Prediction the Charpy impact energy of functionally graded steels
Bibliographic record
Abstract
Article history: Received September 20, 2013 Received in Revised form October, 14, 2013 Accepted 15 December 2013 Available online 20 December 2013 Functionally Graded Steels (FGSs) are possible solutions to improve the properties of steels made by Martensite and Bainite brittle phases. These phases are usually present in the interface between the carbon ferritic steel and the stainless austenitic steel. FGSs materials are widely investigated in the recent literature but only few works have been devoted to investigate the impact energy in the case of crack arresters. To partially fill this gap, the effect of the distance between the notch tip and the position of the median phase on the Charpy impact energy is investigated in the present paper. The results show that when the notch apex is close to the median layer the impact energy reaches its maximum value due to the increment of the absorbed energy by plastic deformation ahead of the notch tip. On the other hand, when the notch apex is far from the median layer, the impact energy strongly decreases. Keeping into account the relationship between the Charpy impact energy and the plastic volume size, a new theoretical model has been developed to link the composite impact energy with the distance from the notch apex to the median phase. The results of the new model show a sound agreement with previous results taken from the literature. © 2013 Growing Science Ltd. All rights reserved.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".