WP2: Framework for Seismic Hazard Analysis of Spatially Distributed Systems

Transcription

1 Systemic Seismic Vulnerability and Risk Analysis for Buildings, Lifeline Networks and Infrastructures Safety Gain WP2: Framework for Seismic Hazard Analysis of Spatially Distributed Systems Graeme Weatherill, Helen Crowley, Rui Pinho, UPAV Paolo Franchin, Francesco Cavalieri, UROMA Simona Esposito, Iunio Iervolino, AMRA SYNER-G Final Workshop, Milano, March

2 Generating Spatial Seismic Hazard: Outline Summary/Review of the Shakefield Approach Seismogenic Sources and Data Needs Ground Motion o Spatial Correlation o Spatial Cross-Correlation Geotechnical Hazard o Site Amplification o Permanent Ground Displacement o Coseismic Rupture SYNER-G Final Workshop, Milano, March

3 The Title Shakefield Approach Stochastic Simulation Generation of spatially correlated and crosscorrelated fields for ground motion intensity measures (IMs) i.e. PGA, PGV, Sa Multiple source typologies Area sources Simple Fault Sources Extension to geotechnical hazard SYNER-G Final Workshop, Milano, March

4 Defining the Hazard Ground Motion Input SYNER-G Final Workshop, Milano, March

5 Data Inputs and Needs Choice of methodologies may depend on data available particularly for geotechnical calculators SYNER-G Final Workshop, Milano, March

6 Seismic Source Supported Definitions & Requirements Source Typology: Area (e.g. uniform zone) Planar (e.g. fault surface) Geometry Activity Rate Recurrence Model Truncated Gutenberg- Richter (current) Alternative Maximum Magnitude Mechanism Strike, Dip, Rake Fault Type New approach for generating stochastic finite rupture planes SYNER-G Final Workshop, Milano, March

7 Ground motions from predictive models are taking into account spatial correlation in the intra-event ground motion residuals (ε ij ) log Y ij Spatial Correlation ( ) = f ( M i, R ij,q i1,i 2, in ) +e ij +h ij The covariance matrix of a set of spatially correlated sites is defined by C(h): A random field (Y) of multivariate Gaussian distributed values is determined from where Z is an independent random Gaussian field, and μ is the mean field (from the GMPE) SYNER-G Final Workshop, Milano, March

8 Spatial Correlation Each Shakefield samples a spatially correlated multivariate Gaussian field of ground motion residuals. Sites can be distributed across a regular grid, or as a list of locations SYNER-G Final Workshop, Milano, March

9 Spatial Correlation in European Strong Motions (Esposito & Iervolino, 2011; 2012) Isotropic semi-variograms used to model spatial correlation in GMPE residuals for 1) Akkar & Bommer (2010) dataset and, 2) ITACA Exponential semi-variograms preferred Resulting correlation model takes functional form of Jayaram & Baker (2009): ( ) = a 1- exp( -3h b(t) ) r h,t éë ù û SYNER-G Final Workshop, Milano, March

10 Spatial Cross-Correlation Software extends the spatial correlation in single ground motion fields to consider spatial cross-correlation across multiple measures of ground motion intensity (e.g. multiple periods of spectral acceleration) Ground motion residual fields conditioned upon the field of a primary IM choice of primary IM may depend on the application in question SYNER-G Final Workshop, Milano, March

11 Spatial Cross-Correlation Spectral correlation model of Baker & Cornell (2006) preferred in this application Choice of spatial and of spectral correlation models could be explored within the epistemic uncertainty analysis SYNER-G Final Workshop, Milano, March

12 Site Amplification and Geotechnical Hazard Emphasis on practical methods and models that can be applied at different spatial scales: Site Urban/Metropolitan Region Computationally feasible within a stochastic seismic hazard framework May preclude certain approaches requiring computationally complex non-linear analysis or highly detailed soil profiles Uncertainty should be considered where possible SYNER-G Final Workshop, Milano, March

13 Site Amplification Available in Software Direct Calculation using Vs30 or GMPE site class NEHRP/IBC (2003/2006) Ground Motion on Rock Design code amplification factors Eurocode (2004) AUTH Eurocode Adjusted Factors Empirical Amplification Models Choi & Stewart (2005) Contextual (Microzonation compatible models) SYNER-G Final Workshop, Milano, March

14 Contextual (Microzonation) Model Spectral amplification factors can be derived for geological zones using nonlinear amplification analysis methods Variability in each zone from site-to-site (i.e. profile-to-profile) variability and from record-to-record variability Methodology implemented in software, but more testing required for use in future case study applications SYNER-G Final Workshop, Milano, March

15 Context-Specific Site Amplification For each zone, define a set of 1D profiles Observed boreholes within zones Monte Carlo generated profiles Spectral amplification factors can be derived for geological zones using nonlinear amplification analysis methods Needs further testing in future case studies! SYNER-G Final Workshop, Milano, March

16 Given a set of Rock ground motion records (V S30 > 850 m/s) Apply 1D-Equivalent Linear Analysis to records for selection of profiles Simulate Amplification function F from multivariate Gaussian distribution Calculate spectral correlation in F SYNER-G Final Workshop, Milano, March

17 For wide application the HAZUS methodology is used as reference HAZUS classifications retained for liquefaction and slope displacement susceptibility categories - Slope displacement model replaced with Saygill & Rathje (2008) Landsliding and Liquefaction Landslide/Liquefaction occurrence probabilities sampled within stochastic framework SYNER-G Final Workshop, Milano, March

18 Coseismic Rupture Translation of Probabilistic Fault Displacement Hazard Assessment (PFDHA) (Youngs et al., 2003) methodology into stochastic framework: Earthquake rate and recurrence model P kn (s m,r) probability of slip at site, given magnitude and distance (1) P kn (D > d m, r, s) probability displacement exceeds D, given m, r, and slip at surface (2) Software samples (1) within the stochastically generated finite ruptures Average displacement from Wells & Coppersmith (1994) model Displacement at a point along fault distributed according to a cumulative gamma distribution (as a function of l/l) SYNER-G Final Workshop, Milano, March

19 Coseismic displacement comes from two sources: i) principal rupture ii) distributed rupture Empirical models give estimates of distributed rupture at a site, given the maximum displacement on the principal rupture (e.g. Youngs et al., 2003; Petersen et al. (2011); Moss & Ross (2011) All implemented in software SYNER-G Final Workshop, Milano, March

20 Conditional Probability P(D > d m, r, s): Challenges Tectonic regionalisation is relevant: models differ between compressional (e.g. Moss & Ross, 2011), transform (e.g. Petersen et al., 2011), and extensional environments (e.g. Youngs et al., 2003) Empirical models data poor in extensional regimes! No models describing the spatial correlation in displacements either principal or distributed rupture Youngs et al. (2003) European composite source faults are inconsistent with the definitions used in this approach SYNER-G Final Workshop, Milano, March

21 Geotechnical Hazard Calculators Novel Developments Geotechnical Hazard Liquefaction Features and Issues Stochastic implementation and practical on urban scale HAZUS susceptibility classes and probabilities retained Slope Displacement Coseismic Rupture HAZUS displacement characterisation retained Stochastic implementation and practical on urban scale Displacement model updated (Saygill & Rathje, 2008) HAZUS susceptibility classes and probabilities retained Complete stochastic fault displacement hazard model Consistency in rupture planes used for ground motion calculation and for displacement hazard More empirical displacement models needed! Transient Strain Paolucci & Smerzini (2008) SYNER-G Final Workshop, Milano, March

22 Geotechnical Hazard Calculators Novel Developments Geotechnical Hazard Liquefaction Features and Issues Stochastic implementation and practical on urban scale HAZUS susceptibility classes and probabilities retained Slope Displacement Coseismic Rupture HAZUS displacement characterisation retained Stochastic implementation and practical on urban scale Displacement model updated (Saygill & Rathje, 2008) HAZUS susceptibility classes and probabilities retained Complete stochastic fault displacement hazard model Consistency in rupture planes used for ground motion calculation and for displacement hazard More empirical displacement models needed! Transient Strain Paolucci & Smerzini (2008) SYNER-G Final Workshop, Milano, March

23 Geotechnical Hazard Calculators Novel Developments Geotechnical Hazard Liquefaction Features and Issues Stochastic implementation and practical on urban scale HAZUS susceptibility classes and probabilities retained Slope Displacement Coseismic Rupture HAZUS displacement characterisation retained Stochastic implementation and practical on urban scale Displacement model updated (Saygill & Rathje, 2008) HAZUS susceptibility classes and probabilities retained Complete stochastic fault displacement hazard model Consistency in rupture planes used for ground motion calculation and for displacement hazard More empirical displacement models needed! Transient Strain Paolucci & Smerzini (2008) SYNER-G Final Workshop, Milano, March

24 In Summary SYNER-G software includes a full stochastic seismic hazard calculator including: 1. Spatial Cross-Correlation in Ground Motions 2. Site amplification 3. Permanent ground deformation from landsliding and liquefaction 4. Permanent ground deformation from co-seismic rupture All features would benefit from further testing in new case studies! Despite objectives of practicality, considerable information is needed to implement some of the methods effectively Future work could focus on refining the empirical models of liquefaction, slope displacement and coseismic rupture SYNER-G Final Workshop, Milano, March