Optimum design of one-dimensional journal bearings

McAllister, G. T.; Rohde, S. M.

doi:10.1007/bf00934646

Cited by 11 publications

(5 citation statements)

References 2 publications

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“…Rayleigh showed, using the calculus of variations, that the optimal load capacity is achieved with a step bearing shape 16) . Rohde and McAllister found the optimal shape of a 1D journal bearing analytically 17) . They developed an optimization algorithm which was based on distributed control theory.…”

Section: Introductionmentioning

confidence: 99%

A Unified Computational Approach to the Optimization of Surface Textures:One Dimensional Hydrodynamic Bearings

2010

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In tribological applications, surface textures are used to increase load capacity and reduce friction losses in hydrodynamic lubricated contacts. However, there is no systematic, efficient and general approach allowing for the optimization of surface texture shapes to give an optimal performance. The work conducted is, in most cases, by "trial and error", i.e. changes are introduced and their effects studied. This is time consuming and inefficient. In this paper, a unified computational approach to the optimization of texture shapes in bearings is proposed. The approach aims at finding the optimal texture shape that supports the maximum load and/or minimizes friction losses in one dimensional hydrodynamic bearings. The texture shape optimization problem is transformed into a nonlinearly constrained mathematical programming problem with general constraints that can be solved using optimal control software. Load-carrying capacity or friction force of a bearing becomes an objective functional that is maximized or minimized, subject to: (i) any Reynolds equations given by first order ordinary differential equations, (ii) pressure boundary conditions and (iii) functions/parameters that define the surface texture shape. This newly developed approach is demonstrated on examples of parallel textured hydrodynamic bearings. The effects of non-Newtonian fluids, cavitation and viscosity varying with temperature are considered.

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Section: Introductionmentioning

confidence: 99%

A Unified Computational Approach to the Optimization of Surface Textures:One Dimensional Hydrodynamic Bearings

2010

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“…The ever-increasing demand of lower initial and running costs for bearings, to withstand competition, has prompted engineers to apply optimization methods in bearing design. To reduce computational effort in optimization, a number of researchers [1][2][3][4] have optimized bearing dimensions using only one-dimensional cases, which are far from reality. McAllister and Rohde [2] optimized the load-carrying capacity of onedimensional journal bearings for a given minimum film thickness.…”

Section: Introductionmentioning

confidence: 99%

“…To reduce computational effort in optimization, a number of researchers [1][2][3][4] have optimized bearing dimensions using only one-dimensional cases, which are far from reality. McAllister and Rohde [2] optimized the load-carrying capacity of onedimensional journal bearings for a given minimum film thickness. They used a long bearing approximation, which is inaccurate in most practical design ranges.…”

Section: Introductionmentioning

confidence: 99%

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Multiobjective optimization of a journal bearing using the Pareto optimality concept

Hirani

2004

Proceedings of the Institution of Mechanical Engineers, Part J:

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This paper deals with multiobjective optimization (minimization of temperature rise, minimization of oil feed flow, minimization of power loss) and discrete design variables (lubricant viscosity, radial clearance, length-diameter ratio) related to the design of a journal bearing. The aim of this paper is to show the sensitivity of radial clearance, oil viscosity and length-diameter ratio on bearing power loss and oil flow. The paper attempts to remove the difficulty of selecting the weighting factor in multiobjective journal bearing optimization problems.The optimization model is based on a hybrid solution scheme for journal bearings. The objective of bearing optimization is to minimize a linear combination (weighted sum) of power loss and oil flow. Constraints are imposed on the maximum fluid film pressure, minimum film thickness, maximum temperature rise and critical speed. A generic algorithm is used as the optimization tool with a penalty to those solutions that violate constraints. The three-level Taguchi method is used to measure the effect of design variables on the optimum solution. The Pareto-optimal set approach is adapted to segregate the superior design vectors.The results of power loss, oil flow, temperature rise, maximum pressure and minimum film thickness are presented in tabular and graphical form for comparative study. Three journal bearing design examples are included, demonstrating the effectiveness of the proposed method. NOTATIONC radial clearance (m) C p specific heat of the lubricant (J/kg 8C) D journal diameter (m) F fluid film force (N) Friction friction force (N) g gravitational acceleration (m/s 2 ) g o , g l pressure correction factors for Ocvirk's and Sommerfeld's bearings respectively h film thickness (mm) H, H p, max non-dimensional film thicknesses L length of the journal (m) n s journal rotational speed (r/s) objf objective function p film pressure (Pa) p max maximum allowable film pressure (Pa) Q supply lubricant quantity (leakage flowrate)(m 3 /s) R radius of the journal (m) S Sommerfeld number DT fluid film temperature rise ( 8C) U journal velocity (m/s) W load applied to bearing (N) X vector of design variables z coordinate of axial direction (m) a 1 , a 2 weighting factors b 1 , b 2 scaling factors e eccentricity ratio y O, max , y S, max location of maximum pressure for Ocvirk's and Sommerfield's bearings (rad) L length-diameter ratio m average viscosity of the lubricant (Pa s) r density of the lubricant (kg/m 3 ) o angular velocity of the journal (s À1 ) o cr whirl onset velocity (s À1 )The MS was

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“…It was found that the deviation of final product is eliminated to a great extent. McAllister and Rohde [24] optimized the load-carrying capacity of one-dimensional journal bearings for a given minimum film thickness by using a long bearing approximation, which is inaccurate in most practical design ranges. Hashimoto [25] presented an optimum study for high speed short journal bearings using successive quadratic programming.…”

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confidence: 99%