Design of composite rectangular tubes for optimum crashworthiness performance via experimental and ANN techniques
<p dir="ltr">This paper examines the crashworthiness performance of composite rectangular tubes using experimental and artificial neural network (ANN) techniques. Based on experimentally obtained values of different crashworthiness parameters under various loading conditions, ANN mod...
محفوظ في:
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| مؤلفون آخرون: | , |
| منشور في: |
2022
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| _version_ | 1864513551780020224 |
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| author | Monzure-Khoda Kazi (17191207) |
| author2 | Fadwa Eljack (3333444) E. Mahdi (17191210) |
| author2_role | author author |
| author_facet | Monzure-Khoda Kazi (17191207) Fadwa Eljack (3333444) E. Mahdi (17191210) |
| author_role | author |
| dc.creator.none.fl_str_mv | Monzure-Khoda Kazi (17191207) Fadwa Eljack (3333444) E. Mahdi (17191210) |
| dc.date.none.fl_str_mv | 2022-01-01T00:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1016/j.compstruct.2021.114858 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Design_of_composite_rectangular_tubes_for_optimum_crashworthiness_performance_via_experimental_and_ANN_techniques/24339241 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Engineering Chemical engineering Mechanical engineering Information and computing sciences Artificial intelligence Crashworthiness Fiber-reinforced composite Rectangular tube Composite design Artificial neural network |
| dc.title.none.fl_str_mv | Design of composite rectangular tubes for optimum crashworthiness performance via experimental and ANN techniques |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">This paper examines the crashworthiness performance of composite rectangular tubes using experimental and artificial neural network (ANN) techniques. Based on experimentally obtained values of different crashworthiness parameters under various loading conditions, ANN models are constructed to identify the optimum cross-sectional aspect ratio of cotton fiber/epoxy laminated composite to achieve the targeted mechanical properties such as load carrying and energy absorption capability. Experimental findings show that axially and laterally loaded rectangular tubes were significantly affected by their aspect ratio. Furthermore, the predictions obtained from the ANN models showed consistency with the experimental data. In addition, the developed ANN captured the complicated nonlinear relationship among crashworthiness parameters to obtain insight into the practical design of the composite materials.</p><h2>Other Information</h2><p dir="ltr">Published in: Composite Structures<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.compstruct.2021.114858" target="_blank">https://dx.doi.org/10.1016/j.compstruct.2021.114858</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_16bf0b9a5ea9ced65ea04ef97035b517 |
| identifier_str_mv | 10.1016/j.compstruct.2021.114858 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/24339241 |
| publishDate | 2022 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Design of composite rectangular tubes for optimum crashworthiness performance via experimental and ANN techniquesMonzure-Khoda Kazi (17191207)Fadwa Eljack (3333444)E. Mahdi (17191210)EngineeringChemical engineeringMechanical engineeringInformation and computing sciencesArtificial intelligenceCrashworthinessFiber-reinforced compositeRectangular tubeComposite designArtificial neural network<p dir="ltr">This paper examines the crashworthiness performance of composite rectangular tubes using experimental and artificial neural network (ANN) techniques. Based on experimentally obtained values of different crashworthiness parameters under various loading conditions, ANN models are constructed to identify the optimum cross-sectional aspect ratio of cotton fiber/epoxy laminated composite to achieve the targeted mechanical properties such as load carrying and energy absorption capability. Experimental findings show that axially and laterally loaded rectangular tubes were significantly affected by their aspect ratio. Furthermore, the predictions obtained from the ANN models showed consistency with the experimental data. In addition, the developed ANN captured the complicated nonlinear relationship among crashworthiness parameters to obtain insight into the practical design of the composite materials.</p><h2>Other Information</h2><p dir="ltr">Published in: Composite Structures<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.compstruct.2021.114858" target="_blank">https://dx.doi.org/10.1016/j.compstruct.2021.114858</a></p>2022-01-01T00:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1016/j.compstruct.2021.114858https://figshare.com/articles/journal_contribution/Design_of_composite_rectangular_tubes_for_optimum_crashworthiness_performance_via_experimental_and_ANN_techniques/24339241CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/243392412022-01-01T00:00:00Z |
| spellingShingle | Design of composite rectangular tubes for optimum crashworthiness performance via experimental and ANN techniques Monzure-Khoda Kazi (17191207) Engineering Chemical engineering Mechanical engineering Information and computing sciences Artificial intelligence Crashworthiness Fiber-reinforced composite Rectangular tube Composite design Artificial neural network |
| status_str | publishedVersion |
| title | Design of composite rectangular tubes for optimum crashworthiness performance via experimental and ANN techniques |
| title_full | Design of composite rectangular tubes for optimum crashworthiness performance via experimental and ANN techniques |
| title_fullStr | Design of composite rectangular tubes for optimum crashworthiness performance via experimental and ANN techniques |
| title_full_unstemmed | Design of composite rectangular tubes for optimum crashworthiness performance via experimental and ANN techniques |
| title_short | Design of composite rectangular tubes for optimum crashworthiness performance via experimental and ANN techniques |
| title_sort | Design of composite rectangular tubes for optimum crashworthiness performance via experimental and ANN techniques |
| topic | Engineering Chemical engineering Mechanical engineering Information and computing sciences Artificial intelligence Crashworthiness Fiber-reinforced composite Rectangular tube Composite design Artificial neural network |