State and Prospects of Wind Hazard Mitigation Research in
TPU
Yukio Tamura a, Masahiro Matsui a, Akihito Yoshida aaWind Engineering Research Center, Tokyo Polytechnic University,
1583 Iiyama Atsugi Kanagawa, 243-0297, Japan

ABSTRACT: In the Global COE Program "New Frontier of Education and Research in Wind
Engineering", the objective of the project-1 is to study how to mitigate the wind hazard. To accomplish this objective, following items were investigated, (1) characteristics gust such as tornadoes and thunderstorm, (2) monitoring of response of buildings and structures with GPS, (3) development of experimental system for cladding under wind pressures, (4) wind damage
recognition using satellite and aerial images, (5) aerodynamics for various structures and groupof buildings, (6) development of engineering virtual organization, EVO, in the cyberinfrastructures and (7) any other issues related to wind engineering in the structural engineering
field. These project items were carried out as planned. More researches were carried out additionally. This report shows the outline of the activities and results of the researches.
KEYWORDS: Wind Hazard Mitigation, Wind Resistant Design, Aero Dynamic Database
1 INTRODUCTION
The overarching objective is to develop a gateway of knowledge base aimed at improving theunderstanding of wind loads and their effects and their efficient modeling at laboratory scale andon computational platforms to achieve robust and cost effective wind-resistant design for urban
disaster prevention. The main target areas in wind disaster prevention and mitigation are: todevelop rapidly deployable wind observation systems aimed at improving understanding of thewind field characteristics in extreme wind events; to establish robust damage identification
schemes at the urban level using satellite imagery and aerial photography; to understand andmodel the effects of gust events including tornadoes on structures; to develop advanced testingprocedures for building exteriors/cladding and components for windborne debris impact andrepeated cyclic loadings under buffeting; to enhance understanding and modeling of the
aerodynamic characteristics of buildings situated in complex urban environments; to improve thewind resistance of green roofing systems and thermal insulation of roofs for environmental
protection and energy savings; to establish a web-based network of GPS monitoring systems toenhance urban disaster prevention; to develop wind-resistant construction methods including
retrofit and repair for Asia-Pacific countries and beyond. Other targets areas include:
establishment of VORTEX-Winds EVO involving a host of analysis and design modules andknowledge bases; to develop domain knowledge necessary for populating the EVO and its
maintenance.

2 CHARACTERISTICS OF TORNADO-LIKE FLOW AND ITS EFFECT TO BUILDINGS,DISASTER INVESTIGATION, DAMAGE RECOGNITION FROM AERIAL IMAGES

2.1 Experimental Research
Tornado is very rare but one of the severest wind event for most countries. In Japan, around
20 to 40 tornadoes have been observed annually. Tornado events are characterized by unpredictability, short life span and danger, making real time evaluation difficult. This necessitates analysis of tornado-wind loadings on buildings in laboratory situations. With this objective, scaledbuilding models were subjected to a stationary vortex created using a tornado simulator. Parameters that govern a tornado like flow such as swirl ratio, aspect ratio were in close agreement withprevious studies. In the present investigation the influence of factors such as building location
relative to vortex center, swirl ratio, and terrain roughness on the mean and peak pressures in abuilding model under tornado-like flow is evaluated. Building faces perpendicular to the tangential flow experiences lesser suction pressures compared to the other faces near the core boundary, whereas they experience higher suction pressures far from vortex center. Lower swirl ratios
produce higher roof suction pressures compared to building walls whereas higher swirl ratios
have roof suction comparable with pressures on leading edge wall. The effect of roughness wasto enhance suction pressures on roofs of buildings and decrease the pressure magnitudes on sidewalls compared to a near smooth ground.
Post tornado damage investigations revealed building roof and openings on buildings as two
critical failure modes. The effect of building location relative to vortex, terrain roughness andswirl ratio on measured internal pressures for two opening ratios namely 3.9% and 0.1% onbuildings were determined. Higher negative minimum peak internal pressure coefficients are experienced by a 3.9% opening ratio case within vortex core compared to case of 0.1%. This behavior reverses outside the vortex core. Lowest minimum net peak roof force coefficients can increase to four fold, for the same building location but different building orientation.

-1

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Cpi m in im um

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3.9% case
0.1% case

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-7
0

0.5

1

1.5

x/ r

2

2.5

3

c

(a)
(b)
(c)
Fig.1 (a) Tornado vortex visualized in the simulator (b) Mean pressure coefficients on cube faces(c) Minimum peak internal pressures at different building locations for two opening ratios [1]2.2 Site investigation after tornado disaster
Based on JMA data, 124 gusty winds are observed on the Japanese islands in 2009 and 2010.
Of the total, 63 were tornadoes, 11 were downbursts, 9 were gust fronts, 21 were water spouts,
and 20 were unknown phenomena. As an example, the major tornadoes, gust fronts and downbursts in 2009 are shown in Fig.2.
Damage investigations, including, Tsukuba-tornado on May 6th 2012 in Tsukuba, Ibaraki, Japan, were carried out actively by GCOE members. As the one of the resolutions for sharing resources, EVO (Engineering Virtual Organization [https://www.vortex-winds.org/]) was developed and released in 2010. The damage database is one of the main contents of EVO. The
Browsing interface of the damage database in Vortex-Winds is shown in Figure 13. When eachpoint is clicked, the browsing interface for each structure appears as shown in Figure 14. The
damage database, powered by Google Earth, allows users to geographically view submissions of
fellow VORTEX-Winds members, sorting by location, event classification and damage attributes. Registered members can also upload their own damage reports to the database.

Fig.2: Damages due to the gusty winds in 2009 in Japan [2]2.3 Automatic wind damage detection from remote sensing image signals using wavelet based
pattern recognition
Damages to building structures, due to strong winds, such as tropical cyclones and tornadoes
have been a fact of life since time immemorial. Rapid relief provided by recognizing the appropriate damaged locations as well as the buildings will reduce the impact of such disasters andwill aid conventional field investigations after a strong wind disaster. Here wind damage location
identification is done automatically from low resolution remote sensing imagery, initially by using texture-wavelet analysis on wind borne debris deposits, for a quick survey and for emergency aid. Then the damaged location in the low resolution is mapped on high resolution imagery.
From this the buildings are automatically segmented by using color invariance properties andedge detection. Damaged buildings are automatically identified using wavelet based feature extraction, in-hand with artificial neural network, (ANN) and support vector machine (SVM). An
economical identification of wind damaged buildings from post-storm imageries alone using texture-wavelet analysis is then performed in the current work. It was observed that even using
post-storm alone an accurate damaged building identification could be achieved. Percentage areaof roof damage is also quantified using texture-wavelet analysis on change detected damagedbuilding roofs as well as on the post-storm roof images alone. A good positive correlation withmanually obtained percentage area of damage was obtained even by using post-storm alone.
New user friendly software is designed for rapid and easy damage detection from debris deposit.
Application of the current research in real time situations such as that of Tuscaloosa, US tornado
and Tokunoshima tornado in Japan and in other type of natural disasters such as Thailand flood,water covered area detection were also investigated. Application in determining F-scale of thetornado from debris deposit path width and a generalization of automatic damaged building detection is also determined in this research. Thus accurate and faster wind damage identificationfrom a remote sensing perspective is successfully achieved through this research.

(1)

(2)

(3)

Fig.3: (1) shows the damaged path detected from debris deposit by texture-wavelet analysis on
post-storm imageries alone, once the damage is identified the buildings are segmented at thedamaged location and damaged building are identified and shown in (2). (3) shows the percentage area of damage identified automatically. [3]3 ESTABLISHEMENT OF WIND-INDUCED RESPONSE MONITORING NETWORK FOR
BUILDINGS USING GPS TECHNOLOGY
3.1 Objective of this research topic
In current wind resistant design, wind loads on buildings and the wind environment aroundbuildings are examined while projects are still in the planning stages, and they are not confirmed
after the completion of construction. Surrounding environments have a strong effect on windloads on buildings, and wind loads on buildings in urban areas are also changing with the growthof cities. Buildings should be treated as elements of an urban area. If publicity of this policy
succeeds, it will be possible to realize long-life cities. This will provide good direction from theviewpoint of safety, environment, and economy. In previous researches[4], feasibility studies
have been conducted on wind-induced responses of buildings by using RTK-GPS (Real-Time
Kinematic GPS) and it was concluded that responses with amplitudes larger than 2.0 cm andnatural frequencies lower than 2.0 Hz could be detected by RTK-GPS. However, to obtain
responses in urban areas by GPS, there is a difficulty in deciding the location of the reference
station. To solve this problem, a virtual reference station is introduced in this paper. The
possibility of a virtual reference station was investigated by full scale tests. It was concluded thatthe virtual reference station can be used as a reference station, and a monitoring network forbuildings was established in the Tokyo area.
3.2 Necessity of Virtual Reference Station
In urban areas, it is especially difficult to set reference stations at arbitrary points. To avoid these
difficulties, the virtual reference station system is employed. The Virtual Reference Stationconsists of multiple GPS reference stations, as shown in Fig.4 (at least 3 stations are needed). As
multiple GPS reference stations, ‘GEONET: electronic reference points by the Geographical
Survey Institute’ or ‘original reference points’ are employed.

Reference
Station

VirtualReference
StationReference
StationReference
StationFig.4 Concept of virtual reference station

3.3 Establishment of real-time-observation network for measuring structural response in urban
area
Based on the results showing the measuring capabilities using RTK-GPS shown in the lastsection, we established a real time observation network in the Tokyo area. In this network, anelectric reference is not used for the reference station. We set 3 reference sensors as shown in
Fig. 5. The incremental time was 0.1 seconds. The 3 sensors for measuring points were on top of
4 buildings in the center of the Tokyo area. Fig. 6 depicts the elevations of these buildings.
The sampling frequency of recording data was 10 Hz. In the measuring system, the recording data was transferred to the Analysis PC in Tokyo Polytechnic University and the responsecould be monitored in real time. Fig. 7 shows the power spectrum of the deformation of Build. 1
based on measured data obtained by this GPS system [NS and EW direction]. When strong wind
was acting on the building, there was a peak around 0.35 and 0.38Hz. This peak could be foundin the record of the accelerometer set at the same location. It was confirmed that these peaks
were the natural frequency. Moreover, in this figure, the frequency components in the low frequency range show high values. This means that the average (static) component could begrasped using this GPS system.
GPS Antenna

SUMIDA

NAKANO

178 m

SHINJUKU(Build. 1)

KOUTOU

Frequency Component

Fig. 5 locations of reference and measuring points-410▼ 0.35Hz
Strong Wind

-5

10

-6

10

-7

Moderate Wind

10(a) NS direction
Fig. 7 Frequency characteristics of measured displacement

Fig. 6 Elevations of measured building
Frequency Component

Reference Points
Target Points

134 m

CHIYODA(Build. 2 and 3)

198 m

GPSｱﾝﾃﾅ-4

0.38Hz

10

▼

-5

10

Strong Wind

-6

10

Moderate Wind

-7

10

0.1

1
Frequency (Hz)(b) EW direction

4 INVESTIGATION OF WIND RESISTANT PERFORMANCE USING PRESSURE
CHAMBER
4.1 Development of wind resistant performance test system
In the past damages due to the strong winds such as tornadoes, typhoon, down burst, most ofdamages are on the low rise buildings. Especially, damages of cladding, roof panel, ceilingboard are remarkable as shown in Fig. 8. The pictures in Fig. 8 show the damages on eaves andceiling boards. Recently, the peak pressure coefficients are estimated under various types ofconditions in the wind engineering field (using wind tunnel tests, numerical simulations, andfield measurements) for cladding design and effective-design materials are organized. However, as shown in these pictures, there are many kinds of the details on the ceiling boards, claddings, eave etc. So it is important to establish the testing system to clarify the strength of cladding against the severe suctions under static and dynamic conditions. The experimental system
for simulating the behaviors of the cladding [It is called pressure chamber] was set in our Wind

Engineering Research Center. The specimen of the cladding is set on the top face of the pressure chamber and pressure inside the chamber (chamber pressure) can be adjusted from -10kPa
to 10kPa. This experimental system consists of 3 parts (Pressure Generating Section, Pressure
Adjusting Section, and Test Section). This system is controlled by the personal computer asshown in Fig. 9. In the pressure generating section, there are the 2 fans (11 kW). One of themis for positive pressure supply and another one is for negative pressure supply. In the Pressure
Adjusting Section, there is a interlock valve for adjusting the pressure inside the pressure chamber.

Fig. 8 Damages due to the strong wind on the ceiling board and eave
Positive
Negativepressurepressure(11kW)(11kW)
PressureFans

Container for
fans

Pressure
Generating
SectionMotor for interlock valve

Flowregulating
valve

Angle gauge

Test
Section

Safety valve
Interlockvalve

Pressure
Adjusting
SectionOpen valve
Barometer

Pressure
Chamber*Control order for fan *Current rpm for fan*It for regulating valve *Current deg for reg. valve*Current kPa for barometer*Triggersignal for
Range:*State of open valve-10.0 ~ 10.0 kPa safety valve*Control orderfor regulating valve
3m(B)×3m(D)×0.3m(H)PC

Touch panel

Measuring system（Max. 8ch can be measured,
Currently 3ch are used）

Fig. 9 Conceptual Drawing of experimental system
4.2 Wind resistant performance of a ceiling panel system of piloti
For establishing the experimental method and solving the problems of test using the pressurechamber, the ceiling setup was set as the specimen the pressure chamber and the strength of thespecimen was measured.
Fig. 10 shows the Vertical displacement of Ceiling Panel and Ceiling Joist. As shown in thisfigure, -2.45kPa is the strength of this ceiling system based on the results of this experiment.
The main reason of the collapse of this ceiling system is 2 types of the failure of the Screw asshown in Fig 11.

Vertical displacement
[mm]

14
12
10
8
6
4
2
0

Ceiling Panel

Ceiling Joist

0

-0.5

-1
-1.5
-2
Chamber Pressure [kPa]-2.5

Fig. 10 Vertical displacement of Ceiling Panel and Ceiling Joist
Screw
Damage on
Ceiling Board
Ceiling Joist
Ceiling Board(a) Damage of Ceiling board
Damage on
Ceiling Joist

Ceiling Joist

Ceiling
Board

Screw

(b) Damage of Ceiling joist
Fig. 11 Observed 2 types of damages on strength test of ceiling system
5 INTERFERENCE EFFECT ON TWO ADJACENT TALL BUILDINGS

5.1 Introduction of this research topic
Most wind load codes have been derived for isolated buildings. However, wind loads on tallbuildings surrounded by other tall buildings in real environments may be quite different fromthose on isolated tall building. Surrounding tall buildings can either increase or decrease not only
overall wind loads on a building but also local peak pressures acting on the building cladding.
Unfortunately, few codes have referred to wind-induced interference effects on wind loads onbuildings (AS/NZS 1170.2[5], 2002; AIJ, 2004[6]). These codes only briefly accommodate windload effects of neighboring tall buildings, mainly dealing with shielding effects, which is beneficial to the building structural system and claddings. Because there are a large number of variables involved, such as building size and shape, relative locations of interfering building(s), wind

directions, upstream terrain conditions and so on, it is difficult to consider all parameters incodes.
The main aim of this study is to tackle the problem of interference for local peak pressures on atall building in order to establish a generalized set of guidelines. Extensive wind tunnel
experiments have been conducted to measure local peak pressures on a tall building with aninterfering building for different height ratios and various wind directions for an urban exposure
condition.[7][8]5.2 Wind tunnel experiments
Wind tunnel experiments on a high-rise building model with various arrangements and heightratios of an adjacent building were carried out in a Boundary Layer Wind Tunnel located at Tokyo Polytechnic University, Japan as shown in Fig 12. For this study, the flow of the atmospheric boundary layer in the wind tunnel was interpreted as a geometrical scale of approximately
1:400. The approach flow represented an urban wind exposure using the spire-roughness technique with a power law exponent of 0.27. The wind speed and the turbulence intensity at theheight of the model (principal building) were 8.2 m/s and 20%, respectively.
The considered experimental models comprised two buildings: the pressure model, referred
to as the principal building, and the other model, referred to as the interfering building. Fig 13
shows the coordinated system indicating the different locations of the interfering building andwind directions. The center-to-center spacing between them was varied by Sx longitudinally andSy laterally. Table 1 shows cases of the experimental models used in this study.
The fluctuating wind pressures on the building faces were simultaneously sampled every
0.00128 seconds and the sampling period was 7.5 seconds for each sample. The data were digitally low-pass filtered at 300 Hz. For each test case, 15 samples of 10-min length in full-scaleconversion were analyzed. The tubing effects were numerically compensated by the gain andphase-shift characteristics of the pressure measuring system. The pressure data were filtered bymeans of a moving average filter corresponding to 0.2sec in full scale. Further, the maximum
and minimum peak pressure coefficients were calculated by the Cook & Mayne method.

Interfering building(4B, 2B)



(0, 0)
Principal building

Fig 12: Experimental models in wind tunnel
tions.

Fig 13: Coordinated system indicating different
locations of interfering building and wind direc-

Table 1. Experimental models
Height ratios Locations Wind directions
Experimental models Dimensions (mm)(B×D×H)(Hr=Hib/H)
Principal building
70×70×280
1
1
0o – 355o (5o steps)
Interfering building
70×70×1400.5
370o – 355o (5o steps)
70×70×196
0.7
470×70×280
1
37
70×70×420
1.5
37
70×70×560
24
 H and Hib are height of principal building and interfering building, respectively

5.3 Simultaneous pressure measurement and flow visualization
To obtain further information and understanding on the interference mechanism for enhanced local peak pressures on the principal building with interfering building of Hr=1, flow
fields around two buildings for worst wind directions in tandem and oblique arrangements havebeen investigated by simultaneous pressure measurements and flow visualization using dynamic
particle image velocimetry (DPIV) in wind tunnel of Shimizu Institute of Technology, Japan.
This system consisted of a high-speed digital video camera, a double pulse Nd: YAG laser and aparticle generator. The fluctuating wind pressures and the image of particle were simultaneously
sampled every 0.0001 seconds and the sampling periods were 7.5 seconds and 6 seconds for eachsample, respectively. Tracer particles were discharged from downstream of the principal building and then circulated in the wind tunnel. The particles were illuminated by a pulsed laser lightsheet. The image was captured in digital memory using a computerized data acquisition system
for a field of view of 276mm×207mm.
5.4 results and discussions
5.4.1 Effects of building arrangement

The minimum negative peak pressure coefficient ( C p ) for all measurement points on the principal building and all wind directions can be expressed by:
C p  min C p (i, j , ) 
i , j , (1)
Fig 14 shows the contour of C p on the principal building for interfering buildings of differ
ent height ratios and various locations, and C p on the isolated building was -3.7. From Fig 14,
C p on the principal building was decreased and expanded with increase in height ratio of the interfering building.

Another interesting observation was that C p for Hr=1 and 1.5 significantly decreased when
the interfering building was located in oblique arrangement. However, it should be noted that thecritical locations of the interfering building vary with increase in height ratio. Interference ef
fects of C p on the principal building were also investigated in this study.
However, the results show that C p on the principal building for interfering building of different height ratios and various locations was similar to that an isolated building.

4

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Sx / B

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1

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8
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2
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2 -4.26-4.

2 -4.2-4-4.8--4-4.4.2
4
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Sy / B

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3

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5

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2 4
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4
.
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2
.
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4

-4 -4
.2

-3.8

Sy / B

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6

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8

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3

5

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4

-4

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5

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6

2

3

4

5

Sx / B-3.8
6(b) Height ratio (Hr) = 1(c) Height ratio (Hr) = 1.5(a) Height ratio (Hr) = 0.5
Fig 14: Contour of C on principal building for interfering building of various height ratios
and locations ( C (Isolated) = -3.7).


p



p

5.5 Flow pattern in oblique arrangement
Fig 15 shows the instantaneous pressure coefficients on the principal building with interferingbuilding of Hr=1, velocity vector and vorticity fields around two buildings in oblique arrangement with (Sx,Sy)=(2.5B,2.5B) for wind direction θ=65o when the smallest minimum peak pressure coefficient on the principal building occurs. From Fig 15(b) and (c), the strong shear layer
generated by the interfering building directly hit the principal building, leading to increased momentum at the upper face (front wall) of the principal building. This rose to a high pressure coefficient near the leading edge of the upper face of the principal building, as shown in Fig 15(a).
Furthermore, it is inferred that some changes of wind directions (55o    85o) could lead to an
obvious decrease in minimum peak pressure coefficients acting on the principal building.
Wi

R ig

ht

Fro

nt

t
Lef

k
Bac

0

-0.5

-0.5

-1

-1

y/B

y/B

Wi
nd

0

-1.5

-1.5

-2

-2

-2.5

-2.5
0

0.5

1

1.5

2

x/B

2.5

3

3.5

0

0.5

1

1.5

2

x/B

2.5

3

3.5

(a) Pressure coefficients(b) Velocity vector field(c) Vorticity field
Fig 15: Instantaneous pressure coefficients on principal building with interfering building of
Hr=1, velocity vector and vorticity fields for wind direction θ=65o in oblique arrangement (Minimum vorticity and increment of vorticity contour are 100 and 100s-1, respectively).
5.6 Conclusions
A detailed and comprehensive study of wind-induced interference effects on buildings has been
carried out. Based on the results of these detailed experiments that consider various relevant pa-

rameters, general guidelines for limiting conditions have been formulated and critical interference effect situations identified.
6 WIND LOADING ON POROUS SUNSHADE ROOF COVER SHEETS

6.1 Introduction of this research
Scaffolding is a temporary structure used to support people and material in the construction or
repair of buildings and other large structures. It is usually a modular system of metal pipes or
tubes. For safety, environmental and noise considerations, it is commonly net clad or sheet clad.
On construction sites, scaffolding collapses sometimes occur due to strong wind when thescaffolding is covered with sheets of 0% porosity, which significantly increases the wind forces
acting on it (Katsutoshi Ohdo, 2005). Furthermore, buildings of different structural types havedifferent kinds of wall openings during construction stages, which also significantly affect windforces (F. Yue, 2005; Yasumichi Hino, et al, 2005). Thus, the influence of building opening
ratios should be considered in the design stage when estimating wind forces acting on
scaffolding. For different construction sequences and engineering needs, for a common
rectangular section building, scaffolding arrangements vary from one side to all four sides,
which affect the wind flow between building and scaffolding (Yasumichi Hino, et al, 2005).
In this study, wind tunnel experiments were carried out based on a prototype of scaffolding
attached to a medium-height building, and covered with sheets of 0% porosity. A systemic studyof the influence of different building openings on wind forces acting on scaffolding covered withsheets was conducted, and scaffolding arrangements were also taken into account.
6.2 Experiment setup
Two scaffolding sheet models 5mm thick and 0.363m high were selected to simulate 0%
porosity sheets covering scaffolding, attached to a medium-height building with 1/75 geometricscale.
304 pressure taps were arranged on both outer and inner sides of the two sheet models (Sheet
A and Sheet B). 4 building opening ratios and 6 scaffolding arrangements were considered.
Building opening ratios  B for Models B0, B20, B40, B80 were 0%, 20% 40%, 80%,
respectively, and two dummy models (no pressure taps) of sheets were used in some scaffolding
arrangements. Fig. 16 shows experiment pictures. Fig. 17 shows building models and scaffolding
arrangements.

(a) U1 arrangement,  B =40%
Fig.16: Experiment pictures(b) I1 arrangement,  B =80%(a) Building models(b) Scaffolding arrangements
Fig. 17: Building models and scaffolding arrangements
6.3 Results and discussions
The maximum local mean Cf usually occurs near wind direction 45 degrees for scaffolding arrangement I1. Fig. 18 shows the local mean Cf distribution of model Sheet A for scaffolding arrangement I1 and wind direction 45 degrees. The maximum local mean Cf occurs at the top corner of the model when B (building opening ratio) increases, and the value of the maximum local
mean Cf becomes smaller, from 2.6 decreasing to 1.8 at the corner of the model.

1.2

1

1.8

1.2 1.5

0.4

0 .4
0 .6

 B =40%

1

0.
8

1

1.4

0.8

 B =20%

1.2

1
0 .6
0.8
0.6 0.4

1

0.
8

0.8
0.6

6
1. .4
1
1 .2

1

0.8

1.2

1

0 .8
0 .6
0.4

0.8

1

0..86
0

1.2
1

0.6

0.6

 B =0%

1.
6

4
1.
1.2

0 .8
0.6
0.4

1.
2

0 .8
0.6

9
0.

0.6

0.
9

2.1 1.8.5
1

1.5

0.9
0.6

1.
2

1

1

 B =80%
Fig. 18: Local mean wind force coefficient distribution, arrangement I1, 45 degrees (Sheet A)

I1 Arrangement
L Arrangement
U1 Arrangement
U2 Arrangement
O Arrangement

3.0
2.5
2.0
1.5
1.0
0.5
0.0

-0.5
-1.0
-1.5
-2.0
-2.5

0

20

40

60

Building opening ratio(%)

80

I1 Arrangement
L Arrangement
U1 Arrangement
U2 Arrangement
O Arrangement

0.0

Minimum local mean Cf (i,)Maximum local mean Cf (i,)The maximum and minimum mean wind force coefficients are expressed as maximum local
mean Cf (i,θ, B) and minimum local mean Cf (i,θ, B), respectively, where i and θ indicate the ith pressure tap and the approaching wind direction, and  B is building opening ratio. Fig. 19
compares the maximum local mean Cf (i,θ) and minimum local mean Cf (i,θ) of model Sheet A
for different building opening ratios. For arrangement I1, when  B increases from 0% to 80%,
the maximum local mean Cf (i,θ) becomes smaller, changing from 2.6 to 1.8, and the minimum
local mean Cf (i,θ) also becomes smaller, from -1.2 to -1.4. For arrangement L, when  B
increases from 0% to 80%, the maximum local mean Cf (i,θ) becomes smaller, changing from 2.2
to 1.6, and the minimum local mean Cf (i,θ) also becomes smaller, from -1.6 to -2.1. For
arrangements U1 and U2, the maximum local mean Cf (i,θ) is almost unchanged, and minimum
local mean Cf (i,θ) changed within the range of ±0.3 for different  B. For arrangement O, boththe maximum local mean Cf (i,θ) and minimum local mean Cf (i,θ) are almost unchanged.

0

20

40

60

Building opening ratio(%)

80

Fig. 19: Maximum local mean Cf(i,θ) and minimum local mean Cf(i,θ) for each building opening
ratio (Sheet A)
Eurocode imply that the force coefficient for wind loads should be 1.3 for winds normal to thescaffolding and 0.1 for winds parallel to the scaffolding, although BS EN 12811 states that thesevalues should not be used for a completely clad building(H. Irtaza et al., 2012). Chinese code
consider the conditions of building with openings and without opening, for sheet clad
scaffolding, JGJ 128 (Safety and technical code for frame scaffolding with steel tubules inconstruction) recommends wind force coefficient should be 1.3φ when building with openings
and 1.0φ for no opening, φ is solidity of sheet. SCEA(Scaffolding and Construction Equipment
Association of Japan) recommends Cf considering parameters of aspect ratio of scaffolding
sheets, subarea and location of sheet, and so on.

Maximum positive total panel Cf()Fig. 20 shows the maximum positive total panel Cf(θ, B) for each scaffolding arrangement.
When scaffolding arrangement is I1, I2, U2 and O, the maximum total panel Cf(θ, B) from windtunnel experiment, 1.41, exceed 1.3 which BS EN 12811 and JGJ 128 recommend, but lower
than 1.61 which was calculated from SCEA Recommendations.
SCEA Recommendations
JGJ 128
BS EN 12811
Sheet A(Experiment)
Sheet B(Experiment)

2.0

1.5

1.0

0.5

0.0

I1&I2

L
U1
U2
Scaffolding arrangement

O

Fig. 20: Comparison between experimental results and wind load recommendations
7 WIND LOADING ON POROUS SUNSHADE ROOF COVER SHEETS

7.1 Introduction of this research topic
Thermal reduction is always a problem for building roofing systems, especially folded steel sheet
systems. Roof insulation helps reduce space heating and cooling, thus reducing requirements forheating and cooling system capacities, increasing occupant comfort, and even eliminating condensation
on roof surfaces in cold climates. Several roof insulation systems have been used up to now, including
the loose laid paver system and heat insulating roof tiles. However, these systems are still expensive.
Porous sunshade roof cover sheets have been introduced as a cheaper alternative. This solution has
several advantages, including cheapness, quick installation and applicability to both new and existingroofs (see Fig. 21 for this solution). Porous sunshade roof cover sheets installed on folded steel sheet
systems reflect sunlight, thus reducing the amount of sunlight reaching the roof. The air layer between
the sheet and the roof prevents the thermal conduction. Fig. 22 illustrates some applications of porous
sunshade roof cover sheets to a real roof of a low-rise building.

Reflective
sunlight

Foldedsteel roof

Porous sunshade
roof cover sheet

Hole

Wind
flow

FixingFig 21: Sketch of porous sunshade roof cover sheet for a Fig 22: Porous sunshade roof coverbuilding roof
sheets on a real building
7.2 Wind pressure experiments[9]H = 200

The wind tunnel experiments for a low-rise building model with the porous sunshade roof coversheets were carried out in a Boundary Layer Wind Tunnel, located in Tokyo Polytechnic
University, Japan. The test section in the wind tunnel has 2.2 m wide by 1.8 m high crosssection. For this study, the flow of atmosphere boundary layer in the wind tunnel was interpreted
as a geometrical scale of 1:50. Terrain category III (profile exponent of 0.2) in AIJ-RLB (2004)
was chosen for the experiments, corresponding to suburban terrain.
The tested model at a length scale of 1:50 is 200 mm high (H)  470 mm wide (B)  710 mmdeep (D), as shown in Fig. 23. The prototype dimensions of the low-rise building were thus 10 mhigh  23.5 m wide  35.5 m deep. There were 3 test model cases to consider the effect of porosities(ratio between area of orifices and area of the sheet) of the porous sunshade roof cover sheets (0%,5% and 10%) with gap between the sheet and the profiled roof a = 4.7 mm (see Fig. 23).

D

B
C

A





Wind

B = 470
D = 710

Fig 23: Test model
7.3 Propose of conversion factor
Fig. 24 shows variationsof the largest maximum peak and smallest minimum peak panel wind
force coefficients C F and C F for sheets A, B, C and D with different porosities . Generally,
the absolute values of the largest C F  and the smallest C F decreased as the porosity increased.
The differences between the largest C F for sheets A and D and for sheets B and C at porosity 

0% and 10% were very small.
 The same phenomenon occurred for values of C F for porosity 
10%. The largest values of C F for porosity  = 0% and 5%
 were higher than that for porosity  =10% up to 180% and 57%, respectively. These values for C F were 176% and 45%.
Based on the results of wind pressure experiment, conversion factors  L to evaluate thewind load acting on the porous sunshade roof cover sheet for porosity  and an underneath volume ratio V* = 0.018 are given inFig. 25.

1-1
Sheet A
Sheet


0.4

Sheet C

0.2

Sheet

-0.6

CF

0.6

Sheet A

-0.8



CF (

0.8

Sheet

-0.4

Sheet D

-0.2

Sheet

0

0
0%

5%

10%

Porosity

0%

5%



(b) Smallest C F(a) Largest C F
Fig 24: Variations of largest C F and smallest C F with different porosities 

0.9

 L = -2 + 0.74

0.8
0.7
0.6
0.5
0.4
0.3
0.2

0.8

Conversion factor LVConversion factor  L

0.9

10%

Porosity

0.7
0.6 LV = 5.8V* + 0.55

0.5
0.4
0.3
0.2
0.1

0.1
0
0%

5%

Porosity ratio (a) Porosity ratio
Fig 25: Variation of conversion factor

10%

0
0.01

0.02

0.03

0.04

Underneath volume ratio(b) Underneath volume

0.05

8 EVALUATION OF WIND RESISTANT PERFORMANCE OF GREEN ROOFINGSYSTEM

8.1 Introduction of this research topic
With trends of increasing urban sprawl, air pollution, heat related illness and mortality, watertemperatures in streams, and greenhouse gas emissions, new mitigation methods are being developed to help address these issues. One such method of mitigation is green roofing systems.
Although green roofing systems are widely popular and well established in European countries,
they are gaining foothold in Asia-Pacific areas such as North America, Japan and China, which
can be reflected from the statistics of the new areas of green roof constructions (Year:
2000~2008) by Ministry of Land, Infrastructure, Transport and Tourism of Japan.
Although green roof systems are gaining popularity, there are few credible guidelines or requirements governing the design and application of green roof systems. During the 2006/2007
code change cycle for the International Building Code requirements, the following section wasadded (International Building Code, 2012):“Section 1507.16 Roof gardens and landscaped roofs.
Roof gardens and landscaped roofs shall comply with the requirements of this chapter and Sections 1607.12.3 and 1607.12.3.1 and the International Fire Code.” As a result, green roofing
systems need to be evaluated for wind resistance.
Corresponding to two types of wind-induced failures for green roofing systems, the two main
objectives of this research are to investigate wind load characteristics of (1) rooftop green roof
modular systems for extensive green roofing systems and (2) rooftop trees for intensive green
roofing systems through wind tunnel experiments.

8.2 Characteristics of wind pressures acting on the multi-level roof
Multi-level flat roofs are widely used in building structures such as public multi-storied buildings, large scale apartments, and industrial buildings. The main concern in the structural designof these buildings was snow drift (Taylor, 1987) rather than wind loads. However, wind pressure
is an important issue in roof cladding design. Moreover, rooftop energy-saving systems such as
green roofing systems are becoming more and more popular and flat roofs as well as multi-level
flat ones provide excellent places for such systems. In order to evaluate the wind resistant performance of such rooftop systems, wind pressure characteristics of multi-level flat roofs with different geometries need to be examined.[10]The height of the prototype building was 30m and the building comprised of 9 stories of
3.3m in height. The geometrical scale of 1:67 was selected to accommodate future study onsmall-sized rooftop systems and the blockage ratio limitation (5%).
In order to conveniently change the geometry of the flat roof, the “Rubic cube” configuration was borrowed and the whole model was constructed from a combination of two kinds ofplexiglass blocks. The lower part included 18 cubic blocks and the upper part comprised 27 cuboid blocks. Flat roofs with multi-level steps could thus be easily realized by removing one orseveral layers of upper blocks. Overall, seven types of roof configurations with different step geometries were investigated, as shown in Fig 26.

450

450

(a) S1(b) M1

45

150

100
450

0
45

300

150

450

50

450

450
450

300

150

450

0
30

150

450

0

(c) M2450(d) M3

0
0 15
15

0 50
0 15 1
15

45
0

45
0

0
45

0
15

400

50
400

50

50

450

50

0
15

0
45

(e) M4(f) M5
Fig 26: Experimental model

45
0

0
45

(g) M6

Besides the maximum (minimum) pressures among all the pressure taps for each wind direction, the structural designers are interested in the maximum (minimum) pressures among all thewind directions for each pressure tap which provide the most unfavorable values at each location.
Maximum positive and minimum negative pressure distributions among all the wind directions for a two-level roof (M1 - see Fig 26) are shown in Fig 27, and results for a simple flat roof
(S1 - see Fig 26) and a three-level roof (M4 - see Fig 26) with two steps with the same totalheights as the two-level roof (M1 - see Fig 26) are also given for comparison.
The smallest negative peak pressure coefficient for the two-level roof was recorded at thecorner of the high-roof section and is comparable in magnitude with that for the simple flat roof.
High suction pressure coefficients were also seen at both the outer and inner corners of the lowroof section, which were a little smaller than those for the high roof section. For the three-levelroof, the smallest negative peak pressure coefficient recorded on the high roof section was alsosimilar to the values for the simple flat roof and the two-level roof. The most unfavourable value
in the corners of the lower two roof sections was smaller than those for the two-level roof.

-5

-3

-6
-4

-2.5

-5

-4

-3

-4 5

-7 - -5
-9 6

-4

-6

-6 -5 -7
-4

-5
-5

-5

-4
-4 5
- -6

-2.5

-7-5

-3.5
-4

-7
-5
- 6 -9-5-9 -6(a) S1(b) M1(c) M4
Fig 27: Minimum pressure distributions among all the wind directions

- -7
-4 5
-5

-5

-5

-3

-9
-3.5
-5 -6
-3.5 -3.5 -4
-3

-6
-4

-3
-2.5

-9.5

-5

-4

-9
-6 -5-4

-6

-4

-6
-10

-6

-4

-4

-1
0

-6

-5
-4 - 4-7-9.5 -5-6-5-6 - 98.3 Aerodynamic characteristics of green roof modules
In order to justify the design of scaled green roof module models for a scaled wind tunnel experiment, this study was carried out to determine the characteristics of wind forces on green roof
modules under uniform steady wind conditions using real green roof modules. The objectives ofthe present study were (a) to investigate the mean drag and uplift coefficients of real green roof
modules in uniform turbulent flows, and (b) (more importantly) to verify the assumption that theeffect of reconfiguration of vegetation on the wind force coefficients of green roof modules islimited. In the experiment, a total of four modules were tested, as shown in Fig 28. M0 (Fig
28(a)) is the original green roof module product of VUS500 with a plastic tray, while M2 (Fig
28(c)) and M3 (Fig 28(d)) are 1/4 part of an original green roof module product of FD-GCU II.
The 1/4 parts were used because of the large weights of the full modules. A square wooden tray
the same height as the original tray was used to contain the 1/4 part of growth media and vegetation. For comparison, M1, 1/4 part of the original green roof module product of VUS500, was also tested (Fig 28(b)). The coverage of the experimental modules was almost 100% and no
growth media or vegetation loss occurred during the experiment.

(a) M0(b) M1(c) M2
Fig 28 Experimental specimen(d) M3

Drag force coefficient which normalizes drag by the frontal area of the module AD2 (including
tray and vegetation), considers the discrepancy in the area of exposed vegetation for each module. Therefore, the discrepancy in the values of CD2 is not due to the absolute amount of vegetation, but to the aerodynamic characteristics of vegetation such as permeability and flexibility. It
is found that the value of CD2 of module M1 is still the smallest of all the tested modules, 0.6,
which is similar to the value of CD1 for the tray. Although the type and exposed area of vegetation are different for M2 and M3 as mentioned above, the values of CD2 of these two modules areboth close to 0.8, which is the largest value among all the tested modules. The value for M0,
which adopts a commercial tray with a different size from the tray for M1~3, is 0.7, which islarger than that for M1, although the types of vegetation for M0 and M1 are the same.
The mean uplift coefficients for each module including the result for the tray plotted in a single point. It is interesting that the discrepancies among uplift force coefficients for all the modules are like a mirror of those depicted in Fig 29(b): the smallest CV value occurs for M2 andMean drag coefficient CD2

1.0
M2
M3
M0
M1

0.8
0.6
container for M1-3

0.4
0.2
0
0.0

0

5
10
15
Mean wind speed (m/s)

20

Mean uplift force coefficient CV

M3, whose CD2 value is the largest; the CV value for M1 is the largest while its CD2 value is thelowest; and M0, whose CD2 value is intermediate, has a CV value between those for M1 and M2,
3.
For comparison with the values for the tray, the M2 and M3 values are smaller while the M1
value is larger, which indicates that although the uplift coefficient for a green roof module withhigh vegetation tends to be smaller than that for a module with a solid square shape, there is also
a possibility that the value for the module with low vegetation exceeds that for a solid module
without vegetation.
The mean uplift coefficients for the modules are between 0.1 and 0.4 in the uniform wind flow
condition. It is expected that, in the rooftop wind field where the uplift wind pressure is significant, the uplift force coefficient for the rooftop module will be higher than the present values.
0.5
0.4
M1
container for M1-3

0.3

M0

0.2

M3
M2

0.1
0
0.0

0

5
10
15
Mean wind speed (m/s)

20(a) Drag force coefficient(b) Uplift force coefficientFig 29: Force coefficient acting on real green module

8.4 Aerodynamic characteristics of green roofing tree system
The goal of this study was to evaluate the effect of wind on aerodynamic characteristics of threedifferent tree species, including drag and overturning moment coefficients, reconfigurations anddeflections. Drag coefficients based on frontal areas in still air and wind-speed-specific frontal
areas were both determined; Overturning moment coefficients based on frontal areas in still air
and aerodynamic centers were provided. Other parameters considered were crown porosity asaffected by crown pruning, turbulence intensity and view angle.
Results of overturning moment coefficients calculated based on frontal area in still air andrelative height of the aerodynamic center are shown in Figs 30 and 31, respectively. The relationships between overturning moment coefficients and wind speeds for the three species weresimilar to the results for drag coefficients.[11](a) Rose of Sharon (HS)Fig 30 Experimental trees(b) Emerald Cedar (TO)(c) Japanese Holly (IC)

0.6
0.5

CM

0.4
0.3
0.2

HS
TO
IC

0.1
0.00
0

2

4

6

8 10
U (m/s)

12

14

16

Fig 31 Variation of mean overturning moment coefficient (CM) with wind speed (U)This study also aimed to identify wind force characteristics of a rooftop model tree installed
on a medium-rise flat-roof building in a simulated boundary layer flow, focusing on the effectsof tree location, wind direction, tree crown shape and parapet height. Wind force measurementson the rooftop model tree were performed using a commercial one-component small-range force
sensor for the uplift force component and a self-constructed strain-gauged force balance for theother five components. Before the experiment under rooftop conditions, 15 trial tree models of
various materials, shapes and crown porosities were tested in the wind speed range from 5 m/s to
10 m/s in a smooth uniform flow. The parameters of the trial model trees were verified by comparing their drag coefficients to those for real trees described in the previous chapter.
Totally 15 trial model trees were fabricated with crowns made of porous foam, land sponge(see Fig 32) and nylon. For the crown material of porous foam and land sponge, different crownshapes were adopted: conical, cylindrical and rectangular prism for porous foam crowns, twoshapes attempting to simulate a coniferous tree (Fig 32a~c) and a ball-shaped evergreen tree (Fig
32d~f) for the land sponge crowns. Three shapes for porous foam crowns were almost regular
geometric, achieved by trimming the foam, while two shapes for land sponge crowns were relatively random. The trunks for the porous foam crowns were the simplest: a stainless bar with ascrew thread at the bottom for connecting to the force measurement equipment, while bendableand paintable, lead-free copper armatures common in model railway scenery accessories neededto added and twisted onto the stainless bar to hold the crown materials for the land sponge andnylon crowns.
About along wind force coefficient shown in Fig.33, for case 1, the model tree was moved
along the windward edge of the roof when wind was normal to the windward surface. The maximum mean and peak force coefficients occurred at the two corners and decreased from the corner to the center of the edge. The maximum mean and positive peak force coefficients were 1.3
and 3.0, respectively. For case 2, the model tree was moved along the central line of the roof
along the wind direction. The maximum mean and peak force coefficients were recorded at thefirst location, which was nearest to the roof edge, and the values gradually decreased with distance between the model tree and the windward edge, changing from 0.1 to 0.4, and then slightly
increased up to the leeward edge.

(a) PA(b) PB(d) SB(e) N1
Fig 32 Model trees for wind force experiment(c) SA(f) Setup of the rooftop model tree

Wind

2

x

L

CFD

1


CFD

CFD

0
-1
0.0

0.2

0.4

0.6

0.8

x/L

1.0

Along-wind lateral force coefficient

Along-wind lateral force coefficient


CFD

3

Wind
x

3


CFD

L

2
1

CFD

CFD

CFD

0
-1
-2
0.0

0.2

0.4

0.6

0.8

1.0

x/L

(a) Case 1(b) Case 2
Fig 33: Along-wind lateral force coefficients on the rooftop model tree at different locations

9 CONTRIBUTIONS OF OVERALL AND LOCAL BEHAVIORS FOR LARGEST WIND
LOAD EFFECTS ON STRUCTURAL MEMBERS

9.1 Introduction of this research topic
In most standards or codes for wind loads (Architectural Institute of Japan, 2004; ASCE7-05,
2005), design wind load is divided into two parts: that on structural frames based on overall
structural behavior and that on components/claddings based on the local behavior of structuralmembers. However, it is impossible to distinguish between the structural frame and components/claddings for Monocoque structures, which support the structural load by using the object’s exterior. Wind loading effects on the exterior walls depend not only on the overall bearing
behavior but also on the local behavior of the shells. Current codes do not provide a means fordetermining the equivalent static wind load aimed at maximum loading effects for members ofsuch structures.
The present work aimed at better understanding of wind loading effects on exterior walls of
Monocoque structures. The internal stresses in the wall members were investigated byconducting time-history analysis using the finite element (FE) method, with special attention to
the largest wind loading effects, including negative and positive peak member stresses. A
method was proposed for estimating the contributions to the largest wind loading effects due tooverall structural behavior.[12]9.2 Wind tunnel experiment9.2.1 Experimental arrangements and proceduresWind tunnel tests were conducted at the Tokyo Polytechnic University in Japan to measure thefluctuating wind pressures. A cylindrical model 0.48m in height and 0.06m in diameter wasused, with 1/250 geometric scale, as shown in Fig 34. 160 wind pressure measurement points
were arranged on the exterior of the model, 16 at each level at 22.5o intervals. The power exponent of the vertical profile of mean wind speed was 0.18. The mean wind speed and the turbu-

lence intensity at the height of the model were 9.9m/s and 11%, respectively. Measured longitudinal mean wind velocity and turbulence intensity profiles are shown in Fig 35.
'

0.0

Turbulence intensity Iu =Uz/Uz
0.1
0.2

1.2

Mean wind speed
Turbulence intensity

1.0
Height z (m)

0.3

11.3(

0.8

z 0.18)zg

Height of the model top

0.6
0.4
0.2
0.0

(a)
(b)
Fig 34. Wind pressure test model: (a) configuration

0

2

4
6
8
10
Mean wind speed Uz (m/s)

1214

Fig 35. Mean wind speed and turbulenceof test model (unit: mm); (b) model in wind tunnel

intensity profiles

9.2.2 Expanding fluctuating wind pressures
Because the locations of the nodes of the FE model did not coincide with those of the pressuretaps on the experimental model, the fluctuating wind pressures at the nodes were simulated byusing a proper orthogonal decomposition (POD) technique. A detailed discussion of this technique is presented in Tamura et al. (1997, 1999), for example. Table 2 gives the results of thenormalized eigenvalues obtained from the POD analysis. The cumulative contribution up to the50th mode is approximately 95%. Therefore, during the following analysis, the wind pressures at
the nodes were simulated for the first 50 eigen-modes.
Mode
1st
2nd
3rd
…
20th
50th

Table 2. Contribution of each mode from POD for Monocoque model
Contribution (%)
Cumulative Contribution
28.21
28.21
8.61
36.82
7.30
44.12
…
…
0.71
85.58
0.16
94.79

9.3 Numerical analysis of wind loading effects
9.3.1 Analytical model
The prototype structure was a steel structure. ANSYS software was used for the FE modelingand analysis. The model was clamped at the bottom end while its top end was free. According to
the geometric scale in the wind tunnel, 1:250, the height and the outside diameter were 120m and
15m, respectively, with a height-to-radius aspect ratio H/R= 16. The shell wall thickness,
t=12mm, was set uniform with height. The mean wind speed at the top (H=120m) was set at
50m/s. The critical damping ratios for the first and second modes were set to 1% to calculate thetwo coefficients for the Raleigh damping equation. In the present study, the effects of aerodynamic damping and stiffness were not considered.
9.3.2 Estimating effects of overall behavior on member stresses
Firstly, the fluctuating wind pressures generated by POD were directly applied to the FEmodel and the dynamic wind load effects due to both overall and local behaviors were obtained.
Then the tip time-history displacements obtained from a 10-lumped mass model system (Fig 37)
under the overall fluctuating wind forces (Fig 36), assumed to represent the overall behavior of
the structure, were applied to the FE model and the load effects were calculated considering only
overall behavior. The effects of the overall behaviors on the member stresses were investigatedby comparisons of the stress results from the above two round time-domain analyses. It was assumed that there was no distortion on the cross sections when only overall behaviors were considered. The horizontal and rotational angular displacements of the lumped-mass system weretransferred to the corresponding displacements of the nodes in the FE model.
1.5

0.8H

a

Cf

1.0
0.5

0.0
200

0.2H
220

240 Time (s) 260

280

300

(a) along-wind
1.0

WIND

0.8H

Cf

0.5 b
0.0

-0.5
-1.0
200

0.2H
220

240

Time (s)260(b) across-wind
Fig 36. Overall wind force coefficients

280

300

Fig 37. FE model and lumped-massmodel system

9.3.3 Results and discussions
In the FE analysis, the global axes x, y, z were consistent with the axes defined earlier in Fig
37. In this case, σz represented the normal stress in the shell structure along the cylindrical axis,
σy represented the stress in the circumferential direction and τyz represented the in-plane shear
stress in the shell structure. The area located at height 0.15H to 0.25H, at angles φ, -50o~50ofrom the windward meridian was chosen for discussion of the stress results. There were a total of
140 shell elements in this area.
The stresses in the elements became smaller when considering the overall behavior only, especially for the circumferential stress component. Because in this case only the bending behaviorof the whole shell wall was considered, the bending moment and shear force were the main internal forces. Thus, the axial and shear stresses were the predominant loading effects when considering only the overall behaviors.
The other two stress components σy and τyz were smaller than the axial normal stress σz. Fig 38
shows the maximum axial tensile stresses and axial compression stresses separately in the orderof the values. It can be clearly seen that considering only the overall behavior will underestimate
the loading effects on the structural members. The effects of the overall behaviors on the member stresses are estimated by calculating the ratio between the largest wind load effects, Rmax, over-all/ Rmax, real and Rmin, overall/ Rmin, real. Here, Rmax, overall and Rmin, overall represent the maximum andminimum stresses under fluctuating wind load considering only overall behaviors for one element; Rmax, real and Rmin, real represent the maximum and minimum stresses under fluctuating windload considering both overall behaviors and local behaviors. The ratios of the maximum axial
normal stresses were about 65%~100%, while the ratios of the minimum axial normal stresses
were about 60%~90%.
72Overall behavior& Local behavior
Overall behavior only

5
4

Overall behavior & Local behavior
Overall behavior only

-1
-2

3

-3

2

-4

1
0

x10

0

Minimum Stress min. z (N/m )2

Maximum Stress max. z (N/m )

7

x10

6

-5

0

30
60
90
120
Order of the Value

150

-6

0

30
60
90
120
Order of the Value

150

Fig 38. Comparison of maximum and minimum axial normal stresses according to order of values

9.4 Conclusion
Time-history displacements based on the overall behaviors and reconstructed fluctuating windpressures were applied on to an FE model of a Monocoque structure. Considering only the overall behavior will underestimate the loading effects on the structural members, especially the circumferential stress component. The effects of the overall behaviors on the member stresses canbe estimated by calculating the ratio between the largest wind load effects. For the elements chosen for discussion, the ratios of maximum axial normal stresses were about 65%~100%, while
the ratios of minimum axial normal stresses were about 60%~90%. The error was more significant when the structural member was near the unfavorable area, where the member stresses werelarger than others.
10 EVALUATION OF AMPLITUDE DEPENDENCY OF DAMPING IN BUILDINGSBASED ON STICK-SLIP CONTACT SURFACE MODEL

10.1 Introduction of this research topic
Damping has been widely thought to increase with amplitude starting from a low-amplitude limit
until a high-amplitude point where the damping starts to plateau. But, such conclusions havebeen made based on experiments under relatively very low amplitudes. Damping appears todecrease instead of plateau with amplitude at the high-amplitude point based on experiments
under relatively higher amplitudes.[13][14]10.2 Method to evaluate the amplitude dependency of damping
This research aims to perform numerical and physical experiments to arrive at generalized
conclusions on characteristics of damping amplitude dependency due to stick-slip surfaces (SSS)
between main structural frames and secondary structural and non-structural elements, and tosome extent, due to soil-structure interaction (SSI).
The numerical experiment first considers a simple 1-degree-of-freedom system with the stickslip contact surface model defined by parameters following a force-displacement relationshipsimilar to an elastic-perfectly-plastic (EPP) material. Cases with one SSS are studied first to
gain a basic understanding of the parameters affecting their individual damping contributions.
Cases with multiple SSS, with parameters of different levels of variability and considering different probability distributions, are studied next. From these numerical experiments, theoreticalexpressions can then be derived.

10.3 Results and discussions
The research work has so far completed analysis of more than 800 cases, a sample result fromwhich is shown in Fig 39, where clearly, the damping due to SSS are shown to decrease withamplitude after a certain point.

Fig 39 Sample theoretical and numerical amplitude-dependency for case with 441 SSS, andcoefficient of variation = 200% and 367% for stiffness and displacement parameters, respecAdditionally, the following general theoretical equation to characterize amplitude-dependent
damping has been derived:s  b 


  d

d
1
2 dc,mean N  k i  c,mean i2  H 1 c,mean i 
 X i1  1 b k0,meani X dc,mean i 
X
X
 


where  are the damping parameters, X is the displacement amplitude, d is the displacement
parameter, k are the stiffness parameters,  and  are distribution parameters, and H is the
Heaviside step function.
11 ESTIMETION OF STIFFNESS OF LOW-RISE STEEL HOUSE

11.1 Introduction of this research topic[14]This research has focused on dynamic properties and stiffness assessment of buildings during
construction. Two three-storey buildings and a one-storey experimental building model have

been built for investigation. Various vibration tests includes the ambient testing, sweep testing,free vibration testing, white noise testing and earthquake excitation testing have been implemented. Amplitudes of excitation and response have been set for relatively small amplitude, medium amplitude and large amplitude levels. Effects of erection cases of buildings, structural andnonstructural components, vibration test and excitation amplitudes on dynamic properties ofbuildings during construction have been studied. Stiffness evaluation of buildings during construction has been investigated. FE models of full-scale three-storey buildings and experimentalbuilding model during their construction have been developed. Output-only and input-output
modal identification techniques have been applied for both ambient vibration data and forced vibration data. Outline of research results are follows: Natural frequencies and damping ratios have been estimated for all full-scale three-storey
buildings and experimental building model.
 Influences of nonstructural and structural components on dynamic properties of threestorey steel building and experimental building model have been investigated.
 3D FE models of full-scale three-storey steel building and experimental building model
during construction have been built up.
 Stiffness evaluation of experimental building during construction has been investigated.

3
Freq u en cy (H z)

2.8
2.6

Damped natural frequency
6

AV
FV(1)
FV(2)
SV(1)
SV(2)
SW(1)
SW(2)

AV
SW(1)
SW(2)

2.4
2.2

FV(2)

5.5

FV(1)

Frequency (Hz)

3.2

SV(2)
SV(1)

2
R1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Erection stages (R1-R23)

5

FS
FM
FL
SS
SM
SL
A1

4.5

A2

4

3.5

3

2.5
DX1 DX2 DX3 DX4 DX5 DX6 DX7 DX8 DX9 DX10 DX11 DX12
Testing cases

Fig 40: Dynamic properties identification and stiffness assessment

Fig 41: Estimated stiffness of secondary member

W15
B10
W30
W60
K60K30 K10
B30
B60

A1
SS
SM
SL
FS
FM
FL
W15
W30
W60
K10
W100
K30
K60
B10
B30
B60
A2

12 AERODYNAMIC CHARACTERISTICS OF VARIOUS CROSS SECTIONAL SHAPETALL BUILDINGS WITH VARIOUS HELICAL ANGLES

12.1 Introduction of this research topic
Tall buildings are particularly prone to dynamic excitations such as those from natural disasters
like strong winds and earthquakes, and this has become an especially important design issue withmanhattanization. One way to minimize wind-induced vibrations of tall buildings is to focus
more on their shapes in the design stage. Tanaka et.al (2012) investigated aerodynamic forces
and wind pressures acting on tall buildings with various unconventional configurations.
Hayashida et.al (1990) studied the effects of building plan shape on aerodynamic forces, anddisplacement responses have been studied for super-high-rise buildings with square andtriangular cross-sections with corner modifications. Kim et.al (2002) discussed aerodynamic
modifications of building shape, such as by changing the cross-section with height throughtapering, which alters the flow pattern around tall buildings, and can reduce wind-induced
excitations. Many researchers have tested wind pressures on buildings with irregular plans(Amin et.al., 2008), with plan shapes that change with height (Harikrishna et.al., 2009), withdifferent rectangular cross-sections (Lin et.al., 2005), and with tapers with taper ratios of 5% and10%, and with set-back at mid-height (Kim et.al., 2010a, 2010b, 2011). However, there havebeen very few studies on the aerodynamic characteristics of triangular-cross-section tallbuildings with various configurations.[15]12.2 Wind tunnel experimentWind tunnel tests were conducted in a boundary layer wind tunnel at the Wind Engineering
Research Center, Tokyo Polytechnic University, Japan. The wind tunnel test section was 19m
long with a cross-section 2.2m wide by 1.8m high. Equilateral triangle models with a side
dimension of 0.076m and a height of 0.4m were used. All the models had the same volume, andStraight Triangle, Corner cut, Clover, 60oHelical, 180oHelical and 360oHelical models were
tested to identify their aerodynamic characteristics. These models are shown in Fig. 42.

H=400(a)Straight(b)Corner(c)Clover(d)60oHelical (e)180oHelical (f)360oHelical
Trianglecut
Fig. 42. Schematic diagram of models (Unit: mm, Volume is same(1х106 mm3))

Fig. 43. shows the variation of mean along-wind OTM coefficient ( C MD ) and mean crosswind
OTM coefficient( C ML ) with wind direction (θ). C MD values decrease and C ML values increaseas helical angle increases. The C MD and C ML values of the Corner cut model follow the same
trend as the Straight Triangle model. The maximum and minimum values of C MD are 0.64 and
0.3 for the Straight Triangle and Corner cut models. The maximum and minimum values of
C ML are 0.45 and -0.45 for the Straight Triangle model. For the 360o Helical model, the C ML
values are around 0.05~0.1 for all wind directions. The C ML and C MD values (around 0.1 and0.4) for all the wind directions are almost constant for the 360oHelical model, as can be seen in
Fig. 43. For the Straight Triangle model, the minimum C MD occurred at 60o wind direction andthe curve is ‘U’-shaped. Torsional moment coefficients are not discussed here in detail as thesevalues were very small compared to the along-wind and crosswind force coefficients. They arealmost 0 for the Straight Triangle, Corner cut and Clover models. The variation of mean dragand mean lift force coefficients were 1.2 and 0 for the Straight Triangle model at 0o wind direction, which is similar to the results of Kanda et.al (1992).
Straight Triangle
Corner cut
Clover1

1

o

60 Helical

0.8

o

0.5

180 Helicalo360 Helical

CMD

CML

0.6

0

0.4

-0.5

0.2
0
0

30

60

90

120

o

Wind Direction ( )(a) Along-wind direction
Fig. 43. Variation of mean OTM coefficients

-1
0

30

60

90

120

o

Wind Direction ( )(b) Crosswind direction

Fig. 44(a) shows the crosswind power spectra, fSCML, for the wind directions at which the maximum peak occurred. The maximum peaks occurred for crosswind spectra at θ=0o, 0o, 15o 45o,
120o and 30o for the Straight Triangle, Corner cut, Clover, 60oHelical, 180oHelical and
360oHelical models. A sharp peak of crosswind spectrum is observed for the Straight Triangle,
Corner cut and Clover models, but the maximum peak is observed for the Clover model. The
sharp peak is reduced drastically for the Helical models as the helical angle increases, indicatingthat the shedding vortices are more disturbed than in the normal condition. As the helical angle
increases, the peak shifts to higher reduced frequency ranges, and also the band width of thespectrum increases. But for the Corner cut and Clover models, the peak appears sharp and shifts
towards slightly higher reduced frequency ranges than the Straight Triangle model.
Fig. 44(b) compares in detail the square root of crosswind power spectra for the design windspeeds corresponding to higher spectral values at a 500-year return period (Up,500) and a 1-year
return period (Up,1). Here, the first natural frequency is assumed to be f1=0.1Hz, and the design
wind speeds are assumed to be Up,500=71m/s and Up,1=30m/s at model height H, respectively,in the Tokyo region. Then, the corresponding spectral values were calculated. The largest values
decreased as the helical angle increased corresponding to Up,500, but the largest value is shownfor the Clover model. For Up,1, the largest values become smaller than those for the Straight
Triangle model. The Corner cut model shows the smallest value of all.

10

0.5

Up,500 Up,1

-1U

Straight Triangle( = 0o)UoCorner cut( = 0 )0.4oClover( = 15 )1060o Helical( = 45o)-2

 SCML,Max

fSCML

10

P,1

180 o Helical( = 120o)
360 o Helical( = 30o)

10

P,500

-3

0.3

0.2

-4

10

0.1

-3

10

-2

fB/UH

10

-1

10

0

0

Straight
Triangle

CornerCut

Clover60o
Helical180o
Helical360o
Helical(a) Power spectral densities(b) Peak spectral values
Fig. 44. Power spectral densities of crosswind OTM coefficients and peak spectral values for 500-year and 1-year
return periods

13 WIND LOAD ESTIMATION OF SOLAR ARRAY

13.1 Introduction of this research topic
The use of solar energy has extensively increased around the globe. It is therefore necessary
to improve understanding of wind loading on solar collectors to ensure proper installation and to
avoid damage by strong wind. In this financial year, three types of wind tunnel test were conducted for the wind loading on solar panel model with different length scale ratio. These experiments are solar panel model placed on the building model to check wind load variation for thechange of building height & width, ground mounted solar panel model placed at different inclination angle & turbulent intensity and wind load reduction experiments by putting different windblockage element.

13.2 Ground mounted solar array
The results on ground mounted solar panel model are shown in the following figures. The
flow of the atmospheric boundary layer in the wind tunnel was interpreted as a geometrical model scale of 1/3.33. The layout of the solar panel model with 15º inclination angle is shown in Fig
45(a) and placed in the wind tunnel is shown in Fig 45(b). The full size was taken as 1m2m andthe model scale was 300mm600mm. A total of 144 equally distributed pressure taps wereplaced on its upper and lower sides. A turbulent flow exposure area was simulated and the velocity scale was taken as 1/3.5. In this test the sampling period was 630 seconds for each sample,
corresponding to 10 minutes in full scale. Mean wind force coefficient on solar panel placed atinclination angles φ = 0º, 5º, 10º, 15º, 30º and 45º for wind direction 0~180º are shown in Fig
45(c). Variation of mean wind force coefficient values at different inclination angle and its comparison with JIS C 8955:2004 are shown in Fig 45(d).

φ(a) Layout of solar panel model(b) Solar panel model placed in the wind tunnel
Max Positive

CF

CF
Min Negative
Wind direction []Inclination angle [](c) Mean wind force coefficient at different(d) Comparison of mean wind force
inclination angle, coefficient with JIS C 8955:2004
Fig 45 Aerodynamic characteristics of ground mounted solar array

13.3 Aerodynamic characteristics of rooftop solar array [16]A series of wind tunnel experiments have been performed to evaluate wind loads on solar
panels on flat roofs, mainly focusing on module forces calculated from area-averaged net pressures on solar modules of a standard size. In order to investigate the module force characteristics
at different locations on the roof, solar array models, which were fabricated with pressure taps
installed as densely as possible, were moved from place to place. Design parameters including
tilt angle and distance between arrays, and building parameters including building depth and parapet height, have also been considered. The results show that unfavorable negative module force
coefficients for single-array cases are much larger than those for multi-array cases; tilt angle anddistance between arrays increase negative module forces; effects of building depth and parapet
height on negative module forces are not obvious; and recommendation values in JIS C 8955
Standard correctly estimate negative mean module force coefficients but not peak values.

140

40

pressure-tappedsolar array model
dummy solar
array modelB

H = 400

50

A

50
h

d

edge of field areawith a setback 0.1B

building model
B=

500

D=

0
50

a. Experimental models
0

0.95

-1

Array A
Array BJIS C 8955
-2

0

15

1.4

30

Tilt angle: (°)

45

Largest negative peak module
force coefficient Cfm

Largest negative mean module
force coefficient Cfm

0Array A
Array BJIS C 8955

-2

2.3
3.4

-4

-6

0

15

30

45

Tilt angle: (°)(a) Mean force coefficient(b) Peak force coefficientFig 46: Effect of tilt angle on largest negative mean and peak module force coefficients

REFERENCE[1] Sabareesh Geetha Rajasekharan, Masahiro Matsui, Yukio Tamura (2012), Characteristics of internal pressuresand net local roof wind forces on a building exposed to a tornado-like vortex, Journal Wind Engineering andIndustrial Aerodynamics, 112, pp.52–57[2].Rei Okada, Masahiro Matsui, Akihito Yoshida, and Yukio Tamura (2011), Damage investigations of recent
tornadoes in Japan and their publication on internet database, Rei Okada a, Masahiro Matsui, Akihito Yoshida,
Yukio Tamura, Proceedings of 13th International Conference on Wind Engineering, CD-Rom, 2011.7[3] Radhika Sudha, Yukio Tamura, Masahiro Matsui (2012), Use of post-storm images for automated tornado-borne
debris path identification using texture-wavelet analysis, Journal Wind Engineering and Industrial
Aerodynamics, 107-108, pp.202–213[4] Yukio Tamura, Masahiro Matsui, L. C. Pagnini, Ryukichi Ishibashi, Akihito Yoshida, Measurement of windinduced response of building using RTK-GPS, Journal of Wind Engineering & Industrial Aerodynamics, Vol.90,
p.1783-1793, 2002.12[5] AS/NZS 1170.2. Structural design actions, part 2: Wind actions”, Australian/New Zealand Standard, 2002.
[6] Architectural Institute of Japan, AIJ Recommendations for Loads on Buildings”, Architectural Institute of Japan,
2004[7] W. Kim, Y. Tamura and A. Yoshida: Study for interference effects on local wind pressures acting on a high-risebuilding, Journal of the Architectural Institute of Korea, Vol. 26, No. 1, pp. 71-78,[8] W. Kim, Y. Tamura and A. Yoshida: Interference effects of an adjacent building on local wind pressure on ahigh-rise building, Journal of the Architectural Institute of Korea, Vol. 26, No. 1, pp. 19-27

[9] V. T. Trung, Y. Tamura, A. Yoshida, Effects of Various Parapets on Wind Loading on Porous Sunshade RoofCover Sheets for a Low-Rise Building, Advances in Structural Engineering, Vol. 14 No. 2 2011.02[10] Jinxin Cao, Yukio Tamura, Akihito Yoshida, Wind pressures on multi-level flat roofs of medium-rise buildings,
Journal of Wind Engineering and Industrial Aerodynamics, 103, pp.1-15, 2012[11] Jinxin Cao, Yukio Tamura, Akihito Yoshida, Wind tunnel study on aerodynamic characteristics of shrubby
specimens of three tree species, Journal of Urban Forestry & Urban Greening, 2012 (Now available in online)[12] Zhibin Ding, Yukio Tamura, Akihito Yoshida, Contribution to member stresses due to overall wind-induced
behaviors of thin-walled cylindrical shell, Journal of Wind Engineering and Industrial Aerodynamics 107-108,
pp.192-201, 2012[13] Ronwaldo E. R. Aquino, Yukio Tamura, On stick-slip phenomenon as primary mechanism behind structural
damping in wind-resistant design application, Journal of Wind Engineering and Industrial Aerodynamics(Accepted for publication)[14] Nakata, S., Le, T.H., Yoshida, A., Kiriyama, S., Naito, S., Tamura, Y. (2011), “Influence of nonstructural andstructural components on dynamic properties of experimental building model on a shaker”, Engineering
Structures (under review)[15] Eswara Kumar Bandi, Yukio Tamura, Akihito Yoshida, Yong Chul Kim, Qing Shan Yang, Experimental
investigation on aerodynamic characteristics of various triangular-section high-rise buildings, Journal of Wind
Engineering and Industrial Aerodynamics (underreview)[16] Jinxin Cao, Akihito Yoshida, Proshit Kumar Saha, Yukio Tamura, Wind loading characteristics of panel
modules in rooftop solar arrays, Journal of Wind Engineering and Industrial Aerodynamics (underreview)