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Finite Difference Methods in Heat Transfer
Finite Difference Methods in Heat Transfer, Second Edition focuses on finite difference methods and their application to the solution of heat transfer problems. Such methods are based on the discretization of governing equations, initial and boundary conditions, which then replace a continuous partial differential problem by a system of algebraic equations. Finite difference methods are a versatile tool for scientists and for engineers. This updated book serves university students taking graduate-level coursework in heat transfer, as well as being an important reference for researchers and engineering. Features Provides a self-contained approach in finite difference methods for students and professionals Covers the use of finite difference methods in convective, conductive, and radiative heat transfer Presents numerical solution techniques to elliptic, parabolic, and hyperbolic problems Includes hybrid analytical–numerical approaches
Finite Difference Methods in Heat Transfer
Finite Difference Methods in Heat Transfer, Second Edition focuses on finite difference methods and their application to the solution of heat transfer problems. Such methods are based on the discretization of governing equations, initial and boundary conditions, which then replace a continuous partial differential problem by a system of algebraic equations. Finite difference methods are a versatile tool for scientists and for engineers. This updated book serves university students taking graduate-level coursework in heat transfer, as well as being an important reference for researchers and engineering. Features Provides a self-contained approach in finite difference methods for students and professionals Covers the use of finite difference methods in convective, conductive, and radiative heat transfer Presents numerical solution techniques to elliptic, parabolic, and hyperbolic problems Includes hybrid analytical–numerical approaches
Data-Driven Evolutionary Modeling in Materials Technology
Due to efficacy and optimization potential of genetic and evolutionary algorithms, they are used in learning and modeling especially with the advent of big data related problems. This book presents the algorithms and strategies specifically associated with pertinent issues in materials science domain. It discusses the procedures for evolutionary multi-objective optimization of objective functions created through these procedures and introduces available codes. Recent applications ranging from primary metal production to materials design are covered. It also describes hybrid modeling strategy, and other common modeling and simulation strategies like molecular dynamics, cellular automata etc. ...
Advances in Evolutionary and Deterministic Methods for Design, Optimization and Control in Engineering and Sciences
This book contains state-of-the-art contributions in the field of evolutionary and deterministic methods for design, optimization and control in engineering and sciences. Specialists have written each of the 34 chapters as extended versions of selected papers presented at the International Conference on Evolutionary and Deterministic Methods for Design, Optimization and Control with Applications to Industrial and Societal Problems (EUROGEN 2013). The conference was one of the Thematic Conferences of the European Community on Computational Methods in Applied Sciences (ECCOMAS). Topics treated in the various chapters are classified in the following sections: theoretical and numerical methods a...
Automated Workflow Scheduling in Self-Adaptive Clouds
This timely text/reference presents a comprehensive review of the workflow scheduling algorithms and approaches that are rapidly becoming essential for a range of software applications, due to their ability to efficiently leverage diverse and distributed cloud resources. Particular emphasis is placed on how workflow-based automation in software-defined cloud centers and hybrid IT systems can significantly enhance resource utilization and optimize energy efficiency. Topics and features: describes dynamic workflow and task scheduling techniques that work across multiple (on-premise and off-premise) clouds; presents simulation-based case studies, and details of real-time test bed-based implemen...
Automated Optimization Methods for Scientific Workflows in e-Science Infrastructures
Scientific workflows have emerged as a key technology that assists scientists with the design, management, execution, sharing and reuse of in silico experiments. Workflow management systems simplify the management of scientific workflows by providing graphical interfaces for their development, monitoring and analysis. Nowadays, e-Science combines such workflow management systems with large-scale data and computing resources into complex research infrastructures. For instance, e-Science allows the conveyance of best practice research in collaborations by providing workflow repositories, which facilitate the sharing and reuse of scientific workflows. However, scientists are still faced with di...
Simulations in Biomedicine V
Computer models have become increasingly successful in simulating biological phenomena. The advantages of this approach are numerous, particularly in biomedicine where it has led to a better understanding of the mechanics of physiological processes. The use of computational models has also spread to many applications in medicine, as demonstrated by the contents of this volume. Containing papers presented at the Fifth International Conference on Computer Simulations in Biomedicine, the book covers a broad spectrum of topics on applications in this area. The contributions featured are arranged in sections according to their medical and biological perspective in order to make the contents more ...
Inverse Heat Conduction and Heat Exchangers
A direct solution of the heat conduction equation with prescribed initial and boundary conditions yields temperature distribution inside a specimen. The direct solution is mathematically considered as a well-posed one because the solution exists, is unique, and continuously depends on input data. The estimation of unknown parameters from the measured temperature data is known as the inverse problem of heat conduction. An error in temperature measurement, thermal time lagging, thermocouple-cavity, or signal noise data makes stability a problem in the estimation of unknown parameters. The solution of the inverse problem can be obtained by employing the gradient or non-gradient based inverse algorithm. The aim of this book is to analyze the inverse problem and heat exchanger applications in the fields of aerospace, mechanical, applied mechanics, environment sciences, and engineering.
