Modeling of lifelines recent advances in re fire following earthquake including reference to the Japan earthquake Realistic Performance Assessment of Water Supply Systems Under Extreme Events Mohammad Javanbarg PEER Center October 1, 2011
Overview Fire following earthquake due to Japan EQ. Motivations Seismic reliability model Seismic damage simulation Hydraulic damage simulation Case study M. Javanbarg, 2011
Total 345 fires ~ 260 prompt 11 March 2011 Eastern Japan Earthquake fire following earthquake
11 March 2011 Eastern Japan Earthquake fire following earthquake Observations ~345 fires following earthquake, due to both shaking and tsunami several urban conflagrations two major oil refinery fires (1 shaking, 1 tsunami) LPG Tank cars scattered by tsunami 30+ ignitions in Tokyo Implications Japan, US very vulnerable to fire following earthquake refineries in LA / LB and SFBA Research Opportunities Tohoku ignitions >> all previous ignitions Get the data! Digest / understand it! Applicable to US impacts of loss of water supply fire department response?
Fire following earthquake - shakout 1,600 ignitions 1,200 large fires Super-conflagrations in LA & Orange County Regional Economics - ShakeOut $213.3 Billion total losses $87 Billion loss from fire 40% of total $53 Billion business interruption loss from water 0-hrs 24-hrs 25% of total 55% of all business interruption Assumes all aqueducts restored in 6 months Superconflagration Damaged pipes inhibit suppression 31% serviceability Central City is insufficient Fire fighting drops serviceability to zero Davis (2009)
Introduction - lit. rev. Shinozuka et al. (1981): Monte Carlo simulation + flow analysis Isoyama and Katayama (1981): Monte Carlo simulation + maximum possible flow Moghtaderizadeh (1981): heuristic Markov et al. (1994): negative pressure treatment Shi (2006) & Wang (2006): leakage modeling (GIRAFEE) M. Javanbarg, 2011
Motivations Pressure driven model vs driven Include pipe failure mechanism due to 1995 Kobe EQ. data Heavy leakage simulation Verification with measured and pressure due to 1995 Kobe EQ. data M. Javanbarg, 2011
ArcGIS EPANET Matlab + EPANET (PDA) Seismic reliability model ArcGIS M. Javanbarg, 2011
Failure mechanisms and damage states 1760 damage location Failure mode occurrence probability Failure mode Pipe material CIP DIP Round crack 0.17 0.00 Longitudinal crack 0.03 0.00 Damage in fitting and tear of pipe wall at welded joint 0.10 0.15 Pull-out 0.40 0.60 Local loss of pipe wall 0.30 0.25 Cumulative failure mode probability 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 Leak1 Leak 2 Leak 3 Leak 4 Leak 5 CIP DIP Leakage scenario M. Javanbarg, 2011
Variability of the pipe fragility functions Damage rate (No./km) 8 7 6 5 4 3 2 1 JWWA (1998) HAZUS (1999) T. O'Rourke and Jeon (2000) Takada (2001) CIP actual data Damage rate for CIP 0 0 20 40 60 80 100 120 140 160 PGV(cm/s) 2.5 JWWA (1998) Damage rate for DIP Damage rate (No/km) 2 1.5 1 0.5 0 JWWA-Liquefied (1998) HAZUS (1999) T. O'Rourke and Jeon (2000) Takada (2001) DIP actual data 0 50 100 150 PGV(cm/s)
upstream node required water L 1 L 2 a) L eakage state leak L downstream node required water Seismic damage simulation available water αkq k leakage i leak k αkq k Q ij ( 1 α ) q k k ( 1 α ) q leakage Leakage model k j k available water Cumulative failure mode probability 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 Rand(0,1) Leak1 Leak 2 Leak 3 Leak 4 Leak 5 Leak scenario CIP DIP b) B reakage state break PDF of failure modes required water L required water 1800 1600 1400 available water i βq ij leakage break βq ij ( 1 β )Q ij leakage Q ij ( 1 β )Q ij j available water Flow rate (L/s) 1200 1000 800 600 400 200 0 300 600 900 1200 1500 1800 Leak 1 Leak 2 Leak 3 Leak 4 Leak 5 Pipe diameter (mm) Breakage model Probabilistic model for leakage simulation Leakage scenarios
Hydraulic damage simulation & verification Kobe WSS Model verification Seismic reliability 1.2 1 0.8 0.6 0.4 0.2 0 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Node number Pressure availibility (Flow analysis using Monte Carlo simulation) Pressure availibility (Flow analysis using actual damage data)
Case study Osaka City WSS Water outage due to the 1995 Kobe EQ. Osaka City WSS Hydraulic calibration M. Javanbarg, 2011
Case study Osaka City WDS Power failure and pipelines damage simulations Water pressure (m) 12 10 8 6 4 Power failure simulation at 6:00 AM Kobe EQ. (TM at 6:00 AM) Power failure and pipeline damage simulation at 6:00 AM Water pressure (m) 18 16 14 12 10 8 6 Power failure simulation at 7:00 AM Kobe EQ. (TM at 7:00 AM) Power failure and pipeline damage simulation at 7:00 AM 2 0 KN249 KN230 KN104 KN22 KN453 KN48 KN324 JN36 JN89 HN88 HN21 HN26 ON45 Node related to telemeter Right after EQ. (6:00 AM) ON276 ON134 TN73 TN113 TN260 SN12 NGN14 4 2 0 KN249 KN230 KN104 KN22 KN453 KN48 KN324 JN36 JN89 HN88 HN21 HN26 ON45 ON276 ON134 Node related to telemeter TN73 TN113 TN260 SN12 NGN14 One hour after EQ. (7:00 AM) 14
Water outage simulation right after EQ. Actual Kobe EQ. Power failure + Pipeline damage Power failure 15
Water outage simulation two hours after EQ. Power failure + Actual data Pipeline damage Power failure 16
Serviceability to Important Customers 17
Thank you Questions? Javanbarg@quake.kuciv.kyoto-u.ac.jp M. Javanbarg, 2011