粒子凝聚模拟软件开发与应用研究
发布时间：2019-06-06 11:39
【摘要】：粒子凝聚是自然界常见现象,雪花的形成、晶体薄膜的生长、闪电的产生、土壤胶体凝聚等都是粒子凝聚过程。粒子凝聚是一个随机的非线性过程,在随机过程的背后往往存在自组织现象和自相似性。一些社会现象,如城市的增长等,也具有类似的特征。但是不同现象的粒子是如何凝聚的?不同条件下形成的凝聚体有什么样的特征?如何控制粒子凝聚?这些问题一直是科学家不断探索的问题,对这些问题的认识有助于了解这些自然和社会现象的形成和发展规律。由于实验方法研究粒子凝聚很难得到随机现象背后的规律性,因此利用计算机模拟粒子凝聚的结构和行为,正逐渐成为一种有力的研究手段。论文研究的目的是结合GIS中的一些方法,改进计算机粒子凝聚模拟算法和分析方法,开发一个粒子凝聚模拟软件,为粒子凝聚模拟应用提供技术平台。 本研究的主要工作和成果有以下六个方面： 1、粒子凝聚模型的算法研究与改进。论文研究了Eden模型、扩散限制凝聚模型(DLA)、反应限制凝聚模型(RLA)、电击穿模型(DBM)和团簇-团簇凝聚模型(CCA),包括扩散限制团簇凝聚模型(DLCA)、反应限制团簇凝聚模型(RLCA)等粒子凝聚模型的实现算法。针对已有算法存在的不足,提出了改进方法：1)已有的DLA算法在确认粒子周围是否被占据时,采用遍历查找的方法,速度较慢,本研究采用在已凝聚粒子上标记前后左右四个位置的占据情况,不再查找,加快了模拟速度。2)在DLCA算法中使用并查集方法对粒子进行查找和合并粘结处理,加快了DLCA模拟的速度。3)在DLCA模型中,目前的实现算法没有考虑粒子的同步运动,即在分析一个粒子移动时,假定其它粒子是静止的。本论文提出了粒子同步运动的连续碰撞检测DLCA算法,方法是先根据粒子运动方向和速度,估计粒子运动轨迹是否相交；如果在相同时间点有相交,则使用自适应技术检测粒子移动的步长；然后采用回退技术将检测出粒子在这种情况下的碰撞位置。使用这种连续检测粒子碰撞的方法,更符合粒子运动的实际情况。 2、凝聚体的分形特征分析,包括不同模型凝聚体的分维值比较、分维值的随机性分析、凝聚过程中分维值的变化、粘结概率对分形的影响和不同分维值计算方法的结果比较等。分析结果表明：1)Eden凝聚体的分维值接近整数,表明分形特征不明显；DLCA和DLA凝聚体的分形特征明显,DLCA凝聚体分维值比DLA凝聚体分维值小；DBM凝聚体分维值与被击穿的概率指数m相关,随着m的增大,分维值变小。2)DLA凝聚过程和DLCA凝聚过程中分维值都是波动的,但波动的幅度都不大。3)粘结概率对分形模型有影响,粘结概率越小,形成的凝聚体越密实,分维值越大。4)对同个凝聚体,用不同的分维值计算方法(盒计数法、回转半径法、SandBox法和密度-密度相关函数法)得到的分维值是有差异的,盒计数法和密度-密度相关函数法计算的分维值比较相近,回转半径法计算出来的分维值偏小,SandBox法计算出来的分维值较大。 3、凝聚体几何特征及与分形特征的关系研究。以往对凝聚体的特征研究主要以分形维数作为定量研究指标,而对其他的几何特征及其与分形维数的定量关系研究较少。论文针对目前孔隙度计算方法在计算各向异性凝聚体的孔隙度时存在的问题,提出利用外接凸多边形来代替原先的外接圆,并利用GIS中的凸包算法来获得外接凸多边形,计算出的孔隙度更符合实际情况。根据实际分析的需要,引入开放度和紧凑度的概念,并提出了计算方法。研究选取了不同模型凝聚体进行比较,分析结果表明：分维值大的凝聚体孔隙度和开放度小、紧凑度大,定量地反映了分维值与孔隙度、开放度、紧凑度的关系。 4、粒子凝聚模拟及可视化软件开发。本研究利用GDI+技术和OpenGL技术,开发了粒子凝聚模拟软件,软件包括粒子凝聚(二维和三维)模拟、凝聚体分形分析、凝聚体几何特征分析等模块。为了能更好地分析具有地理空间特征的粒子凝聚,在软件中还扩展了GIS功能,包括GIS基本功能、模拟结果与背景地图的叠置、研究对象的分形计算等。 5、粒子凝聚模拟及分形分析在土壤胶体凝聚的应用。本研究应用软件系统中的三维团簇凝聚模型模拟土壤胶体凝聚过程,显示随着粒子浓度或体积分数的增大,凝聚体分维值增大的规律；研究不同作用力下形成的凝聚体形态,这些作用力在形式上表现为粘结概率的影响,显示随着粘结概率由0.1变化到1时,凝聚体的分形维数值由2.48降低至1.87,即粘结概率越小,形成的凝聚体结构越致密；研究温度对凝聚的影响,显示温度对团聚体分形结构影响不大,只是影响凝聚的速度。 6、上海市中心城区城市扩展模拟及分形分析。本研究应用改进的Eden模型来模拟城市扩展,方法是根据影响城市发展的因素,确定建成区凝聚体外围栅格转化为城市的概率,再根据转化概率随机选取外围栅格作为新的城市栅格,通过确定性与随机性相结合方法模拟城市扩展。利用改进的Eden模型模拟了1947—1964年、1964—1979年和1979—1993年的城市扩展,通过与实际的建成区范围进行比较,显示模拟结果能够反映城市发展趋势。研究上海市中心城区四个时期建成区形态的分维值,发现除了1947年外,不同时期的城市建成区形态都具有比较明显的分形特征,分维值基本一致(1.7左右)。研究还发现对分形特征明显的城市建成区凝聚体来说,分维值越大,紧凑度也越大。
[Abstract]:Particle aggregation is a common phenomenon in nature, the formation of snowflakes, the growth of crystal thin films, the generation of lightning, the aggregation of soil colloids and so on are the process of particle agglomeration. Particle aggregation is a random non-linear process, and self-organization and self-similarity are often present behind the random process. Some social phenomena, such as the growth of the city, have similar characteristics. But how do the particles of different phenomena coalesce? What are the characteristics of the coacervate formed under different conditions? How to control particle coacervation? These problems have been an ongoing problem for scientists, and their awareness of these issues will help to understand the formation and development of these natural and social phenomena. It is hard to get the regularity of the random phenomenon by the experimental method, so the structure and behavior of the particle aggregation by using the computer are becoming a powerful research means. The purpose of the paper is to improve the computer particle aggregation simulation algorithm and the analysis method in combination with some methods in the GIS, and to develop a particle aggregation simulation software to provide a technical platform for the particle agglomeration simulation application. The main work and results of this study are the following six parties a study on the algorithm of surface:1, particle coacervation model In this paper, the Eden model, the diffusion-limited agglomeration model (DLA), the reaction-limited aggregation model (RLA), the electric breakdown model (DBM) and the cluster-cluster-cluster-aggregation model (CCA) are studied, including the diffusion-limited cluster coacervation model (DL). The Real-time Aggregation Model of the Particle-aggregation Model (RLCA) in the Reaction-restricted Cluster (RCA) An improved method is proposed for the shortcomings of the existing algorithms.1) The existing DLA algorithm is used to find out whether the surrounding of the particles is occupied or not, and the speed is slow. in that DLCA model, the current implementation algorithm doe not take into account the synchronous motion of the particle, i. e., in the analysis of a particle, when moving, it is assumed that other particles are In this paper, a continuous collision detection DLCA algorithm for particle synchronous motion is proposed. The method is based on the direction and velocity of the particle motion, and it is estimated that the particle motion trajectory is intersected. If there is an intersection at the same time point, the self-adaptive technique is used to detect the particle movement. step size; then, a rollback technique will be used to detect the collision of the particles in this case hit position. Use this method of continuous detection of particle collisions that is more consistent with particle motion The fractal analysis of the aggregate, including the comparison of the fractal dimension of the coacervation of different models, the random analysis of the fractal dimension, the change of the fractal dimension in the coacervation, the influence of the bond probability on the fractal and the calculation of the different fractal dimension values. The results show that:1) The fractal dimension of the Eden coacervate is close to an integer, which indicates that the fractal feature is not obvious; the fractal feature of the DLCA and the DLA coacervate is obvious; the fractal dimension of the DLCA aggregate is smaller than that of the DLA coacervate; the fractal dimension of the DBM coacervate is related to the probability index m of the breakdown, and With the increase of m, the fractal dimension is smaller.2) The fractal dimension of the DLA coacervation process and the DLCA coacervation process is wave, but the amplitude of the fluctuation is not small.3) The bond probability has an effect on the fractal model, the smaller the bonding probability, the more dense the condensed body is formed, and the higher the fractal dimension value. The fractal dimension values obtained by using different fractal dimension value calculation methods (box counting method, turning radius method, Sandbox method and density-density correlation function method) are different, and the fractal dimension calculated by the box counting method and the density-density correlation function method is different. The value is similar, and the value of the fractal dimension calculated by the radius of gyration is small, and the SandBox method is calculated. The larger dimension value of the fractal dimension, the geometric characteristics of the coacervate and the fractal dimension In the past, the study of the relationship between the characteristics and the characteristics of the coacervation is mainly based on the fractal dimension as the quantitative research index, and the other geometric features and their relationship with the fractal dimension In order to solve the problems existing in the calculation of the porosity of an anisotropic coacervate, an external convex polygon is used instead of the original circle, and the convex polygon is obtained by using the convex hull algorithm in the GIS to calculate the porosity. according to the needs of the practical analysis, the concept of the openness and the compactness is introduced, The calculation method is presented in this paper. The results show that the size of the fractal dimension and the degree of openness are small and the compactness is large, and the fractal dimension value and the porosity and the degree of openness are reflected quantitatively. the relationship of the compactness, the particle coacervation mode, The software of particle aggregation simulation is developed by using GDI + technology and OpenGL. The software includes particle aggregation (two-dimensional and three-dimensional) simulation, fractal analysis of coacervation, and coacervation. In order to better analyze the agglomeration of the particles with the characteristics of the geospatial features, the GIS function is also extended in the software, including the basic function of GIS, the superposition of the simulation result and the background map, and the research. The fractal calculation of the object and the like. In this paper, the three-dimensional cluster coacervation model in the application software system is used to simulate the soil colloid coacervation process, and the law of the increase of the particle concentration or volume fraction and the increase of the fractal dimension value of the coacervation body is shown. The shape of the coacervate formed by the force is shown as the influence of the bonding probability in the form. When the bonding probability is changed from 0.1 to 1, the fractal dimension of the coacervate decreases from 2.48 to 1.87, that is, the smaller the bonding probability, the more dense the condensed body structure is formed. And the influence of the temperature on the aggregation is studied, and the effect of the temperature on the fractal structure of the agglomerate is not affected. Big, it's just the speed of the coacervation.6. Shanghai Center. The urban expansion simulation and the fractal analysis of the urban area are carried out. The improved Eden model is applied to simulate the urban expansion. The method is based on the factors that affect the development of the city, and the probability that the peripheral grid of the condensed body in the built-up area is transformed into the city is determined, and then randomly selected according to the conversion probability. Take the peripheral grid as a new city grid, with certainty and with An improved Eden model is used to model the urban expansion in 1947-1964,1964-1979 and 1979-1993, and the model is compared with the actual built-up area. The results can reflect the development trend of the city. The fractal dimension of the built-up area in the four periods of the central urban area of Shanghai is studied. The dimension value is basically the same (about 1.7). The study also found that the urban built-up area coacervate with obvious fractal features
【学位授予单位】：华东师范大学
【学位级别】：博士
【学位授予年份】：2013
【分类号】：P208;TP311.52
本文编号：2494339
[Abstract]:Particle aggregation is a common phenomenon in nature, the formation of snowflakes, the growth of crystal thin films, the generation of lightning, the aggregation of soil colloids and so on are the process of particle agglomeration. Particle aggregation is a random non-linear process, and self-organization and self-similarity are often present behind the random process. Some social phenomena, such as the growth of the city, have similar characteristics. But how do the particles of different phenomena coalesce? What are the characteristics of the coacervate formed under different conditions? How to control particle coacervation? These problems have been an ongoing problem for scientists, and their awareness of these issues will help to understand the formation and development of these natural and social phenomena. It is hard to get the regularity of the random phenomenon by the experimental method, so the structure and behavior of the particle aggregation by using the computer are becoming a powerful research means. The purpose of the paper is to improve the computer particle aggregation simulation algorithm and the analysis method in combination with some methods in the GIS, and to develop a particle aggregation simulation software to provide a technical platform for the particle agglomeration simulation application. The main work and results of this study are the following six parties a study on the algorithm of surface:1, particle coacervation model In this paper, the Eden model, the diffusion-limited agglomeration model (DLA), the reaction-limited aggregation model (RLA), the electric breakdown model (DBM) and the cluster-cluster-cluster-aggregation model (CCA) are studied, including the diffusion-limited cluster coacervation model (DL). The Real-time Aggregation Model of the Particle-aggregation Model (RLCA) in the Reaction-restricted Cluster (RCA) An improved method is proposed for the shortcomings of the existing algorithms.1) The existing DLA algorithm is used to find out whether the surrounding of the particles is occupied or not, and the speed is slow. in that DLCA model, the current implementation algorithm doe not take into account the synchronous motion of the particle, i. e., in the analysis of a particle, when moving, it is assumed that other particles are In this paper, a continuous collision detection DLCA algorithm for particle synchronous motion is proposed. The method is based on the direction and velocity of the particle motion, and it is estimated that the particle motion trajectory is intersected. If there is an intersection at the same time point, the self-adaptive technique is used to detect the particle movement. step size; then, a rollback technique will be used to detect the collision of the particles in this case hit position. Use this method of continuous detection of particle collisions that is more consistent with particle motion The fractal analysis of the aggregate, including the comparison of the fractal dimension of the coacervation of different models, the random analysis of the fractal dimension, the change of the fractal dimension in the coacervation, the influence of the bond probability on the fractal and the calculation of the different fractal dimension values. The results show that:1) The fractal dimension of the Eden coacervate is close to an integer, which indicates that the fractal feature is not obvious; the fractal feature of the DLCA and the DLA coacervate is obvious; the fractal dimension of the DLCA aggregate is smaller than that of the DLA coacervate; the fractal dimension of the DBM coacervate is related to the probability index m of the breakdown, and With the increase of m, the fractal dimension is smaller.2) The fractal dimension of the DLA coacervation process and the DLCA coacervation process is wave, but the amplitude of the fluctuation is not small.3) The bond probability has an effect on the fractal model, the smaller the bonding probability, the more dense the condensed body is formed, and the higher the fractal dimension value. The fractal dimension values obtained by using different fractal dimension value calculation methods (box counting method, turning radius method, Sandbox method and density-density correlation function method) are different, and the fractal dimension calculated by the box counting method and the density-density correlation function method is different. The value is similar, and the value of the fractal dimension calculated by the radius of gyration is small, and the SandBox method is calculated. The larger dimension value of the fractal dimension, the geometric characteristics of the coacervate and the fractal dimension In the past, the study of the relationship between the characteristics and the characteristics of the coacervation is mainly based on the fractal dimension as the quantitative research index, and the other geometric features and their relationship with the fractal dimension In order to solve the problems existing in the calculation of the porosity of an anisotropic coacervate, an external convex polygon is used instead of the original circle, and the convex polygon is obtained by using the convex hull algorithm in the GIS to calculate the porosity. according to the needs of the practical analysis, the concept of the openness and the compactness is introduced, The calculation method is presented in this paper. The results show that the size of the fractal dimension and the degree of openness are small and the compactness is large, and the fractal dimension value and the porosity and the degree of openness are reflected quantitatively. the relationship of the compactness, the particle coacervation mode, The software of particle aggregation simulation is developed by using GDI + technology and OpenGL. The software includes particle aggregation (two-dimensional and three-dimensional) simulation, fractal analysis of coacervation, and coacervation. In order to better analyze the agglomeration of the particles with the characteristics of the geospatial features, the GIS function is also extended in the software, including the basic function of GIS, the superposition of the simulation result and the background map, and the research. The fractal calculation of the object and the like. In this paper, the three-dimensional cluster coacervation model in the application software system is used to simulate the soil colloid coacervation process, and the law of the increase of the particle concentration or volume fraction and the increase of the fractal dimension value of the coacervation body is shown. The shape of the coacervate formed by the force is shown as the influence of the bonding probability in the form. When the bonding probability is changed from 0.1 to 1, the fractal dimension of the coacervate decreases from 2.48 to 1.87, that is, the smaller the bonding probability, the more dense the condensed body structure is formed. And the influence of the temperature on the aggregation is studied, and the effect of the temperature on the fractal structure of the agglomerate is not affected. Big, it's just the speed of the coacervation.6. Shanghai Center. The urban expansion simulation and the fractal analysis of the urban area are carried out. The improved Eden model is applied to simulate the urban expansion. The method is based on the factors that affect the development of the city, and the probability that the peripheral grid of the condensed body in the built-up area is transformed into the city is determined, and then randomly selected according to the conversion probability. Take the peripheral grid as a new city grid, with certainty and with An improved Eden model is used to model the urban expansion in 1947-1964,1964-1979 and 1979-1993, and the model is compared with the actual built-up area. The results can reflect the development trend of the city. The fractal dimension of the built-up area in the four periods of the central urban area of Shanghai is studied. The dimension value is basically the same (about 1.7). The study also found that the urban built-up area coacervate with obvious fractal features
【学位授予单位】：华东师范大学
【学位级别】：博士
【学位授予年份】：2013
【分类号】：P208;TP311.52
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