Our Team

Dr. Laura Redmond

Dr. Laura Redmond is the head of the Clemson Advanced Structures Laboratory (CASL). She received her PhD in Civil Engineering from Georgia Tech with a focus on seismic performance and design of concrete and masonry structures using finite element modeling validated with full-scale experiments.  She then worked at NASA Jet Propulsion Laboratory (JPL) in the spacecraft structures and dynamics group (352L) specializing in nonlinear finite element modeling, experimental design, and rigid body dynamics.  She was the lead structural engineer for the Mars 2020 sample tubes and hermetic seals which will be used to store Martian rock samples for a possible return mission. She had roles in the SWOT/NISAR missions helping create rigid body dynamics models of the boom arm deployment system, and as a structural analyst for two proposals: a Europa penetrator and Venus lander. In August 2018, Laura joined Clemson University as an Assistant Professor in the Civil Engineering Department.

Current research expertise spans advanced simulations for civil, mechanical, and aerospace applications, model verification, and model validation by test.

PhD Students

MS Students

Undergraduate Students

Previous Students

PhD Students

John Bell

John Bell is a Civil Engineering PhD student at Clemson University. Bell has a BS in Mathematics from North Greenville University and a MS in Civil Engineering from Clemson. When not enjoying his rigorous coursework and research, Bell likes to bike, climb, and hike the great outdoors.

Bell is currently completing dynamic analysis of the Pop-Up Flat Folding Explorer Robot (PUFFER) for interplanetary exploration. NASA’s Jet Propulsion Laboratory created PUFFER to explore hard-to-reach areas of Mars’ and the Moon’s surfaces. Bell is performing dynamic explicit finite element modeling and performing model correlation and validation through modal analysis in the lab. Ultimately, Bell seeks to simulate 80-meter lunar pitfalls to identify and outline structural deficiencies and to recommend necessary design adjustments.

Omar Abuodeh

Omar Abuodeh is a Civil Engineering student pursuing a PhD degree in Clemson University. Omar obtained a B.Sc. degree in Civil and Environmental Engineering from the University of Sharjah (UAE) and a M.Sc degree in Civil Engineering from American University of Sharjah (UAE). His hobbies/interests include jogging, hiking, cooking and playing video games.

Omar’s doctoral work involves numerically modeling a recently emerging structural health monitoring strategy, Drive-by Health Monitoring (DBHM), in a 3D finite element (FE) environment to identify structural damage in bridges. Researchers often conduct these simulations using contact based methods, which yield high fidelity models but are computationally expensive. Omar’s is developing a node-to-node based method that captures the full dynamics of an actual bridge while preserving a simpler dynamic analysis. This model will then be used to train a machine learning model for bridge damage classification in the context of DBHM. Previously, Omar was also involved in research involving structural rehabilitation of concrete members, employing machine catered models to analyze civil engineering problems, and modeling the structural behavior of concrete members in bending applications using FE commercial software.

Stephen Wright

Stephen Wright is a graduate student at Clemson University pursuing a PhD in Civil engineering. He received both his B.S. and M.S. in civil engineering from Clemson University in 2018 and 2020 respectively. Outside of research and coursework, he enjoys biking, listening to music, cooking, and playing in his band.

Stephen is currently conducting research funded through the US Army’s Ground Vehicle Systems Center as a part of a larger project on refinement and improvement of design methods for next generation combat vehicles. Stephen’s area of work for this project is focused on verification and validation of models with lean datasets. This work performing Bayesian inference on models to calibrate design model parameters and eventually proposing a new method of Bayesian inference that is well suited for calibrating model parameters for models with lean datasets.

MS Students

John Crowder

John Crowder is a graduate student pursuing his master’s in civil engineering with an emphasis in structures. While completing his undergraduate degree in civil engineering at Clemson, John enjoyed working on the concrete canoe team and assisting Dr. Redmond’s graduate students in the lab. When not studying or in the lab, John likes to read, eat oreos, and go to concerts.

John’s goal is to increase the impact resistance of small-scale PCB robots for the exploration of high-risk areas on Mars and the Moon. He is using additive manufacturing technologies to cost effectively prove feasibility for other high-performance polymers. While also optimizing using topology and finite element modeling, his hope is to increase the strength-to-weight ratio of robotics, allowing for cheaper space flight in the future.

Hannah Stewart

Hannah joined the research group in August of 2022. She is co-advised by Dr. Chris McMahan (MATH). Her research focuses on the creation of a Bayesian machine learning tool for digital twin assembly that will select the appropriate mixture of subsystem vehicle models that results in sufficient representation of physical test data while minimizing computational costs. Her research is sponsored by Army GVSC.


Undergraduate Students

Previous Students

PhD Graduates

Robert Locke

Robert (Rob) is an associate in the Buildings and Structures Practice at Exponent. He graduated in May 2021.

Rob’s dissertation focused on developing a mobile health monitoring strategy that utilizes vehicle mounted accelerometers to gather dynamic response features that can be used to continuously evaluate the health of bridge infrastructure networks in a more efficient, cost effective, and less labor-intensive manner than traditional structural health monitoring or visual inspection practices. This Drive-by Health Monitoring approach, as it has been called, relies on training an artificial neural network or Bayesian models to detect damage on realistic vehicle-bridge finite element models (FEMs), and then applies the trained network towards detecting similar damage on physical systems. For simulation trained neural networks to detect physical bridge damage, numerical models must be able to accurately represent the dynamic behavior of a vehicle-bridge system when healthy or damaged. To ensure the vehicle-bridge simulations accurately capture the behavior of physical systems, focus has been placed on identifying methods for incorporating environmental and operational variabilities, such as surface roughness and temperature effects, into simplified FEMs.

MS Graduates

Rumi Shrestha

Rumi is an associate at Walter P. Moore. She graduated in December 2021.

Rumi’s thesis was funded by NCMA (National Concrete Masonry Association) and derived lambda factors for lightweight grout by carrying out development length, anchor bolt, modulus of rupture and shear strength tests to characterize the difference in the performance of light weight grouts in comparison to normal weight grouts. The experimental portion of the project comprised of carrying out mix designs for two different lightweight aggregates and designing test setups for the aforementioned tests. The project aimed to pave a way for developing a codified procedure that can encourage widespread use of lightweight aggregates for grout.

Hannah Kessler

Hannah graduated in August of 2021. She went on to pursue her PhD at Georgia Institute of Technology.

Hannah’s thesis focused on buckling-restrained braces (BRBs) for precast frames. BRB frames are a highly ductile lateral force resisting system that is becoming increasingly popular in high seismic zones in the United States and around the world. Although the precast concrete industry does not currently use this system, the Precast/Prestressed Concrete Institute has funded Hannah’s work to investigate the connection behavior between precast concrete frames and BRBs as an initial step towards use of BRBs in precast structures.

Undergraduate Students

Paul Gennett

Paul Gennett graduated in May 2020 and went on to work for Kimley-Horn.

Paul assisted Dr. Redmond and several graduate students on various ongoing projects. In Spring 2020, Paul worked mostly with John and his dynamic analysis of the PUFFER rover. He also helped Rumi her lightweight grout experimentation.