SEISMIC RISK ANALYSIS OF L AQUILA GAS DISTRIBUTION NETWORK Paper ID. 2999

Transcription

1 SEISMIC RISK ANALYSIS OF L AQUILA GAS DISTRIBUTION NETWORK Paper ID Simona Esposito, Iunio Iervolino Department of Structural Engineering, University of Naples Federico II

2 A gas distribution system comprises two main categories of components: point-like critical facilities (reduction stations and groups where gas is pressurized/depressurized and/or measured) pipelines constituting the distribution network Past earthquakes have caused a significant amount of damage to gas networks, especially to its main component, that is buried pipelines. The causes of earthquake damage to components of gas systems include: Permanent ground deformation (PGD) hazard produced by fault displacements, landslides, liquefaction of sandy soils Transient ground deformation (TGD) hazard associated with travelling seismic waves.

3 Impact of L`Aquila 2009 earthquake (Mw 6.3) on the performance of the local medium- and low-pressure gas distribution networks Damage to stations: repairs to the input/output network of Onna M/R and inclusion of stop-system; -RG housed in a masonry kiosk closed to building and damaged following the 6th April 2009 earthquake; Damage to gas pipes ; gas welded joint of a LP steel pipe pulled apart in Paganica (AQ); gas pipe connected to a damaged bridge in Onna (AQ) replaced with a stand-alone pipe Assessment of the damage occurred on pipes Resilience-related curve for the L Aquila gas network following the 2009 event.

4 OBJECTIVE To evaluate the seismic risk of the medium pressure portion of L Aquila (central Italy) gas distribution system that includes: Probabilistic characterization of seismic input Definition of vulnerability of the network s components Analysis of the system s seismic performance measures Probabilistic simulation for risk assessment. ACCORDING TO THE PBEE FRAMEWORK

5 1.Transient ground deformation (TGD) Seismic zone characterization Ground motion estimation Estimation of peak parameters through ground motion prediction equations considering: orandom fields of peak parameters and spatial correlation ocross -correlation between intensity measures (IMs) oconditional hazard approach Site amplification 2.Permanent Ground Deformation (PGD) The principal forms of permanent ground deformation are: ocoesismic rupture olandsliding oseismic settlement and lateral spreading due to soil liquefaction.

6 3.Vulnerability assessment Characterization Fragility analysis 4.Perfomance FAULT TREE ANALYSIS Boilers Alimentation First Regulator Second Regulator Mechanical Equipment Building Regulators Model Network modelling Connectivity Graph : nodes and edges Perfomance and loss Functionality Flow-based Graph : nodes and edges Functionality Performance indicators: To provide a measure of the impact of the earthquake on the system functionality and serviceability. Connectivity Loss CL 1 N N i source, dam i source, orig i SSI n i 1 n0 i 1 Q Q i i Re. Mi Serviceability index S T A T I O N REPAIR RATIO Analysis tools Graph theory algorithms Flow equation Newton Nodal and Loops methods

7 L Aquila Gas distribution system Gas distribution via a 621 km pipeline (STEEL /HDPE ) network: 234 Km at Medium Pressure; 387 Km at Low Pressure. The MP network connection to HP network through: 3 Metering / Pressure Reduction M/R Stations (Re.Mi. in Italian). The transformation of the MP into the LP through Reduction Groups (RGs). SOFTWARE IMPLEMENTATION (OOFIMS) Safetyrelief Filter Shutoff valve Monitor Regulator valve

8 Start iteration i Uniform PDF on the Paganica fault GMPE of Akkar and Bommer (2010) Spatial correlation model from Esposito and Iervolino (2011) and standard deviation from Akkar and Bommer (2010) Normal PDF from Akkar and Bommer (2010) Sampling of epicenter location Computation of Jooyner-Boore distance (R jb ) for the regular grid Computation of the mean of the logarithm of primary IM on the rock (PGA r ) at each site of the regular grid, conditional to M W 6.3 and R jb, m log(pgar) Mw,Rjb Computation of intra-event residual of log(pga r ) at each site of the regular grid sampling from a GRF, e log(pgar) Sampling of inter-event residual of log(pga r ), h log(pgar) log(pga r )= m log(pgar) Mw,Rjb + e log(pgar) + h log(pgar) Simulation of the event on the considered seismic fault The Paganica fault (normal fault type), characteristic earthquakes of moment magnitude M w 6.3. Simulation of the random field of the primary IM at bedrock (PGA r ); Akkar and Bommer (2010) GMPE and Esposito and Iervolino (2011) spatial correlation model Conditional simulation of the cross-correlated secondary IMs at bedrock (PGV r ); Interpolation of log(pga r ) at the vulnerable sites GMPE of Akkar and Bommer (2010) Computation of the mean of the logarithm of secondary IM on the rock (PGV r ) at the vulnerable sites, m log(pgvr) Mw,Rjb Correlation coefficient estimated, standard deviation from Akkar and Bommer (2010) Computation of the conditional mean and standard deviation of the logarithm of PGV r at the vulnerable sites, m log(pgvr) log(pgar),mw,rjb, s log(pgvr) log(pgar), Mw,Rjb According to condtional hazard approach of Iervolino et al. (2010) Computation of the logarithm of PGV r at the vulnerable sites, log(pgv r ) Amplification factors according to site classification of Akkar and Bommer (2010) Computation of IMs at surface for the vulnerable sites, log(pga S ), log(pgv S )

9 Landslide Critical Acceleration Map Yes K c <PGA S No Amplification due to local site conditions to get PGAs and PGVs that are the IMs at the surface; Uniform PDF Sampling of probability of displacement, P land PGD=0 According to the site classification scheme adopted by the GMPE Map area proportion from Hazus(2004) Displacement model of Saygili and Rathje (2008) Fragility curve from ALA (2001) Fragility curve form Hazus (2004) Performance indicators from Adachi and Ellingwood (2008), Poljanšek et al. (2012) Yes P land <P* la nd No Computation of the landslide displacement for the vulnerable sites, PGD Computation of repair ratio R R for pipelines as a function of PGV S and PGD Computation of the damage state of M/R stations as a function of PGA S Computation of the performance indicators, CL, SR CL, m CL s CL, SR, m SR s SR Stop iteration i Simulation of displacement consequential to PGD (landslide) Critical acceleration map according to Hazus (FEMA, 2004) methdology Fragility assessment Poisson repair rates function of PGV S and PGD (pipelines) ALA (2001) according to Esposito et al (2013) and lognormal fragility curves for un-anchored compressor stations (FEMA, 2004) Connectivity analysis Two performance indicators (Connectvity Loss and Serviceability ratio)

10 Complementary cumulative distribution function (CCDF). Different behavior due to the different definition of the two performance indicators and the network s configuration. Disaggregation of network performance, which indicated a clear influence, on the earthquake loss, of the damage state of the M/R stations