By Xiangju Zhang, Chaglin Gui
The inner combustion is frequent as an influence resource in engineering. because the calls for positioned upon engines have elevated, tribology has come to play an more and more vital position of their development.This ebook is an inventive mixture of clever layout know-how and the tribological layout of engines: engine tribology, details technology, man made intelligence, non numerical algorithms, glossy layout know-how and dynamics to suggest new method and know-how for tribological engine layout. It not just provides a good method of l engine layout but additionally explores a brand new trend for examine and l layout method. Â· a vital reference for the layout of greater and effective enginesÂ· Proposes new concepts for tribological engine designÂ· Combines complex layout applied sciences with conventional tribological layout tools
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Extra resources for An Intelligent System for Engine Tribological Design, Volume 46 (Tribology and Interface Engineering)
Population size is one of the most important parameters. If the population size is too small, the GAs may converge to a local minimum. If the population size is too large, the GAs may waste computational resources, which means that the time for an improvement is very long. For the GAs with a constant population size, the most common sizes of population vary from 50 individuals to 500. 01. 04. When used in engine tribological design problems, GAs encode the potential design solutions into binary gene strings and form a gene population.
Chromosomes), which can be reproduced, crossed, or mutated to enable the creature population to propagate, evolve, or degenerate. , the fittest creatures in a population have more opportunities to survive and reproduce new offspring than others. All the new offspring make up a new generation, which will evolve continually under the above principles. The GAs was first developed as an optimization algorithm by John Holland and his colleagues and students at Michigan University^^^l Genetic algorithms simulate the evolutionary mechanism of living organisms.
S. ). Expert systems in engineering applications. Berlin: Springer-Ver lag, 1993 12. C. Shakeri, I. Deif, P. Katragadda, et al.. Intelligent design system for design automation. Intelligent systems in Design and manufacturing III B. Gopalakrishnan and A. ), Boston: SPLE, 2000, pp 2735 Engine Tribological Design Methodology and Intelligent System 35 13. F. Kimura. Architecture and implementation subgroup—summary of the workshop discussion. Intelligent CAD, III,, H. Yoshikawa, F. Arbab, and T. , 1991, pp 43-49 14.
An Intelligent System for Engine Tribological Design, Volume 46 (Tribology and Interface Engineering) by Xiangju Zhang, Chaglin Gui