DETERMINATION OF POWER LOSSES DUE TO PERIODIC COMPRESSION-EXPANSION OF THE OIL-AIR MIXTURE BETWEEN THE TEETH OF GEARS. PART 1. MATHEMATICAL MODEL
Bibliographic record
Abstract
The simultaneous contact of two pairs of teeth between their active profiles creates a closed volume of the oil-air mixture. Reducing this volume leads to the occurrence of such a negative phenomenon as periodic compression and expansion of the oil-air mixture in volume. At high gear rotation speeds, a significant increase in the pressure of the oil-air mixture is observed and, as a result, additional vibration of the gearing occurs. The oil-air mixture outflow rate can reach the speed of sound, which causes additional noise during gear operation, and at high rotational speeds, a hydraulic shock occurs in the space closed between the pinion and gear teeth, resulting in cavitation. By representing the helical gear as a set of spur gears displaced relative to each other in the tangential direction, it simplified the mathematical model to describe thermodynamic processes in a series of isolated cavities. The following variants are considered: a) the first cavity in the direction of engagement is connected to the environment on one side and to the next second cavity on the other side; b) some i-th cavity is connected to the cavities i - 1 and i + 1, respectively; c) the edge cavity N is connected to the previous cavity N - 1 and the environment. Thus, a mathematical model of the periodic compression-expansion of the oil-air mixture in the space closed between the teeth is presented, which considers the cross-sectional areas of the axial and radial flows of the oil-air mixture, the ambient pressure of the space closed between the teeth, the velocity of the radial flow of the oil-air mixture, the instantaneous volume of the elementary cavity closed between the teeth, and the current pressure in the cavity. Keywords: power losses, oil-air mixture, periodic compression-expansion, toothed gears, mathematical model, hydrodynamic model
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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".