Papers by Keyword: Cellular Automata (CA)

Abstract: In this article a model based on cellular automata (CA) is proposed to simulate the degradation for biodegradable polymer. The transformational rule of this model is constructed based on the hydrolysis reaction, oligomer diffusion equations and the relationship between intensity and number average molecular weight of the polymer. Furthermore, polymer DLPLA plate corresponding to this CA model was carried out. The simulation shows the middle hollow result which is accordance with the experiment phenomenon. The molecular in the degradation process has good fit with the experiment data. It proves that the model in this article is right and can provide numerical lead for the designs of biodegradable polymer devices.

Abstract: Cellular automaton (CA) has been widely investigated as random number generators (RNGs). However, the CA rule and the number of neighbors must be chosen carefully for good randomness. In Ref. [11], non-uniform CA with next nearest neighborhood was applied to generate a pseudo-random sequence. Considering that non-uniform CA has more complex implementation in hardware and needs lager memory to store different rules than uniform CA. In this paper, we propose new RNGs based on uniform CA with next nearest neighborhood. Time spacing technique and NIST statistical test suite are used to find optimal rules for uniform CA. Experiment results show that the sequences generated by uniform CA with optimal rules successfully passed all tests in the NIST suite.

Abstract: As a typical traffic bottleneck, the freeway weaving section is one source of vehicle conflict and an accident-prone area. This paper presents a cellular automaton model to characterize accident-induced traffic behavior around the weaving section, in which different accident sites are considered. The spatial-temporal profiles are presented after the numerical simulation. It is shown that the accident car not only causes a local jam behind the accident car, but also causes vehicles to cluster in the bypass lane. The accident occurring in lane 1 (the left lane) in the weaving section are more inclined to cause traffic jam and the decrease of traffic capacity than in lane 2 (the right lane). Furthermore, the curves of saturated flux of weaving section against different accident sites are given. It is found that the capacity of weaving section will decrease fastest when the accident is located in the downstream of weaving section.

Abstract: Distributed control, represented by Cellular Automata (CA), has advantage over centralized control for Modular Self-Reconfigurable Robot (MSRR) in capability of extension, efficiency and robustness. But due to the fact that the modular constraints, e.g., the number of DOF and the physical geometry, etc., the ideal CA rules cannot be implemented on the real robot system easily. The goal of the research is on design and implementation of distributed control based on integrated module design and CA rules arrangement. 2-DOF cubic-shaped modular model is first proposed, that is the Ubot module. Cellular rules are arranged according to the locomotion property of UBot module, and distributed control algorithm is designed for the robot to cross the uneven terrain. In simulation and on physical robotic hardware platform, experiments are carried out for UBot to verify the validity of CA theory applied on reconfiguration locomotion of UBot MSRR systems in complex environment.

Abstract: Computer simulation of a fluid flow through the declined porous structure is presented in the paper. The hypothesis related to the curious behaviour of the fluid flow inside assembled filters is verified using Lattice Gas Cellular Automata approach. Based on a set of computer simulations the reorganization of the fluid flow inside declined porous structure was obtained for different simulation setups. The results obtained from the computer simulation have shown that LGCA model is not only suitable for a theoretical prediction of a fluid flow inside porous structures but also it can be used as a visualization tool.

Abstract: A new soil-rock mechanics method—parallel cellular element method is introduced. In this method the integer analysis of structure is changed into a series of part analysis by using the idea of Cellular Automata. It may have a good future in soil-rock mechanics. The basic principle is introduced; the computing steps and results are presented. Based on the numerical results, the feasibility, advantages of cellular element method are discussed.

Abstract: Soil-rock mixture is a special kind of geological media,which is mixed of soil particles with weak intensity and rock blocks with strong stiffness and irregular shape. The rock blocks and soil particles cement with each other. The mechanical property of soil-rock mixture is different from rock and soil mass. This paper apply The digital image analysis technique is used to distinguish the features of rock and soil mass,and the model according to the corresponding relationship of cell and pixel is established ,then the numerical statistical laws of pixel can be obtained. As for the pixel between rock and soil mass that cant be distinguished distinctly, the cellular automata theory that with the mean function as the 2-dimensional transformation function is used to transform the image.Then the pixel of rock and soil mass can be distinguished.At the same time it can remove the effect of islanding pixels. Thus it can realize the more effective recognition for soil-rock mixture. It shows good effect through comparison.

Abstract: In order to overcome the drawbacks of Simple Genetic Algorithm such as cannot get the most optimal result, low convergence speed et al. Cellular Simple Genetic Algorithm-a new genetic algorithm based on Cellular Automata-is presented in this paper. Compared with the Simple Genetic Algorithm, the experiment results show the Cellular Simple Genetic Algorithm has remarkable advantages in following aspects: reducing the search-time and improving the precise of target function.

Abstract: For the production and development of Advanced High-Strength Steels adequate understanding of the formation mechanisms of the metallic microstructure is crucial. The superior properties of these steels are based on a sometimes delicate balance between thermodynamic (in) stability and dynamic processes, in which thermodynamic driving force and interface kinetics determine the development of the microstructure of the steel. In order to achieve further development and optimisation of such steels, experimental and modelling studies should go beyond microstructural characterisation in terms of average properties only. In this paper some examples will be given in which full (3D-) microstructures are simulated on the basis of the evolution of diffusional transformations. Although nucleation is not understood to sufficient extent to be predicted quantitatively, growth can adequately be described as governed by short-range diffusion at the interface (the basis for the interface mobility) and, in case of a partitioning phase transformation, the long-range diffusion behaviour (most notably of carbon). Whereas in the literature often one of the two processes is assumed to be rate-determining (interface control or diffusion control), physical modelling taking both into account ("mixed-mode growth") has also been effectuated. The widely used technique of Phase Field modelling and an alternative mixed-mode approach based on Cellular Automata will be presented and compared in this paper. Whereas Phase Field modelling is applicable to a wider range of processes, the Cellular-Automata method is highly efficient and allows 3D-simulations of entire process cycles within very limited computation times. Examples of these modelling techniques applied to the development of microstructures in Dual-Phase and Quenching-&-Partitioning steels are given.

Abstract: A cellular automata model with inhomogeneity and mobility was presented. The inhomogeneity in individuals’ behaviors was considered by assigning the distance on their neighbors, varying levels of infectivity and susceptibility. The individual mobility was reflected by random walk cellular automata. The proposed model can serve as a basis to simulate influenza A (H1N1) based on real data. We studied the effect of two population movement parameters on the epidemic propagation: the percentage and the max-distance of population movement. The results show that the epidemic spreading is more sensitive to the former. The infected individuals are positive growth while the percentage of population movement increases. And the number of infected individual eventually stabilizes in the case of plotting the relation of the max-distance against the infected.