Matlab Code For Keller Box Method ((LINK))
Matlab Code For Keller Box Method
heat transfer in the presence of magnetic field is investigated in the physical situation with heat transfer in a channel. the mathematical model is expressed in the terms of similarity, and the variables involved in the flow are selected by minimizing the error function obtained in the experimentation. the heat transfer coefficients are obtained. the coefficients of the governing equations are determined, and the heat transfer coefficient is obtained. the experimental and numerical results obtained by using the matlab codes are found to be in good agreement.
the keller-box method is a numerical technique for solving two-dimensional steady or time-dependent boundary layer problems. the technique was proposed by cebeci and bradshaw [ 2 ] and then developed and applied by cebeci [ 3 ]. the method for solving steady problems is as follows: the equation to be solved is written in terms of boundary layer variables, and then the boundary layer variables are introduced to a function that generates a keller-box. the continuity equation is considered in its form in terms of boundary layer variables, and then it is reduced to two independent equations, which are solved using keller-box method. the boundary conditions are determined by matching the solution of the equation to that of the equation. after the solution of each boundary layer equation is obtained, the boundary conditions are applied. the boundary conditions must be chosen in such a way that the solution obtained by the keller-box method is physically consistent and matches the solution of the original equation. the technique was extended to time-dependent problems by cebeci [ 4 ].
This element will provide an illustration of stochastic analysis: In the past, the primary issues involved with this region had been to focus on approximations of systems of stochastic differential equations or the time series for ergodic stochastic processes (eg, Levy flights). However, the issue of which derivation was the best route to be utilized is still open. This study intends to present an attempt to address these queries by comparing the properties of the two leading kinds of stochastic analysis: The stochastic differential equations-based versus the probability based-analysis. This study will discuss a wide range of systems of stochastic differential equations for handling a variety of oscillatory, random, and non-deterministic phenomena in several fields, followed by comparison with the properties of these systems using the probability method.
This book contains one of the best theoretical and practical books on diffraction gratings which deals with the full range of design, fabrication, characterization and performance of diffraction gratings. The book was written by a group of well-known researchers working in various fields of optics, i.e., micro-optics, nano-optics, quantum optics and photonic circuits, and group of researchers working in the field of photonics. The book discusses the fundamental concepts and design methods of diffraction gratings, such as theory of diffraction gratings, grating fabrication methods, optical characteristics of diffraction gratings, etc. This book contains varied collections of applications that are usually not found in the existing books on diffraction gratings. These include nonlinear optics, image sensing, holography, and incoherent and coherent optical communications. Apart from the mentioned applications, the book includes several other applications that are related to the classical diffraction phenomena, such as scattered field diffraction, Fresnel diffraction from aperiodic surface, Bragg diffraction, etc.