Argonne to advance AM for high-temperature nuclear reactor components
Argonne National Laboratory, based in Lemont, Illinois, USA, has submitted the first draft of an American Society of Mechanical Engineers (ASME) Code Case to enable the use of Laser Beam Powder Bed Fusion (PBF-LB) Additive Manufacturing for high-temperature reactor components.
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The proposal marks a step towards the qualification of Additive Manufacturing processes for nuclear applications, with the potential to support supply chain resilience, reduce manufacturing lead times, and enable greater design flexibility for high-temperature structural components.
The work was carried out through a collaboration between Argonne National Laboratory, Oak Ridge National Laboratory, Idaho National Laboratory, and Los Alamos National Laboratory, under the US Department of Energy’s Office of Nuclear Energy Advanced Materials and Manufacturing Technologies (AMMT) programme.
The AMMT programme explores advanced manufacturing technologies including PBF-LB, Directed Energy Deposition (DED), and Powder Metallurgy Hot Isostatic Pressing (HIP), with the aim of developing new materials, improving process performance, and addressing challenges associated with nuclear energy systems.
Argonne researchers worked with partners in the AMMT programme to translate laboratory research into standards and regulatory frameworks. The development of the Code Case was led by Mark Messner, Xuan Zhang, and Yiren Chen. Experimental work was conducted at Argonne’s Additive Manufacturing Laboratory.
Argonne stated that it plans to continue investigating approaches to accelerate material qualification, including the use of machine learning and the incorporation of in-situ process monitoring and advanced data analytics. These methods are intended to complement conventional empirical approaches used by ASME for analysing time-dependent material behaviour.
The use of artificial intelligence-based techniques aligns with the Department of Energy’s Genesis initiative, which aims to connect high-performance computing, data resources, and national laboratories to support scientific discovery, energy innovation, and national security.
