Recent and ongoing research projects
Our research is broadly under the realm of fluid mechanics, with an emphasis on multiphase flow, turbulence, reacting flows, and high-performance computing. We develop robust and scalable numerical tools to investigate multiphysics/multiscale phenomena on world-class supercomputers. Applications include renewable energy, propulsion, disease transmission, and space exploration. We thank our current and past sponsors: Office of Naval Research (ONR), Air Force Research Lab (AFRL), National Aeronautics and Space Administration (NASA), National Science Foundation (NSF), National Renewable Energy Lab (NREL), Ford Motor Company, and Link Engineering.

Below is a list of recent and ongoing research projects. A detailed description of research areas by topic can be found here.


Simulation and modeling of airborne disease transmission


Fluid dynamics controls the transmission of airborne viruses (such as COVID-19). In this project, direct numerical simulations of realistic expiratory events are performed to understand and model particle dispersion. We are also leveraging unsteady RANS with the aim of improving 'well-mixed' models commonly employed for analyzing risk associated with transmission in indoor settings.

Funded by University of Michigan (CoE, 2020-2021), NSF (CBET, Fluid Dynamics: 2021-2023)
Multi-Scale Modeling of Plume-Surface Interactions


The success of future lunar and planetary exploration missions will require predictive simulation tools that capture the complex multiphase dynamics associated with rocket exhaust impingement during touchdown. The objective of this project is to develop advanced physics-based models and numerical algorithms to enable predictive simulations of plume-surface interactions under relevant landing conditions.

Funded by NASA (NSTRF: 2016-2020, SBIR: 2019, CIF: 2017-2020, ESI: 2020-2023)
High-Fidelity Modeling of Particulate Transport and Deposition in Gas Turbine Engines


The ingestion of fine particulates in gas turbine engines represents a key outstanding challenge facing military operations in the 21st century. Exposure to sand, volcanic ash, and dust compromises the durability, performance, and safety of engine turbine components. The objective of this project is to develop the predictive modeling capabilities needed to understand and eventually mitigate erosion by particulate deposition in extreme conditions relevant to next-generation aircraft engines. This will be accomplished through a combination of high-fidelity modeling and uncertainty quantification.

Funded by ONR (YIP: 2019-2022)
Understanding and Modeling Turbulent Reacting Particle-Laden Flows

From the production of biofuels to post-combustion carbon capture, multiphase reactors are at the heart of nearly all energy processes. A lack of understanding how turbulent mixing interacts with the kinetics, mass transfer, and heat transfer across scales has prevented new environmentally acceptable, energy efficient technologies from having real-world impact. The aim of this project is to improve the fundamental understanding of turbulent reacting particle-laden flows, and enable accurate, physics-based models that remain predictive across varying flow regimes.

Funded by NSF (CBET, Particulate & Multiphase Processes: 2019-2024, CBET, Thermal Transport Processes: 2019-2021)
Adjoint-Based Optimization of Combustion Systems


The goal of this effort is to establish a systematic approach that combines experimental measurements with first principle-based simulations to (i) provide flow quantities at resolutions beyond what is capable to measure by experiments or simulations alone; (ii) gain new insight into physical processes that can assist in model development; and (iii) inform optimal experimental design decisions (e.g., what to measure and where). New adjoint-based methods are being developed for sensitivity and optimization of turbulent combustion. These methods are being applied to shear coaxial jets that mimic AFRL’s burner configuration to optimize flame characteristics and develop reduced-order models.

Funded by AFRL (subcontract: 2019-2020), DOE (XPACC subcontract: 2016-2019)
Conveying Principles of Fluid Mechanics Through Dance


Kármán Vortex Street is a unique interdisciplinary collaboration in which principles of fluid mechanics are transformed into a dance. Topics in ME 320 (Introduction to Fluid Mechanics) are typically introduced through derivations from first principles. However, fluid mechanics is extremely visual, and the solution to classical fluid mechanics problems are highly aesthetic. Here, dance is used to demonstrate the motion of fluids that the mathematics describes through a physics-constrained dance improvisation.

Sponsored by: University Musical Society, Arts Engine, and Michigan Engineering