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

2013

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

iii

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.

iv

The proposed multi-scale modeling approach is implemented to assess the collapse

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.

v

An important aspect of the seismic assessment procedure presented in this dissertation is

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.

To:

My wife, Maryam

and my parents, Mohammadjavad and Badri

vii

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 Baradaran-

Shoraka 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

viii

Elwood for their support and insight through my graduate studies. They are always willing to

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.

ix

CONTENTS

1 Introduction ............................................................................................................................. 1

1.1 Motivation and Objectives ............................................................................................... 1

1.2 Organization ..................................................................................................................... 4

2 Behavior of Masonry Infilled Reinforced Concrete Frames ................................................... 6

2.1 Overview .......................................................................................................................... 6

2.2 Failure Modes of Infilled RC Frames .............................................................................. 6

2.3 Previous Research ...............................