Papers by Keyword: Cellular Automaton

Abstract: A mathematical physical model of microstructure evolution in Al-Si eutectic solidification process based on cellular automaton (CA) model was developed. Before the establishment of the model, the relevant near-eutectic experiments were carried out to analyze the effect of cooling rates measured by temperature curves on the eutectic structure which was observed through optical microscope (OM) and scanning electron microscope (SEM). Then a multiphase nucleation-growth CA model was applied to simulate the Al-Si irregular eutectic structure. The model adopted an alternative nucleation mechanism to investigate the influence of the critical nucleation value associated with solute concentration during solidification process. The growth kinetics took into account the solute and thermal field. According to the crystal structure of nonfaceted eutectic Al and faceted eutectic Si, different capturing rules were employed to calculate the growth of eutectic. In addition, the model was also used to research the irregular eutectic growth under different undercooling conditions. The results revealed that smaller critical nucleation value (absolute value) or higher eutectic undercooling tended to get a more refined eutectic microstructure. By compared with experimental results, it is indicated that the microstructure evolution of Al-Si eutectic growth can be reproduced quantitatively by numerical simulation with this model.

Abstract: The eutectic structure of aluminum alloys has different morphology. To describe these a different image processing and analysis workflow needs to be built. To assign the different image processing steps to the different structure automatically a computational method had to be developed. In the image processing methods several cellular automata operate. For this expediently a cellular automaton was developed to classify the different eutectic structures. In materials engineering applications a HPP automata is used extensively therefore this type of automata were chosen to solve the mentioned problem. This article shows the simplicity of this method as well as the desired evaluation method.

Abstract: The established cellular automata model of dynamic recrystallization for 316LN simulated microstructure evolution of recrystallization nucleation and grain growth under different conditions. And on the basis of cellular automata model, the influence of strain, strain rate, deformation temperature on dynamic recrystallization behavior was analyzed. Though the hot compress experiment done on the Gleeble-3500 thermo mechanical simulator, combined with metallographic experiment, the microstructure at deformation temperature of 950 oC, 1050 oC and 1150 oC with strain rate of 0.001 s^-1, 0.01 s^-1, 0.1 s^-1 and 1 s^-1 was obtained. Simulation results are compared with metallographic microstructure, the error is small.

Abstract: Based on the theoretical model and physical mechanism of dynamic recrystallization (DRX) in metal materials, the dislocation density change, nucleation and grain growth model during the process of DRX are taken into account. And according to the nucleation driven by dislocation and grain growth kinetic, transformation rules are made. A modeling methodology coupling fundamental metallurgical principles based on amended nucleation rate with the cellular automaton (CA) technique is here derived to simulate the 316LN.The two-dimensional CA model uses quadrilateral element and periodic boundary condition and Von-Neumann neighbor type. The influence of strain, strain rate and deformation temperature on dynamic recrystallization volume fraction and average grain size are analyzed on the basis of established CA model.

Abstract: A modified 2-D CA model has been developed to simulate dynamic recrystallization behavior of Magnesium (Mg) alloy during hot deformation processing. Based on the fact that Mg has an HCP crystal structure with six-fold symmetry, the model employs the hexagonal CA lattice. The initial microstructure with prescribed grain size was generated by a normal grain growth algorithm. The DRX model consists of dislocation density evolution model, DRX nucleation model and recrystallization grain growth model. DRX grain morphology and size, flow curve were simulated by the present model. The calculated results were compared with the available experimental findings in AZ31 Mg alloy, the predictions show very good agreement with the experimental results.

Abstract: As Failure evolution processes algorithms of brittle rocks usually comply with the Single Instruction Multiple Data (SIMD) model, implementation efforts using such hardware resources are suitable. Graphics processor (GPU) is available SIMD hardware component nowadays, which can lead to substantial increase of computing performance. In this paper we propose a novel parallel cellular automaton algorithm for failure evolution processes of brittle rocks based on GPU. The details of implementation and optimized methods are presented. The performance results show that our GPU implementation achieves 39 times faster than original algorithm on common general purpose processor (CPU).

Abstract: We use the cellular automaton (CA) modeling to investigate the ferrite nucleation on the austenite grains. On the basis of the thermodynamics and kinetics of phase transformation from austenite to ferrite, the CA modeling demonstrates that the size of nucleated ferrite grains is increased with increasing of cooling rates, and nucleation process is finished instantly at a given cooling rate. The initial austenite grain size plays an important role in the obtained ferrite nucleation number, and the potential nucleation cells are increased.

Abstract: The austenitization of steels can occur in a wide variety of initial microstructures. In this study we addressed the transformation of banded pearlite steels. Banded pearlite initial structures similar to the real ones were created. In these structures the entire transformation process was simulated whose part processes are nucleation and grain growth. The nucleation is described by a free energy based model, and the Fick II. diffusion equation by using Finite Difference Method describes the grain growth. These models have been coupled in cellular automata simulations.

Abstract: In this paper, we develop models to analyze traffic flow of intelligent transportation system (ITS).The investigation into ITS is carried out in two aspects: one is the partly ITS, the other is the completely ITS. Comparisons between two systems show: with the increasing of intelligence degree, the superiority of each rule becomes more and more obvious. As is mentioned above, each rule is the most ideal for certain traffic state. While the detailed forms of different rules are not the same, the purpose of all rules is to promote the traffic flow. The phenomenon reveals the consistency of the ITS. In another word, the higher the intelligence degree of a system is, the larger its contributions to the traffic flow are.

Abstract: The paper presents an improved cellular automaton model according to the feature of evacuation near the outlet. We studied friction and turning factors that affect pedestrian evacuation speed. By using mathematical methods to derive expressions of friction function and turning function. The average pedestrian outflow of the simulation that includes the effect of both the frictional function and the turning function agrees well with experiment result. On the contrary, the simulation results that only include the effect of the frictional function are not corresponding to the experiment results well. Simulation results show that friction and turning can not be ignored. By analyzing the simulation results, it verified that the model can accurately reflect the actual evacuation process and has practical value.