The tribological characteristic of journal bearing systems can be enhanced with the integrating of textures in the contact interfaces, or using the lubricating effect of non-Newtonian fluids. In this study, the combined effects of bearing surface texturing and non-Newtonian lubricants behavior, using micropolar fluid model, on static characteristics of hydrodynamic circular journal bearings of finite length are highlighted. The modified Reynolds equation of micropolar lubrication theory is solved using finite differences scheme and Elrod's mass conservation algorithm, taking into account the presence of the cylindrical texture shape on full and optimum bearing surfaces. The optimization textured area is carried out through particle swarm optimization algorithm, in order to increase the load lifting capacity. Preliminary results are in good agreement with the reference ones, and present an enhancement in the performances of micro-textured journal bearings (load carrying capacity and friction). The results suggest that texturing the bearing convergent zone significantly increases the load carrying capacity and reduce friction coefficient, while fully texturing causes bad performances. It is also shown that the micropolar fluids exhibit better performances for smooth journal bearings than a Newtonian fluid depending on the size of material characteristic length and the coupling number. The combined effects of fully surface textured with micropolar fluids reduce the performance of journal bearing, especially at lower eccentricity ratios. Considering the optimal arrangement of textures on the contact surface, a significant improvement in terms of load capacity and friction can be achieved, particularly at high eccentricity ratios, high material characteristic lengths and high values of the coupling numbers of micropolar fluids.

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This work describes the application of a multiobjective cuckoo search method for turbomachinery design optimization of an axial pump. Maximization of the total efficiency and minimization of the required net positive suction head of the pump are the two objective functions considered for the optimization problem. The optimization process is carried out on a range of imposed volumetric flow rates, with taking into account at each discretized radius between the hub and tip of the rotor: the profile camber, rotor wall thickness, angular deviation, and the solidity, regarded as geometrical constraints and nominal flow rate as mechanical constraint. Two strategies are proposed in order to solve the problem. In the first one, three forms of mono-objective model with two variables, total efficiency and net positive suction head, are considered. In the second one, a multiobjective model with nondominated sorting scheme is adopted. A comparative evaluation of results obtained from the proposed approach with those of a reference machine and genetic algorithm allowed us to validate the present work.

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Turbomachinery design is a complex problem which requires a lot of experience. The procedure may be speed up by the development of new numerical tools and optimization techniques. The latter rely on the parameterization of the geometry, a model to assess the performance of a given geometry and the definition of an objective functions and constraints to compare solutions. In order to improve the reference machine performance, two formulations including the off-design have been developed. The first one is the maximization of the total nominal efficiency. The second one consists to maximize the operation area under the efficiency curve. In this paper five optimization methods have been assessed for axial pump design: Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Cuckoo Search (CS), Teaching Learning Based Optimization (TLBO) and Sequential Linear Programming (SLP). Four non-intrusive methods and the latter intrusive. Given an identical design point and set of constraints, each method proposed an optimized geometry. Their computing time, the optimized geometry and its performances (flow rate, head (H), efficiency (Á), net pressure suction head (NPSH) and power) are compared. Although all methods would converge to similar results and geometry, it is not the case when increasing the range and number of constraints. The discrepancy in geometries and the variety of results are presented and discussed. The computational fluid dynamics (CFD) is used to validate the reference and optimized machines performances in two main formulations. The most adapted approach is compared with some existing approaches in literature.