Analysis and optimization for the process of glass tempering using autoclave

A mathematical analysis of the glass tempering process was carried out using an autoclave, varying the operating parameters of the system. It was found that the process time can be reduced by up to 3.23% by changing the resistance to 15Ω, but increasing the resistance more than this value would mean...

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Autores:
G E, Valencia
Y D, Cardenas
C H, Acevedo
Tipo de recurso:
Fecha de publicación:
2018
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
eng
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/2936
Acceso en línea:
http://hdl.handle.net/11323/2936
https://repositorio.cuc.edu.co/
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Atribución – No comercial – Compartir igual
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network_acronym_str RCUC2
network_name_str REDICUC - Repositorio CUC
repository_id_str
dc.title.spa.fl_str_mv Analysis and optimization for the process of glass tempering using autoclave
title Analysis and optimization for the process of glass tempering using autoclave
spellingShingle Analysis and optimization for the process of glass tempering using autoclave
title_short Analysis and optimization for the process of glass tempering using autoclave
title_full Analysis and optimization for the process of glass tempering using autoclave
title_fullStr Analysis and optimization for the process of glass tempering using autoclave
title_full_unstemmed Analysis and optimization for the process of glass tempering using autoclave
title_sort Analysis and optimization for the process of glass tempering using autoclave
dc.creator.fl_str_mv G E, Valencia
Y D, Cardenas
C H, Acevedo
dc.contributor.author.spa.fl_str_mv G E, Valencia
Y D, Cardenas
C H, Acevedo
description A mathematical analysis of the glass tempering process was carried out using an autoclave, varying the operating parameters of the system. It was found that the process time can be reduced by up to 3.23% by changing the resistance to 15Ω, but increasing the resistance more than this value would mean compromising the quality of the final product. Thus, it is advisable to make variations of the resistance between 10Ω and15Ω, which will allow the optimization of the process time and pressures without affecting the quality of the result
publishDate 2018
dc.date.issued.none.fl_str_mv 2018
dc.date.accessioned.none.fl_str_mv 2019-03-12T14:23:13Z
dc.date.available.none.fl_str_mv 2019-03-12T14:23:13Z
dc.type.spa.fl_str_mv Otros
dc.type.content.spa.fl_str_mv Text
dc.type.driver.spa.fl_str_mv info:eu-repo/semantics/other
dc.type.redcol.spa.fl_str_mv http://purl.org/redcol/resource_type/ARTOTR
dc.type.version.spa.fl_str_mv info:eu-repo/semantics/acceptedVersion
status_str acceptedVersion
dc.identifier.issn.spa.fl_str_mv 1742-6588
dc.identifier.uri.spa.fl_str_mv http://hdl.handle.net/11323/2936
dc.identifier.instname.spa.fl_str_mv Corporación Universidad de la Costa
dc.identifier.reponame.spa.fl_str_mv REDICUC - Repositorio CUC
dc.identifier.repourl.spa.fl_str_mv https://repositorio.cuc.edu.co/
identifier_str_mv 1742-6588
Corporación Universidad de la Costa
REDICUC - Repositorio CUC
url http://hdl.handle.net/11323/2936
https://repositorio.cuc.edu.co/
dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.references.spa.fl_str_mv Fernlund G, Mobuchon C and Zobeiry N 2018 Autoclave Processing Comprehensive Composite Materials II 2nd edition ed Peter W.R. Beaumont and Carl H. Zweben (Amsterdam: Elsevier) chapter 2 pp 42-62 Smolyanov I, Frizen V, Bolotin K and Ulrych B 2017 Research of the induction heating installation on based autoclave Proc. 18th International Conference on Computational Problems of Electrical Engineering (CPEE) (Kutna Hora, Czech Republic: IEEE) pp 1-4 Ling T C, Mo K H, Qu L, Yang J and Guo L 2017 Mechanical strength and durability performance of autoclaved lime-saline soil brick Cons. and Build. Materials 146 403-409 Wood S G, Giannini E R, Ramsey M A and Moser R D 2018 Autoclave test parameters for determining alkali-silica reactivity of concrete aggregates Cons. and Build. Materials 168 683–691 Mousavi S M, Hormozi E, Moradi M, Shamohammadi M and Rakhshan V 2018 Effects of autoclaving versus cold chemical (glutaraldehyde) sterilization on load-deflection characteristics of aesthetic coated archwires Int. Orth. 16(2) 281-293 Bhavsar R C, Patel R A and Bhalja B R 2014 Condition monitoring of induction motor using Artificial Neural Network Annual International Conference on Emerging Research Areas: Magnetics, Machines and Drives (AICERA/iCMMD) (Kottayam, India: IEEE) pp 1-6 Cotoco E K A, et al 2017 Tempering color classification via artificial neural network (ANN ): An intelligent system approach to steel thermography International Conference on Electrical, Electronics and System Engineering (ICEESE) (Kanazawa, Japan: IEEE) pp 84-88 Cuffe S S 1985 A Variable Frequency AC Blower Drive Installation for Efficient and Accurate Control of Glass Tempering IEEE Trans. on Ind. Appl. 4(1) 1047-1052 P. Yu, K. Zhu, T. Sun, N. Yuan, and J. Ding 2017 Heat transfer rate and uniformity of mist flow jet impingement for glass tempering Int. J. Heat Mass Transfer 115(PartB) 368–378 M. Vocialta, M. Corrado, and J. F. Molinari 2018 Numerical analysis of fragmentation in tempered glass with parallel dynamic insertion of cohesive elements Eng. Frac. Mech. 188 448-469 Seidel S, Franke M, Baumann F, Wilson H and Gromnitza U 2018 Enhancing the energy-efficient production of tempered glass by using simulation-based optimisation 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) (Limassol, Cyprus: IEEE) pp 1-4 Altinsu B, Koçak O and Akpek A 2016 Design and analysis of an autoclave simulation using MATLAB /Simulink Medical Technologies National Congress (TIPTEKNO) (Antalya, Turkey: IEEE) pp 1-4 García E, Amaya I y Correa R 2017 Algoritmos de optimización en la estimación de propiedades termodinámicas en tiempo real durante el tratamiento térmico de materiales con microondas Revista UIS Ingenierías 16(2) 29-40 Matajira-Rueda D, Duarte JC, Cervantes JA, Cely CC 2018 Global optimization algorithms applied in a parameter estimation strategy Revista UIS Ingenierías 17(1) 233-242
dc.rights.spa.fl_str_mv Atribución – No comercial – Compartir igual
dc.rights.accessrights.spa.fl_str_mv info:eu-repo/semantics/openAccess
dc.rights.coar.spa.fl_str_mv http://purl.org/coar/access_right/c_abf2
rights_invalid_str_mv Atribución – No comercial – Compartir igual
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.publisher.spa.fl_str_mv Journal of Physics: Conference Series
institution Corporación Universidad de la Costa
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spelling G E, ValenciaY D, CardenasC H, Acevedo2019-03-12T14:23:13Z2019-03-12T14:23:13Z20181742-6588http://hdl.handle.net/11323/2936Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/A mathematical analysis of the glass tempering process was carried out using an autoclave, varying the operating parameters of the system. It was found that the process time can be reduced by up to 3.23% by changing the resistance to 15Ω, but increasing the resistance more than this value would mean compromising the quality of the final product. Thus, it is advisable to make variations of the resistance between 10Ω and15Ω, which will allow the optimization of the process time and pressures without affecting the quality of the resultG E, Valencia-15305ce7-fc8d-4f07-97f8-4590bfffda59-0Y D, Cardenas-91fb6783-e81a-43f0-8353-98e2fbdb9c67-0C H, Acevedo-1ac2f120-c6d3-4cef-ba51-3a0ec06e68c1-0engJournal of Physics: Conference SeriesAtribución – No comercial – Compartir igualinfo:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Analysis and optimization for the process of glass tempering using autoclaveOtrosTextinfo:eu-repo/semantics/otherhttp://purl.org/redcol/resource_type/ARTOTRinfo:eu-repo/semantics/acceptedVersionFernlund G, Mobuchon C and Zobeiry N 2018 Autoclave Processing Comprehensive Composite Materials II 2nd edition ed Peter W.R. Beaumont and Carl H. Zweben (Amsterdam: Elsevier) chapter 2 pp 42-62 Smolyanov I, Frizen V, Bolotin K and Ulrych B 2017 Research of the induction heating installation on based autoclave Proc. 18th International Conference on Computational Problems of Electrical Engineering (CPEE) (Kutna Hora, Czech Republic: IEEE) pp 1-4 Ling T C, Mo K H, Qu L, Yang J and Guo L 2017 Mechanical strength and durability performance of autoclaved lime-saline soil brick Cons. and Build. Materials 146 403-409 Wood S G, Giannini E R, Ramsey M A and Moser R D 2018 Autoclave test parameters for determining alkali-silica reactivity of concrete aggregates Cons. and Build. Materials 168 683–691 Mousavi S M, Hormozi E, Moradi M, Shamohammadi M and Rakhshan V 2018 Effects of autoclaving versus cold chemical (glutaraldehyde) sterilization on load-deflection characteristics of aesthetic coated archwires Int. Orth. 16(2) 281-293 Bhavsar R C, Patel R A and Bhalja B R 2014 Condition monitoring of induction motor using Artificial Neural Network Annual International Conference on Emerging Research Areas: Magnetics, Machines and Drives (AICERA/iCMMD) (Kottayam, India: IEEE) pp 1-6 Cotoco E K A, et al 2017 Tempering color classification via artificial neural network (ANN ): An intelligent system approach to steel thermography International Conference on Electrical, Electronics and System Engineering (ICEESE) (Kanazawa, Japan: IEEE) pp 84-88 Cuffe S S 1985 A Variable Frequency AC Blower Drive Installation for Efficient and Accurate Control of Glass Tempering IEEE Trans. on Ind. Appl. 4(1) 1047-1052 P. Yu, K. Zhu, T. Sun, N. Yuan, and J. Ding 2017 Heat transfer rate and uniformity of mist flow jet impingement for glass tempering Int. J. Heat Mass Transfer 115(PartB) 368–378 M. Vocialta, M. Corrado, and J. F. Molinari 2018 Numerical analysis of fragmentation in tempered glass with parallel dynamic insertion of cohesive elements Eng. Frac. Mech. 188 448-469 Seidel S, Franke M, Baumann F, Wilson H and Gromnitza U 2018 Enhancing the energy-efficient production of tempered glass by using simulation-based optimisation 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) (Limassol, Cyprus: IEEE) pp 1-4 Altinsu B, Koçak O and Akpek A 2016 Design and analysis of an autoclave simulation using MATLAB /Simulink Medical Technologies National Congress (TIPTEKNO) (Antalya, Turkey: IEEE) pp 1-4 García E, Amaya I y Correa R 2017 Algoritmos de optimización en la estimación de propiedades termodinámicas en tiempo real durante el tratamiento térmico de materiales con microondas Revista UIS Ingenierías 16(2) 29-40 Matajira-Rueda D, Duarte JC, Cervantes JA, Cely CC 2018 Global optimization algorithms applied in a parameter estimation strategy Revista UIS Ingenierías 17(1) 233-242PublicationORIGINALAnalysis and optimization for the process of glass tempering using autoclave.pdfAnalysis and optimization for the process of glass tempering using autoclave.pdfapplication/pdf772850https://repositorio.cuc.edu.co/bitstreams/00591128-79e4-4afe-89d1-0075c2f4bc12/download6ba67c7efe1b4176f01f16696c2d8738MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorio.cuc.edu.co/bitstreams/14bed460-fb8d-4128-9ac2-a6bb2189892a/download8a4605be74aa9ea9d79846c1fba20a33MD52THUMBNAILAnalysis and optimization for the process of glass tempering using autoclave.pdf.jpgAnalysis and optimization for the process of glass tempering using autoclave.pdf.jpgimage/jpeg66664https://repositorio.cuc.edu.co/bitstreams/357acccc-63d4-4c30-95e8-3c8a35a6fdc8/downloada6a0c39e8cec6ce2f5f271edb9166f3fMD54TEXTAnalysis and optimization for the process of glass tempering using autoclave.pdf.txtAnalysis and optimization for the process of glass tempering using autoclave.pdf.txttext/plain17387https://repositorio.cuc.edu.co/bitstreams/0fe6e481-45bb-4918-9059-9cf837b384f4/download767cd5bd29440891e6fac495a958a4ceMD5511323/2936oai:repositorio.cuc.edu.co:11323/29362024-09-16 16:44:08.042open.accesshttps://repositorio.cuc.edu.coRepositorio de la Universidad de la Costa CUCrepdigital@cuc.edu.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