Computational Transport phenomena laboratory
Welcome to the Computational Transport Phenomena Laboratory. Our research in the areas of transport phenomena encompasses physical, analytical, and numerical modeling. We currently focus on the modeling and simulation of turbulent reacting flows, particle formation and growth dynamics, multi-scale modeling, and multi-phase heat, mass and momentum interactions. In these endeavors our goal is two-fold: (1) To utilize the latest mathematical and numerical tools to investigate and elucidate the underlying physico-chemical processes, and (2) to develop models and numerical algorithms which accurately represent the phenomena in a computationally-affordable manner, facilitating their use in solving problems of interest to industry and society.
Research and Education in CTPL
A large number of our simulations are performed at the Minnesota Supercomputing Institute (MSI). The MSI provides supercomputing resources and user support to University of Minnesota researchers. This includes all aspects of high-performance computing and scientific modeling and simulation as well as graphics, visualization, and high-performance network communications. Additionally, CTPL has a number of workstations and software solutions to perform state-of-the-art data visualization and analysis
The Computational Transport Phenomena Laboratory is an environment populated by Undergraduate, Masters, PhD students as well as Post-doctoral scientists. The Lab is continually looking for motivated undergraduate and graduate students who are interested in performing research at a high-level. If interested, please make all inquiries to Professor Garrick.
One current area of focus is energy production (both fossil-fuel based and renewable). 
The United States has the largest proven coal reserves in the world - some 245,000 million tons, enough to meet the world’s energy needs for 15 years. However, emissions from coal-fired power-plants is the largest anthropogenic source of mercury released to the air. CTPL researchers are currently developing computational tools to predict the amount of mercury removed using virtual sorbent beds and electro-static precipitators. This work enables scientists and engineers to design better "retrofit" solutions and, more importantly, design the next generation technologies to be used in the United States and throughout the world.