Application of Soft Computing Paradigm to Large Deformation Analysis of Cantilever Beam under Point Load
In this paper, a mathematical model for large deformation of a cantilever beam subjected to tip-concentrated load is presented. The model is governed by nonlinear differential equations. Large deformation of a cantilever beam has number of applications is structural engineering. Since finding an exa...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2021/2182693 |
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| author | Yanmei Cui Yong Hong Naveed Ahmad Khan Muhammad Sulaiman |
| author_facet | Yanmei Cui Yong Hong Naveed Ahmad Khan Muhammad Sulaiman |
| author_sort | Yanmei Cui |
| collection | DOAJ |
| description | In this paper, a mathematical model for large deformation of a cantilever beam subjected to tip-concentrated load is presented. The model is governed by nonlinear differential equations. Large deformation of a cantilever beam has number of applications is structural engineering. Since finding an exact solution to such nonlinear models is difficult task, this paper focuses on developing soft computing technique based on artificial neural networks (ANNs), generalized normal distribution optimization (GNDO) algorithm, and sequential quadratic programming (SQP). The strength of ANN modeling for governing the equation of cantilever beam is exploited by the global search ability of GNDO and further explored by the local search mechanism of SQP. Design scheme is evaluated for different cases depending on variations in dimensionless end-point load ρ. Furthermore, to validate the effectiveness and convergence of algorithm proposed technique, the results of the differential transformation method (DTM) and exact solutions are compared. The statistical analysis of performance indicators in terms of mean, median, and standard deviations further establishes the worth of ANN-GNDO-SQP algorithm. |
| format | Article |
| id | doaj-art-fad8759196264aef88cdcf1f86fe9796 |
| institution | Kabale University |
| issn | 1099-0526 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-fad8759196264aef88cdcf1f86fe97962025-02-03T05:45:37ZengWileyComplexity1099-05262021-01-01202110.1155/2021/2182693Application of Soft Computing Paradigm to Large Deformation Analysis of Cantilever Beam under Point LoadYanmei Cui0Yong Hong1Naveed Ahmad Khan2Muhammad Sulaiman3School of Mechanical EngineeringSchool of Mechanical EngineeringDepartment of MathematicsDepartment of MathematicsIn this paper, a mathematical model for large deformation of a cantilever beam subjected to tip-concentrated load is presented. The model is governed by nonlinear differential equations. Large deformation of a cantilever beam has number of applications is structural engineering. Since finding an exact solution to such nonlinear models is difficult task, this paper focuses on developing soft computing technique based on artificial neural networks (ANNs), generalized normal distribution optimization (GNDO) algorithm, and sequential quadratic programming (SQP). The strength of ANN modeling for governing the equation of cantilever beam is exploited by the global search ability of GNDO and further explored by the local search mechanism of SQP. Design scheme is evaluated for different cases depending on variations in dimensionless end-point load ρ. Furthermore, to validate the effectiveness and convergence of algorithm proposed technique, the results of the differential transformation method (DTM) and exact solutions are compared. The statistical analysis of performance indicators in terms of mean, median, and standard deviations further establishes the worth of ANN-GNDO-SQP algorithm.http://dx.doi.org/10.1155/2021/2182693 |
| spellingShingle | Yanmei Cui Yong Hong Naveed Ahmad Khan Muhammad Sulaiman Application of Soft Computing Paradigm to Large Deformation Analysis of Cantilever Beam under Point Load Complexity |
| title | Application of Soft Computing Paradigm to Large Deformation Analysis of Cantilever Beam under Point Load |
| title_full | Application of Soft Computing Paradigm to Large Deformation Analysis of Cantilever Beam under Point Load |
| title_fullStr | Application of Soft Computing Paradigm to Large Deformation Analysis of Cantilever Beam under Point Load |
| title_full_unstemmed | Application of Soft Computing Paradigm to Large Deformation Analysis of Cantilever Beam under Point Load |
| title_short | Application of Soft Computing Paradigm to Large Deformation Analysis of Cantilever Beam under Point Load |
| title_sort | application of soft computing paradigm to large deformation analysis of cantilever beam under point load |
| url | http://dx.doi.org/10.1155/2021/2182693 |
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