This thesis investigates the use of genetic algorithms to optimize the shape of an ungrooved fluid-film journal bearing under steady load and steady speed so that it can carry the maximum possible load while constrained to maintaining an adequate minimum film thickness. The shape of the bearing sleeve is assumed to vary only in the radial direction, and the shape is represented by linear interpolation of three film thickness design specifications along the bearing sleeve. Each set of film thickness specifications in the design space is encoded into a binary string called a chromosome, and a set of chromosomes makes up a current generation. The bearing load is calculated for each chromosome, and the genetic algorithm creates a new generation based on these loads using elitism selection and chromosome crossover and mutation operators. Several case studies are presented to investigate the effect of bearing geometric specifications on the resulting optimal shape. For a given bearing diameter and bearing length, a random generation of chromosomes is first constructed. Using recommended chromosome crossover and mutation probabilities, it is shown that randomly created starting sets will eventually converge to a common shape, suggesting that a global optimum may have been achieved. Additional parametric studies show that the load results are dependent upon the mutation operator to achieve global optimums. Further comparisons show that the load carried by the optimal shape bearing can be much greater than that carried by a conventional cylindrical bearing.
Library of Congress Subject Headings
Fluid-film bearings; Journal bearings--Mathematical models
Department, Program, or Center
Mechanical Engineering (KGCOE)
Eshkabilov, Sulaymon, "Optimal shape design of steadily-loaded journal bearings using genetic algorithms" (2001). Thesis. Rochester Institute of Technology. Accessed from
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