Regional-scale nonlinear structural response simulation using building-specific Bouc-Wen models
Abstract
Regional seismic assessments often assign structural properties by building archetype, limiting their representation of building-specific responses. This study develops a modular physics-regularized framework for identifying equivalent single-degree-of-freedom Bouc--Wen models from seismic input--response histories. A differentiable forward solver enables joint estimation of hysteretic parameters and viscous damping through an objective combining response matching with independently weighted dynamic-equilibrium and hysteretic state-evolution residuals. Before regional application, synthetic systems and four-story steel-frame hybrid simulation data are used to evaluate identification and prediction under unseen inputs, showing improved parameter estimation relative to a genetic algorithm and improved predictive performance with physics regularization, respectively. The framework is then applied to a numerical benchmark of 14,280 buildings in Milpitas, California, using models identified from simulated responses to a smaller earthquake to predict responses under larger scenarios. With the inventory, ground-motion inputs, and damage-and-loss models held fixed, archetypal and response-informed portfolios yield distinct damage-fraction distributions and substantially different structural repair costs. For the earthquake scenario with moment magnitude Mw=6.8, the response-informed portfolio yields a mean structural repair cost nearly twice that of the archetypal portfolio, despite nearly identical mean damage fractions. These results highlight the influence of structural model assignment on regional damage and loss estimates and the importance of incorporating building-specific response information into regional assessment.
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BibTeX
@misc{oh2026regionalscale,
title = {{Regional-scale nonlinear structural response simulation using building-specific Bouc-Wen models}},
author = {Sebin Oh and Taeyong Kim},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.38950},
eprint = {2609.38950},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.38950},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Regional-scale nonlinear structural response simulation using building-specific Bouc-Wen models
AU - Sebin Oh
AU - Taeyong Kim
PY - 2026
DA - 2026/09/30
PB - arXiv
DO - 10.48550/arxiv.2609.38950
UR - https://arxiv.org/abs/2609.38950
AB - Regional seismic assessments often assign structural properties by building archetype, limiting their representation of building-specific responses. This study develops a modular physics-regularized framework for identifying equivalent single-degree-of-freedom Bouc--Wen models from seismic input--response histories. A differentiable forward solver enables joint estimation of hysteretic parameters and viscous damping through an objective combining response matching with independently weighted dynamic-equilibrium and hysteretic state-evolution residuals. Before regional application, synthetic systems and four-story steel-frame hybrid simulation data are used to evaluate identification and prediction under unseen inputs, showing improved parameter estimation relative to a genetic algorithm and improved predictive performance with physics regularization, respectively. The framework is then applied to a numerical benchmark of 14,280 buildings in Milpitas, California, using models identified from simulated responses to a smaller earthquake to predict responses under larger scenarios. With the inventory, ground-motion inputs, and damage-and-loss models held fixed, archetypal and response-informed portfolios yield distinct damage-fraction distributions and substantially different structural repair costs. For the earthquake scenario with moment magnitude M_w=6.8, the response-informed portfolio yields a mean structural repair cost nearly twice that of the archetypal portfolio, despite nearly identical mean damage fractions. These results highlight the influence of structural model assignment on regional damage and loss estimates and the importance of incorporating building-specific response information into regional assessment.
ER -