The U.S. Department of Energy (DOE) announced a $2.3 million investment for eight teams who will tap into the U.S. National Laboratories’ high performance computing (HPC) resources to help manufacturers streamline their processes, increase their productivity, and lower their carbon footprint. As part of this High Performance Computing for Manufacturing (HPC4Mfg) program, DOE will match selected teams with the world’s most powerful supercomputers, and the lab experts who operate them, to solve complex challenges in manufacturing and increase energy efficiency across the sector.

“DOE’s investment in the HPC4Mfg program helps manufacturers harness the raw processing power of high performance computing to bring their emissions down and improve their efficiency,” said Acting Director for the Advanced Manufacturing Office Dr. Becca Jones-Albertus. “These projects will provide manufacturers with the information they need to make their processes operate smarter and cleaner – a crucial step on the path toward achieving our clean energy economy.”

High performance computing enables researchers to perform virtual experiments by applying advanced modeling, simulation, and data analysis to manufacturing processes. Running these experiments on supercomputers provides more accurate and expansive data to help manufacturers achieve optimal results, test new ideas, and save energy, time, and resources.

The selected projects will use the National Labs’ supercomputers to optimize processes and end-use products across the manufacturing sector, from increasing the energy efficiency of steelmaking to reducing the weight of vehicle components to save fuel and reduce emissions.

View a full list of selected projects here.

HPC4Mfg is funded by the Office of Energy Efficiency and Renewable Energy’s Advanced Manufacturing Office and is a subprogram of the High Performance Computing for Energy Innovation (HPC4EI) initiative. HPC4EI is managed by Lawrence Livermore National Laboratory (LLNL). Visit the HPC4EI website for additional information.