This project extends transportation resilience modeling beyond emergency response to broader community recovery. I developed a probabilistic framework that links seismic hazard, infrastructure damage, repair and recovery operations, network performance, and community-level economic, environmental, and social losses.

Key contributions

• Integrated hazard, risk, network, and recovery models into a single probabilistic resilience-analysis workflow
• Quantified multiple loss categories, including direct economic, indirect economic, social, socioeconomic, and environmental effects
• Supported resilience-enhancement decisions such as bridge retrofit prioritization and recovery-planning strategies

Impact

The project provides a broader view of transportation resilience by connecting infrastructure disruption to long-term community recovery, enabling better planning decisions than approaches based only on connectivity or travel-time metrics.