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On Describing Mean Flow Dynamics in Wall Turbulence J. Klewicki Department of Mechanical Engineering University of New Hampshire Durham, NH 03824
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Page 1: On Describing Mean Flow Dynamics in Wall Turbulence J. Klewicki Department of Mechanical Engineering University of New Hampshire Durham, NH 03824.

On Describing Mean Flow Dynamics in Wall Turbulence

J. KlewickiDepartment of Mechanical Engineering

University of New HampshireDurham, NH 03824

Page 2: On Describing Mean Flow Dynamics in Wall Turbulence J. Klewicki Department of Mechanical Engineering University of New Hampshire Durham, NH 03824.

Focus

Much effort has been directed toward describing what behaviors occur (e.g., formulas for the mean profile, the exact numerical value of )

Our on-going efforts seek to focus more on why these behaviors occur

Page 3: On Describing Mean Flow Dynamics in Wall Turbulence J. Klewicki Department of Mechanical Engineering University of New Hampshire Durham, NH 03824.

Turbulent Channel Flow Stress Profiles

From, Moser et al. (1999).

Page 4: On Describing Mean Flow Dynamics in Wall Turbulence J. Klewicki Department of Mechanical Engineering University of New Hampshire Durham, NH 03824.

Standard Interpretation

• In the immediate vicinity of the wall viscous effects are much larger than those associated with turbulent inertia (viscous sublayer).

• In an interior region the momentum field mechanisms associated with the viscous forces and turbulent inertia are of the same order of magnitude (buffer layer), and

• For sufficiently large distances from the wall, turbulent inertia is dominant (logarithmic and wake layers)

Page 5: On Describing Mean Flow Dynamics in Wall Turbulence J. Klewicki Department of Mechanical Engineering University of New Hampshire Durham, NH 03824.

The Logarithmic Law Via Overlap Hypothesis

Page 6: On Describing Mean Flow Dynamics in Wall Turbulence J. Klewicki Department of Mechanical Engineering University of New Hampshire Durham, NH 03824.

Overlap + Monotone = Logarithmic

• Pexider (1903) considered the inner/outer/overlap problem for a more general class of functions that encompasses the Izakson/Millikan formulation.

• He explored the case in which the inner and outer functions exactly express the original function.

• Overall he showed that in the overlap layer the function must either be a constant or logarithmic, the latter necessarily being the case if the function is apriori known to not be constant.

• Fife et al. (2008) show that this is also true for functions that approximately overlap.

• These are mathematical properties that have nothing in particular to do with boundary layer physics

Page 7: On Describing Mean Flow Dynamics in Wall Turbulence J. Klewicki Department of Mechanical Engineering University of New Hampshire Durham, NH 03824.

On the Dynamics of the Logarithmic Layer as Derived from the Properties

of the Mean Momentum Equation

Page 8: On Describing Mean Flow Dynamics in Wall Turbulence J. Klewicki Department of Mechanical Engineering University of New Hampshire Durham, NH 03824.

Some Relevant Publications

1) Wei, T., Fife, P., Klewicki, J. and McMurtry, P., 2005 “Properties of the mean momentum balance in turbulent boundary layer, pipe and channel flows,” J. Fluid Mech. 522, 303.

2) Fife, P., Wei, T., Klewicki, J. and McMurtry, P., 2005 “Stress gradient balance layers and scale hierarchies in wall-bounded turbulent flows,” J. Fluid Mech. 532 165.

3) Fife, P., Klewicki, J., McMurtry, P. and Wei, T. 2005 “Multiscaling in the presence of indeterminacy: Wall-induced turbulence,” Multiscale Modeling and Simulation 4 936.

4) Klewicki, J., Fife, P., Wei, T. and McMurtry, P. 2006 “Overview of a methodology for scaling the indeterminate equations of wall turbulence,” AIAA J. 44, 2475.

5) Wei, T., Fife, P. and Klewicki, J. 2007 “On scaling the mean momentum balance and its solutions in turbulent Couette-Poiseuille flow,” J. Fluid Mech. 573, 371.

6) Klewicki, J., Fife, P., Wei, T. and McMurtry, P. 2007 “A physical model of the turbulent boundary layer consonant with mean momentum balance structure,” Phil. Trans. Roy. Soc. Lond. A 365, 823.

Page 9: On Describing Mean Flow Dynamics in Wall Turbulence J. Klewicki Department of Mechanical Engineering University of New Hampshire Durham, NH 03824.

Some Successes

This new theoretical framework (for example):

• Clarifies the relative influences of the various forces in pipes, channels and boundary layers.

• Analytically determines the R-dependence of the position of the Reynolds stress peak in channel flow, the peak value of the Reynolds stress, and the curvature of the profile near the peak, without the use of a logarithmic mean profile or the use of any curvefits.

• Simultaneously derives the scalings for the Reynolds stress and mean profile in turbulent Couette-Poiseuille flow as a function of both Reynolds number and relative wall motion.

• Provides a clear theoretical justification (the only we know of) for the often employed/assumed distance from the wall scaling

• Analytically provides a clear physical description of what the von Karman constant is, and the condition necessary for it to actually be a constant

Page 10: On Describing Mean Flow Dynamics in Wall Turbulence J. Klewicki Department of Mechanical Engineering University of New Hampshire Durham, NH 03824.

Objectives

This part will convey that:

• The mean momentum equation admits a hierarchy of scaling layers, L(y+), the members of which are delineated by the parameter, .

• This scaling hierarchy is rigorously associated with the existence of a logarithmic-like mean velocity profile

• For the mean profile to be exactly logarithmic, the leading

coefficient, A, (proportional to ) must truly equal a constant

• A = constant when the layer hierarchy attains a purely self-similar structure

• Physically, this is reflected in the self-similar behavior of the turbulent force gradient across the layer hierarchy

Page 11: On Describing Mean Flow Dynamics in Wall Turbulence J. Klewicki Department of Mechanical Engineering University of New Hampshire Durham, NH 03824.

Primary Assumptions

• RANS equations describe the mean dynamics

• Mean velocity is increasing and mean velocity gradient is decreasing with distance from the wall

Page 12: On Describing Mean Flow Dynamics in Wall Turbulence J. Klewicki Department of Mechanical Engineering University of New Hampshire Durham, NH 03824.

Channel Flow Mean Momentum Balance

.

Page 13: On Describing Mean Flow Dynamics in Wall Turbulence J. Klewicki Department of Mechanical Engineering University of New Hampshire Durham, NH 03824.

Four Layer Structure (At any fixed Reynolds number)

Page 14: On Describing Mean Flow Dynamics in Wall Turbulence J. Klewicki Department of Mechanical Engineering University of New Hampshire Durham, NH 03824.

Layer II

.

Page 15: On Describing Mean Flow Dynamics in Wall Turbulence J. Klewicki Department of Mechanical Engineering University of New Hampshire Durham, NH 03824.

Balance Breaking and Exchange From Layer II to Layer III

.

Page 16: On Describing Mean Flow Dynamics in Wall Turbulence J. Klewicki Department of Mechanical Engineering University of New Hampshire Durham, NH 03824.

Layer III Rescaling

.

Page 17: On Describing Mean Flow Dynamics in Wall Turbulence J. Klewicki Department of Mechanical Engineering University of New Hampshire Durham, NH 03824.

Layer III Rescaling

.

Page 18: On Describing Mean Flow Dynamics in Wall Turbulence J. Klewicki Department of Mechanical Engineering University of New Hampshire Durham, NH 03824.

Layer II Structure Revisited

.

Page 19: On Describing Mean Flow Dynamics in Wall Turbulence J. Klewicki Department of Mechanical Engineering University of New Hampshire Durham, NH 03824.

Hierarchy Equations

.

Page 20: On Describing Mean Flow Dynamics in Wall Turbulence J. Klewicki Department of Mechanical Engineering University of New Hampshire Durham, NH 03824.

Scaling Layer Hierarchy

• For each value of , these equations undergo the same balance exchange as described previously (associated with the peaks of T)

• For each value of there is a layer, L, centered about a position, y, across which a balance breaking and exchange of forces occurs.

Page 21: On Describing Mean Flow Dynamics in Wall Turbulence J. Klewicki Department of Mechanical Engineering University of New Hampshire Durham, NH 03824.

Layer Hierarchy

0 y

y+ = 26-30 y/ ~ 0.5

ym

L

ym

Ly

m

L …….

Page 22: On Describing Mean Flow Dynamics in Wall Turbulence J. Klewicki Department of Mechanical Engineering University of New Hampshire Durham, NH 03824.

Logarithmic Dependence

.

Page 23: On Describing Mean Flow Dynamics in Wall Turbulence J. Klewicki Department of Mechanical Engineering University of New Hampshire Durham, NH 03824.

Logarithmic Dependence (continued)

It can be shown that:

• A() = O(1) function that may on some sub-domains equal a constant

• If A = const., a logarithmic mean profile is identically admitted

• If A varies slightly, then the profile is bounded above and below by logarithmic functions.

Page 24: On Describing Mean Flow Dynamics in Wall Turbulence J. Klewicki Department of Mechanical Engineering University of New Hampshire Durham, NH 03824.

Logarithmic Dependence (continued)

Page 25: On Describing Mean Flow Dynamics in Wall Turbulence J. Klewicki Department of Mechanical Engineering University of New Hampshire Durham, NH 03824.

Summary

• The mean momentum equation admits a hierarchy of scaling layers, L(y+), the members of which are delineated by the parameter, . The width of these layers asymptotically scale with y.

• This scaling hierarchy is rigorously associated with the existence of a logarithmic-like mean velocity profile

• For the mean profile to be exactly logarithmic, the leading coefficient, A, (proportional to ) must truly equal a constant

• A = constant when the layer hierarchy attains a purely self-similar structure

• On each layer of the hierarchy these physics are associated with a balance breaking and exchange of forces that is also characteristic of the flow as a whole

• Physically, the leading coefficient on the logarithmic mean profile (i.e.,von Karman constant/coefficient) is shown to reflect the self-similar nature of the flux of turbulent force across an internal range of scales /u< L <

• Like many known self-similar phenomena, the natural length scale(s) for the hierarchy are intrinsically determined via consideration of the underlying dynamical equations in a zone that is “remote” from boundary condition effects.

Page 26: On Describing Mean Flow Dynamics in Wall Turbulence J. Klewicki Department of Mechanical Engineering University of New Hampshire Durham, NH 03824.

C-P Reynolds Stress

.


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