Nonlinear analysis of shell structures using image processing and machine learning
<p dir="ltr">In this paper, we propose a novel approach to solve nonlinear stress analysis problems in shell structures using an image processing technique. In general, such problems in design optimisation or virtual reality applications must be solved repetitively in a short period...
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , |
| منشور في: |
2023
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| الموضوعات: | |
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إضافة وسم
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| _version_ | 1864513542579814400 |
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| author | M.S. Nashed (16392961) |
| author2 | J. Renno (16392970) M.S. Mohamed (10796317) |
| author2_role | author author |
| author_facet | M.S. Nashed (16392961) J. Renno (16392970) M.S. Mohamed (10796317) |
| author_role | author |
| dc.creator.none.fl_str_mv | M.S. Nashed (16392961) J. Renno (16392970) M.S. Mohamed (10796317) |
| dc.date.none.fl_str_mv | 2023-02-01T03:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1016/j.advengsoft.2022.103392 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Nonlinear_analysis_of_shell_structures_using_image_processing_and_machine_learning/24474691 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Engineering Mechanical engineering Information and computing sciences Computer vision and multimedia computation Machine learning Software engineering Convolutional neural networks Nonlinear finite element analysis Shell structures Stress prediction |
| dc.title.none.fl_str_mv | Nonlinear analysis of shell structures using image processing and machine learning |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">In this paper, we propose a novel approach to solve nonlinear stress analysis problems in shell structures using an image processing technique. In general, such problems in design optimisation or virtual reality applications must be solved repetitively in a short period using direct methods such as nonlinear finite element analysis. Hence, obtaining solutions in real-time using direct methods can quickly become computationally overwhelming. The proposed method in this paper is unique in that it converts the mechanical behaviour of shell structures into images that are then used to train a machine learning algorithm. This is achieved by mapping shell deformations and stresses to a set of images that are used to train a conditional generative adversarial network. The network can then predict the solution of the problem for a varying range of parameters. The proposed approach can be significantly more efficient than training a machine learning algorithm using the raw numerical data. To evaluate the proposed method, two different structures are assessed where the training data is created using nonlinear finite element analysis. Each structure is studied for a varying geometry and a set of material properties. We show that the results of the trained network agree well with the results of the nonlinear finite element analysis. The proposed approach can quickly and accurately predict the mechanical behaviour of the structure using a fraction of the computational cost. All created data and source codes are openly available.</p><h2>Other Information</h2><p dir="ltr">Published in: Advances in Engineering Software<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.advengsoft.2022.103392" target="_blank">https://dx.doi.org/10.1016/j.advengsoft.2022.103392</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_e2e58e3316a5b43be7092a373bf22a79 |
| identifier_str_mv | 10.1016/j.advengsoft.2022.103392 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/24474691 |
| publishDate | 2023 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Nonlinear analysis of shell structures using image processing and machine learningM.S. Nashed (16392961)J. Renno (16392970)M.S. Mohamed (10796317)EngineeringMechanical engineeringInformation and computing sciencesComputer vision and multimedia computationMachine learningSoftware engineeringConvolutional neural networksNonlinear finite element analysisShell structuresStress prediction<p dir="ltr">In this paper, we propose a novel approach to solve nonlinear stress analysis problems in shell structures using an image processing technique. In general, such problems in design optimisation or virtual reality applications must be solved repetitively in a short period using direct methods such as nonlinear finite element analysis. Hence, obtaining solutions in real-time using direct methods can quickly become computationally overwhelming. The proposed method in this paper is unique in that it converts the mechanical behaviour of shell structures into images that are then used to train a machine learning algorithm. This is achieved by mapping shell deformations and stresses to a set of images that are used to train a conditional generative adversarial network. The network can then predict the solution of the problem for a varying range of parameters. The proposed approach can be significantly more efficient than training a machine learning algorithm using the raw numerical data. To evaluate the proposed method, two different structures are assessed where the training data is created using nonlinear finite element analysis. Each structure is studied for a varying geometry and a set of material properties. We show that the results of the trained network agree well with the results of the nonlinear finite element analysis. The proposed approach can quickly and accurately predict the mechanical behaviour of the structure using a fraction of the computational cost. All created data and source codes are openly available.</p><h2>Other Information</h2><p dir="ltr">Published in: Advances in Engineering Software<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.advengsoft.2022.103392" target="_blank">https://dx.doi.org/10.1016/j.advengsoft.2022.103392</a></p>2023-02-01T03:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1016/j.advengsoft.2022.103392https://figshare.com/articles/journal_contribution/Nonlinear_analysis_of_shell_structures_using_image_processing_and_machine_learning/24474691CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/244746912023-02-01T03:00:00Z |
| spellingShingle | Nonlinear analysis of shell structures using image processing and machine learning M.S. Nashed (16392961) Engineering Mechanical engineering Information and computing sciences Computer vision and multimedia computation Machine learning Software engineering Convolutional neural networks Nonlinear finite element analysis Shell structures Stress prediction |
| status_str | publishedVersion |
| title | Nonlinear analysis of shell structures using image processing and machine learning |
| title_full | Nonlinear analysis of shell structures using image processing and machine learning |
| title_fullStr | Nonlinear analysis of shell structures using image processing and machine learning |
| title_full_unstemmed | Nonlinear analysis of shell structures using image processing and machine learning |
| title_short | Nonlinear analysis of shell structures using image processing and machine learning |
| title_sort | Nonlinear analysis of shell structures using image processing and machine learning |
| topic | Engineering Mechanical engineering Information and computing sciences Computer vision and multimedia computation Machine learning Software engineering Convolutional neural networks Nonlinear finite element analysis Shell structures Stress prediction |