Michael is a Ph.D. student in the Mechanical Engineering and Materials Science department at Duke University. Under the advisement of Dr. Earl Dowell, Michael is currently researching the nonlinear dynamics of turbulence. His first years at Duke have been funded through the National Science Foundation Graduate Research Fellowship Program (NSF GRFP).
Michael’s research in turbulence focuses on reduced-order modeling (ROM), applying in particular the proper orthogonal decomposition (POD) framework. The immediate goal is to identify the extrapolative potential of ROMs such that trends in turbulent dynamics – currently as functions of Reynolds number – can be identified from a mathematically robust perspective (i.e. POD). Future work may involve compressible flow dynamics, novel model-order reduction methods, and the development of computational methods for implementing these and other analytical strategies to more complex problems.
Michael received his B.Sc. in Aeronautical Engineering with a minor in philosophy from Clarkson University in 2016. While at Clarkson, Michael interned at GE Aviation for one semester and NASA Langley Research Center for one summer. His work at GE involved low-cycle fatigue analyses of critical rotating parts in long-haul engine cycles. While at Langley, Michael worked on the implementation of a detached-eddy simulation analytical framework for the Space Launch System at liftoff. His research at Clarkson, which culminated in his Honors Thesis, involved the development of a novel nonplanar wing design strategy inspired by the cambered wings of cruising birds like the albatross.
When he is not researching, Michael enjoys playing and developing board games, ballroom and tap dance, creative writing, and singing and playing piano. Michael has studied traditional karate in the style of Washin-Ryu since 1999.
Graduate Research Topics
An investigation to develop a model-order reduction strategy robust enough to be applied accurately to turbulent flow regimes outside of the data set used to generate the model.
Development of ROM methods in the context of a canonical flow regime.