ryuichi inoue, kyoto university kazuyoshi nishijima, dpri...

Modeling of wind flow around tree for CFD simulation

Ryuichi Inoue, Kyoto University

Kazuyoshi Nishijima, DPRI, Kyoto University (Speaker)

UNESCO-JASTIP Joint Symposium on Intra-Regional Water Securityand Disaster Management, Quezon City, the Philippines, November 16, 2017

Bangladesh, courtesy of Prof. Ando

17/04/2008

西嶋一欽京都大学防災研究所 2会議名発表タイトル17/04/2008

Kazuyoshi Nishijima, DPRI-KU 2UNESCO-JASTIP Symposium Modelling of wind field around tree

• Field surveys on vernacular constructions in southeast Asia.

• Damage survey after typhoon Yolanda with UP Diliman in 2014, J-RAPID project.

• Damage survey after hurricane Pam in Vanuatu in 2015

Observations

• Damages on non-engineered construction with industrial materials.

• Sometimes, traditional constructions behave wellunder extreme events.

Background

Samar, the Philippines

Bangladesh

Tanna, Vanuatu

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Motivation

• Re-evaluate the performance of traditional construction techniques by state-of-the-art technology engineering tools.

• Justify the advantages of the traditional techniques, where true.

Engineeringknowledge body

Pro

gre

ss

Engineeringfrontier

Non-engineeredsystems

Feed

back

JSPS project: 16H05905, Grant-in-Aid for Young Scientists (A), Re-evaluation of vernacular

disaster mitigation technologies by engineering manner – case of wind-induced disaster

(2016-2019)

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Some ongoing projects in our research team

• JASTIP WP4 in corporation with the University of the Philippines, Diliman, 2015-2020.

Telecommunication tower

New tower

Incoming wind

Boundary layer

AnemometersAnemometer

More anemometers

Wind

Kapit Bahay 1.0developed by UPD

Physical computing

• JICA grass-root project“Advancement of vernacular constructions in Tanna island, the Republic of Vanuatu”, 2016-2018.

Full-scale testingIntelligent anemometer

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Today’s talk is...Wind-breaking effect of tree

Contents

• Objective of research

• Wind tunnel experiment

• CFD simulation

• Optimized aerodynamic parameters in CFD

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Objective

Challenge addressed in this research

• Current canopy models do not consider mechanical characteristics of tree behavior under various wind speed; hence, fail to simulate wind field accurately.

Goal of the research

• To develop a canopy model that can simulate wind flow affected by tree and other plants.

Wind tunnel (2m/s)

Wind tunnel (4m/s)

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Wind tunnel experiment

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Tree model

• Tree model consists of trunk, branches and leaves.

• Made of timber, acryl and plastic film respectively.

• Leaves are connected to branches with silicon tubes.

• Leaves are painted white for image analysis.

330m

m120m

m

20°Φ5mmacryl tube

Φ24mmTimber solid pole

Leaf area density: 4.7



500mmplastic film

Top view Side view

(m2/m3)

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330

120

(Unit: mm)

Inflow wind condition

• Uniform flow

• Wind speed: 2, 4 and 8 m/s

U: Mean wind speed

Ur: Reference wind speed (at 510mm)

σu: Standard deviation of wind speed

z: height

Average time = 30 sec.

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Measurement condition

Measurements

• Wind speed measured with I-shape hotwire probe.

• Drag force acting on the tree model with aerodynamic balance.

• Motion of the tree model with video camera.

120

（mm）

wind

600 400

600 400

30m

m×

14

420

30m

m×

24

Measurement pointSide view

Top viewFloor

z

xo

x

o

y

1000

500

Pitottube

1000

500wind

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Result: horizontal wind profile behind tree model

• Wind speed reductionbehind the tree model

• Wind speed recoveryin furtherer points.

Horizontal wind speed profile at height of 300 mm at x=600 mm and 1000mm.

wind 540

z

xo

500

1000-1000

U0(z)U(z)

Pitot

600

(mm)

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Result: Drag force

• (Projected) leaf area density, a

• Drag coefficient, Cf

2 2

1 2A B

D u d u d Drag force:

ρ：Air density

u：Wind speed

σ：Area

Theory A B

Object

Du1 u2

A’ B’

Measured drag force Calculated Cf a

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Result: Aerodynamic parameters



2 2

1 2A B

D u d u d Drag force:

ρ：Air density

u：Wind speed

σ：Area

Theory A B

Object

Du1 u2

A’ B’

Observations

• Aerodynamic parameters depend on wind speed

• Drag force (hence, aerodynamic parameters) are interrelated to the change of the wind speed profile

“Optimal” aerodynamic parameters are identified by CFD simulation.

Measured drag force Calculated Cf a

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CFD simulation

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Generation of inflow

• Boundary condition

–Ceil boundary: slip

–Side boundary: slip

–Floor boundary: canopy model

• Grid condition

–X direction:20mm

–Y direction:10mm

–Z direction:10mm - 80mm

–Volume:18m×2.5m×2.01m

xy

z

O

2.0

1m

2.5m

Analysis of wind flow around the tree model

Generation of inflow

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Generated inflow

*u is calculated based on 0.01-sec averaged wind speed.

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xy

z

O

Analysis condition around the tree model

• Boundary condition

–Ceil boundary: slip

–Side boundary: slip

–Floor boundary: canopy model

• Grid condition

–X direction:20mm

–Y direction:20mm

–Z direction:20mm - 60mm

–Volume:3.5m×2.5m×2.01m

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Re-parameterization of aerodynamic parameters



x-direction wind speedat z=280mm

''

f f

aaC a C

a

Wind speed dependent

Re-parameterization

Wind speed dependent

Leaf area density under no wind

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Result: simplistic modelling of tree

wind

330

Three layered cuboids

330

Rotated three layered cuboids

wind

More precise modeling required.

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Detailed tree modeling for CFD

• Image of tree silhouette at wind speed=0m/s

• Binary analysis (black: no object, : object)

– If an

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Optimized aerodynamic parameters

Comparison of CFD results and experiment results at x=600, z=300

Optimized aerodynamic parametersa’： Projected leaf area density

under no wind

a： Projected leaf area density

Cf： Drag parameter

Adjusted drag parameter

2 4 8a' 19.8 19.8 19.8

a /a'*C f 0.4 0.3 0.2

Wind speed(m/s)

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Conclusion

• A tree model for wind tunnel experiment is developed

– It can show the wind-speed dependence characteristics of aerodynamic parameters.

• Simplistic modeling approach for tree in terms of canopy model fails to reproduce the wind speed profile behind the tree in CFD.

• An elaborated modeling approach shows a potential to be able to reproduce the wind speed profile.

• We will have a tool to evaluate the advantages of wind-breaking forest on wind-resistant performance of buildings.

17/04/2008



“to measure is to know –

if you cannot measure it,

you cannot improve it”

Lord Kelvin

ryuichi inoue, kyoto university kazuyoshi nishijima, dpri...

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