| Common nature phenomenon of the formation of snowflakes, crystal film growth, lightning and soil colloid aggregation are particle aggregation process which is a rando nonlinear one. There is phenomenon of self-organization and self-similarity behind the random process. But how do the particles unite? What are the characteristics of the aggregates formed under different conditions? How to control particle cohesion? The understanding of these problems, which scientists continue to explore, helps to understand these natural and social phenomena of the formation and evelopment of law. The experimental method simulating particle cohesion is difficult to get regularity behind random phenomena, thus the use of computer simulating the structure and behavior of particle cohesion is becoming a powerful tool. In this context, this paper attempts to study the theory, methods, and applications of particle cohesion problem through computer simulation.The main scientific findings of this research include:1) This research has achieved and improved algorithm of variety models of particle cohesion. The algorithms of model of Eden, Diffusion-limited aggregation (DLA), Reaction-limted aggredation (RLA), Dielectric Breakdown Model(DBM) and Cluster-cluster aggregation (CCA),including Diffusion-limited aggregation cluster (DLCA) and Reaction-limted aggregation cluster (RLCA) have been achieved and cohesion results of a variety of models and qualitative analysis have been given. There are three improved methods for shortcomings of the existing algorithms.1) In exisitng DLA algorithms, the traversal find was used and slower in particles around the occupied ones, can not meet the particles aggregation requirements.This study used the mark four locations around the aggregated particles, speeding up the simulation speed.2)The union-find sets have been used in DLCA algorithm for finding and merging particles and the other nodes in the culster are removed, retaining only the root node of the clusters after bonding of the culsters. So the run speed has been enhanced.3) The continuous collision detection, which has been presented in the DLCA algorithm, makes simulation more accord with Colloidal Brownian motion laws.2) The fractal characteristics of particle aggregation simulating by different aggregation model have been analyzed. The random statistical analyses on fractal dimension of aggregation have been studied for DLA and DLCA simulation. The study compared with different methods of fractal dimension calculation.1) The research results show that Eden aggregation have no distinct fractal structure because its fractal dimension is approximately2, that the fractal dimensions of DLCA aggregation are smaller than those of DLA. The fractal dimensions of DBM are associated with the breakdown probability index m, as m increases, the fractal dimensions are smaller.2) The dimensional values of the DLA and DLCA aggregation process are fluctuating and the magnitude of the fluctuations is not large, indicating that the particle aggregaiton process is random, but has incomplete self-similarity and scale invariance.3) The bond probability affect the fractal model, as the smaller of bond probability, the aggregates are more dense, the greater fractal dimension.4) The same aggregates with different fractal dimension calculation method including box counting method, radius of gyration method, SandBox and density-density corrlation function, the fractal value is different. The calculated value by box counting method is similar by using density-density correlation function one, and the calculated value of radius of gyration method is less and greater by SandBox.3) The quantitative relationship between geometric charcteristics and fractal dimension value of aggregates has been discussed. In the past research people made fractal dimension as quantitative indicator of research for aggregates characteristics, and other geometric features, such as porosity, openness and compactness, and their quantitative relationship with fractal dimension were less studied. The geometric characteristics of porosity, openness and compactness have been defined and the calculated methods have been brought forward. The different aggregations of various models have been studied and the results show that the greater the fractal value, the porosity and openness is the less and the compactness is the greater. These results have clarified the quantitative relationship between geometric charcteristics and fractal value.4) Based on the technology of GDI+and OpenGL in.Net IDE, the architecture of the2D and3D system of particle cohesion simulation and software prototype system have been prsented. The functions of various levels and their inner-relationship have been clarified. The architecture is further described in two aspects:Platform Function and Platform Interface. It provids holistic framework and top-level guidance for studying technologies and implementing platform. Under the guidance of the overall architecture, the algorithms of particles aggregation simulation, the analysis of fractal and geometric characteristics have been implemented using computer program and the software platform of particles aggregate simulation has been constructed. The system also extends GIS functions, including basic functions of GIS, the DLA aggregations loading on map and fractal calculations of urban elements.5) The conceptual framework and methods presented in this research have been successfully applied to soil colloid aggregation simulation. The process of soil colloidal aggregation has been simulated by the three-dimensional cluster aggrgation model in software systems. The fractal dimension values of aggregation under various concentrations, the morphology of the aggregates formed in the different biasing force have been studied and the influence on aggregates of temperature also has been discussed. Soil colloidal particle simulation of three-dimensional cluster aggregation is an application example of software platform of the particle cohesion simulation system. These specific application cases have been developed to further verify the feasibility and applicability of the proposed methods and system.The application demonstrate that the fractal method renders a powerful mean for correlative applied research.6) The urban expansion simulation and fractal analysis in this research have been successfully applied to Shanghai downtown urban, China. In this study, the improved Eden model is used to simulate urban expansion. Based on the factors influencing urban development, the probabilities of periphery grids of bulit-up areas translating to city are detemined. According to the probabilty the peripheral grids are randomly selected as a new city. The improved Eden model is used to simulate urban expansion of from1947to1964, from1964to1979and from1979to1993, and compared with the actual range of built-up areas, the simulation results can reflect developed trends of urban morphology. The value of fractal dimension of built-up area in downtown of Shanghai four times is calculated. In addition to1947, the urban built-up area forms at different times have obvious fractal characteristics consistent with the fractal dimension about1.7. The study also finds a significant fractal urban built-up area, the greater the fractal dimension, the greater compactness. |
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