Using genetic algorithms for the optimal design of fluid journal bearing

Proceedings of the ASME Design Engineering Technical Conference

Volumn 7B-1999, Issue , 1999, Pages 3021-3027

  Lin, Yun Jeng ^a   Noah, Sherif T ^a  

^a Texas AandM University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; DESIGN; GENETIC ALGORITHMS; MATHEMATICAL PROGRAMMING; VIBRATIONS (MECHANICAL);

MULTIPARAMETERS; OBJECTIVE FUNCTIONS; OPTIMAL DESIGN; OPTIMAL PARAMETER; OPTIMIZATION TECHNIQUES; OPTIMUM SOLUTION; SINGLE PARAMETER; TRIAL AND ERROR;

JOURNAL BEARINGS;

EID: 85101138763     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1115/detc99-vib-8171     Document Type: Conference Paper

References (8)

1. Childs, D., 1993, Turbomachinery Rot or dynamics: Phenomena, Modeling, and Analysis, Wiley-Interscience, New York.
2. Goldberg, D. E., 1989, Genetic Algorithms in Search, Optimization, and Machine Learning, Reading, Addison-Wesley. MA.
3. Hashimoto, H., 1997, "Optimum Design of High Speed, Short Journal Bearings by Mathematical Programming," Tribology Transactions, Vol. 40, pp. 283-293.
4. Holland, J. H., 1975, Adaptation in Natural and Artificial Systems, The University of Michigan Press, Ann Arbor, MI.
5. McKee, C. A., and McKee, T. R., 1932, "Journal Bearing Friction in the Region of Thin Film Lubrication," SAE Journal, Vol. 31, pp. 371-377.
6. Pinkus, O., 1961, Theory of Hydrodynamic Lubrication, McGraw-Hill, New York.
7. Sternlicht, B., 1985, Mechanical Design and Systems Handbook, Second Edition, Sec. 12, McGraw-Hill, New York.
8. Szeri, A. Z., 1980, Tribology - Friction, Lubrication, and Wear, McGraw-Hill, New York.