On the shape optimization of self-adaptive grooves
Document Type
Article
Publication Date
1-1-2011
Abstract
Microscale mechanical self-adaptive bearings are a recent development in the field that offer promising features such as enhanced load-carrying capacity compared to conventional bearings. This study aims to improve the load-carrying capacity of these bearings by introducing novel deformable groove designs. The objective is to find the optimum groove's top surface shape that maximizes the load-carrying support. Assuming that the thickness can vary along the groove's length, three different thickness patterns including constant, linear, and spline are considered. A hybrid optimization algorithm based on the harmony search (HS) algorithm and sequential quadratic programming (SQP) is utilized to find the optimum shape for each thickness pattern. A benchmark problem is considered to show the performance of new designs. Results show that the optimally designed grooves with spline thickness profile can have load-carrying capacities up to 45% larger than the original ones. © 2011 Society of Tribologists and Lubrication Engineers.
Publication Source (Journal or Book title)
Tribology Transactions
First Page
256
Last Page
264
Recommended Citation
Fesanghary, M., & Khonsari, M. (2011). On the shape optimization of self-adaptive grooves. Tribology Transactions, 54 (2), 256-264. https://doi.org/10.1080/10402004.2010.539772