Experimental verification: a multi-objective optimization method for inversion technology of hydrodynamic journal bearings
Aiming at the key design variables of journal bearings, a novel optimization scheme is proposed to minimize oil leakage and power loss. For the first time, the inversion technology is introduced into the multi-objective optimization genetic algorithm under thermohydrodynamics. Using the hybrid optim...
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| Published in: | Structural and multidisciplinary optimization Vol. 66; no. 1; p. 14 |
|---|---|
| Main Authors: | , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.01.2023
Springer Nature B.V |
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| ISSN: | 1615-147X, 1615-1488 |
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| Abstract | Aiming at the key design variables of journal bearings, a novel optimization scheme is proposed to minimize oil leakage and power loss. For the first time, the inversion technology is introduced into the multi-objective optimization genetic algorithm under thermohydrodynamics. Using the hybrid optimization method (sequential quadratic programming and multi-objective optimization genetic algorithm) and the pareto optimal frontier method, the journal bearing model under the oil supply condition of oil groove (
Model A
) and oil hole (
Model B
) is optimized. More importantly, the oil leakage (
Q
L
) formula is exhaustively deduced, and good prediction results are obtained by simulating the data in literature. The optimization test results show that compared with the maximum errors (13% and 25%) of the power loss and leakage flow prediction results in literature, the maximum errors of this prediction model are 8% and 14%, respectively. In addition, compared with hybrid optimization method, the pareto optimal frontier has better advantages under inversion technology. Both methods can give good prediction results. The accuracy of this model is proved by comparing experimental data in the literature. |
|---|---|
| AbstractList | Aiming at the key design variables of journal bearings, a novel optimization scheme is proposed to minimize oil leakage and power loss. For the first time, the inversion technology is introduced into the multi-objective optimization genetic algorithm under thermohydrodynamics. Using the hybrid optimization method (sequential quadratic programming and multi-objective optimization genetic algorithm) and the pareto optimal frontier method, the journal bearing model under the oil supply condition of oil groove (Model A) and oil hole (Model B) is optimized. More importantly, the oil leakage (QL) formula is exhaustively deduced, and good prediction results are obtained by simulating the data in literature. The optimization test results show that compared with the maximum errors (13% and 25%) of the power loss and leakage flow prediction results in literature, the maximum errors of this prediction model are 8% and 14%, respectively. In addition, compared with hybrid optimization method, the pareto optimal frontier has better advantages under inversion technology. Both methods can give good prediction results. The accuracy of this model is proved by comparing experimental data in the literature. Aiming at the key design variables of journal bearings, a novel optimization scheme is proposed to minimize oil leakage and power loss. For the first time, the inversion technology is introduced into the multi-objective optimization genetic algorithm under thermohydrodynamics. Using the hybrid optimization method (sequential quadratic programming and multi-objective optimization genetic algorithm) and the pareto optimal frontier method, the journal bearing model under the oil supply condition of oil groove ( Model A ) and oil hole ( Model B ) is optimized. More importantly, the oil leakage ( Q L ) formula is exhaustively deduced, and good prediction results are obtained by simulating the data in literature. The optimization test results show that compared with the maximum errors (13% and 25%) of the power loss and leakage flow prediction results in literature, the maximum errors of this prediction model are 8% and 14%, respectively. In addition, compared with hybrid optimization method, the pareto optimal frontier has better advantages under inversion technology. Both methods can give good prediction results. The accuracy of this model is proved by comparing experimental data in the literature. |
| ArticleNumber | 14 |
| Author | Huang, Xuanjun Tong, Haiyang Lu, Liming Zhang, Jingjun Zheng, Zhiyi |
| Author_xml | – sequence: 1 givenname: Jingjun surname: Zhang fullname: Zhang, Jingjun organization: Key Laboratory of Conveyance and Equipment Ministry of Education, East China Jiaotong University – sequence: 2 givenname: Liming surname: Lu fullname: Lu, Liming email: 1199@ecjtu.edu.cn organization: Key Laboratory of Conveyance and Equipment Ministry of Education, East China Jiaotong University – sequence: 3 givenname: Zhiyi surname: Zheng fullname: Zheng, Zhiyi organization: Key Laboratory of Conveyance and Equipment Ministry of Education, East China Jiaotong University – sequence: 4 givenname: Haiyang surname: Tong fullname: Tong, Haiyang organization: Key Laboratory of Conveyance and Equipment Ministry of Education, East China Jiaotong University – sequence: 5 givenname: Xuanjun surname: Huang fullname: Huang, Xuanjun organization: Key Laboratory of Conveyance and Equipment Ministry of Education, East China Jiaotong University |
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| CitedBy_id | crossref_primary_10_3390_lubricants13050207 crossref_primary_10_3390_en17235879 crossref_primary_10_1016_j_engstruct_2024_118024 crossref_primary_10_1007_s00707_023_03734_9 crossref_primary_10_1080_10402004_2023_2254348 crossref_primary_10_1108_ILT_10_2024_0375 |
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| Keywords | Thermohydrodynamics Optimization methods Inversion technology Journal bearing |
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| SubjectTerms | Computational Mathematics and Numerical Analysis Engineering Engineering Design Errors Genetic algorithms Grooves Journal bearings Leakage Model accuracy Multiple objective analysis Optimization Pareto optimization Pareto optimum Prediction models Quadratic programming Research Paper Theoretical and Applied Mechanics Thermohydrodynamics |
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| Title | Experimental verification: a multi-objective optimization method for inversion technology of hydrodynamic journal bearings |
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