Computational Techniques for Complex Transport Phenomena

Abstract

Complex fluid flows are encountered widely in nature, in living beings and in engineering practice. These flows often involve both geometric and dynamic complexity and present problems that are difficult to analyse because of their wide range of length and time scales, as well as their geometric configuration. This book describes some newly developed computational techniques and modelling strategies for analysing and predicting complex transport phenomena. It summarizes advances in the context of a pressure-based algorithm. Among methods discussed are discretization schemes for treating convection and pressure, parallel computing, multigrid methods, and composite, multiblock techniques. With respect to physical modelling, the book addresses issues of turbulence closure and multiscale, multiphase transport from an engineering viewpoint. Both fundamental and practical issues are considered, along with the relative merits of competing approaches. The final chapter is devoted to practical applications that illustrate the advantages of various numerical and physical tools. Numerous examples are given throughout the text. Mechanical, aerospace, chemical and materials engineers can use the techniques presented in this book to tackle important, practical problems more effectively.

Vortex flow and cavitation in diesel injector nozzles

“…The additional effect of the bubbles' relative movement on the liquid phase turbulent kinetic energy and dissipation are also included according to the approach of Laín et al (2002). Note that as part of the numerous numerical tests that have been performed during the development of the model, a number of other turbulence models have been tested, apart from the standard k-ε, namely the RNG of Yakhot et al (1992) and the non-equilibrium version of Shyy et al (1997) as applied in the simulation of cavitating flows by Vaidyanathan et al (2003). Overall, it can be claimed that although a variation of up to 3 % in the predicted nozzle discharge coefficient can be attributed to the turbulence model Giannadakis et al (2007), the details of the underlining physical processes are not affected significantly; furthermore, no model has been found to persistently predict cavitation better than the rest for all test cases, within the context of the Reynolds-averaged methodology.…”

Computational aeroelasticity using a pressure-based solver

“…American Institute of Aeronautics and Astronautics A pressure-based numerical procedure presented (Shyy, 1994;Shyy et al 1997) for curvilinear coordinates is adopted as the flow solver (STREAM). It solves the full Navier-Stokes equations for 3-D incompressible flows.…”

Hydrodynamic Characteristics of Expanded Channels with their Applications----the State-of-the-Art

“…G F / (17) where The modified model was called the non-equilibriumk-ε" turbulence model (Shyy et al [8]), which has been tested in a compressible recirculating flow with improved performance over the standard model. ByusingRastogi and Rodi's [1] depth-averaging approach, the depth-averagednon-equilibrium k-ε" model can be derived from the 3-D version.…”