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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
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
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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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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.
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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
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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
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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.
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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 ...............................