Calibration of empirical models considering model fidelity and model robustness - Focusing on predictions of liquefaction-induced settlements

NCUIR > Engineering College > Department of Civil Engineering > journal & Dissertation > Item 987654321/100457

Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/100457

Title:	Calibration of empirical models considering model fidelity and model robustness - Focusing on predictions of liquefaction-induced settlements
Authors:	莊長賢;Gong, Wenping;Tien, Yong Ming;Juang, C. Hsein;Martin, James R.;Zhang, Jie
Contributors:	工學院土木工程學系
Keywords:	Bayesian theory;Calibration;Design analysis;Design engineering;Empirical models;engineering;geology;Geotechnics;Liquefaction;Mathematical models;Model fidelity;Model robustness;model uncertainty;Multi-objective optimization;prediction;Probabilistic model calibration;Probability theory;Robustness;Settlement;statistical analysis;Uncertainty
Date:	2016-03-25
Issue Date:	2026-04-21 14:03:15 (UTC+8)
Publisher:	Elsevier;Elsevier B.V
Abstract:	摘要： Most data-driven empirical models adopted in the geotechnical design have various degrees of uncertainty. Consequently, it is important to properly calibrate this uncertainty prior to its application in the geotechnical analysis to ensure the integrity of the final design. The conventional probabilistic model calibration approaches, such as maximum likelihood estimate and Bayesian method, focus only on model fidelity (measured through, for example, likelihood). These approaches often yield models with a large model uncertainty, especially when the observed data are scattered. A large model uncertainty leads to a large variation in the model prediction, which poses a significant challenge in a geotechnical design. In this paper, we propose a new model calibration approach that can consider both model fidelity and model robustness. The new model calibration approach offers a way to balance the objectives of model fidelity and model robustness. Because model fidelity and model robustness are two conflicting objectives, the new approach involves a multi-objective optimization that leads to a Pareto front, which defines a tradeoff relationship between model fidelity and model robustness. By enforcing a certain level of robustness, the variation in the model prediction can be reduced, which overcomes the major weakness of the traditional probabilistic approaches that focus solely on model fidelity. The new approach is demonstrated through applications to the problems of liquefaction-induced settlement prediction. •The conventional model calibration approaches focus only on model fidelity, which often yields models with a large model uncertainty.•A new framework that can consider both model fidelity and model robustness in the geotechnical model calibration is proposed.•The new framework is demonstrated through applications to the problem of liquefaction-induced settlement prediction. 出版者： Elsevier B.V 出版日期： 2016-03-25 出處： Engineering geology, 2016-03, Vol.203, p.168-177 資源來源： ScienceDirect 版權： 2015 Elsevier B.V. 識別號： ISSN: 0013-7952 識別號： EISSN: 1872-6917 識別號： DOI: 10.1016/j.enggeo.2015.11.003
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