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Atilla Ansal , Mustafa Erdik,

DISSEMINATION WORKSHOP Lisbon, Portugal, May 25, 2007 Earthquake Disaster Scenario Predictions and Loss Modelling for Urban Areas. ISTANBUL CASE STUDY. Atilla Ansal , Mustafa Erdik, Nuray Ayd ı no ğ lu, Eser Durukal, G ö k ç e T ö n ü k , Aslı Kurtuluş, Ufuk Hancılar,

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Atilla Ansal , Mustafa Erdik,

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  1. DISSEMINATION WORKSHOP Lisbon, Portugal, May 25, 2007 Earthquake Disaster Scenario Predictions and Loss Modelling for Urban Areas ISTANBUL CASE STUDY Atilla Ansal, Mustafa Erdik, Nuray Aydınoğlu, Eser Durukal, Gökçe Tönük, Aslı Kurtuluş, Ufuk Hancılar, Mine Demircioğlu, Karin Şeşetyan Boğaziçi University Kandilli Observatory and Earthquake Research Institute Earthquake Engineering Department

  2. Black Sea Marmara Sea

  3. ISTANBUL EARLY WARNING NETWORK

  4. ASSESSMENT OF DAMAGE AND CASULTIES

  5. LOSS ESTIMATION METHODOLOGY ISTANBUL CASE • Input Data Based on Geo-Cells (Grids) • Seismic Hazard Maps (Spectral Acceleration) • Building Inventory Data Base • Vulnerabilities (Spectral displacement based) • Loss Estimation

  6. Site characterisation (NEHRP site classification) Hazard Scenarios INGV (9 Deterministic Scenarios) KOERI (Probabilistic, Time Dependent, T=475 year) Spectral accelerations (0.2 and 1sec) on the ground surface by NEHRP site factors using KOERI spectral values at B/C boundary Optimized envelope NEHRP spectra for INGV time histories METHODOLOGY • Input Data Based on Geo-Cells (Grids) • Seismic Hazard Maps (Spectral Acceleration) • Building Inventory Data Base • Vulnerabilities (Spectral displacement based) • Loss Estimation

  7. Istanbul NEHRP site classification and grid system

  8. Fault Segmentation Model (Erdik et al., 2005)

  9. Probabilistic Spectral Values at B/C Boundary

  10. INGV Deterministic Scenarios

  11. Optimized Envelope NEHRP Spectra for INGV Time Histories

  12. METHODOLOGY • Input Data Based on Geo-Cells (Grids) Probabilistic Site Dependent Spectral Accelerations • Seismic Hazard Maps (Spectral Acceleration) • Building Inventory Data Base • Vulnerabilities (Spectral displacement based) • Loss Estimation

  13. Average of all INGV Scenarios

  14. Classification of Building Inventory: Bi j k i: Structural systems category i = 1 : RC frame building i = 2 : Masonry building i = 3 : Shear wall building (Tunnel formwork system) i = 4 : Pre-fabricated building j: Number of building stories category j = 1 : 1 – 4 stories (including basement) j = 2 : 5 – 8 stories (including basement) j = 3 : > 8 stories (including basement) k: Construction Year category k = 1 : Construction year: pre-1979 (included) k = 2 : Construction year: post-1980 • METHODOLOGY • Input Data Based on Geo-Cells (Grids) • Seismic Hazard Maps (Spectral Acceleration) • Building Inventory Data Base • Vulnerabilities (Spectral displacement based) • Loss Estimation

  15. RC Frame Building Distribution

  16. Damage Estimation • METHODOLOGY • Input Data Based on Geo-Cells (Grids) • Seismic Hazard Maps (Spectral Acceleration) • Building Inventory Data Base • Vulnerabilities (Spectral displacement based) • Estimate the capacity diagram (capacity spectrum) of the building as an elastic-perfectly plastic • Utilizing the elastic spectral acceleration associated with the natural period of the building (from the site-specific elastic response spectrum)obtain the inelastic spectral displacement demand • Using the inelastic spectral displacement demand, calculate the cumulative and discrete damage probabilities for various damage states. • Loss Estimation Damage Classification N: No damage S:Slight damage M:Moderate damage E:Extensive damage C: Complete damage

  17. Vulnerability Curves Spectral Displacement Based VulnerabilitiesR/C Buildings

  18. Distribution of Collapsed RC Frame Buildings • METHODOLOGY • Input Data Based on Geo-Cells (Grids) • Seismic Hazard Maps (Spectral Acceleration) • Building Inventory Data Base • Vulnerabilities (Spectral displacement based) • Loss Estimation

  19. Distribution of Collapsed Mid-Rise, Post 1980, RC Frame Buildings S111

  20. Distribution of Collapsed Mid-Rise, Post 1980, RC Frame Buildings S112

  21. Number of Damaged , Low-Rise, Post 1980, RC Frame Buildings

  22. Retrofitted Case CAPACITY INCREASE By increasing Cs 2.5 times STIFFNESS INCREASE By decreasing T to 2/3 of original value

  23. Damage Percentages of RC Building Before and Retrofit, Scenario 111

  24. Casualty Rates and Population for different building types

  25. Casualty variation for all RC buildings; Scenario 111

  26. The effect of retrofit on the fatalities for different building types Scenario S111

  27. LOSS ESTIMATION MODELLING BY KOERILOSS V2 ZEYTINBURNU CASE • Input Data Based on Geo-Cells (Grids) • Seismic Hazard Maps • Site Response Analysis • Building Inventory Data Base • Vulnerabilities • Loss Estimation

  28. KOERILoss V2 Probabilistic or Deterministic Seismic Hazard at Engineering Bedrock Outcrop (PGA and Suite of Hazard Compatible Acceleration Time Histories) Local Geological and Geotechnical Site Conditions (Soil Type, Layer Thickness, Ground Water Level, Shear Wave Velocity Profile, Dynamic Soil Properties for Each Soil Type) Site Response Analyses (SHAKE 91) Earthquake Characteristics on the Ground Surface (Response Spectra, PGA) Optimization for the Best-Fit NEHRP Envelope Spectra Microzonation Maps for Ss (T=0.2s) and Sl (T=1s) Vulnerability Analyses Damage Distribution Maps (Number of Buildings for Different Damage Levels) Building Inventory (Construction Type, Construction Year, Number of Stories) Human Casualty Estimations Population (Number of Occupancy per Building) Numbers and Distribution of Human Casualties Input Procedure Output

  29. INGV Stations METHODOLOGY • Input Data Based on Geo-Cells (Grids) • Site Response Analysis • Seismic Hazard Maps • Building Inventory Data Base • Vulnerabilities • Loss Estimation

  30. Input Motion: Earthquake Hazard Compatible

  31. Geotechnical Site Characterisation

  32. Geotechnical Site Conditions • METHODOLOGY • Input Data Based on Geo-Cells (Grids) • Site Response Analysis KOERILoss V2 • Seismic Hazard Maps • Building Inventory Data Base • Vulnerabilities • Loss Estimation

  33. Examples of the best envelop fits obtained from the average elastic acceleration response spectra to determine the values for Sms and Sm1

  34. Seismic Hazard on NEHRP B/C Outcrop

  35. METHODOLOGY • Input Data Based on Geo-Cells (Grids) • Site Response Analysis • Seismic Hazard Maps • Building Inventory Data Base • Vulnerabilities • Loss Estimation Variation of spectral accelerations at 1.0s determined by best envelop Variation of spectral accelerations at 0.2s determined by best envelop

  36. Spectral Acceleration at T=0.2s

  37. Comparison of Spectral accelerations by NEHRP and site response analysis T=0.2s T=1s

  38. Building Types • METHODOLOGY • Input Data Based on Geo-Cells (Grids) • Site Response Analysis • Seismic Hazard Maps • Building Inventory Data Base • Vulnerabilities • Loss Estimation

  39. Probabilistic Simulated • METHODOLOGY • Input Data Based on Geo-Cells (Grids) • Site Response Analysis • Seismic Hazard Maps • Building Inventory Data Base • Vulnerabilities • Loss Estimation

  40. Probabilistic, PGA Scaling1

  41. METHODOLOGY • Input Data Based on Geo-Cells (Grids) • Site Response Analysis • Seismic Hazard Maps • Building Inventory Data Base • Vulnerabilities • Loss Estimation

  42. Variation of Damage before and after Retrofit

  43. Variation of the number of hospitalised and fatalities in Zeytinburnu before and after retrofit due to INGV Scenario S212

  44. CONCLUSIONS • There can be significant differences among the probabilistic and deterministic earthquake hazard scenarios. • The differences between the two options to account for site conditions (a) utilising NEHRP; and (b) based on more detailed geotechnical data and by site response analyses; were significant with respect to earthquake characteristics on the ground surface and damage distribution.

  45. CONCLUSIONS - Retrofitting ISTANBUL Number of RC frame buildings estimated to collapse in the case of KOERI probabilistic hazard scenario will be reduced from 23291 (4.1%) to 1471 (0.26%), and numbers of casualties from 31521 to 2442. ZEYTINBURNU If the simulated mitigation program is carried out for Zeytinburnu, numbers of extensively damaged or collapsed buildings for the worst case earthquake scenario S212 will be reduced from 2208 (16%) to 0, and numbers of casualties from 484 to 0.

  46. THE END

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