Optimal Design of Transmission Shafts Using a Vortex Search Algorithm
This paper analyzes the problem of optimally sizing a transmission shaft via the vortex search algorithm (VSA) optimizer. The objective function was to minimize the shaft weight through an adequate selection of the diameters of each section of the device, and the constraints were the physical condit...
- Autores:
-
Rodriguez-Cabal, M. A.
Betancur-Gómez, J. D.
Grisales-Noreña, Luis Fernando
Montoya, Oscar Danilo
Hincapie, Diego
- Tipo de recurso:
- Fecha de publicación:
- 2021
- Institución:
- Universidad Tecnológica de Bolívar
- Repositorio:
- Repositorio Institucional UTB
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.utb.edu.co:20.500.12585/10044
- Acceso en línea:
- https://hdl.handle.net/20.500.12585/10044
https://link.springer.com/article/10.1007/s13369-020-05121-1
- Palabra clave:
- Mechanical analysis
Machine elements design
Weight shaft optimization
Vortex search algorithm
Continuous genetic algorithm
Nonlinear non-convex optimization
LEMB
- Rights
- closedAccess
- License
- http://purl.org/coar/access_right/c_14cb
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Optimal Design of Transmission Shafts Using a Vortex Search Algorithm |
| title |
Optimal Design of Transmission Shafts Using a Vortex Search Algorithm |
| spellingShingle |
Optimal Design of Transmission Shafts Using a Vortex Search Algorithm Mechanical analysis Machine elements design Weight shaft optimization Vortex search algorithm Continuous genetic algorithm Nonlinear non-convex optimization LEMB |
| title_short |
Optimal Design of Transmission Shafts Using a Vortex Search Algorithm |
| title_full |
Optimal Design of Transmission Shafts Using a Vortex Search Algorithm |
| title_fullStr |
Optimal Design of Transmission Shafts Using a Vortex Search Algorithm |
| title_full_unstemmed |
Optimal Design of Transmission Shafts Using a Vortex Search Algorithm |
| title_sort |
Optimal Design of Transmission Shafts Using a Vortex Search Algorithm |
| dc.creator.fl_str_mv |
Rodriguez-Cabal, M. A. Betancur-Gómez, J. D. Grisales-Noreña, Luis Fernando Montoya, Oscar Danilo Hincapie, Diego |
| dc.contributor.author.none.fl_str_mv |
Rodriguez-Cabal, M. A. Betancur-Gómez, J. D. Grisales-Noreña, Luis Fernando Montoya, Oscar Danilo Hincapie, Diego |
| dc.subject.keywords.spa.fl_str_mv |
Mechanical analysis Machine elements design Weight shaft optimization Vortex search algorithm Continuous genetic algorithm Nonlinear non-convex optimization |
| topic |
Mechanical analysis Machine elements design Weight shaft optimization Vortex search algorithm Continuous genetic algorithm Nonlinear non-convex optimization LEMB |
| dc.subject.armarc.none.fl_str_mv |
LEMB |
| description |
This paper analyzes the problem of optimally sizing a transmission shaft via the vortex search algorithm (VSA) optimizer. The objective function was to minimize the shaft weight through an adequate selection of the diameters of each section of the device, and the constraints were the physical conditions that should be met to design safe, fatigue-proof shafts. The solution and the mathematical model were validated using Autodesk Inventor. In addition, the performance of the VSA was compared to that of the continuous genetic algorithm . The numerical results show that the programmed model has the physical and methodological characteristics needed to produce a better output than conventional design techniques. Therefore, this model can be a powerful tool to solve nonlinear non-convex optimization problems such as the case investigated here. |
| publishDate |
2021 |
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2021-02-17T21:16:13Z |
| dc.date.available.none.fl_str_mv |
2021-02-17T21:16:13Z |
| dc.date.issued.none.fl_str_mv |
2021-01-02 |
| dc.date.submitted.none.fl_str_mv |
2021-02-17 |
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http://purl.org/coar/version/c_970fb48d4fbd8a85 |
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info:eu-repo/semantics/article |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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publishedVersion |
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Rodriguez-Cabal, M.A., Betancur-Gómez, J.D., Grisales-Noreña, L.F. et al. Optimal Design of Transmission Shafts Using a Vortex Search Algorithm. Arab J Sci Eng (2021). https://doi.org/10.1007/s13369-020-05121-1 |
| dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12585/10044 |
| dc.identifier.url.none.fl_str_mv |
https://link.springer.com/article/10.1007/s13369-020-05121-1 |
| dc.identifier.doi.none.fl_str_mv |
10.1007/s13369-020-05121-1 |
| dc.identifier.instname.spa.fl_str_mv |
Universidad Tecnológica de Bolívar |
| dc.identifier.reponame.spa.fl_str_mv |
Repositorio Universidad Tecnológica de Bolívar |
| identifier_str_mv |
Rodriguez-Cabal, M.A., Betancur-Gómez, J.D., Grisales-Noreña, L.F. et al. Optimal Design of Transmission Shafts Using a Vortex Search Algorithm. Arab J Sci Eng (2021). https://doi.org/10.1007/s13369-020-05121-1 10.1007/s13369-020-05121-1 Universidad Tecnológica de Bolívar Repositorio Universidad Tecnológica de Bolívar |
| url |
https://hdl.handle.net/20.500.12585/10044 https://link.springer.com/article/10.1007/s13369-020-05121-1 |
| dc.language.iso.spa.fl_str_mv |
eng |
| language |
eng |
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http://purl.org/coar/access_right/c_14cb |
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info:eu-repo/semantics/closedAccess |
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closedAccess |
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application/pdf |
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Cartagena de Indias |
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Arabian Journal for Science and Engineering (2021) |
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Universidad Tecnológica de Bolívar |
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Rodriguez-Cabal, M. A.1be89097-913e-4af3-9487-97492a811f34Betancur-Gómez, J. D.20e5a207-161f-4d0c-9f4d-51cf48d36a30Grisales-Noreña, Luis Fernando98ba5e2d-fa38-40c5-a05c-d73772e8ab17Montoya, Oscar Danilo8a59ede1-6a4a-4d2e-abdc-d0afb14d4480Hincapie, Diego09fcfbaa-aaec-43c1-8ffd-0d7c67bd910f2021-02-17T21:16:13Z2021-02-17T21:16:13Z2021-01-022021-02-17Rodriguez-Cabal, M.A., Betancur-Gómez, J.D., Grisales-Noreña, L.F. et al. Optimal Design of Transmission Shafts Using a Vortex Search Algorithm. Arab J Sci Eng (2021). https://doi.org/10.1007/s13369-020-05121-1https://hdl.handle.net/20.500.12585/10044https://link.springer.com/article/10.1007/s13369-020-05121-110.1007/s13369-020-05121-1Universidad Tecnológica de BolívarRepositorio Universidad Tecnológica de BolívarThis paper analyzes the problem of optimally sizing a transmission shaft via the vortex search algorithm (VSA) optimizer. The objective function was to minimize the shaft weight through an adequate selection of the diameters of each section of the device, and the constraints were the physical conditions that should be met to design safe, fatigue-proof shafts. The solution and the mathematical model were validated using Autodesk Inventor. In addition, the performance of the VSA was compared to that of the continuous genetic algorithm . The numerical results show that the programmed model has the physical and methodological characteristics needed to produce a better output than conventional design techniques. Therefore, this model can be a powerful tool to solve nonlinear non-convex optimization problems such as the case investigated here.application/pdfengArabian Journal for Science and Engineering (2021)Optimal Design of Transmission Shafts Using a Vortex Search Algorithminfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_970fb48d4fbd8a85Mechanical analysisMachine elements designWeight shaft optimizationVortex search algorithmContinuous genetic algorithmNonlinear non-convex optimizationLEMBinfo:eu-repo/semantics/closedAccesshttp://purl.org/coar/access_right/c_14cbCartagena de IndiasInvestigadoresOptimal Design of Transmission Shafts Using a Vortex Search AlgorithmKim, H.S., Lee, D.G. Optimal design of the press fit joint for a hybrid aluminum/composite drive shaft (2005) Composite Structures, 70 (1), pp. 33-47. Cited 30 times. doi: 10.1016/j.compstruct.2004.08.010Rodriguez-Cabal, M.A., Marín, J.A., Grisales-Noreña, L.F., Montoya, O.D., Del Rio, J.A.S. Optimization of a drive shaft using PSO algorithm (2018) WSEAS Transactions on Applied and Theoretical Mechanics, 13, pp. 130-139. http://www.wseas.org/multimedia/journals/mechanics/2018/a285111-349.pdfReddy, P.S.K., Nagaraju, C. Weight optimization and Finite Element Analysis of Composite automotive drive shaft for Maximum Stiffness (2017) Materials Today: Proceedings, Part A 4 (2), pp. 2390-2396. Cited 11 times. http://www.journals.elsevier.com/materials-today-proceedings/ doi: 10.1016/j.matpr.2017.02.088De Melo, V.V., Carosio, G.L.C. Investigating Multi-View Differential Evolution for solving constrained engineering design problems (2013) Expert Systems with Applications, 40 (9), pp. 3370-3377. Cited 47 times. doi: 10.1016/j.eswa.2012.12.045Husseinzadeh Kashan, A. An efficient algorithm for constrained global optimization and application to mechanical engineering design: League championship algorithm (LCA) (2011) CAD Computer Aided Design, 43 (12), pp. 1769-1792. Cited 96 times. doi: 10.1016/j.cad.2011.07.00Alguliyev, R.M., Aliguliyev, R.M., Abdullayeva, F.J. PSO+K-means algorithm for anomaly detection in big data (Open Access) (2019) Statistics, Optimization and Information Computing, 7 (2), pp. 348-359. Cited 4 times. http://www.iapress.org/index.php/soic/article/download/soic.190606/492 doi: 10.19139/soic.v7i2.623Mendi, F., Başkal, T., Boran, K., Boran, F.E. Optimization of module, shaft diameter and rolling bearing for spur gear through genetic algorithm (2010) Expert Systems with Applications, 37 (12), pp. 8058-8064. Cited 63 times. doi: 10.1016/j.eswa.2010.05.082Choi, B.G., Yang, B.S. Optimum shape design of rotor shafts using genetic algorithm (2000) JVC/Journal of Vibration and Control, 6 (2), pp. 207-222. Cited 45 times. https://journals.sagepub.com/home/jvc doi: 10.1177/107754630000600203Özkış, A., Babalık, A. A novel metaheuristic for multi-objective optimization problems: The multi-objective vortex search algorithm (2017) Information Sciences, 402, pp. 124-148. Cited 29 times. http://www.journals.elsevier.com/information-sciences/ doi: 10.1016/j.ins.2017.03.026Doʇan, B., Ölmez, T. A new metaheuristic for numerical function optimization: Vortex Search algorithm (2015) Information Sciences, 293, pp. 125-145. Cited 137 times. http://www.journals.elsevier.com/information-sciences/ doi: 10.1016/j.ins.2014.08.053Montoya, O.D., Gil-Gonzalez, W., Grisales-Norena, L.F. Vortex search algorithm for optimal power flow analysis in DC resistive networks with CPLs. IEEE Trans (2019) Circuits Syst. II Express Briefs, 7747 (c), p. 1. Cited 3 times.Nadeem, S.K.S., Giridhara, G., Rangavittal, H.K. A Review on the design and analysis of composite drive shaft (2018) Materials Today: Proceedings, Part 3 5 (1), pp. 2738-2741. Cited 9 times. http://www.journals.elsevier.com/materials-today-proceedings/ doi: 10.1016/j.matpr.2018.01.058Rodriguez-Cabal, M.A., Grisales-Norẽa, L.F., Ardila Maŕn, J., Montoya, O.D. Optimal design of transmission shafts: A continuous genetic algorithm approach (Open Access) (2019) Statistics, Optimization and Information Computing, 7 (4), pp. 802-815. Cited 2 times. http://www.iapress.org/index.php/soic/article/download/soic.v7i4.1213/631 doi: 10.19139/soic-2310-5070-641Mott, R.L. Machine elements in mechanical design. (1985) . Cited 17 times. ISBN: 0675203260; 978-067520326-5Alejandra, M.G., Alberto, D. Optimización de la geometría de un eje aplicando algoritmos geneticos Optimising a shaft s geometry by applying genetic algorithms (2005) Ingeniería E Investigación, 25 (2), pp. 15-23. Cited 3 times.Norton, R.L. (1999) Diseño de máquinas, 1. Cited 23 times. Prentice Hall, Londo(2019) MatWeb. AISI Steel, cold drawBeer, F.P., Johnstons, F.P., Mazurek, E., Eisenberg, R., David, F., Beer, E.R. (2010) Mecanica Vectorial Para Ingenieros, 1, p. 654. . Mc Graw HillComino, P., Carigliano, S. (2013) Free Beam Calculator. Cited 2 times.Doǧanşahin, K., Kekezoǧlu, B., Yumurtaci, R., Erdinç, O., Catalão, J.P.S. Maximum permissible integration capacity of renewable DG units based on system loads (Open Access) (2018) Energies, 11 (1), art. no. en11010255. Cited 12 times. http://www.mdpi.com/journal/energies/ doi: 10.3390/en11010255Montoya, O.D., Gil-González, W., Grisales-Noreña, L.F. Optimal power dispatch of DGS in DC power grids: A hybrid gauss-seidel-genetic-algorithm methodology for solving the OPF problem (2018) WSEAS Transactions on Power Systems, 13, pp. 335-346. Cited 15 times. http://wseas.org/wseas/cms.action?id=4057Mastorakis, N.E. Solving non-linear equations via genetic algorithms (2005) Proc. Sixth WSEAS Int. Conf. Evol. Comput., 2005, pp. 24-28. Cited 13 times.Giri, C., Tipparthi, D.K.R., Chattopadhyay, S. A genetic algorithm based approach for system-on-chip test scheduling using dual speed TAM with power constraint (2008) WSEAS Transactions on Circuits and Systems, 7 (5), pp. 416-427. 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