NUMERICAL SIMULATION OF JEFFREY FLUID-FLOW USING ANN-LMM WITH CATTANEO-CHRISTOV HEAT FLUX IN ROTATING AND SQUEEZING DOMAINS

Abstract

The current communication studies the artificial neural networks with Leven-berg-Marquardt method (ANN-LMM) based back propagation find the solutions of thermal radiation on squeezing Jeffrey fluid-flow with heat flux in a rotating frame. Also the heat and mass transfer aspects are examined in the occurrence of the Cattaneo-Christov heat flux model (CCHFM). The governing equations of Navier-Stokes equations with the help of similarity transformation a set of boundary value problem is achived. The numerical method is along withANN-LMM. The Jeffrey fluid is tested for accuracy in the range of E-7 to E-4 by achieving a excellent agreement with the obtainable solutions and is further authorized by error histograms and regression steps. The impact of the physical parameters on the velocity and temperature profiles are discussed briefly. The velocity profile increases with the squeezing parameter and the Deborah number, beta. The velocity profile decreases for the parameters rotation, omega, and relaxation time parameters, lambda(1). Temperature profile decreases for the large value of the squeezing, themal relaxation parameter, and Prandtl number. For the larger value of the Deborah number and rotation parameter, the skin friction coefficient enhance, While for the lambda(1) and squeezing parameter decreases.