Shot peening test rig test database
Bibliographic record
Abstract
This database contains all the output extracted from the tests performed at polytechnique Montreal using the shot peening test rig developped by the Mëkanic company (http://www.mekanic.ca/) in the frame of the Ph.D. thesis of Simon Breumier (ORCID:https://orcid.org/0000-0003-3241-8383). The folder contains all the tests performed on Al6061 samples to : Estimate the canon shooting accuracy Estimate the relation between the canon pressure input and the shot velocity Estimate the coefficients of restitutions (CoR) The dataset contains the following folders: 0-5mm: tests performed using 0.5mm shot diameter to estimate the canon accuracy and pressure/velocity relation. All the tests were performed at the same position, therefore the velocity after impact is not a relevent data. 05mm_COR: tests performed using 0.5mm shot diameter to estimate the CoRs at different velocity. All the tests were performed at separated location so that no interaction between the shot dent occurs 1-19mm: tests performed using 1.19mm shot diameter to estimate the canon accuracy, the pressure/velocity relationship and the CoRs. All the tests were performed at separated location so that no interaction between the shot dent occurs. 2-5mm: tests performed using 2.5mm shot diameter to estimate the canon accuracy and the pressure/velocity. All the tests were performed at the same position, therefore the velocity after impact is not a relevent data. 2-5mm_COR: tests performed using 2.5mm shot diameter to estimate the CoRs at different velocity. All the tests were performed at separated location so that no interaction between the shot dent occurs Angles: tests performed usin 1.19mm shot diameter with different shooting angles. All the tests were performed at separated location so that no interaction between the shot dent occurs. Also, the cameras were recalibrated for each angular position. Each folder contains the different tests made for the three different shot diameters. For each diameter, each folder contains all the test performed at a given test pressure. Each pressure folder contains the folders containing the pictures taken by the left and top camera in tif format. For each pressure, the RESULTS folder containts the resulting trajectory extracted using the 3Deye software developped for the project (https://github.com/lm2-poly/3Deye). Among other things, the software provides a text file for each test summerizing the test conditions, the estimated trajectory, the cameras acquisition and calibration parameters to fully reproduce the analyses. warning: some of the tests were performed with a former version of 3Deye and therefore gave different shot position estimations. This was accounted for in the final results but was not corrected in the current database.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.003 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.025 |
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".