MétaCan
Menu
Back to cohort
Record W4417273195 · doi:10.31399/asm.hb.v25a.a0007141

Understanding Residual Stresses in the Field of Additive Manufacturing

2025· book-chapter· en· W4417273195 on OpenAlex
Mathieu Brochu, Amit Kumar, Sıla Ece Atabay

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.

Bibliographic record

VenueASM International eBooks · 2025
Typebook-chapter
Languageen
FieldEngineering
TopicAdditive Manufacturing Materials and Processes
Canadian institutionsMcGill University
Fundersnot available
KeywordsResidual stressField (mathematics)MicrostructureResidualAlloyPhase (matter)Work (physics)Fusion

Abstract

fetched live from OpenAlex

Abstract This article discusses the additive manufacturing (AM) processes involving solidification, because this liquid-to-solid phase transformation can develop important residual stresses (RS). Three subcategories are examined: powder-bed fusion (PBF), directed-energy deposition (DED), and wire arc additive manufacturing (WAAM). The understanding of the field is achieved by linking the RS, cooling rate, alloy composition, and the solidification microstructure length scale. To provide guidelines for the best combination of RS measurement techniques for a given type of AM part, an understanding of the measurement techniques, their working principles, and their limitations is presented. Two families of techniques exist for measuring RS, namely, destructive and non-destructive testing methods. The article presents case studies illustrating the relations between residual stress measurement techniques, the AM process, and the microstructure.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.923
Threshold uncertainty score0.731

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 head0.035
GPT teacher head0.255
Teacher spread0.220 · 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