Madison, WI (November 19, 2015) - Dr. P. Kelly Senecal, Co-Founder and Vice President of Convergent Science, was awarded the ASME ICE Division Speaker Award for his presentation at the 2014 Internal Combustion Engine Division Fall Technical Conference in Indiana. His presentation was titled Modeling Fuel Spray Vapor Distribution with Large Eddy Simulations of Multiple Realizations. The accompanying paper was co-authored by Eric Pomraning and Saurav Mitra of Convergent Science; Qingluan Xue and Sibendu Som of Argonne National Laboratory; and Siddhartha Banerjee, Bing Hu, Kai Liu, Divakar Rajamohan, and John Deur of Cummins. The award was presented in Houston, Texas, on November 10, 2015.
In 2000 Dr. Senecal won this award, in addition to the award for best paper, for his pioneering work on the use of genetic algorithms and computational fluid dynamics (CFD) in the engine design process.
About Dr. P. Kelly Senecal
Dr. Senecal is a co-founder of Convergent Science and one of the original developers of the CONVERGE CFD code. He is a consultant to the automotive industry, where he works closely with engineers on problems related to internal combustion engine modeling. He is experienced at managing large consulting and software development projects for the private sector.
Dr. Senecal has authored numerous papers in the area of engine modeling. His pioneering research on the use of CFD in the engine design process has been featured in The New York Times and many other media outlets. He is also an author of the widely used LISA (Linearized Instability Sheet Atomization) spray breakup model.
About Convergent Science
Founded in Madison, Wisconsin, Convergent Science is a world leader in computational fluid dynamics (CFD) software. Its flagship product, CONVERGE, includes groundbreaking technology that eliminates the user-defined mesh, fully couples the automated mesh and the solver at runtime, and automatically refines the mesh when and where it is needed. CONVERGE is revolutionizing the CFD industry and shifting the paradigm toward predictive CFD.