Release Date: May 29, 2013
Modeling Through Shared Resources, No High-Fashion Experience Required
Modeling—the computer kind, not the runway kind—can help researchers predict particle movement, enabling improvements in the design of components used in energy production. To give graduate students experience modeling these systems, the National Energy Technology Laboratory (NETL) has placed several high-performance computer clusters at Oregon State University.
Oregon State professor Sourabh Apte and his graduate students use the computer clusters to work with NETL scientists on U.S. Department of Energy (DOE)-funded projects to develop models for fashioning new energy technologies. Models of particle movement developed by Dr. Apte’s group can help predict how movement of small particles in a fluid affects the fluid’s structure and changes the movement of the fluid. These techniques can also predict such things as beach erosion in populated areas, movement of pollutants in a stream, or how new ship-propeller designs could dampen noise by getting rid of the bubbles generated during rotation.
Former Oregon State doctoral candidates Mathew Cleveland and Andrew Cihonski were able to develop and test models and algorithms on the computer clusters before shipping the programs off to supercomputers such as Lonestar at the Texas Advanced Computing Center at the University of Texas, Austin. Access to the high-performance computer clusters, close to home, helped Cleveland and Cihonski complete their degrees, and both have now begun their careers at DOE national labs after publishing their work. Although the newly minted Ph.D.’s didn’t get to spend time on the catwalk, their simulations help develop approaches to retrofit power plants to increase their efficiency and capability for carbon capture.
Future use of the computer clusters promises access to more computational tools for current and future Oregon State students—nurturing their educational growth, heading them in the right direction for successful job placement, and training the next generation of American scientists.