+ All Categories
Home > Documents > Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California,...

Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California,...

Date post: 12-Jan-2016
Category:
Upload: rose-holland
View: 213 times
Download: 0 times
Share this document with a friend
Popular Tags:
52
Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis
Transcript
Page 1: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

Observation and simulation of flow in vegetation canopies

Roger H. ShawUniversity of California, Davis

Page 2: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.
Page 3: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

•Kinetic energy spectral densities that are strongly peaked•Strong correlations between streamwise and vertical velocities•Large velocity skewness (Sku>0; Skw<0)•Transport dominated by organized structures•Larger contributions from sweep motions than ejections

Canopy turbulence

Page 4: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

“We will understand the movement of the stars long before we understand canopy turbulence”

Galileo Galilei

Page 5: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.
Page 6: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.
Page 7: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

Time traces of velocity components

Page 8: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

Z=2.4h

Page 9: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

Z=0.9h

Page 10: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

Scalar ‘ramps’ correlated through the depth of the canopy show wholesale ‘flushing’ of

the canopy airspace by large scale gusts.

Page 11: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.
Page 12: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.
Page 13: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

Scalar

Page 14: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

Vertical velocity

Page 15: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

Streamwise velocity

Page 16: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

Turbulent kinetic energy budget determined from LES

Page 17: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

Large-eddy simulation of surfaceand canopy layers

•Based on NCAR code developed by Moeng (1984)•Modified to include drag effects on both the resolved-scale flow and SGS motions•An experimental tool and framework for investigation of observed phenomena

Page 18: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

2

Resolved- and subgrid-scales

in large-eddy simulation (LES)

Page 19: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

W av en u m b er

Ene

rgy

spec

tral

den

sity

x

R eso lv ed -sca les

S u b g rid -sca le s

LES resolved- and subgrid-scales

Page 20: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

X = 96 grids

Z=30grids

A sketch of simulated domain

canopy( green region ) = 1/3 vertical domainshear dominant ( neutral )

F ig u re 1

canopy

• periodic horizontal boundary conditions

• frictionless lid at upper boundary (no flux)

• uniform force to drive the flow

• scalar source through depth of canopy

Page 21: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

Canopy specification:

•Represented at each grid point by element area density a (m2/m3)•Area density horizontally uniform but a(z)•Canopy elements rigid•Volume occupied by solid elements is considered to be negligible

Page 22: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

Static pressure perturbation

Page 23: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

2

Resolved- subgrid- and wake-scales

Page 24: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

Mean flow KE

Resolved-scale TKE

Subgrid-scale TKE

Internal energy

1 2 3

Page 25: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

Mean flow KE

Resolved-scale TKE

Subgrid-scale TKE

Wake-scale TKE

Internal energy

Viscous drag

Form drag

1 2 3

4 5 6 7

8 9 10

Page 26: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

Drag parameterization:

i d sf iF C C au V

1.328 2.326sfC

RR

Blasius solution for flow parallel to a flat plate:

Page 27: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

inertialcascade

formdrag

SGS energy pool

Page 28: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

inertialcascade

formdrag

SGS energy wake energyw

sgs

Page 29: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

ii ij m fd sf

i j i i

ue e eu K

t x x x x

Subgrid-scale energy equation

where

3/ 2 8 8

; ;3 3fd d sf sf

c eC aVe C aVe

Page 30: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

Wake-scale energy equation

3 8

3w w w

i d d m wi i i

e e eu C aV C aVe K

t x x x

where

3/ 2w

wf

c e

Page 31: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

0 .0 0 0 1 0 .0 0 1 0 .0 1 0 .1 1 1 0

N o rm a lize d T K E e / u *2

0

1

2

3

Nor

mal

ized

hei

ght z

/h

W a k e

S u b g r id

T o ta l

R e s .

Page 32: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

1 e -0 0 6 1 e -0 0 5 0 .0 0 0 1 0 .0 0 1 0 .0 1 0 .1 1

N o rm a lize d d if f u s iv ity K / h u *

0

1

2

3

Nor

mal

ized

hei

ght z

/h

W a k e

S u b g rid

R e s .

T o ta l

Page 33: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

- 2 - 1 0 1 2 3

S G S k in e tic e n e rg y b u d g e t

0

1

2

3

Nor

mal

ized

hei

ght z

/h R e so lv e d sh e a r

D iss ip a tio n

D if f u s io n

W a k e e f f ec t

Page 34: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

•Additional variable ew to represent kinetic energy associated with wake motions•Dissipation of ew controlled by dimension of canopy elements

Page 35: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

•Additional variable ew to represent kinetic energy associated with wake motions•Dissipation of ew controlled by dimension of canopy elements•Rate of conversion of kinetic energy from resolved scales to wake scales is large•Effective diffusivity of wake-scale turbulence can be ignored

Page 36: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

•Additional variable ew to represent kinetic energy associated with wake motions•Dissipation of ew controlled by dimension of canopy elements•Rate of conversion of kinetic energy from resolved scales to wake scales is large•Effective diffusivity of wake-scale turbulence can be ignored•Important to include the conversion of resolved and SGS energy to wake-scale kinetic energy

Page 37: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

•Additional variable ew to represent kinetic energy associated with wake motions•Dissipation of ew controlled by dimension of canopy elements•Rate of conversion of kinetic energy from resolved scales to wake scales is large•Effective diffusivity of wake-scale turbulence can be ignored•Important to include the conversion of resolved and SGS energy to wake-scale kinetic energy•Viscous drag and direct dissipation in viscous boundary layers of leaves is of little consequence

Page 38: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

0 1 2 3 4 5 6 7 8 9

x /h

0

1

2

3

4

5

6

7

8

9

y/h

P e rtu rb a tio n sca la r co n c en tra tio n c /c*

Page 39: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

0 1 2 3 4 5 6 7 8 90

1

2

3

z/h

N o rm a liz e d sc a la r c o n c e n tra tio n

0 1 2 3 4 5 6 7 8 90

1

2

3

z/h

N o rm a liz e d p re ssu re

0 1 2 3 4 5 6 7 8 9

x /h

0

1

2

3

z/h

N o rm a liz e d s tre a m w ise v e lo c ity p e rtu rb a tio n

Page 40: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

Conditional sampling of LES output and composite averaging of flow structures

1. Pressure signal at z/h=1 used as detection function2. Structures aligned according to peak in pressure signal3. Composite averages of various elements of the structures

Approximately 1,600 events extracted from one 30-minutetime series (but not all independent)

Page 41: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

- 4 - 3 - 2 - 1 0 1 2 3 4

S tream w ise p o s itio n x /h

1

2

3

Hei

ght z

/h

P ertu rb a tio n s ta tic p re ssu re

Page 42: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

- 4 - 3 - 2 - 1 0 1 2 3 4

S tream w ise p o s itio n x /h

0

1

2

3

Hei

ght z

/h

S tream w ise v e lo c ity p e rtu rb a tio n

Page 43: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

- 4 - 3 - 2 - 1 0 1 2 3 4

S tream w ise p o s itio n x /h

1

2

3

Hei

ght z

/h

V ertica l v e lo c ity

Page 44: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

- 4 - 3 - 2 - 1 0 1 2 3 4

S tream w ise p o s itio n x /h

1

2

3

Hei

ght z

/h

S ca la r co n cen tra tio n p e rtu rb a tio n

Page 45: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

270 seconds (17 frames)

Page 46: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

-4 -2 0 2 4

-2

0

2

-4 -2 0 2 4

-2

0

2

y/h

x/h

Page 47: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.
Page 48: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

0

1

2

-4

-2

0

2

4

-5

-4

-3

-2

-1

0

1

2

3

4

XY

Z

x

0

1

2

-4

-2

0

2

4

-5

-4

-3

-2

-1

0

1

2

3

4

XY

Z

y

0

1

2

-2

0

2

4

-4

-3

-2

-1

0

1

2

3

4

XY

Z

z

Page 49: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

0

1

2

-4

-2

0

2

4

-2-1

01

2

X

Y

Z

0

1

2

-4

-2

0

2

4

-2-1012

X

Y

Z

0

1

2

-4

-2

0

2

4

-2

-1

0

1

2

X

Y Z

Page 50: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

The structure of the large-eddy motion as a solution to the eigenvalue problem:

Where ij is the spectral density tensori is the eigenvector is the associated eigenvalue

*, , , , , , , ,j iij x y x y x y x yD

k k z z k k z k k k k z

Page 51: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

u -v e lo c ity

w -v e lo c ity

sca la r

- 8 - 6 - 4 - 2 0 2 4 6 8

rx /h

00.51

1.52

z/h

- 8 - 6 - 4 - 2 0 2 4 6 8

rx /h

00.51

1.52

z/h

- 8 - 6 - 4 - 2 0 2 4 6 8

rx /h

00.51

1.52

z/h

Page 52: Observation and simulation of flow in vegetation canopies Roger H. Shaw University of California, Davis.

Recommended