Extreme Events Engineering

2021 ~ Present | National Science Foundation, GDOT, IDOT, Industry

Goals

Advance the fundamental science in the assessment of natural and man-made hazards (e.g. earthquakes, landslides, liquefaction, sea-level rise, hazards in tailing dams, heap leach pads, coal ash facilities) through novel developments in performance-based and risk engineering.

We combine performance-based engineering, reliability, machine learning, and artificial intelligence tools with advanced numerical simulations, and novel experimental procedures to advance the fundamental understanding of the interaction between geo-hazards and geotechnical systems under extreme loading events and climate change stressors. The ultimate goal is to make infrastructure systems and cities more resilient, saving lives, and reducing economic losses. Additionally, we address the issues that have led to recent catastrophic worldwide failures in the mining industry.

Issues Involved or Addressed

Natural and man-made hazards, Geotechnical earthquake engineering,Advance numerical modeling and machine learning, performance-based design, risk engineering, mining geotechnics.

 

Methods and Technologies

  • Machine Learning
  • Artificial Intelligence
  • Numerical modeling (FEM, FDM, MPM, DEM)
  • Advanced laboratory tests (static and cyclic)
  • Material characterization techniques (e.g. image-based analyses)
  • Programing (Matlab, Python, C++)

Academic Majors of Interest

  • Algorithms, Combinatorics and Optimization
  • Computational Science and Engineering
  • Computer Science
  • OMSCS asynchronous
  • OMSCS synchronous
  • Civil Engineering
  • Computer Engineering
  • Electrical Engineering
  • Materials Science and Engineering
  • Earth and Atmospheric Sciences
  • Statistics

Preferred Interests and Preparation

Major(s) Civil Engineering:  Computational science, Statistics, Material Science, Earth and atmospheric sciences:  Background/interest in Natural hazards (earthquakes, landslides, liquefaction), man-made hazards (e.g. static liquefaction in tailing dams), Statistics, Machine Learning, Artificial Intelligence, Laboratory Experiments, Material Science.  

 

Meeting Schedule & Location

Time 
5:00-5:50
Meeting Location 
TBD
Meeting Day 
Thursday

Team Advisors

Mr. Jorge Macedo
  • Civil and Environmental Engineering

Partner(s) and Sponsor(s)

National Science Foundation, GDOT, IDOT, Industry