Assessment, analysis and optimization for high temperature sliding wear process parameter with additive built nickel base superalloy
Bibliographic record
Abstract
Abstract Superalloys are highly demanding alloy for high temperature application. The conventional production process and metallurgical sustainability of the superalloy against the applications is the preamble of the existing research. Based on the review it is clear to say that the development of nickel base superalloy with advanced technique without compensating the quality is open for research. The nickel base superalloy is developed through additive manufacturing process following a metal laser sintering technique. The developed alloy is used to perform high temperature sliding wear analysis with the different input process conditions. Applied load, sliding duration and the working temperature are the defined process environment for the investigation. The process conditions are designed with twenty-seven set of experimental trials for statistical analysis and process assessment. The responses on surface roughness and the material loss with respect to the input process parameters are technically assessed and justifications made with the electron microscopic images. The surface topography has influenced due to applied load and the sliding duration. Applied load has influenced the contact area prone with severe wear and the ridges are notice from the microscopic analysis. The statistical analysis has proved that the influence of temperature is less and negotiable compared to the load and time factor. From the optimization process, the optimal parameter for the experimental design is 10 N, 100 °C and 30 min is the ultimate condition to produce best results from the high temperature sliding wear analysis.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| 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 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".