Modeling and optimization of parameters for high-temperature solid particle erosion of the AISI 446SS using RSM and ANN

In the present study, the effect of high-temperature erosion of AISI 446SS in the temperature range of 350 °C–750 °C using 50 μ m alumina particle with the impact angle of 30° − 90° and velocity of 40–100 m s −1 is studied using Air Erosion Test Rig, keeping Abrasive flux rate constant at 4.2 gm min −1 . Increase in erosion rate (ER) is seen with increasing temperature, which is attributed to change in properties of materials at elevated temperature. A second order polynomial model is developed using response surface methodology (RSM), and effect of the main and interactive parameters on erosion rate is optimized. A well trained artificial neural network (ANN) with back propagation algorithm is used to verify the optimized parameters for erosion rate generated by RSM.