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Research
"Nothing is harder to surmount than a corpus of true but too special knowledge; to reforge the tradition of his forebears is the greatest originality a man can have."
Clifford Truesdell
Research Philosophy and Interests
The problem of describing motion and forces in solids has fascinated humans since the dawn of civilization. Over many centuries, this field called Mechanics has tremendously advanced through multiple paradigm shifts, from purely experimental investigations before Rennaisance to analytical equations as the primary tools up to the 1950s, followed by the era of computational mechanics and, most recently, the paradigm of data-driven methods. Each new paradigm brought new methods and tools to advance our knowledge further of mechanics. Our laboratory focuses on utilizing these four paradigms of mechanics: experimental mechanics, anaytical mechanics, computational mechanics, and data-driven mechanics, to develop novel approaches and tools to understand the mechanics of soft materials for targeted applications.
Our research utilizes and develops the following methods and tools:
Experimental: Environment-controlled quasi-static and high strain rate Kolsky-bar mechanical testing. Our experimental setups include novel test fixtures, high-speed imaging, full-field deformation mapping tools (e.g., Digital Image Correlation (DIC)), and environment-control systems.
Analytical: Hyperelasticity; finite viscoelasticity; damage mechanics.
Computational: Finite element method; Material point method.
Data-driven: Surrogate modeling (including data-driven constitutive models); Bayesian experimental design and parameter estimation; Uncertainty quantification and sensitivity analysis.
Active Research Projects
Extreme Mechanics of the Human Brain via Integrated In vivo - Ex vivo Experiments
(A collaborative project with Dr. Curtis Johnson (University of Delaware) and Dr. Michael Shields (Johns Hopkins University))
Funding Agency:
The National Science Foundation (NSF)
Student researchers:
Siddarth Sriram, Nihar Moghe and Carson Cooper
Description:
The primary objective of this project is to understand the high strain rate mechanics of the living human brain. As direct experiments that may risk human safety are ethically impossible, a uniquely coupled multi-fidelity experimental–modeling framework that combines information from in vivo and ex vivo tests is being developed to discover mechanical property maps of the living brain.
Artificial Intelligence–Based Automated Neural Cell Phenotype Identification
Funding Agency:
Student researchers:
Description:
The Office of Naval Research (ONR)
S. M. A Anam Shovon
The primary objective of this research is to develop a framework for rapidly identifying different neural cell types in 3D polyculture systems from confocal micrographs, contributing to the next-generation of high-throughput in-vitro TBI studies.
3D-printable regolith-shape memory polymer composites
for long-term lunar habitats
Funding Agency:
Researchers:
Description:
National Aeronautics and Space Administration (NASA)
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Motivated by NASA’s goal of long-term space exploration, this research addresses the need for durable, lightweight materials for constructing lunar habitats using in-situ resources. The primary objective is to develop a 3D printable regolith-polymer composite, enhancing thermal stability and mechanical performance for extreme lunar environments while contributing to NASA’s space-resilient structure initiatives.
Machine Learning–Guided Exploration and Optimization of the Fracture Resistance of Additively-Manufactured Shape Memory Polymers
Funding Agency:
Student researchers:
Louisiana Board of Regents (LABoR) and NSF
Yogesh Chandrashekar
Description:
The primary objective of this project
is to understand the effect of additive manufacturing on the fracture resistance of thermoset SMPs (or TSMPs), and to develop guidelines for optimizing their fracture resistance.
Damage Mechanics of Tendon
Funding Agency:
Student researchers:
LSU
Yogesh Chandrashekar
Description:
The primary objective of this research is to develop constitutive models to capture the rate-dependent damage in tendons under large deformations.
Personalized mTBI digital twins for American Football athletes
Funding Agency:
Student researchers:
Description:
LSU and Our Lady of the Lake Health (OLOL)
Carson Cooper
This research is motivated by growing concerns about the long-term cognitive effects of football-related concussions and seeks to address the gap between impact sensing and brain injury prediction. The main objective is to develop digital twins of football athletes to improve real-time concussion risk assessment.
Entropy-based prediction of the remaining fatigue life of soft materials
Funding Agency:
Student researchers:
Description:
NSF-REU
Braden Hebert and Cody Hurst
The primary objective of this project is to evaluate entropy-based strain rate–dependent fatigue life prediction of networked polymers such as elastomers and hydrogels.
Funding Support
We are grateful for funding support from the following agencies.
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