Estéfan Garcia

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Prof. Garcia’s primary research interests are in the realm of granular materials and granular systems. Granular and particulate materials represent some of the most commonly manipulated materials in our society. A fundamental understanding of their behavior at the scale of individual grains or particles has wide-ranging benefits in several fields including civil engineering, geology, additive manufacturing, and planetary exploration. Prof. Garcia uses advanced numerical modeling techniques that can simulate large-strain behavior while also capturing directly the fundamental discontinuous nature of granular systems. His simulations rely on high-performance computing to simulate the interactions of millions of grains within a particle assemblage as the entire mass undergoes large-strain deformation due to phenomena such as earthquake surface fault rupture and trapdoor displacement. This approach allows us to model phenomena at the near-surface such as liquefaction or larger-scale phenomena such as tectonic deformations. The focus on individual particles elucidates the influence of depositional history and soil fabric on the deformation behavior of soils. This line of research advances understanding of how ground surface deformations can impact infrastructure and ultimately aims to improve the resiliency of infrastructure against geologic hazards.

X-ray tomography scan of an intact naturally deposited shoal sample with individual grains labelled and colorized.

Hardik Patil

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Year
2021-2022

Research Description
An optimization framework and an inverse-design method for using curved crease folding to create desired shapes.

Mentor
Evgeni Filipov, Civil and Environmental Engineering

Min-Chun Han

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Year
2021-2022

Research Description
Numerical modelling of community resilience in the face of natural disasters, including models of entire cities, accounting for individual buildings, bridges, infrastructure systems and people.

Mentor
Sherif El-Tawil, Civil and Environmental Engineering

Seymour M.J. Spence

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Dr. Spence’s main research thrusts are focused on the theoretical and computational development of models and frameworks for the implementation and adoption in practice of performance-based wind engineering, optimization of structural systems subject to uncertainty and experimental/stochastic wind loads, and metamodeling of nonlinear and dynamic structural systems under uncertainty. Specific areas in which Dr. Spence’s research group have made contributions are: performance-based wind engineering, system-level analysis and optimization of uncertain dynamic systems, probabilistic modeling and uncertainty propagation, metamodeling of static and dynamic systems, machine learning in stochastic analysis of structures, resilience and adaptation of communities subject to severe wind events, topology optimization of uncertain stochastic systems, and computational fluid dynamics for wind and rain simulation.

Computational fluid dynamics simulation of wind driven rain in hurricanes

Portrait of Jeremy Bricker

Jeremy Bricker

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Jeremy Bricker is an Associate Professor in the department of Civil and Environmental Engineering. His research is focused on hydraulic engineering to investigate the resilience of structures and infrastructure exposed to both increasing hazard due to climate change and increasing consequences due to expansion of development in coastal and flood-prone areas.

Computational methods are useful in hydraulic engineering for assessing the safety of coastal and hydraulic structures, estimating the flood risk experienced by communities, and predicting damage to buildings during floods, hurricanes, and tsunamis. At a large scale of hundreds to thousands of kilometers, shallow water equation models simulate tsunami propagation, storm surge and wave generation, and river flood occurrence. At scales of kilometers to tens of kilometers, these models resolve overland inundation due to flood events, allowing empirical or analytical estimates of forces on structures and damage to buildings and infrastructure. At a small scale of tens to hundreds of meters, computational fluid dynamics (CFD) directly calculates pressures and forces on submerged and emergent structures from floodwaters and waves. This can be linked with a dynamic response model to assess whether resonance could lead to structural failure, or linked with a Finite Element Method (FEM) model to assess stresses within the structure. Such modeling is useful for forensic analysis of the failure of bridges, buildings, and other infrastructure after floods, as well as for planning and design of new structures.

 

Streamlines around the cross-section of a 3-girder bridge deck submerged by a river flood, from Oudenbroek et al. (2018).

 

 

Yi Zhu

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Year
2020-2021

Research Description
Simulation of multi-physical behavior in active shape morphing micro-origami

Mentor
Evgueni Filipov, Civil and Environmental Engineering

Daeho Kim

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Year
2020-2021

Research Description
Conclusive, predictive, and scalable robotic hazard detection using deep neural networks and synthetic training data.

Mentor
Prof. SangHyun Lee, Civil and Environmental Engineering

Paul Beata

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Graduation Year

2017

Thesis Title

Computational Approaches to Fire-structure Interaction and Real-time Fire Monitoring