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Record W4362699247 · doi:10.3390/met13040725

Process Parameter Optimization of 2507 Super Duplex Stainless Steel Additively Manufactured by the Laser Powder Bed Fusion Technique

2023· article· en· W4362699247 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMetals · 2023
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing Materials and Processes
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceFusionKeyholePorosityLaser power scaling3D printingLaserComposite materialPower densityPower (physics)WeldingOptics

Abstract

fetched live from OpenAlex

Laser powder bed fusion is an attractive technology for producing high-strength stainless steel alloys. Among the stainless steels, 2507 super duplex stainless steel (2507 SDSS) is known for its excellent combination of corrosion resistance and high strength. Although there are some studies that aimed at optimizing the laser powder bed fusion (LPBF) printing parameters to print highly dense 2507 SDSS parts; However, a full optimization study is not reported yet. This study aims at optimizing the printing parameters for 2507 SDSS, namely: laser power, scan speed, and hatch distance. The response surface methodology was used in generating a detailed design of experiment to investigate the different pore formation types over a wide energy density range (22.22–428.87 J/mm3), examine the effects of each process parameter and their interactions on the resulting porosity, and identify an optimized parameter set for producing highly dense parts. Different process parameters showed different pore formation mechanisms, with lack-of-fusion, metallurgical or gas, and keyhole regimes being the most prevalent pore types identified. The lack-of-fusion pores are observed to decrease significantly with increasing the energy density at low values. However, a gradual increase in the keyhole pores was observed at higher energy densities. An optimal energy density process window from 68.24 to 126.67 J/mm3 is identified for manufacturing highly dense (≥99.6%) 2507 SDSS parts. Furthermore, an optimized printing parameter set at a laser power of 217.4 W, a scan speed of 1735.7 mm/s, and a hatch distance of 51.3 µm was identified, which was able to produce samples with 99.961% relative density. Using the optimized parameter set, the as-built 2507 SDSS sample had a ferrite phase fraction of 89.3% with a yield and ultimate tensile strength of 1115.4 ± 120.7 MPa and 1256.7 ± 181.9 MPa, respectively.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.788
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.013
GPT teacher head0.234
Teacher spread0.221 · 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