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Results for “STEELS, STAINLESS - WELDING”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Mechanical Properties of Tritium Precharged and Aged Additively Manufactured Austenitic Stainless Steel

What is “known” about tritium effects on austenitic steel • Decreased ductility and fracture resistance • Hardening/strengthening • Hydrogen is believed to interact with dislocations, grain boundaries, vacancies, and other microstructural features2 • But what about AM?? • Similar behavior/trends? • How do we account for differences between AM and forged? • Can we design based on material with similar microstructure that has already been tested?

Wieber, Natalie [Savannah River National Laborator↗
DOE OSTI2025

Microstructural evaluation of thin-wall sections of 316L stainless steel produced by laser powder-bed fusion processing

Laser powder bed fusion (LBPF) is a method of additive manufacturing (AM) that offers a means to fabricate complex components with features which rely upon the mechanical integrity of thin-wall (less than 0.4 mm thick) structures. The microstructure of a 316L AM thin wall is investigated as metallographically prepared from a cylindrical shell. Optimization is pursued through mechanical polishing and chemical etching to minimize the effects of surface roughness. Microanalysis measurements of the sectioned component reveal the sample has high microstructural fidelity, uniform composition and phase content across grain as well as powder layer boundaries within the thin wall. The results are attributed to a uniform thermal gradient at the part scale during rapid solidification.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Advanced Materials & Manufacturing Technology (AMMT): Development of Additive Manufacturing Agnostic Process Parameter Procedure, 316H Stainless Steel Readiness Level Data Sets, and Machine Maintenance Plan

The University of California, Davis is involved in a project to deploy and enhance an artificial intelligence (AI) system for predicting and preventing plasma disruptions on the DIII D tokamak, under the funding from Department of Energy DE-SC0023500 (title: AI/Deep Learning FRNN Software for Prediction & Real-Time Control of DIII-D Plasma Control System (PCS)). The overarching goal is to demonstrate that real-time, AI-guided intervention can proactively modify the plasma state to avoid or mitigate disruptions—a critical challenge for the future of fusion energy.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Microstructural evaluation of thin-wall sections of 316L stainless steel produced by laser powder-bed fusion processing

The synthesis of thin wall sections that are only 0.4 mm thick is achieved with LPBF AM. Sample preparation is optimized using metallographic polishing to produce samples with only 0.3 um rms roughness for scanning electron microanalysis with EBSD and EDS. A fully austenitic 316L phase is found without evidence of secondary phases. Unlike some AM products that can readily evidence composition segregation due to solute rejection as attributable to temperature gradients within the solidification

Jankowski, Alan F. [Sandia National Laboratories (↗