The US Department of Energy (DOE) is awarding $3.6 million to 12 projects under its High Performance Computing for Energy Innovation (HPC4EI) initiative. Selected projects will receive access to the National Laboratories’ high-performance computing (HPC) facilities and expertise to help address key challenges in US manufacturing, material, and mobility development.
HPC4EI is the umbrella program for DOE’s HPC for Manufacturing, HPC for Materials, and HPC for Mobility initiatives.
DOE maintains world-class HPC expertise and facilities, currently hosting seven of the top 12 most powerful computers in the world. From detailed atomic-level simulations to massive cosmological studies, researchers use HPC to probe science and technology questions inaccessible by other experimental methods. Successful applicants will work collaboratively with the DOE National Laboratories to conduct project activities across the various HPC areas of expertise. Selected projects include:
HPC for Manufacturing
United Technologies Research Center (UTRC) - UTRC will partner with Argonne National Laboratory (ANL) to develop innovative and affordable machine learning enabled high-fidelity flow-physics models to be used in the design cycle of a gas turbine engine project titled “Deep Learning-Augmented Flow Solver to Improve the Design of Gas-Turbine Engines.”
General Motors LLC (GM) - GM will partner with Oak Ridge National Laboratory (ORNL) to develop residual stress models for laser-welded dissimilar joints (HSLA/CE steel) for car light-weighting in a project titled “Simulation Tools for Characterizing Stress Distribution in Laser Welded Dissimilar Joints.”
United Technologies Research Center (UTRC) - UTRC in collaboration with Sandia National Laboratories will aim to develop a first-principles based simulation framework for predicting deposition of dirt, sand, volcanic ash and other particulates on aero-engine components operating in polluted urban environments in a project titled “Fully-Resolved DNS Simulation of Particulate Deposition for Aeroengine Combustor Applications.”
Praxair Inc., a member of the Linde group - Praxair, Inc. will partner with ORNL to develop a multi-physics 3D CFD model of an Oxygen Transport Membrane (OTM) reactor module in a project titled “High Performance Computing for Improvement of Syngas Production Efficiency with OTM Technology.”
Dow, Inc. - Dow Chemical Company will partner with the National Renewable Energy Laboratory to model how flow in plastic impacts polymers at a molecular level in a project titled “Non-equilibrium Molecular Simulations of Polymers under Flow: Saving Energy through Process Optimization.”
Saint Gobain Ceramics & Plastics, DBA SEFPRO (Partnering Institution) - Owens Corning & Saint Gobain Ceramics & Plastics., DBA SEFPRO and Lawrence Livermore National Laboratory (LLNL) will collaborate to optimize the operating conditions in the glass manufacturing process in a project titled “Spectral Radiative Modeling of Glass Furnaces.”
United Technologies Research Center - United Technologies Research Center and Los Alamos National Laboratory will collaborate on developing a multiscale model to predict the mechanical behavior of additively manufactured components, particularly for creep applications in a project titled “Integrated Predictive Tools for Property Prediction in Additive Manufacturing.”
HPC for Materials
PPG Industries, Inc. | DBA PPG Coatings and Resins R&D (Allison Park, PA) will work with LLNL and PNNL to develop a computational screening algorithm based on experimental data that predicts corrosion inhibition performance of organic molecules. New environmentally-friendly pretreatments are needed to provide corrosion protection to the mix of lightweight metals being incorporated in more fuel-efficient vehicles.
Sinter Print Inc. dba Elementum 3D (Erie, CO) will partner with ANL to develop and validate a multi-scale model that enhances the control of nucleant formation and solidification structures for improved aluminum alloy properties. The improved alloys increase energy efficiency for automotive applications and reduce energy requirements for production of complex, high-performance components.
LM Industries Group, Inc. (Knoxville, TN) will partner with ORNL to improve predicting layer temperature profiles to reduce print time and waste and optimize large-scale additive manufacturing process and reduce its energy cost.
HPC for Mobility
City of San José – Department of Transportation (San Jose, CA) will partner with Lawrence Berkeley National Laboratory to develop a quasi-dynamic traffic assignment model that reduces compute times of from days to hours for a metropolitan area.
Chicago Transit Authority (Chicago, IL) will partner with ANL to use HPC and modeling to evaluate regional travel behavior and better understand interplay between variables affecting the Chicago Transit Authority’s operations and inform future decisions, such as pricing strategies, fleet electrification, and equitable distribution of transit services to optimize the region’s transportation energy use.