Evaluation the effect of heat treatment parameters on morphology and mechanical properties of dual phase steels using neural computation

This study is intended to develop the potential of artificial neural networks (ANN) as an alternative modeling method for predicting the ultimate tensile stress (UTS) and morphology of dual-phase steels. The strategy of experiments consists of three inputs (intercritical annealing temperature, martensite volume fraction and manganese weight percent) and single-output (UTS and morphology) in different analysis steps. The comparison of neuralnetwork model and experimental data, which was obtained by standard tensile test, shows the ability of developed neural network used

Keywords:

Dual phase steel , Artificial neural networks , Simulated annealing