Application of artificial neural networks to the evaluation of the ultimate strength of uniaxially compressed welded stiffened aluminium plates

Zareei, Mohammad Reza; Khedmati, Mohammad Reza; Rigo, Philippe

doi:10.1177/1475090212445865

Cited by 4 publications

(3 citation statements)

References 21 publications

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“…Benson et al (2011) investigated the ultimate strength characteristics of aluminium plates for high-speed vessels. Artificial neural networks (ANNs) were applied by Zareei et al (2012) in order to evaluate the ultimate strength of uniaxially compressed welded stiffened aluminium plates. Also, the effects of geometrical imperfections on the ultimate strength of aluminium stiffened plates subject to combined longitudinal compression and lateral pressure were studied by Khedmati et al (2014).…”

Section: Introductionmentioning

confidence: 99%

Empirical formulations for estimation of ultimate strength of continuous aluminium stiffened plates under combined transverse compression and lateral pressure

Khedmati

Memarian

Fadavie

et al. 2014

Ships and Offshore Structures

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Empirical expressions are developed for predicting ultimate compressive strength of welded aluminium stiffened plates used in marine applications under combined transverse in-plane compression and different levels of lateral pressure. A database of the ultimate transverse strengths for aluminium stiffened plates numerically obtained by the authors is used for deriving formulations as functions of two parameters, namely the plate slenderness ratio and the column (stiffener) slenderness ratio. Regression analysis is used in order to derive the empirical formulations. The formulae implicitly include the effects of the weld on the initial imperfections and the heat-affected zone.

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Section: Introductionmentioning

confidence: 99%

Empirical formulations for estimation of ultimate strength of continuous aluminium stiffened plates under combined transverse compression and lateral pressure

Khedmati

Memarian

Fadavie

et al. 2014

Ships and Offshore Structures

Self Cite

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“…Several studies have been conducted to predict the ultimate strength of structural members using ANN. Zareei et al [6] estimated the ultimate strength of stiffened aluminum plates with flat-bar stiffeners under in-plane longitudinal compression loads using an ANN. When comparing this value with the ultimate strength obtained using empirical equations, it was confirmed that the model prediction was close to the FEM result.…”

Section: Introductionmentioning

confidence: 99%

A Novel Deep Learning Model to Predict Ultimate Strength of Ship Plates under Compression

2022

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The evaluation of ship strength during the hull structure design stage is essential for structural safety. Additionally, plate is one of the basic structural members of the hull, it is important to analyze and predict the ultimate strength. The curved plate used for shipbuilding must be able to withstand repeated axial loads and complex loads, and stability needs to be confirmed through ultimate strength analysis. In general situations, the magnitude of the transverse compression is smaller than that of the longitudinal and combined loads, but transverse compression causes different physical behaviors from the longitudinal load state, which affects the ultimate strength, so study on the ultimate strength of the curved-plate under transverse compression is essential. Therefore, in this paper, a curved plate under transverse compressive load was selected as a subject, and the ultimate strength of the curved plate under the corresponding compression condition was predicted using a deep learning model. To obtain the training data for the deep-learning model, 4050 cases were selected and analyzed using the ANSYS. The accuracy of the model was verified by comparing the results predicted by the model and empirical equations with those of the FEM analysis. The study shows that it is possible to consider the ultimate strength more efficiently in the initial design stage of the ship.

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“…Zareei et al [6] performed a series of elastoplastic large-deflection analyses of stiffened aluminum plates and applied artificial neural network to predict the ultimate compressive strength.…”

Section: Introductionmentioning

confidence: 99%

Effect of geometrical properties of aluminum extrusion on post-buckling behaviour of stiffened panels in marine applications

Elmalaki

Saad-Eldeen

El-Kilani

2021

Port-Said Engineering Research Journal

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The aim of the present paper is to define guidelines for the appropriate selection of the optimal geometrical characteristics for different aluminum extruded profiles based on the ultimate load carrying capacity as well as the post-collapse deformed shape of stiffened panels. A series of finite element analysis has been conducted for stiffened aluminum panels subjected to uniaxial compressive load; the master model has been validated based on full-scale experimental test results. The effect of open and closed section dimensions on the ultimate compressive capacity has been investigated. The analyses are performed for several cross-sections classified in groups, all with the same plate and column slenderness. The numerical results obtained are compared with the design capacity according to European standard for aluminum structures, Eurocode 9. Based on the comparative analysis, several concluding remarks ad recommendations which are benefit both design and repair strategies are summarized, and a criterion has been proposed for selecting the best cross-section considering both load carrying capacity and cross-section weight.

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Application of artificial neural networks to the evaluation of the ultimate strength of uniaxially compressed welded stiffened aluminium plates

Cited by 4 publications

References 21 publications

Empirical formulations for estimation of ultimate strength of continuous aluminium stiffened plates under combined transverse compression and lateral pressure

Empirical formulations for estimation of ultimate strength of continuous aluminium stiffened plates under combined transverse compression and lateral pressure

A Novel Deep Learning Model to Predict Ultimate Strength of Ship Plates under Compression

Effect of geometrical properties of aluminum extrusion on post-buckling behaviour of stiffened panels in marine applications

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