peer research: accomplishments & impact greg deierlein, stanford university and the peer...

PEER Research:Accomplishments & Impact

Greg Deierlein, Stanford Universityand the PEER Research Committee

PEER Summative Meeting – June 13, 2007

NSF-PEER Summative Meeting

Base Shear

Deformation

Damage Threshold

CollapseOnset

OPEN

OPEN

OPEN

FEMA 356 Performance LevelsIO LS CPPBEE yesterday

$, % replacement0 25% 50% 100%

Downtime, days0

1 7 30 180

Casualty risk0.00.0001 0.001 0.01 0.25

PBEE today

Evolution of PBEE


REF: Yang, Conte, Elgamal (UCSD)

Comprehensive System Simulation

S chemat ic of the F inite E lement M odel

2 D , 4 D

N o n - l in e a r p -y e le m e n t

N o n - l in e a r

N o n - lin e a r p -y e le m e n t

N o n - l in e a r F ib e r B e a m E le m e n t

D ra g

C lo s u re

P la s t ic E la s t ic

G a p

P ile N o d e

N e a r f ie ldP la s t ic R e s p o n s e

F a r - f ie ldE la s t ic

S te e l F ib e rs

U n c o n fin e d

C o n c re te F ib e rs

R e s p o n s e

C o n c re te F ib e rs

C o n fin e d C o re

F ib e r B e a m E le m e n t

= 1 4 D

1 4 E le m e n tsa t 1 .0 D o .c .

C o m p re s s io nA x ia l

E x te n d e d

G ro u n d L e v e l

PV

P ile S h a fto r 6 D

D is p la c e m e n t T im e h is to ry in p u tsfro m 1 -D n o n l in e a r s ite re s p o n s e

A

REF: Boulanger (UCDavis)


PEER’s Research Projects & Products

PBEE Methodology Technologies & Data Illustrative Examples Guidelines

SimulationSimulation

HazardHazard

MethodologyMethodologyModelsModels

ImpactImpact

t r a n s i t i o n s

Year 1 Year 5 Year 10

Methodology: Development ---- Application/PackagingData/Model: Creation ---- Implementation/ValidationDemonstrations: Evaluate/Synthesize ---- Impact of PBEE


Engineering Demand Parameter

Engineering Demand Parameter

Intensity Measure Intensity Measure

Damage MeasureDamage Measure

Performance-Based Framework: Buildings

Decision VariableDecision Variable• Collapse & Casualties

• Direct Financial Loss

• Downtime

drift as an EDP


Bridge and Transportation Systems

Damage Measure (DM)Damage Measure (DM)

Decision Variable (DV)Decision Variable (DV)

Engineering Demand Parameter (EDP)



Quality of Network Service

Restoration ($ and Time)


Electric Utility Lifeline Systems

Damage Measure (DM)Damage Measure (DM)

Decision Variable (DV)Decision Variable (DV)Power

Transmission Lines




Quality of ServiceRestoration ($ and Time)


Performance Assessment Components

Decision Variable

Decision Variable

Intensity Measure

Intensity Measure

Damage Measure

Damage Measure

Engineering Demand

Parameter

Engineering Demand

Parameter

Relating Performance to Risk Decision Making

Quantifying Damage Measures

Simulation of System Response

Earthquake Hazard Characterization


)(||| IMdIMEDPdGEDPDMdGDMDVGDVv

PBEE – Probability Framework Equation

Performance (Loss) Models and Simulation HazardImpact

IM – Intensity Measure

EDP – Engineering Demand Parameter

DM – Damage Measure

DV – Decision Variable

(DV) – Probabilistic Description of Decision Variable

(e.g., Mean Annual Probability $ Loss > 50% Replacement Cost)


Hazard Characterization

PEER Ground Motion Database

Next Generation Attenuation Functions Hazard Mapping

Geotechnical Data Center

Selection & Scaling of Ground Motions

Spatial Hazard & Correlations (scenario)

Site Response and Effects

Utilization of GM Shaking Data

Decision Variable

Decision Variable

Intensity Measure

Intensity Measure

Damage Measure

Damage Measure

Engineering Demand

Parameter

Engineering Demand

Parameter

Decision Variable

Decision Variable

Intensity Measure

Intensity Measure

Damage Measure

Damage Measure

Engineering Demand

Parameter

Engineering Demand

Parameter


PEER Ground Motion Database Decision Variable

Decision Variable

Intensity Measure

Intensity Measure

Damage Measure

Damage Measure

Engineering Demand

Parameter

Engineering Demand

Parameter

Decision Variable

Decision Variable

Intensity Measure

Intensity Measure

Damage Measure

Damage Measure

Engineering Demand

Parameter

Engineering Demand

Parameter

New Data Previous Data

0 . 1 1 1 0 1 0 0 1 0 0 0Distance (km )

4

5

6

7

8

Mag

nitude

0 . 1 1 1 0 1 0 0 1 0 0 0Distance (km )

4

5

6

7

8

Mag

nitude

-0.5

0.0

0.5

Ac

ce

l. (g

)

-0.5

0.0

0.5

Ac

ce

l. (g

)

PS10, 47 Deg.

PS10, Vertical

20 25 30 35 40

-0.5

0.0

0.5

Ac

ce

l. (g

)

PS10, 317 Deg.

2002 Denali (A laska) EQ, Pum p Station 10

0.01 0.1 1 10Period (sec)

0

0.5

1

1.5

Sp

ec

tra

l A

cc

ele

rati

on

(g

)

Over 10,000 recordsUniformly Processed Available On-Line“Google Inspired”

Ground motions Maps Damage Photos


Attenuation Functions & Hazard MapsDecision Variable

Decision Variable

Intensity Measure

Intensity Measure

Damage Measure

Damage Measure

Engineering Demand

Parameter

Engineering Demand

Parameter

Decision Variable

Decision Variable

Intensity Measure

Intensity Measure

Damage Measure

Damage Measure

Engineering Demand

Parameter

Engineering Demand

Parameter

NGA Attributes Long Period (0 to 10 sec.) Magnitude Range (5.0 to 8.5) Distance Range (0 to 200 km) Fault Mechanisms (SS, R, N)

More Accurate Lower intensity in many

places

Improved Understanding Spectral shape Spatial correlations

Influencing US national seismic hazard maps

Atten 805r, PEN, SS, Rrup=10.0 km, Vs30=760, D=1

0.01 0.1 1 10

Period (sec)

0.0001

0.001

0.01

0.1

1

Sp

ectr

al

Ac

cele

rati

on

(g

)

M=7.5

6.5

5.5

4.5

C&B 2003

C&B 2005 NGA

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

Sa co

mpo

nent

[g]

Period [seconds]

BJF Prediction: MedianBJF Prediction: Median +/- 1.0 sigmaBJF Prediction: Median +/- 1.0 sigmaBJF Prediction: Median +/- 2.0 sigmaBJF Prediction: Median +/- 2.0 sigmaObserved Sa - Loma Prieta (ID 11022)

+1.7 at T = 1.0 sec.

-0.3 at T = 0.45 sec.

Decision Variable

Decision Variable

Intensity Measure

Intensity Measure

Damage Measure

Damage Measure

Engineering Demand

Parameter

Engineering Demand

Parameter

Decision Variable

Decision Variable

Intensity Measure

Intensity Measure

Damage Measure

Damage Measure

Engineering Demand

Parameter

Engineering Demand

Parameter

Selection & Scaling of Ground Motions

the “+ effect”

• Spectral Shape of Extreme (Rare) Ground Motions

• Collapse Assessment at the MCE

Significance of +(SSF) effect

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20

0.2

0.4

0.6

0.8

1

1.2

1.4

Period [seconds]

Sa co

mpo

nent

[g]

Set selected for 2% in 50 yrs ( > 1.0)Set selected without considering

0 0.5 1 1.5 2 2.5 3 3.5 40

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Sag.m.

[g]

P[c

olla

pse]

Non-Epsilon SetEpsilon Set ( > 1.0)

Average Response Spectra

(from bins of + and epsilon neutral records)

+

+

+22% increase in apparent collapse capacity

Building Collapse Fragility

(case study 4-story building from NL dynamic analyses)

Period (sec)Sa (T1)

Pro

b [

coll

apse

]

Sa/

gDecision Variable

Decision Variable

Intensity Measure

Intensity Measure

Damage Measure

Damage Measure

Engineering Demand

Parameter

Engineering Demand

Parameter

Decision Variable

Decision Variable

Intensity Measure

Intensity Measure

Damage Measure

Damage Measure

Engineering Demand

Parameter

Engineering Demand

Parameter


Structural & Geotechnical Simulation

Reinforced Concrete Structural Modeling Cyclic degradation and shear needed for

assessing damage and collapse potential

Continuum Soil Models Large ground deformations & Liquefaction

Soil-Foundation-Structure Interaction Site response, foundation interaction necessary

for system performance

Computational Reliability Consistent tracking of uncertainty from hazard

to model uncertainty

Advanced Computing and Simulation Integrating with NEESit and cyberinfrastructure

Decision Variable

Decision Variable

Intensity Measure

Intensity Measure

Damage Measure

Damage Measure

Engineering Demand

Parameter

Engineering Demand

Parameter

Decision Variable

Decision Variable

Intensity Measure

Intensity Measure

Damage Measure

Damage Measure

Engineering Demand

Parameter

Engineering Demand

Parameter


Integrated Simulation/Assessment Platform

Algorithms,Solvers,Parallel/distributedcomputing

Simulation & Reliability Models for Materials, Components, and Systems

http://opensees.berkeley.edu

Computation InformationTechnology

Software framework,Databases, Visualization,Internet/grid computation

Models

Decision Variable

Decision Variable

Intensity Measure

Intensity Measure

Damage Measure

Damage Measure

Engineering Demand

Parameter

Engineering Demand

Parameter

Decision Variable

Decision Variable

Intensity Measure

Intensity Measure

Damage Measure

Damage Measure

Engineering Demand

Parameter

Engineering Demand

Parameter


Simulating Non-Ductile RC Columns

Numerical Models


Simulating Collapse of RC Buildings

Building Frame Definitions

-100 -50 0 50 100 150-200

-150

-100

-50

0

50

100

150

200

Sh

ea

r F

orc

e (

kN)

Column Top Horizontal Deflection (mm)

Test 19 (kN, mm, rad): K

e = 3.1779e+007

Kinit

= 7.4024e+007

s = 0.02

c = -0.04 (ND = 1)

y = 0.0091

cap,pl

= 0.069 (LB = 1)

u,mono,pl = 0.116 (LB = 1)

= 85, c = 1.20 isPDeltaRemoved = 1

Experimental ResultsModel Prediction

Component Tests & Models

EQ: 11011, Sa: 4.39g EQ: 11012, Sa: 2.66g

EQ: 11021, Sa: 2.52g EQ: 11022, Sa: 2.12g

Collapse Mechanisms

0 1 2 3 4 50

0.2

0.4

0.6

0.8

1

[Sacomp

(T=1.0s)] / [MCE of 0.9g]

P[c

olla

ps

e]

Empirical CDFLognormal CDF (RTR Var.)Lognormal CDF (RTR + Modeling Var.)

P[Collapse/MCE] = 16 %

Collapse Fragility Curves

beam-column joint

column

beam

foundation

MWtrib

Wlean

bay size

H1

st-s

tory

n-s

torie

s a

t H

leaning (P-D)

column

Building System Simulation


Geotechnical and Soil-Foundation Models

4 @

11’

= 4

4’

6’

Nodes

Elastic beam-column elements

24’

12’ 12’Le Lm

-0.8 -0.4 0 0.4 0.8Norm alized settlem ent (s/z50)

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

No

rmal

ized

ver

tica

l lo

ad (

Q/Q

ult

)

Fo

rce

Disp

Qz springs (Boulanger, 2000)

Centrifuge Experiments (NEES-UC Davis)

Soil-Foundation Model


Soil-Structure-Foundation Interaction

Behaviour of piles in liquefied soils using coupled fluid-soil models

System performance analyses


Damage Measures & Fragility Functions

Reinforced Concrete Components columns & beam-column joints

Nonstructural Components & Contents interior partitions laboratory equipment HVAC facilities

Electric Utility Equipment

Decision Variable

Decision Variable

Intensity Measure

Intensity Measure

Damage Measure

Damage Measure

Engineering Demand

Parameter

Engineering Demand

Parameter

Decision Variable

Decision Variable

Intensity Measure

Intensity Measure

Damage Measure

Damage Measure

Engineering Demand

Parameter

Engineering Demand

ParameterDevelopment of concepts, techniques and data applied to:


Repair-Specific Damage Functions

Damage State 0

Damage State 2

Damage State 4

0.0 1.0 2.0 3.0 4.0 5.0 6.000.10.20.30.40.50.60.70.80.91

Drift (%)

MOR 0MOR 1MOR 2MOR 3MOR 4

0.0 1.0 2.0 3.0 4.0 5.0 6.000.10.20.30.40.50.60.70.80.91

Drift (%)



MOR 0MOR 1MOR 2MOR 3MOR 4Pr

obab

ility

of

Req

uiri

ng a

MO

R

Components Evaluated:

• RC Beam-Columns, Joints, Walls• Interior Partitions• Laboratory Equipment• Ceiling & MEP Systems• Electric Utility Components

P[DM:EDP]

Decision Variable

Decision Variable

Intensity Measure

Intensity Measure

Damage Measure

Damage Measure

Engineering Demand

Parameter

Engineering Demand

Parameter

Decision Variable

Decision Variable

Intensity Measure

Intensity Measure

Damage Measure

Damage Measure

Engineering Demand

Parameter

Engineering Demand

Parameter

Testing Nonstructural Components & Equipment

Lab Equipment• Development of Damage (Fragility) Functions• Design Improvements to Components and Equipment• Development of Testing Standards

- FEMA 461: Interim Protocols For Determining Seismic Performance Characteristics of Structural and Nonstructural Components

- IEEE-693 standard for testing

Electric Utility Equipment

Motion-Damage Pairs from Real Buildings

0.2 0.4 0.80.6 1.0 1.2 1.61.4

No Damage

Heavy damage

Moderate damage

PFA (g)

DM

161 97 25 171150

Insignificant damage

2 16 29 51210 112

1 1 113 111 1 1

HVAC Systems

P [ DM | EDP = PGA ]

0.0

0.2

0.4

0.6

0.8

1.0

0.0 0.5 1.0 1.5 2.0 2.5

EDP [ PGA (g) ]

DM1

DM2

HVAC systems

EDP ( PFA g )

HVAC Systems1.0

0.8

0.6

0.4

0.2

0.00.0 0.5 1.0 1.5 2.0 2.5

P (DM | EDP = PFA )a model for systematically collecting & characterizing data from damaged buildings


Translating Damage to Decision Variables


Decision Making and PBEE Applications

Tradeoffs in Decision Making quantifying benefits and costs

Influencing practice “early adopters” codes and standards implementing new technologies

Influencing policy benchmarking standards and practice collaborating with stakeholders regulatory models

Decision Variable

Decision Variable

Intensity Measure

Intensity Measure

Damage Measure

Damage Measure

Engineering Demand

Parameter

Engineering Demand

Parameter

Decision Variable

Decision Variable

Intensity Measure

Intensity Measure

Damage Measure

Damage Measure

Engineering Demand

Parameter

Engineering Demand

Parameter


Integrative Testbeds

Buildings - Van Nuys - UC Sciences

UCB Campus

Bridges - Humboldt Bay - I-880 Viaduct

Bay Area Highway Network

0.2 0 0.2 0.4 0.6 Miles

Map 8.2Building Downtime in Months from a Rare Earthquake

StreetsHayward FaultTopo LinesNon-core Buildings

Downtime for Building in Months0 - 12 - 45 - 1213 - 2425 - 40

N

EW

S

#

OXFORD

#

HEARSTBarker Hall Tolman Hall

Giannini Hall

Hesse Hall

Warren Hall

Mulford Hall

Campbell Hall

McLaughlin Hall

Latimer Hall

Lewis Hall

Hildebrand Hall

Wurster Hall

2251 COLLEGE AVE

Berkeley Art Musuem

Art Gallery

Barrows Hall

2223 Fulton

2111 BANCROFT WAY

Doe Annex

0.2 0 0.2 0.4 0.6 Miles

Map 8.2Building Downtime in Months from a Rare Earthquake

StreetsHayward FaultTopo LinesNon-core Buildings

Downtime for Building in Months0 - 12 - 45 - 1213 - 2425 - 40

N

EW

S

#

OXFORD

#

HEARSTBarker Hall Tolman Hall

Giannini Hall

Hesse Hall

Warren Hall

Mulford Hall

Campbell Hall

McLaughlin Hall

Latimer Hall

Lewis Hall

Hildebrand Hall

Wurster Hall

2251 COLLEGE AVE

Berkeley Art Musuem

Art Gallery

Barrows Hall

2223 Fulton

2111 BANCROFT WAY

Doe Annex


High-priority Issues for Bridges

Post-earthquake residual displacements are a primary contributor to bridge closure.

Liquefaction hazards continue to cause widespread damage or drive huge foundation costs.

After sixth repetition of Maximum Run - Olive View

About 100 columns with more than

1.75% drift were demolished after

1995 Kobe Earthquake although

they did not collapse.


Bridge Testbed Model in OpenSees

Modular design developed

(Stojadinovic)

Core

Foundation

Deck

Columns

Abutment

Billington, Eberhard, Lehman,

Mahin plus Kunnath

Arduino & Kramer, Boulanger,

Brandenberg, Bray, Martin plus Jeremic,

Elgamal Ashford


Bridges with lateral spreading / liquefactionAssessment of current approaches, improve understanding, and identification of benefits of nonlinear analysis:

Current design and remediation methods, vs. coupled soil-pile-structure models in OpenSees

Columns

Deck

CL

Wing wall

Bearing padsBack wall

Exterior shear keysSuperstructure

Expanded Polystyrene

Stem wallFooting

Piles

3

Columns

Deck

CL

Wing wall

Bearing padsBack wall

Exterior shear keysSuperstructure

Expanded Polystyrene

Stem wallFooting

Piles

3


New Technologies: Self-Centering Columns

0

-0.8 0 0.8

-30 -15 0 15 30

-400

-200

0

200

400

Design method: Mild reinforcement reduced Prestressing force from a

central unbonded tendon Same envelop Q- Peak displacements within

10% of RC column Residual displacements

less than 20% of RC column

Q

ECC, Steel Jackets, Unbonded Rebars


Building Benchmarking Studies

multiple realizations

“design uncertainty”

Facility Definition

PBEE Assessment

IM-EDP-DM-DV

DV’s:

p(collapse)

p($ > X)

p(D.T. > Y)

2003 Code Compliant- Strength- Stiffness- Capacity Design- Detailing

… …


Benchmarking: 1967 vs. 2003 Designs

1960’s Vintage 2003 Design Codes

Building

Collapse Risk

Pcol./MCE MAFcollapse

2003 5% 1 x 10-4

1967 40 to 80%

20 to 50 x 10-4

Effect of Design Parameters on Performance: Minimum Base Shear Strength

0 5 10 15 200

0.1

0.2

0.3

0.4

0.5

Number of StoriesP

[Col

laps

e|S

a2

/50]

Space FramesPerimeter Frames

Issue: What minimum base shear (if any) should be imposed in ASCE 7 Minimum Design Loads Standard?

EQ: 121231, Sag.m.

(T=0.87sec): 2.26g EQ: 121232, Sag.m.

(T=0.87sec): 1.66g

EQ: 121321, Sag.m.

(T=0.87sec): 3.06g EQ: 121322, Sag.m.

(T=0.87sec): 2.99g

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0 2 4 6 8

Period (Sec)

Vd/W

Design Spectra(SDC D, R=8)

0.044 minimum base shear

T4stT20st


Building code, regulation and policy issues

Benchmarking building codes Absolute safety and performance Relative safety and performance across:

systems/materials building heights/configurations, seismic hazard categories use/occupancy

Non-ductile RC Building Risks how bad is the problem? technologies to address it cost-effectively policy, incentives and regulation

Residential High Rise structural systems not envisioned by

code tenant & societal performance

expectations

New Innovative structural systems


PEER --- Making an IMPACT Tools for decision makers

Cost-benefit, financial models Regulatory & implementation issues (IRCC)

Packaging of PBEE Methodology Specificity & Simplification !

Demonstrate value/benefits of PBEE Building benchmarking Bridge systems (liquefiable soil, self-centering)

Dissemination & Outreach Initiatives Research community (NEES researchers) Professional engineers Other design professionals & decision makers

Implementation Initiatives Buildings - ATC 58, 63, NEHRP, Insurance, … Bridges – Caltrans, FHWA, …

peer research: accomplishments & impact greg deierlein, stanford university and the peer...

Documents

peer summative meetingref

systemssoftware framework

nmore accuratelower

distance range

magnitude range

story building

stanford universityand

effectsutilization of