Six projects to improve energy efficiency and productivity in the manufacturing sector 

High-performance computing

The U.S. Department of Energy (DOE) announced a $1.8 million investment for six teams. Which will leverage U.S. National Laboratories’ high-performance computing (HPC) resources to help manufacturers streamline their processes, increase their productivity and reduce their carbon footprint. 


High-Performance Computing for Manufacturing

As part of the High-Performance Computing for Manufacturing (HPC4Mfg) program, the selected teams will harness the raw processing power of the world’s most powerful supercomputers – and the lab experts who operate them – to tackle today’s most demanding manufacturing challenges and move country closer to a clean and equitable energy future for all Americans.

High-performance computing enables researchers to conduct virtual experiments by applying advanced modeling, simulation, and data analysis to manufacturing processes. Running these experiments on supercomputers instead of in the real world allows manufacturers to test new ideas while saving energy, time, and resources.

The six selected projects will use the National Labs’ supercomputers to optimize processes and end products across the manufacturing sector, from increasing the energy efficiency of steel manufacturing to improving the manufacturing process for electric vehicle batteries.  

DOE has selected the following projects:
M2X Energy Inc.: 

M2X Energy Inc. is working to mitigate methane and carbon dioxide emissions by replacing gas flares with systems that manufacture economically viable, low-carbon chemicals. With Argonne National Laboratory’s HPC capabilities, M2X Energy Inc. will optimize engine design for methane-to-syngas reforming, resulting in a reduction of greenhouse gas emissions and energy consumption from the global oil and gas sector by 43 million metric tons per year.

Solar Turbines Inc.: 

Solar Turbines Incorporated will use HPC expertise from Oak Ridge National Laboratory to employ crystal plasticity finite element (CPFE) modeling to quantify the factors determining surface fatigue behavior in additive manufacturing. This could reduce CO2 emissions by up to 376 million tons per year.

Danieli USA:

Steel manufacturing currently accounts for 8% of global carbon emissions. Danieli USA will collaborate with the National Renewable Energy Laboratory. To develop computational simulation models of direct reduction iron (DRI) and H2DRI melting processes for industrial use. Accelerating the adoption of low-carbon steelmaking. This could help reduce CO2 emissions by up to 32 million tons annually.

Allegheny Technologies Inc.: 

The manufacture of near-net shape mill products used in aerospace, automotive, and other industries has the potential to reduce both energy use and associated CO2 emissions significantly. Allegheny Technologies Incorporated and Lawrence Livermore National Laboratory will collaborate to manufacture HPC-based digital twins for sustainable metallurgy. That could reduce material waste from the manufacturing process by 50% and CO2 emissions by 564 tons annually.


Phase change composite materials (C-PCMs) play a crucial role in industrial energy and storage applications. To drive efficiency improvements, thermal energy management, and carbon emission reductions. Siemens and Oak Ridge National Laboratory will use HPC to enable high-resolution C-PCM microstructure modeling to design better waste heat capture materials.

Ford Motor Company: 

An efficient battery manufacturing process is vital to the mass production of electric vehicles. And drying is one of the most energy-intensive steps. Ford Motor Company will leverage Sandia National Laboratory’s expertise to optimize battery drying. By developing a high-fidelity model for solvent evaporation and transport during drying in a porous electrode structure. This will reduce energy consumption during battery manufacturing and could reduce CO2 emissions by 10 million tons annually.


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