Geometry optimization of textured 3-D micro - Thrust bearings

Papadopoulos, CI; Efstathiou, EE; Nikolakopoulos, PG; Kaiktsis, L

dc.contributor.author	Papadopoulos, CI	en
dc.contributor.author	Efstathiou, EE	en
dc.contributor.author	Nikolakopoulos, PG	en
dc.contributor.author	Kaiktsis, L	en
dc.date.accessioned	2014-03-01T02:53:18Z
dc.date.available	2014-03-01T02:53:18Z
dc.date.issued	2011	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/36219
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-84865480195&partnerID=40&md5=23f99b70292a8cdc9c12adaa95955f2c	en
dc.subject	3-D micro-thrust bearings	en
dc.subject	Multiobjective optimization	en
dc.subject	Navier-Stokes equations	en
dc.subject	Rectangular texturing	en
dc.title	Geometry optimization of textured 3-D micro - Thrust bearings	en
heal.type	conferenceItem	en
heal.publicationDate	2011	en
heal.abstract	The paper presents an optimization study of the geometry of three-dimensional micro-thrust bearings, in a wide range of convergence ratios. The optimization goal is the maximization of the bearing load carrying capacity. The bearings are modeled as microchannels, consisting of a smooth moving wall (rotor), and a stationary wall (stator) with partial periodic rectangular texturing. The flow field is calculated from the numerical solution of the Navier-Stokes equations for incompressible isothermal flow; processing of the results yields the bearing load capacity and friction coefficient. The geometry of the textured channel is defined parametrically for several width-tolength ratios. Optimal texturing geometries are obtained by utilizing an optimization tool based on genetic algorithms, which is coupled to the CFD code. Here, the design variables define the bearing geometry and convergence ratio. To minimize the computational cost, a multiobjective approach is proposed, consisting in the simultaneous maximization of the load carrying capacity and minimization of the bearing convergence ratio. The optimal solutions, identified based on the concept of Pareto dominance, are equivalent to those of singleobjective optimization problems at different convergence ratio values. The present results demonstrate that the characteristics of the optimal texturing patterns depend strongly on both the convergence ratio and the width-to-length ratio. Further, the optimal load carrying capacity increases at increasing convergence ratio, up to an optimal value, identified by the optimization procedure. Finally, proper surface texturing provides substantial load carrying capacity even for parallel or slightly diverging bearings. Based on the present results, we propose simple formulas for the design of textured micro-thrust bearings. Copyright © 2011 by ASME.	en
heal.journalName	Proceedings of the ASME Turbo Expo	en
dc.identifier.volume	3	en
dc.identifier.spage	801	en
dc.identifier.epage	810	en