🤖 AI Summary
This study addresses the limitation of regional seismic assessments that rely on building archetypes for attribute assignment, which often fail to capture structure-specific responses. To this end, we propose a modular physics-regularized framework that leverages differentiable programming to construct a forward solver. By integrating dynamic equilibrium residuals with response matching for joint parameter estimation, the framework identifies single-degree-of-freedom Bouc-Wen models from seismic input-response histories, enabling refined simulation of regional nonlinear structural responses. Applied to an M6.8 earthquake scenario, the aggregate repair cost derived from individual structure responses is approximately twice that estimated by the archetype-based approach. These findings demonstrate the critical value of incorporating structure-specific information in enhancing the accuracy of regional seismic damage assessments.
📝 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 $M_w=6.8$, 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.