McKinsey & Company
Joshua graduated from Duke University in May 2016, earning a PhD in Mechanical Engineering and Material Science.
As a high school student growing up in Maine, Joshua developed a keen interest in mathematics. His early tenure on the Maine All-Star Math team exposed him to the world of problem solving, which ultimately encouraged him to pursue an engineering education at the University of Maine, graduating in 2010 with a B.S. in Mechanical Engineering and a minor in Mathematics minor. During these early New England years, Joshua had two engineering internships: one researching Magneto-Rheological fluid dynamics and the other working with the DoD’s Atmospheric Diving Suit team at Portsmouth Naval Shipyard.
Ultimately deciding to further his education, Joshua moved to Durham, North Carolina, where he was accepted into the PhD program at Duke University. In 2013, Joshua received his M.S. degree in Mechanical Engineering at Duke under adviser Dr. Lawrie Virgin. The thesis involved the application of analytical and experimental nonlinear dynamics, and specifically investigated the initial condition sensitivity of nonlinear structural systems exhibiting dynamic snap-through buckling.
For his PhD research, Joshua studied turbomachinery aeroelasticity under the advisement of Dr. Robert Kielb at Duke University. In 2013, Joshua was one of 188 scholars awarded the NDSEG fellowship, which funded his research on jet engines and power turbines. His collaborations with industry and the DoD targeted various high-impact issues surrounding jet engine aeromechanics, with an emphasis on low-pressure turbine flutter and the improvement of preliminary CFD predictive capabilities.
Outside of research, Joshua enjoys being active in many recreational sport leagues including basketball, soccer, football, and softball. He has an eclectic range of interests that include golf, skiing, Scuba, poker, and other games of strategy.
Graduate Research Topics
- Sensitivities to Initial Conditions of a Dynamic Snap-Through Buckling Structure
- A nonlinear, dynamic snap-through buckling apparatus was constructed. Its vast bifurcation tendencies were explored experimentally and numerically, basins of attractions were created, and pathological behavior was identified and validated via numerical modeling.
- Flutter Sensitivities in Low-Pressure Turbines
- Successful, efficient turbine design requires a thorough understanding of the underlying physical phenomena such as the flutter phenomenon found in the low pressure turbine (LPT) blades of aircraft engines and power turbines. The beginning stages of this research will involve CFD analyses of a publicly available LPT airfoil geometry (EPFL's Standard Configuration 4) using a frequency domain RANS solver. Flutter sensitivity analyses are conducted on three key parameters: reduced frequency, mode shape, and Mach number. Additionally, exact two-dimensional acoustic resonance inter-blade phase angles (IBPAs) are analytically predicted as a function of reduced frequency. Studies of the decay of unsteady aerodynamic influence coefficients away from a reference blade are also of current interest as they provide key insights into the harmonic content of the unsteady pressure field.
- Acoustic-Induced Flutter
- A recent finding is that flutter will occur when the acoustic pressure field associated with blade vibration is simultaneously cut-on upstream and cut-off downstream of the rotor. To solve this problem, the computational fluid dynamics (CFD) grid can be expanded to include an upstream inlet, which will allow the CFD to "see" the acoustic effects. The end goal in this research is to develop better knowledge of controlling design variables and to characterize advanced design criteria.
- Coupled Row Flutter
- Experimental and analytical flutter predictions are not matching well in low-pressure turbines (LPT) among other turbomachinery components. Most existing LPT studies model single stage aerodynamics. However, multistage interaction can greatly affect aerodynamic loads acting on a given blade row. Therefore, by implementing a coupled-row analysis, its effect on the flutter boundary can be quantified and used to create flutter prevention design guidelines.