SESAME: Site Effects Assessment Using Ambient Excitations

EVG1-CT-2000-00026

SESAME: Site Effects Assessment Using Ambient Excitations

EVG1-CT-2000-00026

K. Atakan1, A-M. Duval, N. Theodulidis, B.Guillier, J-L.Chatelain, P-Y. Bard, and the SESAME Consortium

1 Department of Earth ScienceUniversity of Bergen

Allégt.41, N-5007 Bergen, NorwayTel: +47-55-583600 Fax: +47-55-583660

E-mail: atakan@geo.uib.no

The H/V Spectral Ratio Technique:Experimental Conditions, Data

Processing and EmpiricalReliability Assessment

The reliability of the H/V technique is evaluated

systematically through the following aspects:

• Experimental conditions

• Data processing

• Empirical evaluation

On the reliability of the H/V spectral ratio technique:

Motivations

On the reliability of the H/V spectral ratio technique:

Motivations

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Experimental conditionsExperimental conditions

H/V technique: Experimental conditions

Objectives: This part is dedicated to investigations on the required experimental conditions (instrumental characteristics, data acquisition, external conditions) for warranting the stability and reproducebility of measurements

Participants:CETE, NiceUJF/LGIT, GrenobleUiB, BergenITSAK, ThessalonikiICTE/UL, LisbonINGV, Rome

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Experimental conditionsExperimental conditions

Description of the work:

• Instrument calibration and testing, and comparison of the instruments that are used in the project were completed, following a dedicated workshop in Bergen, Norway

• Assessment of the effects of the experimental conditions isperformed and a large number of tests are conducted (see Poster 183 Paper ID 306).

Milestones and results:

• Get together experiment for instrument calibration and testing • Field work for studying the influence of experimental conditions • Guidelines for measurements

Experimental Conditions:Examples of instrumentation from UiB

Experimental Conditions:Examples of instrumentation from UiB

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GBV-316´s are used withdifferent casing

Data acquisition is aPocket-PC basedSEISLOG system

Experimental Conditions:Instrument tests

Experimental Conditions:Instrument tests

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Instrument tests in the lab

Instrument tests in the free-field

Sensor tests: seismometers vs accelerometers

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Instrument comparisons: Lab vs free-field

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Experimental ConditionsExperimental Conditions

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Effect of weather conditions

Rain and strong wind

SnowReference

Experimental ConditionsExperimental Conditions

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Effect of ground coupling

Asphalt

GrassPavement

Experimental ConditionsExperimental Conditions

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The aim is to evaluate the influence of various experimental conditionson the H/V results. In total 58 different tests were performed and the results are classified into three main categories:

(1) The experimental conditions that do not influence the results(2) Those that influence the results(3) Those that may influence the results

(1) Beyond some limits that can easily be controlled and set up(2) Beyond a limit where there is no control

In order to reach a conlusion statistical tests (Student-t test) areapplied systematically to all measurements and standard ”Technical cards” are produced

Experimental ConditionsExperimental Conditions

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Technical cardexample

Experimental ConditionsExperimental Conditions

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Out of 58 different tests that were performed

• 22 tests in general do not influence (OK) the H/V results• 17 tests may influence (May Infl.) the results

•13 tests show that the results influence the H/V ratios and are not recommended (N.R.)• 6 tests have not enough data (N.E.D) to reach a conclusion

Experimental ConditionsExperimental Conditions

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Following test results influence the H/V ratios and are not recommended (N.R.):

• Some ground-sensor coupling conditions (gravel, karstic limestone, etc.)• Modified sensor coupling (i.e. artificial interface between the sensor and the ground)• Weather conditions (rain and especially wind)• Buried underground structures

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Data ProcessingData Processing

H/V technique: Data processing

Objectives: This part is devoted to investigations on the various data processing alternatives and produce a standard processing software based on the most robust alternative

Participants:UiB, BergenUJF/LGIT, GrenobleCNR-IRRS, MilanoICTE/UL, LisbonETH, ZurichINGV, RomeCETE, NiceRésonance, Zurich

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Data ProcessingData Processing

Description of the work:• Existing algoritms for each processing step were collected• The best (robustness-simplicity-resolution) solution for processing is found based on comparisons with representative data sets• Design and implementation is done by a dedicated sub-group• Distributing for evaluation and review within consortium• Final version and user guidelines

Milestones and results:• Report with processing options• Report with these options on different noise data sets• Recommendations and software implementation (J-SESAME)(see Poster 199 Paper ID 2270)

Data processing Software: J-SESAMEData processing Software: J-SESAME

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H/V Software (J-SESAME) development is mainly done by:

Browsing module (Bladimir Moreno, UiB Bergen)Window selection module (Pierre-Yves Bard, LGIT Grenoble)Processing module (Alberto Tento, CNR Milano; Fortunat Kind, ETHZ)Display module (Pedro Roquette, UL Lisbon)

Testing of the processing module was performed by three groupstaking in to account the machine dependence ad functionality. A specific parametric survey was conducted and some format conversion programs are developed:

CETE, Nice (Etor Querendez, Anne-Marie Duval)INGV, Rome (Fabrizio Cara, Giuseppe Di Giulio, Giovanna Cultrera)IRD-LGIT, Grenoble (Jean-Luc Chatelain, Bertrand Guillier)

Data processing SoftwareData processing Software

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BrowsingModule

Data processing SoftwareData processing Software

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WindowSelectionModule

Data processing SoftwareData processing Software

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ProcessingModule

Data processing SoftwareData processing Software

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DisplayModule

Data processing SoftwareData processing Software

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DisplayModule

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Empirical evaluationEmpirical evaluation

H/V technique: Empirical evaluation

Objectives: Systematically evaluate and compare (using the J-SESAME software developed) the H/V ratios with other more reliable estimates (reference site). Compare H/V results with observed damage on recent earthquakes

Participants:ITSAK, ThessalonikiUJF/LGIT, GrenobleUiB, BergenETH, ZurichICTE/UL, LisbonINGV, RomeCNR-IRRS, MilanoCETE, Nice

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Empirical evaluationEmpirical evaluation

Description of the work:

• Collecting existing data sets (earthquake and noise)• Perform experimental measurements and processing of

ambient vibrations at selected sites• Systematic comparisons with weak- and strong-motion data

as well as damage disribution in urban areas• Comparing experimentally and theoretically estimated

transfer functions with H/V ratios

Milestones and results:

• Collection of different data sets• Report on the experimental measurement results• Comparison of the results (noise vs other data sets) (see Poster 200 Paper ID 2323)

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Empirical evaluationEmpirical evaluation

SESAME Standard Information Sheets (SIS)

A relational database is created storing the standardizedinformation for each experiment´s data set

Data are collected from:EQ + Noise 200 sitesEQ + damage + noise 6 locations

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Empirical evaluationEmpirical evaluation

IN STITUTE SIT E NAME SIS EVENTS RECORDS

ITSAK S.M. NETWORKEUROSEISTEST

637

28856

492247

INGV BENEVENTOCATANI A

CITTA-CASTELLOVERCHIA NOCOLFIORITO

631593

4231101523

1888514012269

CNR FABRIANNOPREDAPPIOROVETTA

6184

8112814

326123044

LGIT NI CEEBRON

GUADELUPETEHRAN

LOURDESGRENOBLE

547141015

161617

1492131

576785

1347149208

ETHZ S-M N ETWORK 22 62 115

TOTAL 211 1227 5194

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Empirical evaluationEmpirical evaluation

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Empirical evaluationEmpirical evaluation

Comparison between the H/V ratios of noise (black) and earthquake (red) data from two sites in Greece.

1 10

fre q . ( H z )

1

10

(h/v

)

a m l 1 - N / Z - r u n 1 0

1 10

1

Frequency (Hz)

H/V

1 10

fre q . (H z )

1

10

(h/v

)

a r g 1 - N / Z - r u n 1 0

101

1

Frequency (Hz)

H/V

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ConclusionsConclusions

• Instrumental and experimental conditions, which may influence the H/V ratios are identified. Among the 58 different experimental conditions 13 gave clear influence. The most critical seems to be the effect of wind.

• Dedicated software (J-SESAME) is developed to allow standard processing routines.

• A database of earthquake and noise records are compiled for comparison. Standard Information Sheets (SIS) are prepared for easy access.

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ConclusionsConclusions

• Correlations that were performed between the H/V ratios and near-surface geology gave promising results. However, correlation with damage seems difficult to obtain due to the complex nature of damage distribution.

• Guidelines are being prepared for the use of H/V spectral ratio technique, including experimental factors affecting the results, the standardized processing software with a user manual and recommendations with regard to the empirical evaluation.

• In parallel to the work presented here, within the SESAME project numerical simulations are also perfomed to better understand the nature of the noise field and to investigate the actual capability of H/V technique to retrieve useful information on site conditions.

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SESAME ProjectSESAME Project

Main results and reports on the ongoing workcan be found at the SESAME Project web-site:

http://sesame-fp5.obs.ujf-grenoble.fr

See also the Posters 183,199 and 200

Code LE TI ET ML RE MA IN HA SS GB

Sampling rate 100 Hz 125 Hz 100 Hz 125 Hz 125 Hz 125 Hz 50 Hz 50 Hz 200 Hz 100 Hz

Dynamic (bit)24 – 6(mask)

131.1 dB21.5 bits

108 dB18 bits

120 dB20 bits

140 dB24 bits

120 dB20 bits

140 dB24 bits

24 - 5(mask)

16 16

GAIN 1 256 1 32 1 1 1 1 1 1000

Manufacturer = theoriticalvalue of one count

(µV/counts)19.073 0.58 0.30 32.00 1.91 1.00 0.85 9.539 76.29 0.0763

Z channel (µV/counts) 19.146 0.600 0.298 31.562 1.907 1.000 0.849 9.579 76.753 0.0765

Z deviation from theoriticalvalue:

0.384 % -3.53 % 0.67 % 1.37 % 0.02 % -0.02 % 0.06 % -0.42 % -0.60 % 0.26 %

N-S channel (µV/counts) 19.147 0.600 0.298 31.559 1.906 1.001 0.850 9.577 76.442 0.0769 

NS deviation fromtheoritical value:

0.390% -3.45 % 0.67 % 1.38 % 0.04 % -0.05 % 0.02 % -0.40 % -0.19 %  0.78 %

E-W channel (µV/counts) 19.146 0.600 0.298 31.561 1.906 0.999 0.850 9.581 82.177  0.0768

EW deviation fromtheoritical value

0.382 % -3.45 % 0.67 % 1.37 % 0.03 % 0.09 % 0.03 % -0.44 % -7.71 %  0.65 %

polarity normal normal normal normal normal normal normal normalnormal (pb

on EWneg)

normal

Battery voltage (variation) 1.547 V 1.546 V - 0.439 V 1.579 V 0.840 V 1.547 V 1.548 V1.48 V to

1.5 V4.67mV 

mean deviation fromtheoritical valus (in %)

0.385 3.48 0.67 1.37 0.03 0.07 0.04 0.42 2.83 0.0187

mean total variation in volt 3.094 3.092 - 0.878 3.158 1.68 3.094 3.096 2.98 9.33 mV

Z MEASUREMENT totalvariation

161599 5149256 - 27818 1656376 1679748 3642154 323200 38826 121960

N-S MEASUREMENT totalvariation

161589 5143398 - 27821 1656665 1679104 3640689 323264 38984 121326

E-W MEASUREMENTtotal variation

161601 5141723 - 27819 1656458 1681592 3641245 323136 36263 121484

Table 2: Summary of the digitizer sensitivity tests.

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Experimental ConditionsExperimental Conditions

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The experimental tested parameters are classified in nine families, termed P1 to P9(see annex 1).Two types of parameters can be distinguished:* parameters relative only to the characteristics of the site itself and to theinstrumentation. Ideally, the noise source and external conditions should not varyduring the experiment. This is the case for the series of parameters P1, P2, P3, P4, P5,and P6;* parameters relative to the variation of external conditions at the same place (weather,time, noise sources …): P7, P8 and P9.

The t-test can be performed knowing just the means, standard deviation, and numberof data points. Note that the raw data must be used for the t-test. The two sample t-testyields a statistic t, in which

€

t=|x1−x2|A×B (1)

where

€

A=(n1+n2)n1n2 (2)

€

B=n1−1( )σ12+n2−1( )σ22n1+n2−2 (3)

€

x is the sample mean, and σ is the sample standard deviation. Note that thenumerator of the formula is the difference between the means and the denominator is ameasurement of experimental erro r in the two groups combined. Thus the higher the

value of t, t he greater t he confidence tha t the reis a difference.

Experimental ConditionsExperimental Conditions

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TEST Number P1-1-1 P1-1-2 P1-2 P1-3 P1-4 P1-5 P1-6 P1-7 P1-8

CONCLUSION OK OK May Infl.

OK May Infl.

OK OK OK May Infl.

TEST Number P2-1 P2-2 P2-3 P2-4 P2-5 P2-6-1 P2-6-2 P2-7 P2-8 P2-9 P2-10

CONCLUSION May Infl.

N.R. OK May Infl.

May Infl.

OK May Infl.

May Infl.

May Infl.

N.R. N.R.

TEST Number P3-1-1 P3-1-2 P3-1-3 P3-1-4 P3-1-5 P3-1-6 P3-1-7

CONCLUSION N.R. N.R. N.R. N.R. May Infl.

OK OK

Experimental ConditionsExperimental Conditions

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TEST Number P3-1-8 P3-1-9 P3-1-10

P3-1-11

P3-1-12

P3-1-13

CONCLUSION OK N.R. May Infl.

OK OK OK

TEST Number P3-2 P3-3 P3-4 P3-5 P3-6 P3-7

CONCLUSION OK N.R. OK May Infl.

OK May Infl.

TEST Number P4-1 P4-2

CONCLUSION N.R. N.R.

Experimental ConditionsExperimental Conditions

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TEST Number P6-1 P6-2 P6-3 P6-4 P7-1

CONCLUSION N.R. N.R. N.E.D OK N.E.D

TEST Number P8-1 P8-2 P8-3 P8-4

CONCLUSION N.E.D OK OK

TEST Number P9-1 P9-2-1 P9-2-2 P9-3 P9-4-1 P9-4-2 P9-5 P9-6 P9-7

CONCLUSION May Infl.

May Infl.

May Infl.

N.E.D May Infl.

N.E.D OK N.E.D OK