development of vulnerability curves of key building types to different hazards in the philippines

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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!