INGV-DPC S4 riunione Siena Aprile 2010 ITACA the Italian strong-motion database Task5 – site classification R. Paolucci, S. Giorgetti Politecnico di Milano (POLIMI) L. Luzi, F. Pacor, R. Puglia, M. Massa, D. Bindi Istituto Nazionale di Geofisica e Vulcanologia (INGV) M. R. Gallipoli, M. Mucciarelli Università della Basilicata

INGV-DPC S4 riunione Siena Aprile 2010 Analysis description The performance of different classification schemes has been tested through the evaluation of GMPEs The GM is represented by the acceleration response spectra ordinates (5% damping) The response variables are: magnitude, distance, style of faulting and soil classes A GMPE is derived for each classification The GMPE performance has been evaluated in terms of standard deviation of the GMPEs and of the errors associated to the classes of each scheme

INGV-DPC S4 riunione Siena Aprile 2010 Response variable: SA (5%, 0.04T 4sec) Geomean of H components Functional form (e.g. Akkar & Bommer, 2007): Functional form for regression M ref = 5.6, R ref = 1km

INGV-DPC S4 riunione Siena Aprile 2010 Regression approach Random effect model (e.g. Brillinger & Preisler, 1985) : Inter-event ( i ) Inter-station ( k ) Inter-event error = error due to an earthquake recorded by many stations Inter-station error = error due to a station which recorded several events

INGV-DPC S4 riunione Siena Aprile 2010 Mean prediction Earthquake i recorded at station k Inter-event distribution of error : it assumes a value for each earthquake and describes the correlation among the errors for different recordings of the same earthquake. It is a normal distribution with standard deviation equal to Error distributions Observation Intra-event distribution of error : it assumes a value for each recording. It is a normal distribution with standard deviation equal to. The error distributions and are assumed to be independent. RANDOM EFFECT MODEL inter/intra - event

INGV-DPC S4 riunione Siena Aprile 2010 Mean prediction Earthquake i recorded at station k Error distributions Observation The residuals are decomposed as the sum of the inter- and intra- event error distributions Since the distributions are independent, the total variance is the sum of the two variances: RANDOM EFFECT MODEL inter/intra - event

INGV-DPC S4 riunione Siena Aprile 2010 Inter/intra – event error

INGV-DPC S4 riunione Siena Aprile 2010 Mean prediction Earthquake i recorded at station k Inter-station distribution of error : it assumes a value for each station and describes the correlation among the errors for different recordings at the same station. It is a normal distribution with standard deviation equal to Error distributions Observation Intra-station distribution of error: it assumes a value for each recording. It is a normal distribution with standard deviation equal to. The error distributions and are assumed to be independent. RANDOM EFFECT MODEL inter/intra - station

INGV-DPC S4 riunione Siena Aprile 2010 Example of ITACA, SA at T=1.75 s Bindi et al, 2010 Recordings ik % Stations k % k ik Residual ik k ik = + Error distributions tot 2 = = = = + variances

INGV-DPC S4 riunione Siena Aprile 2010 Bindi et al, 2010 CLC AVZ Different earthquakes with magnitude 5.5±0.2 recorded at GBP GBP Model for ITACA (black): mean prediction for a M=5.5, class C - EC8 Example of ITACA, SA at T=1.75 s

INGV-DPC S4 riunione Siena Aprile 2010 Model for ITACA (black): mean prediction for a M=5.5, class C - EC8 Bindi et al, 2010 GBP Different earthquakes with magnitude 5.5±0.2 recorded at GBP CLC AVZ GBP Inter-station error for GBP CLC AVZ nearly zero Red curve= Mean GMPE + inter-station error for GBP Example of ITACA, SA at T=1.75 s

INGV-DPC S4 riunione Siena Aprile 2010 Bindi et al, 2010 GBP Different earthquakes with magnitude 5.5±0.2 recorded at GBP CLC AVZ GBP Inter-station error for GBP Intra-station error for event i recorded at GBP GBP,i Example of ITACA, SA at T=1.75 s Model for ITACA (black): mean prediction for a M=5.5, class C - EC8

INGV-DPC S4 riunione Siena Aprile 2010 Different earthquakes with magnitude 5.5 ± 0.4 recorded by different class C stations Red curve= Mean + inter-station standard deviation Blue curve= Mean + intra-station standard deviation Dashed curve= Mean + total standard deviation Example of ITACA, SA at T=1.75 s Model for ITACA (black): mean prediction for a M=5.5, class C - EC8

INGV-DPC S4 riunione Siena Aprile 2010 Classification schemes: EC8 Subsoil class Description of stratigraphic profileParameters V s,30 (m/s) N SPT (bl/30cm)c u (kPa) ARock or other rock-like geological formation, including at most 5m of weaker material at the surface 800 __ BDeposits of very dense sand, gravel, or very stiff clay, at least several tens of m in thickness, characterised by a gradual increase of mechanical properties with depth 360 – CDeep deposits of dense or medium-dense sand, gravel or stiff clay with thickness from several tens to many hundreds of m 180 – – 250 DDeposits of loose-to-medium cohesionless soil (with or without some soft cohesive layers), or of predominantly soft-to-firm cohesive soil EA soil profile consisting of a surface alluvium layer with V s,30 values of class C or D and thickness varying between about 5 m and 20 m, underlain by stiffer material with V s,30 > 800 m/s S1S1 Deposits consisting – or containing a layer at least 10 m thick – of soft clays/silts with high plasticity index (PI 40) and high water content 100 (indicati ve) _10 – 20 S2S2 Deposits of liquefiable soils, of sensitive clays, or any other soil profile not included in classes A –E or S 1

INGV-DPC S4 riunione Siena Aprile 2010 based on V s,30 when available (~ 80 stations at the present time) OR based on an expert evaluation when Vs, 30 is not available, account for: detailed geology and stratigraphic profiles when available H/V from noise and/or earthquake data 1:100,000 lithologic map ITACA - EC8

INGV-DPC S4 riunione Siena Aprile 2010 Classification schemes: Sabetta & Pugliese (1987) Based on geological and geotechnical information and the thickness H of the soil layer, three categories: Rock sites Stiff, shallow alluvium (H =< 20 m) Deep alluvium (H > 20 m) Stiff sites have average shear-wave velocity greater than 800 m/s alluvium sites have a shear-wave velocity between 400 and 800 m/s

INGV-DPC S4 riunione Siena Aprile 2010 Classification schemes: Rovelli et al. (2008) ZHAO et al. (2006) FUKUSHIMA et al. (2007) PERIOD T (sec) CAT. SCI SCII SCIII SCIV T < <= T < <= T < 0.6 T >= 0.6 PERIOD T (sec) CAT. SC1 SC2 SC3 SC4 T < <= T < 0.6 T >= 0.6 SC5 Generic Soil Generic Rock JAPAN ROAD ASSOCIATION Rovelli et al. CAT. SCI SCII SCIII SCIV T < 0.2 T >= 0.6 PERIOD T (sec) 0.2 <= T < <= T < 0.6 SCV SCVI SCVII Unknown T unknown & orig. AB site T unknown & orig. CD site based on predominant period of H/V SA ratios

INGV-DPC S4 riunione Siena Aprile 2010 Classification based on f 0 -Vs, 30 Based on Vs, 30 and fundamental frequency of the site, evaluated through H/V of acceleration response spectra 3 classes are individuated on the base of cluster analysis Sites are assigned to a class on the base of the membership degree

INGV-DPC S4 riunione Siena Aprile 2010 Mean f 0 Std f 0 C C C C1 C2 C3 Mean Vs30Std Vs30 C C C Cluster analysis: the error of each cluster is calculated as the mean point – to – centroid distance (normalized to the standard deviation of the cluster) Cluster analysis

INGV-DPC S4 riunione Siena Aprile 2010 C1 C2 C3 Degree of membership to a class

INGV-DPC S4 riunione Siena Aprile 2010 C1 C2 C3 Cluster analysis (one variable) Degree of membership to a class Mean f 0 Std f 0 C C C

INGV-DPC S4 riunione Siena Aprile 2010 Degree of membership to a class Assuming that the variables of the points in a cluster are normally distributed, the membership to a soil class can be evaluated as probability density For a normal distribution of one variable, the probability density function is: is the variable mean The assigned class is the one with the highest probability is the standard deviation

INGV-DPC S4 riunione Siena Aprile 2010 Data set for regression Magnitude range 3.5 – 6.3 Distance range 0 – 300 km A common data set of 1000 records

INGV-DPC S4 riunione Siena Aprile 2010 Number of stations for each class = rock sites

INGV-DPC S4 riunione Siena Aprile 2010 Soil coefficients

INGV-DPC S4 riunione Siena Aprile 2010 Preliminary considerations SP96 has 2 soil classes, therefore the soil coefficients tend to smooth the behaviour of peculiar sites. The classification is efficient, as the curves are clearly separated. EC8 has 4 soil classes, 2 classes represent sites with well defined response (classes D and E), while classes B and C tend to be very similar at low periods ROV has 6 soil classes, 2 have well defined response (classes 1 and 4), classes 2 and 3 have intermediate response, but they are too similar ( s and 0.4–0.6 s), coefficients of classes 6 and 7 also tend to be very similar (problem in class attribution?) S4-MI has 3 soil classes, each one with a well defined response.

INGV-DPC S4 riunione Siena Aprile 2010 GMPE tot

INGV-DPC S4 riunione Siena Aprile 2010 GMPE sta

INGV-DPC S4 riunione Siena Aprile 2010 Preliminary considerations T (0.04-1s): SP96 EC8 and ROV have similar total standard deviations, S4-MI has lowest T>1s: EC8 is the classification with the lowest standard deviation, and it depends on the fact that 2 classes amplify the GM, class D (but represented only by 3 stations…..) and C

INGV-DPC S4 riunione Siena Aprile 2010 Error distribution for each class (SP96) Sigma >= 0.3

INGV-DPC S4 riunione Siena Aprile 2010 Error distribution for each class (EC8) A B C

INGV-DPC S4 riunione Siena Aprile 2010 Error distribution for each class (MI) 1 2

INGV-DPC S4 riunione Siena Aprile 2010 Error distribution for each class (MI) 3 4

INGV-DPC S4 riunione Siena Aprile 2010 A new soil class A new soil class Sites with broad band amplification: multiple peaks and average amplitude greater than 2.7 for a wide frequency range FHC LNS 2.5 MNF GRR 2.5 AQG PSC Rock sites=38 ?

INGV-DPC S4 riunione Siena Aprile 2010 Performance Before

INGV-DPC S4 riunione Siena Aprile 2010 Error distribution for each class (ROV) I II

INGV-DPC S4 riunione Siena Aprile 2010 III IV Error distribution for each class (ROV)

INGV-DPC S4 riunione Siena Aprile 2010 Error distribution for each class (ROV) V VI