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«By SIAMAK SATTAR B.S., Azad University of Najafabad, Iran, 2004 M.S., Mazandaran University of Science and Technology, Iran, 2007 M.S., University of ...»

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INFLUENCE OF MASONRY INFILL WALLS AND OTHER BUILDING

CHARACTERISTICS ON SEISMIC COLLAPSE OF CONCRETE FRAME BUILDINGS

By

SIAMAK SATTAR

B.S., Azad University of Najafabad, Iran, 2004

M.S., Mazandaran University of Science and Technology, Iran, 2007

M.S., University of Colorado Boulder, 2010

A thesis submitted to the

Faculty of Graduate School of the University of Colorado in partial fulfillment Of the requirement for the degree of Doctor of Philosophy Department of Civil, Environmental and Architectural Engineering

This thesis entitled:

Influence of Masonry Infill Walls and Other Building Characteristics on Seismic Collapse of Concrete Frame Buildings written by Siamak Sattar has been approved for the Department of Civil, Environmental, and Architectural Engineering ______________________________________________

(Abbie Liel) ______________________________________________

(Guido Camata) ______________________________________________

(Kenneth Elwood) ______________________________________________

(Keith Porter) ______________________________________________

(Yunping Xi) Date____________

The final copy of this thesis has been examined by the signatories, and we find that both the content and the form meet acceptable presentation standards of scholarly work in the above mentioned discipline Abstract Siamak Sattar (Ph.D., Civil, Environmental and Architectural Engineering) Thesis title: Influence of Masonry Infill Walls and Other Building Characteristics on Seismic Collapse of Concrete Frame Buildings Thesis directed by Assistant Professor Abbie Liel Reinforced concrete frame buildings with masonry infill walls have been built all around the world, specifically in the high seismic regions in US. Observations from past earthquakes show that these buildings can endanger the life of their occupants and lead to significant damage and loss. Masonry infilled frames built before the development of new seismic regulations are more susceptible to collapse given an earthquake event. These vulnerable buildings are known as non-ductile concrete frames. Therefore, there is a need for a comprehensive collapse assessment of these buildings in order to limit the loss in regions with masonry infilled frame buildings.

The main component of this research involves assessing the collapse performance of masonry infilled, non-ductile, reinforced concrete frames in the Performance Based Earthquake Engineering (PBEE) framework. To pursue this goal, this study first develops a new multi-scale modeling approach to simulate the response of masonry infilled frames up to the point of collapse. In this approach, a macro (strut) model of the structure is developed from the response extracted from a micro (finite element) model specific to the infill and frame configuration of interest. The macro model takes advantage of the accuracy of the micro model, yet is computationally efficient for use in seismic performance assessments requiring repeated nonlinear dynamic analyses. The robustness of the proposed multi-scale modeling approach is examined through comparison with selected experimental results.

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performance of a set of archetypical buildings, representative of the 1920s era of construction in Los Angeles, California. The collapse performance assessment is conducted for buildings with varying height and infill configurations. Dynamic analyses are performed for the constructed nonlinear models. Results of this study capture the influence the infill panel has on the collapse performance of the frame. This assessment is also used to investigate the significant difference infill configurations have on the collapse performance of the frame. These results can be used to prioritize mitigation of the most vulnerable RC frames.

This research also examines the collapse performance of non-ductile RC frames without infill walls. One of the primary goals in the seismic assessment procedure used in this study is to identify the hazardous buildings that are in critical need of rehabilitation. These buildings are known as “killer buildings.” In order to reduce the seismic hazard risk, we need a simple evaluation methodology for existing buildings that can quickly identify the killer buildings. In this evaluation methodology, the collapse safety of the buildings is defined as a function of a set of parameters that are known to significantly affect the risk of building collapse. These parameters are known as “collapse indicators.” This research uses these collapse indicators to examine the trend between the collapse risk and variation of each indicator. In addition, this study investigates the relation between building collapse and the extent of deficiency. The extent of the deficiency is defined by the number or percentage of the deficient elements, for instance number of columns with wide transverse reinforcement spacing, in the story of interest. These results are used to investigate the appropriate definition of these collapse indicators in the evaluation methodology.

–  –  –

to quantify the uncertainty embedded in the nonlinear model used in nonlinear dynamic analysis.





In the last part of this study, a new methodology is proposed to quantify modeling uncertainty through a set of drift distributions derived from data submitted to a blind prediction contest conducted at UCSD (2007). In this contest, participants were asked to develop models for predicting the experimental seismic response of a building. After quantifying the modeling uncertainty, this source of uncertainty is combined with another source of uncertainty, known as record-to-record uncertainty, in order to measure the total uncertainty in the assessment procedure. This study is conducted on a concrete wall bearing system, to identify the extent of modeling uncertainty. This methodology can then be implemented to other structural systems if the corresponding blind prediction data are available.

–  –  –

My wife, Maryam and my parents, Mohammadjavad and Badri Acknowledgment I am grateful to many individuals whom I worked with during my Ph.D. I would first like to thank my advisor, Professor Abbie Liel, for her guidance and support for this research and my overall graduate school career at University of Colorado at Boulder. I would also like to acknowledge my committee members Professors Ken Elwood, Guido Camata, Keith Porter, and Yunping Xi for serving on my research committee and providing thoughtful insight and comments on my research.

I am grateful for the opportunity to work on ATC-78 project during my Ph.D. In this project, I have had the opportunity to work with a group of knowledgeable and experienced people from industry and academia. I would like to thank all of them, including Mr. Bill Holmes, Prof. Jack Moehle, Drs. Mike Mehrain and Bob Hanson, and Mr. Panos Galanis and Peter Somers. Their suggestions and insights were very helpful in developing this work. This part of my research is funded by Applied Technology Council (through funding from FEMA), which is greatly appreciated.

I would also like to thank Drs. Maziar Partovi and Kesio Palacio from TNO DIANA for their valuable feedback on micro-modeling of masonry infilled frames, and Mr. Majid BaradaranShoraka from UBC, who graciously shared his code for triggering collapse. In addition, thank you to Prof. Paolo Martinelli from Politecnico di Milano for sharing the results of his nonlinear model used in quantifying modeling uncertainty.

I am grateful to all the people I worked with in my research group. I wish to thank my dear friends Holly Bonstrom, Meera Raghunandan, Cody Harrington, Jared DeBock, and Emily

–  –  –

provide feedback and encouragement, which has greatly motivated me throughout my work.

Above all, my special thanks to my wife, Maryam, for her support and patience during my studies, and to my parents Badri and Mohammadjavad for everything they have done for me.

–  –  –

1 Introduction

1.1 Motivation and Objectives

1.2 Organization

2 Behavior of Masonry Infilled Reinforced Concrete Frames

2.1 Overview

2.2 Failure Modes of Infilled RC Frames

2.3 Previous Research

2.3.1 Experimental Investigations

2.3.2 Analytical Investigations: Strut (Macro) Modeling of Masonry Infill Panel......... 17 2.3.3 Analytical Investigations: Finite Element (Micro) Modeling of Masonry Infilled Frames 27 3 Development of Micro-model of Masonry Infilled RC Frames for Use in Proposed MacroModel

3.1 Introduction to the Proposed Macro-Model

3.2 Introduction to Micro-modeling of Masonry Infilled Frames

3.3 Development of Calibrated Finite Element Model for Masonry Infilled RC Frames... 37 3.3.1 Selection of Software for Modeling of Masonry Infilled RC Frames

3.3.2 Overview of Micro-Model

3.4 Model Calibration and Validation through Finite Element Modeling of a Masonry Infilled Reinforced Concrete Frame Specimen

3.4.1 Overview

3.4.2 Experimental Tests

3.4.3 Proposed Finite Element Model for Experimental Specimen

–  –  –

3.4.5 Pushover Analysis of a Second Masonry Infilled Frame (Specimen 9).................. 63 3.5 Conclusions

4 Proposed Macro-Modeling Approach for Masonry Infilled Reinforced Concrete Frames... 67 4.1 Overview

4.2 Modeling of Masonry Infill Panel

4.2.1 Extraction of the Force-Displacement Relationship for the Infill Wall.................. 70 4.2.2 Multi-Linear Representation of Strut Force-Displacement Response

4.2.3 Strut Configuration in the Proposed Macro-model

4.3 Frame Modeling

4.3.1 Frame Modeling Overview

4.3.2 Flexural Failure Modeling of RC Beams and Columns

4.3.3 Shear and Flexure-Shear Failure Modeling of Non-Ductile RC Columns............. 80 4.3.4 Axial Failure Modeling of Non-Ductile RC Columns

4.4 Comparison of Macro-Model with Experimental Results for Two Infilled Frame Specimens

4.5 Application of Proposed Macro-model

4.6 Conclusions

5 Collapse Assessment of Masonry Infilled RC Frames Using Multi-scale Modeling Approach 5.1 Overview

5.2 Characteristics of RC Buildings in California for Case Study

5.2.1 Configuration of the Archetypical Buildings

5.3 Material Properties and Design of the Concrete Frames in Archetypical Buildings..... 98

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5.5 Overview of Modeling and Collapse Assessment Approach

5.5.1 Multi-scale Modeling Approach

5.5.2 Incremental Dynamic Analysis for Assessing Collapse Performance.................. 106 5.5.2.1 Collapse Definition

5.6 Micro-Modeling of the Archetypical Buildings

5.6.1 Properties of the Infill and Frame in the Micro-Model

5.7 Micro-Modeling Analysis and Results for Archetypical Buildings

5.7.1 Effect of Vertical Load in the Micro-model for Archetype Buildings................. 115 5.7.2 Pushover Results from the Micro-Models for Archetypical Buildings................ 117 5.7.3 Extracted Infill Force-Displacement Responses for Archetypical Buildings....... 119 5.8 Out-of-Plane Behavior of the Archetypical Building

5.9 Macro-Modeling of the Archetypical Buildings

5.10 Seismic Response of the Archetypical Buildings from Macro-Models

5.10.1 Static Pushover Analysis Results

5.10.2 Incremental Dynamic Analysis Results

5.11 Conclusions

6 Collapse Indicators for Existing Nonductile Concrete Buildings with Varying Column and Frame Characteristics

6.1 Objectives

6.2 Overview of the ATC-78 Project

6.2.1 Collapse Indicators

6.2.2 Collapse Indicator Evaluation Methodology

–  –  –

6.3 Study of Collapse Indicators in Case Study Building

6.3.1 Case Study Building

6.3.1.1 Building Design

6.3.1.2 Modeling and Collapse Simulation

6.3.2 Variation of Column to Beam Strength Ratio, Mc/Mb

6.3.2.1 Context and Mc/Mb Parameter Definition

6.3.2.2 Variation Mc/Mb in Uniform Building

6.3.2.3 Variation of Mc/Mb with Non-Uniform Mc/Mb Ratios

6.3.3 Variation of Adjacent Story Strength Ratio, Vi/Vi+1

6.3.3.1 Context and Vi/Vi+1 Parameter Definition

6.3.3.2 Variation Vi/Vi+1 in Building with Non-Uniform Frame Lines

6.3.4 Variation of Column Flexural-Shear Strength Ratio, Vp/Vn

6.3.4.1 Context and Vp/Vn Parameter Definition

6.3.4.2 Variation of Vp/Vn in Building with Non-Uniform Columns

6.4 Conclusions

7 Quantification of Modeling Uncertainties Based on the Blind Prediction Contest Submissions

7.1 Overview

7.2 Methodology of Study

7.3 Application of the Proposed Methodology

7.4 Combination of Modeling Uncertainty With RTR Uncertainty

7.5 Conclusions and Recommendations

8 Conclusion

–  –  –

8.2 Future Research

8.2.1 Modeling of Masonry Infilled RC Frames

8.2.2 Quantification of Modeling Uncertainty

–  –  –

Table 2-1. Summary of strut models developed for infill panels.

Table 2-2. Chronological improvements on in-plane modeling the masonry wall/infill.............. 34 Table 3-1. Modeling parameters and their definition for the interface model

Table 3-2. Model interface properties, illustrating the process of determining, first, tensile properties (row 1), second, monotonic shear properties (row 2), third, cyclic shear properties (row 3), fourth, dilatation (row 4), and fifth, prism sample (row 5).

Table 3-3. Properties of the total strain crack model to represent concrete behavior in the concrete frame and hollow bricks.

Table 3-4. Properties of total strain crack model used in model of bare frame.

Table 3-5. Steel material properties.

Table 3-6. Properties of the total strain crack model to represent the hollow concrete bricks in the FE model.

Table 3-7. Material properties of the head-joint and wall-to-frame joints.

Table 5-1. Steel and concrete material properties (reproduced from FEMA 356).



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