АНАЛІЗ КОНСТРУКЦІЙ РЕСОРНИХ ПІДВІШУВАНЬ РЕЙКОВОГО МІСЬКОГО ЕЛЕКТРОРУХОМОГО СКЛАДУ
Bibliographic record
Abstract
The object under consideration in the article is the spring suspension of the city railroad electric vehicle. The purpose of the article: to carry out an analysis of the current state of the structures of spring suspensions of the railroad urban electric vehicle and identify perspective directions for their improvement. Results The article considers modern technical solutions used in the spring suspension of tram cars: the trolley of the tramcar T-3, Czechoslovakia; Trolleybus car "Spectrum" produced by OJSC "Uraltransmash", Russia; The trolley of Flexx Urban 1000 tram carriages in Bombardier, Canada. The article analyzes the designs of spring suspended tram and subway cars of city electric rolling stock. Conclusions. It was determined that in the tram and subway carriages, most often, friction dampers are used to dampen vibrations, which are installed in the central suspension; in the latest modern constructions, both on tram-wagons and on subway cars, pneumatic adjustable under-hanging, which is installed instead of the friction damper in the second degree of spring suspension, has been used to dampen vibrations. Propulsion systems for extinguishing oscillations that can be installed on the MERS, may be electromechanical shock absorbers, which are widespread in recent times in road transport.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 0.006 |
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".