Multiobjective optimization of thermohydrodynamic journal bearing using MOPSO algorithm

被引:10
作者
Akbarzadeh, P. [1 ]
Mikaeeli, S. Z. [1 ]
Rahimiyan, M. [2 ]
机构
[1] Shahrood Univ Technol, Sch Mech Engn, POB 3619995161, Shahrood, Iran
[2] Shahrood Univ Technol, Sch Elect & Robot Engn, Shahrood, Iran
关键词
Multiobjective particle swarm optimization; objective functions; Pareto front; journal bearing; thermohydrodynamic; GENETIC ALGORITHM; OPTIMUM DESIGN; HIGH-SPEED;
D O I
10.1177/1350650117724639
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
This article focuses on the use of multiobjective particle swarm optimization algorithm in combination with the thermohydrodynamic governing equations of fluid film (i.e. momentum and energy equations) in developing an efficient design method to optimize hydrodynamic partial pad journal bearings, for the first time. The governing equations are solved by using the central difference technique with a successive over relaxation scheme. In the simulation, the lubricant viscosity is changed with the temperature variation in whole fluid film. In this problem, the bearing power loss, the minimum oil film thickness, and the maximum oil temperature are selected as three objective functions and the radial clearance and length-to-diameter ratio are considered as two important design variables. The results of the objective functions are presented in tabular and Pareto-front curves. Further, the effect of bearing speed, bearing load, and inlet oil temperature on the mentioned objective functions is illustrated.
引用
收藏
页码:657 / 671
页数:15
相关论文
共 17 条
[1]   Numerical Study of Thermohydrodynamic Characteristics of Oil Tilting-Pad Journal Bearings with a Self-Pumping Fluid Flow Circulation [J].
Akbarzadeh, Pooria .
TRIBOLOGY TRANSACTIONS, 2015, 58 (01) :18-30
[2]   Optimal shape design of steadily loaded journal bearings using genetic algorithms [J].
Boedo, S ;
Eshkabilov, SL .
TRIBOLOGY TRANSACTIONS, 2003, 46 (01) :134-143
[3]  
Coello CAC, 2004, IEEE T EVOLUT COMPUT, V8, P256, DOI [10.1109/TEVC.2004.826067, 10.1109/tevc.2004.826067]
[4]  
EI-Sherbinyt M, 1984, TRIBOL INT, V17, P155
[5]  
Engelbrecht A.P, 2007, Computational Intelligence an Introduction, Vsecond
[6]   Design predictive tool and optimization of journal bearing using neural network model and multi-objective genetic algorithm [J].
Ghorbanian, J. ;
Ahmadi, M. ;
Soltani, R. .
SCIENTIA IRANICA, 2011, 18 (05) :1095-1105
[7]  
Gorasso L., 2015, PROC 9 IFTOMM INT C, V21, P1057
[8]   Improvement of operating characteristics of high-speed hydrodynamic journal bearings by optimum design: Part I - Formulation of methodology and its application to elliptical bearing design [J].
Hashimoto, H ;
Matsumoto, K .
JOURNAL OF TRIBOLOGY-TRANSACTIONS OF THE ASME, 2001, 123 (02) :305-312
[9]   Optimum design of high-speed, short journal bearings by mathematical programming [J].
Hashimoto, H .
TRIBOLOGY TRANSACTIONS, 1997, 40 (02) :283-293
[10]  
Havlik N, 2015, TURB TECHN C EXP MON