Entropy optimized dissipative CNTs based flow with probable error and statistical declaration
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Updated: Jan 4, 2026

Curtain Flow Column: Optimization of Efficiency and Sensitivity
Published on: June 12, 2016
M Ijaz Khan1, Arfan Ali1, T Hayat2
1Department of Mathematics, Quaid-I-Azam University 45320 Islamabad 44000, Pakistan.
Background:
CNTs are categorized subject to their structures i.e., SWCNTs (single wall nanotubes), DWCNTs (double wall nanotubes) and MWCNTs (multi-wall nanotubes). The various structures have distinct characteristics that make the nanotubes suitable for various physical applications. It is due their unique electrical, mechanical and thermal attributes CNTs present thrilling opportunities for mechanical engineering, industrial, scientific research and commercial applications. There is fruitful potential for carbon nanotubes in the composites business and industry. Today, CNTs find utilization in frequent various products, and analyst continue to explore new applications. Currently applications comprise wind turbines, bicycle components, scanning probe microscopes, flat panel displays, marine paints, sensing devices, electronics, batteries with longer lifetime and electrical circuitry etc. Such applications in mind, entropy optimized dissipative CNTs based flow of nanomaterial by a stretched surface. Flow is caused due to stretching phenomenon and studied in 3D coordinates. Both types of CNTs are studied i.e., SWCNTs and MWCNTs. CNTs are considered for nanoparticles and water for continuous phase fluid. Special consideration is given to the analysis of statistical declaration and probable error for skin friction and Nusselt number. Furthermore, entropy rate is calculated. Entropy rate is discussed in the presence of four main irreversibilities i.e., heat transfer, Joule heating, porosity and dissipation.
Method:
Homotopy technique is utilized to develop the convergence series solutions.
Results:
Impacts of sundry variables subject to both SWCNTs (single) and MWCNTs (multi) are graphically discussed. Statistical analysis and probable error for surface drag force and Nusselt number are numerically calculated subject to various flow variables. Numerical results for such engineering quantities are displayed through tables. In addition, comparative analysis for SWCNTs and MWCNTs are presented for the velocity, concentration and thermal fields.
Conclusions:
Results for entropy rate is calculated in the presence of various sundry variable through implementation of second law of thermodynamics. It is examined from the results that velocity decreases for both CNTs via higher magnetic, inertia coefficient and porosity parameters. Secondary velocity i.e., velocity in g-direction boosts up versus rotation parameter while it declines for larger slip parameter for both CNTs. thermal field intensifies for both CNTs via larger heat generation/absorption parameter. Concentration which shows the mass transfer of species increases subject to higher homogeneous parameter and Schmidt number in case of both CNTs. Entropy rate in more for larger magnetic, Reynolds number and slip parameter. Bejan number boosts up for higher Reynold number and slip parameter while it declines for magnetic parameter.
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