Application of neural-networks and neuro-fuzzy systems for the prediction of short-duration forces acting on the blunt bodies

Present studies deal with application of finite element method and intelligent soft computing techniques viz. neural network (NN) and adaptive neuro-fuzzy inference system (ANFIS) for the prediction of short duration impulse, ramp and hat forces. Two blunt bodies viz. a hemisphere and a blunt cone with cylindrical aft body have been considered in these investigations. Training of the NN and ANFIS has been carried out using one axial acceleration and two normal accelerations obtained from known input forces and a moment. It is shown here that the NN is unable to recover the unknown forces and moment. However, ANFIS-based strategy is found better for prediction of the same forces and moment. Thus, novelty of these studies exists in the assessment and successful implementation of the soft computing techniques like NN and ANFIS for prediction of the unknown short-duration force and moment time histories. These predictions are also cross-checked for the error, and it has been observed that the ANFIS can be used for short-duration force prediction in high-speed aerospace applications.