• Advances in nano research
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• 제10권3호
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• pp.271-280
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• 2021

The present work deals with an investigation on longitudinal wave propagation in nanobeams made of graphene sheets, for the first time. The nanobeam is modelled via a higher-order shear deformation theory accounts for both higher-order and thickness stretching terms. The general nonlocal strain gradient theory including nonlocality and strain gradient characteristics of size-dependency in order is used to examine the small-scale effects. This model has three-small scale coefficients in which two of them are for nonlocality and one of them applied for gradient effects. Hamilton supposition is applied to obtain the governing motion equation which is solved using a harmonic solution procedure. It is indicated that the longitudinal wave characteristics of the nanobeams are significantly influenced by the nonlocal parameters and strain gradient parameter. It is shown that higher nonlocal parameter is more efficient than lower nonlocal parameter to change longitudinal phase velocities, while the strain gradient parameter is the determining factor for their efficiency on the results.

• Steel and Composite Structures
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• 제47권5호
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• pp.601-613
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• 2023

Numerous methods have been proposed in predicting formability of sheet metals based on microstructural and macro-scale properties of sheets. However, there are limited number of papers on the optimization problem to increase formability of sheet metals. In the present study, we aim to use novel optimization algorithms in neural networks to maximize the formability of sheet metals based on tensile curve and texture of aluminum sheet metals. In this regard, experimental and numerical evaluations of effects of texture and tensile properties are conducted. The texture effects evaluation is performed using Taylor homogenization method. The data obtained from these evaluations are gathered and utilized to train and validate an artificial neural network (ANN) with different optimization methods. Several optimization method including grey wolf algorithm (GWA), chimp optimization algorithm (ChOA) and whale optimization algorithm (WOA) are engaged in the optimization problems. The results demonstrated that in aluminum alloys the most preferable texture is cube texture for the most formable sheets. On the other hand, slight differences in the tensile behavior of the aluminum sheets in other similar conditions impose no significant decreases in the forming limit diagram under stretch loading conditions.