Prediction of Internal Flow’s Characteristics Around Two Cylinders in Tandem using optimal T-S fuzzy

Laminar unsteady incompressible flow past two-cylinders in tandem is investigated numerically. The vortex shedding over the cylinders' arrangement is studied at various Reynolds numbers and blockage ratios while changing the distance between the two cylinders. The output from the numerical simulations is used to feed different regression methodologies to find the optimal approach for the proposed system modeling and identification. Artificial Neural Network (ANN) using Levenberg-Marquardt Algorithm (LM) training algorithm is used, as well as Takagi-Sugeno (T-S) fuzzy model are used and optimized using Particle swarm optimizer (PSO) in order to enhance the system model features. A comparison analysis is performed between the proposed ANN and T-S fuzzy models shows the superior ability of nonlinear modeling of T-S fuzzy with PSO over ANN.