Location-Dependent Mechanical Property Evaluation on Additively Manufacture Materials

This report summarizes research activities conducted at Argonne National Laboratory in support of the development, qualification and certification of additively manufactured (AM) metallic components to allow for innovative reactor design and licensing. In this program, AM 316L stainless steel (SS) was evaluated in both light water reactor (LWR) environments as well as at higher temperatures expected in advanced reactors.In order to assess the long-term performance of AM 316L SS as a structural material in hightemperature nuclear environment, fatigue and creep-fatigue tests were performed. The results were compared with conventionally made wrought 316L SS. It was found that fatigue lives of AM 316L SS were slightly lower than that of wrought 316L SS, and decreased with the increase of test temperature from 300 to 550°C. The specimens machined from printed rods performed somewhat worse than those machined from printed plates, and no obvious difference can be identified between the samples parallel and perpendicular to the build direction. While both fatigue strength and ductility contribute to the fatigue performance of AM materials, the temperature effect on the fatigue life manifested mainly thought its impact on fatigue ductility.The tests conducted at 550°C with a short hold time of 30 s did not deteriorate the fatigue performance of AM 316L SS at 0.2% and 0.3% strain amplitudes.The void distribution in a creep tested AM 316L specimen was characterized by synchrotron xray tomography and compared to that in a conventional 316L specimen tested under the same condition. Comparison was also made to the untested AM 316L material. It was discovered that the built-in voids from the LPBF process and the laser hatching pattern had critical roles in the creep performance of the AM material.The variable of void distributions at different locations of an AM 316L rod (4" long x 0.5" dia.) was also characterized by synchrotron x-ray tomography. Specimens were extracted from different locations on the rod. It was found that the top segment had a higher density of small voids than the bottom segment, leading to a slightly higher porosity level.

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“…Figure 16Internal porosity and cracks in the gauge section of the rod specimen, L2-5 after 220 cycles tested at 550°C, 0.5%[18].…”

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Mechanical Testing of Additively Manufactured Materials

Alexandreanu

Zhang

Chen

et al. 2022

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A Data-Driven Framework for Direct Local Tensile Property Prediction of Laser Powder Bed Fusion Parts

Scime,

Joslin,

Collins

et al. 2023

Materials

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This article proposes a generalizable, data-driven framework for qualifying laser powder bed fusion additively manufactured parts using part-specific in situ data, including powder bed imaging, machine health sensors, and laser scan paths. To achieve part qualification without relying solely on statistical processes or feedstock control, a sequence of machine learning models was trained on 6299 tensile specimens to locally predict the tensile properties of stainless-steel parts based on fused multi-modal in situ sensor data and a priori information. A cyberphysical infrastructure enabled the robust spatial tracking of individual specimens, and computer vision techniques registered the ground truth tensile measurements to the in situ data. The co-registered 230 GB dataset used in this work has been publicly released and is available as a set of HDF5 files. The extensive training data requirements and wide range of size scales were addressed by combining deep learning, machine learning, and feature engineering algorithms in a relay. The trained models demonstrated a 61% error reduction in ultimate tensile strength predictions relative to estimates made without any in situ information. Lessons learned and potential improvements to the sensors and mechanical testing procedure are discussed.

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Location-Dependent Mechanical Property Evaluation on Additively Manufacture Materials

Cited by 2 publications

References 61 publications

Mechanical Testing of Additively Manufactured Materials

Mechanical Testing of Additively Manufactured Materials

A Data-Driven Framework for Direct Local Tensile Property Prediction of Laser Powder Bed Fusion Parts

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