Recrystallization behavior and mechanical properties of Haynes 282 fabricated by wire-arc additive manufacturing with post-heat treatment

Pizano, Luis Fernando Ladinos; Sridar, Soumya; De Vecchis, Rafael Rodriguez; Wang, Xin; Biddlecom, Jacob; Pataky, Garrett J.; Sudbrack, Chantal; Xiong, Wei

doi:10.1016/j.jmapro.2024.04.015

Cited by 2 publications

(1 citation statement)

References 13 publications

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“…As a result, the HIP treatment was performed at 1250°C for 2 hours at a pressure of 150 MPa followed by furnace cooling to reduce the porosity. The HIP temperature is higher than the conventional solution treatment temperature (1121–1149°C) to promote recrystallization of the as-printed microstructure and obtain an equiaxed grain structure [ 22 ]. As shown in Figure 2(b) , most of the lack of fusion pores and solidification cracks were closed, with some remnant gas pores and the porosity reduced to 1%.…”

Section: Resultsmentioning

confidence: 99%

Aging heat treatment design for Haynes 282 made by wire-feed additive manufacturing using high-throughput experiments and interpretable machine learning

Wang,

Ladinos Pizano,

Sridar

et al. 2024

Science and Technology of Advanced Materials

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Wire-feed additive manufacturing (WFAM) produces superalloys with complex thermal cycles and unique microstructures, often requiring optimized heat treatments. To address this challenge, we present a hybrid approach that combines high-throughput experiments, precipitation simulation, and machine learning to design effective aging conditions for the WFAM Haynes 282 superalloy. Our results demonstrate that the γ’ radius is the critical microstructural feature for strengthening Haynes 282 during post-heat treatment compared with the matrix composition and γ’ volume fraction. New aging conditions at 770°C for 50 hours and 730°C for 200 hours were discovered based on the machine learning model and were applied to enhance yield strength, bringing it on par with the wrought counterpart. This approach has significant implications for future AM alloy production, enabling more efficient and effective heat treatment design to achieve desired properties.

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Section: Resultsmentioning

confidence: 99%

Aging heat treatment design for Haynes 282 made by wire-feed additive manufacturing using high-throughput experiments and interpretable machine learning

Wang,

Ladinos Pizano,

Sridar

et al. 2024

Science and Technology of Advanced Materials

Self Cite

View full text Add to dashboard Cite

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Effect of solution treatment temperature on recrystallisation behaviour of Haynes 282 manufactured through laser powder bed fusion

Swaminathan,

Andersson

2024

IOP Conf. Ser.: Mater. Sci. Eng.

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Increasing layer thickness in Laser Powder Bed Fusion (PBF-LB) process of metals enable increasing productivity and facilitate industrialisation of metal additive manufacturing (AM) process. Understanding of microstructure in as-built stage and possible post-processing steps to modify the microstructure is critical for metal AM components. Haynes 282 Nickel based superalloy, typically used in aerospace and energy industries, was manufactured using PBF-LB process at 60 microns layer thickness. Two different solution treatment temperatures were studied to analyse the recrystallization behaviour of the as-built material. The as built microstructure consisted high dislocation density given the rapid cooling in PBF-LB process. Solution treatment at 1150°C resulted in reduced dislocation density but similar morphology to grains in as built condition with visible residual melt pool boundaries. Solution treatment at 1250°C resulted in recrystallised grain structure. The recrystallisation behaviour is discussed with relation to manufacturing process and kinetic behaviour of alloying elements.

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Recrystallization behavior and mechanical properties of Haynes 282 fabricated by wire-arc additive manufacturing with post-heat treatment

Cited by 2 publications

References 13 publications

Aging heat treatment design for Haynes 282 made by wire-feed additive manufacturing using high-throughput experiments and interpretable machine learning

Aging heat treatment design for Haynes 282 made by wire-feed additive manufacturing using high-throughput experiments and interpretable machine learning

Effect of solution treatment temperature on recrystallisation behaviour of Haynes 282 manufactured through laser powder bed fusion

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