The aim of this investigation was determining the fatigue behaviour of welded aluminium joints and so the appertaining SN-lines by application of Artificial Neural Network (ANN) architectures. For this, fatigue data obtained with aluminium welded joints subjected to constant amplitude loading were used. The main benefit of ANN is the good description of the effects of different factors on fatigue life. The results determined by the ANN method for four aluminium alloys are displayed in scatter bands of SN-lines. It is observed that the trained results are in good agreement with the tested data and enable the estimation of SN-lines
Artificial neural networks (ANNs) were used to predict the residual strength of glass fibre-reinforc...
In this study, a static shear force and fatigue life prediction model was developed using artificial...
Suitable methods and transferability criteria and knowledge of the cyclic material behaviour is esse...
The aim of this investigation was determining the fatigue behaviour of welded aluminium joints and s...
The aim of this investigation was determining the fatigue behaviour of welded aluminium joints and s...
This study presents a model for estimating the fatigue life of magnesium and aluminium non-penetrate...
This study presents a model for estimating the fatigue life of magnesium and aluminium non-penetrate...
The applicability of artificial neural networks (ANN) in predicting the strain-life fatigue properti...
In this study, a static shear force and fatigue life prediction model was developed using artificial...
This article discusses the results of studies using the developed artificial neural networks in the ...
ARCAKLIOGLU, Erol/0000-0001-8073-5207WOS: 000242785600009An artificial neural network (ANN) model wa...
A large number of oil and gas pipelines in the Russian Federation have been in operation for over 20...
In this study, fatigue life predictions for the various metal matrix composites, R ratios, notch geo...
Artificial neural networks (ANN) are extensively utilized in structural health monitoring. Neverthel...
The current financial climate is driving a move towards increased use of computer modelling techniqu...
Artificial neural networks (ANNs) were used to predict the residual strength of glass fibre-reinforc...
In this study, a static shear force and fatigue life prediction model was developed using artificial...
Suitable methods and transferability criteria and knowledge of the cyclic material behaviour is esse...
The aim of this investigation was determining the fatigue behaviour of welded aluminium joints and s...
The aim of this investigation was determining the fatigue behaviour of welded aluminium joints and s...
This study presents a model for estimating the fatigue life of magnesium and aluminium non-penetrate...
This study presents a model for estimating the fatigue life of magnesium and aluminium non-penetrate...
The applicability of artificial neural networks (ANN) in predicting the strain-life fatigue properti...
In this study, a static shear force and fatigue life prediction model was developed using artificial...
This article discusses the results of studies using the developed artificial neural networks in the ...
ARCAKLIOGLU, Erol/0000-0001-8073-5207WOS: 000242785600009An artificial neural network (ANN) model wa...
A large number of oil and gas pipelines in the Russian Federation have been in operation for over 20...
In this study, fatigue life predictions for the various metal matrix composites, R ratios, notch geo...
Artificial neural networks (ANN) are extensively utilized in structural health monitoring. Neverthel...
The current financial climate is driving a move towards increased use of computer modelling techniqu...
Artificial neural networks (ANNs) were used to predict the residual strength of glass fibre-reinforc...
In this study, a static shear force and fatigue life prediction model was developed using artificial...
Suitable methods and transferability criteria and knowledge of the cyclic material behaviour is esse...