Effective Model Calibration via Sensible Variable Identification and Adjustment, with Application to Composite Fuselage Simulation

TL;DR

This paper introduces a calibration method that identifies and adjusts sensitive model variables using limited data, demonstrated on a composite fuselage simulation, improving model accuracy in engineering applications.

Contribution

The paper proposes a novel calibration approach focusing on sensible variables, enhancing model calibration efficiency with limited experimental data.

Findings

Effective identification of sensible variables in calibration.

Improved model accuracy in composite fuselage simulation.

Method reduces need for extensive physical experiments.

Abstract

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 adjust the sensible variables with limited physical experimental data. The methodology is applied to a composite fuselage simulation problem.