Bayesian inference for calibration and validation of uniaxial reinforcing steel models

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dc.creatorBirrell, Matias
dc.creatorAstroza, Rodrigo
dc.creatorRestrepo, José I.
dc.creatorLoftizadeh, Koorosh
dc.creatorCarreño, Rodrigo
dc.creatorBazáez, Ramiro
dc.creatorHernández, Francisco
dc.date2021-09-15
dc.date.accessioned2025-10-28T16:27:16Z
dc.date.available2025-10-28T16:27:16Z
dc.description<p>With ever-advancing structural design and evaluation techniques becoming available for structural engineers, the required level of knowledge about nonlinear material behavior in civil structures has increased accordingly over recent years. In the context of finite element (FE) modeling, constitutive material models play a crucial role in the computation of the structural response. Although significant research has focused on characterizing the stress–strain relationship in reinforcing steel, most of these efforts have considered experimental response data from monotonic tests. In this paper, results from experimental cyclic tests conducted on 36 reinforcing steel coupons obtained from three major manufacturers encompassing two widely used steel grades are employed to gain a deep understanding of the relationship between model formulation and response, for three well-known hysteretic reinforcing steel one-dimensional constitutive stress–strain relationships. Initially, the three models are briefly described. Then, a local sensitivity analysis (LSA) is performed to provide an insight on the influence of each model parameter in model response, followed by a global sensitivity analysis (GSA) performed to further understand the composition of response variability due to parameter uncertainty. Model calibration is then carried out in a probabilistic manner, using the Bayesian estimation (BE) framework through the use of Markov Chain Monte Carlo (MCMC), and informed by LSA and GSA results. Parameter estimation results for each model are discussed, with an emphasis on the level of accuracy of predictions achieved with estimated sets of parameters in each case. The amount of information extracted about each parameter during calibration is assessed, leading to a performance comparison between the three constitutive laws under study.</p>eng
dc.descriptionWith ever-advancing structural design and evaluation techniques becoming available for structural engineers, the required level of knowledge about nonlinear material behavior in civil structures has increased accordingly over recent years. In the context of finite element (FE) modeling, constitutive material models play a crucial role in the computation of the structural response. Although significant research has focused on characterizing the stress–strain relationship in reinforcing steel, most of these efforts have considered experimental response data from monotonic tests. In this paper, results from experimental cyclic tests conducted on 36 reinforcing steel coupons obtained from three major manufacturers encompassing two widely used steel grades are employed to gain a deep understanding of the relationship between model formulation and response, for three well-known hysteretic reinforcing steel one-dimensional constitutive stress–strain relationships. Initially, the three models are briefly described. Then, a local sensitivity analysis (LSA) is performed to provide an insight on the influence of each model parameter in model response, followed by a global sensitivity analysis (GSA) performed to further understand the composition of response variability due to parameter uncertainty. Model calibration is then carried out in a probabilistic manner, using the Bayesian estimation (BE) framework through the use of Markov Chain Monte Carlo (MCMC), and informed by LSA and GSA results. Parameter estimation results for each model are discussed, with an emphasis on the level of accuracy of predictions achieved with estimated sets of parameters in each case. The amount of information extracted about each parameter during calibration is assessed, leading to a performance comparison between the three constitutive laws under study.spa
dc.formatapplication/pdf
dc.identifierhttps://investigadores.uandes.cl/en/publications/9046a504-13c9-428e-99be-c048a19df854
dc.identifierhttps://doi.org/10.1016/j.engstruct.2021.112386
dc.identifierhttps://investigadores.uandes.cl/ws/files/83538723/1-s2.0-S0141029621005368-main.pdf
dc.identifierhttps://www.scopus.com/pages/publications/85108057862
dc.identifierhttps://www.mendeley.com/catalogue/8875225f-71a3-3bdc-b313-e7574321c4a2/
dc.identifier.urihttps://repositorio.uandes.cl/handle/uandes/49733
dc.languageeng
dc.relationinfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.engstruct.2021.112386
dc.rightsinfo:eu-repo/semantics/openAccess
dc.sourceBirrell, M, Astroza, R, Restrepo, J I, Loftizadeh, K, Carreño, R, Bazáez, R & Hernández, F 2021, 'Bayesian inference for calibration and validation of uniaxial reinforcing steel models', Engineering Structures, vol. 243, 112386. https://doi.org/10.1016/j.engstruct.2021.112386
dc.subjectBayesian estimationeng
dc.subjectConstitutive modelseng
dc.subjectReinforcing steeleng
dc.subjectSensitivity analysiseng
dc.titleBayesian inference for calibration and validation of uniaxial reinforcing steel modelseng
dc.typearticle
dc.typeinfo:eu-repo/semantics/publishedVersion
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