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.
Predicting the nonlinear seismic response of structures that have entered the plastic range under strong ground motions is severely constrained by data scarcity and computational cost. In this article, to address this dual challenge, we propose a physics-guided ensemble model based on Support Vector Regression. A finit...
Wan-Qi Zheng, Ai-Fu Sun, Han-Wei Wang et al.· Buildings· 0 citations
This study examines how lead-rubber bearing (LRB) isolation changes the seismic response of a ten-story reinforced-concrete building using matched fixed-base and isolated models. Three-dimensional ETABS models were analyzed using nonlinear direct integration under the EQ-X component of the 1999 Kocaeli earthquake recor...
A. Kadhum, Mohammed Abid Jameel, Mohammed A. Radi et al.· Civil Engineering Journal· 0 citations
The increasing complexity and vulnerability of urban structures under seismic excitation demand real-time, accurate, and adaptive assessment methodologies. Traditional earthquake response evaluations, primarily based on static finite element analysis or delayed post-event data processing, often fail to capture the evol...
Jian-Guang Lin· International Conference on...· 0 citations
This study evaluates the post-earthquake damage of a 17-story plan-irregular reinforced concrete (RC) building damaged during the 2024 Hualien earthquake. A three-dimensional numerical model was constructed in ETABS, utilizing nonlinear component characteristics derived from the mechanics-based Seismic Evaluation of RC...
Conventional machine learning approaches in earthquake engineering have primarily focused on predicting peak structural response quantities, often neglecting the time-dependent nature of seismic behavior. This study applies a sequence-learning framework to directly map ground-motion time series to the full dynamic resp...
Arcan Yanik· Journal of Vibration and Con...· 0 citations
A unified surrogate modeling framework to predict the structural responses of a steel box girder bridge under moving-load analysis is developed, ensuring consistency in both data generation and model assessment.
Yun-Fei Wang, Bing Zhao, Jie Wang et al.· Bridge Structures· 0 citations
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