Scalable Deployment of MFEM for Generative Design and Additive Manufacturing Applications

The goal of this proposal is to build tools centered around the Modular Finite Element Library (MFEM) to support rapid design of parts with lattice structures made with Additive Manufacturing (AM). These parts include critical components used in aerospace, defense, and automotive applications including light-weighting of structural brackets, engine components, heat exchangers, nuclear reactor cores, and consumer goods such as footwear, helmets, bike saddles, orthopedic casts. Such parts which are increasingly generatively designed using Finite Element Analysis (FEA) simulation and additively manufactured. The state-of-the-art design and simulation tools cannot handle AM related advanced thermo-mechanical physics considerations (thermal distortions and residual stresses) on complicated heterogeneous representations due to the following two challenges: (a) lack of automated preprocessing and postprocessing tools with intuitive user interfaces, and (b) lack of easy access to scalable computational tools. Our proposed innovation is built around the scalable MFEM software. It can effectively address the design and simulation challenges by leveraging the mathematical libraries in MFEM. These libraries can solve non-linear multi-million degrees of freedom systems repeatedly, making MFEM a critical component in solving this problem. In Phase I, we will de-risk the innovation by developing a proof-of-concept (POC) framework for each of above the innovations. At the end of Phase I, we demonstrate a POC MFEM-based workflow that can compute sensitivity information for heterogeneous representations (lattice structures) in a simplified self-adjoint thermo-mechanical FEA simulation setting for AM. In Phase II, we will we will significantly extend the POC framework to include adjoint-based generative design and topology optimization with AM related thermo-mechanical physics considerations, thus taking full advantage of MFEM’s advanced capabilities. The proposed effort aims to bring the advantages of MFEM scalable FEA simulations to 3D printing communities. By leveraging high-fidelity FEA simulation data, users can efficiently analyze, optimize, and additively manufacture lattice structures. The solution offers a user-friendly GUI that integrates with existing design tools, eliminating entry barriers for inexperienced users and encouraging the adoption of MFEM-based tools.