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Record W7019868889

Influence of electromagnetic treatment of fuels and oils on the formation of wear resistance of friction pairs

2020· article· en· W7019868889 on OpenAlexaboutno aff

Bibliographic record

VenueElectronic Institutional Repository of the National Aviation University of Ukraine (National Aviation University, Ukraine) · 2020
Typearticle
Languageen
FieldEngineering
TopicLubricants and Their Additives
Canadian institutionsnot available
Fundersnot available
KeywordsTribologyLubricityAviation fuelDiesel fuelWear resistanceAviationResource (disambiguation)Petroleum
DOInot available

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.518
Threshold uncertainty score0.525

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.008
GPT teacher head0.170
Teacher spread0.162 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

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