Aircraft engine

Argonne National Lab Offers Supercomputing Time to Boost Manufacturing Efficiencies

May 11, 2021
Companies can apply for dedicated supercomputing time and assistance in addressing manufacturing and materials development problems.

Supercomputers hold the potential to quickly solve large, complex problems. But the cost of owning one is prohibitive and using them requires a comprehensive knowledge of advanced modeling and simulation techniques.

To make the power of supercomputers accessible to companies, the U.S. Department of Energy (DOE) is giving some U.S. companies access to its world-class computing resources and technical expertise through High Performance Computing for Energy Innovation (HPC4EI), a program that uses high-performance computing (HPC) to solve development problems.

The program focuses on manufacturing (HPC4Mfg) and materials (HPC4Mtls). Companies interested in the program can apply for up to $300,000 in funding, generally twice per year. Companies accepted in the program can suggest a national laboratory as a partner, or DOE officials may match companies with a national lab. The companies then enter a collaborative agreement with the laboratory that protects its rights to generated data and new intellectual property.

The HPC4EI program is best for companies with energy-focused projects that could benefit from having access to HPC resources. Projects that involve substantial energy savings for the company or the end-user, or that support development of new clean-energy technologies, are favored.

Some of the HPC4EI projects that have been concluded at Argonne National Lab have tackled:

Reducing harmful emissions in diesel engines. Argonne worked with Caterpillar Inc. to improve efficiency and reduce emissions in heavy-duty diesel engines. The team ran hundreds of high-fidelity combustion simulations to identify designs for the combustion chambers in diesel engines that could improve fuel efficiency while reducing emissions.

Designing a more efficient aircraft engine. Raytheon Technologies Research Center is working with Argonne to use HPC and machine learning to create models that accurately predict air flow and heat transfer inside a gas turbine engine, identifying fine-scale surface effects that could not have been discovered with physical experiments alone. These simulations will let Raytheon modify their manufacturing process to minimize heat loss and maximize engine component durability.

Manufacturing defect-free steel. ArcelorMittal Global Research and Development worked with Argonne to develop energy-efficient methods for manufacturing defect-free steel slabs. The project lowered ArcelorMittal’s energy use for some of the largest steel mill in North America, at the same time letting the company turn out higher-quality cast steel while lowering its greenhouse gas emissions.

Optimizing manufacturing processes. 3M turned to Argonne for help in leveraging machine learning and computational fluid dynamics to improve a fiber spinning process used in making filters, fabrics and insulation. The collaborative effort reduced the amount of energy used in making these materials.

Companies interested in working with Argonne should contact it via email.

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