Research Experiences for Undergraduates in Computational Methods with Applications in Materials Science
MSU Affiliation
Applied Research Collaboratory; Institute for Systems Engineering Research; Center for Computational Sciences
Major
Mechanical Engineering
Research Mentor
Eric M. Collins, Jacob L. Moore
Creation Date
7-27-2026
Abstract
Metal additive manufacturing has experienced rapid growth across a variety of industries due to its ability to fabricate parts with complex, customizable geometries in a fraction of the time and material required by conventional processes. However, because metal is selectively melted and resolidified in a layer-wise deposition process, the cyclical heating and cooling induces expansion and contraction that can accumulate as residual stress within the part's microstructure. This buildup of residual stress can lead to print failures or degraded part performance, yet the mechanisms governing residual stress formation during printing remain poorly understood. Existing simulation techniques for predicting residual stress in additively manufactured parts are either inaccurate or too computationally expensive for practical use. This project advances a new thermal solver for metal additive manufacturing simulation, built within Fierro — a computational mechanics code developed at Los Alamos National Laboratory (LANL) that leverages the MATAR library and the Kokkos framework to run efficiently across CPU and GPU architectures. Key advancements include a more flexible heat source model capable of representing both symmetric and directionally dependent (scan-direction-oriented) energy distributions. The solver was also extended to support multilayer simulations, with melt-region temperatures output for process visualization. Together, these advancements represent significant progress toward a high-fidelity, computationally efficient thermal solver capable of studying the relationship between the printing process and residual stress accumulation in metal additively manufactured parts.
Presentation Date
Summer 7-30-2026
Keywords
additive manufacturing, computational mechanics
Recommended Citation
Busching, Luther W.; Collins, Eric M.; and Moore, Jacob L., "Toward an Efficient Simulation Tool for Predicting Residual Stress in Metal Additively Manufactured Parts" (2026). Research Experiences for Undergraduates in Computational Methods with Applications in Materials Science. 25.
https://scholarsjunction.msstate.edu/ccs-reu/25
