Mechanical fracture of aluminium alloy (AA 2024-T4), used in the manufacture of a bioproducts plant
Aluminium alloy (AA2024-T4) is a material commonly used in the aerospace industry, where it forms part of the fuselage of aircraft and spacecraft thanks to its good machinability and strength/weight ratio. These characteristics allowed it to be applied in the construction of the structure of a pilot...
- Autores:
-
Urrego, Luis Fabian
García-Beltrán, Olimpo
Arzola, Nelson
Araque, Oscar
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2023
- Institución:
- Universidad de Ibagué
- Repositorio:
- Repositorio Universidad de Ibagué
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.unibague.edu.co:20.500.12313/3876
- Acceso en línea:
- https://hdl.handle.net/20.500.12313/3876
- Palabra clave:
- Crack
Fatigue
Geometric factor
Support vector regression
Pilot plant
- Rights
- openAccess
- License
- http://purl.org/coar/access_right/c_abf2
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dc.title.eng.fl_str_mv |
Mechanical fracture of aluminium alloy (AA 2024-T4), used in the manufacture of a bioproducts plant |
title |
Mechanical fracture of aluminium alloy (AA 2024-T4), used in the manufacture of a bioproducts plant |
spellingShingle |
Mechanical fracture of aluminium alloy (AA 2024-T4), used in the manufacture of a bioproducts plant Crack Fatigue Geometric factor Support vector regression Pilot plant |
title_short |
Mechanical fracture of aluminium alloy (AA 2024-T4), used in the manufacture of a bioproducts plant |
title_full |
Mechanical fracture of aluminium alloy (AA 2024-T4), used in the manufacture of a bioproducts plant |
title_fullStr |
Mechanical fracture of aluminium alloy (AA 2024-T4), used in the manufacture of a bioproducts plant |
title_full_unstemmed |
Mechanical fracture of aluminium alloy (AA 2024-T4), used in the manufacture of a bioproducts plant |
title_sort |
Mechanical fracture of aluminium alloy (AA 2024-T4), used in the manufacture of a bioproducts plant |
dc.creator.fl_str_mv |
Urrego, Luis Fabian García-Beltrán, Olimpo Arzola, Nelson Araque, Oscar |
dc.contributor.author.none.fl_str_mv |
Urrego, Luis Fabian García-Beltrán, Olimpo Arzola, Nelson Araque, Oscar |
dc.subject.proposal.eng.fl_str_mv |
Crack Fatigue Geometric factor Support vector regression Pilot plant |
topic |
Crack Fatigue Geometric factor Support vector regression Pilot plant |
description |
Aluminium alloy (AA2024-T4) is a material commonly used in the aerospace industry, where it forms part of the fuselage of aircraft and spacecraft thanks to its good machinability and strength/weight ratio. These characteristics allowed it to be applied in the construction of the structure of a pilot plant to produce biological extracts and nano-encapsulated bioproducts for the phytosanitary control of diseases associated with microorganisms in crops of Theobroma cacao L. (Cacao). The mechanical design of the bolted support joints for this structure implies knowing the performance under fatigue conditions of the AA2024-T4 material since the use of bolts entails the placement of circular stress concentrators in the AA2024-T4 sheet. The geometric correction constant (Y) is a dimensionless numerical scalar used to correct the stress intensity factor (SIF) at the crack tip during propagation. This factor allows the stress concentration to be modified as a function of the specimen dimensions. In this work, four compact tension specimens were modeled in AA2024-T4, and each one was modified by introducing a second circular stress concentrator varying its size between 15 mm, 20 mm, 25 mm, and 30 mm, respectively. Applying a cyclic load of 1000N, a load ratio R=-1 and a computational model with tetrahedral elements, it was determined that the highest SIF corresponds to the specimen with a 30 mm concentrator with a value close to 460 MPa.mm0.5. Where the crack propagation had a maximum length of 53 mm. Using these simulation data, it was possible to process each one and obtain a mathematical model that calculates the geometric correction constant (Y). The calculated data using the new model was shown to have a direct relationship with the behavior obtained from the simulation. |
publishDate |
2023 |
dc.date.accessioned.none.fl_str_mv |
2023-10-26T22:15:43Z |
dc.date.available.none.fl_str_mv |
2023-10-26T22:15:43Z |
dc.date.issued.none.fl_str_mv |
2023-06-16 |
dc.type.none.fl_str_mv |
Artículo de revista |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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Urrego LF, García-Beltrán O, Arzola N, Araque O. Mechanical Fracture of Aluminium Alloy (AA 2024-T4), Used in the Manufacture of a Bioproducts Plant. Metals. 2023;13(6):1134. https://doi.org/10.3390/met13061134. |
dc.identifier.issn.none.fl_str_mv |
2075-4701 |
dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12313/3876 |
identifier_str_mv |
Urrego LF, García-Beltrán O, Arzola N, Araque O. Mechanical Fracture of Aluminium Alloy (AA 2024-T4), Used in the Manufacture of a Bioproducts Plant. Metals. 2023;13(6):1134. https://doi.org/10.3390/met13061134. 2075-4701 |
url |
https://hdl.handle.net/20.500.12313/3876 |
dc.language.iso.none.fl_str_mv |
eng |
language |
eng |
dc.relation.citationedition.none.fl_str_mv |
1134 |
dc.relation.citationendpage.none.fl_str_mv |
1134 |
dc.relation.citationissue.none.fl_str_mv |
6 |
dc.relation.citationvolume.none.fl_str_mv |
13 |
dc.relation.ispartofjournal.none.fl_str_mv |
Metals |
dc.relation.references.none.fl_str_mv |
Sanchez-Capa, M.; Viteri-Sanchez, S.; Burbano-Cachiguango, A. New Characteristics in the Fermentation Process of Cocoa (Theobroma cacao L.) ‘Super Á rbol’ in La Joya de los. Sustainability 2022, 14, 7564. Gómez, E.H.; Campo, I.; Rosario, E.; Tapachula, K.C. Factores socieconómicos y parasitológicos que limitan la producción del cacao en Chiapas, México Socioeconomic and parasitological factors that limits cocoa production in Chiapas, Mexico, 2015. Rev. Mex. Fitopatol. 2015, 33, 232–246. Chitiva-Chitiva, L.C.; Ladino-Vargas, C.; Cuca-Suárez, L.E.; Prieto-Rodríguez, J.A.; Patiño-Ladino, O.J. Antifungal Activity of Chemical Constituents from Phytopathogen Fungi of Cocoa. Molecules 2021, 26, 3256. Guerrini, A.; Sacchetti, G.; Rossi, D.; Paganetto, G.; Muzzoli, M.; Andreotti, E.; Tognolini, M.; Maldonado, M.E.; Bruni, R. Bioactivities of Piper aduncum L. and Piper obliquum Ruiz & Pavon (Piperaceae) essential oils from Eastern Ecuador. Environ. Toxicol. Pharmacol. 2009, 27, 39–48. Guerrero, R.; Risco, G.; Cevallos, O.; Villamar, R.; Peñaherrera, S. Extractos vegetales: Una alternativa para el control de enfermedades en el cultivo de cacao (Theobroma cacao). Ing. Innovación 2020, 8, 2326. Nairn, J.A. Direct comparison of anisotropic damage mechanics to fracture mechanics of explicit cracks. Eng. Fract. Mech. 2018, 203, 197–207. Mecholsky, J.J. Fracture mechanics principles. Dent. Mater. 1995, 11, 111–112. Taylor, D.; Cornetti, P.; Pugno, N. The fracture mechanics of finite crack extension. Eng. Fract. Mech. 2005, 72, 1021–1038. Atzori, B.; Lazzarin, P.; Meneghetti, G. Fracture mechanics and notch sensitivity. Fatigue Fract. Eng. Mater. Struct. 2003, 26, 257–267. Smith, S.M.; Scattergood, R.O. Crack-Shape Effects for Indentation Fracture Toughness Measurements. J. Am. Ceram. Soc. 1992, 75, 305–315. Newman, J.C., Jr.; Raju, I. An empirical stress-intensity factor equation for the surface crack. Eng. Fract. Mech. 1981, 15, 185–192. Nix, K.J.; Lindley, T.C. The Application of Fracture Mechanics to Fretting Fatigue. Fatigue Fract. Eng. Mater. Struct. 1985, 8, 143–160. Clarke, S.M.; Griebsch, J.H.; Simpson, T.W. Analysis of Support Vector Regression for Approximation of Complex Engineering Analyses. J. Mech. Des. 2004, 127, 1077–1087 Smola, A.J.; Scholkopf, B. A tutorial on support vector regression. Stat. Comput. 2004, 14, 199–222 Heydari, M.H.; Choupani, N. A New Comparative Method to Evaluate the Fracture Properties of Laminated Composite. Int. J. Eng. 2014, 27, 991–1004. El-Desouky, A.R. Mixed Mode Crack Propagation of Zirconia/Nickel Functionally Graded Materials. Int. J. Eng. 2013, 26, 885–894. Guo, K.; Gou, G.; Lv, H.; Shan, M. Jointing of CFRP/5083 Aluminum Alloy by Induction Brazing: Processing, Connecting Mechanism, and Fatigue Performance. Coatings 2022, 12, 1559. USA Department of Defense. MIL-HDBK-2097, Military Handbook: Acquisition of Support Equipment and Associated Integrated Logistics Support; USA Department of Defense: Washington, DC, USA, 1997. Haji, Z. Low cycle fatigue behavior of aluminum alloys AA2024-T6 and AA7020-T6. Diyala J. Eng. Sci. 2010, 127–137. Meggiolaro, M. Statistical evaluation of strain-life fatigue crack initiation predictions. Int. J. Fatigue 2004, 26, 463–476. Faisal, B.M.; Abass, A.T.; Hammadi, A.F. Fatigue Life Estimation of Aluminum Alloy 2024-T4 and Fiber Glass-Polyester Composite Material. Int. Res. J. Eng. Technol. 2016, 2016, 1760–1764. Available online: www.irjet.net (accessed on 10 April 2023). Yang, G.; Gao, Z.L.; Xu, F.; Wang, X.G. An Experiment of Fatigue Crack Growth under Different R-Ratio for 2024-T4 Aluminum Alloy. Appl. Mech. Mater. 2011, 66–68, 1477–1482. Hudson, M.; Scardina, J. Effect of stress ratio on fatigue crack growth in 7075-T6 Al alloy sheet. Natl. Symp. Fract. Mech. 1967. Wei, R.P. Fatigue-crack propagation in a high-strength. Int. J. Fract. Mech. 1968, 4, 159–168. ANSYS. Meshing Guide; Finite Elem. Simulations Using ANSYS; Ansys: Canonsburg, PA, USA, 2015; Volume 15317, pp. 407–424. Araque, O.; Arzola, N. Weld Magnification Factor Approach in Cruciform Joints Considering Post Welding Cooling Medium and Weld Size. Materials 2018, 11, 81. Shawe-Taylor, J.; Cristianini, N. Kernel Methods for Pattern Analysis; Cambridge University Press: Cambridge, UK, 2004. Demir, S.; Toktamiş, Ö. On the adaptive Nadaraya-Watson kernel regression estimators. Hacet. J. Math. Stat. 2010, 39, 429–437. Fan, J.; Gijbels, I. Local Polynomial Modelling and Its Applications; Applied Pr. New York; CRC Press: Boca Raton, FL, USA, 1996. Chu, C.-Y.; Henderson, D.J.; Parmeter, C.F. On discrete Epanechnikov kernel functions. Comput. Stat. Data Anal. 2017, 116, 79–105. Alshoaibi, A.M. Computational Simulation of 3D Fatigue Crack Growth under Mixed-Mode Loading. Appl. Sci. 2021, 11, 5953. Rahmatabadi, D.; Pahlavani, M.; Bayati, A.; Hashemi, R.; Marzbanrad, J. Evaluation of fracture toughness and rupture energy absorption capacity of as-rolled LZ71 and LZ91 Mg alloy sheet. Mater. Res. Express 2018, 6, 036517. |
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Urrego, Luis Fabian4d32823e-6312-4810-b6db-612534a1c190-1García-Beltrán, Olimpodfe2bbe7-81d5-415c-9be6-6469a5a40c75-1Arzola, Nelson98a2f36b-b5ae-4397-93f0-cf08f3f4ad9c-1Araque, Oscaredc2c29e-176c-4dde-a414-bf83fddfa5d1-12023-10-26T22:15:43Z2023-10-26T22:15:43Z2023-06-16Aluminium alloy (AA2024-T4) is a material commonly used in the aerospace industry, where it forms part of the fuselage of aircraft and spacecraft thanks to its good machinability and strength/weight ratio. These characteristics allowed it to be applied in the construction of the structure of a pilot plant to produce biological extracts and nano-encapsulated bioproducts for the phytosanitary control of diseases associated with microorganisms in crops of Theobroma cacao L. (Cacao). The mechanical design of the bolted support joints for this structure implies knowing the performance under fatigue conditions of the AA2024-T4 material since the use of bolts entails the placement of circular stress concentrators in the AA2024-T4 sheet. The geometric correction constant (Y) is a dimensionless numerical scalar used to correct the stress intensity factor (SIF) at the crack tip during propagation. This factor allows the stress concentration to be modified as a function of the specimen dimensions. In this work, four compact tension specimens were modeled in AA2024-T4, and each one was modified by introducing a second circular stress concentrator varying its size between 15 mm, 20 mm, 25 mm, and 30 mm, respectively. Applying a cyclic load of 1000N, a load ratio R=-1 and a computational model with tetrahedral elements, it was determined that the highest SIF corresponds to the specimen with a 30 mm concentrator with a value close to 460 MPa.mm0.5. Where the crack propagation had a maximum length of 53 mm. Using these simulation data, it was possible to process each one and obtain a mathematical model that calculates the geometric correction constant (Y). The calculated data using the new model was shown to have a direct relationship with the behavior obtained from the simulation.16 páginasapplication/pdfUrrego LF, García-Beltrán O, Arzola N, Araque O. Mechanical Fracture of Aluminium Alloy (AA 2024-T4), Used in the Manufacture of a Bioproducts Plant. Metals. 2023;13(6):1134. https://doi.org/10.3390/met13061134.2075-4701https://hdl.handle.net/20.500.12313/3876engBasilea, Suiza11341134613MetalsSanchez-Capa, M.; Viteri-Sanchez, S.; Burbano-Cachiguango, A. New Characteristics in the Fermentation Process of Cocoa (Theobroma cacao L.) ‘Super Á rbol’ in La Joya de los. Sustainability 2022, 14, 7564.Gómez, E.H.; Campo, I.; Rosario, E.; Tapachula, K.C. Factores socieconómicos y parasitológicos que limitan la producción del cacao en Chiapas, México Socioeconomic and parasitological factors that limits cocoa production in Chiapas, Mexico, 2015. Rev. Mex. Fitopatol. 2015, 33, 232–246.Chitiva-Chitiva, L.C.; Ladino-Vargas, C.; Cuca-Suárez, L.E.; Prieto-Rodríguez, J.A.; Patiño-Ladino, O.J. Antifungal Activity of Chemical Constituents from Phytopathogen Fungi of Cocoa. Molecules 2021, 26, 3256.Guerrini, A.; Sacchetti, G.; Rossi, D.; Paganetto, G.; Muzzoli, M.; Andreotti, E.; Tognolini, M.; Maldonado, M.E.; Bruni, R. Bioactivities of Piper aduncum L. and Piper obliquum Ruiz & Pavon (Piperaceae) essential oils from Eastern Ecuador. Environ. Toxicol. Pharmacol. 2009, 27, 39–48.Guerrero, R.; Risco, G.; Cevallos, O.; Villamar, R.; Peñaherrera, S. Extractos vegetales: Una alternativa para el control de enfermedades en el cultivo de cacao (Theobroma cacao). Ing. Innovación 2020, 8, 2326.Nairn, J.A. Direct comparison of anisotropic damage mechanics to fracture mechanics of explicit cracks. Eng. Fract. Mech. 2018, 203, 197–207.Mecholsky, J.J. Fracture mechanics principles. Dent. Mater. 1995, 11, 111–112.Taylor, D.; Cornetti, P.; Pugno, N. The fracture mechanics of finite crack extension. Eng. Fract. Mech. 2005, 72, 1021–1038.Atzori, B.; Lazzarin, P.; Meneghetti, G. Fracture mechanics and notch sensitivity. Fatigue Fract. Eng. Mater. Struct. 2003, 26, 257–267.Smith, S.M.; Scattergood, R.O. Crack-Shape Effects for Indentation Fracture Toughness Measurements. J. Am. Ceram. Soc. 1992, 75, 305–315.Newman, J.C., Jr.; Raju, I. An empirical stress-intensity factor equation for the surface crack. Eng. Fract. Mech. 1981, 15, 185–192.Nix, K.J.; Lindley, T.C. The Application of Fracture Mechanics to Fretting Fatigue. Fatigue Fract. Eng. Mater. Struct. 1985, 8, 143–160.Clarke, S.M.; Griebsch, J.H.; Simpson, T.W. Analysis of Support Vector Regression for Approximation of Complex Engineering Analyses. J. Mech. Des. 2004, 127, 1077–1087Smola, A.J.; Scholkopf, B. A tutorial on support vector regression. Stat. Comput. 2004, 14, 199–222Heydari, M.H.; Choupani, N. A New Comparative Method to Evaluate the Fracture Properties of Laminated Composite. Int. J. Eng. 2014, 27, 991–1004.El-Desouky, A.R. Mixed Mode Crack Propagation of Zirconia/Nickel Functionally Graded Materials. Int. J. Eng. 2013, 26, 885–894.Guo, K.; Gou, G.; Lv, H.; Shan, M. Jointing of CFRP/5083 Aluminum Alloy by Induction Brazing: Processing, Connecting Mechanism, and Fatigue Performance. Coatings 2022, 12, 1559.USA Department of Defense. MIL-HDBK-2097, Military Handbook: Acquisition of Support Equipment and Associated Integrated Logistics Support; USA Department of Defense: Washington, DC, USA, 1997.Haji, Z. Low cycle fatigue behavior of aluminum alloys AA2024-T6 and AA7020-T6. Diyala J. Eng. Sci. 2010, 127–137.Meggiolaro, M. Statistical evaluation of strain-life fatigue crack initiation predictions. Int. J. Fatigue 2004, 26, 463–476.Faisal, B.M.; Abass, A.T.; Hammadi, A.F. Fatigue Life Estimation of Aluminum Alloy 2024-T4 and Fiber Glass-Polyester Composite Material. Int. Res. J. Eng. Technol. 2016, 2016, 1760–1764. Available online: www.irjet.net (accessed on 10 April 2023).Yang, G.; Gao, Z.L.; Xu, F.; Wang, X.G. An Experiment of Fatigue Crack Growth under Different R-Ratio for 2024-T4 Aluminum Alloy. Appl. Mech. Mater. 2011, 66–68, 1477–1482.Hudson, M.; Scardina, J. Effect of stress ratio on fatigue crack growth in 7075-T6 Al alloy sheet. Natl. Symp. Fract. Mech. 1967.Wei, R.P. Fatigue-crack propagation in a high-strength. Int. J. Fract. Mech. 1968, 4, 159–168.ANSYS. Meshing Guide; Finite Elem. Simulations Using ANSYS; Ansys: Canonsburg, PA, USA, 2015; Volume 15317, pp. 407–424.Araque, O.; Arzola, N. Weld Magnification Factor Approach in Cruciform Joints Considering Post Welding Cooling Medium and Weld Size. Materials 2018, 11, 81.Shawe-Taylor, J.; Cristianini, N. Kernel Methods for Pattern Analysis; Cambridge University Press: Cambridge, UK, 2004.Demir, S.; Toktamiş, Ö. On the adaptive Nadaraya-Watson kernel regression estimators. Hacet. J. Math. Stat. 2010, 39, 429–437.Fan, J.; Gijbels, I. Local Polynomial Modelling and Its Applications; Applied Pr. New York; CRC Press: Boca Raton, FL, USA, 1996.Chu, C.-Y.; Henderson, D.J.; Parmeter, C.F. On discrete Epanechnikov kernel functions. Comput. Stat. Data Anal. 2017, 116, 79–105.Alshoaibi, A.M. Computational Simulation of 3D Fatigue Crack Growth under Mixed-Mode Loading. Appl. Sci. 2021, 11, 5953.Rahmatabadi, D.; Pahlavani, M.; Bayati, A.; Hashemi, R.; Marzbanrad, J. Evaluation of fracture toughness and rupture energy absorption capacity of as-rolled LZ71 and LZ91 Mg alloy sheet. Mater. Res. 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