Engineering Civil Infrastructures under Multi Natural Hazards

Coastal and inland infrastructure systems are increasingly exposed to compound and sequential hazards,
including hurricane wind, storm surge, waves, and flooding. This research thrust advances
physics-based, damage-conditioned modeling frameworks that capture how hazard loading and
infrastructure capacity evolve together, enabling realistic performance assessment and risk-informed design.

Core Research Focus

  • Coupled wind–wave–surge–flood loading characterization
  • Fluid–structure interaction (FSI) and aero/hydro-dynamics
  • Damage-conditioned loading and progressive failure modeling
  • Nonstationary storm evolution and demand modeling
  • Validated computational pipelines for diverse infrastructure types

What Has Been Done

  • Developed physics-based vulnerability assessment frameworks for compound hurricane hazards
  • Established high-fidelity finite element models to quantify progressive damage and failure mechanisms
  • Investigated wind–surge interaction effects and damage-sensitive demand amplification
  • Advanced methodologies that improve realism beyond independent-hazard assumptions

What We Are Doing Now

  • Building hazard-to-load simulation pipelines (CFD/FSI + reduced-order surrogates)
  • Developing damage-conditioned load updating strategies for progressive failure analysis
  • Extending multi-hazard mechanics across buildings, bridges, coastal defenses, and lifelines

Strategic Plan

  1. Develop scalable, validated multi-hazard load-generation workflows for infrastructure portfolios
  2. Enable closed-loop hazard–damage–load feedback modeling to capture evolving exposure
  3. Transition high-fidelity mechanics into scalable tools via hybrid physics–AI surrogates
  4. Integrate outputs with lifeline network resilience and community-scale recovery modeling

How This Connects

This thrust provides the mechanics foundation for DM2L’s research program and directly supports
hybrid physics–AI reliability modeling, lifeline resilience (power/transportation), interdependency analysis,
and community resilience planning.


Figure (TBA)