Design optimization of vein-bionic textured hydrodynamic journal bearing using genetic algorithm

Abstract

Surface texturing is an efficient approach for boosting the performance of bearing. In this paper, a vein bionic texture has been applied to the surface of hydrodynamic journal bearing in order to improve its bearing performance. The bionic texture is inspired by the pattern of a peepal (ficus religiosa) leaf and optimized by a bio-inspired genetic algorithm technique. In this study, the use of bionic texture without GA optimization has been observed to increases the value of stability parameter by 13.08% and reduces the value of friction torque by 21.17%, while the use of the GA-optimized vein-bionic texture resulted in a significant improvement in bearing performance, with the stability parameter increases by up to 18.24% and friction torque being reduced by up to 46.66%. This class of surface texture improves both static and dynamic characteristics of the bearing. Further, the bifurcation diagram has been plotted to examine the system’s stability. The findings of this study should prove useful for rotor-dynamic researcher in their efforts to stabilize systems with the use of GA-optimized vein-bionic textured journal bearings. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.