This research examines the thin-film nanomaterial movement in three dimensions over a stretchable rotating inclined surface. Similarity variables are used to transform fundamental systems of equations into a set of first-order differential equations. The Runge–Kutta Fourth Order approach is utilized for numerical computations. The impact of embedded parameters (variable thickness, unsteadiness, Prandtl number, Schmidt number, Brownian-motion, and thermophoretic) is examined carefully. Physically and statistically, the indispensable terms namely Nusselt and Sherwood numbers are also investigated. Results indicated that, as the dimensionless parameter S raises, the temperature field decreases. In reality, as the values of S increases, heat transmission rate from the disc to the flowing fluid reduces. Internal collisions of liquid particles are physically hampered at a low rate. The momentum boundary layer is cooled when the parameter S is increased, as a consequence local Nusselt number rises. Sherwood number decreases as the parameter S increases because of inter collision of the microscopic fluid particles. Enhancing in the apparent viscosity and concentrations of the chemical reactions, a higher Schmidt number, Sc, lowers the Sherwood number. With increasing values of Prandtl number the Nusselt number decreases. For validation purpose, the RK4 method is also compared with homotopy analysis method (HAM). The results are further verified by establishing an excellent agreement with published data.
Electricity theft and fraud in energy consumption are two of the major issues for power distribution companies (PDCs) for many years. PDCs around the world are trying different methodologies for detecting electricity theft. The traditional methods for non-technical losses (NTLs) detection such as onsite inspection and reward and penalty policy have lost their place in the modern era because of their ineffective and time-consuming mechanism. With the advancement in the field of Artificial Intelligence (AI), newer and efficient NTL detection methods have been proposed by different researchers working in the field of data mining and AI. The AI-based NTL detection methods are superior to the conventional methods in terms of accuracy, efficiency, time-consumption, precision, and labor required. The importance of such AI-based NTL detection methods can be judged by looking at the growing trend toward the increasing number of research articles on this important development. However, the authors felt the lack of a comprehensive study that can provide a one-stop source of information on these AI-based NTL methods and hence became the motivation for carrying out this comprehensive review on this significant field of science. This article systematically reviews and classifies the methods explored for NTL detection in recent literature, along with their benefits and limitations. For accomplishing the mentioned objective, the opted research articles for the review are classified based on algorithms used, features extracted, and metrics used for evaluation. Furthermore, a summary of different types of algorithms used for NTL detection is provided along with their applications in the studied field of research. Lastly, a comparison among the major NTL categories, i.e., data-based, network-based, and hybrid methods, is provided on the basis of their performance, expenses, and response time. It is expected that this comprehensive study will provide a one-stop source of information for all the new researchers and the experts working in the mentioned area of research.
The present work discusses the 2D unsteady flow of second grade hybrid nanofluid in terms of heat transfer and MHD effects over a stretchable moving flat horizontal porous plate. The entropy of system is taken into account. The magnetic field and the Joule heating effects are also considered. Tiny-sized nanoparticles of silicon carbide and titanium oxide dispersed in a base fluid, kerosene oil. Furthermore, the shape factors of tiny-sized particles (sphere, bricks, tetrahedron, and platelets) are explored and discussed in detail. The mathematical representation in expressions of PDEs is built by considering the heat transfer mechanism owing to the effects of Joule heating and viscous dissipation. The present set of PDEs (partial differential equations) are converted into ODEs (ordinary differential equations) by introducing suitable transformations, which are then resolved with the bvp4c (shooting) scheme in MATLAB. Graphical expressions and numerical data are obtained to scrutinize the variations of momentum and temperature fields versus different physical constraints.
In this study, we have used Lie group analysis procedure to propose a novel model for transforming the governing equations of double diffusive MHD hyperbolic tangent fluid flow model into a system of nonlinear ordinary differential equations (ODEs). The solution of these equations is then investigated numerically by employing Shooting method. We also reported and presented our results graphically illustrating the results and analysis of physical parameters on concentration, velocity, and temperature profiles and on other physical quantities present in the flow model. The results show that fluid temperature increases with rise in the modified Dufour and velocity slip parameters whereas opposite behavior is observed for thermal slip parameter. Moreover, the Nusselt number declines with enhanced values of modified Dufour parameter whereas its opposite effect has been observed for Dufour-solutal Lewis number and Prandtl number.
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