Integrated Thermal Process Optimization of Alloy 718Plus® for Additive Manufacturing

Gong, Jiang Hong; Deutchman, H.; Peralta, Alonso; Snyder, D J; Enright, Michael P.; McFarland, John; Neumann, J.; Sebastian, Jason; Olson, G. B.

doi:10.1002/9781119075646.ch109

Cited by 4 publications

(2 citation statements)

References 14 publications

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“…At 704°C, the material is held for 8 h then cooled in a furnace. This heat treatment procedure has been shown to provide optimal microstructures and preferred strength characteristics [59]. The resulting microstructure, obtained via electron backscatter diffraction (EBSD), is shown in figure 1a.…”

Section: (A) Materials Processingmentioning

confidence: 99%

“…In particular, this material is processed via additive manufacturing, specifically selective laser melting, using an EOS M280 laser powder-bed machine at Honeywell Aerospace, Phoenix, AZ, USA. The build parameters are optimized based on process modelling, discussed in [58], to result in minimal porosity [59]. The optimized parameter values are 300 W laser power, 0.09 mm hatch spacing, 1.65 m s −1 laser speed and stripe width of 5 mm.…”

Section: (A) Materials Processingmentioning

confidence: 99%

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Microstructure-sensitive critical plastic strain energy density criterion for fatigue life prediction across various loading regimes

et al. 2020

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In the present work, we postulate that a critical value of the stored plastic strain energy density (SPSED) is associated with fatigue failure in metals and is independent of the applied load. Unlike the classical approach of estimating the (homogenized) SPSED as the cumulative area enclosed within the macroscopic stress–strain hysteresis loops, we use crystal plasticity finite element simulations to compute the (local) SPSED at each material point within polycrystalline aggregates of a nickel-based superalloy. A Bayesian inference method is used to calibrate the critical SPSED, which is subsequently used to predict fatigue lives at nine different strain ranges, including strain ratios of 0.05 and −1, using nine statistically equivalent microstructures. For each strain range, the predicted lives from all simulated microstructures follow a lognormal distribution. Moreover, for a given strain ratio, the predicted scatter is seen to be increasing with decreasing strain amplitude; this is indicative of the scatter observed in the fatigue experiments. Finally, the lognormal mean lives at each strain range are in good agreement with the experimental evidence. Since the critical SPSED captures the experimental data with reasonable accuracy across various loading regimes, it is hypothesized to be a material property and sufficient to predict the fatigue life.

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Section: (A) Materials Processingmentioning

confidence: 99%

Section: (A) Materials Processingmentioning

confidence: 99%

Microstructure-sensitive critical plastic strain energy density criterion for fatigue life prediction across various loading regimes

et al. 2020

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A Methodology for Predicting Surface Crack Nucleation in Additively Manufactured Metallic Components

Chan

Peralta-Duran

2019

Metall Mater Trans A

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A Methodology for the Rapid Qualification of Additively Manufactured Materials Based on Pore Defect Structures

Stopka,

Desrosiers,

Andreaco

et al. 2024

Integr Mater Manuf Innov

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Additive manufacturing (AM) can create net or near-net-shaped components while simultaneously building the material microstructure, therefore closely coupling forming the material and shaping the part in contrast to traditional manufacturing with distinction between the two processes. While there are well-heralded benefits to AM, the widespread adoption of AM in fatigue-limited applications is hindered by defects such as porosity resulting from off-nominal process conditions. The vast number of AM process parameters and conditions make it challenging to capture variability in porosity that drives fatigue design allowables during qualification. Furthermore, geometric features such as overhangs and thin walls influence local heat conductivity and thereby impact local defects and microstructure. Consequently, qualifying AM material within parts in terms of material properties is not always a straightforward task. This article presents an approach for rapid qualification of AM fatigue-limited parts and includes three main aspects: (1) seeding pore defects of specific size, distribution, and morphology into AM specimens, (2) combining non-destructive and destructive techniques for material characterization and mechanical fatigue testing, and (3) conducting microstructure-based simulations of fatigue behavior resulting from specific pore defect and microstructure combinations. The proposed approach enables simulated data to be generated to validate and/or augment experimental fatigue data sets with the intent to reduce the number of tests needed and promote a more rapid route to AM material qualification. Additionally, this work suggests a closer coupling between material qualification and part certification for determining material properties at distinct regions within an AM part.

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Integrated Thermal Process Optimization of Alloy 718Plus® for Additive Manufacturing

Cited by 4 publications

References 14 publications

Microstructure-sensitive critical plastic strain energy density criterion for fatigue life prediction across various loading regimes

Microstructure-sensitive critical plastic strain energy density criterion for fatigue life prediction across various loading regimes

A Methodology for Predicting Surface Crack Nucleation in Additively Manufactured Metallic Components

A Methodology for the Rapid Qualification of Additively Manufactured Materials Based on Pore Defect Structures

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