HPC4mfg – Integrated Predictive Tools for Customizing Microstructure and Material Properties of Additively Manufactured Aerospace Components

Project Description

Advanced modeling and simulation capabilities and large scale data analysis provide tools to address challenging problems in decision making, process and design optimization, and performance prediction that occur in manufacturing. Effective use of High Performance Computing (HPC) in manufacturing has the potential to improve quality, reduce energy costs, accelerate or eliminate expensive testing, and accelerate the time of adoption of new technologies. With the support of the Department of Energy’s Advanced Manufacturing Office (AMO), Lawrence Livermore National Laboratory (LLNL), Oak Ridge National Laboratory (ORNL,) and Lawrence Berkeley National Laboratory (LBNL) have formed the HPC4Mfg program designed to allow partnerships with industry in bringing HPC into manufacturing.

This award supports the HPC4Mfg program, providing time on HPC resources to three National Laboratory/Industry partnerships designed as pilot programs for applying HPC to advanced manufacturing projects. This specific HPC4Mfg project is described below:

“Integrated Predictive Tools for Customizing Microstructure and Material Properties of Additively Manufactured Aerospace Components,” a partnership between United Technologies Research Center and ORNL, will simulate heat transfer in titanium alloys during additive manufacturing processes. Because thermal effects determine the materials properties of the final part, the results will allow prediction of materials properties, and optimization of the manufacturing processes.