Development of ANN model and study the effect of temperature on strain ratio and sensitivity index of EDD steel

Abstract

Anisotropy and strain rate sensitivity index (m) plays a very important role in the formability of materials. In the present investigation strain ratios in 0°, 45° and 90° to the rolling direction and the strain rate sensitivity index were calculated at different temperatures. After developing the data from experiments, Artificial Neural Network (ANN) models are trained for different properties. Trained ANN models are used to calculate different strain ratios and sensitivity index at unknown temperatures. The results are promising and the percentage error in ANN prediction is found to be around 10%.