Desarrollo de un Modelo Virtual para el Conformado de Aceros Inoxidables
Bibliographic record
Abstract
En este trabajo se presenta un modelo virtual en ANSYS del proceso de conformado en aceros inoxidables que permite la obtención de la fibra neutra. La fibra neutra, también conocida como factor K, permite el cálculo del desarrollo de una pieza para su posterior conformado. Dada la complejidad de los procesos de conformado en la industria, como lo son el doblado, embutido y estampado, es necesario realizar el análisis computacional de los mismos. Es importante disponer de modelos que permitan conocer el comportamiento de los materiales durante su procesamiento para disminuir los posteriores errores de manufactura. Este trabajo propone un método de análisis por elementos finitos para el conformado de aceros inoxidables y presenta la comparativa con la experimentación física. Se ha caracterizado el proceso particular de doblado y se ha hecho la comparativa con probetas físicas de los aceros inoxidables 201 y 304, la cual muestra una diferencia de apenas el 0.4 por ciento entre ambas. El factor K obtenido puede ser utilizado directamente para cálculos analíticos para el desarrollo de piezas, o en los softwares de plegado de chapa metálica.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".