development of vulnerability curves of key building types to different hazards in the philippines
DESCRIPTION
A powerpoint presentation discussing vulnerability curves of key type buildings to earthquake and other environmental disasters.TRANSCRIPT
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B.M. Pacheco, J.Y. Hernandez Jr., E.A.J. Tingatinga, P.P.M. Castro, F.J. Germar, U.P. Ignacio, M.C.L. Pascua, L.R.E. Tan,
I.B.O. Villalba, D.H.M. Aquino, R.E.U. Longalong, R.N. Macuha, W.L. Mata, R.M. Suiza, M.A.H. Zarco
How do we measure vulnerability of different types of structures to Natural Hazards?
Earthquake and Wind
CE 10 Disaster Mitigation, Adaptation, and Preparedness Strategies (DMAPS)
January 21, 2014
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After the lecture, the student should be able to answer the ff:
What is the definition of vulnerability?Enumerate the parameters used in quantifying vulnerability to different hazards.Enumerate the different building types found in Metro Manila.Differentiate between the methods of developing vulnerability curves.Enumerate the different damage states of a building.What is the difference between fragility and vulnerability curves?Explain the capacity spectrum method for developing earthquake fragility curves.Explain the computational method for developing wind fragility curves. Explain how empirical and heuristic vulnerability curves are developed.
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July 16, 1990 Philippine Earthquake (by Caranto)
March 11, 2011 Japan Earthquake (abc News international)
February 22, 2011 New Zealand Earthquake (San Antonio Express News)
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Typhoon “UNDANG” (Agnes) Nov 3-6,1984 230 kph 895 deaths Php 1.9 B damage
Typhoon “REMING” (Durian) Nov 28-Dec 1, 2006 281 kph (Gust 320 kph)709 deaths 2,190 injured 753 missing Php 10.89 B damage
Typhoon “MILENYO” (Xangsane) Sep 25-29,2006 150 kph (Gust 160 kph)45 deaths Php 1.251 B damage
Source: PAGASA
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Will you, as private citizens, take steps to increase the capacity of your houses or buildings if you knew beforehand that they are at risk to a particular hazard? Will you reduce (if not minimize) the risk?Are our government officials willing to invest resources in improving the condition of existing government infrastructure (buildings, bridges, elevated roads and railways, airports, etc.) if they knew beforehand that these are vulnerable to damage?
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VULNERABILITY – the degree of loss to a given element at risk resulting from a given level of hazard (e.g. ground motion intensity, wind speed, depth of inundation). It is defined as the ratio of the cost of damage to the cost of structure and finishes, on a scale of 0 to 1 (or 0 to 100%)VULNERABILITY CURVE – a plot of the vulnerability of a structure vs. the level of hazard.
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Da
ma
ge
Ra
tio
Modified Mercalli Intensity (MMI)or Peak Ground Acceleration (PGA)
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Da
ma
ge
Ra
tio
Wind Speed (kph)
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Wood Structures
Wood Light-frame (W1) Bamboo Hut (W3)
Makeshift (N)
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Masonry Structures
Concrete Hollow Block (CHB)
Unreinforced Adobe (URA) Walls
Unreinforced Masonry (URM) Walls
Concrete Hollow Blocks with Woodor Light Metal (MWS)
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Concrete Structures
Reinforced Concrete Frames with Woodor Light Metal (CWS)
Reinforced Concrete Moment Frame (C1)
Concrete Shear Walls and Frames (C4)
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Precast Concrete Frames with Concrete Shear Walls (PC2)
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Steel Moment Frames (S1)
Steel Moment Frames (S1) Steel Frames with Cast-in-placeConcrete Shear Walls (S4)
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Methods for Deriving Vulnerability Curves
COMPUTATIONAL
EMPIRICAL
VULNERABILITYCURVE
HEURISTIC
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Computational Methods
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NSP Analysis
PERFORMANCE POINTS
PROBABILITY OF EXCEEDANCE
CURVE FITTING
FRAGILITY CURVES
BUILDING DATABASE
DAMAGE STATE EVALUATION
THRESHOLD VALUES
Capacity Spectrum MethodDEMAND SPECTRUM
Computational Method for EarthquakeVulnerabilityCurves
VULNERABILITY CURVES
DIFFERENT ATTRIBUTES
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Building Model of a Moment-resisting Frame
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18 m
Typical Frame Building Model
Material Properties:Unit weight = 23.5 kN/m3
Concrete compressive strength, fc’ = 21 MPaReinforcement yield stress, fy = 240 MPaModulus of elasticity, E = 25 GPaPoisson’s Ratio, ν = 0.20
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(Source: ATC-40)
Nonlinear Static Pushover Analysis
• Provides an estimate of the Capacity of the Building
Base Shear
Roof Displ.
Plastic HingesWhere yieldingOccurs (shearand bending moment)
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Earthquake Demand Spectrum
Spec
tral
Acc
eler
atio
n (g
)
Period
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PERFORMANCE POINT
CAPACITY SPECTRUM METHOD
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Damage Threshold Values
Spectral Displacement
Spec
tral
Acc
eler
atio
n (g
)
Sd-Moderate = 0.035m
Sd-Extensive = 0.073m
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Damage Probability Matrix
1111151515150.64
0.867111131515150.48
0.40.6670.6670.66761010100.4
0.1330.3330.40.425660.32
000.2670.26700440.24
000.2670.26700440.16
000.20.26700340.128
0000.26700040.096
000000000.048
CompleteExtensiveModerateSlightCompleteExtensiveModerateSlight
Probability of Exceeding a Damage StateNumber of Models Exceeding a Damage StatePGA
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Fragility Curves
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Damage States Damage Ranges (%) Damage Indices (%)None 0-2 1Slight 2-10 6Moderate 10-50 30Extensive 50-100 75Complete 100 100
Damage index at different damage states
Using the fitted fragility curves, the vulnerability curves can be derived
Where,Pv,GMI = damage probability at a certain GMI.PF,I = Probability of a structure being in a certain damage state i (from Fragility Curves).Di = Damage index for a certain damage state i from HAZUS.
∑= iFiGMIv PDP ,, *
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Da
ma
ge
Ra
tio
Modified Mercalli Intensity (MMI)
Earthquake Vulnerability Curve
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Curve‐fitting of LognormalCumulative Probability Distribution
Computational Fluid Dynamics (CFD)Analysis
Pressure Distribution Due to Wind
Damage State Evaluation
Probability of Exceedance
Building Database
Computational Fragility Curves
HAZUS MH Damage States
Repeated forall building modelsin the databaseuntil 350 kph
Vulnerability Curve
Suction Pressure Threshold Values from
Experiments (Resistance)
Computational Method for WindVulnerabilityCurves
Varying attributes
Varying wind speeds And 3 directions (0, 45, & 90 deg)
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CFD Analysis – Velocity Streamlines
0o wind direction ‐ perspective view 0o wind direction ‐ side view
90o wind direction ‐ perspective view 90o wind direction ‐ side view
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Pressure Distribution
Perspective View
Windward side
Roof
Leeward side
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Sample Wind Vulnerability curve
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Heuristic Method
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Survey form used for Earthquake Vulnerability Curves
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Sample Responses
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Sample Heuristic Earthquake Vulnerability Curves
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Empirical Method
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Methodology used for Empirical Earthquake Vulnerability Curve
1. Collection of building damage observations due to recent/historical earthquakes from published papers, field reports, etc. (Obtained the report from PHIVOLCS and GA last November 12,
2012)
2. Classification and extraction of useful data for the building types.
For CHB or MWS, key phrases like “concrete hollow blocks”, “residential house” (without description if it is reinforced concrete), and “masonry” were used as identifiers.
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Methodology
For URA or URM, key phrases like “church” were used.Validation of building type using available photos and descriptions (in the internet).
3. Assignment, based on the descriptions of building damage for several earthquakes, of damage ratio for each recorded earthquake intensity.
4. Development of the vulnerability curve for each type
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Data for CHB/MWS
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CHB/MWS Vulnerability Curve
Median 6.88Beta 0.21
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URM Vulnerability Curve
Median 7.12Beta 0.17
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Typhoon Simulation by PAGASA
Building Type Identification
Building Damage Quantification
Post‐storm data
Vulnerability Curve
Curve‐fitting of LognormalCumulative Probability Distribution
Methodology used for Empirical Wind Vulnerability Curves
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Sample Photos of Damaged Structures after a Typhoon
Typhoon PedringMaximum gust = 61mps = 219.6kph
55% Damage
Typhoon MelenyoMaximum gust = 65 mps= 234kph
65% Damage
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Wind Vulnerability Curves for Buildings
0
10
20
30
40
50
60
70
80
90
100
0 50 100 150 200 250 300 350
Wind Speed (kph)
% Dam
age W3
W1 & W2
CHB & CWS
C1 & C2
Dam
age
Rat
io (%
)
Empirical Wind Vulnerability Curves
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SummaryVulnerability curves were developed for each building type using the 3 methods (computational, heuristic, and empirical) for earthquake, and severe wind.The vulnerability curves can now be used to estimate the risk to our existing building stock.
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Acknowledgment
The authors would like to acknowledge and thank PAGASA, PHIVOLCS, CSCAND, Geosciences Australia (GA), and Australian Aid (AusAid) for their collaboration and financial support of this project.
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Thank you for your kind attention!