Modern infrastructure is interconnected. Failures in one network (e.g., power) can propagate to others
(e.g., transportation, emergency access), producing cascading disruptions that dominate community impacts.
DM2L develops system-of-systems modeling frameworks to quantify interdependency, cascading risk,
and staged recovery under compound hazards.
Core Research Focus
- Multi-layer network modeling of connected infrastructures
- Dependency and interdependency quantification
- Cascading failure propagation under spatially varying hazards
- Staged restoration and recovery optimization
- System-level reliability and resilience metrics
What Has Been Done
- Developed community-scale vulnerability and resilience modeling frameworks under hurricane hazards
- Advanced methodologies that improve prediction accuracy for coupled hazard scenarios
- Established building blocks for cascading impact assessment across infrastructure layers
What We Are Doing Now
- Building coupled power–transportation disruption and recovery models
- Developing scalable cascading failure simulators using hybrid physics–AI methods
- Integrating restoration constraints (access, priority, resources) into recovery optimization
Strategic Plan
- Formalize multi-layer interdependency models for compound hazard environments
- Enable cascading failure simulation at regional scales with uncertainty quantification
- Integrate recovery optimization with community resilience and equity-informed metrics
- Deliver decision-support tools for agencies and infrastructure owners
How This Connects
This thrust integrates outputs from lifeline resilience modeling and feeds directly into community resilience
assessment by quantifying indirect impacts and recovery pathways across sectors.
Figure (TBA)