Topology and Shape Optimization of Hydrodynamically–Lubricated Bearings for Enhanced Load-Carrying Capacity

Bearings are basic and essential components of nearly all machinery. They must be designed to work under different loads, speeds, and environments. Of all the performance parameters, load-carrying capacity (LCC) is often the most crucial design constraint. The objective of this research is to investigate different design methodologies that significantly improve the LCC of liquid-lubricated bearings. This goal can be achieved by either altering the surface texture or the bearing geometrical configuration. The methodology used here is based on mathematical topological/shape optimization algorithms. These methods can effectively improve the design performance while avoiding time-consuming trial-and-error design techniques. The first category of design studied is a micro-scale mechanical self-adaptive type which can provide “flexible surface texturing”. An accurate 3D model based on the classic plate theory and thin film lubrication is developed and a shape optimization analysis is carried out. Special attention is given to the cavitation phenomena and its numerical analysis. Also proposed is a numerical procedure to improve the convergence rate and stability of the Elrod cavitation algorithm. The idea of using self-adaptive mechanism to improve LCC is also adopted for thrust bearings. Novel flexible-pad thrust bearing designs that provide an optimum load-responsive mechanism are presented and an accurate multi-physics model that considers the coupled mechanism between the lubricant pressure and the pad deformation is developed. The optimum shapes for different bearing geometries are given and a detailed design guideline is provided for optimum performance. The second category of design studied focuses on bearing geometrical configuration. The optimum shape of finite width sectorial sliders, which is an open problem in the field, is determined for the first time in this research using topological optimization algorithms. Also three suboptimum solutions for special cases of 2D step profile, constant film thickness in the radial direction and constant film depth with quadrilateral shape are presented. These configurations are particularly attractive because they can be easily manufactured. The optimum shape of bearings with periodic surface grooves is also determined in this research. It is shown that the optimum shape is dependent to the aspect ratio of the grooves and it can change from elongated “heart-like” shapes to spiral-like shapes. A series of laboratory tests to authenticate the theoretical development is carried out. Results show very good agreement with the theory validating the accuracy of the model. Finally, the optimum geometry of spiral grooves that provide the highest LCC in liquid-lubricated parallel flat surface bearings is determined and a detailed design guideline is provided. The thermal effects are also considered and an approximate thermo-hydrodynamic model is developed for a range of seal geometries and operating conditions

Convergence versus diversity in multiobjective optimization

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI linkConvergence and diversity are two main goals in multiobjective optimization. In literature, most existing multiobjective optimization evolutionary algorithms (MOEAs) adopt a convergence-first-and-diversity-second environmental selection which prefers nondominated solutions to dominated ones, as is the case with the popular nondominated sorting based selection method. While convergence-first sorting has continuously shown effectiveness for handling a variety of problems, it faces challenges to maintain well population diversity due to the overemphasis of convergence. In this paper, we propose a general diversity-first sorting method for multiobjective optimization. Based on the method, a new MOEA, called DBEA, is then introduced. DBEA is compared with the recently-developed nondominated sorting genetic algorithm III (NSGA-III) on different problems. Experimental studies show that the diversity-first method has great potential for diversity maintenance and is very competitive for many-objective optimization

A Pareto-based multi-objective optimization algorithm to design energy-efficient shading devices

In this paper we address the problem of designing new energy-efficient static daylight devices that will surround the external windows of a residential building in Madrid. Shading devices can in fact largely influence solar gains in a building and improve thermal and lighting comforts by selectively intercepting the solar radiation and by reducing the undesirable glare. A proper shading device can therefore significantly increase the thermal performance of a building by reducing its energy demand in different climate conditions. In order to identify the set of optimal shading devices that allow a low energy consumption of the dwelling while maintaining high levels of thermal and lighting comfort for the inhabitants we derive a multi-objective optimization methodology based on Harmony Search and Pareto front approaches. The results show that the multi-objective approach here proposed is an effective procedure in designing energy efficient shading devices when a large set of conflicting objectives characterizes the performance of the proposed solutions. (C) 2016 Elsevier Ltd. All rights reserved

A robust stochastic approach for design optimization of air cooled heat exchangers

This study investigates the use of global sensitivity analysis (GSA) and harmony search (HS) algorithm for design optimization of air cooled heat exchangers (ACHEs) from the economic viewpoint. In order to reduce the size of the optimization problem, GSA is performed to examine the effect of the design parameters and to identify the non-influential parameters. Then HS is applied to optimize influential parameters. To demonstrate the ability of the HS algorithm a case study is considered and for validation purpose, genetic algorithm (GA) is also applied to this case study. Results reveal that the HS algorithm converges to optimum solution with higher accuracy in comparison with GA.Air cooled heat exchanger Harmony search algorithm Global sensitivity analysis Optimization