Abstract
The performance of air bearing is highly influenced by the geometrical parameters of its restrictor. This study aims to maximize the load-carrying capacity and stiffness of air bearing, and minimize its volume flow rate by optimizing the geometrical parameters of restrictor. To facilitate the calculation of air bearing performance, a parametric computational fluid dynamics model is developed. Then, it is combined with multiobjective optimization genetic algorithm to search the Pareto optimal solutions. Furthermore, as a case study, the optimal design of an annular thrust air bearing is implemented. The stiffness of air bearing is improved 38.5%, the load-carrying capacity is improved 33.9%, and the volume flow rate is declined 19.6%, which are finally validated by experiments. It proves the reliability of proposed parametric computational fluid dynamics model and genetic optimization algorithm.
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Schedule a callMore From: Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology
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