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Numerical Modeling on Buckling Behavior of Structural Stiffened Panel
Stiffened panels are essential building elements in weight-sensitive structures. They have various applications in marine, aircraft, and other structures. Plate structures can undergo buckling when subjected to axial compression loads and then exhibit out of plane displacements. The present work aims to study the buckling behavior of the stiffened panel. The finite element model of the stiffened panel is developed, and buckling analysis is performed using ANSYS software. This model is validated with the published experimental work. Once the model is validated, total of 320 numbers of models of stiffened panels with varying plate thickness, stiffener height, stiffener thickness, and distance between stiffeners are modeled in ANSYS-2020, and buckling analysis is performed. An artificial neural network model is proposed to predict the buckling load of the stiffened panel. Neural network model is created in MATLAB software, and it is trained, tested, and validated, and its performance is checked by statistical relations like coefficient of correlation and mean square error. Proposed ANN model shows high accuracy in the prediction of buckling load.
Numerical Modeling on Buckling Behavior of Structural Stiffened Panel
Stiffened panels are essential building elements in weight-sensitive structures. They have various applications in marine, aircraft, and other structures. Plate structures can undergo buckling when subjected to axial compression loads and then exhibit out of plane displacements. The present work aims to study the buckling behavior of the stiffened panel. The finite element model of the stiffened panel is developed, and buckling analysis is performed using ANSYS software. This model is validated with the published experimental work. Once the model is validated, total of 320 numbers of models of stiffened panels with varying plate thickness, stiffener height, stiffener thickness, and distance between stiffeners are modeled in ANSYS-2020, and buckling analysis is performed. An artificial neural network model is proposed to predict the buckling load of the stiffened panel. Neural network model is created in MATLAB software, and it is trained, tested, and validated, and its performance is checked by statistical relations like coefficient of correlation and mean square error. Proposed ANN model shows high accuracy in the prediction of buckling load.
Numerical Modeling on Buckling Behavior of Structural Stiffened Panel
Lecture Notes in Civil Engineering
Hau, Kong Kian (editor) / Gupta, Ashok Kumar (editor) / Chaudhary, Sandeep (editor) / Gupta, Tanmay (editor) / Alagundi, Shreyas (author) / Palanisamy, T. (author)
Recent Advances in Structural Engineering and Construction Management ; Chapter: 8 ; 77-87
2022-09-28
11 pages
Article/Chapter (Book)
Electronic Resource
English
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