Assessment of Microstructure Prediction Capabilities for Powder Bed Fusion Stainless Steel 316
Open Access
- 1 August 2025
- report
- Published by Office of Scientific and Technical Information (OSTI)
Abstract
The Advanced Materials and Manufacturing Technologies program aims to accelerate the development, qualification, demonstration, and deployment of advanced materials and manufacturing technologies to enable reliable and economical nuclear energy. However, the characteristic process-structure-property relationships of additive manufacturing (AM) materials pose challenges for the qualification and certification of AM nuclear components. In particular, component-scale variations in microstructure and properties can be driven by localized changes in melt pool dynamics due to how process parameters interact with different part geometries. Computational modeling tools can play a crucial role in predicting and controlling this variability. This report presents final results on process modeling tools designed to predict microstructure variability in additively manufactured stainless steel 316 parts. It details the software packages and physical modeling approaches employed to simulate an AM component within an automated process modeling workflow. Results are demonstrated through comparisons between predicted microstructures and experimental measurements across various representative processing conditions. The report concludes by discussing identified challenges and future opportunities for connecting the developed simulation workflow with mechanics simulations for prediction of part performance.Keywords
Funding Information
- USDOE Office of Nuclear Energy (NE) (AC05-00OR22725)
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Energy Efficiency Office. Advanced Materials & Manufacturing Technologies Office (AMMTO) (AC05-00OR22725)
- USDOE Office of Science (SC) (AC05-00OR22725)
This publication has 22 references indexed in Scilit:
- Myna: Connecting powder bed fusion build data to simulation tools for digital twin applicationsComputational Materials Science, 2025
- Localized orientation gradients in additively manufactured stainless steel 316H structuresMaterials Characterization, 2025
- ExaCA v2.0: A versatile, scalable, and performance portable cellular automata application for additive manufacturing solidificationComputational Materials Science, 2025
- A dynamic volumetric heat source model for laser additive manufacturingAdditive Manufacturing, 2024
- Grain structure and texture selection regimes in metal powder bed fusionAdditive Manufacturing, 2024
- ExaCA: A performance portable exascale cellular automata application for alloy solidification modelingComputational Materials Science, 2022
- Heterogeneity and Solidification Pathways in Additively Manufactured 316L Stainless SteelsMetallurgical and Materials Transactions A, 2022
- Influence of geometry on columnar to equiaxed transition during electron beam powder bed fusion of IN718Additive Manufacturing, 2021
- Influence of defects on mechanical properties of Ti–6Al–4V components produced by selective laser melting and electron beam meltingMaterials & Design, 2015
- Effect of build geometry on the β-grain structure and texture in additive manufacture of Ti6Al4V by selective electron beam meltingMaterials Characterization, 2013