ADVANCES IN UNCERTAINTY ANALYSIS FOR INFRASTRUCTURE RISK AND RESILIENCE ASSESSMENT

The increasing frequency and intensity of natural hazards, combined with evolving environmental stressors and material degradation, pose significant challenges to the long-term resilience of civil infrastructure systems. Effective risk and resilience assessment is complicated by multiple sources of uncertainty, including incomplete or limited knowledge of future conditions, the high computational demands of probabilistic modeling, and the underutilization of real-time monitoring data. This dissertation addresses these challenges by proposing various solutions, including robust decision-making under deep uncertainty, computationally efficient scenario reduction, and dynamic resilience assessment through real-time data integration.