Performance assessment under multiple hazards

Transcription

1 Performance assessment under multiple hazards D. Vamvatsikos, Dept of Civil and Environmental Engineering, University of Cyprus, Cyprus E. Nigro, Dept of Structural Engineering, University of Naples Federico II, Naples, Italy L.A. Kouris, G. Panagopoulos, A.J. Kappos, Dept of Civil Engineering, Aristotle University of Thessaloniki, Greece T. Rossetto & T.O. Lloyd, Dept of Civil, Environmental and Geomatic Engineering, University College London, UK T. Stathopoulos, Dept of Building, Civil and Environmental Engineering, Concordia University, Canada

2 Introduction Vulnerability can be defined in multiple ways it can be evaluated using widely different formats that are typically inconsistent with each other, especially when considering different hazards! Emergence of multi-hazard assessment concepts, hence important to collectively discuss such methods understand their merits attempt to cast them in a format that is suitable for integration within a single practical assessment framework Here: review of vulnerability assessment methods for earthquake hazard landslides and flowslides tsunami strong wind and hurricanes

3 1. Vulnerability of structures to earthquakes

4 Code RC1L RC1M Structural system Frame Infills No infills Building height No. of storeys Low-rise 1 to 3 4 to 7 RC1H High-rise 8+ RC3.1L RC3.1M Regularly infilled Low-rise 1 to 3 4 to 7 RC3.1H High-rise 8+ RC3.2L RC3.2M Soft storey (pilotis) Low-rise 1 to 3 4 to 7 RC3.2H High-rise 8+ RC4.1L RC4.1M Dual (walls+frames) No infills Low-rise 1 to 3 4 to 7 RC4.1H High-rise 8+ RC4.2L RC4.2M Regularly infilled Low-rise 1 to 3 4 to 7 RC4.2H High-rise 8+ RC4.3L RC4.3M Soft storey (pilotis) Low-rise 1 to 3 Mediumrise Mediumrise Mediumrise Mediumrise Mediumrise Mediumrise 4 to 7 RC4.3H High-rise 8+ Classification of the building stock several systems available need to converge! Code Structural system Storey number MSt1-2 Stone 1 2 MSt3+ masonry 3+ MBr1-2 Brick masonry 1 2 MBr3+ 3+ RISK-UE system, as adapted by AUTh Team

5 Example of compilation of inventory in Grevena loss assessment project (AUTh) Digital map (ArcMap) Building inventory (Εxcel) UID GIS

6 Damage definition six (5+1) damage states (DS0 to DS5) age Grading and Loss Indices for R/C structures Damage State Damage state label Range of damage factor Central damage factor (%) DS0 None 0 0 DS1 Slight DS2 Moderate DS3 Substantial to heavy DS4 Very heavy DS5 Collapse damage threshold different for R/C, URM

7 Ground motion characterisation Choice of a ground motion parameter that represents the seismic demand is crucial. Possible choices: macroseismic intensity based approaches (e.g. ATC-13) can be misleading!(rather subjective quantity, associated with great uncertainty, dependent on building stock performance) but: (limited) available damage data is usually associated (only) with intensity levels! direct ground motion quantities, such as PGA or PGV or even spectral quantities, like S d (HAZUS) or S a (Kiremidjian 1996) pertinent empirical data very scarce!

8 Determination of vulnerability functions Empirical approach [e.g. Spence et al. 2008; Rota et al. 2008] most common problem in purely empirical approach: lack of (sufficient and reliable) statistical data for several intensities Judgement-based and rating methods expert opinion [e.g. ATC-13] subjectivity?... scoring method (questionnaires) [e.g. GNDT] Analytical approach scores=?... from (equiv.)sdof to response-history of full structures! might seriously diverge from reality, usually overestimating loss! Hybrid approach combines empirical data with inelastic analysis (static/dynamic) critical point: definition of damage in each component!

9 The primary vulnerability curve (evolution of damage with intensity of seismic action) Damage-state medians determined from analytical L PGA relationship, scaled based on statistical data available e.g. DS4 (L=30%)

10 P[ds>dsi PGA] P[ds>dsi PGA] The probabilistic vulnerability curve ( fragility curve) lognormal distribution assumed for fragility analysis for given distribution type, only L DSi and β needed fragility curves for R/C and URM buildings developed by Kappos et al. using the hybrid approach typical fragility curves for typical fragility curves for URM buildings R/C buildings DS1 DS2 DS DS4 DS PGA (g) DS1 DS2 DS DS4 DS PGA (g)

11 Epistemic uncertainty Uncertainty is important (lack of knowledge of properties, coarse models) Recent methodologies remain computationally intensive and often difficult to apply for practical purposes 200 realizations of static pushover capacity curves for a two story masonry building, caused by epistemic uncertainty [Vamvatsikos & Pantazopoulou 2010]

12 2. Vulnerability of structures subjected to landslides and flowslides Eruption of St. Helens volcano (1980) resulting in a catastrophic landslide Landslide triggered by the eruption of Stromboli in 2002

13 Landslides triggered by the 1949 Khait earthquake, Tajikistan: major bend in Khait landslide path

14 Building damage due to debris flow height of debris flow breaking of brick or tuff external walls in R.C. framed structure

15 Building damage due to debris flow: Reinforced concrete buildings Breaking of brick or tuff external walls Failure of corner column

16 Building damage due to debris flow: Reinforced concrete buildings (contnd.) Plastic collapse mechanism of columns

17 Building damage due to debris flow: Masonry (URM) buildings Masonry building impacted by debris flows Remaining parts of masonry buildings

18 Mechanical models for assessment of buildings p u P u u p C f V cos V g V g L p cos L cos 1 g Pu 2 1 cos L 2 L Type-A Mechanism Collapse of the tuff or brick external walls uncertainties in both the hydrodynamic and structural models!

19 Mechanical models for assessment of buildings R/C q u 16 L M 2 u u 2 2 q C f D V D V g g V q g 16 2 M u D L D Type-B Mechanism Three-plastic-hinge collapse mechanism in reinforced concrete columns

20 Mechanical models for assessment of buildings R/C q V u 4 g M L 2 q u u g 4 2 M u D L D V g 4 L 2 i M i ui, D i Type-C Mechanism Two-plastic-hinges collapse mechanism in reinforced concrete columns

21 Mechanical models for assessment of buildings R/C q q V u u 2 T u L 2 Tu 1 L L / L 2 L / L g q u D 1 1 Type-D Mechanism Shear collapse mechanism in reinforced concrete columns

22 Mechanical models for assessment of buildings - URM p p uv uo L k M u 1 s b L 1 3 g pu 1 g V p 2 uv p cos cos uo Type-E Mechanism Debris flow impact against the ground floor walls of masonry buildings fragility curves?...

23 23 3. Vulnerability to Strong Wind events - Hurricanes Vulnerability of structures is assessed through: damage assessment field examinations of wind-structure interaction hurricane risk assessment from the insurance perspective

24 Homes destroyed by the storm in Plaquemines, Parish, Louisiana 24 Image from NOAA

25 Highway 90 bridge from Biloxi, Mississippi to Ocean Springs lies in a twisted mass as result of catastrophic wind and storm surge from Hurricane Katrina 25 (photo from FEMA)

26 26 Damage Assessment Several studies assessed damage through on-site observations Components that suffered excessive damage were roofs gable-end walls connections and sheathing Fully engineered buildings showed superior performance over pre- or non-engineered buildings

27 Field Studies 27 Valuable information has been produced by field (fullscale) studies Monitoring of both wind characteristics and impact on structures Evaluating wind-induced envelope pressures and structural response

28 Hurricane Risk Assessment Risk assessment involves several points of view (e.g. engineering, economic etc.) Research aims at developing appropriate risk assessment models influenced by various factors such as: weather data type of building occupancy construction method

29 4. Vulnerability to Tsunami Tsunami vulnerability is still in its infancy Generation of tsunami vulnerability curves has been hampered by the rarity of events Leading to lack of knowledge on tsunami behaviour near and on-shore Difficulty of current numerical models to accurately reproduce velocity profiles onshore

30 Empirical tsunami vulnerability curves Majority of existing tsunami vulnerabilty curves are empirical. Some examples: Peiris (2006): For low-rise URM houses in Sri Lanka (SL) affected by the 2004 Indian Ocean Tsunami (n=8672, from 11 locations) SL census data posttsunami 3 damage states X-axis = submerged height

31 Empirical tsunami vulnerability curves Examples of empirical tsunami vulnerabilty curves Koshimura et al. (2009): Buildings in Banda Aceh affected by Indian Ocean Tsunami (mix of low-rise timber and nonengineered RC) Based on damage interpreted from pre- and post-satellite imagery 1 damage state (collapse) X-axis = inundation depth, velocity, and hydrodynamic force, calculated numerically and very coarsely (e.g. assuming buildings as a roughness coefficient)

32 Spatial distribution of structural damage interpreted from post-tsunami satellite image

33 Tsunami Vulnerability - Gaps Lack of vulnerability curves for engineered buildings Lack of analytical vulnerability curves Few curves with x-axes other than water depth this is not representative of the impact forces and pressures that are better represented by other parameters, e.g. velocity and momentum Lack of field measurements of onshore flows and tsunami characteristics Difficulty in simulating tsunami onshore flow parameters numerically and experimentally Accounting for interactions of flows with bathymetry, coastal barriers etc. and variation of flow between buildings