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%0 Thesis
%A Wang, Yujun
%T Design of surface textures in journal bearings for optimizing operational performance
%I Rheinisch-Westfälische Technische Hochschule Aachen
%V Dissertation
%C Aachen
%M RWTH-2026-01315
%P 1 Online-Ressource : Illustrationen
%D 2026
%Z Veröffentlicht auf dem Publikationsserver der RWTH Aachen University
%Z Dissertation, Rheinisch-Westfälische Technische Hochschule Aachen, 2026
%X The growing demand for energy efficiency and power density in machinery requires journal bearings to have lower friction losses (FL) and higher load-carrying capacities (LCC). Surface textures on the sliding surface in a journal bearing have shown their promising results in both the reduction of FL and the improvement of LCC. However, the improper design of texture parameters is reported to be detrimental to both parameters. Although numerous studies have been conducted to apply surface textures into journal bearings, the method to properly design surface textures in journal bearings is primarily constrained by inadequate prediction models and trial-and-error design methods. Therefore, a validated design method of surface textures in journal bearings is becoming essential. This dissertation proposes a strategy to design surface textures in journal bearings with the aim of a higher LCC and a lower FL. The design strategy integrates three sub-models for textured journal bearings: the Navier-Stokes based mixedelasto hydrodynamic lubrication (mixed-EHL) model for the accurate prediction of LCC and FL, the machine learning-based surrogate model for the efficient prediction of LCC and FL, and the multi-objective optimization model to determine the design parameters of textures to achieve a higher LCC and a lower FL. The results show that the proposed design strategy works successfully for different lubrication conditions of journal bearings. With the optimized texture design parameters, the FL is reduced by approximately 11.97
%F PUB:(DE-HGF)11
%9 Dissertation / PhD Thesis
%R 10.18154/RWTH-2026-01315
%U https://publications.rwth-aachen.de/record/1027247