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Proposed Damage Estimation Module

Expert Panel Open Meeting

Austin, TexasMay 29, 2014

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Agenda

Introductions Overview Proposed Damage Estimation Module

Wind Surge and Wave

Claims Data Review Future Work Q&A

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Introductions

Sam Amoroso, Ph.D. P.E., S.E. Forte & Tablada, Inc.

Bob Bailey, Ph.D., P.E. Exponent, Inc.

Bill Coulbourne, P.E. Coulbourne Consulting

Andrew Kennedy, Ph.D. University of Notre Dame

Doug Smith, Ph.D., P.E. Texas Tech University

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Overview 1st Open Meeting

Austin, August 22, 2013

Develop Framework Plan

2nd Open MeetingCorpus Christi, December 10, 2013

3rd Open MeetingAustin, March 13, 2014

4th Open MeetingAustin, May 29, 2014

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1st Open Meeting Panel Member Backgrounds

The TWIA expert panel has been appointed under Insurance Code §2210.578 and 28 Texas Administrative Code §§5.4260-5.4268. The panel’s purpose is to develop ways of determining whether a loss to TWIA-insured property was caused by wind, waves, tidal surges, or rising waters not caused by waves or surges.

After the panel completes its work, the commissioner will consider the panel’s findings and publish guidelines that TWIA must use to settle claims.

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2nd Open Meeting

Present Preliminary Overall Methodology Initial Focus: Residential Slab Only Claims

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3rd Open Meeting

Present Proposed Hazard Module Methodology Goal: To provide a time history of wind, surge, and

wave heights for a given property location.

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Preliminary Overall Methodology

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Proposed Damage Estimation Module Wind

Dr. Sam Amoroso Basis for Development of Damage Functions Component Demand Component Capacity Examples

Surge and Wave

Dr. Andrew Kennedy Process Definition Examples

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Damage Estimation Module

Based on Probabilities of Component Failure (Wind) or Probability of Structural Collapse (Surge and Wave)

Coupling of Component Damages

Time Histories of Damage estimated from Hazard Time Histories

Damage Estimation Module

Damage Estimate forEconomic Loss Module

BuildingSpecific

Information

Wind, Surge &Wave Time

Histories

BuildingVulnerabilityFunctions

Database ofObserved Damage

from SurvivingStructures

Damage Functionsfor

Building Components

Peak WindSpeed

Surge & WaveHeights

Damage Estimatefor Building Components

from Model

Damage Estimatefor Building Componentsfrom Damage Functions

Refinement ofDamage Estimate

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Wind

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Wind Damage Estimation

Probability-Based: What is the likelihood that wind pressure exceeds resistance capacity?

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Wind Damage Estimation Develop Probability Distributions for Component Demands and

Capacities

Probability Distribution defines likelihood of possible values of a variable

Component Demand (Wind Pressure) depends on: Wind Speed Wind Direction Surrounding Terrain Building Height and Shape Location of Component on Building Size of Component Whether Building Remains Enclosed

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Wind Damage Estimation

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Wind Damage Estimation

Component Capacities are also uncertain due to: Age Material Fasteners Configuration

Source: Florida Public Hurricane Loss Model

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Wind Damage Estimation

Component Capacities are variable

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Wind Damage Estimation

Preliminary Demand (Wind Load) PDF Parameters from “Wind Load Statistics for Probability Based Structural Design,” Ellingwood and Tekie, 1999, ASCE Journal of Structural Engineering

Preliminary Capacity PDF parameters from Florida Public Hurricane Loss Model engineering documentation

Additional sources and claim data will be used to refine PDF’s

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Wind Damage Estimation

Required: Time history of likely wind damage

Method: Monte Carlo Simulation Randomly sample values of demand and capacity from

respective PDF’s Simulate demand for every time step, using associated

wind speed and direction from hazard module Large number of simulations for the storm Damage statistics at each time step can be extracted from

simulations Mean, median, quartiles, etc.

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Wind Damage Estimation

Component damage is coupled: Damage to roof panels triggers damage to roof covering Loss of cladding element triggers higher internal pressure

Several Components Considered, Including Roof Covering Windows Doors Garage Doors

Relative Proportion of Component Damage Reported

Roof Panels/Decking Roof Trusses/Rafters Wall Studs/Wall Sheathing Shear Walls

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Wind Damage Estimation – Sample Structure One-story residential structure Gable roof Length = 56 feet, Width = 35

feet Eave height = 10 feet Roof Slope = 6:12 Roof ridge is oriented in N-S

direction Open Terrain (ASCE 7 Exposure

Category C) Overhead Garage Door Attached Garage

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Wind Damage Estimation – Sample Storm

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Wind Damage Estimation – Sample Results

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Wind Damage Estimation – Sample Results

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Surge and Wave

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Wave And Surge Failures for Slab Claims

• In those cases when a house is completely destroyed, it is important to know at what point wind, waves, or surge caused failure.

• The expert panel will develop methods to estimate timing of any wind, wave, or surge slab failure.

• The relative timings of wind, wave, and surge damage will be compared.

• Process is under development for wave and surge damage – will likely employ Wave Height, Freeboard, and House Age.

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Significant Wave Height

Zero NAVD88 Datum

Water depth

Wave Crest

Surge Elevation

Ground Elevation

Freeboard (negative here)

House Age(likely in ranges of years)

Definitions for Wave/Surge Processes

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Surviving, higher elevation homes

Destroyed, lowerelevation homes

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Example of Surge/Wave Failure Prediction

• Failure increases strongly with increasing wave heights• Older houses significantly more fragile• Higher house elevations (higher Freeboard) survive better

Different Freeboards

Significant Wave Height (m)

Significant Wave Height (m)

Significant Wave Height (m)

Significant Wave Height (m)

Age Pre-1974

1974-1987

1987-1995

1995-2008

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Preliminary Overall Methodology

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Claims Data Review Methodology Used for Review

Determine fields of data of interest. Select small sample and test difficulty in finding that data of interest. Each panel member search sample files for data of interest. Instruct panel member firms who will help with data search on what

data is of interest and how to complete data fields. Conduct data search of 500 claims files.

Current Status Fields of data have been determined based on data needed for

vulnerability model. Sample files have been selected. Panel members have searched sample files.

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Fields of DataTWIA file no.AddressCityStateZip CodeLatitudeLongitudePolicy Value Bldg Value Bldg SFApprox LengthApprox WidthPerimeter (ft)Plan Shape (R, T, U, L)Roof Cover TypeRoof Shape (H, G)Age of Roof CoverOrientation of long axis w.r.t NorthExposure CategoryO'hd garage door (Y, N)Garage Attached? (Y/N)Direction Garage Door FacesEave heightRoof slopeRoof ridge height1st floor elevationGround elevationNo. floorsYear Built

• • • • • • • • • Fdn Type• Roof sheathing type• % glass area• Window protection (Y, N)• Wall sheathing type• Exterior wall finish• Fence (Y, N)• Out building (Y, N)• Canopy (Y, N)• Tree w/in striking distance (Y, N)• Total Ike loss ($) • Total Ike Loss (% Value)• % Roof Cover Damage• % Roof sheathing damage• % Roof framing damage• % Window damage• % Door damage• % Garage door damage• % shear wall damage• % out-of-plane wall damage• % wall sheathing damage• % fence damage• % out building damage• % canopy damage• tree fall damage• Flooded• Depth of Water (ft)• Flood damage

Fdn TypeRoof sheathing type% glass areaWindow protection (Y, N)Wall sheathing typeExterior wall finishFence (Y, N)Out building (Y, N)Canopy (Y, N)Tree w/in striking distance (Y, N)Total Ike loss ($) Total Ike Loss (% Value)% Roof Cover Damage% Roof sheathing damage% Roof framing damage% Window damage% Door damage% Garage door damage% shear wall damage% out-of-plane wall damage% wall sheathing damage% fence damage% out building damage% canopy damagetree fall damageFloodedDepth of Water (ft)Flood damage

57 Fields of Data

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Data Collection

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Claims Data Locations Mapped

Location Colors show Roof Damage %Blue: 0 – 9%Yellow: 10 – 19%Red: 20% +

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Data Issues Must estimate component damage by “eye” or very

rough measurements. Some components are not visible and thus are

unknown (wall sheathing, roof sheathing). Some damage is collateral – tree fall damages

building. Some claim files cover multiple physical locations. Need multiple resources to collect all data – not just

claim files.

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Calibration Methodology

From Hazard Data for wind and flood – determine time histories for highest winds and storm surge.

At a location, determine the highest wind speeds and storm surge levels.

Determine damage levels for components based on those highest wind speeds and storm surge levels.

Compare predicted damage levels obtained from models with claim file damage.

Adjust damage module where deemed appropriate.

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Future Work

Calibration and Validation of Model Compare Ike damage with model predictions for same

location. Adjust model as necessary. Conduct randomized model validation using claim

data from Hurricane Ike. Present findings in a future Open Meeting.

Finalize recommendations and present to TDI.

Continue with development of a method or model to estimate damage to commercial properties starting with slab-only cases.

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Q&A