Research Topics and Interests

DM²L is a multi-scale, multi-hazard infrastructure systems modeling laboratory. We develop
physics-grounded and uncertainty-aware methodologies to quantify damage, functionality loss, and
recovery of civil infrastructure under extreme environments. Our work integrates structural and fluid
mechanics, computational modeling, reliability engineering, and data-driven methods to support life-cycle
performance design and resilient, sustainable coastal communities.

Our research interests are organized into six integrated pillars:

1. Multi-Hazard Infrastructure Mechanics
   High-fidelity physics-based modeling of wind–wave–surge–flood loading and infrastructure response, including damage-conditioned progressive failure.
2. Hybrid Physics–AI Damage & Reliability Modeling
   Physics-informed and data-driven methods for fragility, vulnerability, reliability, and uncertainty quantification; scalable surrogates for high-fidelity simulation.
3. Lifeline Systems Resilience (Power & Transportation)
   Component-to-network modeling of outages, service disruption, restoration, and hardening strategies for lifeline infrastructure systems.
4. Infrastructure Interdependency & Cascading Risk
   System-of-systems modeling of dependencies, cascading impacts, and recovery optimization under compound hazards across interconnected infrastructures.
5. Life-Cycle Damage Mechanics (Fatigue/Corrosion/Fracture)
   Multi-scale mechanics for long-term deterioration and life-cycle performance of materials and structural details, supporting reliability-based durability and maintenance planning.
6. Resilient Renewable & Offshore Energy Systems
   Structural dynamics and reliability of offshore wind and wave energy systems under environmental uncertainty; vibration-based energy harvesting concepts and devices.

Current Research Directions

The current research directions below are actionable thrusts that advance the six pillars above.
These efforts integrate hazard simulation, mechanics-based damage modeling, data analytics, and decision optimization
to deliver scalable tools for infrastructure risk assessment and resilience planning.

1. Multi-Hazard Infrastructure Mechanics
   • Engineering Civil Infrastructures under Multi Natural Hazards— wind–wave–surge–flood loading, coupled fluid–structure interaction, and damage-conditioned progressive failure modeling.
   • Hazard-to-load simulation pipelines — CFD/FSI workflows and validated reduced-order surrogates to generate physically consistent load fields for buildings, bridges, and coastal defenses.
2. Hybrid Physics–AI Damage & Reliability Modeling
   • Physics-informed Machine Learning Surrogates — accelerate high-fidelity simulation (wind/wave loading, response prediction, fragility surfaces) while preserving physical constraints.
   • Reliability under nonstationary hazards — uncertainty quantification methods addressing spatial heterogeneity and limited-data regimes.
3. Lifeline Systems Resilience (Power & Transportation)
   • Damage Modeling and Resilience Assessment of Power Infrastructure — fragility, outage prediction, and hardening strategies for transmission and distribution systems under extreme weather.
   • Coastal Hazards and Lifeline Infrastructure Systems— integrated modeling of coastal hazards and lifelines (power + transportation) for disruption, accessibility, and recovery analysis.
4. Infrastructure Interdependency & Cascading Risk
   • Infrastructure Interdependency and Cascading Failures— multi-layer network modeling of dependencies, cascading impacts, and staged restoration optimization.
   • Community Resilience — link physical damage to system functionality, recovery trajectories, and resilience metrics to support planning and mitigation.
5. Life-Cycle Damage Mechanics (Fatigue/Corrosion/Fracture)
   • Fatigue Damage Modeling of Structures and Materials — multi-scale fatigue/fracture/corrosion modeling and reliability-based durability assessment for infrastructure details and materials.
   • Life-cycle planning — integrate deterioration models with hazard-driven loading to support maintenance, inspection, and rehabilitation optimization.
6. Resilient Renewable & Offshore Energy Systems
   • Offshore wind and wave energy reliability — response and fatigue models under coupled wind–wave environments and long-term loading.
   • Vibration-based energy harvesting — concepts and devices for sensing/monitoring applications in harsh coastal environments.