Argonne, Convergent and Cummins cooperate to discover the secrets of fuel injectors

Argonne, Ill. – In the swirling, churning fireball at the heart of every internal combustion engine, complexity reigns supreme.

Valves and pistons lunge up and down at thousands of feet per second, pressure spikes to peak levels in an instant and sprays of fuel spread throughout the maelstrom in impossibly intricate patterns.

That complexity is a daunting task for anyone trying to understand the interacting forces at work in an engine. But a team of researchers at the U.S. Department of Energy’s (DOE) Argonne National Laboratory has stepped up to the challenge by creating integrated modeling of one key element of that mechanical mayhem: the fluid dynamics of fuel injectors in modern engines.

Partnering with industry leaders Cummins, Inc., and Convergent Science, Inc. (CSI), and using the unique facilities and massive computing resources available at Argonne, the team hopes to take one step closer to the Holy Grail of engine design: cleaner and more efficient engines simulated, designed and optimized in virtual space before production ever begins.

“Fuel injection is the first step toward the type of simulation we want to do someday,” said Sibendu Som, principal investigator and principal mechanical engineer at Argonne’s Center for Transportation Research. “It’s like running a marathon. It’s a long race, and you have to train for it over time, taking it piece by piece.”

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About Convergent Science

Founded in 1997 in Madison, Wisconsin, Convergent Science is a global leader in computational fluid dynamics (CFD) software. Its customers include leading automotive and commercial vehicle manufacturers, tier one suppliers, and professional motorsport teams.
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 towards predictive CFD.