Generalized polynomial chaos expansion by reanalysis using static condensation based on substructuring

This paper presents a new computational method for forward uncertainty quantification(UQ)analyses on large-scale structural systems in the presence of arbitrary and dependent random inputs.The method consists of a generalized polynomial chaos expansion(GPCE)for statistical moment and reliability analyses associated with the stochastic output and a static reanalysis method to generate the input-output data set.In the reanalysis,we employ substructuring for a structure to isolate its local regions that vary due to random inputs.This allows for avoiding repeated computations of invariant substructures while generating the input-output data set.Combining substructuring with static condensation further improves the computational efficiency of the reanalysis without losing accuracy.Consequently,the GPCE with the static reanalysis method can achieve significant computational saving,thus mitigating the curse of dimensionality to some degree for UQ under high-dimensional inputs.The numerical results obtained from a simple structure indicate that the proposed method for UQ produces accurate solutions more efficiently than the GPCE using full finite element analyses(FEAs).We also demonstrate the efficiency and scalability of the proposed method by executing UQ for a large-scale wing-box structure under ten-dimensional(all-dependent)random inputs.

浅海声场对不确定环境参数的灵敏度分析方法

为分析不确定环境参数对浅海声场的影响,用非嵌入式随机多项式展开法获得声场与不确定环境参数之间函数关系式,建立声场对单个不确定参数的局部灵敏度分析方法;当多参数不确定时,提出依据某参数变化前后声场概率密度的变化,定性表征声场对该不确定参数的全局灵敏度分析方法,引入Sobol指数法定量计算声场对不确定环境参数的全局灵敏度。算例结果表明文中提出的分析方法可快速获得浅海声场对不确定参数的灵敏度,可用于优化不确定浅海环境参数模型。

多导体传输线串扰概率分布计算方法

针对实验设备中可视为多导体传输线结构的导线、微带线等存在的串扰不确定性问题,提出采用非干涉的广义混沌多项式展开法(gPCE)对串扰概率分布情况进行计算分析。结合多导体传输线理论建立多导体传输线串扰模型,分析实际情况下对传输线串扰产生影响的相关因素。将传输线的相关几何参数和位置参数选作为输入变量,采用(gPCE)计算得到传输线串扰的统计特征参数,基于(gPCE)建立的代理模型对传输线串扰的概率分布情况进行计算分析。通过与传统的蒙特卡洛法计算结果进行对比,证明了基于(gPCE)的传输线串扰概率分布计算的准确性和高效性。

随机热方程的数值解

将应用SG方法来求解一维的随机热方程和具有随机边界条件的确定型热方程.求解过程中,选择高斯积分公式进行数值积分;应用Legendre多项式噪声进行随机空间离散;应用Chebyshev多项式展开来逼近空间导数和它们的系数.特别地,在不存在理论解的模型中,应用Monte Carlo(MC)方法来验证方法的精确性.

大气边界层模式中随机参数的反演与不确定性分析

在大气边界层气象中湍流黏性系数是一个很重要的参数,通过直接观测往往无法得到其准确值,仅能通过间接观测获得大致范围.本文选用随机广义Ekman动力近似模式中的湍流黏性系数进行反演研究与不确定性分析.首先利用风速观测数据,并采用基于混沌多项式的集合Kalman滤波方法对系数进行反演,降低其不确定性,缩小可能取值的范围,该方法的核心思想是将集合Kalman滤波方法中求解模式不确定性传播的方法由蒙特卡罗法改为混沌多项式展开,从而避免大规模采样带来的计算资源耗费.然后进行数值实验,结果表明该方法能够有效且快速地求解出湍流黏性的后验概率分布,从而达到降低系数不确定性的目的.根据系数的先验分布计算出风速的先验分布,从而找到风速不确定性大的区域,且揭示了在不确定性大的区域内的观测数据进行系数反演可得到十分明显的效果,这对于观测点位置的选择提供了重要的指导.

High-Order Spectral Stochastic Finite Element Analysis of Stochastic Elliptical Partial Differential Equations

This study presents an experiment of improving the performance of spectral stochastic finite element method using high-order elements. This experiment is implemented through a two-dimensional spectral stochastic finite element formulation of an elliptic partial differential equation having stochastic coefficients. Deriving this spectral stochastic finite element formulation couples a two-dimensional deterministic finite element formulation of an elliptic partial differential equation with generalized polynomial chaos expansions of stochastic coefficients. Further inspection of the performance of resulting spectral stochastic finite element formulation with adopting linear and quadratic (9-node or 8-node) quadrilateral elements finds that more accurate standard deviations of unknowns are surprisingly predicted using quadratic quadrilateral elements, especially under high autocorrelation function values of stochastic coefficients. In addition, creating spectral stochastic finite element results using quadratic quadrilateral elements is not unacceptably time-consuming. Therefore, this study concludes that adopting high-order elements can be a lower-cost method to improve the performance of spectral stochastic finite element method.

Structural Reliability Assessment by a Modified Spectral Stochastic Meshless Local Petrov-Galerkin Method

This study presents a new tool for solving stochastic boundary-value problems. This tool is created by modify the previous spectral stochastic meshless local Petrov-Galerkin method using the MLPG5 scheme. This modified spectral stochastic meshless local Petrov-Galerkin method is selectively applied to predict the structural failure probability with the uncertainty in the spatial variability of mechanical properties. Except for the MLPG5 scheme, deriving the proposed spectral stochastic meshless local Petrov-Galerkin formulation adopts generalized polynomial chaos expansions of random mechanical properties. Predicting the structural failure probability is based on the first-order reliability method. Further comparing the spectral stochastic finite element-based and meshless local Petrov-Galerkin-based predicted structural failure probabilities indicates that the proposed spectral stochastic meshless local Petrov-Galerkin method predicts the more accurate structural failure probability than the spectral stochastic finite element method does. In addition, generating spectral stochastic meshless local Petrov-Galerkin results are considerably time-saving than generating Monte-Carlo simulation results does. In conclusion, the spectral stochastic meshless local Petrov-Galerkin method serves as a time-saving tool for solving stochastic boundary-value problems sufficiently accurately.

基于FPGA的电力电子变换器随机实时仿真建模方法

确定性模型无法对系统的随机特性进行准确描述,而目前的随机模型难以应用于现场可编程门阵列(FPGA)的实时仿真。基于广义多项式混沌展开方法建立电力电子变换器的随机实时仿真模型,针对复杂概率分布随机变量以及高复杂度系数矩阵导致的硬件资源消耗问题,提出一种最优正交多项式基函数的构建方法,减少FPGA的计算资源消耗,并提高模型精度。以三相脉宽调制整流器作为研究对象,通过离线仿真验证所提建模方法的准确性与有效性;并基于FPGA的实时仿真平台,搭建变换器的随机实时仿真模型。离线与实时仿真结果表明,所提模型可以实时求解系统输出响应的统计矩信息,高效地反映系统概率运行情况。

基于广义多项式混沌展开的无人机飞行性能不确定性分析

无人机飞行性能的不确定性分析有助于评估不确定性对无人机飞行任务规划的影响,为飞行任务方案的鲁棒性设计提供支撑。基于广义多项式混沌展开方法,建立了无人机飞行性能不确定性近似分析模型,利用样本实现了无人机性能多项式系数的非侵入式计算,研究了无人机状态在不确定条件下的非线性演化。在考虑初始条件、大气环境和气动参数存在不确定性的情况下,量化了不确定性对无人机性能的影响。数值分析结果表明,相比于传统的需要大量仿真样本的蒙特卡洛分析方法,提出的非侵入式展开方法在具有较高近似精度的情况下,仅需要少量的样本就可以完成无人机性能的不确定性分析,具有较高的计算效率。

垂直起降运载火箭返回轨迹不确定性优化

针对垂直起降运载火箭一子级在返回着陆的过程中存在的参数不确定性,提出了一种基于非侵入式多项式混沌展开的序列优化和可靠度评估的返回轨迹不确定性优化方法。首先,建立了返回多飞行段轨迹在确定性条件下的优化模型。然后,为同时兼顾轨迹的鲁棒性和可靠性,建立了由鲁棒最优目标函数、基于可靠度的路径约束和鲁棒等式约束组成的不确定性返回轨迹优化模型。最后,基于非侵入式多项式混沌展开方法对鲁棒目标函数和等式约束进行量化处理,将原随机鲁棒优化问题转化为高维状态空间中的等价确定性优化问题;为提高路径约束的可靠度评估效率,基于非侵入式多项式混沌展开方法对最可能点法进行改进,进一步发展了序列优化和可靠度评估策略。数值仿真结果表明,所提出的不确定性优化方法具有较好的鲁棒性,可以满足工程可靠性指标要求,同时还具有较高的精度和计算效率。