passive monitoring of actual buildings · continuous aging and subsequent structural deterioration...

Passive monitoring of actual buildings

Philippe GuéguenISTerre @ Joseph Fourier University Grenoble

Coll. C. Michel (ETHZ), P. Johnson (LANL), P. Roux (ISTerre), T. Kashima (BRI-Japan), ...Students: A. Mikael (former PhD), M.A. Brossault (PhD), A. Astorza, M. Munoz..

Continuous aging and subsequent structural deterioration of a large number of existing structures

Structural Health Monitoring

Motivation

International Energy Agency (IEA 2001) : “in the absence of changes in policy on nuclear energy, the lifespan of plants is the most determining factor for nuclear power for the next decade".

Risk of collapse of the administrative building center in Nice "certainly unpredictable in time or in terms of probabilities, but there exists a real emergency to evacuate

Condition Based Maintenance

Conditional

Planed

Corrective

Regressive

Let it deteriorate

Let it deteriorate

Repair before

failure - Lessdeterioration

Repair before

failure -D

eterioration elim

ination

Action

Man

agem

ent

effe

ctiv

enes

s

Cost

Motivation

To prevent the total interruption of production activity by anticipating the renovation operations engaged on the basis of the observed structural condition

Seismic crisis management

Motivation

Iervolino et al., Earthq. Spectra, 2014

Progressive damage and change of condition of structures during aftershock sequences

MotivationDesign-related uncertainties in Damageand risk prediction

€

P d > ds( ) A[ ] =121+ erf ln(A) − ln(µ)

σ 2$

% &

'

( )

$

% &

'

( )

Motivation

σ2= σ2IM + σ2EDP + σ2Mod σMod = Building-to-building variability within a building class (e.g variability of building properties and design for a given typology)

- Default of design - Aging or damage changing the model

- Boundary condition - Non linear response

Part 1: Motivation

Part 2: Structural Dynamics

Part 3: Experimental assessment of dynamic parameters

Part 4: Passive imaging of buildings

Part 5: Non-linear seismic response of buildings

Part 6: Natural wandering of the building response

Presentation Outline

F = k.Uk = 3.E.I/L3 for fixed base model

E,I

F=m.Ü

U

L

F [N] ForceU [m] Displacementk [N/m] StiffnessÜ [m/s2] Acceleration

E= Young modulus - MaterialI= Inertia momentum - Geometry/shear resistance

Structural dynamics

FU

U F = k.U U=f(t) ü = f(T,earthq.)

k, ζ =f(E,I,H, boundaries conditions)

Static Dynamic Dynamic Free-oscillations Forced Oscillations

ζ

k

F

üg

Structural dynamicsSingle-Degree-of-Freedom - SDOF

natural frequency

% of critical damping

üg: Seismic ground motion (# seismic regulation)

U ü = f(T,earthq.)

k, ζ =f(E,I,L, boundariesconditions)

ζ

k

Equation of motion - SDOF

Structural dynamics

Frequency response of SDOF (with fo const., varying ζo)

0 5 10 15 20−1

−0.5

0

0.5

1

Ampl

itude

2 %

0 5 10 15 20−1

−0.5

0

0.5

1

5 %

0 5 10 15 20−1

−0.5

0

0.5

1

Times − sec

Ampl

itude

10 %

0 5 10 15 20−1

−0.5

0

0.5

1

Times − sec

20 %

Time response of SDOF (with fo const., varying ζo)

1

100

Frequency ratio

Ampl

ifica

tion

fact

or D

0 %5 %10 %20 %100 %

3dB = A/√2

f2f1

Structural dynamics

Wet spongeFlexible-base building

Dry spongeFixed-base building

Structural dynamics

(k , c )hx hx

(k , c )hxry hxry

(k , c )1 1

m J0 0

m J1 1

(k , c )ry ry

xg x1x0

y

H y

H

a) Chargement harmonique (type séisme) b) Chargement ponctuel (type essai de lâcher)

x1x0

y

H y

F0

φ

φ

F=KUK = kstat (kx+iωcx)

m1 : m1(x1 + x0 +H�y

) + c1x1 + k1x1 = �m1xg

m0 : m0x0 + chx

x0 + khx

x0 + chxry

�y

+ khxry

�y

� c1x1 � k1x1 = �m0xg

J0�y

+ cry

�y

+ kry

�y

+ cryhx

x0 + kryhx

x0 �Hc1x1 �Hk1x1 = 0

Xg=input seismic motionX0=relative motion of m0X1=inertial motion of m1Φ=rocking motion

k1,c1: stifness and damping coefficients of the building (fixed-base)

khx,chx: impedance coefficients for translation kry,cry: impedance coefficients for rockingkhxry,chxry: impedance coefficients for translation/rocking coupling

(k , c )hx hx

(k , c )hxry hxry

(k , c )1 1

m J0 0

m J1 1

(k , c )ry ry

xg x1x0

y

H y

H

a) Chargement harmonique (type séisme) b) Chargement ponctuel (type essai de lâcher)

x1x0

y

H y

F0

φ

φ

Structural dynamics

X(ω)

frequency

β1

β3

β2

S-wave velocity β1< β2< β3

{X} (�) = {�m}Xg(�)�2

[Kt]� [M ]�2

1

e!2=

1

!20

+1

!21

+1

!2✓

1e⇣=

⇣!0

e!

⌘3 1

⇣0+

⇣!1

e!

⌘3 1

⇣1+

⇣!✓

e!

⌘3 1

⇣✓

Stewart and Fenves, 2005

Structural dynamics

u(t) un(t)

ui(t)

u1(t)

mn

kn cn

mi

ki ci

m1

k1 c1

A more realistic representation of real structures is: a multi-degree-of-freedom system MDOF

Equation of motion of MDOF

n floor system has n natural frequencies (eigenvalues) and n associated modeshapes (eigenvectors)

Courtesy G. Hivin UJF

Structural dynamics

Orthogonality of the modes

Structural dynamics

Structural dynamics

Euler-Bernoulli beam (Cantilever or bending beam)

Shear beam

Timoshenko beam

C =EI⇡2

4KSH2

Constant mass and stiffness

@

2u(x, t)

@x

2=

m

KS

@

2u(x, t)

@t

2

EI

@

4u(x, t)

@x

4+m

@

2u(x, t)

@t

2�m

EI

KS

@

4u(x, t)

@x

2@t

2= 0

Boutin et al., Earthq. Engng. Struct. Dyn, 2005

Part 1: Motivation


Part 3: How to we get the dynamic properties ?





Asynchronous shaker at the top of the building.

J. L. ALFORD and G. W. HOUSNERA dynamic test of a four-story reinforced concrete building

Bulletin of the Seismological Society of America, Jan 1953; 43: 7 - 16.

How to we get the dynamic properties ?

Bob Barret web page


Michel et al., SDEE, 2008

Air blast or explosion

Boutin et al., EESD, 2005

Shocks


1906: San Francisco earthquake, California. 1923: Great Kanto earthquake, Japan.

US Intrumentation Programs:Californian Strong Motion Instrumentation Program (1960)National Strong Motion Program (USGS) California Strong Motion Instrumentation Program (CGS)Buildings ~ 225 (1-62 stories high); Code Buildings: instrumented by owner

Hollywood Storage Building:Longest history of recording in U.S. – 80 years. First record in 1933 (So. California earthquake).Factor Building:70 sensors in one building - On-line available data - Continuous recordingsMilikan Library:damaged building after the San Fernando earthquake (1971) + permanent shaker at the top


French Intrumentation Program:French Acceletometric Networks (1995)National Building Array Program (2004) 5 Buildings - low seismicity - low sensibility - continuous recordings - 3 buildings in France - 2 in French west indies including one isolating rubber bearing system - 24 channels + free-field + additional sensors

Instrumentation programs in Taiwan, Romania, Greece, Italy, Turkey ... but data are not available online

Japaneese Intrumentation Programs:Building Research Institute BRIBuilding array from 40’1964 Nigata Earthquake - 2012 Tohoku Earthquake74 buildings (top/bottom + boreholes st)


Celebi, 1998


Dynamic and frequency ranges of the typical sensors overlain on a bandpassed signal amplitude plot

➪ the first were analogue / 12bits digitaltriggered accelerometers. Recordingscontinuously misses moderate strong motion and ambient vibrations

Bradford, PhD thesis 2006

Peterson (1992) Low and High noise model


Input/output modal analysis!Input force is measured!Output force is measured!Output is related to input through an Impulse Response Filter!IRF is independent of the input force

StructureInput signal Output signal

Time domain : Out(t)=I(t)*h(t)+n(t)Frequency domain : H(ω)=Out(ω)/I(ω)


Deconvolution (water-level) Clayton and Wiggins, J. Royal Astr. Soc. 1976

Dynamic and frequency ranges of the typical sensors overlain on a bandpassed signal amplitude plot

➪ the first were analogue / 12bits digitaltriggered accelerometer. Recordingcontinuously misses moderate strong motion and ambient vibrations

➪ 24 bit accelerometer (begining of 90’s) continuoulsy recording can record all ranges of vibration in a structure


Bradford, PhD thesis 2006

City-Hall Grenoble

Daily variations of vibration energy

May, 2009

Output-only modal analysis : Ambient vibrations


!

Low cost but less sensitive.But all types of recordings: torsion, gyroscope, GPS etc...

Courtesy T. Heaton

Micro-Electro-Mechanical Systems

Episensor noise level

Phidgets noise level

Android Phone noise level

101

100

10-1

10-2

10-3

10-4

10-5

10-6

10-7

10-8

10-3 10-2 10-1 100 101 102

Frequency - Hz

Acc

eler

atio

n - m

/s2

M7.5 max

M7.5

M6.5

M5.

5M

4.5

M3.

5 M2.

5

M1.5

M7.5

M6.5M5.5M4.5M3.5

M2.5

M1.5

Near Source - 10kmRegional Source - 100km


Mesure LIDAR des vibrations ambiantes •  Portée de 200 m •  Cartographie bâtiment par tourelle •  Acquisition de 10 min

LIDAR Measurements (optical technology)

Gueguen et al., Bull. Earthq. Engng., 2010Valla et al., ASCE Civil Engng,2014

Spectres de vibration, fréquence dopplerPrincipales fréquences d’intérêt

1.2 km

Long-term monitoring of buildings from one remote reference site: successful measurements up to 5 km!


Part 1: Motivation







Carder D. S. Observed vibration of buildings. Bulletin of the Seismological Society of America 1936; 26:245–277.

0 50 100 150 200 250 300 350 400−2

0

2x 10

−5

Time − secAm

plit

ud

e −

co

un

t

100 110 120 130 140 150 160 170 180 190 200−2

0

2x 10

−5

Time − sec

10−1

100

101

0

0.5

1

1.5

Frequency − Hz

FF

T

Average FFT: 21 windows 8192 pointsFs=200Hz

Belledonne towerIle Verte

Not a new technique:

Output only - Parametric

Passive imaging of buildings

Φ/Φmax

Mode 1 L-Direction

Mode 3 L-DirectionMode 2 L-Direction

# St

orey

# St

orey

0 1 2 3 4 5 6

4 5 6 7

# St

orey

11 12 13 Frequency - HzFrequency - Hz

f1 = 1.9 Hz - f2 = 6.1 Hz - f3 = 11.4 Hz=== > f2 / f1 = 3.2 - f3 / f1 = 6.0

# St

orey

Passive imaging of buildings: Peak-pickingTimoshenko beam

Experimental modelling

Numerical modelling

Michel et al., Earthq. Engng. Struct. Dyn., 2009

Output-only - non-parametric

Passive imaging of buildings: SV decomposition

0.4 1.2 2.0

Passive imaging of buildings: SV decomposition

Time (s)

Hei

ght (

m)

Model

Passive imaging of buildings: SI by deconvolution

V0 =�i,i+1

�

Snieder and Safak, 2006

Time (s)

Hei

ght (

m)

Model

Building testing


H

H

Courtesy of M. Todorovska


Part 1: Motivation







Strain

Dy= 2.10 -3 - 5.10-3

Hazus (US) methods to predict earthquake-based damage:Dy= 2.10 -3 - 5.10-3

Elastic Plastic

Non linear seismic response

IG−EPN building − Colombia M 7.3 earthquakeFr

eque

ncy

(Hz)

0 100 200 300 400 500 600 700 800 9000.5

1

1.5

2

2.5

3

0 100 200 300 400 500 600 700 800 900−5

0

5 x 104

Time (s)

Acce

lera

tion

(cm

/s2)

IG-EPN building - Colombia M 7.3 earthquake

f0

fmin


Clinton et al., BSSA, 2006


BRI Annex building

In collaboration with Pr Kashima BRI Japan


Steel-frame RC Japanese buildings

Tohoku earthquake



Years1998 2001 2004 2007 2009 2012

Freq

uenc

y by

dec

onvo

lutio

n

0.40.60.8

11.21.41.61.8

22.2

-5

-4

-3

-2

-1

0

1

normalized frequency1998 2001 2004 2007 2009 2012

Vs b

y de

conv

olut

ion

100

150

200

250

-5

-4

-3

-2

-1

0

1

Years

log(Max Acc.)

V0

Year1998 2001 2004 2007 2009 2012

Freq

uenc

y by

dec

onvo

lutio

n

0.5

1

1.5

2

Year09/2010 04/2011 10/2011 05/2012 11/2012 06/2013 01/2014Fr

eque

ncy

by d

econ

volu

tion

0.8

1

1.2

1.4

Non linear seismic responseSampling: N=25 events


Years03/2010 09/2010 04/2011 10/2011 05/2012

Freq

uenc

y by

dec

onvo

lutio

n

1.05

1.1

1.15

1.2

1.25

1.3

1.35

1.4

Frequency by deconvolution1 1.2 1.4 1.6 1.8 2

Top

Acce

lera

tion

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45 ×105

7.3

7.31

7.32

7.33

7.34

7.352012

2009

2007

2004

2001

1998

Sampling: N=25 events


Vo[m/s]400 450 500 550 600

Stra

in

10-8

10-7

10-6

Freq 0.50 @ 7.50 Hertz

µ= 504.79 σ= 11.52 σ/µ=2.3%

Vo[m/s]100 120 140 160 180 200 220

Stra

in

10-7

10-6

10-5

10-4

10-3 Freq 0.30 @ 3.00 Hertz

µ= 161.55 σ= 4.76 σ/µ=2.9%

Michel et al., EESD, submitted

Part 1: Motivation





Part 6: Natural wandering and nonlinear elasticity


Filtered signal - 1 hour

Time windows - !

RDT signature

N windows having the same initial condition intial condition found in the signal

0 10 20 30 40 50 60

Am

plit

ud

e -

co

un

ts

Time - s

2

1

0

-1

-2

x 10-5

1+...+ 6+...+N

[500T - 1000T]

Random Decrement Technique RDTstationnary and white noise conditions of ambient vibrationsTo stack a large number of short windows having the same triggering conditionMikael et al., BSSA, 2013

- Band-pass filtering Butterworth (order 4)[f1 - f2] at ΔA > 3dB

- N windows <=> 500-1000 T - 20 minutes- τ= 10T - 5 secondes- Triggering conditions: v(t)=0, u(t)>0

Natural wandering

Mikael et al., BSSA, 2013

Natural wandering: example 1 City Hall Grenoble

Guéguen et al.,SCHM, submitted

OGH1OGH3

OGH4OGH6

OGH2

OGH5

44 m

49 m

13 m

1

e!2=

1

!20

+1

!21

+1

!2✓

Natural wandering: example 1 City Hall Grenoble

Guéguen et al.,SCHM, submitted

ῶ redω black

The Anne Paul’s buildings

Natural wandering: example 2 Anne Paul building

Quasi-static events: environmental loading

L

T

Days07-May09 15-Aug09 23-Nov09 03-Mar10 11-Jun10 19-Sept10 28-Dec10 07-Apr11

2.75

2.70

2.65

2.60

2.55

Freq

uenc

y - H

z

3.38

3.37

3.36

3.35

3.34

Freq

uenc

y - H

z

Δf +/-4% L Δf +/-0.6 T


Summer time

Non-linear elasticity of building response to slow loadingTe

mpe

ratu

re °C

Frequency - Hz

Natural wandering: nonlinear elasticity

Long-term (seasonal) variations - Smoothed with a sliding windows of 120 hours length

Quasi-static events: environmental loading

2.75

2.70

2.65

2.60

2.55

Freq

uenc

y - H

z

Days

07-May09 15-Aug09 23-Nov09 03-Mar10 11-Jun10 19-Sept10 28-Dec10 07-Apr11

2.2

2.0

1.8

1.6

1.4

1.2

1.0

0.8

0.6

Dam

ping - %


Strain = max[Utop

(t)� Ubot

(t)

H]

Factor building (IRIS web service)

Data from Sept. to Dec. 2004

2004/09/28 - Parkfield Earthquake Mw=6.0 200 km far from the building

Top and bottom recordings

Natural wandering: example 3 factor Building (CA)

0.55

0.6

Freq

. [Hz

]

0

4

8

Dam

p. [%

]

02040

Tem

p. [°

C]

050

100

Hum

. [%

]

Oct. 04 Nov. 04 Dec. 040

1632

Days in 2004

Win

d. S

p.

[km

/h]

UCLA Factor building

Meteorological Station: DOWNTOWN L.A./USC CAMPUS

Event 428/11/2004

Event 506/12/2004

Event 331/10/2004

Event 128/09/2004

Event 223/09/2004a)

c)

d)

e)

b)

Dynamic - Event 1 - 2004/09/28 - Parkfield Earthquake Mw=6.0 - R=200 kmStatic - Events 2 to 5 - Elastic variation controlled by atmospheric conditions Clinton et al., BSSA, 2006; Todorovska and Al Rjoub, SDEE, 2006; Todorovska, BSSA, 2009; Mikael et al., BSSA 2013

Guéguen, Johnson, Roux, will be published next decade

Dynamic Event Event 1 Top disp: 2 mm Drift: 3 10-5

Static Event Event 3 Top Disp: 0.5 mm Drift: 4 10 -6

Natural wandering: example 3 factor Building (CA)


Hazus : Yield capacity Dy=2.10 -3 - 5.10-3

Nonlinear elasticity at Factor building compared to laboratory scale resultsNatural wandering: example 3 factor Building (CA)

Modified fromJohnson and Sutin , JASA 2005


Hazus : Yield capacity Dy=2.10 -3 - 5.10-3

−0.1 −0.05 0

10−7

10−6

10−5

10−4

∆f/fapp

∆/H

0 2 4 6

10−7

10−6

10−5

10−4

∆ζ/ζapp

∆/H

0 2 4 6x 10−3∆ζ/ζapp

−10 −5 0x 10−3∆f/fapp

Event1Event2Event3Event4Event5

PySPAMQG

a) b) c) d)

Natural wandering: example 3 factor Building (CA)Nonlinear elasticity at Factor building compared to laboratory scale results

Mod

ified

from

John

son

and

Sut

in ,

JAS

A 20

05


Conclusions

Building testing thanks to new instrumentation

- physical origin of frequencies and damping in actual buildings- for SHM and CBM

NL elasticity and slow dynamic

- probing the invariant scale of NL elasticity (laboratory mm Johnson, building m, earth km Brenguier)

- related to the structural health

Philippe Guéguen ISTerre/[email protected]

mailto:[email protected]

mailto:[email protected]

passive monitoring of actual buildings · continuous aging and subsequent structural deterioration...

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