Fragility analysis of degraded structures considering soil-structure interaction

This project framework helps you evaluate how likely degraded structures are to be damaged by earthquakes, and it includes the effects of soil‑structure interaction (SSI). Traditional methods for seismic fragility often assume a lognormal distribution, which adds epistemic uncertainty, or they use non‑parametric Monte Carlo simulations that require a lot of computing time. To overcome these issues, the study proposes an active‑learning surrogate model that builds accurate fragility curves while using far fewer calculations. The method combines pushover analysis with adaptive sampling, so it picks the most important training points and updates the surrogate model on the fly. This reduces the number of expensive nonlinear response analyses, especially in the

low‑probability failure region. The implementation guide covers how to set up numerical models of degraded reinforced‑concrete (RC) frames, how to represent the soil‑foundation interface, and how to run the active‑learning loop. In the end, the approach gives M.Tech students a clear way to see how structural degradation and SSI interact, and it provides a solid computational workflow for performance‑based earthquake engineering.

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