Adding-Point Strategy for Reduced-Order Hypersonic Aerothermodynamics Modeling Based on Fuzzy Clustering

作     者：CHEN Xin LIU Li ZHOU Sida YUE Zhenjiang 

作者机构：Key Laboratory of Dynamics and Control of Flight Vehicle of Ministry of EducationBeijing Institute of Technology School of Aerospace Engineering Beijing Institute of Technology 

出 版 物：《Chinese Journal of Mechanical Engineering》 (中国机械工程学报（英文版）)

年 卷 期：2016年第29卷第5期

页      面：983-991页

核心收录：

学科分类：0817[工学-化学工程与技术] 080103[工学-流体力学] 08[工学] 0807[工学-动力工程及工程热物理] 080104[工学-工程力学] 0802[工学-机械工程] 0811[工学-控制科学与工程] 0801[工学-力学（可授工学、理学学位）] 

基　　金：Supported by National Natural Science Foundation of China(Grant No.11372036) 

主　　题：reduced order model fuzzy clustering hypersonic aerothermodynamics adding-point strategy 

摘      要：Reduced order models（ROMs） based on the snapshots on the CFD high-fidelity simulations have been paid great attention recently due to their capability of capturing the features of the complex geometries and flow configurations. To improve the efficiency and precision of the ROMs, it is indispensable to add extra sampling points to the initial snapshots, since the number of sampling points to achieve an adequately accurate ROM is generally unknown in prior, but a large number of initial sampling points reduces the parsimony of the ROMs. A fuzzy-clustering-based adding-point strategy is proposed and the fuzzy clustering acts an indicator of the region in which the precision of ROMs is relatively low. The proposed method is applied to construct the ROMs for the benchmark mathematical examples and a numerical example of hypersonic aerothermodynamics prediction for a typical control surface. The proposed method can achieve a 34.5% improvement on the efficiency than the estimated mean squared error prediction algorithm and shows same-level prediction accuracy.