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| Reference : Application of artificial neural networks to the evaluation of the ultimate strength of ... |
| Scientific journals : Article | |||
| Engineering, computing & technology : Civil engineering | |||
| http://hdl.handle.net/2268/130938 | |||
| Application of artificial neural networks to the evaluation of the ultimate strength of uniaxially compressed welded stiffened aluminium plates | |
| English | |
| Zareei, Mohammad Reza [] | |
| Khedmati, Mohammad Reza [] | |
Rigo, Philippe  [Université de Liège - ULg > Département ArGEnCo > Constructions hydrauliques et navales >] | |
| 1-Jun-2012 | |
| Proceedings of the Institution of Mechanical Engineers. Part M, Journal of Engineering for the Maritime Environment | |
| International | |
| 1475-0902 | |
| [en] Ultimate strength ; stiffened aluminium plates ; axial compression ; empirical formulation ; heat-affected zone ; finite element method ; artificial neural networks | |
| [en] A series of elastoplastic large-deflection finite element analyses is performed on stiffened aluminium plates with flat-bar
stiffeners under in-plane longitudinal compression loads. Then, the closed-form ultimate compressive strength formula is derived for stiffened aluminium plates by regression analysis. Finally, artificial neural network methodology is applied to predict the ultimate strength of uniaxially compressed stiffened aluminium plates. It is found that artificial neural network models can produce a more accurate prediction of the ultimate strength of the stiffened aluminium plates than can the existing empirical formula. | |
| Researchers | |
| http://hdl.handle.net/2268/130938 |
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