New HPC4EI project to create 'digital twin' models for aerospace manufacturing
A partnership involving LLNL aimed at developing “digital twins” for producing aerospace components is one of six new projects funded under the HPC for Energy Innovation (HPC4EI) initiative, the Department of Energy’s Office of Energy Efficiency and Renewable Energy announced. Sponsored by the HPC4Manufacturing (HPC4Mfg) Program, one of the pillars of HPC4EI, the collaboration between LLNL and specialty materials producer Allegheny Technologies Incorporated (ATI) will leverage advanced HPC software to create a digital twin of the near-net shape mill-products (NNS-MP) system—a strategy in which components are initially fabricated to be as close to the finished product as possible. The project will address reducing energy usage and CO2 production in aircraft manufacturing, where about 95% of metal used in the process is converted to scrap due to the complex shape of components. For the collaboration with ATI, led at LLNL by co-principal investigators Aaron Fisher and Vic Castillo, researchers will simulate the multiphysics problem of multi-stand bar-shaped rolling and produce a machine learning model. The model will act as a digital object for a digital twin of the NNS-MP system, helping to optimize the process for manufacturing aerospace components. Read more at LLNL News.