Numerical Methods In Turbulence Simulation
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Numerical Methods in Turbulence Simulation
Numerical Methods in Turbulence Simulation provides detailed specifications of the numerical methods needed to solve important problems in turbulence simulation. Numerical simulation of turbulent fluid flows is challenging because of the range of space and time scales that must be represented. This book provides explanations of the numerical error and stability characteristics of numerical techniques, along with treatments of the additional numerical challenges that arise in large eddy simulations. Chapters are written as tutorials by experts in the field, covering specific both contexts and applications. Three classes of turbulent flow are addressed, including incompressible, compressible and reactive, with a wide range of the best numerical practices covered. A thorough introduction to the numerical methods is provided for those without a background in turbulence, as is everything needed for a thorough understanding of the fundamental equations. The small scales that must be resolved are generally not localized around some distinct small-scale feature, but instead are distributed throughout a volume. These characteristics put particular strain on the numerical methods used to simulate turbulent flows. - Includes a detailed review of the numerical approximation issues that impact the simulation of turbulence - Provides a range of examples of large eddy simulation techniques - Discusses the challenges posed by boundary conditions in turbulence simulation and provides approaches to addressing them
Analysis of the K-Epsilon Turbulence Model
Aimed at applied mathematicians interested in the numerical simulation of turbulent flows. Centered around the k-&epsis; model, it also deals with other models such as one equation models, subgrid scale models and Reynolds Stress models. Presents the k-&epsis; method for turbulence in a language familiar to applied mathematicians, but has none of the technicalities of turbulence theory.
Approximate Deconvolution Models of Turbulence
This volume presents a mathematical development of a recent approach to the modeling and simulation of turbulent flows based on methods for the approximate solution of inverse problems. The resulting Approximate Deconvolution Models or ADMs have some advantages over more commonly used turbulence models – as well as some disadvantages. Our goal in this book is to provide a clear and complete mathematical development of ADMs, while pointing out the difficulties that remain. In order to do so, we present the analytical theory of ADMs, along with its connections, motivations and complements in the phenomenology of and algorithms for ADMs.