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Record W4405724737 · doi:10.3390/jmmp8060297

Elevated-Temperature Tensile Behavior and Properties of Inconel 718 Fabricated by In-Envelope Additive–Subtractive Hybrid Manufacturing and Post-Process Precipitation Hardening

2024· article· en· W4405724737 on OpenAlexafffund
Sheida Sarafan, Priti Wanjara, Roger Pelletier, Sıla Ece Atabay, Javad Gholipour, Josh Soost, Robert Amos, Prakash Patnaik

Bibliographic record

VenueJournal of Manufacturing and Materials Processing · 2024
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing Materials and Processes
Canadian institutionsDepartment of National DefenceNational Research Council Canada
FundersNational Research Council CanadaMinistère de la Défense NationaleMcGill University
KeywordsInconelMaterials scienceMachiningUltimate tensile strengthSurface roughnessAlloyHardening (computing)Precipitation hardeningEnvelope (radar)Surface finishComposite materialFabricationMetallurgyComputer science

Abstract

fetched live from OpenAlex

The present study focuses on advancing one of the most popular AM techniques, namely, laser powder bed fusion (LPBF) technology, which has the ability to produce complex geometry parts with minimum material waste but continues to face challenges in minimizing the surface roughness. For this purpose, a novel hybrid manufacturing technology, which applies in a single setup (in-envelope) both LPBF technology and high-speed machining, was examined in this research for the fabrication of tensile specimens with three different surface finish conditions: as-built, hybrid (in-envelope machining) and post-machining (out-of-envelope) on Inconel® alloy 718, hereafter referred to as IN718. As the application of the IN718 alloy in service is typically specified in the precipitation-hardened condition, three different heat treatments were applied to the tensile specimens based on the most promising thermal cycles identified previously for room-temperature tensile properties by the authors. The as-built (AB) specimens had the highest average surface roughness (Ra) of 5.1 μm ± 1.6 μm, which was a significant improvement (five-fold) on the hybrid (1.0 μm ± 0.2 μm) and post-machined (0.8 μm ± 0.5 μm) surfaces. The influence of this surface roughness on the mechanical properties was studied both at ambient temperature and at 650 °C, which is close to the maximum service temperature of this alloy. Regardless of the surface conditions, the room-temperature mechanical properties of the as-fabricated IN718 specimens were within the range of properties reported for standard wrought IN718 in the annealed condition. Nonetheless, detailed examination of the strain localization behavior during tensile testing using digital image correlation showed that the IN718 specimens with AB surfaces exhibited lower ductility (global and local) relative to the hybrid and post-machined ones, most likely due to the higher surface roughness and near-surface porosity in the former. At 650 °C, even though the mechanical properties of all the heat-treated IN718 specimens surpassed the minimum specifications for the wrought precipitation-hardened IN718, the AB surface condition showed up to 4% lower strength and 33–50% lower ductility compared with the hybrid and PM surface conditions. Microfocus X-ray computed tomography (µXCT) of the fractured specimens revealed the presence of numerous open cracks on the AB surface and a predisposition for the near-surface pores to accelerate rupture, leading to premature failure at lower strains.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.217
Teacher spread0.209 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2024
Admission routes2
Has abstractyes

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