6TH INTERNATIONAL CONFERENCE ON DAM ENGINEERING C.Pina, E.Portela, J.Gomes (ed.)

Lisbon, Portugal, February 15-17, 2011

1

LONG-TERM DYNAMIC MONITORING SYSTEMS FOR THE SAFETY CONTROL OF LARGE CONCRETE DAMS. THE CASE OF

CABRIL DAM, PORTUGAL

S. Oliveira* , P. Mendes†, A. Garrett ‡, O. Costakkkk, J. Reiskkkk

* Laboratório Nacional de Engenharia Civil (LNEC) Av. Brasil 101,1700-066 Lisboa, Portugal

Keywords: Dynamic monitoring systems for dams, finite element models, modal identification, evolutionary deterioration, ambient and seismic monitoring, state space formulations, non-stationary vibration modes

Abstract. In the scope of LNEC investigations on safety control methodologies for concrete dams, a long-term dynamic monitoring system was recently installed in Cabril dam. The collected data (acceleration records) is automatically processed using modal identification techniques, in order to obtain experimental information about the evolution of natural frequencies, modal damping, and mode shapes (stationary or non-stationary modes). It is emphasized that this information can be used: i) as complementary information about the evolution of dam deterioration gathered from other monitoring equipment; ii) for detection of structural behaviour changes related to reservoir level variations, thermal effect, and deterioration - for example, cracking evolution can occur due to evolutionary processes like swelling, or to exceptional events like earthquakes, that are also recorded; and iii) for calibration/validation of finite element models in order to improve the assessment of the dam structural integrity. In modelling the dam dynamic behaviour there are some important hypothesis related with the simulation of water-structure interaction and damping effects that remain under investigation due to the present lack of experimental reliable data, which is expected to be covered with this type of long-term dynamic monitoring systems.

1 INTRODUCTION

In dam monitoring, the automatic data acquisition systems (ADAS) can be used not only for measuring the dam response to static loads but also for the continuous long-term dynamic monitoring1,2. With these systems, the collected data (acceleration records at high sampling rates ~50Hz) is automatically analyzed using modal identification techniques3,4,5 (considering time periods of about one hour long). Then, the time evolution of the identified modal parameters (natural frequencies, mode shapes and modal damping) can be compared with numerical results from finite element models6 and/or discrete element models7 (figure 1). † Instituto Superior de Engenharia de Lisboa (ISEL) ‡ Laboratório Nacional de Engenharia Civil (LNEC)

S. Oliveira, P. Mendes, A. Garrett, O. Costa and J. Reis

2

The use of ADAS for long-term dynamic monitoring of large dams is the best way to get useful experimental information to: i) study the evolution of the main modal parameters; ii) gather information about the correlation between changes in the modal parameters and structural changes due to deterioration processes8; iii) measure the dynamic dam response under ambient excitation and under seismic loads, iv) study the influence of the reservoir on the structural dynamic behaviour of the dam-foundation-reservoir system.

STUDY OF THE DYNAMIC BEHAVIOUR OF DAM-RESERVOIR-FOUNDATION SYSTEMS

Monitoring and modal identification

Numerical results from FE models

Figure 1: Integrated use of dynamic monitoring data, modal identification methodologies (in frequency FDD and in time domain SSI-COV3), and numerical results from FE models with different hypothesis for

simulating the hydrodynamic pressure and the damping.

2 MODELLING THE DYNAMIC BEHAVIOUR OF CONCRETE DAMS

The effectiveness of ADAS for the continuous monitoring of dam dynamic behaviour depends not only on the hardware components reliability (which is fundamental to ensure the quality of collected data) but also depends greatly on the potentialities of the software used for the automatic data analysis.

So, it is fundamental to develop software for data analysis automation that allows generating and/or updating, each hour, synthetic information under graph form to be used by engineers and other technicians from the staff responsible for the dam safety control. With that graph information, it should be easy to analyze the evolution in the main parameters and variables that characterize the dam dynamic response: modal parameters, water level, maximum accelerations, acceleration spectra, etc.

This software should include computational modules that make it possible to detect special events (earthquakes, civil works nearby the dam site, hydraulic discharges, etc.) and to detect abnormal structural changes through comparison between the dynamic monitored response (analysed by modal identification) and the dam response predicted by numerical modelling (FE/DE) and by means of statistical models for effects separation.

In the development of the above mentioned software, the used models/formula-tions/algorithms/interfaces should be specifically adapted to the simulation and analysis of the dynamic behaviour of dam-foundation-reservoir systems (figure 2). In particular, the used models should make it possible to analyse the observed dynamic behaviour by taking into account the water level variations, the temperature variations and the time effects, which can be related to deterioration processes (i.e. progressive cracking due to swelling reactions or induced by exceptional actions like floods or earthquakes).

tMean value

Wave 1Wave 2

Wave 3Wave 4

Wave 5Wave 6

Wave 7Wave 8

Wave 9Wave 10

Wave 11

a(t)

SPECTRALANALYSIS

S. Oliveira, P. Mendes, A. Garrett, O. Costa and J. Reis

3

Figure 2: Modelling and measuring the dynamic behaviour of concrete dams. Mathematical formulations

using the state matrix for developing finite element models and modal identification methodologies.

Problem statement. Linear elastic approach

Numerical solution (FEM)

1 Step. Spatial integration

2 Step. Time integration

L(DLu) ++++ f = 0~ ~ ~ T

(Lu) D (Lϕ) dV = f ϕ , ϕ~ ~V ~D

∋

~

Integral form or weak form

V

T

~

FLVCDifferential form or strong form

, em V

u =~ f~.(t) (t)u

~

.(t).

m_ + c_ u~(t)k_+ G

Equilibrium of energy to be verified in all the volume: VWP Equilibrium of forces at a point

Green-GaussTheoremInitial and boundary contitions

Initial and boundary contitions

Initial conditions

Form that is used in FEM

System of N differential 2 order eq. System of 2N of 1 order differential equations.

u~

.(t)

v~

.(t)

= u~(t)

v~(t)

0_ I_k_m_-1- c_m_-1-

+

m_-10_ f

~(t)G

Initial conditions

The time integration can be performed using modal or structural coordinates. Generally the time isdiscretized in equal time steps t = k ∆t and recursive solutions are derived.

DF DF

VeV Σ= Ve The displacement field and the test func-

tions (or virtual displac.) are approachedby interpolation, and .For each FE we obtain:

N ue~

c_m_

k_

= =

=

e e

e

c_m_

k_= =

=

c_m_

k_

e e

e

Σ ΣΣ f~G =

eΣ f~ef~ =

VemN N dV

T

VecN N dV

T

VeB D B dV

T m_e aeS~(seismic action)

Elasticity matrix (isotropic material)

E 3(1-2ν) K =v

E 2(1+ν) G =

D=

0K G43v

G

GG

0

∂∂x 0 0

0 ∂∂x 0

0 0 ∂∂x0

∂∂x∂

∂x

∂∂x

∂∂x

0

∂∂x∂

∂x0

L=

Differential operator

1

2

3

3 2

2

3 1

1

u~

ε=Lu~~σ=Dε~ ~Lσ+f=0

~ ~~ T

aS~tT0

Compatibility

Constitutive equation

Equilibrium

f~

= mg -m (u+a ) - c u~.. .

~~ s~

ϕ~ u~

Classical representation (in displacements) Representation in the state space (in displacements u and velocities v )

ConcreteE = 30b

b

Water

G = 0

K v= 2 GPa

Rock massE =R Eb

~

νR=~ νb

m =2,4b

cbton/m3

GPa

m =1a ca

ton/m3

mR cR

sim.

00

K G43v

K G43v

K G23v

K G23vK G23v

σ~

σ11σ22σ33σ23σ31σ12

=

ε~ε11ε22ε33ε23ε31ε12

222

=

=

x1x2

x3

u~=uuu

1

2

3

x1( x2 x t3 ), , ,

x1( x2 x t3 ), , ,

x1( x2 x t3 ), , ,

Initial conditions

x =~ A_x~ +B_ f~.(t)

(mck) (ms)

(t) (t)G

STATE FORMULATION IN A FE MODEL PERSPECTIVE

~~

STATE FORMULATION IN A MODAL IDENTIFICATION PERSPEC TIVE (TIME DOMAIN)

y =~ C_ x~ + D_ f~(t) (t) (t)x =~ A_x~ +B_ f~.(t)

(mck) (ms)

(t) (t) x =~ A_ x~ + B_ f~y =~

C_ x~ + D_ f~A_

(mck)A_ e=t∆ B_= A_( - I )A B_ _ _

(mck) (ms)

From the eigen values (complex) λ -ξ ω iω 1-ξ of the state matrix we can obtain the natural frequenciesω λ and the modal damping ξ -Re(λ )/ω . The vibration modes are given by the corresponding eigen vectors withcomplex components, that can describe non-stationary vibration modes.

Formulation based in the dynamic'sequation and in the equation of observation

A_(mck)

A_ E.V.P µ λ = ln(µ ) t∆, ,being V C_ = _ _( )On n O

φφ(n n)

,

- n. of hist. of applied forcesN - n. of degrees of freedom - n. of measurements

O

( = 3)In ( = 4)n

In

On DF

( 2N )GLO

n ( )On In

n 2NGL

( 1)On

If c_ α m_ + β k_ the systemis said to be non-classically dampedand the vibration modes arenon-stationary (with complexcomponents)

(N 1)DF

x~ (2N 1)DF

state vector

state matrix(2N 2N )

GL GL

n

2

n n n n

n n n n n

(6 6) (6 3)

Model order Recursive solution: Discrete time model

The matrix A is identified by adjustment of the discrete timemodel parameters to the observed time series or to thecorresponding matrix of correlation functions [Juang 1994]

_

(3 1)

(6 1)

(6 1)

(3 1)

x =~ A_xk~ +wk~y =~

C_ x~ +~νStocastic input wDeterministic input f~

y~

(t) seriesmeasured k

k+1 k+1k k

k k k k k

k

t

Seismic action

Ambientand operational excitation

n n~ n n(n n)

B = L N [Zienkiewicz 1967]

[Chen; Saleeb 1994]

[Veletsos; Ventura 1986]

ν = 0,2

Contractionjoints

k ~

DYNAMIC BEHAVIOUR OF DAM-RESERVOIR-FOUNDATION SYSTEMS

st

nd

Nϕ~=eϕ

~

stnd

k

S. Oliveira, P. Mendes, A. Garrett, O. Costa and J. Reis

4

For choosing adequate models/hypothesis to be used in the software development for supporting ADAS for dam dynamic monitoring, one important feature that should be take into account refers to the fact that these structures can present non-stationary vibration modes9 which, as is well known, cannot be simulated using simple elastic models based on the hypothesis of classical damping of Rayleigh type (proportional to the global mass and/or stiffness). This hypothesis of classical damping is generally used as a good approximation in civil engineering structures with no dynamic water-structure interaction phenomena.

In order to take into account the existence of non-stationary vibration modes, the models used should enable the consideration of the generalized damping hypothesis (non-classical damping that means non proportional to the mass and stiffness). Among these models, the simplest ones can be formulated using state formulations as indicated in figure 2, in which a distinction was made between the finite element model perspective and the modal identification perspective.

Figure 2 emphasizes the interest of the state space formulations in structural dynamics. Using the state matrix, the natural frequencies, modal damping and modal configurations can be easily computed throughout its eigenvalues and eigenvectors.

For generalized damping, the eigenvalues nλ of the state matrix are complex numbers as well as the j components of the corresponding eigenvectors jnφ . Physically, these complex values correspond to the existence of the previously mentioned non-stationary modes that are graphically represented in figure 3. So, for the generalized damping hypothesis, we can say that for a given mode n, the vibration at each DOF j is described by an harmonic decreasing wave (fig.3), which is completely defined by four parameters that can be “extracted” from the complex value nλ and from the complex modal componentjnφ : i) natural frequency

n nω = λ ; ii) modal damping, ( )n n nRe /ξ = − λ ω ; iii) amplitude jnφ ; and iv) phase angle ( )jn jnatan Im( ) / Re( )φ φ .

Figure 3: Concept of non-stationary vibration modes (usually measured on arch dams). Physical meaning

of the complex components of the state matrix eigenvectors.

STATIONARY VIBRATION MODE (classical damping)

NON-STATIONARY VIBRATION MODE (generalized damping)

t

t

1 2

1 2

Synchronized waves

Non synchronized waves

Modal oscillation at points 1 and 2

The waves that represent the modal oscillation at the various locations are synchronized(in phase or in opposite phase)

The waves that represent the modal oscillation at the various locations are not synchronized. Themathematical description of this non synchronized waves requires the computation of modal vectoreswith complex components (eigenvectores of the state matrix assembled for generalized damping)

Modal oscillation at points 1 and 2

S. Oliveira

2. CABRIL DAM

Cabril dam (4a) is a double curvature arch dam tallest in Portugal), founded on a granitic rock masspresents a higher thickness at the crest. The dam was built

Early, during the first filling of the reservodownstream face was detectedthe crest. In 1981, after analyzing the structural behaviorepairs10 consisting of the treatment of cracks with injections of rthe reservoir, we observed that the cracking in 1996, as well asobservation data and numerical resultsbehaviour, which can be simulated using a viscoelastic model with damageprocess has been recently detected

Figure 4: a) View of Cabril dam; b) Plan. c) Cracking at

displacements at the central

3 CONTINUOUS DYNAMIC M

The continuous dynamic monitoring system of Cabrilplanned, by taking into account: i) the observation data obtained during the dam observation along its lifetime; ii) experimental information from several forced vibration tests and ambient vibration tests 3; and iiielement models used for studying the dam dynamic behaviournumber and location of the sensors (uniaxial accelerometers)main configuration parameters in order to capable of measuring continuously and accurately the dam response to the several actions: ambient excitation, operational excitation and seismic actions of different magnitudes.The system is composed by 16 uniaxial accelerometersthe crest gallery and 7 at the gallery under the cracked zone, as shown in figure 5)were calibrated for measuringgeneration). Three (3) triaxial accelerometersmeasuring high amplitude vibrations (due to seismic actions for example)located near the rock mass for measuring seismic accelerations (at the top of the drainage

A B C ED F IHG J KII D ID

a)

c)

S. Oliveira, P. Mendes, A. Garrett, O. Costa and J. Reis

5

a) is a double curvature arch dam with a maximum height of 132 m (the founded on a granitic rock mass. It is approximately symmetric

at the crest. The dam was built in 1953 on Zêzere riverthe first filling of the reservoir, a significant horizontal cracking at thewas detected, which was located in a range between 10 m and 20 m below

the crest. In 1981, after analyzing the structural behaviour, a decision was made treatment of cracks with injections of resin. With the refilling of that the cracks occured again in the same area. Figure 4

s well as the deformation of the central cantilever (full reservoir) bservation data and numerical results - showing the cracking influence on the structural dam

which can be simulated using a viscoelastic model with damageprocess has been recently detected10.

4: a) View of Cabril dam; b) Plan. c) Cracking at downstream face 199610

;

displacements at the central cantilever10

.

CONTINUOUS DYNAMIC M ONITORING SYSTEM

The continuous dynamic monitoring system of Cabril dam (in operation since late 2008) was taking into account: i) the observation data obtained during the dam observation

along its lifetime; ii) experimental information from several forced vibration tests and ; and iii) numerical data from different finite element and discrete

element models used for studying the dam dynamic behaviour7. From this informationnumber and location of the sensors (uniaxial accelerometers) was defined, as well as their

n parameters in order to obtain a system with a high dynamic range, measuring continuously and accurately the dam response to the several actions:

ambient excitation, operational excitation and seismic actions of different magnitudes.is composed by 16 uniaxial accelerometers oriented in the radial direction (9 at

the crest gallery and 7 at the gallery under the cracked zone, as shown in figure 5)for measuring low intensity vibrations (induced by the wind or due to power

triaxial accelerometers were also used, which werehigh amplitude vibrations (due to seismic actions for example)

he rock mass for measuring seismic accelerations (at the top of the drainage

NLK M PO Q VTR S U III EE

200

180

1710

260

240

220

297

280

-20-10

m

Linear viscoelastic

Downstream displacement

b)

d)

with a maximum height of 132 m (the pproximately symmetric and

in 1953 on Zêzere river. gnificant horizontal cracking at the

located in a range between 10 m and 20 m below , a decision was made to carry out

. With the refilling of again in the same area. Figure 4 presents

the deformation of the central cantilever (full reservoir) - showing the cracking influence on the structural dam

which can be simulated using a viscoelastic model with damage10. A swelling

; d) Analysis of the

dam (in operation since late 2008) was taking into account: i) the observation data obtained during the dam observation

along its lifetime; ii) experimental information from several forced vibration tests and ) numerical data from different finite element and discrete

. From this information, the was defined, as well as their

a system with a high dynamic range, measuring continuously and accurately the dam response to the several actions:

ambient excitation, operational excitation and seismic actions of different magnitudes. oriented in the radial direction (9 at

the crest gallery and 7 at the gallery under the cracked zone, as shown in figure 5), which low intensity vibrations (induced by the wind or due to power

were also used, which were calibrated for high amplitude vibrations (due to seismic actions for example): two of them are

he rock mass for measuring seismic accelerations (at the top of the drainage

-20 mm -50-40-30 -60

Observation dataStatistical separation

Viscoelastic modelwith damage

ModelLinear viscoelastic

Downstream displacement

effects model

d)

S. Oliveira, P. Mendes, A. Garrett, O. Costa and J. Reis

6

galleries) and the third was located at the centre of the crest gallery, where maximum acceleration values are expected. With these maximum acceleration values the dynamic amplification coefficient can be computed (by comparison with the maximum accelerations measured at the rock foundation).

Figure 5: Cabril dam. Main components of the continuous dynamic monitoring system2.

The accelerometers are linked to a modular system composed by units for acquisition and digitalization, which are controlled by 4 data concentrators (figure 5) that fetch the data from the digitalization units, store it locally and, as soon as receives the demand send the data to the computer through an optical fibre local net (LAN) (figure 5). The synchronization of the data concentrators as well as the procedures to start and recover from abnormal conditions is performed by an application, named Cabril Aquis, running in the computer located at the dam power station. In this place all the data is collected, stored and processed continuously using automatic modal identification procedures: for storing the main natural frequencies, mode shapes (amplitude and phase at each measuring point) and modal damping. For the communication between the data concentrators and the acquisition units we used RS485 copper nets (with a maximum of four RS485 in each data concentrator). When the distance is too long (f. ex. connection to the triaxial accelerometers near the rock foundation) we use an optical fibre link to extend the RS485 net. The redundant time synchronization of the data collected by the different concentrators is ensured by an electronic device developed at CIC/LNEC. This device send the time pace and the sync signals multiplexed over the same fibre and is designed to ensure flowing of the sync data in both directions. There are many other important components that are located in boxes near the accelerometers (see figure 5): i) Electronic gain circuits for amplifica-tion of the measured signals; ii) Electrical-optical signal convertors; iii) Supply devi-ces; iv) Batteries. As figure 5 shows the system can be accessed remotely via internet (using a virtual private network - VPN) from the analysis centre located at LNEC, in Lisbon. The data collection automation is a key operation in these monitoring systems. The data packages at the concentrators are sent, continuously, to the computer at the dam site where

Controlcenter (dam)

VPN

AnalysiscenterLNECInternet

S. Oliveira, P. Mendes, A. Garrett, O. Costa and J. Reis

7

are stored under a binary file format. These binary data files (one for each data concentrator) are “closed” at the end of each hour11. The original stored data - the measured acceleration time series - should be automatically analyzed in order extract and store the main modal parameters of the dam and in order to detect special events as is the case of earthquakes. For the purpose the following was developed: i) Computational modules for automatic modal identification using formulations in the frequency domain and in the time domain3,4,5; ii) Statistical models for effect separation10 for the analysis of the evolution in the main natural frequencies; iii) Finite element models for numerical computation of the main modal parameters6,7 . Figure 6 presents some interfaces of the computational modules that are developed for supporting the monitoring data analysis. Figure 6a shows the time evolution of the 1st natural frequency (values identified automatically and an approximation curve from a statistical model of effect separation) and the corresponding evolution in the water level. Figure 6b shows a comparison between the numerical 1st mode shape and the corresponding mode shape identified from the acceleration time series measured for one hour.

Figure 6: Program interfaces

2: a) Evolution in the 1st natural frequency; b) 1st mode shape: numerical and

experimental results; c) Sousel earthquake information and accelerations measured at the top of Cabril dam central cantilever during this earthquake.

4. LONG-TERM DYNAMIC MONITORING OF CABRIL DAM Figure 7 presents the main four vibration modes identified with the SSI-COV method3,7 using the acceleration records measured with the system on 1st September 2009 (10:00-11:00 UTC) with the water level at 279.2 m and the power groups in operation. As can be seen, for these excitation conditions, with the power groups on, the identified vibration modes reveal non-stationary characteristics. It should be noticed that for a lower amplitude excitation, modal configurations were identified, which are nearly stationary. This may be understood by considering the hypothesis that the global damping for low vibration amplitudes is of the type “classical damping” 9 (proportional to the mass and/or stiffness) and that for high amplitudes is of the type “generalized damping” (non-proportional). Figure 8 presents the evolution in the main natural frequencies of Cabril dam (four), identified between Nov-2008 and Oct-2009. The adjusted curves for each modal frequency

a) b)

c)

S. Oliveira, P. Mendes, A. Garrett, O. Costa and J. Reis

8

evolution are obtained through a multiple linear regression for adjusting the parameters of a statistical model of effect separation (see figure 9), which considers the three usual variables: water level h, day of the year t (annual thermal effect) and time t, measured on the basis of a reference date (usually at the end of construction).

1st Mode

λ = -0,275 + 15,782 i

f = 2,52 Hz ξ= 1,62 %

2nd Mode

λ = -0,166 + 16,557 i

f = 2,64 Hz ξ= 1,15 %

3rd Mode

λ = -1,133 + 23,476 i

f = 3,77 Hz ξ= 4,71 %

4thMode

λ = -0,447 + 27,046 i

f = 4,28 Hz ξ= 1,17 %

Figure 7: Identified vibration modes using the SSI-COV method (1st Sep.2009 (10:00–11:00 UTC) – water level 279.2 m. Time oscillation at three measuring points at the crest gallery and modal configuration (crest plan) for a chosen instant (vertical line in the temporal representation). Comparison with numerical results.

-0,004

-0,003

-0,002

-0,001

0

0,001

0,002

0,003

0,004

0 0,2 0,4 0,6 0,8 1 1,2 1,4 1,6 1,8 2

Am

pliru

de

t (s)

-0,01

-0,005

0

0,005

0,01

0 0,2 0,4 0,6 0,8 1 1,2 1,4 1,6 1,8 2

Am

plir

ude

t (s)

-0,004

-0,003

-0,002

-0,001

0

0,001

0,002

0,003

0,004

0 0,2 0,4 0,6 0,8 1 1,2 1,4 1,6 1,8 2

Am

plir

ude

t (s)

-0,006

-0,004

-0,002

0

0,002

0,004

0,006

0 0,2 0,4 0,6 0,8 1 1,2 1,4 1,6 1,8 2

Am

plir

ude

t (s)

2.51 Hz

2.68 Hz

3,89 Hz

4,58 Hz

Spectrum (FDD) and Stabilization

diagram (SSI-COV)

Power generation frequency

peak

S. Oliveira

The effect separation is explicitly represented in figure 8effect on the natural frequencies variation is nearly the only one that counts: the annual thermal effect is almost negligiblefor long periods (decades long) the timay be used as an indicator of evolutionary deterioration. The negligible decrease identified in the time effect of the fourth mode frequency (cracking) is presented with a view to showthe deterioration effects with the possible time decrease

a)

b)

Figure 8: Evolution of the main natural frequencies of Cabril dam. a) Water level variation; b) Identified natural frequencies from Nov-2008 to Octseparation.

5. CONCLUSIONS This work has shown that the

term dam dynamic continuous monitoringdynamic response for ambient aneffectiveness of these systems greatly depends on the software used to support the automatic analysis of all the data that is continuousupporting the automation procedures should (with sophisticated graph capabilities), management and storage, accordingto distinguish special events like earthquakes; iii) data analysis using different modal identification techniques (FDD, SSItools to generate graph representations of spev) emailing to pre-defined internet addresses (dam safety control staff), graphic files (.dxf) with useful information about evolution alerts if some special events are modes that are usually identified in dams and the interest their study was emphasizedidentification perspective.

265

270

275

280

285

Nív

el d

a a

lbuf

eira

(m)

S. Oliveira, P. Mendes, A. Garrett, O. Costa and J. Reis

9

The effect separation is explicitly represented in figure 8, where it can be seen that the water effect on the natural frequencies variation is nearly the only one that counts: the annual

negligible as well as the time effect. However, it can be noticed that for long periods (decades long) the time effects on the frequencies may be not negligible and may be used as an indicator of evolutionary deterioration. The negligible decrease identified n the time effect of the fourth mode frequency (which is a mode related with the horizontal

with a view to show the potential of this type of analysis for correlatthe deterioration effects with the possible time decrease in the natural frequencies

volution of the main natural frequencies of Cabril dam. a) Water level variation; b) Identified natural

2008 to Oct-2009 and corresponding adjusted curves of a statistical

that the recent technologies enable the use of ADAS for longterm dam dynamic continuous monitoring. These systems make it possible to measuredynamic response for ambient and operational excitation and for seismic excitation. The effectiveness of these systems greatly depends on the software used to support the automatic analysis of all the data that is continuously collected. This software for

the automation procedures should consist of several computational modules (with sophisticated graph capabilities), in particular for: i) data acquisition; ii) data management and storage, according to basic procedures for maximum to distinguish special events like earthquakes; iii) data analysis using different modal identification techniques (FDD, SSI-COV, etc.); iv) comparison with FE models

graph representations of spectral information and vibration mode shapes; defined internet addresses (dam safety control staff), graphic files

(.dxf) with useful information about evolution in the main modal parameters and emailing alerts if some special events are detected. Reference was made to the nonmodes that are usually identified in dams and the interest in using state formulations for

was emphasized, both in the FE model perspective and in the

Nível albufeira

4th Mode

3rd Mode

2nd Mode

1st Mode

Water level evolution

it can be seen that the water effect on the natural frequencies variation is nearly the only one that counts: the annual

it can be noticed that me effects on the frequencies may be not negligible and

may be used as an indicator of evolutionary deterioration. The negligible decrease identified is a mode related with the horizontal

the potential of this type of analysis for correlating the natural frequencies identified.

volution of the main natural frequencies of Cabril dam. a) Water level variation; b) Identified natural a statistical model of effect

the use of ADAS for long-make it possible to measure the

operational excitation and for seismic excitation. The effectiveness of these systems greatly depends on the software used to support the

sly collected. This software for several computational modules

for: i) data acquisition; ii) data detection in order

to distinguish special events like earthquakes; iii) data analysis using different modal COV, etc.); iv) comparison with FE models using

ctral information and vibration mode shapes; defined internet addresses (dam safety control staff), graphic files

the main modal parameters and emailing eference was made to the non-stationary

using state formulations for and in the modal

Natural frequencies identified automatically using the FDD modal identification technique

S. Oliveira

EFFECT

Natural frequency : f (h, t , t) a h a h a h a h b cos b si

Figure 9: Application of a statistical model for effect separation to the analysis of the main natural frequencies of Cabril dam identified between Novfrom a simple FE model - linear elastic behaviour, Westergaard associated water masses and classical damping); b) Thermal effect due to the annual air temperature wave; c) Time effect.

ACKNOWLEDGMENTS The authors would like to thank EDP

6 REFERENCES [1] Oliveira,S. (2002) “Continuous monitoring system for the dynamic performance assessment of

arch dams. Sub-programme D”, in Safety control over time”. Nat. Sci. Re

[2] Mendes,P. (2010) “Observação e análise do comportamento dinâmico de barragens dePhD Thesis, FEUP, Porto.

[3] Peeters,B. (2000) “System identification and damage detection in civil engineering”. PhD Thesis, Univ. Loivana, Belgium.

[4] Juang,J.; Phang,M. (2001) “Identification and Control of Mechanical Systems”.Camb.Univ.Press.[5] Rodrigues, J. (2004) “Identificação Modal Estocás

estruturas de engenharia civil[6] Oliveira,S.; Rodrigues,J.; Mendes,

tamento dinâmico de barragens de betão”, VII Cong. App.[7] Lemos,J.; Oliveira,S.; Mendes,P. (2008) “Analysis of the dynamic behaviour of Cabril dam

considering the influence of contraction joints”. EURODYN2008, Southampton, England.[8] Oliveira,S.;Ferreira,I.;Berberan,A.;Mendes,P.;Boavida,J.;Baptista,B.(2010)“Monitoring the struc

tural integrity of large concrete dams. The case of Cabril dam, Portugal”. Hydro2010, Lisbon.[9] Veletsos,A.; Ventura, C. (1986) “Modal analysis of non

Earthquake Engineering and Structural Dynamics, Ed. John Wiley & Sons, vol.14, p.217[10] Oliveira,S. (2000) “Modelos para análise do comportamento de barragens de betão considerando

a fissuração e os efeitos do tempo. Formulações de dano”. [11] Reis,J., Oliveira Costa,C. (200

NSE, LNEC, Lisboa.

S. Oliveira, P. Mendes, A. Garrett, O. Costa and J. Reis

10

4 3 21 2 3 4 1 2

water effectTh

EFFECT SEPARATION MODEL (Multiple linear regression)

2 t 2 tNatural frequency : f (h, t , t) a h a h a h a h b cos b sin

365 365

π π = + + + + +

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ermal effect�������������

of a statistical model for effect separation to the analysis of the main natural frequencies Nov-2008 and Oct-2009: a) Water effect (comparison with numerical results

linear elastic behaviour, Westergaard associated water masses and classical damping); b) Thermal effect due to the annual air temperature wave; c) Time effect.

thank EDP for all the support provided during the system setup.

[1] Oliveira,S. (2002) “Continuous monitoring system for the dynamic performance assessment of programme D”, in “Study of evolutive deterioration processes in concrete dams.

. Nat. Sci. Re-equipment Programme of FCT (REEQ/815/ECM/2005).) “Observação e análise do comportamento dinâmico de barragens de

) “System identification and damage detection in civil engineering”. PhD Thesis,

[4] Juang,J.; Phang,M. (2001) “Identification and Control of Mechanical Systems”.Camb.Univ.Press.Identificação Modal Estocástica. Métodos de análise e aplicações em

estruturas de engenharia civil”. PhD Thesis FEUP, Porto. Mendes,P.; Costa, A. (2003) “Monitorização e modelação do compor

arragens de betão”, VII Cong. App.Computa. Mechanics, Univ.[7] Lemos,J.; Oliveira,S.; Mendes,P. (2008) “Analysis of the dynamic behaviour of Cabril dam

considering the influence of contraction joints”. EURODYN2008, Southampton, England.[8] Oliveira,S.;Ferreira,I.;Berberan,A.;Mendes,P.;Boavida,J.;Baptista,B.(2010)“Monitoring the struc

tural integrity of large concrete dams. The case of Cabril dam, Portugal”. Hydro2010, Lisbon.[9] Veletsos,A.; Ventura, C. (1986) “Modal analysis of non-classically damped linear systems”. J.

Earthquake Engineering and Structural Dynamics, Ed. John Wiley & Sons, vol.14, p.217Modelos para análise do comportamento de barragens de betão considerando

a fissuração e os efeitos do tempo. Formulações de dano”. PhD Thesis, FEUP, Porto.(2009) “CABRILAQUIS – Manual do Utilizador”, Relatório 211/2009.

b) a) Water effect

c) Time effect

Water level (m)

Natural frequencies from a FE model with a

transversely damaged zone for a simplified cracking

simulation

ssion)

2 t 2 tNatural frequency : f (h, t , t) a h a h a h a h b cos b sin

365 365

π π

[ ]�

1

timeeffect

c t k+ +�������������

of a statistical model for effect separation to the analysis of the main natural frequencies

a) Water effect (comparison with numerical results linear elastic behaviour, Westergaard associated water masses and classical damping);

ll the support provided during the system setup.

[1] Oliveira,S. (2002) “Continuous monitoring system for the dynamic performance assessment of n processes in concrete dams.

equipment Programme of FCT (REEQ/815/ECM/2005). ) “Observação e análise do comportamento dinâmico de barragens de betão”,

) “System identification and damage detection in civil engineering”. PhD Thesis,

[4] Juang,J.; Phang,M. (2001) “Identification and Control of Mechanical Systems”.Camb.Univ.Press. tica. Métodos de análise e aplicações em

Costa, A. (2003) “Monitorização e modelação do compor-. Mechanics, Univ. Évora.

[7] Lemos,J.; Oliveira,S.; Mendes,P. (2008) “Analysis of the dynamic behaviour of Cabril dam considering the influence of contraction joints”. EURODYN2008, Southampton, England.

[8] Oliveira,S.;Ferreira,I.;Berberan,A.;Mendes,P.;Boavida,J.;Baptista,B.(2010)“Monitoring the struc-tural integrity of large concrete dams. The case of Cabril dam, Portugal”. Hydro2010, Lisbon.

ssically damped linear systems”. J. Earthquake Engineering and Structural Dynamics, Ed. John Wiley & Sons, vol.14, p.217-243.

Modelos para análise do comportamento de barragens de betão considerando PhD Thesis, FEUP, Porto.

Manual do Utilizador”, Relatório 211/2009.

b) Thermal effect

Mode 1

Mode 2

Mode 3

Mode 4