rodriguezmarek tues 130pm ven v

8/12/2019 Rodriguezmarek Tues 130pm Ven V

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February 12, 2014

Adrian Rodriguez-Marek, Ph.D.

Associate Professor

The Charles E. Via, Jr. Department of Civil and

Environmental Engineering

TWENTY YEARS AFTER NORTHRIDGE:ENGINEERING LESSONS

Cat Modeling 2014, Orlando , Florida


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Outline

Northridge EQ: event summary

Engineering lessons learned

Structural

GeotechnicalGround motions

Progress in hazard assessment in the last 20 years

Future trends


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A little about myself

Civil Engineer (B.S., M.S., and Ph.D.)

Career as a Geotechnical Earthquake Engineer

Ph.D. topic: Near-Fault Ground Motions (U.C. Berkeley,2000)

Research: Site response, liquefaction, ground motionprediction, seismic hazard analysis

Consulting

Seismic hazard assessment of nuclear power plants Thyspunt Siting Project, South Africa

Pacific Northwest National Lab and CGS, Hanford, WA


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Northridge Earthquake: General Data

Date: 17 January, 1994

Time: 4:30:55 AM (local time)

Magnitude: 6.7 (Moment Magnitude)

Focal Depth: 19 km

Blind-thrust event

Event Summary Engineering Lesson s Learned Progress in Hazard Ass essment Future Trends

From. http://earthquake.usgs.gov/earthquakes/states/events/1994_01_17.php

From P. Somerville


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Northridge Earthquake: Damage

60+fatalities

9,000 injured

20,000 homeless, 40,000 buildings damaged

1,600 red-tagged 7,300 yellow tagged

20 - 25 Billion dollars in estimated losses (source:

USGS)


From. http://pubs.usgs.gov/of/1996/ofr-96-0263/introduc.htm)


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Northridge Earthquake: Damage

Ground motion intensity

was high in the near fault,

but not beyond

design ground motions formost structures

Significantly more damage

than would be expected

for a M 6.7 event


From. http://pubs.usgs.gov/of/1996/ofr-96-0263/introduc.htm)


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Engineering Lessons Learned


8/78From Silva (1991)

Structural Engineering


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From Silva (1991)

Engineering

Seismology/Ground

Motion Engineering


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From Silva (1991)

Geotechnical Engineering


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Engineering Lessons Learned: Structural Engineering

Northridge was a Structuralearthquake Major lessons Steel structures Unexpected fractures in moment connections

Fractured steel braces in braced frames

Concrete structures Large deformations in floor diaphragms

Brittle columns

Known vulnerabilities that were exposed

Soft Storycollapse, masonry structures Non-structural components Significant damage led to large losses

Event Summ ary Engineering Lesson s Learned : Structural Hazard Ass essment Future Trends


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Engineering Lessons Learned: Steel Structures

Unexpected fractures in steel moment frame beam-tocolumn connections

Primary problem: brittle fractures of the weld between

beam flange and column flange


Sketch courtesy of T.Sabol, EnglekirkInstitutional, Inc


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Unexpected fractures in steel moment frame beam-tocolumn connections


From PropertyRisk.com

From Forell.com andMichael Engelhardt


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Unexpected fractures in steel moment frame beam-tocolumn connections: Causes

NOT: excessive ground motions

Many fractures occurred in buildings that should have

responded elastically (Mahin, 2014)

Most buildings were stronger than minimum code forces

Design issues: connections not properly tested, deep steel

beams

Construction issues: poor welding quality

Inspection problems



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Major research initiatives: FEMA/SAC Steel Project


From S. Mahin,Northridge at 20Symposium


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20 years later: resulting changes FEMA/SAC research reports

FEMA-350: Design Criteria for New Buildings

FEMA-351: Existing Welded Steel Moment-Frame Buildings

FEMA-352: Recommended Post-earthquake Evaluation and Repair FEMA-353: Quality Assurance Guidelines

FEMA-354: Policy Guide for Steel Frame Construction

Improve quality of welding materials

AISC Seismic provisions: expanded

AISC Connection prequalification standard



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Engineering Lessons Learned: Concrete Structures

Large deformations in long-span diaphragms Excessive diaphragm flexibility

Code level diaphragm forces were several times too

small


Northridge Fashion Center Parkinggarage (EERI Recon report)

CSUN parking structure in1994 (EERI Recon report)
http://seismo.berkeley.edu/gifs/northridge.gif


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Engineering Lessons Learned: Concrete Structures

NEES project: Seismic Design Methodology for PrecastBuilding Diaphragms (U. Arizona, UCSD, U. Buffalo,Lehigh U.)

Fleischman, R. B.; Naito, C.; Restrepo, J.; Sause R.; and Ghosh, S. K., "Seismic DesignMethodology for Precast Concrete Diaphragms, Part 1: Design Framework," PCI

JOURNAL, 2005 Rodriguez, M.E., Restrepo, J. and Blandon, Seismic Design Forces for Rigid Floor

Diaphragms in Precast Concrete Building Structures, JSE, 2007.

Actual diaphragm forces far exceed ASCE 7-05specified diaphragm forces

BSSC Provisions Updated Committee on diaphragmforces


E i i L L d N St t l


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Engineering Lessons Learned: Non-Structural

Components

Olive View Hospital

Near elastic response

Ground accelerations were amplified (0.91g free field

and 2.31g at roof (Celebi 1997, JSE) Removed from use due to extensive nonstructural damage

(sprinklers, light fixtures, etc)


E i i L L d N St t l


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Components

Recognition of large damages/cost due to non-structuralcomponents

NEES Project, UNR (http://www.nees-nonstructural.org/)

Response of the nonstructural components, as part of a

system under large drifts/accelerations.

Interactions within and between the nonstructural components.

Interactions between the components and the structure.

Effects of structural yielding on response of the nonstructural

components.


Engineering Lessons Learned Non Str ct ral
http://www.nees-nonstructural.org/http://www.nees-nonstructural.org/http://www.nees-nonstructural.org/http://www.nees-nonstructural.org/


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Components

Damages resulting from the Northridge EQ resulted ina push for PERFORMANCE BASED EARTHQUAKE

ENGINEERING


Performance Based Earthquake Engineering:


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Moehle (2003)

Performance Based Earthquake Engineering:PEER methodology

Ground Motion Intensity Measure(s)

Simple parameterizations of (complex) seismic ground motions Predictable as a function of site/seismic parameters

Full probability distribution function(s)

Relevant: can be related to structural response




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Moehle (2003)


Engineering Demand Parameter(s)

Quantify structural response Predictable as a function of IMs

Full probability distribution function(s)

Relevant: can be related to structural damage




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Moehle (2003)


Damage Measure(s)

Predictable as a function of EDPs Full probability distribution function(s)




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Moehle (2003)


Decision Variable(s)

Tools for decision maker$ (owners, public policy officials)


Engineering Lessons Learned: Performance Based


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ATC-58 (2004)

Engineering Lessons Learned: Performance Based

Design

IO LS CP10

-5

10-4

10-3

10-2

10-1

100

Damage Measures (DMs)

MeanAnnualRateofExceedanceofDM

s

Seismic Demand Curve

2%, 50 yrs

20%, 50yrs

%10, 50 yrs

Replacement Cost


0 0.2 0.4 0.6 0.8 110

-5

10-4

10-3

10-2

10-1

100

Peak Horizontal Acceleration (PHA)

Mea

nAnnualRateofExceedanceofPHA

Seismic Hazard Curve

(% 50, 50 yrs)

(% 20, 50 yrs)

(%10, 50 yrs)

(% 2, 50 yrs)


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Engineering Lessons Learned: Geotechnical

Major lessons Damages in pipelines (water/gas) due to ground

deformation

Seismic compression of non-saturated engineering fills

Site response of deep soils/basin effects

Event Summ ary Engineering Lesson s Learned : Geotechnic al Hazard Ass essment Future Trends


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Damage in water/gasdistribution systems

Damage correlated to Peak

Ground Velocity

(Jeong and ORourke, 2005)


G


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Damage in water/gas distribution systems


Photos courtesyof J. Bray, UCB

E i i L L d G h i l


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Seismic compression of non-saturated engineering fills Amount of damage to residential housing was large

Well documented case-histories (Stewart et al., 2004,

JGGE)


Source: Alan Kropp & David McMahon

Engineering Lessons Learned: Geotechnical/Ground


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g ee g esso s ea ed Geo ec ca /G ou d

Motions

Site response: clusters ofred-tagged buildings

Site response at deep soil sites

Basin effects

Observations led to changes in

the way site response is accounted

for

No similar changes yet for basineffects (too complex a problem)


Source: Davis et al. 2000, Science

Engineering Lessons Learned: Site Response in


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g g p

Codes

Before Northridge Zone Map


Courtesy of Jon Stewart, UCLA



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g g p

Codes


Linear PGA site

factors





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g g p

Codes


Linear PGA site

factors

Site-dependent

spectral shapes




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Codes

After Northridge USGS online hazard

maps

Spectral shape

anchored at two

periods

Nonlinear site-

factors

New updates

proposed (Seyhan andStewart, 2014)


Courtesy of Jon Stewart, UCLASeyhan and Stewart 2014


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Engineering Lessons Learned: Ground Motions


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Engineering Lessons Learned: Ground Motions

Near-fault Ground Motions:Forward-directivity effects

Initiate with high-intensity-long-period pulses

Higher Peak Ground Velocity(PGV)

Higher level of spectralaccelerations within a narrowband

Shorter duration Higher damage potential

Event Summ ary Engineering Lessons Learned : Ground Motio nsHazard Ass essment Future Trends

Sommervile et al. 1997


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Progress in Seismic Hazard Assessmentin the last 20 years


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Progress in Seismic Hazard Assessment: Ground


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Motion Prediction

Ground motion prediction is key to seismic hazardassessment

Attenuation relationships, now called Ground Motion

Prediction Equations (GMPEs)

Event Summ ary Engineering Lesson s Learned : Geotechnic al Hazard Assessm ent Future Trends

Ground Motion Prediction


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ProblemDetermine the ground motion parameters for a

hypothetical future earthquake scenario

Known Magnitude, distance, etc.

Since this is a prediction exercise, there is uncertainty

Prediction must be made in probabilistic terms




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1 2 10 20 1000.01

0.02

0.1

0.2

1

2

Distance from earthquake (km)

SpectralAcceleration,

(T

=

0.0

5

s)(g

)

Earthquakes of magnitude 7Earthquakes of magnitude 6

Ground MotionPrediction Equation(GMPE) or AttenuationRelationship

Courtesy of J. Bommer




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log(R)

M

log(Y)

, residual

log(Ypred)

log(Yobs)

Courtesy of J.Bommer


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Ground Motion Prediction Equations


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G ou d Mo o ed c o qua o s

Ground Motion Prediction Equations A function that predicts a ground motion parameters as a

function of Source, Site, and Geometrical parameters

log(Y) = f(M, F, R, S) + = f(M, F, R, S) + .

Ground Motion Parameter

Usually the log (natural log or base 10 log is taken because the

distribution is log-normal) Usually Y = Geometric Mean of Sa (T, x=5%), but can be anything

Duration, Tms, Arias Intensity, etc




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q



log(Y) = f(M, F, R, S) + = f(M, F, R, S) + .

Median Prediction

This is the equation itself

In data rich regions: obtained fromregression analysis of recorded data

In CEUS, obtained from data andseismological simulations




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q



log(Y) = f(M, F, R, S) + = f(M, F, R, S) + .

Deviation from median

s : standard deviation(predicted by the GMPE)

e: number of standard deviationsaway from the median



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Motion Prediction


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Motion Prediction

Since Northridge: large increase in available groundmotion data



Pre-Northridge Data


Motion Prediction


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Motion Prediction




Northridge Data


Motion Prediction


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Motion Prediction




NGA West II Data


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Progress in Seismic Hazard Assessment: GroundMotion Prediction


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Motion Prediction


What is new?: Complexity!



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Motion Prediction


NGA West 2 GMPEs capture: Magnitude range: 3 to 8.5 (for strike-slip events) Distance range: 0 to 300 km Hanging wall effects Site conditions: parameterized by Vs30 Term to capture deep site response (deep basin effect) Style of faulting term: strike slip, reverse, normal Magnitude saturation at short periods Buried ruptureeffects

Separate group working on Directivity effects (part ofNGA West 2 project)



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Motion Prediction


NGA West 2 GMPEs capture: Magnitude range: 3 to 8.5 (for strike-slip events) Distance range: 0 to 300 km Hanging wall effects Site conditions: parameterized by Vs30 Term to capture deep site response (deep basin effect) Style of faulting term: strike slip, reverse, normal Magnitude saturation at short periods

Buried ruptureeffects

Separate group working on Directivity effects (part ofNGA West 2 project)



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Motion Prediction


Magnitudesaturation is now a

common feature(from Y. Bozorgnia)



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Motion Prediction


Buried Rupture M7 Surface Rupture

(from P. Somverville)



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Motion Prediction


Period-to-Period correlation models Baker and Jayaram (2008), Baker (2011)



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Period-to-Period correlation models Baker and Jayaram (2008), Baker (2011)

Very useful for ground motion selection/assessment of

losses over a system with multiple components

NGA West 2: Period-to-Period correlation model will

be part of the final product

Progress in Seismic Hazard Assessment: Partiallynon-ergodic PSHA


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g


Key to PSHA: accounting for uncertainties

Smalluncertainty

Largeuncertainty



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g


Two types of uncertainties

UNCERTAINTIES

ALEATORY EPISTEMIC

True randomness

(natural variability) Quantified by the

standard deviation (s) ofa probabilistic distribution

Cant be reduced with

more data

Lack of knowledge

Expert judgment Logic-trees

Can be reduced withmore data



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g

Epistemic Uncertainty

Yucca Mountain Project(Stepp et al. )


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Sigma (aleatory variability) has remained constant over the

years, despite improved parameterizationFrom Strasser et al. (2009)



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Why hasnt sigma decreased?

Some components of variability cant be reduced!

Within out limited parameterization (e.g., M, R, Vs30),

there is true natural variability

Improved characterization of some effects (hanging wall,directivity, etc):

Important in reducing bias

Does not reduce sigma because it affects only a limited portion

of the data




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However, one component of variability can bereduced: site-to-site variability

Variability that results from treating all sites with the

same parameterization (e.g., Vs30) as identical

Resulting variability is known as single-station sigma

For site-specific analysis, this variability can be

removed

At the cost of computing/measuring the averageresidual (e.g., the site term) at the given site




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0.01 0.1 0.2 0.3 0.5 1.0 3.00.2

0.4

0.6

0.8

Period (Sec)

ss

and

5.0


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0.01 0.1 0.2 0.3 0.5 1.0 3.00.2

0.4

0.6

0.8

Period (Sec)

ss

and

5.0


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Non-ergodic PSHA (e.g., use of single station sigmaUNCERTAINTIES

ALEATORY EPISTEMIC

Cant be reduced with

more data Can be reduced with

more data

PREDICTION OF SITE

RESPONSE

- Use generic predictive

variables

- Use measurements

- Site responseanalysis ($)


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What the future holds

Future Trends


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More NGA Projects (information below from Y. Bozorgnia, PEER) NGA West 3

Expand range of applicability of models into softer soil and

harder rock

Refinement of directivity models Improvement in prediction of vertical motions

Beyond elastic response spectra

Incorporate Single Station Sigma


Future Trends


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More NGA Projects (information from Y. Bozorgnia,PEER)

NGA East for stable continental regions (2015)

NGA Subduction (2016)


Future Trends


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Use of seismological models in hazard analyses Large scale validation project (SCEC)

Models already work well to predict median motions for

a low frequencies

At issue is how to predict input parameters for models

More applications of Single Stationconcept

Use of project-specific instrumentation to measure site

terms


Concluding Remarks


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Research pays off Response to Northridge earthquake: Reaction from industry/funding agencies

Research

Code implementation

Civil engineering moving (fast) towards PerformanceBased Design

Important for insurance industry

Continued funding of research for seismic hazardreduction is important

Acknowledgments


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Matthew Eatherton (Virginia Tech) Jonathan Stewart (UCLA)

Julian Bommer (Imperial College)

Jonathan Bray (U.C. Berkeley)

Yousef Bozorgnia (U.C. Berkeley)

PEER (Northridge at 20 symposium)


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Thank you!

rodriguezmarek tues 130pm ven v

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