Work

Structural Damage Identification via Bayesian Inference with a New Hierarchical Modeling and Spike-and-Slab Prior

Year: 2024

Type: article

Abstract: The present work aims to formulate and solve the inverse problem of structural damage identification using Bayesian Inference. In the solution of the direct problem, the Finite Element Method (FEM) is considered. The modeling of the damage field is performed through the cohesion parameter, which continuously describes the integrity of the structure. The damage identification problem is formulated as an inverse parameter estimation problem, where the posterior probability distribution of the cohesion parameters is sampled using the Adaptive Markov Chain Monte Carlo method and a Spike-Slab prior, adopting a novel hierarchical modeling approach for the inverse problem and an appropriate prior distribution that naturally models the available information about the parameters of interest.

Source: Ciência e Natura

DOI: 10.5902/2179460x87212

Authors: Josiele da Silva Teixeira, Helio dos Santos Migon, Leonardo Tavares Stutz, Diego Campos Knupp, Antônio José da Silva Neto

Institution: Universidade do Estado do Rio de Janeiro

Language: English

Topic: Structural Health Monitoring Techniques

Subfield: Civil and Structural Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: diamond

Funders: Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Conselho Nacional de Desenvolvimento Científico e Tecnológico, Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro

Award: G29316538