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Ali Behbahani

PhD Candidate
University of Tennessee Knoxville

Ali Behbahani is a Ph.D. candidate at the University of Tennessee, Knoxville, specializing in computational solid mechanics and data-driven modeling for Additive Manufacturing. His research focuses on developing high-fidelity, predictive "digital twins" for metal AM. He builds advanced thermo-mechanical models to simulate the LPBF process, predicting how process parameters and residual stresses influence part-scale performance and failure. He integrates these physics-based models with machine learning to accelerate the design and certification of AM components.

Ali also has a strong background in auxetic meta-materials, stemming from his master's research, where he led the experimental and numerical study of auxetic foams. This work included tensile testing to extract their mechanical properties and analyze their unique behavior. He is currently applying this expertise to the design of novel metallic auxetic structures for fabrication via AM, targeting high-performance energy absorption. His work has been applied to critical sectors, including orthopaedic biomechanics, where he has modeled the performance of TKA implants and dental crowns.

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