Influence of electromagnetic treatment of fuels and oils on the formation of wear resistance of friction pairs
Bibliographic record
Abstract
1. Increasing the resource of technical systems through the use of electric and magnetic fields: monographs / [E. E. Alexandrov, I. A. Kravets, E. P. Lysikov et al.]. – Kharkov: NTU „KhPI”, 2006. – 544 p. 2. Kravets, I. A. Reparative regeneration of tribo systems / I. A. Kravets – T.: Berezhansky Agrotechnical Institute Publishing House, 2003. – 284 p. 3. Evdokimov, A.Yu. Lubricants and environmental problems: textbook, manual / A. Yu. Evdokimov, I.G. Fuchs, T.N. Shabalina. – M.: GUP Oil and Gas, 2000. – 424 p. 4. Diha O. The Rosrakhunkovo-experimental research of tribological authorities of the masters of mathematics // O. Diha, A. Kuzmenko, V. Mokritsky – Machinstvo. – 2001. – №7. – P. 29–32. 5. Lisikov E.M. Partitioning the resource of tribo-technical systems by means of the grid for the electrostatic field to the masters of materials / E.M. Lisikov // Tekhnika ta vikonya technology Budivnich, Kolіynykh and perevaltazhvalnyh robіt on transport: Zb. sciences. prat Iss. 58. – Kharkiv: UkrDAZT, 2004. – P. 5–10. 6. Tretyakov I.G. The effect of electromagnetic treatment on the antiwear properties of individual hydrocarbon compounds / I.G. Tretyakov, Yu.I. Korolenko // Problems of Aviation Chemotology. Mezhvuz. Sat, Issue 2. – Kiev, 1978. – P. 141–144. 7. Morozov V.I. Effect of electrophysical effects on the performance properties of diesel fuel / V.I. Morozov, Ya.E. Belokon, A.I. Okocha. // Studies of the processes of preparation, application and quality control of aviation fuel and special liquids. – 1992. – № 5. – P. 94−98. 8. Bazhenov Yu.V. Triboelectrization of oil and diesel fuel // Yu.V. Bazhenov, Yu.A. Mikiporis, A.N. Pavlov // Friction and lubrication in machines and mechanisms. – 2006. – № 10. – P. 24−27. 9. Trofimov I. L. Pidvischennya tribotehnichnyh power of paliv and olive field of electricity / І. L. Trofimov // Questions of chemistry and chemical technology. – 2010. – № 3. – P. 132–137. 10. Podgorkov V.V. The carrying capacity of magnetic fluids / V.V. Podgorkov // Friction and wear. – 1990. – Vol. 11. – № 2. – P. 359–361. 11. Sudbury A. Quantum mechanics and particle physics / A. Sudbury. – M.: Mir, 1989. – 488 p. 12. Boom A. Quantum mechanics: fundamentals and applications / A. Boum. – M.: Mir, 1990. – 720 p. 13. Trofimov I.L. Systems and means of motor transport (selected problems), by Politechnika Rzeszowska / I.L. Trofimov, N.N. Zakharchuk. – Rzeszow, Poland. – P. 295–301. 14. Pat.72848 Ukraine. F02M 27/00, F02M 27/04 (2006.01). Spalib processing paliva / Andrіevsky A.P., Matveeva O.L., Nechosov V.V.; applicants and vlasniki Andrієvsky A.P, Matveeva O.L., Nechosov V.V. – № u2012 03103; declared 03/16/2012; publ. 27.08.2012, Bull. №16. 15. Pat.72858 Ukraine. B01D 36/00, F02M 27/04 (2006.01). Filipr-activator paliva / Andrievsky A.P., Matveeva O.L., Nechosov V.V.; applicants and vlasniki Andrіevsky A.P, Matveea O.L., Nechosov V.V. – № u2012 03245; declared 03/19/2012; publ. 27.08.2012, Bull. №16. 16. Svirid M.M. The complex for the progress of the tribotechnical parameters of the institute / M.M. Svirid, V.G. Paraschanov, A.V. Onishchenko // Problem rubbing that znoshuvannya. – 2006. – No. 45. – P. 204–209. 17. Pat. № 70877. Ukraine. G01N 3/56. Device for study of friction surfaces in permanent uniform and non-uniform magnetic field / Svirid M.M., Kudrin A.P., Kravets I.A., Priymak L.B., Borodiy V.M. – № u201115161; declared 12/21/2011. Publ.25.06.2012, Bull. № 12 – 5 p.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".