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

作     者：D.LEE S.CHANG J.LEE D.LEE;S.CHANG;J.LEE

作者机构：Department of Automotive EngineeringHanyang UniversitySeoul 04763Republic of Korea School of Mechanical EngineeringChungnam National UniversityDaejeon 34134Republic of Korea Department of MechanicalRobotics and Energy EngineeringDongguk UniversitySeoul 04620Republic of Korea 

出 版 物：《Applied Mathematics and Mechanics(English Edition)》 (应用数学和力学（英文版）)

年 卷 期：2024年第45卷第5期

页      面：819-836页

核心收录：

学科分类：07[理学] 070104[理学-应用数学] 0701[理学-数学] 0801[工学-力学（可授工学、理学学位）] 

基　　金：Project supported by the National Research Foundation of Korea(Nos.NRF-2020R1C1C1011970 and NRF-2018R1A5A7023490) 

主　　题：forward uncertainty quantification(UQ) generalized polynomial chaos expansion(GPCE) static reanalysis method static condensation substructuring 

摘      要：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 *** 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 *** the reanalysis,we employ substructuring for a structure to isolate its local regions that vary due to random *** allows for avoiding repeated computations of invariant substructures while generating the input-output data *** substructuring with static condensation further improves the computational efficiency of the reanalysis without losing ***,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 *** 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.