Recent and ongoing research projects
Our group develops numerical methods and data-driven approaches
for the prediction and optimization of "messy turbulent flows"
relevant to energy and the environment (often multiphase and
reacting). A large emphasis is on computational methods for disperse
two-phase flows (solid particles suspended in a carrier phase,
liquid droplets in gas, or gaseous bubbles in liquid). A main focus
of our research involves developing robust and scalable numerical
tools to investigate the multiphysics/multiscale phenomena on
world-class supercomputing resources. 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), 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
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)