Optimal seismic design using Performance-Based Engineering

• Ano de defesa: 2025
• Autor(a) principal: Rodrigues, Isabela Durci
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Biblioteca Digitais de Teses e Dissertações da USP
• Palavras-chave em Português: engenharia sísmica baseada em desempenho; metamodelagem; metamodeling; otimização de risco baseada em desempenho; otimização estrutural; performance-based earthquake engineering; performance-based risk optimization; quantificação de incertezas; structural optimization; uncertainty quantification
• Link de acesso: https://www.teses.usp.br/teses/disponiveis/18/18134/tde-09022026-140715/

Performance-Based Earthquake Engineering (PBEE) enables rational structural design by explicitly accounting for seismic hazard uncertainty and balancing construction costs with expected consequences such as repair costs, replacement, injury, and death. Risk-based optimization can be naturally integrated into PBEE to pursue economically efficient designs, forming a framework referred to as Performance-Based Risk Optimization (PBRO). However, the application of PBRO remains limited due to the heavy computational burdenimposed by the nonlinear time history analysis (NLTHA) to propagate uncertainty and characterize the joint probability distribution of the Engineering Demand Parameters (EDP) and parameters of the fragility functions. This dissertation proposes methodologies for estimating statistical parameters of the EDPs and fragility functions using metamodeling (or surrogate modeling) strategies to emulate both the deterministic and stochastic simulations to obtain the structural response. The adopted framework builds upon the assessment procedures defined in international standards for PBEE, and introduces Gaussian processbased metamodels to approximate computationally intensive simulations while incorporating the associated uncertainties of the problem. Case studies on reinforced concrete and steel structures are presented to demonstrate how metamodels and PBRO can be combined to optimize structural parameters under seismic demands. The results show that the proposed framework enables accurate representation of EDP uncertainties and supports the derivation of optimal designs with significantly reduced computational cost. By comparing different strategies for uncertainty representation, the research illustrates how metamodels can maintain the fidelity of PBEE-based risk assessments while making PBRO computationally tractable. Overall, this work contributes to advancing the integration of risk optimization into seismic design practice, offering evidence that balanced trade-offs between construction cost and expected seismic loss can be achieved within a metamodel-enhanced PBRO framework.