Modeling and Analysis of Modern Fluids helps researchers solve physical problems observed in fluid dynamics and related fields, such as heat and mass transfer, boundary layer phenomena, and numerical heat transfer. These problems are characterized by nonlinearity and large system dimensionality, and 'exact' solutions are impossible to provide using the conventional mixture of theoretical and analytical analysis with purely numerical methods. To solve these complex problems, this work provides a toolkit of established and novel methods drawn from the literature across nonlinear approximation theory. It covers Padé approximation theory, embedded-parameters perturbation, Adomian decomposition, homotopy analysis, modified differential transformation, fractal theory, fractional calculus, fractional differential equations, as well as classical numerical techniques for solving nonlinear partial differential equations. In addition, 3D modeling and analysis are also covered in-depth. - Systematically describes powerful approximation methods to solve nonlinear equations in fluid problems - Includes novel developments in fractional order differential equations with fractal theory applied to fluids - Features new methods, including Homotypy Approximation, embedded-parameter perturbation, and 3D models and analysis

This book is a printed edition of the Special Issue "The Craft of Fractional Modelling in Science and Engineering" that was published in Fractal Fract

This book is devoted to current problems of artificial and computational intelligence including decision-making systems. Collecting, analysis, and processing information are the current directions of modern computer science. Development of new modern information and computer technologies for data analysis and processing in various fields of data mining and machine learning creates the conditions for increasing effectiveness of the information processing by both the decrease of time and the increase of accuracy of the data processing. The book contains of 54 science papers which include the results of research concerning the current directions in the fields of data mining, machine learning, and decision making. The papers are divided in terms of their topic into three sections. The first section "Analysis and Modeling of Complex Systems and Processes" contains of 26 papers, and the second section "Theoretical and Applied Aspects of Decision-Making Systems" contains of 13 papers. There are 15 papers in the third section "Computational Intelligence and Inductive Modeling". The book is focused to scientists and developers in the fields of data mining, machine learning and decision-making systems.

It is very well known that differential equations are related with the rise of physical science in the last several decades and they are used successfully for models of real-world problems in a variety of fields from several disciplines. Additionally, difference equations represent the discrete analogues of differential equations. These types of equations started to be used intensively during the last several years for their multiple applications, particularly in complex chaotic behavior. A certain class of differential and related difference equations is represented by their respective fractional forms, which have been utilized to better describe non-local phenomena appearing in all branches of science and engineering. The purpose of this book is to present some common results given by mathematicians together with physicists, engineers, as well as other scientists, for whom differential and difference equations are valuable research tools. The reported results can be used by researchers and academics working in both pure and applied differential equations.

Researches and investigations involving the theory and applications of integral transforms and operational calculus are remarkably wide-spread in many diverse areas of the mathematical, physical, chemical, engineering and statistical sciences. This Special Issue contains a total of 36 carefully-selected and peer-reviewed articles which are authored by established researchers from many countries. Included in this Special Issue are review, expository and original research articles dealing with the recent advances on the topics of integral transforms and operational calculus as well as their multidisciplinary applications

Nanofluids: Advanced Applications and Numerical Simulations combines the mathematical and numerical studies of nanofluids and their application to a range of applications. The book begins by introducing the principles of nanofluids, structures, types, properties, methods and stability. This is followed by a detailed chapter that explains a full range of numerical techniques for the modeling of nanofluids. Subsequent chapters offer in-depth coverage of target areas, including cooling and heating applications, micro-electric and magnetic devices, chemistry and oil recovery, biomedicine, renewable energy, and automotive engineering. Throughout the book, methods for numerical modelling are described in detail, with supporting equations, techniques, and applied examples. This is a valuable resource for advanced students, scientists, engineers, and R&D professionals working with nanofluids, simulation, and numerical methods for advanced applications, as well as researchers across nanotechnology, biomedicine, electronics, energy, chemistry, materials science and mechanical engineering. - Presents numerical methods for modelling of nanofluids in details - Examines stability, magnetic field, electric field, and other effects on behavior and optical properties - Explores cutting-edge applications of nanofluids by numerical methods

This thesis reports the calculation of neutrino production for the T2K experiment; the most precise a priori estimate of neutrino production that has been achieved for any accelerator-based neutrino oscillation experiment to date. The production of intense neutrino beams at accelerator facilities requires exceptional understanding of chains of particle interactions initiated within extended targets. In this thesis, the calculation of neutrino production for T2K has been improved by using measurements of particle production from a T2K replica target, taken by the NA61/SHINE experiment. This enabled the reduction of the neutrino production uncertainty to the level of 5%, which will have a significant impact on neutrino oscillation and interaction measurements by T2K in the coming years. In addition to presenting the revised flux calculation methodology in an accessible format, this thesis also reports a joint T2K measurement of muon neutrino and antineutrino disappearance, and the accompanying electron neutrino and antineutrino appearance, with the updated beam constraint.

This book provides a general introduction to fluid mechanics in the form of biographies and popular science. Based on the author’s extensive teaching experience, it combines natural science and human history, knowledge inheritance and cognition law to replace abstract concepts of fluid mechanics with intuitive and understandable physical concepts. In seven chapters, it describes the development of fluid mechanics, aerodynamics, hydrodynamics, computational fluid dynamics, experimental fluid dynamics, wind tunnel and water tunnel equipment, the mystery of flight and aerodynamic principles, and leading figures in fluid mechanics in order to spark beginners’ interest and allow them to gain a comprehensive understanding of the field’s development. It also provides a list of references for further study.

Modern Fluid Dynamics, Second Edition provides up-to-date coverage of intermediate and advanced fluids topics. The text emphasizes fundamentals and applications, supported by worked examples and case studies. Scale analysis, non-Newtonian fluid flow, surface coating, convection heat transfer, lubrication, fluid-particle dynamics, microfluidics, entropy generation, and fluid-structure interactions are among the topics covered. Part A presents fluids principles, and prepares readers for the applications of fluid dynamics covered in Part B, which includes computer simulations and project writing. A review of the engineering math needed for fluid dynamics is included in an appendix.

"Probability and Partial Differential Equations in Modern Applied Mathematics" is devoted to the role of probabilistic methods in modern applied mathematics from the perspectives of both a tool for analysis and as a tool in modeling. There is a recognition in the applied mathematics research community that stochastic methods are playing an increasingly prominent role in the formulation and analysis of diverse problems of contemporary interest in the sciences and engineering. A probabilistic representation of solutions to partial differential equations that arise as deterministic models allows one to exploit the power of stochastic calculus and probabilistic limit theory in the analysis of deterministic problems, as well as to offer new perspectives on the phenomena for modeling purposes. There is also a growing appreciation of the role for the inclusion of stochastic effects in the modeling of complex systems. This has led to interesting new mathematical problems at the interface of probability, dynamical systems, numerical analysis, and partial differential equations. This volume will be useful to researchers and graduate students interested in probabilistic methods, dynamical systems approaches and numerical analysis for mathematical modeling in the sciences and engineering.