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Resilience
Engineering for
Urban Tunneling
Edited by
Michael Beer, Dr.-Ing.
Hongwei Huang, Ph.D.
Bilal M. Ayyub, Ph.D., P.E.
Dongming Zhang, Ph.D.
Brian M. Phillips, Ph.D.
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INFRASTRUCTURE RESILIENCE PUBLICATION NO. 2
Resilience Engineering
for Urban Tunnels
Edited by
Michael Beer, Dr.-Ing.
Hongwei Huang, Ph.D.
Bilal M. Ayyub, Ph.D., P.E.
Dongming Zhang, Ph.D.
Brian M. Phillips, Ph.D.
Sponsored by
Center for Technology and Systems Management, University of Maryland
Institute for Risk and Reliability, Leibniz Universität Hannover
Tongji University
China Civil Engineering Society
Institute for Risk and Uncertainty, University of Liverpool
Infrastructure Resilience Division of the
American Society of Civil Engineers
Published by the American Society of Civil Engineers
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Library of Congress Cataloging-in-Publication Data
Names: International Workshop on Resilience of Urban Tunnels (2016 : College Park, Md.) |
Beer, Michael, editor. | Huang, Hongwei, editor. | Ayyub, Bilal M., editor. | Zhang, Dongming,
editor. | Phillips, Brian M., editor. | Center for Technology and Systems Management, sponsoring
body.
Title: Resilience engineering for urban tunnels / sponsored by Center for Technology and Systems
Management, University of Maryland, Institute for Risk and Reliability, Leibniz Universitt Hannover,
Tongji University, China Civil Engineering Society, Institute for Risk and Uncertainty, University of
Liverpool, Infrastructure Resilience Division of the American Society of Civil Engineers ; edited by
Michael Beer, Dr.-Ing, Hongwei Huang, Ph.D., Bilal M. Ayyub, Ph.D., P.E., Dongming Zhang, Ph.D.,
Brian M. Phillips, Ph.D.
Description: Reston, Virginia : American Society of Civil Engineers, [2018] | Series: Infrastructure
resilience publication ; no. 2 | Includes bibliographical references and index.
Identifiers: LCCN 2018028802 | ISBN 9780784415139 (soft cover : alk. paper) | ISBN
9780784481813 (pdf) | ISBN 9780784481820 (epub)
Subjects: LCSH: Tunnels–Design and construction–Congresses. | Tunnels–Reliability—
Congresses. | Urban transportation–Congresses.
Classification: LCC TA800.I73 2016 | DDC 624.1/93–dc23
LC record available at https://lccn.loc.gov/2018028802
Published by American Society of Civil Engineers
1801 Alexander Bell Drive
Reston, Virginia 20191-4382
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1 2 3
4 5
Photo credit: Front cover photograph courtesy of Dongming Zhang.
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Contents
Preface................................................................................................................................................. v
Acknowledgments .......................................................................................................................vii
Attendees and Affiliations ........................................................................................................ ix
Introduction ..................................................................................................................................... xi
Keynote Speaker Papers
Enhancing Civil Infrastructure Resilience with Structural
Health Monitoring ............................................................................................. 3
Yunfeng Zhang, Bilal Ayyub, and Hongwei Huang
Reliability Analysis and Real-Time Predictions in Mechanized
Tunneling .......................................................................................................... 13
Günther Meschke, Ba Trung Cao, and Steffen Freitag
Non-intrusive Inspection and Real-Time Monitoring for Tunnel
Structural Resilience........................................................................................ 29
Hongwei Huang and Dongming Zhang
Efficient Reliability and Risk Analysis of Complex Interconnected
Systems .............................................................................................................. 43
J. Behrensdorf, M. Broggi, and M. Beer
Enhancing Resilience of Traffic Networks with a Focus on Impacts
of Neuralgic Points Like Urban Tunnels ..................................................... 55
Katharina Klemt-Albert, Robert Hartung, and Sascha Bahlau
Reliability of Critical Infrastructure Networks: Challenges...................... 71
Konstantin M. Zuev and Michael Beer
Decision Aids for Tunneling .......................................................................... 83
Herbert H. Einstein
Breakout Session Reports
Topic 1: Monitoring for Resiliency of Urban Tunnels .............................. 89
Topic 2: Robust Design of Tunnels .............................................................. 95
Topic 3: Modeling and Management of Uncertainties............................. 99
iii
iv
CONTENTS
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Research Recommendations
1. Monitoring for Resiliency of Urban Tunnels .......................................105
2. Robust Monitoring and Maintenance for Durability..........................107
3. Resilience Engineering at System Scale ...............................................109
Index................................................................................................................................................115
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Preface
This report addresses the area of resilience engineering with specific emphasis on
urban tunnels and their embedding into civil infrastructure systems. It provides
bases for developing a comprehensive overall approach to resilience of urban
tunnels. The contributions in this report cover the state of the art from various
relevant perspectives, as well as conclusions made for perspective developments.
As such, this report provides a source for students and researchers interested in
resilience of urban tunnel and infrastructure to get a quick impression on the state
of development. It may also serve as a resource for practitioners to adopt recent
developments for current and future engineering projects to address and increase
resilience. Eventually, the report will increase awareness of the significant importance of resilience among authorities to implement requirements to ensure
sustained societal and economic benefits.
The state of the art is represented in seven invited papers. The paper by Zhang
and Ayyub describes pathways for using integrated structural health monitoring to
enhance the resilience of civil infrastructure. Meschke, Cao, and Freitag report on
recent developments for controlling mechanized tunneling using real-time predictions for ensuring structural reliability. An advanced technology for real-time
monitoring of tunnels is presented by Huang and Zhang, where non-intrusive
inspections are used to ensure tunnel resilience. These three contributions
demonstrate the current level of achievement in the area using advanced engineering models and technologies. In addition, they provide a perspective for
further developments expanding from this platform. The remaining papers
address selected specific challenges and ideas for solution that seek their synergetic
marriage with the broad powerful platform to form a comprehensive overall
framework to address resilience of urban tunnels at large. Behrensdorf, Broggi,
and Beer explore a numerical concept for assessing the reliability of complex
interconnected systems. Klemt-Albert, Hartung, and Bahlau discuss the criticality
of neuralgic points in traffic networks in view of enhancing resilience. Zuev and
Beer highlight issues and potential solutions when assessing reliability of networks
of critical infrastructure. Eventually, Einstein documents the importance of
decision aids in tunneling with respect to risk and resilience.
The second part of this report is built on the discussions from the First
International Workshop on Resiliency of Urban Tunnels (Reston, Virginia, USA,
September 1, 2016) and the conclusions drawn for perspective developments. This
part is structured in conclusions from three breakout session reports, and three
structured research recommendations on the key topics are identified. The first
breakout session report concerns the monitoring for resiliency of urban tunnels.
The second report refers to robust design of tunnels. Third, the modeling and
v
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vi
PREFACE
management of uncertainties is considered. The reports in these three topic areas
summarize synergetic findings and advice from expert discussions as a guide for
future developments. They were used as a basis to develop three structured
research recommendations, which were rolled out after the breakout session
reports. The first recommendation is focused on developments on monitoring for
resiliency of urban tunnels. The second concerns robust monitoring and maintenance for durability. The third is devoted to resilience engineering at a system
scale. These recommendations are intended to be developed into large-scale
research programs.
All materials presented in this report were peer reviewed according to the
standards of ASCE.
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Acknowledgments
The organizers of the First International Workshop on Resiliency of Urban
Tunnels, held in Reston, Virginia, USA, September 1, 2016,
Michael Beer, Leibniz Universität Hannover, Germany
Hongwei Huang, Tongji University, Shanghai, China
Bilal M. Ayyub, University of Maryland, College Park, USA
would like to express their sincere appreciation to the keynote speakers
Yunfeng Zhang, University of Maryland, College Park, USA
Günther Meschke, Ruhr Universität Bochum, Germany
Loic Galisson, Soldata Group, USA
Charng Hsein Juang, Clemson University, USA
Sez Atamturktur, Clemson University, USA
Konstantin M. Zuev, California Institute of Technology, USA
Herbert H. Einstein, Massachusetts Institute of Technology, USA
Bill Bergeson, Federal Highway Administration, USA
Brian Wolfe, Maryland Transportation Authority, USA
for their inspiring contributions. Highly appreciated are the contributions by all
authors of the invited papers and of the breakout session reports. For providing
high-quality service we thank our reviewers and the facilitators of the breakout
sessions. Particular thanks are conveyed to
Brian Phillips, University of Maryland, College Park, USA
Dongming Zhang, Tongji University, Shanghai, China
for their marvelous preparation of this report.
For the financial support we thank the
American Society of Civil Engineers
and for supporting organization, travel, and attendance we thank
Leibniz Universität Hannover, Germany
University of Liverpool, UK
University of Maryland, College Park, USA
Tongji University, China
China Civil Engineering Society
National Natural Science Foundation, China
Shanghai Science and Technology Committee, China
Peak Discipline Construction on Civil Engineering of Shanghai, China.
vii
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Attendees and Affiliations
Last
First
Amare
Ariaratnam
Atamturktur
Ayyub
Beer
Bergeson
Broggi
Butry
Tekeste
Samuel
Sez
Bilal
Michael
Bill
Matteo
David
Einstein
Herbert
Galisson
Gong
Huang
Irias
Juang
Klemt-Albert
McLeod
McPherson
Meschke
Nie
Ning
Phillips
Saadat
Sansavini
Shou
Topa Gomes
Wu
Xie
Xiong
Zhang
Zhang
Zhang
Zhang
Zhou
Zuev
Loic
Wenping
Hongwei
Xavier
Hsein
Katharina
Marshall
David
Günther
Xingyao
Zhangwei
Brian
Yalda
Giovanni
Kehjian (Albert)
António
Jingzhe
Xiongyao
Haocheng
Dongming
Jie
Yunfeng
Yinning
Biao
Konstantin
Affiliation
Maryland Transportation Authority
Arizona State University
Clemson University
University of Maryland
Leibniz Universität Hannover
Federal Highway Administration
Leibniz Universität Hannover
National Institute of Standards and
Technology (NIST)
Massachusetts Institute of Technology
(MIT)
Soldata Northern America
Clemson University
Tongji University
East Bay Municipal Utility District
Clemson University
Leibniz Universität Hannover
East Bay Municipal Utility District
HDR, Inc.
Ruhr University Bochum
Tongji University
Soldata Northern America
University of Maryland
University of Maryland
ETH Zurich
National Chung-Hsing University
University of Porto
University of Maryland
Tongji University
Virginia Tech
Tongji University
Clemson University
University of Maryland
Virginia Tech
Tongji University
California Institute of Technology
ix
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Introduction
Urban tunnels nowadays play a quite significant role in transportation systems,
not only to make transportation more efficient avoiding congestions but also to
improve the quality of life in metropolitan areas by removing traffic from the
living environment. As the number of urban tunnels increases incredibly, questions and concerns regarding their safe operation, potential vulnerability and
recovery after intentional or unexpected disruption have become central issues not
only among engineers and stakeholders but also in the society and governmental
administration. Clearly, this situation is calling for a generalized structured
approach not only for assessing, mitigating and managing risk but actually for
a comprehensive resilient design and operation. However, in practice, operation
and maintenance of tunnels is largely realized through heuristic approaches.
Current research and practice show a key deficiency: while significant efforts have
been made on risk assessment, only little has been done for risk control including
resilience of underground structures, thus resulting in unexpected economic
losses. An application-oriented method for dynamic risk control and resilient
design is of great necessity for the safe operation of our underground systems. As a
particular technical challenge, this approach needs to combine elements from
structural engineering and systems engineering. Moreover, it needs to include a
large monitoring component, and it needs to be dynamic to account for rapid
changes in system states and conditions. In operating such ever-growing infrastructure systems, the risk associated with tunnels has become a focus of the
government and the public in the world. Since this situation does not only apply
to one country or society but is a global problem, it can be addressed best with
joint forces.
With this mission in mind, we have brought together more than 30 selected
researchers in the areas of geotechnical, structural and system risk from the United
States, China, Germany, and with diverse responsibilities from academic, industrial, and governmental perspectives. To identify a clearly structured research
agenda for the development of a dynamic risk control and resilient design
approach, the workshop covered three major topics including smart sensing,
robust design and uncertainty modeling. Seven keynotes covering the aforementioned three topics were delivered by distinguished researchers in each area. After
a seed discussion, seven subtopics were identified with the goal of driving projects
in global collaborations. The first topic covers monitoring for urban tunnel
resilience. The second topic addresses robustness against uncertainties in the
construction. The third topic puts efforts on the integrated robust design through
modularity and adaptability. The fourth topic is devoted to robust monitoring and
maintenance for durability. The fifth topic concerns generalized modeling for
xi
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xii
INTRODUCTION
resilience engineering with a component scale and a systems scale perspective.
The sixth topic covers resilience-informed decision making, and the last topic
addresses multisector interdependencies in the resiliency modeling.
With this structure the workshop was cumulated in the development of largescale research proposals by the attendees, which are all synchronized. In combination of the developments we then aim for a comprehensive overall approach to
resilience of urban tunnels to be established within a reasonably short time. To
monitor the developments and their interaction, this workshop is expanded into a
series of annual meetings around the world, rotating between America, Europe,
and Asia.
Michael Beer, Chair
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KEYNOTE SPEAKER PAPERS
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CHAPTER 1
Enhancing Civil Infrastructure
Resilience with Structural
Health Monitoring
Yunfeng Zhang*
Bilal Ayyub*
Hongwei Huang†
Abstract: In natural hazardous events such as strong earthquakes, engineers are
usually faced with many competing priorities in making safety and occupancy
decisions about large inventories of civil infrastructure building and bridge assets
and usually there is shortage in experienced engineers available for inspection and
repair work. For structural members hidden behind drywall or ceilings, inspection is
particularly time consuming and costly because those nonstructural components
have to be removed first. One of the ultimate goals in inspection is to quickly and
accurately determine the residual capacity (in strength and deformation) of
structural members to assure structural safety in future events such as aftershocks.
Structural health monitoring (SHM) technologies are useful for rapid structural
condition assessment especially for many hidden locations after major hazardous
events. This paper describes a strategy for enhancing structural resilience by
integrating innovative SHM technologies focused on limited number of structural
fuse members within resilient structures. The proposed framework will be helpful in
facilitating the implementation of SHM technologies into civil infrastructures by
quantifying and comparing the resilience metrics of different SHM options.
INTRODUCTION
After natural hazardous events such as strong earthquakes, engineers are usually
faced with many competing priorities in making safety and occupancy decisions
about large inventories of building and bridge assets and usually there is shortage
*
Department of Civil & Environmental Engineering, University of Maryland at College Park, USA
†
Department of Geotechnical Engineering, Tongji University, Shanghai, China
3
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4
RESILIENCE ENGINEERING FOR URBAN TUNNELS
in experienced engineers available for inspection and repair work. However, most
of the post-hazard inspections and structural condition assessment are performed
manually at present. Intensive labor, high cost and variable results are typical of
manual operation.
In buildings, structural members are often hidden behind fireproof coating
and drywalls, and thus buckling or yielding of these hidden steel members are
difficult to detect, often requiring removal of coverings and thus time consuming
and costly. For example, a steel tube brace hidden behind drywalls in a 4-story
office building buckled and then fractured in the 1994 Northridge earthquake
(Tremblay et al. 1994; Sabelli et al. 2013). Tremblay et al. (1995) reported that
“The building remained plumb following the earthquake : : : the initial assessment of the structure by the owner’s representative prior to the review engineer
arriving on site was that the structure had not sustained much damage (only one
window had been broken). Only after the preliminary assessed cosmetic damage
to the dry wall was removed, at the order of the engineer, was the extent of damage
revealed and proper assessment of the structure could begin.” In a more recent
event, the 22-story Pacific Residential Tower in Christchurch was green-tagged
following the MW 6.2 Christchurch earthquake of February 2011, indicating that
they were safe to occupy but would require some minor repairs of non-structural
components (Clifton et al. 2012). In the 2011 Christchurch earthquake, numerous
eccentrically braced frames (EBFs) buildings were found to yield in the link beam
that typically exhibits paint flaking and Luder lines (Grilli et al. 2012, Clifton et al.
2012). For a 12-story EBF building damaged in this 2011 earthquake, estimates of
the peak inelastic demand in the active link were made through visible assessment
of the active link yielded web metal and secondly through estimation of the peak
inter-story building drift and conversion of this to a peak inelastic demand in the
EBF active links (Clifton et al. 2012). If the link beam were instrumented, peak
shear strain in the links would have been determined much faster and more
accurately. Clearly from these two real examples, it can be concluded that visual
signs of minor cosmetic damage in non-structural elements do not give reliable
results in revealing the actual severe damage sustained by hidden structural
members.
SHM technologies are useful for rapid structural condition assessment
especially for many hidden locations after major hazardous events. Under extreme
loading such as strong earthquakes or winds, structural members in steel
structures could fail in buckling or yielding. However, assessment by inexperienced workers is subject to a high degree of uncertainty and may lead to
misleading judgment on structural condition and safety. Civil structures could
be more effectively managed through automated inspection and computerized
condition assessment information processing. The replacement of our present-day
manual inspection with automated condition assessment would substantially
reduce the associated costs/downtime and enhance community resilience. Sensor
data from SHM systems provides the base data for real-time updating of the
structural condition and reliability.
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ENHANCING CIVIL INFRASTRUCTURE RESILIENCE WITH STRUCTURAL
HEALTH MONITORING
5
Structural health monitoring (SHM) is also helpful to understand the safety
state of the geostructures, in particular for large-scaled distributed geo-systems
such as metro tunnel networks (O’Rourke, 2010). It is recognized that sensing and
monitoring systems could support engineering judgement and even complement
it especially for the case of a ductile performance response but will not attempt to
replace it (Huang and Zhang 2016).
New design trends for seismic resistant structures is to incorporate fuse
members (sacrificial elements to dissipate energy) into structures so that damage
is concentrated to fuse members while other parts of the structure remain
undamaged during design level earthquakes. Few implementations of the structural
fuse concept have been rigorous in emphasizing easy replaceability of the sacrificial
elements and absence of damage to the primary structural system (El-Bahey and
Bruneau 2011). Examples of structural fuses are buckling restrained braces (BRBs),
steel shear links and slit steel plate wall with buckling restrain cover plate. Such
structure design concept is also appealing to SHM since condition assessment or
monitoring work can now be focused on a limited number of fuse members. For
such smart fuse members instrumented with sensors, automated structural health
monitoring of fuse zone for possible damages inflicted by earthquakes or strong
winds could be performed in a very efficient way and this practice would greatly
accelerate condition assessment and thus enhance resilience through shorter and
more accurate inspection. Consequently, decision on whether to do structural repair
or no need for evacuation could be made after extreme events.
In certain types of structural fuses such as BRBs (El-Bahey and Bruneau 2011)
and buckling restrained slit steel plate wall (Sun et al. 2011), crack was seen to
develop, and the steel core plate eventually fractured when they sustain severe
plastic deformation in order to dissipate energy. An important question to address
is how to detect the crack before the steel core plate completely fractures, but this
has been found to be very difficult because the steel core plate is hidden behind the
buckling restraining members and direct access to the interior steel core plate for
visual inspection is not an option before those buckling restraining members can
be removed. Therefore, SHM technology that can remotely monitor the plastic
deformation development and cracks is desired for condition assessment of such
structural fuse members.
This paper presents preliminary research work toward integrating SHM
technologies with resilient civil infrastructure design and establishing a resilience
metric for rating candidate SHM technologies. As a demonstration of SHM
feasibility in resilience enhancement by reducing post-hazard inspection and
recovery time, wireless scanning for strain information using RFID based passive
wireless sensor without the need for battery, is described. Preliminary experimental results have suggested this method is very promising for structural condition
assessment. This novel BT sensor is developed for detection of surpassing prespecified threshold strain level and thus can be used for monitoring steel yielding
and buckling occurrence. The BT sensor uses a special design of trigger device to
activate the sensor and RFID tag for wireless damage scanning.
6
RESILIENCE ENGINEERING FOR URBAN TUNNELS
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RESILIENCE METRICS FOR RATING STRUCTURAL HEALTH
MONITORING TECHNOLOGY
Most of the post-hazard inspections and structural condition assessment are
performed manually at present. Intensive labor, high cost and variable results
are typical of manual operation. The replacement of our present-day manual
inspection with automated condition assessment would substantially reduce the
associated costs/downtime and enhance community resilience. SHM technology
targeting such fuse members are thus of importance in the context of rapid posthazard structural condition inspection and recovery. With the advancement in
this field, several SHM techniques will be proposed for a specific type of structural
fuse and how to rate the performance of these SHM technique candidates becomes
an important issue in the process of choosing the cost-effective SHM technology
for the fuse condition assessment application. This practice would greatly
accelerate condition assessment and thus enhance resilience through shorter and
more accurate inspection, as shown in Figure 1. Consequently, decision on
whether to do structural repair or no need for evacuation could be made after
extreme events.
Resilience may be defined as a function indicating the capability to sustain a
level of functionality, or performance, for a given building, bridge, lifeline network,
or community, over a period defined as the control time (Renschler et al. 2010).
The change in functionality due to strong earthquake or wind events is characterized by a drop, representing a loss of functionality and a recovery as shown in
Figure 1.
The following resilience metrics was proposed by Ayyub (2014) based on this
definition that meet logically consistent requirements drawn partly from measure
theory and provide a basis for the development of effective decision-making tools
for multi-hazard environments.
ResilienceðRe Þ =
T i þ FΔT f þ RΔT r
T i þ ΔT f þ ΔT r
(1-1)
Figure 1. Resilience enhancement through rapid structural condition assessment
7
ENHANCING CIVIL INFRASTRUCTURE RESILIENCE WITH STRUCTURAL
HEALTH MONITORING
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where for any failure event (f ) as illustrated in Figure 8, the corresponding failure
profile F and the corresponding recovery profile R are measured as follows:
R tr
R tf
FailureðFÞ =
t i f dt
,
R tf
t i Qdt
tf
rdt
tf
Qdt
RecoveryðRÞ = R t r
(1-2)
The failure-profile value (F) can be considered as a measure of robustness and
redundancy; whereas the recovery-profile value I can be considered as a measure
of resourcefulness and rapidity. Q is defined as the system’s performance in terms
of its strength (S) minus the corresponding load effect (L) in consistent units,
i.e., Q = S − L. Both L and S are treated as random variables, the time to failure
(Tf) can be characterized by its probability density function that can be found in
the work by Ayyub (2014). The primary basis for evaluating Eqn. 1 is the
definition of performance (Q) at the system level with meaningful and appropriate
units, followed by the development of an appropriate breakdown for this performance, using what is termed herein as performance segregation.
In previous definition of resilience metrics, SHM is not explicitly considered;
rather structural condition assessment (inspection or SHM) is implicitly included
in the recovery phase. In order to rate the performance of civil infrastructures that
might be designed with different candidate SHM systems, the above resilience
metric is proposed by explicitly considering the inspection phase of the recovery
process. This becomes an important issue in the process of choosing the most costeffective SHM technology for practical implementation.
ResilienceðRe Þ =
FailureðF m Þ =
R tm
t
R tmi
ti
t i þ F m ΔT m þ Rm ΔT r
t i þ ΔT m þ ΔT r
Q · ΔT m
= Rtrue
,
tm
Qdt
t i Qdt
f dt
(1-3)
R tr
t
rdt
tm
Qdt
RecoveryðRm Þ = R trm
(1-4)
where f = Qtrue, a random variable that represents the true condition of civil
infrastructures (see the horizontal green line in Figure 2); ΔTm = total inspection
(or SHM) time taken to get closer enough (error between Qphase_i and Qtrue <
acceptable value) to the true condition Qtrue. Qphase_i is a random variable that
represents the condition assessment result from the ith phase in SHM process. For
certain hazardous events such as earthquakes, ΔTf ( = Tf − Ti) is typically very short
(often less than a minute) and thus neglected here for simplicity. ti is thus
approximately equal to Time to failure (tf), which has the following density function:
d
ti = −
dt
Z∞
c=0
Zt
1
exp −λt 1 −
F L ðαðτÞsÞdτ f S0 ðsÞds
t
τ=0
(1-5)