Advances In Computation, Modeling And Control Of Transitional And Turbulent Flows
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Advances In Computation, Modeling And Control Of Transitional And Turbulent Flows

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Advances In Computation, Modeling And Control Of Transitional And Turbulent Flows

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About This Book

The role of high performance computing in current research on transitional and turbulent flows is undoubtedly very important. This review volume provides a good platform for leading experts and researchers in various fields of fluid mechanics dealing with transitional and turbulent flows to synergistically exchange ideas and present the state of the art in the fields.

Contributed by eminent researchers, the book chapters feature keynote lectures, panel discussions and the best invited contributed papers.

The role of high performance computing in current research on transitional and turbulent flows is undoubtedly very important. This review volume provides a good platform for leading experts and researchers in various fields of fluid mechanics dealing with transitional and turbulent flows to synergistically exchange ideas and present the state of the art in the fields.

Contributed by eminent researchers, the book chapters feature keynote lectures, panel discussions and the best invited contributed papers.

Readership: Researchers, professionals, academics, graduate and senior undergraduates in aerospace engineering, mechanical engineering, engineering mechanics, geophysics and fluid mechanics.

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Yes, you can access Advances In Computation, Modeling And Control Of Transitional And Turbulent Flows by Tapan K Sengupta, Sanjiva K Lele, Katepalli R Sreenivasan, Peter A Davidson in PDF and/or ePUB format, as well as other popular books in Biological Sciences & Science General. We have over one million books available in our catalogue for you to explore.

Information

Publisher
WSPC
Year
2015
ISBN
9789814635172

A Critical Assessment of Simluations for Transitional
and Turbulent Flows

Tapan K Sengupta

High Performance Computing Laboratory, Dept. of Aerospace Engg.,
Indian Institute of Technology Kanpur,
Kanpur 208 016, India.
E-mail: [email protected], [email protected]

In the symposium we have seen a very wide range of simulations for transitional and turbulent flows. In writing this epilogue, the author takes the responsibility of identifying some common elements which add to success of desired DNS and LES. Of course, the single common element of any such activities is to be aware of numerical dispersion relation and how it relates to physical dispersion relation. We also investigate suitability of a specific combined implicit-explicit (IMEX) time integration method in performing DNS, which has been used to explore the so-called bypass transition. While IMEX methods have often been used, yet its properties and potentials are not assessed. Specifically, error analysis by solving a model equation that mimics some of the physical processes in DNS is not performed. A model equation with exact solution allows tracking of error with time for IMEX time integration methods, with either explicit or implicit spatial discretization. This analysis is motivated by recent DNS of flow transition over a flat plate reported in Bhaumik and Sengupta (Phys. Rev. E, 89, 043018, 2014) and Sayadi et al. (J. Fluid Mech., 724, 480-509, 2013), both trying to mimic the classical experimental results on flow transition in Schubauer and Skramstad (J. Aero. Sci., 14, 69, 1947). These two simulations show distinctly different computed solutions, yet the average flow quantities show remarkable similarity. In Bhaumik and Sengupta (2014), explicit dispersion relation preserving time integration method has been used everywhere in the domain. In contrast, in Sayadi et al. (2013), implicit time integration method is used very close to the plate, while explicit time integration method is used in rest of the domain. Such splitting of domain into explicit and implicit regions causes spurious internal reflection of the signal at the interface between these regions, creating unphysical, spurious and upstream-propagating q-waves which considerably contaminates solution. This is investigated in detail along with other issues of high resolution computing here to show suitable methods for DNS.
Keywords: DNS; LES; Transitional Flow; Turbulent flow; Error analysis; q-waves; Compact schemes; IMEX method; Anisotropic wave propagation; Round-off error

1. Introduction

Direct numerical simulation (DNS) is attempted by many investigators for canonical problems. Despite its widespread use as a tool of scientific computing, yet there are no known accepted definition of what constitutes DNS. It is not adequate to state that not using any model(s) of transition and turbulence in simulating high Reynolds number flows qualifies as DNS. In that case, all laminar flow computations should have been considered as DNS. It is understood in fluid mechanics context, that simulating flow fields with wide-band energy and enstrophy spectrum without models constitute DNS. In a generic simulation of dynamical system governing space-time dynamics, this definition can be broadened to include simulations of wide-band spectral events without any numerical artifacts. Such numerical artifacts could be wide ranging from altering the governing dynamical equation; trying to study so called free vibration problems by studying forced vibration; adding spurious dispersion and dissipation of numerical methods, so much so that the physical dispersion relation (if it can be identified in the first place) is poorly followed by adopted numerical dispersion relation and adding other sources of numerical errors. In this context, the main issue is one of evaluating the numerical dispersion relation. It is somewhat ironic that the celebrated error analysis of von Neumann used all over the world today, and which remained classified during the second world war years due to its supposed importance, has been the main reason, which has spawned misunderstanding of numerical dispersion relation. This has been corrected by the author’s group and reported in Refs. 33 and 35, following an early lead in Ref. 14. This will be amply demonstrated by a simple test case and rudimentary metrics identified for correct error analysis. This may provide another qualitative description of what constitute DNS. In short, DNS is one, in which dispersion relation preserving (DRP) method is used and which minimizes all known sources of error. This has been supported by Prof. Sheu and Prof. Deville in the panel discussion that DRP schemes have to be established as the principal tool for DNS and LES.
Thus it appears that not obtaining the correct numerical dispersion relation is responsible for the slow growth of scientific computing, apart from nonlinearity of the governing differential equation. However, computers are used to solve nonlinear problems to understand the physics of the problem. So the inability to solve nonlinear problems in closed form provide opportunity for scientific computing to bring the second wave of development in mathematical physics. Establishment of calculus brought the first wave of scientific knowledge creation. So it is going to be very interesting to be traveling with the second wave! Computing and continuum mechanics is again the crucible where ideas and applications are fine-grained and analyzed for further development. However, we will keep our attention focused mainly on fluid dynamical problems in this section.
The second-most important issue of scientific computing related to inability of handling non-periodic problems. Lack of analysis tools for numerical methods has somewhat delayed progress so far. The community (specially who are more mathematically inclined) has spent a lot of time to study so-called periodic problems (note the warning of Prof. Deville in the panel discussion in this context). A global spectral analysis (GSA) has appeared in literature over more than a decade from the author’s group (see Refs. 28 and 36 for complete details) for full domain analysis of non-periodic problems. It is equally relevant to note that GSA can accommodate all types of discretization schemes and nothing escapes its scrutiny, be it a finite difference, finite volume, finite element or Fourier spectral method – all such schemes have been analyzed29,32. The existence of such a tool should be viewed as a great advantage for all sentient researchers in the field.
Of course GSA requires adopting a model equation for calibration and the one adopted here is the linear wave equation or one-dimensional (1D) convection equation. The reason for the choice of this model equation needs some elaboration. In the context of the symposium theme, we gathered to discuss about transitional and turbulent flow. The governing Navier-Stokes equation (NSE) is a statement of dynamical equilibrium between mainly two processes: convection and diffusion; apart from imposed pressure gradient and unsteadiness. For high Reynolds number transitional and turbulent flows, convection mainly dictates the dynamics. So from that perspective alone, adopting linear convection equation appears as the lowest common denominator. It is not relevant to distinguish between 1D and multi-dimensional convection, as it has been amply demonstrated in Ref. 39, as to how GSA can be extended to multi-dimensions and related errors due to anisotropy of numerical methods can also be studied. The second reason for adopting linear wave equation is due to the perspective that...

Table of contents

  1. Cover
  2. Halftitle
  3. Title Page
  4. Copyright
  5. Preface
  6. Contents
  7. Large-Eddy Simulation of the Navier-Stokes Equations: Deconvolution, Particle Methods, and Super-Resolution
  8. Convective Transport in the Sun
  9. Rapidly-Rotating Turbulence and its Role in Planetary Dynamos
  10. Low-Order Models for Control of Fluids: Balanced Models and the Koopman Operator
  11. Different Routes of Transition by Spatio-Temporal Wave-Front
  12. Bypass Transitional Flow Past an Aerofoil With and Without Surface Roughness Elements
  13. Global Stability and Transition to Intermittent Chaos in the Cubical Lid-Driven Cavity Flow Problem
  14. Spatio-Temporal Wave Front – Essential Element of Flow Transition for Low Amplitude Excitations
  15. Simulations Using Transition Models within the Framework of RANS
  16. DNS of Incompressible Square Duct Flow and Its Receptivity to Free Stream Turbulence
  17. Evolution of RANS Modelling of High Speed Mixing Layers using LES
  18. Numerical Investigation of Centrifugal Instability Around a Circular Cylinder Rotated Impulsively
  19. Direct Numerical Simulations of Riblets in a Fully-Developed Turbulent Channel Flow: Effects of Geometry
  20. Computational Studies on Flow Separation Controls at Relatively Low Reynolds Number Regime
  21. Frequency Dependent Capacitance SDBD Plasma Model for Flow Control
  22. Effects of Uniform Blowing or Suction on the Amplitude Modulation in Spatially Developing Turbulent Boundary Layers
  23. Turbulent Drag Reduction in Channel Flow Using Weak-Pressure Forcing
  24. Drifting of Internal Gravity Wave in a Non-Boussinesq Stably Stratified Turbulent Channel Flow
  25. Numerical Study of Sink Flow Turbulent Boundary Layers
  26. Coherent Structure in Oil Body Embedded in Compound Vortex
  27. Quantitative Characterization of Single Orifice Hydraulic Flat Spray Nozzle
  28. Shell Model for Buoyancy-Driven Turbulent Flows
  29. Numerical Simulations in Low–Prandtl Number Convection
  30. Effect of Buoyancy on Turbulent Mixed Convection Flow Through Vertical and Horizontal Channels
  31. Computation of Boundary Layer Flow over Porous Laminated Flat Plate
  32. Boundary Condition Development for an Adverse Pressure Gradient Turbulent Boundary Layer at the Verge of Separation
  33. Some Interesting Features of Flow Past Slotted Circular Cylinder at Re = 3500
  34. A High-Resolution Compressible DNS Study of Flow Past a Low-Pressure Gas Turbine Blade
  35. Numerical Simulation of Impulsive Supersonic Flow from an Open End of a Shock Tube: A Comparative Study
  36. Green’s Function Analysis of Pressure-Strain Correlations in a Supersonic Pipe, Nozzle and Diffuser
  37. The Structure of Turbulence in Poiseuille and Couette Flow at Computationally High Reynolds Number
  38. A New Reynolds Stress Damping Function for Hybrid RANS/LES with an Evolved Functional Form
  39. Direct Numerical and Large Eddy Simulations of Helicity-Induced Stably Stratified Turbulent Flows
  40. Comparison of RANS and DNS for Transitional Flow Over WTEA-TE1 Airfoil
  41. Extracting Coherent Structures to Explore the Minimum Jet Noise
  42. Synchronized Large-Eddy Simulations for Sound Generation Analysis
  43. DNS of a Turbulent Jet Issuing from an Acoustically Lined Pipe
  44. Decomposition of Radiating and Non-Radiating Linear Fluctuating Components in Compressible Flows
  45. Toward Control of Compressible Shear Flows: Investigation of Possible Flow Mechanisms
  46. Damping Numerical Oscillations in Hybrid Solvers through Detection of Gibbs Phenomenon
  47. Forward and Inverse 3D Fourier Transforms of a DNS Wavepacket Evolving in a Blasius Boundary Layer
  48. Reduced Order Modeling by POD of Supercritical Flow Past Circular Cylinder
  49. Proper Orthogonal Decomposition vs. Fourier Analysis for Extraction of Large-Scale Structures of Thermal Convection
  50. Energy Spectrum and Flux of Buoyancy-Driven Turbulence
  51. DNS of a Buoyant Turbulent Cloud under Rapid Rotation
  52. Numerical Simulation of Shock-Bubble Interaction using High Order Upwind Schemes
  53. Rayleigh-Taylor Instability of a Miscible Fluid at the Interface: Direct Numerical Simulation
  54. A High Resolution Differential Filter for Large Eddy Simulation on Unstructured Grids for High-Order Methods
  55. A Critical Assessment of Simulations for Transitional and Turbulent Flows
  56. Panel Discussion