A thermo-structural manufacturing process using AISI 304L stainless steel
Bibliographic record
Abstract
This article presents a study of high-temperature heating of AISI 304L stainless steel to induce deformations in a manufactured part. Small square samples of AISI 304L were heated to deform a slot using an oxy-acetylene torch. The sample temperature profiles were measured using three thermocouples with maximum temperature values ranging from 760 °C to 1130 °C. Three-dimensional thermo-structural finite element models were created to predict the magnitude of permanent deformation and were validated experimentally. Torch modeling parameters were optimized numerically using a series of finite element simulations. The finite element predictions for deformation were found to be in reasonable agreement with the experimental results. The variation in yield strength of AISI 304L was shown to be an important factor in affecting the magnitude of deformations. Repeated heating experiments also demonstrated additive plastic strain with each heating cycle. The results provide a means to use high temperatures to purposefully alter the dimensions of a slot in a manufactured part but with varying accuracy.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".