基于扩展多面体组合单元的非规则颗粒材料离散元方法北大核心CSCD

非规则颗粒材料广泛地存在于自然界和工业生产中,其复杂的几何形态对力学性质有显著的影响.为构建更接近真实颗粒形态的理论模型,以扩展多面体为基本单元,发展了扩展多面体组合单元.为验证扩展多面体组合单元的可靠性,分别对凸形三棱柱单元、凹形正倒锥体单元在平底漏斗中的卸料过程进行了离散元模拟,并与试验结果进行比较分析,得到其具有较好的一致性.在此基础上,对不同形态的组合单元进行堆积和卸料离散元模拟,研究了颗粒形状对堆积分数、卸料流量和休止角的影响.结果表明,颗粒形状越复杂,颗粒之间的互锁效应越显著,颗粒系统更加稳定.扩展多面体组合单元的有效应用,为离散元数值模拟描述任意形态颗粒材料提供了一种新的构建方法.     

三维稳态对流扩散问题的无网格求解算法研究

无网格法是一种不需要生成网格就可模拟复杂形状流场计算的流体力学问题求解算法.为了提高基于Galerkin弱积分形式的无网格方法求解三维稳态对流扩散问题的计算效率,提出了在空间离散上采用基于凸多面体节点影响域的无网格形函数,并通过选取适当节点影响半径因子避免节点搜索问题,同时减少系统刚度矩阵带宽.计算中当节点影响因子为1.01时,无网格方法的形函数近似具有插值特性且本质边界条件的施加与有限元一样简单.三维立方体区域的稳态对流扩散数值算例表明:在保证计算精度的同时,采用凸多面体节点影响域的无网格方法比传统无网格方法最高可节省计算时间42%.因此从计算效率和精度考虑,在运用无网格方法求解三维问题时建议采用凸多面体节点影响域的无网格方法.     

高体积百分比颗粒增强聚合物材料的有效粘弹性性质

聚合物材料通常表现为粘弹性性质．为了改进聚合物材料的力学性能,通常将某种无机材料以颗粒或纤维的形式填充到聚合物中,从而得到增强、增韧的聚合物基复合材料．提出了一个新的细观力学模型,用于预测颗粒增强聚合物复合材料的有效粘弹性性质,尤其针对高体积百分比的颗粒夹杂复合材料,该方法基于Laplace变换和双夹杂相互作用的弹性模型．计算了玻璃微珠/ED-6复合材料的有效松弛模量以及恒应变率下的应力应变关系．计算结果表明在高体积百分比下该文方法比基于Mori Tanaka方法预测的粘弹性效应明显减弱．     

Prediction of Concrete Meso-Model Stress-Strain Curves Based on GoogLeNet北大核心CSCD

非均质复合材料的宏观力学性能往往取决于细观组分的分布方式和力学性能，但是建立明确的关系表达式极其困难。为了应对这一挑战，以混凝土为研究对象，提出了一种基于深度学习的策略，能够高效、准确地通过细观模型图像信息获取应力-应变曲线。首先，使用基于卷积神经网络（convolutional neural network，CNN）的GoogLeNet模型进行图像信息识别和提取，并针对应力-应变曲线的复杂性特点，进行了数据预处理操作，并且设计了相应的多任务损失函数。数据集中的细观模型图像采用基于Monte-Carlo的随机骨料模型生成，并且使用数值模拟试验获取对应细观模型的单轴压缩应力-应变曲线。最后，通过对神经网络的训练和测试评估了所提出方法的可行性。结果表明，GoogLeNet模型训练效率和预测精度均优于AlexNet和ResNet模型，具有良好的泛化能力和鲁棒性。     

颗粒随机分布复合材料热传导问题均匀化方法的理论分析

针对区域内颗粒随机分布复合材料的热传导问题给出了一种均匀化理论计算温度场.首先根据复合材料的特性以及通过用多尺度方法预测复合材料热传导参数的要求定义了一些基本的概率空间,然后结合材料的物理特性做合理的假设得到了在整个随机复合材料区域上的期望温度场与均匀化温度场之间的一种理论估计,从而说明了此均匀化温度场可以作为预测此类随机颗粒分布复合材料期望温度场的理论基础.     

多项式族的根分布不变性

本文研究多项式族的根分布不变性问题.我们首先提出了多项式族根分布的广义剔零原理,给出了参数空间中鲁棒稳定性的复边界定理和复棱边定理,并基于广义剔零原理得到了参数空间和系数空间中关于根分布的相应结论.另外,对于系数空间中鲁棒稳定性中实棱边定理,我们证明了它对稳定区域的要求还可放宽.对于一些更具几何特征的凸多面体和特定的稳定区域,棱边定理还可进一步改进,使所需检验的棱边数目与凸多面体的棱边数目无关.最后,我们给出了检验棱边根分布的Nyquist型图示方法.     

任意凸多面体上布点均匀性的度量

均匀性度量是构作均匀设计的基础,本文从距离概念出发,通过对称的方法,得到一种新的距离函数-势函数,并将势函数作为衡量任意凸多面体上布点均匀性好坏的准则.数值例子和多变量Kendall 协和系数检验表明,当试验区域限制在单位立方体上时,势函数与目前常用的两种偏差-中心化L_2-偏差和可卷L_2.偏差在度量布点均匀性方面结论一致.     

一种颗粒随机分布复合材料弹性位移场均匀化方法的理论分析

针对计算随机颗粒分布复合材料弹性位移/力学场时,采用样本求力学性能期望值需要花费大量时间和内存的问题,给出了一种计算颗粒随机分布复合材料弹性位移场的均匀化方法,并且获得了均匀化位移场与期望位移场之间的一种理论误差.首先由复合材料的特性定义了均匀化理论的随机场和概率空间,然后结合单胞内颗粒随机分布复合材料的特性做了一些合理假设得到了在整个颗粒随机分布复合材料组成区域上的期望位移场与均匀化位移场之间的一种理论估计,最后对此法所具有的优点、适应范围,缺点、以及需要改进的地方做了进一步讨论.     

细观等效理论预测再生混凝土宏观力学参数北大核心CSCD

预测分析再生混凝土各组分对再生混凝土宏观力学参数的影响是开展再生混凝土基本力学性能的一种方式.为了分析再生混凝土各组分对再生混凝土宏观力学参数的影响,根据再生混凝土的细观结构组成,建立了细观等效模型,利用扭转变形、细观夹杂理论、弹性等效思想和M-T模型方法,推导了由原生骨料、老界面层、老水泥砂浆、新界面层和新水泥砂浆等组成的再生混凝土的宏观力学参数预测模型.预测结果表明,随着再生骨料的取代率增加,水泥砂浆的含量不断增加,再生混凝土孔隙率也随之增大,导致再生混凝土的Poisson比随之增大,弹性模量、剪切模量和体积模量不断降低.模型的预测结果较好地反映了再生混凝土宏观力学参数随再生骨料取代率的增加不断变化的这一趋势,也为再生混凝土宏观力学参数的预测提供了一条简单实用的新方法,有利于再生混凝土基本力学性能的研究分析.     

基于三维CFD-DEM的多孔介质流场数值模拟

将多孔介质局部细观流动与基于Darcy定律的宏观物理模型相结合，应用三维CFD-DEM对多孔介质流场进行局部细观数值模拟，得到多孔介质的惯性阻力系数和粘性阻力系数.并将其作为参数提供给基于Darcy定律的CFD多孔介质模型，从而可用于更大规模的多孔介质流场计算.应用Voronoi多面体作为网格单元，解决了CFD DEM中网格孔隙率精确计算的困难.文中发展的多尺度结合应用的研究方法，在计算精度和计算效率的矛盾中找到了较好的平衡，对于工程应用而言，有节约实验成本、提高计算结果可靠性的功效.     

On Some Properties of Generalized Proximal Point Methods for Variational Inequalities

We discuss here generalized proximal point methods applied to variational inequality problems. These methods differ from the classical point method in that a so-called Bregman distance substitutes for the Euclidean distance and forces the sequence generated by the algorithm to remain in the interior of the feasible region, assumed to be nonempty. We consider here the case in which this region is a polyhedron (which includes linear and nonlinear programming, monotone linear complementarity problems, and also certain nonlinear complementarity problems), and present two alternatives to deal with linear equality constraints. We prove that the sequences generated by any of these alternatives, which in general are different, converge to the same point, namely the solution of the problem which is closest, in the sense of the Bregman distance, to the initial iterate, for a certain class of operators. This class consists essentially of point-to-point and differentiable operators such that their Jacobian matrices are positive semidefinite (not necessarily symmetric) and their kernels are constant in the feasible region and invariant through symmetrization. For these operators, the solution set of the problem is also a polyhedron. Thus, we extend a previous similar result which covered only linear operators with symmetric and positive-semidefinite matrices.     

Finding a best approximation pair of points for two polyhedra

Given two disjoint convex polyhedra, we look for a best approximation pair relative to them, i.e., a pair of points, one in each polyhedron, attaining the minimum distance between the sets. Cheney and Goldstein showed that alternating projections onto the two sets, starting from an arbitrary point, generate a sequence whose two interlaced subsequences converge to a best approximation pair. We propose a process based on projections onto the half-spaces defining the two polyhedra, which are more negotiable than projections on the polyhedra themselves. A central component in the proposed process is the Halpern–Lions–Wittmann–Bauschke algorithm for approaching the projection of a given point onto a convex set.     

Minimum L1-Distance Projection onto the Boundary of a Convex Set: Simple Characterization

We show that the minimum distance projection in the L ₁-norm from an interior point onto the boundary of a convex set is achieved by a single, unidimensional projection. Application of this characterization when the convex set is a polyhedron leads to either an elementary minmax problem or a set of easily solved linear programs, depending upon whether the polyhedron is given as the intersection of a set of half spaces or as the convex hull of a set of extreme points. The outcome is an easier and more straightforward derivation of the special case results given in a recent paper by Briec (Ref. 1).     

A maxmin location problem with nonconvex feasible region

The problem dealt with consists of locating a point in a given convex polyhedron which maximizes the minimum Euclidean distance from a given set of convex polyhedra representing protected areas around population points. The paper describes a finite dominating solution set for the optimal solution and develops a geometrical procedure for obtaining the optimal solution comparing a finite number of candidates.     

A geometrical interpretation of the Hungarian method

In this paper a geometrical interpretation of the Hungarian method will be given. This special algorithm to solve the dual transportation problem is not restricted to the edges of the convex polyhedron of feasible solutions. Each covering-step can be considered as a determination of a direction of steepest descent, each reduction-step as movement along that direction to a boundary point of the polyhedron. The dimension of the face that will be crossed depends on the covering that is chosen.     

A simple algorithm for building the 3-D convex hull

A new algorithm is given for finding the convex hull of a finite set of distinct points in three-dimensional space. The algorithm finds the faces of the hull one by one, thus gradually building the polyhedron that constitutes the hull. The algorithm is described as developed through stepwise refinement.     

Weber‘s Problem with Attraction and Repulsion under Polyhedral Gauges

Given a finite set of points in the plane anda forbidden region , we want to find a point , such thatthe weighted sum to all given points is minimized.This location problem is a variant of the well-known Weber Problem, where wemeasure the distance by polyhedral gauges and alloweach of the weights to be positive ornegative. The unit ballof a polyhedral gauge may be any convex polyhedron containingthe origin. This large class of distance functions allows verygeneral (practical) settings – such as asymmetry – to be modeled. Each given point isallowed to have its own gaugeand the forbidden region enables us to include negative information in the model. Additionallythe use of negative and positive weights allows to include thelevel of attraction or dislikeness of a new facility.Polynomial algorithms and structural properties for this globaloptimization problem (d.c. objective function and anon-convex feasible set) based on combinatorial and geometrical methodsare presented.     

On the Quasiconcave Bilevel Programming Problem

Bilevel programming involves two optimization problems where the constraint region of the first-level problem is implicitly determined by another optimization problem. In this paper, we consider the case in which both objective functions are quasiconcave and the constraint region common to both levels is a polyhedron. First, it is proved that this problem is equivalent to minimizing a quasiconcave function over a feasible region comprised of connected faces of the polyhedron. Consequently, there is an extreme point of the polyhedron that solves the problem. Finally, it is shown that this model includes the most important case where the objective functions are ratios of concave and convex functions     

A finite concave minimization algorithm using branch and bound and neighbor generation

In this article we present a new finite algorithm for globally minimizing a concave function over a compact polyhedron. The algorithm combines a branch and bound search with a new process called neighbor generation. It is guaranteed to find an exact, extreme point optimal solution, does not require the objective function to be separable or even analytically defined, requires no nonlinear computations, and requires no determinations of convex envelopes or underestimating functions. Linear programs are solved in the branch and bound search which do not grow in size and differ from one another in only one column of data. Some preliminary computational experience is also presented.