Machine learning calculation model for hydrodynamic lubrication characteristics of a miter gate bottom pivot
Authors:
- Xiang Xu,
- Zhengguo Guan,
- Zhixiong Li,
- Maciej Sulowicz,
- Grzegorz Królczyk,
- Tiancan Dai,
- Xinze Zhao
Abstract
The bottom pivot is a vital support device in the miter gate but is often subject to poor lubrication and wear failures. Calculating the hydrodynamic lubrication characteristics of the bottom pivot is a complex three-dimensional (3D) problem, and most of existing models adopt simplified assumptions to reduce the calculation difficulty. To solve this issue, this work develops a 3D model to calculate the hydrodynamic lubrication characteristics of the miter gate bottom pivot. The finite difference method is used to solve the oil film thickness and pressure distribution based on the spherical coordinates Reynolds equation. The component forces in three directions are calculated from the pressure distribution and compared with the theoretical values to generate the calculation difference. Then, the genetic algorithm (GA) is used to minimize the difference to determine the optimal initial parameters for the 3D model. The analysis results show that the calculation accuracy can be significantly improved by using the optimal initial model parameters. When our initial pressure is 5.64MPa, the results meet the engineering accuracy requirements.
- Record ID
- CUT51429c5eea8f4827a15af39304ae4841
- Publication categories
- ;
- Author
- Journal series
- Engineering Analysis with Boundary Elements, ISSN 0955-7997, e-ISSN 1873-197X
- Issue year
- 2022
- Vol
- 142
- Pages
- [1-9]
- Other elements of collation
- rys.; schem.; tab.; wykr.; Bibliografia (na s.) - 9; Bibliografia (liczba pozycji) - 19; Oznaczenie streszczenia - Abstr.; Numeracja w czasopiśmie - Vol. 142
- Keywords in English
- miter gate, bottom pivot, hydrodynamic lubrication, genetic algorithm
- ASJC Classification
- ; ; ;
- DOI
- DOI:10.1016/j.enganabound.2022.05.024 Opening in a new tab
- URL
- https://www.sciencedirect.com/science/article/abs/pii/S0955799722001801 Opening in a new tab
- Related project
- Nowatorska, sterowana danymi, oparta na inteligentnym prognozowaniu platforma do złożonych systemów cyber-fizycznych w kierunku przyszłości. . Project leader at PK: , ,
- Language
- eng (en) English
- Score (nominal)
- 100
- Score source
- journalList
- Score
- Publication indicators
- Citation count
- 1
- Additional fields
- Indeksowana w: Web of Science, Scopus
- Uniform Resource Identifier
- https://cris.pk.edu.pl/info/article/CUT51429c5eea8f4827a15af39304ae4841/
- URN
urn:pkr-prod:CUT51429c5eea8f4827a15af39304ae4841
* presented citation count is obtained through Internet information analysis, and it is close to the number calculated by the Publish or PerishOpening in a new tab system.