Dr. Tootkaboni researches integrating advances in stochastic modeling, applied statistics, and data analytics with methods of applied and computational mechanics to develop techniques that help the structural mechanics community move toward more reliable, resource-efficient, and resilient solutions.
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Dr. Tootkaboni’s cross-disciplinary research mainly focuses on integrating advances in stochastic modeling, applied statistics, and data analytics with methods of applied and computational mechanics to develop techniques that help the structural mechanics community move toward more reliable, resource-efficient, and resilient solutions.
These techniques are highly relevant in devising risk- and uncertainty-conscious design and analysis frameworks and have a wide range of applications, from the study of instability and collapse behavior in stability-critical structures and multi-scale modeling of materials to robust (uncertainty-informed) topology optimization and the study of dynamics of structure-equipment interactions.
Dr. Tootkaboni is a recipient of the NSF early CAREER award in 2014, an associate member of ASCE, a member of the Engineering Mechanics Institute (EMI) and an active member of EMI's Probabilistic Mechanics Committee. In addition to his CAREER grant on predictive analysis of stability critical structures, Dr. Tootkaboni has secured multiple federal and state grants including a $215,000 NSF grant for developing a probabilistic paradigm for advancing analysis-based design of thin-walled structures and a $188,000 NSF grant for developing geometric flaw-tolerant optimal structures and material microarchitectures.
He received another $368,000 in funding from NSF for devising a comprehensive computational framework for analysis and optimization of wave energy converters, in which Dr. Tootkaboni serves as co-PI and Dr. Raessi of Mechanical Engineering is the PI. Dr. Tootkaboni’s research on rain-induced erosion in composite wind turbine blades is funded by UMass President’s Science and Technology Initiative.