by Kate Caponi

When you watch from the ground as an airplane take off, the process looks smooth. If you were riding in that plane, you would see and feel vibrations in the wings and body, a physical inkling of some of the forces working for and against the aircraft as it leaves the earth's surface. These forces reflect the influence of the air making its complicated path around the moving airplane. If you could see the actual airflow, you'd notice millions of little eddies--like tiny tornadoes--skimming the metal and affecting the drag and smoothness of the ride.

The need to predict the forces at play drives turbulent fluid motion studies. Numerical computation of how fluids move around the surface of given objects is crucial to the analysis and design of airplanes, automobiles, engines, computer chips, submarines, and many other technologies. In recent years, design teams in government and industry have invested millions of dollars in software capable of solving practical flow problems.

However, traditional models of turbulent fluid flow are unreliable and can be costly to implement. New capabilities in the prediction of turbulent fluid flow are needed if the full potential of computational fluid dynamics is to be exploited. Peter Bernard, professor of mechanical engineering at the University of Maryland, College Park, and a team of researchers from the company VorCat, Inc., have used more than 60,000 hours on the University of Kentucky's HP Superdome, NCSA's Titan Linux cluster, and Boston University's IBM P-Series supercomputer to develop advanced, grid-free techniques in modeling turbulent flow.

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Access Online | Posted 9-8-2004