A Numerical Study on MHD 3-D Casson-Nanofluid Flow Past an Exponentially Stretching Sheet with Double Cattaneo-Christov Diffusion Effects

• Murali Gundagani ^[2] ; Venkata Madhu Javvaji ^[3] ; Deepa Gadipalli ^[4] ; Suresh Pallerla ^[4] ; Qasem M. Al-Mdalla ^[1] ; S. M. Bhat ^[5]
  1. [1] United Arab Emirates University

     United Arab Emirates University

     Emiratos Árabes Unidos

     
  2. [2] Department of Freshman Engineering, Geethanjali College of Engineering and Technology, Cheeryal, Hyderabad, 501301, India
  3. [3] Department of Mathematics, Sreenidhi Institute of Science and Technology, Yamnampet, Hyderabad, 501301, India
  4. [4] Department of Mathematics, Chaitanya Bharathi Institute of Technology, Gandipet, Hyderabad, 500075, India
  5. [5] Department of Engineering Science, KBT College of Engineering, Nashik, 422013, India

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• Localización: Métodos numéricos para cálculo y diseño en ingeniería: Revista internacional, ISSN 0213-1315, Vol. 41, Nº 2, 2025, 19 págs.
• Idioma: español
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  • A numerical study of a three-dimensional steady-state flow of a viscous incompressible Casson fluid containing nanofluid particles interacting with a stretching sheet is the primary focus of this work. The equations for concentration and energy include the Cattaneo-Christov double diffusion effects. This work transforms deriving the controlling boundary layer equations into similarity equations using non-linear similarity transformations in three-dimensional analyses. To evaluate this study, the following was done. In the case of the combined Runge-Kutta method and the shooting approach, it is possible to provide an analytical solution for the obtained equations. Moreover, a comparative analysis of the collected data with previously published results under certain circumstances demonstrates a significant concordance between the two sets of findings. The problem is governed by thirteen physical parameters. Figures and tables are used to depict the effects of different characteristics in the following chapters, including temperature, velocity, and concentration profiles, on distinct flow distributions.