Numerical Simulation of Random Close Packing with Tetrahedra

The densest packing of tetrahedra is still an unsolved problem. Numerical simulations of random close packing of tetrahedra are carried out with a sphere assembly model and improved relaxation algorithm. The packing density and average contact number obtained for random close packing of regular tetrahedra is 0.6817 and 7.21 respectively, while the values of spheres are 0.6435 and 5.95. The simulation demonstrates that tetrahedra can be randomly packed denser than spheres. Random close packings of tetrahedra with a range of height are simulated as well. We find that the regular tetrahedron might be the optimal shape which gives the highest packing density of tetrahedra.     

Polytetrahedral nature of the dense disordered packings of hard spheres

We study the structure of numerically simulated hard sphere packings at different densities by investigating local tetrahedral configurations of the spheres. Clusters of tetrahedra adjacent by faces present relatively dense aggregates of spheres atypical for crystals. The number of spheres participating in such polytetrahedral configurations increases with densification of the packing, and at the Bernal's limiting density (the packing fraction around 0.64) all spheres of the packing become involved in such tetrahedra. Thus the polytetrahedral packing cannot provide further increase in the density, and alternative structural change (formation of crystalline nuclei) begins henceforth.     

Optimal packings of superdisks and the role of symmetry

Almost all studies of the densest particle packings consider convex particles. Here, we provide exact constructions for the densest known two-dimensional packings of superdisks whose shapes are defined by |x{1}|{2p}+|x{2}|{2p}or=0.5) and concave (0相似文献   

Dense packing in the monodisperse hard-sphere system: A numerical study

We report a numerical study of the close packing of monodisperse hard spheres. The close packings of hard spheres are produced by the Lubachesky-Stillinger (LS) compression algorithm and span the range from the disordered states to the ordered states. We provide quantitative evidence for the claim that the density and structural order of the arrested close packing can be determined by the compression rate, i.e., with slower rates producing denser and more ordered structures. Through deeply analyzing the structure of the resulting arrested close packings, a transition region has been identified in the plane of density and reciprocal compression rate, in between what have been historically thought of as amorphous and crystalline packings. We also find clear system size dependences in studying the structural properties of the packings from the disordered ones to the ordered ones. These detailed investigations, on the structure of the arrested close packings, may provide a link between the glassy states and the crystalline states in the hard spheres.     

Statistical Analysis of Simulated Random Packings of Spheres

This paper describes two algorithms for the generation of random packings of spheres with arbitrary diameter distribution. The first algorithm is the force‐biased algorithm of Mościński and Bargieł. It produces isotropic packings of very high density. The second algorithm is the Jodrey‐Tory sedimentation algorithm, which simulates successive packing of a container with spheres following gravitation. It yields packings of a lower density and of weak anisotropy. The results obtained with these algorithms for the cases of log‐normal and two‐point sphere diameter distributions are analysed statistically, i. e. standard characteristics of spatial statistics such as porosity (or volume fraction), pair correlation function of the system of sphere centres and spherical contact distribution function of the set‐theoretical union of all spheres are determined. Furthermore, the mean coordination numbers are analysed. These results are compared for both algorithms and with data from the literature based on other numerical simulations or from experiments with real spheres.     

Rotating bearings in regular and irregular granular shear packings

For 2D regular dense packings of solid mono-size non-sliding disks there is a mechanism for bearing formation under shear that can be explained theoretically. There is, however, no easy way to extend this model to include random dense packings which would better describe natural packings. A numerical model that simulates shear deformation for both near-regular and irregular packings is used to demonstrate that rotating bearings appear roughly with the same density in random and regular packings. The main difference appears in the size distribution of the rotating clusters near the jamming threshold. The size distribution is well described by a scaling form with a large-size cut-off that seems to grow without bounds for regular packings at the jamming threshold, while it remains finite for irregular packings. At packing densities above the jamming transition there can be no shear, unless the disks are allowed to break. Breaking of disks induces a large number of small local bearings. Clusters of rotating particles may contribute to e.g. pre-rupture yielding in landslides, snow avalanches and to the formation of aseismic gaps in tectonic fault zones.     

Dynamically tessellating algorithm for analysis of pore size distribution in particle agglomerates

We describe a novel physical application of the OctTree data structure [P. Meagher, Comput. Graphics Image Process 19(2) (1982) 129–147] in a dynamically tessellating algorithm, in conjunction with an object-oriented, constructive solid geometry library (DOC), to efficiently determine pore size distributions in large multi-particle systems. We apply the DOC library to investigate the evolving dynamics of pore formation in multi-particle systems, such as a mixture of smooth hard cubes and spheres and a collection of frictional soft spheres. We demonstrate that the algorithm is able to provide insight into the effect of structural changes on the porosity network; for example, during the uniaxial compaction of soft spheres, we find the number density of pores increases while the mean volume of the pores decreases. This trend is responsible for a shift in the distribution of the pore volumes to favour smaller volumes. We anticipate that the DOC method will have wider applications in the area of granular materials for studying the changes in pore structure in both experimental and numerical systems as a complement to the analysis of particle packing.     

Entropy of jammed matter

We investigate the nature of randomness in disordered packings of frictional spheres. We calculate the entropy of 3D packings through the force and volume ensemble of jammed matter, a mesoscopic ensemble and numerical simulations using volume fluctuation analysis and graph theoretical methods. Equations of state are obtained relating entropy, volume fraction and compactivity characterizing the different states of jammed matter. At the mesoscopic level the entropy vanishes at random close packing, while the microscopic states contribute to a finite entropy. The entropy of the jammed system reveals that the random loose packings are more disordered than random close packings, allowing for an unambiguous interpretation of both limits.     

非球体填充的组合球模型及松弛算法

现有的松弛算法由于仅用于球填充而只考虑颗粒的平动,故提出考虑非球体转动的改进松弛算法并采用组合球模型,使其能够模拟任意形状非球体的随机填充以及多种非球体的混合填充.用多个球体的外包络面近似一个非球体外形的组合球模型,将非球体之间的接触转化为球体之间的接触,从而简化并统一非球体接触判断算法.通过引入非球体的转矩和转角松弛机制,使改进松弛算法克服了"自锁"现象,并能生成非球体的随机密填充.算例表明,填充结果与现有的数值模拟及实验结果相符.     

基于超二次曲面的颗粒材料缓冲性能离散元分析

自然界或工业中普遍是由非球形颗粒组成的复杂体系,与球形颗粒相比,非球形颗粒间的高离散和咬合互锁可使冲击载荷引起的能量有效衰减实现缓冲作用.基于连续函数包络的超二次曲面单元能准确地描述非球形颗粒的几何形态,并可精确地计算单元间的接触碰撞作用.本文采用离散元方法对冲击载荷作用下非球形颗粒物质的缓冲性能进行数值分析,并与圆柱体冲击的理论结果和球体冲击的实验结果进行对比验证.在此基础之上,进一步研究了筒底作用力在不同颗粒层厚度和形状等因素影响下的变化规律.计算结果表明:不同颗粒形状都存在一个临界厚度H_c.当HH_c时,缓冲率随H的增加而增加;当HH_c时,缓冲率的变化不再显著并趋于稳定值.此外,减小颗粒表面尖锐度和增加或减小圆柱形和长方形颗粒的长宽比都会提高颗粒材料的缓冲效果.     

Experiments on random packings of ellipsoids

Recent simulations indicate that ellipsoids can pack randomly more densely than spheres and, remarkably, for axes ratios near 1.25:1:0.8 can approach the densest crystal packing (fcc) of spheres, with a packing fraction of 74%. We demonstrate that such dense packings are realizable. We introduce a novel way of determining packing density for a finite sample that minimizes surface effects. We have fabricated ellipsoids and show that, in a sphere, the radial packing fraction phi(r) can be obtained from V(h), the volume of added fluid to fill the sphere to height h. We also obtain phi(r) from a magnetic resonance imaging scan. The measurements of the overall density phi(avr), phi(r) and the core density phi(0) = 0.74 +/- 0.005 agree with simulations.     

Boerdijk-Coxeter helix and biological helices

Helices and dense packing of spherical objects are two closely related problems. For instance, the Boerdijk-Coxeter helix, which is obtained as a linear packing of regular tetrahedra, is a very efficient solution to some close-packing problems. The shapes of biological helices result from various kinds of interaction forces, including steric repulsion. Thus, the search for a maximum density can lead to structures related to the Boerdijk-Coxeter helix. Examples are presented for the -helix structure in proteins and for the structure of the protein collagen, but there are other examples of helical packings at different scales in biology. Models based on packing efficiency related to the Boerdijk-Coxeter helix, explain, mainly from topological arguments, why the number of amino acids per turn is close to 3.6 in -helices and 2.7 in collagen. Received 26 November 1998 and Received in final form 12 April 1999     

Thermodynamic properties of water in confined environments: a Monte Carlo study

Monte Carlo simulations of Mercedes-Benz water in a crowded environment were performed. The simulated systems are representative of both composite, porous or sintered materials and living cells with typical matrix packings. We studied the influence of overall temperature as well as the density and size of matrix particles on water density, particle distributions, hydrogen bond formation and thermodynamic quantities. Interestingly, temperature and space occupancy of matrix exhibit a similar effect on water properties following the competition between the kinetic and the potential energy of the system, whereby temperature increases the kinetic and matrix packing decreases the potential contribution. A novel thermodynamic decomposition approach was applied to gain insight into individual contributions of different types of inter-particle interactions. This decomposition proved to be useful and in good agreement with the total thermodynamic quantities especially at higher temperatures and matrix packings, where higher-order potential-energy mixing terms lose their importance.     

A model of binary assemblies of spheres

We propose a theoretical model of random binary assemblies of spheres at any packing fraction. We use the notion of geometrical neighborhood between grains that is defined through two generalizations of the Vorono? tessellation: the radical (or Laguerre) tessellation and the navigation map. The model is tested on different numerical packings. We find a weak local segregation for high packing fraction. We also find that the higher the size ratio of the particles, the more important the segregation. Received 19 February 2001 and Received in final form 27 June 2001     

Jamming and crystallization in athermal polymer packings

Dense packings of chains of hard spheres possess characteristic features that do not have a counterpart in corresponding packings of monomeric spheres especially near the maximally random jammed (MRJ) state. From the modelling perspective the additional requirement that spheres keep their connectivity while maximizing the occupied volume fraction imposes severe constraints on generation algorithms of dense chain configurations. The extremely sluggish dynamics imposed by the uncrossability of chains precludes the use of deterministic or stochastic dynamics to generate all but dilute polymer packings. As a viable alternative, especially tailored chain-connectivity-altering Monte Carlo (MC) algorithms have been developed that bypass this kinetic hindrance and have actually been able to produce packings of hard-sphere chains in a volume fraction range spanning from infinite dilution up to the MRJ state. Such very dense athermal polymer packings share a number of structural features with packings of monomeric hard spheres, but also display unique characteristics due to the constraints imposed by connectivity. We give an overview of the most relevant results of our recent modeling work on packings of freely-jointed chains of tangent hard spheres about the MRJ state, local structure, chain dimensions and their scaling with density, topological constraints in the form of entanglements and knots, contact network at jamming, and entropically driven crystallization.     

Comparison of two representations of a random cut of identical sphere packing

We compare two-dimensional froths obtained by radical tessellation of random planar cuts made through disordered assemblies of monosize spheres at different packing fractions C from C=0 to C=0.64 with two-dimensional stereological cuts obtained through the three-dimensional froths made with the same packing. We have built numerically the packings using different algorithms. The study of both topological and metric properties shows significant differences between the two representations. Received 26 May 1999 and Received in final form 13 November 1999     

Using level sets for creating virtual random packs of non-spherical convex shapes

Random packs of spheres have been used to model heterogeneous and porous material morphologies during simulations of physical processes such as burning of coal char, convective burning in porous explosives, and regression of solid rocket propellant. Sphere packs have also been used to predict thermo-mechanical properties, permeability, packing density, and dissolution characteristics of various materials. In this work, we have extended the Lubachevsky–Stillinger (LS) sphere packing algorithm to create polydisperse packs of non-spherical shapes for modeling heterogeneity in complex energetic materials such as HMX and pressed gun propellants. In the method, we represent the various particle shapes using level sets. The LS framework requires estimates of inter-particle collision times, and we predict these times by numerically solving a minimization problem. We have obtained results for dense random packs of various convex shapes such as cylinders, spherocylinders, and polyhedra, and we show results with these various particles packed together in a single pack to high packing fraction.     

Onset of mechanical stability in random packings of frictional spheres

Using sedimentation to obtain precisely controlled packings of noncohesive spheres, we find that the volume fraction phiRLP of the loosest mechanically stable packing is in an operational sense well defined by a limit process. This random loose packing volume fraction decreases with decreasing pressure p and increasing interparticle friction coefficient mu. Using x-ray tomography to correct for a container boundary effect that depends on particle size, we find for rough particles in the limit p-->0 a new lower bound, phiRLP=0.550+/-0.001.     

General magnetostatic shape-shape interaction forces and torques

Expressions for the magnetostatic interaction force and torque between two magnetic objects of arbitrary shape are derived within the shape amplitude formalism. A generalized force is derived as the gradient of the magnetometric tensor field, which is the convolution of the cross-correlation of the object shapes with the dipolar tensor field. Expressions for the mechanical and magnetic torques are also derived in terms of the magnetometric tensor field. Expressions suitable for numerical evaluation are given as finite Fourier summations. Example computations are given for the interactions between pairs of uniformly magnetized spheres (for which analytical results are compared to numerical results), cubes, octahedra, tetrahedra, and cuboctahedra. The accuracy of the derived numerical relations for energy, force, and torques is of the order of 0.1% for object spacings smaller than the object dimensions.     

Simulation of random packing of spherical particles with different size distributions

A numerical model for a loose packing process of spherical particles is presented. The simulation model starts with randomly choosing a sphere according to a pregenerated continuous particle-size distribution, and then dropping the sphere into a dimension-specified box, and obtaining its final position by using dropping and rolling rules which are derived from a similar physical process of spheres dropping in the gravitational field to minimize its gravity potential. Effects of three different particle-size distributions on the packing structure were investigated. Analysis on the physical background of the powder-based manufacturing process is additionally applied to produce optimal packing parameters of bimodal and Gaussian distributions to improve the quality of the fabricated parts. The results showed that higher packing density can be obtained using bimodal size distribution with a particle-size ratio from 1.5 to 2.0 and the mixture composition around n ₂:n ₁=6:4. For particle size with a Gaussian distribution, the particle radii should be limited in a narrow range around 0.67 to 1.5.