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New Analytical Models and Tools for Nonlinear Modeling of Reinforced Concrete Wall Structures Kristijan Kolozvari, CSU Fullerton 2019 PEER Annual Meeting January 18, 2019

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Page 1: New Analytical Models and Tools for Nonlinear Modeling of ... · 37 SW7 Zhang and Wang R 2.14 305 0.88 0.67 1.01 1.80 0.24 6.0 BR 38 SW8 Zhang and Wang R 2.14 305 0.65 0.67 1.01 1.80

New Analytical Models and Tools for Nonlinear Modeling of Reinforced

Concrete Wall Structures

Kristijan Kolozvari, CSU Fullerton

2019 PEER Annual MeetingJanuary 18, 2019

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Presentation Outline ◼ Description and validation of

new 3D models for RC walls

◼ MVLEM_3D

◼ SFI_MVLEM_3D

◼ quadWall

◼ Convert ETABS to OpenSees

◼ Description

◼ Example

◼ Summary and future work

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Background

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◼ P-M fiber section

◼ V - shear spring

◼ P-M and V uncoupled

MVLEM

Existing OpenSees RC Wall Models

Strain,

Str

ess,

O

TensionNot to scale

Compression

( c

' , fc' )

(0, 0)

(0+ t , ft)

Concrete

Strain,

Str

es

s,

y

E0

E1= bE0y

O

Steel

-80 -60 -40 -20 0 20 40 60 80

Top Flexural Displacement, top (mm)

-200

-150

-100

-50

0

50

100

150

200

La

tera

l L

oa

d,

Pla

t (

kN

)

-2 -1.5 -1 -0.5 0 0.5 1 1.5 2

Lateral Flexural Drift (%)

Test

AnalysisPax 0.07Ag f c

'

Plat , top

0

100

200

300

400

500

Pax (k

N)

RW2

RW2Boundary Zone

100 150 200 250 300 350 400 450 500 550 600

Data Point

-0.01

-0.005

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

Co

ncre

te S

train

Concrete Strain Gage

LVDT

Analysis

0.25%0.5%

0.75

%

1.0

%

1.5

%

1.0

%

2.0

%

1.5%

RW2, Thomsen and Wallace (1994)

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SFI_MVLEM

Existing OpenSees RC Wall Models

Concrete Struts

Reinforcement dowel action

Shear aggregate interlock

Reinforcement

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Flexure ShearPlat ≈ 180 k

Uncoupled

Model: Geff

Good prediction of hysteretic behavior

Nonlinear shear deformations

Shear-flexural interaction

Tran and Wallace (2015)

Existing RC Wall Models

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Coupled versus Uncoupled Wall Models

a) b) c) d)

V

MVLEM: uncoupled(Perform 3D, Shear Wall)

SFI-MVLEM: coupled

a) b) c) d)a) b) c) d)

gxy

a) b) c) d)

a) b) c)

a) b) c)

+30%

-30%

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◼ Extensive Documentation

◼ OpenSeesWiki (manuals, examples) - 15,000+ visits

◼ Kolozvari et al. (2015) ASCE Structural. Journal

◼ Kolozvari et al. (2015) PEER Report 2015/12

◼ Kolozvari et al. (2018) Computers and Structures Jour.

PEER Report

Existing OpenSees RC Wall Models

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Model Shortcomings & Objectives◼ Models are 2-node

◼ Cumbersome connecting wall and frame elements (requires rigid beams)

◼ Models are 2-D

◼ Limited ability in modeling nonplanar walls

◼ Impossible to model 3D behavior of walls

◼ Impossible to model 3D building systems

Rigid beam

Wall

Rigid beam

Beam

Kim (2016)

only

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Models Description and Validation

Macroscopic Models

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◼ MVLEM_3D

◼ SFI_MVLEM_3D

4-node Element12 in-plane DOFs

4-Node 3D MVLEM Elements

2-node 2D element 4-node Elastic Plate12 out-of-plane DOFs

3D Wall Element24 DOFs

NEWPublicly available

in 2019

4-node 2D element

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◼ Planar walls

◼ T-shaped walls under uniaxial loading

◼ U-shaped walls under biaxial loading

Models Validation

Beyer et al. (2008)

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TUB (Beyer et al., 20018)◼ SFI-MVLEM-3D

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Models Description and Validation

Finite Element Models

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Finite Element Models

◼ 4-Node FE

◼ Bilinear

◼ FSAM material

◼ 3D behavior

◼ In-Plane

◼ Out-of-plane

◼ Single layer

◼ Multi layer

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◼ Planar Walls

◼ 40 specimens

◼ 8 experimental programs

◼ Range of parameters

◼ hw/lw = 1.50 - 3.13

◼ N/Agf’c = 0.00 - 0.35

◼ Vn,psi = 1.1 – 12.3 √f’c

◼ Failure modes

Validation

16

Spec.

No.Spec. ID Author

Cross-

sectionh/lw

fyBE

(MPa)

rb,v

(%)

rw,v

(%)

rw,h

(%)M/(Vlw) P/(Agf

'c)

Vmax/(Acv√f'c)

(psi)

Failure

Mode 1)

1 RW1 Thomsen and Wallace R 3.00 434 1.15 0.33 0.33 3.13 0.11 2.6 BR

2 RW2 Thomsen and Wallace R 3.00 434 1.15 0.33 0.33 3.13 0.09 2.7 CB

3 SP1 Tran and Wallace R 2.00 472 3.23 0.27 0.27 2.00 0.10 3.8 DT

4 SP2 Tran and Wallace R 2.00 477 7.11 0.61 0.61 2.00 0.10 6.3 CB

5 SP3 Tran and Wallace R 1.50 472 3.23 0.32 0.32 1.50 0.10 5.1 CB

6 SP4 Tran and Wallace R 1.50 477 6.06 0.73 0.73 1.50 0.10 7.8 DC

7 SP5 Tran and Wallace R 1.50 477 6.06 0.61 0.61 1.50 0.03 6.4 DC

8 R1 Oesterle et al R 2.34 512 1.47 0.25 0.31 2.40 0.00 1.1 BR

9 R2 Oesterle et al R 2.34 450 4.00 0.25 0.31 2.40 0.00 2.1 BR

10 B1 Oesterle et al B 2.34 449.5 1.11 0.29 0.31 2.40 0.00 2.4 R

11 B2 Oesterle et al B 2.34 410.2 3.67 0.29 0.63 2.40 0.00 6.0 BR

12 B3 Oesterle et al B 2.34 437.8 1.11 0.29 0.31 2.40 0.00 2.6 BR

13 B4 Oesterle et al B 2.34 450.2 1.11 0.29 0.31 2.40 0.00 2.8 CB

14 B5 Oesterle et al B 2.34 444.0 3.67 0.29 0.63 2.40 0.00 7.1 BR

15 B6 Oesterle et al B 2.34 441 3.67 0.29 0.63 2.40 0.13 12.9 CB

16 B7 Oesterle et al B 2.34 458 3.67 0.29 0.63 2.40 0.08 9.2 R

17 B8 Oesterle et al B 2.34 447 3.67 0.29 1.38 2.40 0.09 10.1 BR

18 B9 Oesterle et al B 2.34 430 3.67 0.29 0.63 2.40 0.09 9.7 BR

19 B10 Oesterle et al B 2.34 447 1.97 0.29 0.42 2.40 0.09 7.2 CB

20 F1 Oesterle et al F 2.34 444.7 3.89 0.30 0.71 2.40 0.00 8.4 BR

21 F2 Oesterle et al F 2.34 430 4.35 0.31 0.63 2.40 0.07 9.2 CB

22 WSH1 Dazio et al R 2.02 548 1.32 0.30 0.25 2.28 0.06 2.0 R

23 WSH2 Dazio et al R 2.02 583 1.32 0.30 0.25 2.28 0.06 2.3 BR

24 WSH3 Dazio et al R 2.02 601 1.54 0.54 0.25 2.28 0.06 2.9 BR

25 WSH4 Dazio et al R 2.02 576 1.54 0.54 0.25 2.28 0.06 2.8 CB

26 WSH5 Dazio et al R 2.02 584 0.67 0.27 0.25 2.28 0.14 2.8 BR

27 WSH6 Dazio et al R 2.02 576 1.54 0.54 0.25 2.26 0.11 3.6 CB

28 W1 Liu R 3.13 458 1.24 0.54 0.40 3.13 0.08 2.3 CB

29 W2 Liu R 3.13 458 1.24 0.27 0.47 3.13 0.04 1.7 BR

30 W3 Tupper R 3.13 458 1.24 0.54 0.40 3.13 0.08 2.3 CB

31 SW4 Pilakoutas and Elnashai R 2.00 500 6.30 0.79 0.39 2.00 0.00 5.1 CB

32 SW5 Pilakoutas and Elnashai R 2.00 530 9.60 0.79 0.35 2.00 0.00 5.0 DC

33 SW6 Pilakoutas and Elnashai R 2.00 500 6.30 0.79 0.35 2.00 0.00 4.7 DC

34 SW7 Pilakoutas and Elnashai R 2.00 530 9.60 0.79 0.39 2.00 0.00 6.6 BR

35 SW8 Pilakoutas and Elnashai R 2.00 530 6.50 0.79 0.42 2.00 0.00 5.0 BR

36 SW9 Pilakoutas and Elnashai R 2.00 530 6.50 0.79 0.60 2.00 0.00 6.6 CB

37 SW7 Zhang and Wang R 2.14 305 0.88 0.67 1.01 1.80 0.24 6.0 BR

38 SW8 Zhang and Wang R 2.14 305 0.65 0.67 1.01 1.80 0.35 6.4 CB

39 SW9 Zhang and Wang R 2.14 305 1.80 0.67 1.01 1.80 0.24 8.3 CB

40 SRCW12 Zhang and Wang R 2.14 305 1.53 0.67 1.01 1.80 0.35 8.2 CB

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WSH4h/l = 2.34vn = 9.2√f’cN/Agf’c= 8%

h/l = 2.0vn = 2.8√f’cN/Agf’c= 6%

h/l = 3.13vn = 1.7√f’cN/Agf’c= 4%

h/l = 2.14vn = 6.4√f’cN/Agf’c=35%

h/l = 3.0vn = 2.7√f’cN/Agf’c= 9%

h/l = 1.5vn = 7.8√f’cN/Agf’c= 7%

h/l = 1.5vn = 6.4√f’cN/Agf’c=2.5%

h/l = 2.34vn = 2.1√f’cN/Agf’c= 0

RW-A15-P10-S78 RW-A15-P2.5-S6.4 R2

W2 SW8B7

RW2

Validation: Planar Walls

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Validation: Planar Walls

Vertical Strain Profiles at Wall Base

Axial Growth at Wall TopCracking Pattern

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3D Models for RC Walls◼ Validation

◼ Nonplanar walls under biaxial loading

19

Beyer et al. (2008)

Constantin (2013)

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3D Models for RC Walls◼ TUC (Constantin, 2016)

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3D Models for RC Walls◼ Validation

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Development & Validation◼ New 3D OpenSees Models for RC Walls

◼ MVLEM_3D

◼ SFI_MVLEM_3D

◼ quadWall

◼ Validation

◼ Planar wall subjected to uni-directional loading

◼ Nonplanar walls subjected to multi-directional loading

◼ Reasonable prediction of global and local responses

◼ Implementation and public release in 2019

◼ Wiki Pages

◼ Examples

Macro models

FE model

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Related Ongoing Work

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Resilient-Based Design of Tall Buildings◼ Analysis of tall RC core wall buildings

using new OpenSees model

◼ Assessment of structural and nonstructural components

◼ Loss and downtime estimation

◼ Varying design parameters to find optimal design solution

◼ Applications of new materials and technology

◼ Collaboration Vesna Terzic (CSULB)

◼ CMMI: 1563428 & 1563577

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System-Level Analysis ◼ System-level

behavior

◼ Component interactions

◼ 3D System Tests

◼ E-Defense tests:

◼ 4-story (2011)

◼ 10-story (2015, 2019)

◼ IZIIS tests:

◼ 3-story coupled walls (2019)

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Acknowledgements◼ CSUF Students

◼ Carlos Garcia

◼ Ben Chan

◼ Nathanael Rea

◼ Kamiar Kalbasi

◼ Ross Miller

◼ Colleagues

◼ John Wallace, UCLA

◼ Kutay Orakcal, Bogazici University

◼ Vesna Terzic, Cal State Long Beach