EFFECTIVE MODEL CALIBRATION VIA SENSIBLE VARIABLE IDENTIFICATION AND ADJUSTMENT WITH APPLICATION TO COMPOSITE FUSELAGE SIMULATION

• 成果类型: Article
• 署名作者: Wang, Yan; Yue, Xiaowei; Tuo, Rui; Hunt, Jeffrey H.; Shi, Jianjun
• 署名单位: Beijing University of Technology; Virginia Polytechnic Institute & State University; Texas A&M University System; Texas A&M University College Station; Boeing; University System of Georgia; Georgia Institute of Technology
• 刊物名称: ANNALS OF APPLIED STATISTICS
• ISSN/ISSBN: 1932-6157
• DOI: 10.1214/20-AOAS1353
• 发表日期: 2020
• 页码: 1759-1776
• 关键词: bayesian calibration; computer; shrinkage; selection

摘要

Estimation of model parameters of computer simulators, also known as calibration, is an important topic in many engineering applications. In this paper we consider the calibration of computer model parameters with the help of engineering design knowledge. We introduce the concept of sensible (calibration) variables. Sensible variables are model parameters, which are sensitive in the engineering modeling, and whose optimal values differ from the engineering design values. We propose an effective calibration method to identify and to determine appropriate levels for the sensible variables with limited physical experimental data. The methodology is applied to a composite fuselage simulation problem.