A study on the influence of laser hardening on microstructure, and microhardness of additively manufactured H13
Bibliographic record
Abstract
Laser surface treatment was employed as a promising approach to enhance the fatigue life of additively manufactured samples by increasing the surface hardness of the material. In this study, H13 tool steel was manufactured using the selective laser melting method, and lines of laser treatment were applied to the surface. Experimental and statistical approaches were utilised to investigate the microstructural changes, microhardness variations, and weld geometry resulting from different laser treatment processes. The aim was to control the laser parameters and analyse the behaviour of the microstructure and hardness profile of the laser-treated zone. The results revealed an amelioration in the hardness of the laser-treated surface, except for the heat-affected zone, which exhibited a lower hardness compared to the substrate. Statistical approaches were employed to study the effect of laser parameters on the weld geometry including width and depth of the laser-treated area using ANOVA method, elucidating the impact of each factor on these values. Finally, a predictive method for estimating the width and depth was proposed, to facilitate the adjustment of laser parameters for achieving specific outcomes, such as desired hardness profiles or geometrical characteristics, in the laser surface treatment process.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".