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Caterpillar, Argonne and Convergent Science Enter into Cooperative Research and Development Agreement (CRADA)

ArgonneNLARGONNE, Ill ― Internal combustion engines are poised for dramatic breakthroughs in improving efficiency with lower emissions, thanks in part to low-temperature combustion regimes. Such regimes show great efficiency and emissions potential, but they present optimization and control challenges that must be addressed before they enter the engine mainstream.

Caterpillar Inc. (Cat), Peoria, Ill., recognizing that we are entering an age of high-fidelity engine modeling, turned to U.S. Department of Energy’s Argonne National Laboratory and its Virtual Engine Research Institute and Fuels Initiative (VERIFI), where experts are developing new engine combustion models that incorporate accurate descriptions of two-phase flows, chemistry, transport phenomena and device geometries to provide predictive simulations of engine and fuel performance. Cat and Argonne have entered into a Cooperative Research and Development Agreement (CRADA) along with Convergent Science, Inc., Madison, Wis., to further explore ways to predict how things work in diesel engine performance and emissions before any experimental work is conducted. This is the first such CRADA undertaken by VERIFI since its inception this spring.

Read more @ Caterpillar, Argonne undertake cooperative virtual engine design, control project


About Convergent Science

Headquartered in Madison, Wisconsin, Convergent Science is a global leader in computational fluid dynamics (CFD) software. Our mission is to enable our customers to perform revolutionary CFD simulations by creating accurate, versatile, user-friendly software and providing unparalleled support.
Our flagship product, CONVERGE, is an innovative CFD software that eliminates the grid generation bottleneck through autonomous meshing. With a suite of advanced physical models, fully coupled detailed chemistry, and the ability to easily accommodate moving geometries, CONVERGE is transforming the CFD industry and shifting the paradigm toward predictive simulations.
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Published July 1, 2014