微纳米尺度下材料性能多尺度模拟方法进展

微纳米材料的力学行为正日益引起研究者的关注.微纳米材料的性能取决于从微观、细观到宏观多个空间、时间尺度上不同物理过程非线性耦合演化的结果,发展相应的多尺度数值模拟方法已成为该领域研究工作的一个热点.本文对微纳米材料模拟中比较典型的几种协同多空间尺度和协同多时间尺度方法进行了介绍,着重介绍这些方法的的基本思想、应用情况, 以及各自的优缺点,并对微纳米材料多尺度方法的发展趋势进行总结和评述.      

基于离散缝洞网络模型的缝洞型油藏混合多尺度有限元数值模拟

针对缝洞型油藏具有多尺度特征,基于离散缝洞网络模型,建立了Darcy/Stokes-Brinkman多尺度耦合数学模型,采用多尺度混合有限元方法,对缝洞型油藏的流体流动问题进行了研究。阐述了多尺度混合有限元方法的基本原理,推导得到了Darcy/Stokes-Brinkman多尺度模型的多尺度混合有限元计算格式。数值计算结果表明,在大尺度模型上进行计算能够捕捉到小尺度上的流动特征;相对于传统有限元,多尺度混合有限元能够捕捉小尺度上的非均质特征而具有更高的计算精度,在保证计算精度的同时能够减少计算量。     

可压缩流体流动多尺度混合有限元数值方法研究

可压缩流体是天然油藏中广泛存在的一种流体,研究其在多孔介质中的渗流规律对于油藏开发具有重要意义。本文采用多尺度混合有限元方法,对可压缩流体渗流问题进行了研究。考虑流体的可压缩性以及介质形变,推导得到了可压缩流体渗流问题的多尺度计算格式。数值计算结果表明,多尺度混合有限元适于求解非均质性和可压缩流问题,具有节省计算量、计算精度高等优势,对于实际大规模油藏模拟具有重要意义。     

基于多尺度网格细胞模型的无人机类脑矢量导航方法

动物具有优秀的矢量导航能力,为发展未知环境下无人机新型自主智能面向目标导航方法提供了较好的生物模型。首先阐述了动物大脑矢量导航机理,然后重点研究了多尺度网格细胞模块编码与解码机制,提出一种大尺度空间下基于多尺度网格细胞模型的无人机类脑矢量导航方法。通过在多个吸引子神经网络中引入指数递增型速度增益因子,提出了多尺度网格细胞路径积分方法(编码);基于余数系统框架提出了大尺度空间网格细胞矢量导航解算方法(解码)。仿真实验结果表明:所提方法能够适应在最大范围38km的大尺度空间中对速度、方位信息进行准确多尺度路径积分(编码),并准确解算当前距目标矢量(解码);验证了所提方法能够进行大尺度空间矢量导航,对进一步发展大尺度空间下无人机三维类脑矢量导航方法具有较好的参考意义。     

关于采用粗粒化提高颗粒材料多尺度模拟守恒特性的研究

连续体-颗粒耦合方法常用来描述连续-非连续颗粒行为或解决颗粒材料与其他可变形构件间相互作用问题。粗粒化coarse-graining (CG)是基于统计力学的均匀化方法,由离散的颗粒运动定义连续的宏观物理场。本文利用粗粒化(CG)推导有限元-离散元(FEM-DEM)表面和体积耦合的一般性表达式。对于表面耦合,CG可以将耦合力分布到颗粒-单元接触点以外的位置,如相邻的积分点;对于体积耦合,CG可以将颗粒尺度的运动均匀化到耦合单元上。由粗粒化推导出的耦合项仅包含一个参数,即粗粒化宽度,为均匀化后的宏观场定义了一个可调整的空间尺度。当粗粒化宽度为零时,表面和体积耦合表达式简化为常规局部耦合。本文通过弹性立方体冲击颗粒床和离散-连续介质间波传播两个数值算例,展示使用粗粒化方法提高耦合系统能量守恒的优势,并结合其他耦合参数(如体积耦合深度)讨论了粗粒化参数对数值稳定性和计算效率的影响。     

计算材料科学中桥域多尺度方法的若干进展

材料科学中存在固有的多尺度特性,桥域多尺度方法是在宏观尺度(如连续介质力学)中引入不同的细微观尺度的计算区域,乃至纳米尺度的分子动力学、量子力学计算区域,将不同尺度的研究方法通过一定的数学模型耦合在一起。该方法既能节约计算成本,又能保证所研究问题的物理特性。本文对多尺度方法的基本概念、跨尺度桥域多尺度方法的发展、基本原理、耦合方法和离散方程进行了讨论,给出了几个应用算例,并在最后进行了总结,展望了今后的可能发展方向。     

水下发射水动力的多尺度预测网络研究

空泡的演化和水动力特征的预测在航行体发射的设计中有非常重要的意义.人工智能技术已经成为了参数预测的重要手段.为了能够快速预测航行体水下发射过程的尾部压力的复杂变化,提出了一种多尺度深度学习网络.该网络模型以一维卷积网络(1DCNN)为基础,构建了一种编码--解码型网络结构,通过不同的采样频率将原始数据分解为光滑部分和脉...     

离散颗粒集合体-Cosserat连续体模型的连接尺度方法

基于针对分子动力学-Cauchy连续体模型提出的连接尺度方法(BSM)[1,2],发展了耦合细尺度上基于离散颗粒集合体模型的离散单元法(DEM)和粗尺度上基于Cosserat连续体模型的有限元法(FEM)的BSM。仅在有限局部区域内采用DEM以从细观层次模拟非连续破坏现象,而在全域则采用花费计算时间和存储空间较少的FEM。通过连接尺度位移(包括平移和转动)分解,和基于作用于Cosserat连续体有限元节点和颗粒集合体颗粒形心的离散系统虚功原理,得到了具有解耦特征的粗细尺度耦合系统运动方程。讨论和提出了在准静态载荷条件下粗细尺度域的界面条件,以及动态载荷条件下可以有效消除粗细尺度域界面上虚假反射波的非反射界面条件(NRBC)。本文二维数值算例结果说明了所提出的颗粒材料BSM的可应用性和优越性,及所实施界面条件对模拟颗粒材料动力学响应的有效性。     

基于扩展多尺度有限元法的含液闭孔材料拓扑优化

基于扩展多尺度有限元方法,提出了含液闭孔结构多尺度拓扑优化方法.该多尺度优化方法旨在研究含液闭孔胞元布局对整体含液闭孔结构力学性能的影响.首先针对含液闭孔结构的整体结构柔顺性问题,采用类似SIMP模型对结构的宏观粗网格等效刚度阵进行插值,建立含液闭孔结构柔顺性的拓扑优化列式;其次,针对含液闭孔材料能够利用胞体内部液体腔体积增量产生变形的特性,提出含液闭孔材料柔性机构的概念,并以结构指定位置方向输出位移为目标,建立液体体积膨胀作用下的含液闭孔柔性机构多尺度拓扑优化数学模型.论文基于自主软件平台SiPESC完成了程序研发,并通过数值算例验证了所提出的拓扑优化方法的有效性.     

多尺度材料模拟的自适应有限元方法研究

研究了材料模拟中一类新型耦合多尺度的自适应有限元方法. 采用微观分子动力学耦合宏观有限元的桥尺度方法来模拟材料破坏的前期行为,其中宏观有限元计算推广到了一般非结构三角形网格. 材料破坏形成后,停止微观尺度的计算,它的进一步发展和演化通过一个宏观模型来描述,采用自适应有限元方法来求解这一宏观模型. 其中,后验误差估计的基础是变分多尺度理论,即自适应网格加密是基于粗尺度上残差分布和细尺度上单元Green's函数. 计算中采用了破坏准则来模拟材料的断裂. 数值实验表明了方法的有效性.      

A finite element variational multiscale method for incompressible flows based on the construction of the projection basis functions

In this article, we present a finite element variational multiscale (VMS) method for incompressible flows based on the construction of projection basis functions and compare it with common VMS method, which is defined by a low‐order finite element space L_h on the same grid as X_h for the velocity deformation tensor and a stabilization parameter α. The best algorithmic feature of our method is to construct the projection basis functions at the element level with minimal additional cost to replace the global projection operator. Finally, we give some numerical simulations of the nonlinear flow problems to show good stability and accuracy properties of the method. Copyright © 2011 John Wiley & Sons, Ltd.     

Estimation of structural element sizes in sand and compacted blocks of ground calcium carbonate using a void network model

An algorithm has been developed for the calculation of the size of the effective structural or skeletal elements which make up the solid phase of an unconsolidated or consolidated porous block. It is based on a previously presented algorithm, but it has now been validated on unconsolidated samples and tested on consolidated samples. It also includes a virtual reality representation of the structures. First, a network model named Pore-Cor is made to reproduce the percolation behaviour of the experimental sample, by matching its simulated percolation characteristics to an experimental mercury intrusion curve. The algorithm then grows skeletal elements between the cubic pores and cylindrical throats of the void network model until they touch up to four of the adjacent void features. The size distributions of the simulated solid elements are compared with each other and with experimentally determined particle size distributions, using a Mann–Whitney test. The algorithm was shown to simulate skeletal elements with the correct trends in size distribution for two different sand samples, provided the sand packed itself optimally under the applied mercury pressure. It was also applied to two samples of variously compressed calcium carbonate powder, having fine and coarse particle size distributions respectively. The simulation demonstrated that on compressing the powder at the minimum force, the skeletal elements differed from the constituent particle sizes, as expected. The average size of the skeletal elements increased as the compression force was increased on the calcium carbonate powders. The results suggest that the method could be useful as a tool for probing the effect of compaction on aggregation or sintering, and for studying other effects such as cementation in geological samples, where other more direct techniques cannot be applied.     

A stochastic approximation approach to improve the convergence behavior of hierarchical atomistic-to-continuum multiscale models

The aim of this work is to provide an improved information exchange in hierarchical atomistic-to-continuum settings by applying stochastic approximation methods. For this purpose a typical model belonging to this class is chosen and enhanced. On the macroscale of this particular two-scale model, the balance equations of continuum mechanics are solved using a nonlinear finite element formulation. The microscale, on which a canonical ensemble of statistical mechanics is simulated using molecular dynamics, replaces a classic material formulation. The constitutive behavior is computed on the microscale by computing time averages. However, these time averages are thermal noise-corrupted as the microscale may practically not be tracked for a sufficiently long period of time due to limited computational resources. This noise prevents the model from a classical convergence behavior and creates a setting that shows remarkable resemblance to iteration schemes known from stochastic approximation. This resemblance justifies the use of two averaging strategies known to improve the convergence behavior in stochastic approximation schemes under certain, fairly general, conditions. To demonstrate the effectiveness of the proposed strategies, three numerical examples are studied.     

Coupling the finite element method and molecular dynamics in the framework of the heterogeneous multiscale method for quasi-static isothermal problems

Multiscale models are designed to handle problems with different length scales and time scales in a suitable and efficient manner. Such problems include inelastic deformation or failure of materials. In particular, hierarchical multiscale methods are computationally powerful as no direct coupling between the scales is given. This paper proposes a hierarchical two-scale setting appropriate for isothermal quasi-static problems: a macroscale treated by continuum mechanics and the finite element method and a microscale modelled by a canonical ensemble of statistical mechanics solved with molecular dynamics. This model will be implemented into the framework of the heterogeneous multiscale method. The focus is laid on an efficient coupling of the macro- and micro-solvers. An iterative solution algorithm presents the macroscopic solver, which invokes for each iteration an atomistic computation. As the microscopic computation is considered to be very time consuming, two optimisation strategies are proposed. Firstly, the macroscopic solver is chosen to reduce the number of required iterations to a minimum. Secondly, the number of time steps used for the time average on the microscale will be increased with each iteration. As a result, the molecular dynamics cell will be allowed to reach its state of thermodynamic equilibrium only in the last macroscopic iteration step. In the preceding iteration steps, the molecular dynamics cell will reach a state close to equilibrium by using considerably fewer microscopic time steps. This adapted number of microsteps will result in an accelerated algorithm (aFE-MD-HMM) obtaining the same accuracy of results at significantly reduced computational cost. Numerical examples demonstrate the performance of the proposed scheme.     

装药不耦合系数对碳酸盐岩爆炸地震波能量的影响

针对碳酸盐岩中化学爆炸地震勘探激发地震波能量弱、频率高、信噪比低的现状,为对炮孔装药结构提出合理的改进措施,建立了耦合与不耦合装药孔壁爆炸载荷及透射波能量的计算模型,并借助MATLAB编程计算得到解析解.同时在灰岩场地进行了装药不耦合系数Kd对地震波能量影响的现场实验,应用基于功率谱的能量分析方法对实验数据进行了分析....     

不规则区域平面弹性问题的正则区域重心插值配点法

将不规则区域嵌入到规则的矩形区域,在矩形区域上将弹性平面问题的控制方程采用重心Lagrange插值离散,得到控制方程矩阵形式的离散表达式。在边界节点上利用重心插值离散边界条件,规则区域采用置换法施加边界条件,不规则区域采用附加法施加边界条件,得到求解平面弹性问题的过约束线性代数方程组,采用最小二乘法进行求解,得到整个规则区域上的位移数值解。利用重心插值计算得到不规则区域内任意节点的位移值,计算精度可到10^-14以上。数值算例验证了所建立方法的有效性和计算精度。     

Yeast protein-protein interaction network model based on biological experimental data

Duplication and divergence have been widely recognized as the two dominant evolutionary forces in shaping biological networks, e.g., gene regulatory networks and protein-protein interaction (PPI) networks. It has been shown that the network growth models constructed on the principle of duplication and divergence can recapture the topological properties of real PPI networks. However, such network models only consider the evolution processes. How to select the model parameters with the real biological experimental data has not been presented. Therefore, based on the real PPI network statistical data, a yeast PPI network model is constructed. The simulation results indicate that the topological characteristics of the constructed network model are well consistent with those of real PPI networks, especially on sparseness, scale-free, small-world, hierarchical modularity, and disassortativity.     

冲击地压时列建模的进化神经网络方法

考虑到冲击地压时序的特点,采用基于免疫进化规划的进化神经网络进行了冲击地压非线性系统的建模研究。并采用一个矿山实测得到的震级数列进行了进化神经网络方法的实用性验证,结果表明,进化神经网络不但模型拟合精度高,而且预测性能也较好。     

基于链式贝叶斯网络的结构可靠性分析

将贝叶斯网络与传统可靠性方法结合,建立结构系统的可靠性贝叶斯网络模型,通过改进的分支限界法确定结构主要失效模式,并将贝叶斯网络链式化来提升计算效率。根据可靠性方法计算条件概率表;使用概率网络估算法来考虑主要失效模式之间的相关性,计算系统可靠性;当有新信息出现时,利用贝叶斯网络推理,对结构系统可靠性进行评估。以一桁架结构为研究对象,计算结构系统的可靠性,并在新信息出现的情况下对系统可靠性进行了更新。