This study presents an innovative approach to enhance performance-based earthquake engineering (PBEE) by combining reliability-based methods with seismic hazard disaggregation. PBEE aims to reduce damage and losses in structures subjected to stochastic excitations, such as earthquakes and wind turbulence. Unlike conventional probabilistic seismic hazard disaggregation, which may not fully address structural performance requirements, this approach focuses on disaggregating seismic demand within the Probabilistic Seismic Demand Analysis (PSDA) framework, making it a vital component of seismic risk analysis. This involves identifying the ground motion intensity measures contributing to specific structural response levels. The proposed methodology combines stochastic ground motion modeling with random vibration theory to estimate the failure probability of both linear and nonlinear systems under various seismic scenarios characterized by magnitude (M) and distance (R). Compared to traditional approaches requiring extensive record scaling and nonlinear time history analysis, this method leverages simulated excitations, offering significant computational efficiency. Results show that failure probability for linear systems remains relatively constant across scenarios, whereas nonlinear systems exhibit a strong dependence on the selected scenario, highlighting their sensitivity to varying seismic inputs. This research emphasizes the critical role of scenario selection in seismic demand analysis and introduces three cases—modal, worst, and weighted scenarios—for estimating failure probabilities. The findings provide practical insights for seismic risk assessment and structural design optimization, particularly in regions with sparse recorded ground motion data. This framework offers an efficient and robust solution for advancing PBEE practices in seismic engineering.
