Influence of surface roughness effects on the performance of non-recessed hybrid journal bearings

Nagaraju, T. Vamsi; Sharma, Satish C.; Jain, S. C.

doi:10.1016/s0301-679x(02)00037-3

Cited by 25 publications

(18 citation statements)

References 28 publications

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“…Using this pressure field, the journal centre equilibrium position for the specified vertical load is established as explained by Nagaraju et. al [10]. Once the journal centre equilibrium position is established, the results for the objective functions such as minimum fluid-film thickness, frictional torque and critical journal mass of the bearing are computed using the following expressions.…”

Section: Boundary Conditionsmentioning

confidence: 99%

“…Nodes situated on the external boundary of the bearing have zero pressure, At the trailing edge of the positive region, flow Equation The flow equation for capillary restrictor is expressed in non-dimensional form as[10] …”

mentioning

confidence: 99%

“…Issue VII, July 2019-Available at www.ijraset.com 200 ©IJRASET: All Rights are ReservedA. Average Reynolds EquationThe average Reynolds equation governing the laminar flow of an incompressible, Newtonian lubricant in the clearance space between rough surface of journal and bearing in non-dimensional form is written as[10] …”

mentioning

confidence: 99%

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Optimization of Hybrid Journal Bearing using Artificial Neural Network and Genetic Algorithm

Ravindra¹

2019

IJRASET

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A rapid and globally convergent predictive tool for optimization of capillary compensated hole-entry hybrid journal bearing having transverse roughness pattern is developed using Artificial Neural Network (ANN) and Multi Objective Genetic Algorithm (MOGA). ANN is trained to compute the objective functions for the multi-objective GA optimization problem of hybrid journal bearing. Five most important parameters such as supply pressure, restrictor design parameter, dynamic viscosity of oil, surface roughness characteristics of opposing surfaces (i.e. variance ratio) and roughness pattern parameter are selected as design variables. Minimum fluid film thickness, frictional torque and critical journal mass of capillary compensated hybrid journal bearing are selected as objective functions. The optimum values of design variables are obtained by interfacing multiobjective GA with ANN. The optimization goal is to maximize the minimum oil film thickness and critical journal mass and to minimize frictional torque on journal surface as three objectives and is achieved using a Pareto optimal front. Achievement of regression value above 99% and close agreement between expected and predicted value of all the three output functions shows the suitability of ANN in Multi-objective Genetic Algorithm optimization problem.

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Section: Boundary Conditionsmentioning

confidence: 99%

mentioning

confidence: 99%

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Optimization of Hybrid Journal Bearing using Artificial Neural Network and Genetic Algorithm

Ravindra¹

2019

IJRASET

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“…The non-dimensional form of average fluid-film thickness, T h , in fully lubricated ( ) regions can be expressed as The temperature viscosity relation is defined by an exponential law and is expressed in nondimensional form [11] as…”

Section: B Average Fluid-film Thicknessmentioning

confidence: 99%

“…Ramesh et al [10] investigated the combined influence of 3D surface roughness and thermal effects on performance of a submerged oil journal bearing and they assumed average cross-film viscosity variation in their study. Recently, Nagaraju et al [11,12] demonstrated the individual as well as the combined influence of surface roughness and bearing flexibility on the performance of hybrid journal bearing using Patir and Cheng's average flow model. Later, Nagaraju et al [13] and Sharma et al [14] modified the average Reynolds equation to include the viscosity variation across and along the fluid-film and investigated non-Newtonian behavior of lubricant and thermal effects on journal bearing performance.…”

Section: Introductionmentioning

confidence: 99%

Thermohydrodynamic Performance of a Journal Bearing With 3d-Surface Roughness and Fluid Inertia Effects

Prasad¹,

Nagaraju²,

Sagar³

2012

IJARME

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This theoretical work describe the combined influence of surface roughness, thermal and fluid-inertia effects on performance characteristics of hydrodynamic journal bearing. The average Reynolds equation that modified to include the surface roughness, viscosity variation due to temperature rise in lubricant fluid-film and fluid-inertia is used to obtain pressure field in the fluid-film. The matched solutions of modified average Reynolds, energy and conduction equations are obtained using finite element method and appropriate iterative schemes. The effects of surface roughness parameter, roughness orientation, and roughness characteristics of opposing surfaces on circumferential fluid-film pressure distribution, load carrying capacity and stability threshold speed of the bearing are studied by considering thermal and fluid-inertia effects.

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On the design and development of hybrid journal bearings: a review

2005

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This paper presents a comprehensive review of developments in the design and application of hydrostatic and hybrid journal bearing systems during the last few decades. Revolutionary changes have taken place in the applications of hydrostatic and hybrid journal bearings, from very low‐speed radar to very high‐speed turbo‐machinery and ultra‐precision machine tools requiring high stiffness to improve accuracy. Hydrostatic and hybrid bearings are of interest because of their potential at very high operating speed and heavy load‐carrying capacity. This paper also outlines the analyses done of these types of journal bearings in practical application, which has led to improved bearing design. This review critically discusses the parameters that significantly affect the static and dynamic performance of a journal bearing. This review includes coverage of recent publications in the literature pertaining to hydrostatic and hybrid journal bearings focusing on the influence of parameters such as bearing geometry, supply pressure, flow control devices, fluid compressibility, fluid inertia, journal misalignment, bearing flexibility, surface roughness, and thermal effects. Copyright © 2006 John Wiley & Sons, Ltd.

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Influence of surface roughness effects on the performance of non-recessed hybrid journal bearings

Cited by 25 publications

References 28 publications

Optimization of Hybrid Journal Bearing using Artificial Neural Network and Genetic Algorithm

Optimization of Hybrid Journal Bearing using Artificial Neural Network and Genetic Algorithm

Thermohydrodynamic Performance of a Journal Bearing With 3d-Surface Roughness and Fluid Inertia Effects

On the design and development of hybrid journal bearings: a review

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