Comprehensive design methodology for an engine journal bearing

Hirani, Harish; Athre, K.; Biswas, S.

doi:10.1243/1350650001543287

Cited by 23 publications

(14 citation statements)

References 28 publications

(47 reference statements)

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“…He considered rotating disks, journal bearings, pressure vessels, gears, beams with axial shock, shafts under transverse loads and torques, and devices having elastic contacts and load variations. A design procedure was suggested by Hirani et al (2000) for the journal bearing of an engine. The methodology was presented for choosing the bearing length and the diametral clearance by optimizing the minimum film thickness, the maximum temperature and the maximum pressure.…”

Section: Introductionmentioning

confidence: 99%

Optimal design of deep-groove ball bearings based on multitude of objectives using evolutionary algorithms

Tiwari

Chandran

2018

MMMS

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Purpose In optimum designs of deep-groove ball bearings (DDGBs), an extended service life is one of the vital criteria. The life of a bearing depends on several factors. The purpose of this paper is to sequentially optimize three prime objectives for DDGB, i.e. the dynamic capacity (Cd), the maximum bearing temperature (Tmax) and the elasto-hydrodynamic minimum film thickness (Hmin). Design/methodology/approach For solving constrained non-linear optimization formulations with multitude of objectives, an optimal design methodology has been put forth with the help of artificial bee colony algorithms. A study on the constraint violation has been carried out. By the Monte Carlo simulation method, a sensitivity investigation of diverse design variables has been done to examine variations in three objective functions and violation of constraints. Findings Excellent improvement in the dynamic capacity (Cd), the maximum bearing temperature (Tmax) and the elasto-hydrodynamic minimum film thickness (Hmin) have been found in optimized bearing designs. Originality/value Ball bearing design has been done based on multi-discipline objectives that are based on strength, tribology and thermal consideration. This type of design is essential in practical scenario where these physical phenomena will be present simultaneously.

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Section: Introductionmentioning

confidence: 99%

Optimal design of deep-groove ball bearings based on multitude of objectives using evolutionary algorithms

Tiwari

Chandran

2018

MMMS

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“…GA is a popular metaheuristics algorithm which has been broadly applied to solve various design optimization problems and proven to be successful in finding the global best than traditional methods. These include the design optimization of machine elements such as gears [1], gearbox [2], journal bearing [3], magnetic thrust bearing [4], rolling element bearing [5], and automotive wheel bearing unit [6]. Swarm intelligence is another important concept in many recent metaheuristics algorithms such as particle swarm optimization, firefly algorithm, artificial bee colony algorithm, and cuckoo search.…”

Section: Introductionmentioning

confidence: 99%

Multiobjective Optimization Method Based on Adaptive Parameter Harmony Search Algorithm

Sabarinath¹,

Thansekhar²,

Saravanan³

2015

Journal of Applied Mathematics

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The present trend in industries is to improve the techniques currently used in design and manufacture of products in order to meet the challenges of the competitive market. The crucial task nowadays is to find the optimal design and machining parameters so as to minimize the production costs. Design optimization involves more numbers of design variables with multiple and conflicting objectives, subjected to complex nonlinear constraints. The complexity of optimal design of machine elements creates the requirement for increasingly effective algorithms. Solving a nonlinear multiobjective optimization problem requires significant computing effort. From the literature it is evident that metaheuristic algorithms are performing better in dealing with multiobjective optimization. In this paper, we extend the recently developed parameter adaptive harmony search algorithm to solve multiobjective design optimization problems using the weighted sum approach. To determine the best weightage set for this analysis, a performance index based on least average error is used to determine the index of each weightage set. The proposed approach is applied to solve a biobjective design optimization of disc brake problem and a newly formulated biobjective design optimization of helical spring problem. The results reveal that the proposed approach is performing better than other algorithms.

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“…These include gears, journal bearings, rotating discs, pressure vessels, shafts under bending and torsion, beams subjected to the longitudinal impact, and problems of the elastic contact and load distributions. Hirani et al [15] proposed a design methodology for an engine journal bearing. The procedure of selection of the diametral clearance and the bearing length was described by limiting the minimum film thickness, the maximum pressure, and the maximum temperature.…”

Section: Introductionmentioning

confidence: 99%

Development of an Optimum Design Methodology of Cylindrical Roller Bearings Using Genetic Algorithms

Kumar

Tiwari

Reddy

2008

International Journal for Computational Methods in Engineering

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In the design of cylindrical roller bearings, the long life is the one of the most important criterion. Bearing standards define the design space available to a designer for deciding internal geometries of the bearing. Based on the rated speed and loading conditions, the design has to satisfy constraints of geometry and strength. An optimum design methodology is needed to achieve this objective. Since the fatigue life is directly proportional to the basic dynamic capacity, for the present case it has been chosen as objective function. It has been optimized by using a constrained non-linear formulation with real-coded genetic algorithms. Design variables include four geometrical parameters: the bearing pitch diameter, the diameter of the roller, the effective length of the roller, and the number of rollers. In addition to these another five design constraint constants are included, which indirectly affect the basic dynamic capacity of cylindrical roller bearings. The five design constraint constants have been given bounds based on the parametric studies through initial optimization runs. The effective length of the roller is taken corresponding to the standard roller diameter, which has standard discrete dimensions. There is good agreement between the optimized and standard bearings in respect to the basic dynamic capacity of the bearing. A constraints violation study has been performed to assess the effectiveness of each of the constraints. A convergence study has been carried out to ensure the global optimum point in the design. A sensitivity analysis of various geometric design parameters has been performed to see changes in the basic dynamic capacity of the bearing, and results show that no geometric parameters have adverse affects.

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Comprehensive design methodology for an engine journal bearing

Cited by 23 publications

References 28 publications

Optimal design of deep-groove ball bearings based on multitude of objectives using evolutionary algorithms

Optimal design of deep-groove ball bearings based on multitude of objectives using evolutionary algorithms

Multiobjective Optimization Method Based on Adaptive Parameter Harmony Search Algorithm

Development of an Optimum Design Methodology of Cylindrical Roller Bearings Using Genetic Algorithms

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