硬岩介质中洞室渗水的随机数值模拟

以岩石的绝对渗透率符合对数正态分布,及其协方差函数为离散指数型的假设为基础,建立了硬岩介质中圆形洞室渗水的二维随机模型。采用Karhunen-Loeve展开、随机摄动法对随机偏微分方程进行求解,并用蒙特卡罗法对计算结果进行了验证,进一步说明该方法的正确性及高效性。计算结果说明:(1)岩石非均质性对洞室壁左上方与右上方两点的水饱和度标准差影响最大;(2)渗透率均值与水饱和度均值及标准差反相关;渗透率对数标准差与水饱和度标准差正相关,与水饱和度均值不相关。

自然风速下低雷诺数风力机翼型气动特性随机数值分析

为量化随机自然风速条件下风力机翼型气动特性不确定程度,以S809风力机翼型为研究对象,基于非嵌入式概率配置点法和Transition SST转捩方程,建立了低雷诺数风力机翼型气动特性随机数值分析模型,获得了自然风速条件下风力机翼型气动力确定性和不确定性成分比例,并揭示了风速大小和方向随机耦合作用对翼型流场结构、压力系数和摩阻分布及湍动能的影响及不确定传播机制.结果表明,随机风速风向对翼型升阻气动因子不确定度影响显著,在计算攻角范围内S809翼型升阻比3σ置信区间相对不确定度最大为±35.13%;随机风速风向耦合作用下翼型升阻比不确定度分别是单随机因素下的4.76倍和1.08倍;翼型对来流不确定性敏感区域为前缘,可以考虑在翼型前缘部分进行气动稳健性优化设计.

一维对流扩散方程的随机数值解

本文首先采用对流迎风格式提出一维对流扩散方程的随机数值解法及随机游动模型,在此基础上给出了一维对流扩散方程的拉格朗日质点跟踪解法。

随机数发生器种子值对岩石试样弹塑性破裂过程的影响研究

阐述了岩土类材料的非匀质性特性,以及对岩土类材料弹塑性破裂过程进行数值模拟的分析程序REPFPA,通过8个试样的数值模拟"试验",深入地研究了随机数发生器种子值对岩石试样弹塑性破裂过程的影响.分析结果表明:只要岩石材料力学性质的均质度和其它参数保持不变,随机数发生器种子值对岩石试样弹塑性破裂过程与结果的影响很小.

随机锈蚀H型钢柱偏压承载力分析

为了揭示随机锈蚀对H型钢柱在偏压作用下极限承载能力的影响,采用随机有限元方法对随机点蚀钢柱的抗弯承载力的变化规律进行了研究,考虑了轴压比、几何参数以及锈蚀深度对H型钢柱抗弯承载力折减系数的影响;得到了不同几何尺寸下H型钢柱的适用性,揭示了折减系数随锈蚀深度的变化规律,提出了用于预测抗弯承载力折减系数的理论计算公式。结果表明,所提出的理论公式可以准确预测随机点蚀H型钢柱的抗弯承载力,可为评估既有H型钢柱的极限承载力提供理论基础。

多孔材料等效导热系数与分形维数关系的数值模拟研究

采用有限元方法模拟了多孔材料的导热系数与孔隙率和分形维数之间的非线性关系。有限元模型中的固体骨架和孔隙根据孔隙率的大小随机生成,模型中的材料参数和单元属性用ANSYS中的APDL参数化语言赋值。根据有限元随机模拟断面的热流密度分布和稳态热传导傅立叶定律,计算在不同孔隙率条件下的等效导热系数。研究表明,多孔材料模型等效导热系数随着孔隙的增加而线性减小。在孔隙率为常数的条件下,模型等效导热系数随着模型比例因子的增加而呈指数增加。等效导热系数随着孔隙分形维数的增加而减小,随着固体颗粒分形维数的增加而增加。

海岸河口水动力数值模拟的研究方向

海岸河口水动力数值模拟的发展新动向 :(1)发展高、新、精、细模型 ;(2 )开发多因素过程模拟 ;(3)建立与物模结合的复合模型 ;(4)实现智能型可视化模拟系统 ;(5 )

基于点蚀演化的Q235钢材强度退化行为研究

【目的】为了评估腐蚀后钢材强度随点蚀演化的退化行为,基于不同腐蚀时间的钢基体表面蚀坑统计结果,利用ABAQUS有限元分析软件与Python程序实现了随机点蚀的原位演化,在此基础上提出了随机点蚀演化的力学性能评估方法。【方法】在保证数值模型与试验质量损失率一致的前提下,分析并验证了腐蚀钢材强度数值解的准确性和适用性,建立了点蚀影响下钢材的强度退化模型。此外,通过3组153个数值模型系统分析了蚀坑深度及质量损失率共同影响下Q235腐蚀钢材的屈服强度与极限强度的退化规律,提出了具有通用性的腐蚀后钢材屈服强度与极限强度随质量损失率与腐蚀深度的演化公式。【结果】结果表明,当蚀坑深度已知时,钢材剩余强度随质量损失率的增加呈指数型下降。点蚀影响下钢材的屈服强度和极限强度同时由质量损失率与蚀坑深度决定。

基于随机配点法的饱和-非饱和水流运动模拟

为解决土壤水分运动的不确定性问题,研究了随机配点方法,并应用此方法建立了饱和-非饱和水分运动的随机模型,考虑了土壤分层及参数分布函数的差异,视渗透系数等参数为随机输入,探讨了土壤中水分运动的随机数值模拟,分析了随机配点法的计算性能和选点原则。研究结果表明:基于随机配点法的饱和-非饱和水分运动模拟相比于传统的Monte Carlo模拟极大地节省了计算成本,提高了计算效率;随机配点法可以直接在经典非饱和模型基础上搭建随机模型,这种方法能够快速地构建出水头的概率分布函数;不同的非饱和输入参数对水头的不确定性产生不同影响;随机参数的分布类型会影响到水分运动不确定性的预测。

一种关于浮点乘加的测试方法

目前浮点乘加部件的算法研究和实现已成为高性能微处理器研究的热点之一,对其进行测试也显得尤为重要和必要。论文介绍了一种浮点乘加的测试方法,并从特殊值和随机数两个角度进行测试。

Stochastic resonance based on correlation coefficient in parallel array of threshold devices

The phenomenon of stochastic resonance （SR） based on the correlation coefficient in a parallel array of threshold devices is discussed. For four representative noises： the Gaussian noise, the uniform noise, the Laplace noise and the Cauchy noise, when the signal is subthreshold, noise can improve the correlation coefficient and SR exists. The efficacy of SR can be significantly enhanced and the maximum of the correlation coefficient can dramatically approach to one as the number of the threshold devices in the parallel array increases. Two theorems are presented to prove that SR has some robustness to noises in the parallel array. These results further extend the applicability of SR in signal processing.

STOCHASTIC BOUNDARY ELEMENT METHODS FOR 3D PROBLEMS WITH BODY FORCES AND ITS APPLICATION IN RELIABILITY OF TURBINE DISKS

The stochastic boundary element method(SBEM)is developed in this paper for 3D problems with body forces and reliability analysis of engineering structures.The integral equations of SBEM are established by the approach of partial derivation with respect to stochastic variables,considering the yield limit,rotation speeds and material density to be the fundamental stochastic variables.Through analyzing a numerical example and a turbo-disk of an aeroengine,the results show that the method developed is successful.

蒙特卡洛法的应用

大家知道,BASIC语言中由随机函数RND产生的随机数值在0到1之间是均匀分布的,或者说是矩形地均匀地分布在0到1的区间上。所谓蒙特卡洛法就是借助计算机产生随机数来计算数值的方法。它是由美国专家Monte Carlo发明的。本文着重阐述蒙特卡洛法的应用。

Stability and reliability of pit slopes in surface mining combined with underground mining in Tonglushan mine

Slope stability is of critical importance in the process of surface-underground mining combination. The influence of underground mining on pit slope stability was mainly discussed, and the self-stabilization of underground stopes was also studied. The random finite element method was used to analyze the probability of the rock mass stability degree of both pit slopes and underground stopes. Meanwhile, 3D elasto-plastic finite element method was used to research into the stress, strain and rock mass failure resulting from mining. The results of numerical simulation indicate that the mining of the underground test stope has certain influence on the stability of the pit slope, but the influence is not great. The safety factor of pit slope is decreased by 0.06, and the failure probability of the pit slope is increased by 1.84%. In addition, the strata yielding zone exists around the underground test stope. The results basically conform to the information coming from the field monitoring.

Generation of 3D random meso-structure of soil-rock mixture and its meso-structural mechanics based on numerical tests

The mesoscopic failure mechanism and the macro-mechanical characteristics of soil-rock mixture(S-RM) under external load are largely controlled by S-RM's meso-structural features. The objective of this work is to improve the three-dimensional technology for the generation of the random meso-structural models of S-RM, for randomly generating irregular rock blocks in S-RM with different shapes, sizes, and distributions according to the characteristics of the rock blocks' size distribution. Based on the new improved technology, a software system named as R-SRM3 D for generation and visualization of S-RM is developed. Using R-SRM3 D, a three-dimensional meso-structural model of S-RM is generated and used to study the meso-mechanical behavior through a series of true-triaxial numerical tests. From the numerical tests, the following conclusions are obtained. The meso-stress field of S-RM is influenced by the distribution of the internal rock blocks, and the macro-mechanical characteristics of S-RM are anisotropic in 3D; the intermediate principal stress and the soil-rock interface properties have significant influence on the macro strength of S-RM.

Dynamics and Control of Infectious Diseases in Stochastic Metapopulation Models

The research on spatial epidemic models is a topic of considerable recent interest. In another hand, the advances in computer technology have stimulated the development of stochastic models. Metapopulation models are spatial designs that involve movements of individuals between distinct subpopulations. The purpose of the present work has been to develop stochastic models in order to study the transmission dynamics and control of infectious diseases in metapopulations. The authors studied Susceptible-Infected-Susceptible （SIS） and Susceptible-lnfected-Recovered （SIR） epidemic schemes, using the Gillespie algorithm, Computational numerical simulations were carried in order to explore the models. The results obtained show how the dynamics of transmission and the application of control measures within each subpopulation may affect all subpopulations of the system. They also show how the distribution of control measures among subpopulations affects the efficacy of these strategies. The dynamics of the stochastic models developed in the current study follow the trends observed in the classic deterministic designs. Also, the present models exhibit fluctuating behavior. This work highlights the importance of the spatial distribution of the population in spread and control of infectious diseases. In addition, it shows how chance could play an important role in these scenarios.

Numerical Simulation of 2D and 3D Sloshing Waves in a Regularly and Randomly Excited Container

In this paper,various aspects of the 2D and 3D nonlinear liquid sloshing problems in vertically excited containers have been studied numerically along with the help of a modified-transformation.Based on this new numerical algorithm,a numerical study on a regularly and randomly excited container in vertical direction was conducted utilizing four different cases： The first case was performed utilizing a 2D container with regular excitations.The next case examined a regularly excited 3D container with two different initial conditions for the liquid free surface,and finally,3D container with random excitation in the vertical direction.A grid independence study was performed along with a series of validation tests.An iteration error estimation method was used to stop the iterative solver（used for solving the discretized governing equations in the computational domain） upon reaching steady state of results at each time step.In the present case,this method was found to produce quite accurate results and to be more time efficient as compared to other conventional stopping procedures for iterative solvers.The results were validated with benchmark results.The wave elevation time history,phase plane diagram and surface plots represent the wave nonlinearity during its motion.

More general results on mixed extreme value distributions

The sequences {Zi,n, 1≤i≤n}, n≥1 are multi-nomial distribution among i.i.d, random variables {X1,i, i≥1}, {X2,i, i≥1 } {Xm,i, i≥1 }. The extreme value distribution Gz（x） of this particular triangular array of i.i,d, random variables Z1,n, Z2 n,...,Zn,n is discussed. A new type of not max-stable extreme value distributions which are Fréchet mixture, Gumbel mixture and Weibull mixture has been found if Fj,…… Fm belong to the same MDA. Whether mixtures of different types of extreme value distributions exist or not and the more general case are discussed in this paper. We found that Gz（x） does not exist as mixture forms of the different types of extreme value distributions after we investigated all cases.

Stochastic Lattice gas Cellular Automata Model for Epidemics

The aim of this study was to develop and explore a stochastic lattice gas cellular automata （LGCA） model for epidemics. A computer program was development in order to implement the model. An irregular grid of cells was used. A susceptible-infected-recovered （SIR） scheme was represented. Stochasticity was generated by Monte Carlo method. Dynamics of model was explored by numerical simulations. Model achieves to represent the typical SIR prevalence curve. Performed simulations also show how infection, mobility and distribution of infected individuals may influence the dynamics of propagation. This simple theoretical model might be a basis for developing more realistic designs.

Random seismic noise attenuation by learning-type overcomplete dictionary based on K-singular value decomposition algorithm

The transformation of basic functions is one of the most commonly used techniques for seismic denoising,which employs sparse representation of seismic data in the transform domain. The choice of transform base functions has an influence on denoising results. We propose a learning-type overcomplete dictionary based on the K-singular value decomposition( K-SVD) algorithm. To construct the dictionary and use it for random seismic noise attenuation,we replace fixed transform base functions with an overcomplete redundancy function library. Owing to the adaptability to data characteristics,the learning-type dictionary describes essential data characteristics much better than conventional denoising methods. The sparsest representation of signals is obtained by the learning and training of seismic data. By comparing the same seismic data obtained using the learning-type overcomplete dictionary based on K-SVD and the data obtained using other denoising methods,we find that the learning-type overcomplete dictionary based on the K-SVD algorithm represents the seismic data more sparsely,effectively suppressing the random noise and improving the signal-to-noise ratio.