TY - JOUR
TI - Numerical simulation of Jeffrey fluid-flow using ANN-LMM with Cattaneo-Christov heat flux in rotating and squeezing domains
AU - Mahariq Ibrahim
AU - Islam Saeed
AU - Ali Ishtiaq
AU - Ullah Kashif
AU - Fiza Mehreen
AU - Ullah Hakeem
AU - Akgul Ali
JN - Thermal Science
PY - 2025
VL - 29
IS - 5
SP - 3697
EP - 3705
PT - Article
AB - The current communication studies the artificial neural networks with  Levenberg-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 with ANN-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, β. The velocity profile  decreases for the parameters rotation, ω, and relaxation time parameters,  λ1. 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 λ1 and squeezing parameter decreases.