LEMONT, Ill.–(BUSINESS WIRE)–For the past six years, researchers at the U.S. Department of Energy’s (DOE) Argonne National laboratory have collaborated with Cummins, an engine design and manufacturing company, and Convergent Science, Inc., a software developer, to create predictive engine simulations using the high-performance computing tools at the laboratory. Now, they’re extending their partnership for three more years, and adding new collaborators and capabilities to further speed the research.
Under a new Cooperative Research and Development Agreement (CRADA), the three organizations, along with DOE’s Sandia National Laboratories, will work together to build more accurate fuel spray models and integrate them into full engine simulations. This effort will build on the fuel spray and combustion modeling work the three organizations have done over the past six years, which Cummins has adopted in its own internal workflow.
Addressing the weak link between injector and fuel spray models
Traditional modeling approaches don’t accurately represent the formation of a fuel spray as it emerges from the nozzle of an injector. But what happens in this region determines how the fuel is distributed further downstream.
In their renewed partnership, Argonne and its collaborators will develop a way to more accurately represent the near-nozzle region by dynamically coupling models that detail internal flow and spray formation using machine learning, a form of artificial intelligence.
Their advanced approach builds on existing methods for modeling fuel sprays, but will require fewer assumptions about how fuel jets form and could therefore yield a more predictive engine modeling tool.
Such a tool would enable manufacturers like Cummins to better understand how fuel and hardware choices impact engine performance and emissions. For engine makers focused on decarbonizing transportation using alternative fuels, this tool can help them make informed decisions on fuel choice and its impacts on injector and engine performance.
X-ray and laser diagnostics will also be used to add more knowledge to injector and fuel spray models and to validate the team’s dynamic coupling approach. Once proven, Convergent Science, which developed a widely used platform for engine modeling, can implement the technology into their code, where Cummins and other engine manufacturers can leverage it.
“The enhanced modeling capability developed in this CRADA will give industry the tools it needs to design cleaner and more efficient engines,” says Kelly Senecal, co-founder of Convergent Science.
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Christopher J. Kramer
Head of Media Relations
Argonne National Laboratory