Research Interests
- Infrastructure Resilience
- Digital Twin Modeling
- AI and Computer Vision
Activity
Digital Twin Modeling of Infrastructure System
The DISCOVER (Digital Twin Infrastructure Science for Operations and Visualization in Engineering Resilience) laboratory at the University of Pittsburgh advances research in the fields of digital twin modeling and multiscale computational simulations of materials and structures for civil engineering applications. My research focuses on the numerical simulation of coupled physical phenomena occurring at multiple time and length scales, with the goal of predicting degradation in critical infrastructure systems at the regional and national level. My research team leverages data from remote and embedded sensing to augment the computational simulations and perform assessment of civil infrastructure systems. Advanced visualization techniques (e.g., Augmented and Virtual Realities, Holographic models) are leveraged in the research, allowing fora new generation of tools for the design, operation, maintenance, and retrofitting of horizontal and vertical civil infrastructure.
Advanced Computational Modeling for Structure and Infrastructure Applications
Accurate predictions of the structural behavior of civil infrastructure systems rely on the formal description of the mechanical response of the constituent materials. Resilient structure and infrastructure networks require high-performance materials designed to respond consistently and efficiently in normal and extraordinary conditions. My research team tackles high-complexity structural mechanics problems by defining and implementing novel multiscale and Multiphysics computational approaches, which are informed by experimental results at different scales to evaluate the mechanical parameters used as input for the simulations.
