An Interval Reduced Basis Approach and its Integrated Framework for Acoustic Response Analysis of Coupled Structural-Acoustic System

作     者：Lv, Zheng Qiu, Zhiping Li, Qi 

作者机构：Beijing Univ Aeronaut & Astronaut Inst Solid Mech Beijing 100191 Peoples R China Chinese Acad Sci Shenyang Inst Automat State Key Lab Robot Shenyang 110016 Liaoning Peoples R China 

出 版 物：《JOURNAL OF COMPUTATIONAL ACOUSTICS》 (计算声学杂志)

年 卷 期：2017年第25卷第3期

页      面：1750009-1750009页

核心收录：

学科分类：07[理学] 082403[工学-水声工程] 08[工学] 070206[理学-声学] 0824[工学-船舶与海洋工程] 0701[理学-数学] 0702[理学-物理学] 

基　　金：Defense Industrial Technology Development Program [A0820132001, JCKY2013601B] "111" Project [B07009] National Nature Science Foundation of the P. R. China [11372025, 11432002, 11602283] Aeronautical Science Foundation of China [2012ZA51010] 

主　　题：Interval reduced basis approach integrated framework structural-acoustic system interval parameters quadratic programming problem DC algorithm 

摘      要：An interval reduced basis approach (IRBA) is presented for analyzing acoustic response of coupled structural-acoustic system with interval parameters. Simultaneously an integrated framework based on IRBA is established to deal with uncertain acoustic propagation using deterministic finite element (FE) software. The present IRBA aims to improve the accuracy of the conventional first-order approximation and also allow the efficient calculation of second-order approximation of acoustic response. In IRBA, acoustic response is approximated using a linear combination of interval basis vectors with undetermined coefficients. To get explicit expression of acoustic response in terms of interval parameters, the three terms of the second-order perturbation method are employed as basis vectors, and the variant of the Galerkin scheme is applied for derivation of the reduced-order system of equations. For the second-order approximation, the determination of acoustic response interval is reformulated into a series of quadratic programming problems, which are solved using the difference of convex functions (DC) algorithm effectively. The performance of IRBA and availability of the present framework are validated by numerical examples.