Comportement mécanique monotone et cyclique d'éprouvettes de section millimétrique mises en forme par fusion laser sur lit de poudre
Bibliographic record
Abstract
RÉSUMÉ: Ce travail s’inscrit dans le cadre d’un programme de recherche collaboratif entre le milieu académique et des acteurs industriels du secteur aérospatial au Québec. Le projet constitue un effort vers la certification des pièces technologiques obtenues par fabrication additive des métaux. L’objectif principal de ce doctorat consiste à proposer des stratégies de mesures justes et précises pour la caractérisation en traction et en fatigue d’éprouvettes de section millimétrique mises en forme par fusion laser sur lit de poudre (LPBF). Aucune norme n’existe à ce jour pour l’utilisation de telles éprouvettes. Dans un premier temps, une méthodologie d’essais de traction a été développée avec des éprouvettes rectangulaires ayant des dimensions dans la section réduite de 1 × 1,5 × 7 mm³. Ces éprouvettes miniatures ont été utilisées pour mesurer les propriétés en traction de l’acier inoxydable 316L mis en forme par LPBF. Trois états de surface ont été considérés : telle que fabriquée par LPBF avec une rugosité de surface moyenne ABSTRACT: This work is part of a collaborative research program between academic and industrial actors of the aerospace sector in Quebec. The program constitutes an effort towards the certification of additively manufactured metallic parts. The objective of this PhD thesis is to propose experimental methodologies for the precise and accurate measurement of the tensile and fatigue properties of millimetric specimens fabricated by laser powder bed fusion (LPBF). First, a tensile test methodology was developed using rectangular specimens with a reduced section of 1 × 1,5 × 7 mm³. These miniature specimens were employed for the tensile characterization of 316L stainless steel produced by LPBF. Three surface conditions were considered: as-built by LPBF, with an average surface roughness
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".