The deformation behavior of metal materials in plastic forming is intimately related to
deformation conditions, which are greatly affected by deformation rate, forming temperature …

Artificial neural networks are an effective and frequently used modelling method in
regression and classification tasks in the area of steels and metal alloys. New publications …

Correctly determining the onset of fracture is crucial when performing mechanical
experiments. Commonly carried out by visual inspection, here an image-based machine …

Hot forming is an essential part of the manufacturing of most steel products. The hot
deformation behaviour is determined by temperature, strain rate, strain and chemical …

Aluminum alloys have low weldability by conventional fusion welding processes. Friction stir
welding (FSW) is a promising alternative to traditional fusion welding techniques for …

Abstract Ti-6Al-4V alloy is one of the most widely used material in both research as well as
in commercial industries at present due to its high strength-to-weight ratio, low density and …

The behavior of hot deformed flow curves in a 9Cr-1Mo steel have been analysed using
constitutive and artificial neural network (ANN) approaches. At each temperature (850° C …

The hot compressive tests of 6082 aluminum alloy were conducted on a Gleeble-3500
thermomechanical simulator at temperature ranges of 380-530° C and strain rate range of …

In the current work, the automated fracture identification in material testing experiments is
investigated through deep learning convolutional neural network (CNN) techniques. Three …

In this investigation, processing maps and artificial neural network (ANN) models were
carried out to describe and predict the flow behavior of pure aluminum at various initial grain …