular Automaton with Heating and Cooling Algorithm

The spin-3/2 B1ume-Capel model is studied using the heating and cooling algorithms improved from the Creutz cellular automaton （CCA）. The calculations are done on various sizes of the simple cubic lattice in the 0 ≤ D/J ≤ 5 parameter region. The phase diagram of the model and temperature variation of the thermodynamic quantities are obtained. We confirm the existence of a critical end point within the heating calculations. However, in contrast to the heating calculations, we do not obtain the first-order line at low temperature with cooling algorithm calculations. The results are compared with those of other theories.

Modeling of solidification grain structure for Ti-45%Al alloy ingot by cellular automaton

A cellular automaton model for simulating grain structure formation during solidification processes of Ti-45%Al(mole fraction) alloy ingot was developed, based on finite differential method for macroscopic modeling of heat transfer and a cellular automaton technique for microscopic modeling of nucleation, growth, solute redistribution and solute diffusion. The relation between the growth velocity of a dendrite tip and the local undercooling, which consists of constitutional, thermal, curvature and attachment kinetics undercooling is calculated according to the Kurz-Giovanola-Trivedi model. The effect of solidification contraction is taken into consideration. The influence of process variables upon the resultant grain structures was investigated. Special moving allocation technique was designed to minimize the computation time and memory size associated with a large number of cells. The predicted grain structures are in good agreement with the experimental results.

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。