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ORIGINAL PAPER
MOGA-Based Optimization and Performance Comparison of Plain and Multi-Lobe Hydrodynamic Journal Bearings
Nitin B. Ahire 1
,
 
Dhiraj D. Deshmukh 1
 
 
 
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1
Department of Mechanical Engineering, METs Institute of Engineering, India
 
These authors had equal contribution to this work
 
 
Submission date: 2025-03-25
 
 
Final revision date: 2025-05-28
 
 
Acceptance date: 2025-09-10
 
 
Online publication date: 2025-12-05
 
 
Publication date: 2025-12-05
 
 
Corresponding author
Nitin B. Ahire   

Department of Mechanical Engineering, METs Institute of Engineering, Adgaon, 422003, Nashik, India
 
 
International Journal of Applied Mechanics and Engineering 2025;30(4):1-17
DOI: https://doi.org/10.59441/ijame/210536
 
 
Article (PDF)
References (24)
 
KEYWORDS
Stability
MOGA
HJBs
Load-Carrying Capacity
multi objective optimization
 
TOPICS
ABSTRACT
Choosing the best hydrodynamic journal bearing (HJB) involves a complex multi-objective optimization challenge that requires balancing load-carrying capacity (LCC), friction loss, oil film temperature increase, and dynamic stability. This research utilizes the multi-objective genetic algorithm (MOGA) to optimize plain, two-lobe, three-lobe, and four-lobe journal bearings under different operating conditions. The variable parameters of HJBs, including rotational speed, clearance, L/D ratio, and load, were taken into account. The optimization process utilized Pareto-based selection, simulated binary crossover, and Gaussian mutation techniques to determine the optimal bearing choice. The three-lobe bearing proved to be the most suitable choice based on its superior load-carrying capacity, minimal temperature rise, reduced friction loss, and overall stability performance. The findings reveal that the four-lobe bearing excels in LCC, while the plain and two-lobe bearings are advantageous for their simple design and low manufacturing costs. These results offer valuable insights for engineers and designers in choosing the most appropriate bearing type based on specific operational needs and performance trade-offs.
REFERENCES (24)
1.
Abass B., Ahmed S.Y. and Kadhim Z.H. (2023): Analysis and optimization of nanolubricated journal bearing under thermoelasto-hydrodynamic lubrication considering cavitation effect.– Tribology in Industry, vol.45, No.4, pp.618-633, https://doi.org/10.24874/ti.14....
CrossRef
 
Google Scholar
 
 
2.
Hirani H. (2004): Multiobjective optimization of a journal bearing using the Pareto optimality concept.– Proc. Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology, vol.218, No.4, pp.323-336, https://doi.org/10.1243/135065....
CrossRef
 
Google Scholar
 
 
3.
Bouyer J., Fillon M. and Pierre-Danos I. (2006): Influence of wear on the behavior of a two-lobe HJB subjected to numerous startups and stops.– Journal of Tribology - Transactions of the ASME, vol.129, No.2, pp.205-208, https://doi.org/10.1115/1.2401....
CrossRef
 
Google Scholar
 
 
4.
Chen Y., Feng J., Sun Y., Peng X., Dai Q. and Yu C. (2019): Effect of groove shape on the hydrodynamic lubrication of journal bearing considering cavitation.– Engineering Computations, vol.37, No.5, pp.1557-1576, https://doi.org/10.1108/EC-06-....
CrossRef
 
Google Scholar
 
 
5.
Pinkus O. (1956): Analysis of elliptical bearings.– Transactions of the American Society of Mechanical Engineers, vol.78, No.5, pp.965-972.
Google Scholar
 
 
6.
Dhande D.Y., Lanjewar G.H. and Pande D.W. (2018): Implementation of CFD-FSI technique coupled with response surface optimization method for analysis of three-lobe hydrodynamic journal bearing.– Journal of the Institution of Engineers (India): Series C, vol.100, No.6, pp.955-966, https://doi.org/10.1007/s40032....
CrossRef
 
Google Scholar
 
 
7.
Dhande D.Y., Pande D.W. and Lanjewar G.H. (2018): Numerical analysis of three-lobe HJB using CFD-GA technique based on response surface evaluation.– Journal of the Brazilian Society of Mechanical Sciences and Engineering, vol.40, No.8, https://doi.org/10.1007/s40430....
CrossRef
 
Google Scholar
 
 
8.
Biswas N., Chakraborti P. and Dhar P. (2016): Optimization of pressure and oil film thickness in multilobe bearing using response surface methodology and MOGA. – International Journal of Engineering Research and Applications, vol.6, No.3, pp.56-62.
Google Scholar
 
 
9.
Vinh D.P. (2022): Effect of loaded-pad thickness on the static behaviors of five-pad hydrodynamic journal bearings. – Journal of Science and Technology Issue on Information and Communications Technology, pp.15-19, DOI:10.31130/ud-jst.2022.503E.
CrossRef
 
Google Scholar
 
 
10.
Shinde A.B. and Pawar P.M. (2017): Multi-objective optimization of surface textured journal bearing by Taguchi-based Grey relational analysis. – Tribology International, vol.114, pp.349-357. https://doi.org/10.1016/j.trib....
CrossRef
 
Google Scholar
 
 
11.
Dang R.K., Goyal D., Chauhan A. and Dhami S.S. (2021): Numerical and experimental studies on performance enhancement of journal bearings using nanoparticles-based lubricants.– Archives of Computational Methods in Engineering, pp.1-29, https://doi.org/10.1007/s11831....
CrossRef
 
Google Scholar
 
 
12.
Yang J. and Palazzolo A. (2022): Deep convolutional autoencoder augmented CFD thermal analysis of bearings with inter pad groove mixing.– International Journal of Heat and Mass Transfer, vol.188, 122639, https://doi.org/10.1016/j.ijhe....
CrossRef
 
Google Scholar
 
 
13.
Yadav S.K., Khatri C.B., Kumar A. and Chaturvedi S. (2024): Optimization of twin grooved two-lobe textured hydrodynamic journal bearing design by using genetic algorithm.– Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, vol.238, No.20, pp.10205-10221, https://doi.org/10.1177/095440....
CrossRef
 
Google Scholar
 
 
14.
de Castro H.F., de Paula E.H. and Visnadi L.B. (2024): Reliability-based design optimization applied to a rotor supported by hydrodynamic bearings.– Machines, vol.12, No.4, p.233, https://doi.org/10.3390/machin....
CrossRef
 
Google Scholar
 
 
15.
Zhao J., Li Y., Li Y. and Liu J. (2025): Multi-objective optimization of tribological properties of diesel engine camshaft bearings. – Structural and Multidisciplinary Optimization, vol.68, No.1, pp.1-17, DOI:10.1007/s00158-024-03959-9.
CrossRef
 
Google Scholar
 
 
16.
Joy N.M. and Roy L. (2016): Determination of optimum configuration among different configurations of two-axial groove hydrodynamic bearings.– Proc. Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology, vol.230, No.9, pp.1071-1091, https://doi.org/10.1177/135065....
CrossRef
 
Google Scholar
 
 
17.
Bhagat C. and Roy L. (2014): Steady state thermo-hydrodynamic analysis of two-axial groove and multilobe hydrodynamic bearings. – Tribology in Industry, vol.36, No.4.
Google Scholar
 
 
18.
Das B.J. and Roy L. (2018): Analysis and comparison of steady-state performance characteristics of two-axial groove and multilobe hydrodynamic bearings lubricated with non-Newtonian fluids. – Proc. Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology, vol.232, No.12, pp.1581-1596.
Google Scholar
 
 
19.
Dewangan A., Bhagat S. and Jha V. (2016): Minimization of power loss in plain journal bearings using genetic algorithms. – International Journal of Applied Engineering Research, vol.11, No.3, pp.2093-2099.
Google Scholar
 
 
20.
Zhang Y., He L., Yang J., Zhu G., Jia X. and Yan W. (2021): Multi-objective optimization design of a novel integral squeeze film bearing damper.– Machines, vol.9, No.10, p.206, https://doi.org/10.3390/machin....
CrossRef
 
Google Scholar
 
 
21.
Shaltout M.L. and Hegazi H.A. (2021): Multi-objective design optimization of hydrodynamic journal bearings using a hybrid approach.– Industrial Lubrication and Tribology, vol.73, No.7, pp.1052-1060, https://doi.org/10.1108/ILT-05....
CrossRef
 
Google Scholar
 
 
22.
Roy L. and Kakoty S.K. (2014): Application of genetic algorithm in optimization of hydrodynamic bearings.– Advances in Intelligent Systems and Computing, pp.207-217, https://doi.org/10.1007/978-81....
CrossRef
 
Google Scholar
 
 
23.
Banerjee P., Karri R.R., Mukhopadhyay A. and Das P. (2021): Review of soft computing techniques for modeling, design, and prediction of wastewater removal performance. – Soft Computing Techniques in Solid Waste and Wastewater Management, pp.55-73, https://doi.org/10.1016/B978-0....
CrossRef
 
Google Scholar
 
 
24.
Deb K., Pratap A., Agarwal S. and Meyarivan T.A.M.T. (2002): A fast and elitist multiobjective genetic algorithm: NSGA-II. – IEEE Transactions on Evolutionary Computation, vol.6, No.2, pp.182-197.
Google Scholar
 
 
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