粒子凝聚模擬軟件開發(fā)與應(yīng)用研究
發(fā)布時間：2019-06-06 11:39
【摘要】：粒子凝聚是自然界常見現(xiàn)象,雪花的形成、晶體薄膜的生長、閃電的產(chǎn)生、土壤膠體凝聚等都是粒子凝聚過程。粒子凝聚是一個隨機(jī)的非線性過程,在隨機(jī)過程的背后往往存在自組織現(xiàn)象和自相似性。一些社會現(xiàn)象,如城市的增長等,也具有類似的特征。但是不同現(xiàn)象的粒子是如何凝聚的?不同條件下形成的凝聚體有什么樣的特征?如何控制粒子凝聚?這些問題一直是科學(xué)家不斷探索的問題,對這些問題的認(rèn)識有助于了解這些自然和社會現(xiàn)象的形成和發(fā)展規(guī)律。由于實驗方法研究粒子凝聚很難得到隨機(jī)現(xiàn)象背后的規(guī)律性,因此利用計算機(jī)模擬粒子凝聚的結(jié)構(gòu)和行為,正逐漸成為一種有力的研究手段。論文研究的目的是結(jié)合GIS中的一些方法,改進(jìn)計算機(jī)粒子凝聚模擬算法和分析方法,開發(fā)一個粒子凝聚模擬軟件,為粒子凝聚模擬應(yīng)用提供技術(shù)平臺。 本研究的主要工作和成果有以下六個方面： 1、粒子凝聚模型的算法研究與改進(jìn)。論文研究了Eden模型、擴(kuò)散限制凝聚模型(DLA)、反應(yīng)限制凝聚模型(RLA)、電擊穿模型(DBM)和團(tuán)簇-團(tuán)簇凝聚模型(CCA),包括擴(kuò)散限制團(tuán)簇凝聚模型(DLCA)、反應(yīng)限制團(tuán)簇凝聚模型(RLCA)等粒子凝聚模型的實現(xiàn)算法。針對已有算法存在的不足,提出了改進(jìn)方法：1)已有的DLA算法在確認(rèn)粒子周圍是否被占據(jù)時,采用遍歷查找的方法,速度較慢,本研究采用在已凝聚粒子上標(biāo)記前后左右四個位置的占據(jù)情況,不再查找,加快了模擬速度。2)在DLCA算法中使用并查集方法對粒子進(jìn)行查找和合并粘結(jié)處理,加快了DLCA模擬的速度。3)在DLCA模型中,目前的實現(xiàn)算法沒有考慮粒子的同步運動,即在分析一個粒子移動時,假定其它粒子是靜止的。本論文提出了粒子同步運動的連續(xù)碰撞檢測DLCA算法,方法是先根據(jù)粒子運動方向和速度,估計粒子運動軌跡是否相交；如果在相同時間點有相交,則使用自適應(yīng)技術(shù)檢測粒子移動的步長；然后采用回退技術(shù)將檢測出粒子在這種情況下的碰撞位置。使用這種連續(xù)檢測粒子碰撞的方法,更符合粒子運動的實際情況。 2、凝聚體的分形特征分析,包括不同模型凝聚體的分維值比較、分維值的隨機(jī)性分析、凝聚過程中分維值的變化、粘結(jié)概率對分形的影響和不同分維值計算方法的結(jié)果比較等。分析結(jié)果表明：1)Eden凝聚體的分維值接近整數(shù),表明分形特征不明顯；DLCA和DLA凝聚體的分形特征明顯,DLCA凝聚體分維值比DLA凝聚體分維值�。籇BM凝聚體分維值與被擊穿的概率指數(shù)m相關(guān),隨著m的增大,分維值變小。2)DLA凝聚過程和DLCA凝聚過程中分維值都是波動的,但波動的幅度都不大。3)粘結(jié)概率對分形模型有影響,粘結(jié)概率越小,形成的凝聚體越密實,分維值越大。4)對同個凝聚體,用不同的分維值計算方法(盒計數(shù)法、回轉(zhuǎn)半徑法、SandBox法和密度-密度相關(guān)函數(shù)法)得到的分維值是有差異的,盒計數(shù)法和密度-密度相關(guān)函數(shù)法計算的分維值比較相近,回轉(zhuǎn)半徑法計算出來的分維值偏小,SandBox法計算出來的分維值較大。 3、凝聚體幾何特征及與分形特征的關(guān)系研究。以往對凝聚體的特征研究主要以分形維數(shù)作為定量研究指標(biāo),而對其他的幾何特征及其與分形維數(shù)的定量關(guān)系研究較少。論文針對目前孔隙度計算方法在計算各向異性凝聚體的孔隙度時存在的問題,提出利用外接凸多邊形來代替原先的外接圓,并利用GIS中的凸包算法來獲得外接凸多邊形,計算出的孔隙度更符合實際情況。根據(jù)實際分析的需要,引入開放度和緊湊度的概念,并提出了計算方法。研究選取了不同模型凝聚體進(jìn)行比較,分析結(jié)果表明：分維值大的凝聚體孔隙度和開放度小、緊湊度大,定量地反映了分維值與孔隙度、開放度、緊湊度的關(guān)系。 4、粒子凝聚模擬及可視化軟件開發(fā)。本研究利用GDI+技術(shù)和OpenGL技術(shù),開發(fā)了粒子凝聚模擬軟件,軟件包括粒子凝聚(二維和三維)模擬、凝聚體分形分析、凝聚體幾何特征分析等模塊。為了能更好地分析具有地理空間特征的粒子凝聚,在軟件中還擴(kuò)展了GIS功能,包括GIS基本功能、模擬結(jié)果與背景地圖的疊置、研究對象的分形計算等。 5、粒子凝聚模擬及分形分析在土壤膠體凝聚的應(yīng)用。本研究應(yīng)用軟件系統(tǒng)中的三維團(tuán)簇凝聚模型模擬土壤膠體凝聚過程,顯示隨著粒子濃度或體積分?jǐn)?shù)的增大,凝聚體分維值增大的規(guī)律；研究不同作用力下形成的凝聚體形態(tài),這些作用力在形式上表現(xiàn)為粘結(jié)概率的影響,顯示隨著粘結(jié)概率由0.1變化到1時,凝聚體的分形維數(shù)值由2.48降低至1.87,即粘結(jié)概率越小,形成的凝聚體結(jié)構(gòu)越致密；研究溫度對凝聚的影響,顯示溫度對團(tuán)聚體分形結(jié)構(gòu)影響不大,只是影響凝聚的速度。 6、上海市中心城區(qū)城市擴(kuò)展模擬及分形分析。本研究應(yīng)用改進(jìn)的Eden模型來模擬城市擴(kuò)展,方法是根據(jù)影響城市發(fā)展的因素,確定建成區(qū)凝聚體外圍柵格轉(zhuǎn)化為城市的概率,再根據(jù)轉(zhuǎn)化概率隨機(jī)選取外圍柵格作為新的城市柵格,通過確定性與隨機(jī)性相結(jié)合方法模擬城市擴(kuò)展。利用改進(jìn)的Eden模型模擬了1947—1964年、1964—1979年和1979—1993年的城市擴(kuò)展,通過與實際的建成區(qū)范圍進(jìn)行比較,顯示模擬結(jié)果能夠反映城市發(fā)展趨勢。研究上海市中心城區(qū)四個時期建成區(qū)形態(tài)的分維值,發(fā)現(xiàn)除了1947年外,不同時期的城市建成區(qū)形態(tài)都具有比較明顯的分形特征,分維值基本一致(1.7左右)。研究還發(fā)現(xiàn)對分形特征明顯的城市建成區(qū)凝聚體來說,分維值越大,緊湊度也越大。
[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
【學(xué)位授予單位】：華東師范大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2013
【分類號】：P208;TP311.52
本文編號：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
【學(xué)位授予單位】：華東師范大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2013
【分類號】：P208;TP311.52
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