External aerodynamic investigation over Ahmed body for optimal topology selection between upper and under bodywork using ANN approach

Aerodynamic improvements primarily result in decreased fuel usage and carbon dioxide emissions into the atmosphere. Numerous governments support ongoing aerodynamics development initiatives as a means of addressing the energy problem and reducing air pollution, Ahmed body investigation helps research to investigate versatile approaches and flexibility of design. This study is carried over a generic design of Ahmed body model. We attempted a passive arrangement system to reduce drag coefficient with a correlation of cases such as in primary objective varying parameter of slant angle from 20∘ to 30∘ proposed to monitor the behavior of drag coefficient. Once we finalized the optimum slant angle, which gives a lower drag coefficient, the next proposed configuration is to vary passive arrangement between lower and upper blend length to see the deflection of the boundary layer in correlation with the drag coefficient. The final topology is selected, which gives the lowest drag coefficient. The post-process correlation study was proposed by using an artificial neural network (ANN) scheme. The ANN model is developed between an achieved set of data from CFD investigation, ANN model indicates a strong correlation between the varying percentage of blend angle and increment percentage of the drag coefficient.