Volume 16, Issue 2 (4-2026)
IJOCE 2026, 16(2): 301-324 |
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Maleki S, Ilchi Ghazaan M, Ghafouri A. UNCERTAINTY QUANTIFICATION IN APPROXIMATING DYNAMIC RESPONSES OF STRUCTURES USING REDUCED ORDER MODELS. IJOCE 2026; 16 (2) :301-324
URL: http://ijoce.iust.ac.ir/article-1-679-en.html
URL: http://ijoce.iust.ac.ir/article-1-679-en.html
1- School of Civil Engineering, Iran University of Science and Technology, P.O. Box 16846-13114, Iran
Abstract: (399 Views)
Reduced order models (ROMs) are widely used to approximate the dynamic response of large-scale structural systems while substantially reducing computational cost. Inherent uncertainties necessitate the assessment of ROMs within an uncertainty quantification (UQ) framework. Although the deterministic accuracy of reduction techniques has been extensively investigated, their capability for UQ remains insufficiently understood. This study presents a systematic UQ-based assessment of four condensation techniques: Guyan reduction, dynamic condensation, Improved Reduced System (IRS), and the System Equivalent Reduction Expansion Process (SEREP). A shear frame and a plane truss are used to evaluate the combined influence of the reduction technique, master degree of freedom (DOF) selection, and structural dynamic complexity on ROM predictive capability. Polynomial Chaos Expansion (PCE) is employed for UQ, and variance-based Sobol' indices are adopted for global sensitivity analysis (GSA). SEREP consistently provides the closest approximation to the full order model, whereas IRS also maintains high accuracy over most vibration modes. The accuracy of the Guyan and dynamic condensation methods decreases as higher-order dynamics become increasingly important.
Keywords: Reduced order models, Uncertainty quantification, Polynomial Chaos Expansion, Global sensitivity analysis, Structural dynamics
Type of Study: Research |
Subject:
Applications
Received: 2026/03/26 | Accepted: 2026/05/28 | Published: 2026/05/30
Received: 2026/03/26 | Accepted: 2026/05/28 | Published: 2026/05/30
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