DOI: 10.17603/ds2-3z11-d239
title: Fragility Analysis of Buildings Under Mainshock-Aftershock Sequences: Simulation Data and Results
title: in Single-Variable Fragility Analysis of Mainshock-Aftershock Sequences for Community Resilience Studies: Data and Code

description: This simulation investigates the seismic fragility of buildings subjected to mainshock-aftershock sequences to assess their progressive damage and structural vulnerability. The study utilizes Nonlinear Time History Analysis (NTHA) implemented in OpenSeesPy, incorporating Monte Carlo Simulation (MCS) and Multiple Strip Analysis (MSA) to model damage accumulation under successive seismic events. The dataset includes structural response parameters, fragility curves, and probability distributions of damage states across varying hazard intensities.

The results provide critical insights into the incremental damage effects of aftershocks, which are often overlooked in conventional fragility assessments. These findings contribute to improved seismic risk modeling, community resilience planning, and performance-based engineering. The data can be reused by researchers and engineers for developing advanced fragility models, validating resilience frameworks, and integrating aftershock considerations into structural design and retrofitting strategies.
description: This project presents a data-driven methodology for developing single-variable fragility functions to assess the seismic vulnerability of buildings subjected to mainshock-aftershock sequences. The study focuses on reinforced concrete (RC) and woodframe structures, capturing incremental damage accumulation from successive seismic events. By explicitly incorporating aftershock effects—often overlooked in traditional fragility analyses—this research enhances seismic risk assessments and community resilience planning.

Using Monte Carlo Simulations (MCS) and Multiple Strip Analysis (MSA), the project quantifies progressive structural damage under sequential seismic events. The methodology is implemented in OpenSeesPy, leveraging Nonlinear Time History Analysis (NTHA) and high-resolution finite element (FE) modeling. Findings are integrated into the IN-CORE (Interdependent Networked Community Resilience Modeling Environment) to evaluate community-wide risk and economic losses.

Data Reusability and Applications:

The datasets, fragility functions, and computational models developed in this project can be reused in various fields, including:

- Seismic Risk Assessment: Researchers and engineers can use the fragility curves to predict damage probabilities for different building types under mainshock-aftershock sequences.
- Community Resilience Modeling: Urban planners and policymakers can integrate these fragility functions into regional resilience assessments to improve post-earthquake recovery planning.
- Structural Design and Retrofitting: The data supports performance-based earthquake engineering (PBEE), helping engineers design more resilient structures.
- Machine Learning Applications: The fragility datasets can be used to train ML models for predicting seismic performance based on structural characteristics and seismic intensity measures.
- Further Investigation: The project provides testbed information and a Jupyter Notebook for replicating and extending the analysis.

This research offers a comprehensive, computationally efficient framework for integrating aftershock effects into seismic vulnerability assessments—a critical step toward improving community resilience against successive seismic events.

Reference papers: 

Harati, M., & van de Lindt, J. W. (2024). Mainshock-aftershock building fragility methodology for community resilience modeling. Structures, 70, 107742. https://doi.org/10.1016/j.istruc.2024.107742

Harati, M., & van de Lindt, J. W. (2024). Community-level resilience analysis using earthquake-tsunami fragility surfaces. Resilient Cities and Structures, 3(2), 101–115. https://doi.org/10.1016/j.rcns.2024.07.006

Harati, M., & van de Lindt, J. W. (2024). Methodology to generate earthquake-tsunami fragility surfaces for community resilience modeling. Engineering Structures, 305, 117700. https://doi.org/10.1016/j.engstruct.2024.117700