This article investigates the effect of bearing Location and length on the shaft life under multi-axial non-proportional loading. The goal of this study is to increase long shaft life by deciding best location for bearing and its length. Loading condition and shaft properties was assumed according to helicopter. The most common case for this study observed in tail rotor of the Helicopter. Tail rotor drive shaft depended on helicopter type consist of 3 to 5 sections due to high length. Normally these sections assumed identical for simple production but it is shown that using non-identical sections is more proper than the other one. Optimization of shaft life and mass with design variable of the bearing locations and length is performed by ANSYS Workbench software and it is observed that these design variables have a major effect in objective functions. In the next step, we optimize maximum bearing pressure by two new advance methods named Genetic algorithm (GA) and Particle swam algorithm (PSO) and compare these algorithm abilities.
| Published in | Science Discovery (Volume 3, Issue 3) |
| DOI | 10.11648/j.sd.20150303.11 |
| Page(s) | 17-24 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2015. Published by Science Publishing Group |
Multi-Axial Non-Proportional Loading, Strain Life, Stress Life, Multi-Objective Optimization, Genetic Algorithm, Particle Swam Algorithm
| [1] | Prasanth, K., Prabhu, S. (2014). Design optimization and analysis of an automotive manual transmission shaft using Titanium alloy (TI6AL4V), International Journal of Mechanical And Production Engineering, vol. 4, no. 2, p. 320-334. |
| [2] | Rangaswamy,T.Vijayarangan, S. (2005).Optimal Sizing and Stacking Sequence of Composite Drive Shafts, Materials Science. Materials Science, vol. 11, no. 2, p. 1392-1320. |
| [3] | Ooi, J.B. Wang, X. Lim, Y.P.Tan, K.Ch. (2013). 3Parametric Optimization of the Output Shaft of a Portal Axle using Finite Element Analysis. Materials Science, vol. 59, no. 10, p. 613-619. |
| [4] | Li, Q. Steven, G.P.Querin, O.M.Xie, Y.M. (2001). Stress based optimization of torsional shafts using an evolutionary procedure. International Journal of Solid and Structure, vol. 38, p. 5661-5677. |
| [5] | Fatemi, A.Plaseied, A.Khosrovaneh, A.K. (2005). Application of bi-linear log–log S–N model to strain-controlled fatigue data of aluminum alloys and its effect on life predictions. International Journal of Fatigue, vol. 27, p.1040-1050. |
| [6] | Rahman, M.M.Kadirgama, K.Noor, M.M.Rejab, R.M. (2009). Fatigue Life Prediction of Lower Suspension Arm Using Strain-Life Approach. European Journal of Scientific Research, vol. 30, no. 3, p. 437-450. |
| [7] | Pandura, M.A., Brizuela, C.A., Balderas, D.A. (2009). A comparison of genetic algorithms, particle swarm optimization and the diferential evolution method for the design of scannable circular antenna arrays, Progress In Electromagnetics Research, vol. 13, p. 171-186. |
| [8] | Zhijie, L., Xiaodong, L., Xiaodong, D. (2010Comperative research on particle swarm optimization and genetic algorithm,Computer and Information Science, vol. 3, no. 1, p. 120-127. |
| [9] | Panda, S., Padhy, N.P. (2008). Comparison of particle swarm optimization and genetic algorithm for FACTS-based controller gesign, Applied Soft Computing, vol. 8, p. 1418-1427. |
| [10] | Lindsey, J., Fatemi, A. (2008). Applicability of constant amplitude fatigue data to life predictions under variable amplitude service loading, Recent Advances in Mechanical Engineering Applications, ISBN: 978-960-474-345-2. |
| [11] | Li, B., Reis, L.Freitas, M. (2006). Simulation of cyclic stress/strain evolutions for multiaxial fatigue life predicti, International Journal of Fatigue, vol. 28, p. 451-458. |
| [12] | J. Shigley, E. Gordon, R. Mischke, Mechanical engineering design, McGraw-hill, 2004. |
APA Style
Mohammad Baharvand, Mohammad Pourmohammadi, Mehran Felfeli. (2015). Multi Objective Optimization of Long Hollow Simple Drive Shaft Under Multi-axial Non-Proportional Loading. Science Discovery, 3(3), 17-24. https://doi.org/10.11648/j.sd.20150303.11
ACS Style
Mohammad Baharvand; Mohammad Pourmohammadi; Mehran Felfeli. Multi Objective Optimization of Long Hollow Simple Drive Shaft Under Multi-axial Non-Proportional Loading. Sci. Discov. 2015, 3(3), 17-24. doi: 10.11648/j.sd.20150303.11
AMA Style
Mohammad Baharvand, Mohammad Pourmohammadi, Mehran Felfeli. Multi Objective Optimization of Long Hollow Simple Drive Shaft Under Multi-axial Non-Proportional Loading. Sci Discov. 2015;3(3):17-24. doi: 10.11648/j.sd.20150303.11
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Download@article{10.11648/j.sd.20150303.11,
author = {Mohammad Baharvand and Mohammad Pourmohammadi and Mehran Felfeli},
title = {Multi Objective Optimization of Long Hollow Simple Drive Shaft Under Multi-axial Non-Proportional Loading},
journal = {Science Discovery},
volume = {3},
number = {3},
pages = {17-24},
doi = {10.11648/j.sd.20150303.11},
url = {https://doi.org/10.11648/j.sd.20150303.11},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sd.20150303.11},
abstract = {This article investigates the effect of bearing Location and length on the shaft life under multi-axial non-proportional loading. The goal of this study is to increase long shaft life by deciding best location for bearing and its length. Loading condition and shaft properties was assumed according to helicopter. The most common case for this study observed in tail rotor of the Helicopter. Tail rotor drive shaft depended on helicopter type consist of 3 to 5 sections due to high length. Normally these sections assumed identical for simple production but it is shown that using non-identical sections is more proper than the other one. Optimization of shaft life and mass with design variable of the bearing locations and length is performed by ANSYS Workbench software and it is observed that these design variables have a major effect in objective functions. In the next step, we optimize maximum bearing pressure by two new advance methods named Genetic algorithm (GA) and Particle swam algorithm (PSO) and compare these algorithm abilities.},
year = {2015}
}
TY - JOUR T1 - Multi Objective Optimization of Long Hollow Simple Drive Shaft Under Multi-axial Non-Proportional Loading AU - Mohammad Baharvand AU - Mohammad Pourmohammadi AU - Mehran Felfeli Y1 - 2015/07/10 PY - 2015 N1 - https://doi.org/10.11648/j.sd.20150303.11 DO - 10.11648/j.sd.20150303.11 T2 - Science Discovery JF - Science Discovery JO - Science Discovery SP - 17 EP - 24 PB - Science Publishing Group SN - 2331-0650 UR - https://doi.org/10.11648/j.sd.20150303.11 AB - This article investigates the effect of bearing Location and length on the shaft life under multi-axial non-proportional loading. The goal of this study is to increase long shaft life by deciding best location for bearing and its length. Loading condition and shaft properties was assumed according to helicopter. The most common case for this study observed in tail rotor of the Helicopter. Tail rotor drive shaft depended on helicopter type consist of 3 to 5 sections due to high length. Normally these sections assumed identical for simple production but it is shown that using non-identical sections is more proper than the other one. Optimization of shaft life and mass with design variable of the bearing locations and length is performed by ANSYS Workbench software and it is observed that these design variables have a major effect in objective functions. In the next step, we optimize maximum bearing pressure by two new advance methods named Genetic algorithm (GA) and Particle swam algorithm (PSO) and compare these algorithm abilities. VL - 3 IS - 3 ER -
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