Laboratory and Rig Tests of High-Strength and High Crack Resistance Wheel Tyres
Bibliographic record
Abstract
The paper presents development/comprehension tests outcomes of locomotive wheel tyre prototypes of grade ‘H’ medium alloy steel. These high-strength and high crack resistance tyres are intended for use with series 2EC10, 2EC7 and 2EC6 new generation freight electric locomotives with asynchronous traction drive. The work under discussion was carried out by the JSC VNIIZhT experts in cooperation with JSC “EVRAZ NTMK”. It covered the development of wheel tyre production specifications including those related to chemical content and mechanical properties of steel, appraisal of the tyre heat treatment conditions, manufacturing of tyre prototypes as well as laboratory and rig testing aimed to assess the tyre property package. Wheel tyre prototypes of grade “H” steel were subject to laboratory and rig tests at the JSC VNIIZhT experimental facilities inclusive of analysis of working layer mechanical properties and of hardness/microstructure distribution over the cross-section, assessment of cold resistance, determination of the tyre static fracture toughness (crack resistance) K1С and damping capacity (tenacity) Kfc, as well as analysis of the tyre stress state. Based on the positive results of the initial and acceptance tests of the grade ‘H’ steel tyres pilot run there was adopted the decision on the under-control operation of the tyres with the series 2EC10 electric locomotives on the Sverdlovskaya Railway network.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".