Kamiński, M.; Strąkowski, M. Relative Entropy Application to Study the Elastoplastic Behavior of S235JR Structural Steel. Materials2024, 17, 727.
Kamiński, M.; Strąkowski, M. Relative Entropy Application to Study the Elastoplastic Behavior of S235JR Structural Steel. Materials 2024, 17, 727.
Kamiński, M.; Strąkowski, M. Relative Entropy Application to Study the Elastoplastic Behavior of S235JR Structural Steel. Materials2024, 17, 727.
Kamiński, M.; Strąkowski, M. Relative Entropy Application to Study the Elastoplastic Behavior of S235JR Structural Steel. Materials 2024, 17, 727.
Abstract
The main issue in this work is to study limit functions necessary for the reliability assessment of the structural steel with the use of the relative entropy apparatus. This would be done using a few different mathematical theories relevant to this relative entropy, namely those proposed by Bhattacharyya, Kullback-Leibler, Jeffreys, and Hellinger. Probabilistic analysis in the presence of uncertainty in material characteristics would be delivered using three different numerical strategies – Monte-Carlo simulation, stochastic perturbation method as well as the semi-analytical approach. All these methods are based on the Weighted Least Squares Method approximations of the structural response functions versus the given uncertainty source and they would allow efficient determination of the first two probabilistic moments of the structural responses including stresses, displacements, and strains. The entire computational implementation would be delivered using the Finite Element Method system ABAQUS and computer algebra program MAPLE, where relative entropies, as well as polynomial response functions, would be determined. This study would demonstrate that the relative entropies may be efficiently used in reliability assessment close to the widely engaged First Order Reliability Method (FORM).
Keywords
Stochastic Finite Element Method; Ramberg-Osgood material model; stochastic perturbation technique; Monte–Carlo simulation; semi-analytical method; Least Squares Method
Subject
Engineering, Civil Engineering
Copyright:
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