Seismic Risk Maps for Non-Ductile Concrete Buildings 1 Matthew J. Zahr 2 Nicolas Luco 3 Hyeuk Ryu USGS Geologic Hazards Science Center Golden, Colorado 1: PEER intern 2: Research Structural Engineer 3: Postdoctoral Researcher U.S. Department of the Interior USGS – Geologic Hazards Team Seminar Series U.S. Geological Survey 10 June 2010
Outline of Presentation Motivation for Risk Maps Outline Pertaining to Non-Ductile Concrete Motivation Background on Risk Risk Components Risk Maps Case Studies Computation Closing Discussion of Risk Maps Original version vs. updated version Methodology Difference Maps Case Studies
Motivation of Risk Maps Outline 1971 San Fernando Earthquake Magnitude 6.6 Motivation Intensity XI Risk Property Damage: over $500,000k Risk Maps Casualties: 65 deaths Case Studies Majority of the damage and casualties were a direct result of Closing the collapse of older concrete buildings These older concrete buildings were observed to behave in a non-ductile manner under seismic loading Initiated implementation of building code revisions in the mid-1970s to increase ductile behavior during cyclic loading and prevent catastrophic failure However, there are still a great number of buildings built prior to building code revisions that pose a high risk of collapse in their lifetime
Motivation of Risk Maps Outline Top: Stair tower collapse at west end of Motivation Wing B in Olive View Hospital Bottom Left: Partial collapse of first Risk floor of Olive View Medical treatment and Risk Maps care unit Bottom Right: Collapsed overpass at Case Studies the Route 14-Route 5 interchange Closing
Motivation of Risk Maps Outline To prevent such catastrophic failures, concrete buildings built prior to the building code revision in Motivation 1976 are in need of seismic retrofit Risk Current estimates approximate 40,000 non-ductile Risk Maps concrete buildings in the western US (Emmett Case Studies Seymour, PEER intern) Closing Given the enormous quantity of these buildings, a systematic method to identify the highest risk buildings is desired
Motivation of Risk Maps Outline Seismic Risk Maps address these issues by: Identifying the most seismically problematic Motivation areas Risk Pinpointing the specific buildings in greatest Risk Maps need of retrofit Case Studies Prioritizing and quantifying retrofit Closing
Components of Risk Outline Hazard Motivation Exposure to Hazard Risk Fragility/Vulnerability Risk Maps Resilience Case Studies Closing
Hazard Outline Mean annual frequency of ground motion (spectral acceleration at a particular period of oscillation) Motivation exceeding some value at a particular location Risk Risk Maps Case Studies Closing
Site Class Affect on Hazard Outline NEHRP Site Class Definitions Motivation Risk Risk Maps Case Studies Closing USGS Hazard data is specific to Site Class B/C Boundary Site Coefficients exist to scale the ground motion data for different site classes Depends on: Spectral Acceleration and Period of Oscillation (or PGA)
Site Class Affect on Hazard My Hazard Tasks: Outline – Adjust for the other 4 site classes as if each particular Motivation site class covers the continental US (“Site General”) Risk – Using V S 30 values based on topography (Wald & Allen, 2007), assign each site class to Risk Maps its proper location (“Site Specific”) Case Studies – Create a site specific hazard file Closing
Site Class Distribution Outline Motivation Risk Risk Maps Case Studies Closing
Adjustment for Site Class Outline Motivation Risk Risk Maps Case Studies Closing
Exposure to Hazard: HAZUS Outline HAZUS Structural Types and Heights HAZUS Levels of Seismic Design Motivation Risk Risk Maps Case Studies Closing
Fragility Outline HAZUS Damage States Motivation Risk Risk Maps Case Studies Closing Probability of exceeding a certain damage state given a certain ground motion (spectral acceleration at a particular period of oscillation) for a particular building
Fragility Outline USGS fragility functions were derived by Luco & Karaca (2008) using curvilinear push-over curves from HAZUS Motivation Generic due to: Risk Generic structural properties Risk Maps They are based on the past performance of buildings Case Studies with similar structural designs Closing Curvilinear pushover curves are based on expert opinion Fragility functions based on multilinear pushover curves are being developed by Ryu et. al.
Vulnerability • Expected Loss Ratio (Repair Cost/Replacement Cost) for Outline a given spectral acceleration Motivation • Randomness about the expected value can be considered Risk • Derived by Karaca & Luco (2008) from fragility functions Risk Maps Case Studies Closing
Fragility & Hazard to Risk Outline Risk Summation (risk of DS i in 1 year) Motivation Risk Risk Maps Assume Poisson Process to extend time interval Probability of Exceedance in t years: Case Studies Approximation due to the associated assumptions PE in t years = 1 – exp(- λ [DS i ]t) Closing •Randomly occurring events where: λ = mean annual frequency of exceedance •Events are statistically independent •Probability of events in small time intervals are proportional to the time interval •Probability of more than one occurrence in a small time interval is negligible
Vulnerability & Hazard to Risk Outline Risk Summation (expected loss ratio in 1 year) Motivation Risk Risk Maps When E[LR] is multiplied by the value of a building, the Case Studies expected annual loss, in monetary unit, of the building Closing can be determined Note: Expected values can be added across buildings
Seismic Risk Maps Outline Contour/“Raster” Maps Several types to be discussed Motivation General Risk Map Risk Inventory-Specific Risk Map Loss Ratio Map Risk Maps Difference Map Case Studies Closing
Risk Maps – Original Tool Outline Original Tool Contour maps Motivation User specifies structural type, code level, planning Risk horizon, and damage state Create risk map assuming parameters exist at every Risk Maps point on grid ( General Risk Maps) Case Studies Site general risk maps with respect to the B/C boundary Closing
Risk Maps – Updated Tool Outline Updated Tool “Raster” maps Motivation Assume site class distribution based on VS30 values Risk determined from topography (Wald and Allen 2007) Inventory-specific risk maps Risk Maps User-specified site class (Inventory maps only) Case Studies User-inputted fragility/vulnerability information Difference maps – site distribution & code level Closing Loss Ratio maps
Risk Maps – Updated Tool Outline Motivation Risk Risk Maps Case Studies Closing
Risk Maps – Updated Tool Outline Motivation Risk Risk Maps Case Studies Closing
Risk Maps – Updated Tool Outline Motivation Risk Risk Maps Case Studies Closing
Risk Maps – Updated Tool Outline Motivation Risk Risk Maps Case Studies Closing
Risk Maps – Updated Tool Outline Motivation Risk Risk Maps Case Studies Closing
Risk Maps – Updated Tool Outline Motivation Risk Risk Maps Case Studies Closing
Risk Maps – Updated Tool Outline Motivation Risk Risk Maps Case Studies Closing
Risk Maps – Updated Tool Outline Motivation Risk Risk Maps Case Studies Closing
Risk Maps – Updated Tool Outline Motivation Risk Risk Maps Case Studies Closing
Risk Maps – Updated Tool Outline Motivation Risk Risk Maps Case Studies Closing
Risk Maps – Updated Tool Outline Motivation Risk Risk Maps Case Studies Closing
Risk Maps – Updated Tool Outline Motivation Risk Risk Maps Case Studies Closing
Risk Maps – Updated Tool Outline Motivation Risk Risk Maps Case Studies Closing
Risk Maps – Trials/Successes Outline Increased variability/complexity when incorporating site class distribution Motivation Use “raster” mapping instead of contours Risk Confidentiality issues with inventory-specific maps Scaling based on lat/lon precision Risk Maps Impose lower bound on scaling of boxes Case Studies Password protect KMZ files Drastic improvement on the generality and functionality of Closing the USGS risk map web tool
Risk Maps – Examples Outline Original Tool vs. Updated Tool Motivation Risk Risk Maps Case Studies Closing
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