Model calibration of locally nonlinear dynamical systems: Extended constitutive relation error with multi-harmonic coefficients. Issue 2 (9th January 2019)

• Record Type: Journal Article
• Authors: Hu, Xiaoyu; Chodora, Evan; Prabhu, Saurabh; Gupte, Akshay; Atamturktur, Sez
• Is Part Of: Engineering computations. Volume 36:Issue 2(2019)
• Page Start: 466
• Page End: 490
• Publication Date: 2019-01-09
• Subjects: Finite element method -- Model uncertainty -- Constrained minimization -- ECL benchmark -- Nonlinear model calibration; Computer-aided engineering -- Periodicals; Computer graphics -- Periodicals; 620.00285
• DOI: 10.1108/EC-10-2017-0419
• Languages: English
• ISSNs: 0264-4401

Abstract

Abstract : Purpose: This paper aims to present an approach for calibrating the numerical models of dynamical systems that have spatially localized nonlinear components. The approach implements the extended constitutive relation error (ECRE) method using multi-harmonic coefficients and is conceived to separate the errors in the representation of the global, linear and local, nonlinear components of the dynamical system through a two-step process. Design/methodology/approach: The first step focuses on the system's predominantly linear dynamic response under a low magnitude periodic excitation. In this step, the discrepancy between measured and predicted multi-harmonic coefficients is calculated in terms of residual energy. This residual energy is in turn used to spatially locate errors in the model, through which one can identify the erroneous model inputs which govern the linear behavior that need to be calibrated. The second step involves measuring the system's nonlinear dynamic response under a high magnitude periodic excitation. In this step, the response measurements under both low and high magnitude excitation are used to iteratively calibrate the identified linear and nonlinear input parameters. Findings: When model error is present in both linear and nonlinear components, the proposed iterative combined multi-harmonic balance method (MHB)-ECRE calibration approach has shown superiority to the conventional MHB-ECRE method, while providing more reliable calibration results of the nonlinear parameter with less dependency on a priori knowledge of the associated linear system. Originality/value: This two-step process is advantageous as it reduces the confounding effects of the uncertain model parameters associated with the linear and locally nonlinear components of the system.