1 LES of Turbulent Flows: Lecture 6 (ME EN 7960-008) Prof. Rob Stoll Department of Mechanical Engineering University of Utah Spring 2011.

Slides:



Advertisements
Similar presentations
Lecture 15: Capillary motion
Advertisements

Conservation Equations
Continuity Equation. Continuity Equation Continuity Equation Net outflow in x direction.
Convection.
Boundary Layer Flow Describes the transport phenomena near the surface for the case of fluid flowing past a solid object.
Dr. Kirti Chandra Sahu Department of Chemical Engineering IIT Hyderabad.
1 LES of Turbulent Flows: Lecture 9 (ME EN ) Prof. Rob Stoll Department of Mechanical Engineering University of Utah Fall 2014.
LES of Turbulent Flows: Lecture 10 (ME EN )
Equations of Continuity
1 MECH 221 FLUID MECHANICS (Fall 06/07) Tutorial 7.
Chapter 2 Reynolds Transport Theorem (RTT) 2.1 The Reynolds Transport Theorem 2.2 Continuity Equation 2.3 The Linear Momentum Equation 2.4 Conservation.
Sensible heat flux Latent heat flux Radiation Ground heat flux Surface Energy Budget The exchanges of heat, moisture and momentum between the air and the.
1 MECH 221 FLUID MECHANICS (Fall 06/07) Tutorial 6 FLUID KINETMATICS.
CHE/ME 109 Heat Transfer in Electronics
Introduction to Convection: Flow and Thermal Considerations
LES of Turbulent Flows: Lecture 3 (ME EN )
Lecture of : the Reynolds equations of turbulent motions JORDANIAN GERMAN WINTER ACCADMEY Prepared by: Eng. Mohammad Hamasha Jordan University of Science.
Numerical Hydraulics Wolfgang Kinzelbach with Marc Wolf and Cornel Beffa Lecture 1: The equations.
Viscosity. Average Speed The Maxwell-Boltzmann distribution is a function of the particle speed. The average speed follows from integration.  Spherical.
Simulation and Animation
Instructor: André Bakker
Flow and Thermal Considerations
FUNDAMENTAL EQUATIONS, CONCEPTS AND IMPLEMENTATION
FLUID DYNAMICS Phys 5306 By Mihaela-Maria Tanasescu
ME 231 Thermofluid Mechanics I Navier-Stokes Equations.
Conservation Laws for Continua
Introduction to Convection: Flow and Thermal Considerations
Review (2 nd order tensors): Tensor – Linear mapping of a vector onto another vector Tensor components in a Cartesian basis (3x3 matrix): Basis change.
Lecture Objectives: -Define turbulence –Solve turbulent flow example –Define average and instantaneous velocities -Define Reynolds Averaged Navier Stokes.
Chapter 9: Differential Analysis of Fluid Flow SCHOOL OF BIOPROCESS ENGINEERING, UNIVERSITI MALAYSIA PERLIS.
1 LES of Turbulent Flows: Lecture 11 (ME EN ) Prof. Rob Stoll Department of Mechanical Engineering University of Utah Fall 2014.
AOE 5104 Class 7 Online presentations for next class: Homework 3
1 LES of Turbulent Flows: Lecture 12 (ME EN ) Prof. Rob Stoll Department of Mechanical Engineering University of Utah Spring 2011.
ME 254. Chapter I Integral Relations for a Control Volume An engineering science like fluid dynamics rests on foundations comprising both theory and experiment.
Governing equations: Navier-Stokes equations, Two-dimensional shallow-water equations, Saint-Venant equations, compressible water hammer flow equations.
Reynolds-Averaged Navier-Stokes Equations -- RANS
Mathematical Equations of CFD
1 LES of Turbulent Flows: Lecture 15 (ME EN ) Prof. Rob Stoll Department of Mechanical Engineering University of Utah Fall 2014.
Yoon kichul Department of Mechanical Engineering Seoul National University Multi-scale Heat Conduction.
1 LES of Turbulent Flows: Lecture 16 (ME EN ) Prof. Rob Stoll Department of Mechanical Engineering University of Utah Fall 2014.
LES of Turbulent Flows: Lecture 2 (ME EN )
Chapter 03: Macroscopic interface dynamics Xiangyu Hu Technical University of Munich Part A: physical and mathematical modeling of interface.
FLUID PROPERTIES Independent variables SCALARS VECTORS TENSORS.
Measurements in Fluid Mechanics 058:180:001 (ME:5180:0001) Time & Location: 2:30P - 3:20P MWF 218 MLH Office Hours: 4:00P – 5:00P MWF 223B-5 HL Instructor:
Vectors n v What is the projection of the vector (1, 3, 2) onto the plane described by ? Louisiana Tech University Ruston, LA
Quantification of the Infection & its Effect on Mean Fow.... P M V Subbarao Professor Mechanical Engineering Department I I T Delhi Modeling of Turbulent.
MAE 5360: Hypersonic Airbreathing Engines
1 LES of Turbulent Flows: Lecture 7 (ME EN ) Prof. Rob Stoll Department of Mechanical Engineering University of Utah Fall 2014.
INTRODUCTION TO CONVECTION
LES of Turbulent Flows: Lecture 5 (ME EN )
Scales of Motion, Reynolds averaging September 22.
1 LES of Turbulent Flows: Lecture 2 (ME EN ) Prof. Rob Stoll Department of Mechanical Engineering University of Utah Spring 2011.
Basic concepts of heat transfer
1 LES of Turbulent Flows: Lecture 10 (ME EN ) Prof. Rob Stoll Department of Mechanical Engineering University of Utah Spring 2011.
Fluid Mechanics-I Spring 2010 Lecture # Course Outline  Introduction to Fluids and Fluid Properties  Fluid Statics  Integral Relations for fluid.
1 LES of Turbulent Flows: Lecture 7 (ME EN ) Prof. Rob Stoll Department of Mechanical Engineering University of Utah Spring 2011.
Viscosità Equazioni di Navier Stokes. Viscous stresses are surface forces per unit area. (Similar to pressure) (Viscous stresses)
Heat Transfer Su Yongkang School of Mechanical Engineering # 1 HEAT TRANSFER CHAPTER 6 Introduction to convection.
1 LES of Turbulent Flows: Lecture 9 (ME EN ) Prof. Rob Stoll Department of Mechanical Engineering University of Utah Spring 2011.
1 LES of Turbulent Flows: Lecture 13 (ME EN ) Prof. Rob Stoll Department of Mechanical Engineering University of Utah Spring 2011.
Remark: foils with „black background“ could be skipped, they are aimed to the more advanced courses Rudolf Žitný, Ústav procesní a zpracovatelské techniky.
Introduction to the Turbulence Models
Chapter 4 Fluid Mechanics Frank White
DIFFERENTIAL EQUATIONS FOR FLUID FLOW Vinay Chandwani (Mtech Struct.)
FLUID DYNAMICS Made By: Prajapati Dharmesh Jyantibhai ( )
Heat Transfer Coefficient
Fluid properties 1.
Today’s Lecture Objectives:
MAE 3241: AERODYNAMICS AND FLIGHT MECHANICS
Topic 6 NavierStokes Equations
Presentation transcript:

1 LES of Turbulent Flows: Lecture 6 (ME EN ) Prof. Rob Stoll Department of Mechanical Engineering University of Utah Spring 2011

2 Kolmogorov’s Similarity hypothesis (1941) Kolmogorov’s 1 st Hypothesis: smallest scales receive energy at a rate proportional to the dissipation of energy rate. motion of the very smallest scales in a flow depend only on: a)rate of energy transfer from small scales: b)kinematic viscosity: With this he defined the Kolmogorov scales (dissipation scales): length scale: time scale: velocity scale: Re based on the Kolmolgorov scales => Re=1

3 Kolmogorov’s Similarity hypothesis (1941) From our scales we can also form the ratios of the largest to smallest scales in the flow (using ). Note: dissipation at large scales => length scale: velocity scale: time scale: For very high-Re flows (e.g., Atmosphere) we have a range of scales that is small compared to but large compared to. As Re goes up, / goes down and we have a larger separation between large and small scales.

4 Kolmolgorov’s 2 nd Hypothesis: In Turbulent flow, a range of scales exists at very high Re where statistics of motion in a range (for ) have a universal form that is determined only by (dissipation) and independent of (kinematic viscosity). Kolmogorov formed his hypothesis and examined it by looking at the pdf of velocity increments Δu. Another way to look at this (equivalent to structure functions) is to examine what it means for E(k) Recall Kolmogorov’s Similarity hypothesis (1941) Δu pdf (Δu) The moments of this pdf are the structure functions of different order (e.g., 2 nd, 3 rd, 4 th, etc. ) variance skewnesskurtosis

5 Kolmogorov’s Similarity Hypothesis (1941) What are the implications of Kolmolgorov’s hypothesis for E(k)? By dimensional analysis we can find that: This expression is valid for the range of length scales where and is usually called the inertial subrange of turbulence. graphically:

6 We now have a description of turbulence and the range of energy containing scales (the dynamic range) in turbulence In CFD we need to discretize the equations of motion (see below) using either difference approximations (finite differences) or as a finite number of basis functions (e.g., Fourier transforms) To capture all the dynamics (degrees of freedom) of a turbulent flow we need to have a grid fine enough to capture the smallest and largest motions ( and ) From K41 we know and we have a continuous range of scales between and We need points in each direction. Turbulence is 3D => we need N~Re 9/4 points. Degrees of freedom and numerical simulations

7 When will we be able to directly simulate all the scales of motion in a turbulent flow? (Voller and Porté-Agel, 2002, see handouts for the full paper)

8 Equations of Motion Turbulent flow (and fluid dynamics in general) can be mathematically described by the Navier-Stokes equations (see Bachelor, 1967 for a derivation of equations/Pope Ch 2) The primary goal of CFD (and LES) is to solve the discretized equations of motion. we use the continuum hypothesis (e.g., mean free path of molecules) so that Conservation of Mass: Using Reynolds Transport Theorem (RTT, see any fluids textbook) Using Gauss’s theorem and shrinking the control volume to an infinitesimal size:

9 Equations of Motion Conservation of Momentum: (Newton’s 2 nd law) The shear stress tensor depends on molecular processes. For a Newtonian fluid  Using RTT  shear stress body forces Where is the deformation (rate of strain) tensor and I is the unit tensor (or identity matrix) The equivalent index-notation (differential) form of the momentum equation is: where the stress has been split into shear (viscous) and normal (pressure) components.

10 Conservation of Energy Conservation of Energy: (1 st law of Thermodynamics) For a system conservation of energy is: or: (in-out) + produced = stored - (in-out) is the convective flux of energy -Production is the heat conducted in + the work done on the volume (e.g., thermal flux and shear stress) if we use (specific internal energy) and define as the thermal conductive flux where c V is the specific heat and T is temperature. We can derive the following differential form for energy Where the total energy is: