EXPERIMENTAL STUDY AND MODELLING OF DEFORMATION OF RECTANGULAR PLATES SUBJECTED TO HYDRODYNAMIC LOADING USING NEURAL NETWORK
In this paper, experimental responses of fully clamped aluminium and steel rectangular plates are presented subjected to hydrodynamic loading. The GMDHtype neural networks (Group Method of Data Handling) are then used for the modelling of the mid-point deflection thickness ratio of the rectangular p...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Taylor's University
2016-09-01
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| Series: | Journal of Engineering Science and Technology |
| Subjects: | |
| Online Access: | http://jestec.taylors.edu.my/Vol%2011%20issue%209%20September%202016/11_9_7.pdf |
| _version_ | 1818201719598743552 |
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| author | HASHEM BABAEI TOHID MIRZABABAIE MOSTOFI MAJID ALITAVOLI ASGHAR SAEIDINEJAD |
| author_facet | HASHEM BABAEI TOHID MIRZABABAIE MOSTOFI MAJID ALITAVOLI ASGHAR SAEIDINEJAD |
| author_sort | HASHEM BABAEI |
| collection | DOAJ |
| description | In this paper, experimental responses of fully clamped aluminium and steel rectangular plates are presented subjected to hydrodynamic loading. The GMDHtype neural networks (Group Method of Data Handling) are then used for the modelling of the mid-point deflection thickness ratio of the rectangular plates
using the experimental results. The purpose of this modelling is to display how the variations of the significant parameters changes with the mid-point deflection. In addition, the results indicate that dimensionless input variables provide simpler polynomial expressions in comparison with actual physical parameters. It should be mentioned that, for validation of presented model, the yielded results of modelling are contrasted with experimental results. This comparison demonstrates that the results of modelling have satisfying compatibility with experimental results. In general, regarding the presented model, 80% of data are in the reliable
range. Hence, utilizing the mentioned equations for modelling of the mid-point deflection of rectangular plates is appropriate. |
| first_indexed | 2024-12-12T02:58:02Z |
| format | Article |
| id | doaj.art-a7af2049faa847cdb98acda454d46536 |
| institution | Directory Open Access Journal |
| issn | 1823-4690 |
| language | English |
| last_indexed | 2024-12-12T02:58:02Z |
| publishDate | 2016-09-01 |
| publisher | Taylor's University |
| record_format | Article |
| series | Journal of Engineering Science and Technology |
| spelling | doaj.art-a7af2049faa847cdb98acda454d465362022-12-22T00:40:41ZengTaylor's UniversityJournal of Engineering Science and Technology1823-46902016-09-0111913111320EXPERIMENTAL STUDY AND MODELLING OF DEFORMATION OF RECTANGULAR PLATES SUBJECTED TO HYDRODYNAMIC LOADING USING NEURAL NETWORKHASHEM BABAEI0TOHID MIRZABABAIE MOSTOFI1MAJID ALITAVOLI2ASGHAR SAEIDINEJAD31Department of Mechanical Engineering, Faculty of Engineering, University of Guilan, Rasht, Iran1Department of Mechanical Engineering, Faculty of Engineering, University of Guilan, Rasht, Iran1Department of Mechanical Engineering, Faculty of Engineering, University of Guilan, Rasht, IranDepartment of Mechanical Engineering, University of Guilan, Campus 2, Rasht, IranIn this paper, experimental responses of fully clamped aluminium and steel rectangular plates are presented subjected to hydrodynamic loading. The GMDHtype neural networks (Group Method of Data Handling) are then used for the modelling of the mid-point deflection thickness ratio of the rectangular plates using the experimental results. The purpose of this modelling is to display how the variations of the significant parameters changes with the mid-point deflection. In addition, the results indicate that dimensionless input variables provide simpler polynomial expressions in comparison with actual physical parameters. It should be mentioned that, for validation of presented model, the yielded results of modelling are contrasted with experimental results. This comparison demonstrates that the results of modelling have satisfying compatibility with experimental results. In general, regarding the presented model, 80% of data are in the reliable range. Hence, utilizing the mentioned equations for modelling of the mid-point deflection of rectangular plates is appropriate.http://jestec.taylors.edu.my/Vol%2011%20issue%209%20September%202016/11_9_7.pdfNeural networkRectangular plateHydrodynamic loadDeformation |
| spellingShingle | HASHEM BABAEI TOHID MIRZABABAIE MOSTOFI MAJID ALITAVOLI ASGHAR SAEIDINEJAD EXPERIMENTAL STUDY AND MODELLING OF DEFORMATION OF RECTANGULAR PLATES SUBJECTED TO HYDRODYNAMIC LOADING USING NEURAL NETWORK Journal of Engineering Science and Technology Neural network Rectangular plate Hydrodynamic load Deformation |
| title | EXPERIMENTAL STUDY AND MODELLING OF DEFORMATION OF RECTANGULAR PLATES SUBJECTED TO HYDRODYNAMIC LOADING USING NEURAL NETWORK |
| title_full | EXPERIMENTAL STUDY AND MODELLING OF DEFORMATION OF RECTANGULAR PLATES SUBJECTED TO HYDRODYNAMIC LOADING USING NEURAL NETWORK |
| title_fullStr | EXPERIMENTAL STUDY AND MODELLING OF DEFORMATION OF RECTANGULAR PLATES SUBJECTED TO HYDRODYNAMIC LOADING USING NEURAL NETWORK |
| title_full_unstemmed | EXPERIMENTAL STUDY AND MODELLING OF DEFORMATION OF RECTANGULAR PLATES SUBJECTED TO HYDRODYNAMIC LOADING USING NEURAL NETWORK |
| title_short | EXPERIMENTAL STUDY AND MODELLING OF DEFORMATION OF RECTANGULAR PLATES SUBJECTED TO HYDRODYNAMIC LOADING USING NEURAL NETWORK |
| title_sort | experimental study and modelling of deformation of rectangular plates subjected to hydrodynamic loading using neural network |
| topic | Neural network Rectangular plate Hydrodynamic load Deformation |
| url | http://jestec.taylors.edu.my/Vol%2011%20issue%209%20September%202016/11_9_7.pdf |
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