Civil Structural Health Monitoring Workshop (CSHM-6) Structural health monitoring of new and ageing infrastructure
Programme and Abstract Book
Queen’s University Belfast, Northern Ireland 26th – 27th May 2016
General Information
2 CSHM6
WORKSHOP VENUE
School of Planning, Architecture & Civil Engineering
Queen’s University Belfast
David Keir Building, 39‐123 Stranmillis Road
Belfast BT9 5AG, Northern Ireland
UK
Web: www.qub.ac.uk/space
SOCIAL PROGRAMME
Workshop Dinner at the Queen’s University Great Hall: 18:00 on
Thursday, 26th May 2016
Optional: Game of Thrones tour: 09:00 – 18:00 on Saturday, 28th May 2016
o Tour cost per person: £36
o Ticket(s) can be purchased at registration
EXHIBITION
Specialist companies in the field of Civil Structural Health Monitoring will
exhibit their equipment and capabilities.
List of Exhibitors
BeanAir; Berlin, Germany
HBM United Kingdom Ltd; Middlesex, UK
McFarland Associates Ltd; Belfast, Northern Ireland, UK
Sengenia Ltd; Dollingstown, Northern Ireland, UK
INTERNET SERVICE
Free internet access is available via wireless network. Login details will be
provided at registration. No technical support is provided; delegates must
assume responsibility for PC security.
Cover images adapted from photos: ©Copyright Stuart Yates; ©Copyright Rossographer
and licensed for reuse (https://creativecommons.org/licenses/by‐sa/2.0/deed.en)
General Information
CSHM6 3
WORKSHOP ORGANISATION
CO-CHAIRS
Prof. Su Taylor
Queen’s University Belfast, DKB, Stranmillis Rd, Belfast, BT9 5AG, Northern
Ireland, UK
Phone: +44 (0)28 90974010
Email: [email protected]; [email protected]
Dr.‐Ing. Wolfgang R. Habel
BAM Federal Institute for Materials Research and Testing, Unter den Eichen
87, 12205, Berlin, Germany
Phone: +49 30 8104‐1916
E‐mail: [email protected]
Secretariat
D. Hester, Queen’s University Belfast, UK
G. Amato, Queen’s University Belfast, UK
M. Lydon, Queen’s University Belfast, UK
Organising Committee
S. Taylor, Queen’s University Belfast, UK
F. Ansari, University of Illinois, Chicago, USA
S. Donohue, Queen’s University Belfast, UK
W. R. Habel, BAM, Berlin, Germany
B. McFarland, McFarland Associates Ltd, Belfast, UK
A. Mufti, University of Manitoba, Winnipeg, Canada
Programme Committee
S. Taylor, Queen’s University Belfast, UK
G. Amato, Queen’s University Belfast, UK
S. Donohue, Queen’s University Belfast, UK
D. Hester, Queen’s University Belfast, UK
M. Lydon, Queen’s University Belfast, UK
P. McGetrick, Queen’s University Belfast, UK
M. Sonebi, Queen’s University Belfast, UK
Workshop Topics
4 CSHM6
Structural health monitoring of new and ageing infrastructure
The Civil Structural Health Monitoring (CSHM) workshop was established to
promote discussion and develop sustainable solutions for infrastructure with
an extended service life. Key topics include developing an IT‐based bridge
health monitoring system, incorporating the latest information technologies
for lifetime management of existing bridges, and managing data collection
systems designed for bridge health monitoring.
The most recent CSHM workshops were held in Berlin, Germany Nov. 6‐8,
2012 and Yamaguchi, Japan Oct 24‐26, 2013 respectively. These workshops
provided a forum for the efficient exchange of ideas on the latest information
processing technologies applied to civil infrastructure and intelligent
structural health monitoring techniques.
The economic analysis of SHM methods was also discussed as in developed
countries the large proportion of aging small and medium infrastructure raises
concerns for long term management and impacts decision‐making on essential
civil infrastructure service life strategies.
This year at CSHM‐6 Belfast a new session on geotechnical monitoring of civil
infrastructure is introduced to extend the holistic approach to SHM of
infrastructure.
Topics for CSHM‐6 Belfast include:
• Monitoring strategies for the evaluation of structures exceeding
their design life
• Management of structures exceeding their design life
• Geotechnical monitoring of civil infrastructure to extend life and
improve safety
• Addressing challenges in the practical application of structural
health monitoring to civil infrastructure
Workshop Session Overview
CSHM6 5
The workshop has been divided into four sessions as follows:
Session 1: Sensors and structural health monitoring systems
Session 2: Structural health monitoring strategies for bridge structures
Session 3: Geotechnical monitoring of civil infrastructure
Session 4: Challenges in practical application of SHM systems
Each presentation is allocated 15 minutes in total; the session chair will notify
the presenter when they have 2 minutes remaining. An additional 5 minutes
are allocated to allow for questions and discussion after each presentation (~20
minutes).
Presenting authors are kindly asked to prepare their presentation using MS
PowerPoint and save it on a USB drive for uploading to the computer in the
session room. Please upload your presentation at least 15 minutes before the
start of the session.
All poster authors will have the opportunity to present a 2 minute ‘elevator
pitch’ at the end of the sessions prior to lunch. Please ensure your presentation
is uploaded to the computer in the session room.
All paper contributions and posters are available on the USB drive provided.
Workshop Session Overview
6 CSHM6
MAY 26th (THURS) MAY 27th (FRI) 08:00 Registration
(Tea and coffee) Registration (Tea and coffee) 08:30
09:00 Keynote Lecture Keynote Lecture 09:30
Session 1 (DKB/LG/024)
Session 3 (DKB/LG/024)
09:50 10:10 10:30 10:50 Coffee break Coffee break 11:20
Session 1 cont. (DKB/LG/024)
Session 3 cont. (DKB/LG/024)
11:40 12:00 12:20
12:40 Elevator Pitch Session (DKB/LG/024)
Elevator Pitch Session (DKB/LG/024)
13:00 Lunch Lunch 14:00 Keynote Lecture Keynote Lecture 14:30
Session 2 (DKB/LG/024)
Session 4 (DKB/LG/024) 14:50
15:10 15:30 Coffee break Coffee break 16:00
Session 2 cont. (DKB/LG/024)
Session 4 cont. (DKB/LG/024)
16:20 16:40 17:00 17:20 17:40 Closing Comments Closing Comments
18:00 Workshop Dinner
(Great Hall, The Lanyon Building, Queen's University Belfast)
Note: All keynote lectures and sessions will take place in room DKB/LG/024
Programme Thursday, 26th May 2016
CSHM6 7
08:00
Registration
(Tea and coffee)
KN1 09:00
Keynote Lecture 1: Prof. Hui Li
Data Science and Engineering in Structural Health Monitoring
Session 1: Sensors and structural health monitoring systems
S1-1 09:30
Recent Contributions to Strain‐Based Structural Health Monitoring
using Long‐Gauge Fiber Optic Sensors – An Overview
Glisic, B., Sigurdardottir, D.H., Abdel‐Jaber, H., Kliewer, K., Li, X., Reilly, J.
S1-2 09:50
Damage Detection of Concrete Elements Retrofitted With TRM or
FRP Jackets: A Comparison Between Equivalent Strengthening
Systems
Tzoura, E.A., Laory, I., Triantafillou, T.C., Choutopoulou, E., Kollia C.,
Basheer, P.A.M.
S1-3 10:10
A Framework for Rail Integrity Assessment Based on Rolling
Vertical Deflection Measurements
Nafari, S.F., Gül, M., Cheng, J.J.R.
S1-4 10:30
Ambient Vibration Analysis of a Strategic Base Isolated Building
Bongiovanni, G., Buffarini, G., Clemente, P., Saitta, F., Serafini, S., Felici, P.
10:50 Coffee Break
S1-5 11:20
Monitoring Wooden Warren Truss Hangars to Extend their Design
Life
Locklin, L., Orellana, J., Akhras G.
S1-6 11:40
Dynamic Monitoring System for Utility‐Scale Wind Turbines:
Damage Detection and Fatigue Assessment
Oliveira, G., Magalhães, F., Cunha, Á., Caetano, E.
Programme Thursday, 26th May 2016
8 CSHM6
S1-7 12:00
Large Scale Parallel Neural Network for Structural Damage
Identification
Park, K.T., Darsono, D., Torbol, M.
S1-8 12:20
Compressive Sensing for Wireless Sensors and Sensor Networks in
Structural Health Monitoring
Bao, Y. and Li, H.
12:40 Elevator Pitch Session
13:00 Lunch
KN2 14:00
Keynote Lecture 2: Prof. F. Necati Catbas
Monitoring Strategies for the Evaluation of Structures Exceeding
their Design Life
Session 2: Structural health monitoring strategies for bridge structures
S2-1 14:30
Instantaneous Curvature in Bridge Damage Detection
Sevillano, E., OBrien, E.J., Martinez, D.
S2-2 14:50
Analysis of Load Test on Composite I‐Girder Bridge
Huseynov, F., Brownjohn J.M.W., OBrien E.J., Hester, D.
S2-3 15:10
Sources of Errors Identified in Fatigue Assessment of Ageing Steel
Bridge Integrating BWIM System
Faraz, S., Helmi, K., Algohi, B., Bakht, B., Mufti, A.
15:30 Coffee Break
S2-4 16:00
Monitoring and Evaluation of a Stayed Bridge During a Structural
Failure
Carrion, F.J., Quintana, J.A., Crespo, S.E.
Programme Thursday, 26th May 2016
CSHM6 9
S2-5 16:20
Workshop on Bridge Health Monitoring for the ‘End of Service Life’
of Bridges
Peelen, W.H.A., Klatter, L., Brownjohn, J.M.W.
S2-6 16:40
The Influence of Varying Temperature on Measures of Bridge
Health Monitoring ‐ Problem Description and Possible Accounting
Approaches
Baessler, M. and Hille, F.
S2-7 17:00
Field Testing of a Drive‐By Monitoring System For Transport
Infrastructure Utilising GPS
McGetrick, P.J., Hester, D., Lydon, M., Amato, G., Taylor, S.E.
S2-8 17:20
Ground Penetrating Radar in Built Structures (Bridges, Docks,
Airport Runways, Railway Lines): Successes and Failures
Ruffell, A., Taylor, S.E., Hughes, D.
17:40 Closing Comments
18:00 Workshop Dinner
(Great Hall, The Lanyon Building, Queenʹs University Belfast)
Programme Friday, 27th May 2016
10 CSHM6
08:00
Registration
(Tea and coffee)
KN3 09:00
Keynote Lecture 3: Dr Paolo Mazzanti
Toward Transportation Asset Management: Which is the Role
of Geotechnical Monitoring?
Session 3: Geotechnical monitoring of civil infrastructure
S3-1 09:30
Critical Aspects when using Total Stations and Laser Scanners for
Geotechnical Monitoring
Lienhart, W.
S3-2 09:50
Photogrammetric and Conventional Deformation Monitoring of an
Existing Tunnel while a New Cross‐Passage Tunnel is Excavated
through its Concrete Lining for AWAKE Project at CERN
Alhaddad, M., Di‐Murro, V., Acikgoz, S., Soga, K., Morton, R.F., Weber,
R.
S3-3 10:10
Aged Embankment Characterisation using Non‐Invasive
Geophysics
Gunn, D., Dashwood, B., Chambers, J.E., Dijkstra, T., Uhlemann, S., Swift,
R. Kirkham, M. & Donohue, S.
S3-4 10:30
Settlement‐Induced Damage Monitoring of a Historical Building
Located in a Coal Mining Area using PS‐Insar
Bejarano‐Urrego, L., Verstrynge, E., Van Balen, K., Wuyts, V., Declercq,
P.Y.
10:50 Coffee Break
S3-5 11:20
Non‐Invasive Geophysics for the Water Content Monitoring of
Earthen Embankments
Utili, S.
S3-6 11:40
Geotechnical Monitoring ‐ Case Studies
Doherty, P.
Programme Friday, 27th May 2016
CSHM6 11
S3-7 12:00
Geotechnical Monitoring of Infrastructure using Distributed Fibre
Optic Sensing: Project Examples, Results and Limitations
Iten, M., Fischli, F. & Puzrin, A.M.
S3-8 12:20
Geotechnical Investigation and Basement Reinforcement of BEIAN
Covered Bridge
Tang, Y.J.
12:40 Elevator Pitch Session
13:00 Lunch
KN4 14:00
Keynote Lecture 4: Prof. Mohamed A. Zaki
Lessons Learned from HBRC Infrastructure Testing Activities in
Egypt
Session 4: Challenges in practical application of SHM systems
S4-1 14:30
Statistical Hypothesis Test for Damage Detection of a Truss Bridge
Utilizing a Damage Indicator from a Multivariate Autoregressive
Model
Goi, Y. and Kim, C.W.
S4-2 14:50
Strategies for Assessing the Structural Performance of Electric Road
Infrastructures
Ceravolo, R., Miraglia, G., Surace C.
S4-3 15:10
System Identification Analysis using Ambient Vibration Testing for a
Reinforced Concrete Building
Merino, Y. and Botero, J.C.
15:30 Coffee Break
S4-4 16:00
Health Monitoring of Steel Structure in Oil Refinery Plant
Hee, L.M. and Leong, M.S.
Programme Friday, 27th May 2016
12 CSHM6
S4-5 16:20
Monitoring Based Fatigue Damage Prognosis of Wind Turbine
Composite Blades under Uncertain Wind Loads
Zhang, C. and Chen, H.P.
S4-6 16:40
Abercorn Bridge – An Innovative Approach for Bridge Remediation
O’Higgins, C., McFarland, B., Callender, P., Taylor, S.E., Gilmore, D.
S4-7 17:00
Challenges Associated with Integrating a Corrosion Monitoring
System into a Facility Wide Structural Health Monitoring System
Gooderham, T., John, G., Viles, S., Anderson, M.
S4-8 17:20
Distributed Strain Monitoring of Tunnels
Paris, J.B., Michelin, F., Maraval, D., Lamour, V. & Medrano, C.
17:40 Closing Comments
Posters
CSHM6 13
P1 Application of Intelligent Structural Monitoring Based on IPv6
Hong, W.X., Fang, C., Yao, H.B., Li, L.J.
P2 A Strain Correlation Based Damage Detection Framework for
Railway Bridges
Azim, M.R., Renker, F., Gül, M., Cheng, J.J.R., Bindiganavile, V.
P3 Static and Dynamic Elastic Moduli of Historical Brick Masonry
Subjected to Freeze‐Thaw Cycles
Merli, F., Tang, Y.J.
P4
Moving Force Identification as a Bridge Damage Indicator
Sevillano, E., OBrien, E.J., Fitzgerald P.C.
Keynote Lectures KN1
14 CSHM6
Keynote Lecture 1: 09:00, Thursday, 26th May 2016
Data Science and Engineering in Structural Health Monitoring
Li, H.1, Bao, Y.1, Li, S.2, Zhang, D.1, Zhou, W.1
1Center of Structural Health Monitoring and Control, School of Civil Engineering, Harbin Institute of Technology, Harbin, 150090, China
2School of Transportation Engineering, Harbin Institute of Technology, Harbin, 150090, China
Hundreds of civil infrastructure have been implemented with structural health
monitoring (SHM) systems in China. The SHM systems have generated huge
data. All the structural loads, environmental actions, response, behavior and
performance are embedded in the data. Therefore, data analysis is a very
crucial issue in structural health monitoring field. The authors propose the
research topic of SHM data science and engineering, which include data
acquisition, data transmission, data storage and management, and data
analysis. Data analysis can be categorized two levels, i.e. data‐driven level and
model‐based level. For data‐driven level, some machine learning algorithms
have been proposed to use in SHM data analysis, including wind speed, wind‐
induced vibration, earthquake damage detection, and condition assessment
based on long‐term monitoring cable tension, strain and displacement. For
model‐based level, the framework of safety evaluation based on structural
health monitoring is first proposed. Then the spatial‐temporal distribution of
vehicle is identified using computer vision technique and then modelling by
using Markov unidirection graphic model. The deep learning algorithm is
used to learn and predict local minor damage (corrosion, crack, defaults, etc.)
based on computer vision technique. Then a multiple‐scale model updating
approach is proposed based on the local minor damage detection results and
modal identification results. The identification approaches of cable tension in
real time are proposed. The condition assessment and safety evaluation of
structures including ultimate capacity and fatigue are conducted based on the
monitoring loads and responses, and updated model.
Keynote Lectures KN2
CSHM6 15
Keynote Lecture 2: 14:00, Thursday, 26th May 2016
Monitoring Strategies for the Evaluation of Structures Exceeding their Design Life
F. Necati Catbas1,2
1Professor, Department of Civil, Environmental and Construction Engineering, University of Central Florida, Orlando, USA ([email protected])
2Visiting Professor, Department of Civil Engineering, Bogazici University, Istanbul, Turkey
There are several scenarios, which may justify the maintenance, retrofit and
decommissioning, based on the results of field monitoring, experiments, and
use of field‐calibrated analytical models for simulating an actual constructed
system. As such, there are different strategies for the evaluation of structures
exceeding their design life. In that context, some scenarios that can be
considered are given as: i) Structural intervention, modification, retrofit or
hardening due to changes in use‐modes, codes, aging, and/or for increasing
system‐reliability to more desirable levels, ii) Health and performance
monitoring for operational and maintenance management of large systems; iii)
Asset management of a population of constructed systems. In this
presentation, such considerations will be discussed along with case studies
where conventional and novel methods of monitoring can be implemented.
Keynote Lectures KN3
16 CSHM6
Keynote Lecture 3: 09:00, Friday, 27th May 2016
Toward Transportation Asset Management: Which is the Role of Geotechnical Monitoring?
Mazzanti, P.1,2
1NHAZCA S.r.l., spinoff “Sapienza” University of Rome, Via Cori snc, 00177, Rome
2Department of Earth Sciences, “Sapienza” University of Rome, P.le Aldo Moro n.5, 00185, Rome
The increasing need of ground transportation is requesting for more effective
Transportation Assets Management plans. Geotechnical assets are vital for the
efficiency of transportation corridors and geotechnical monitoring can be a
powerful tool in supporting the management of transportation assets for both
efficiency and safety purposes. Thanks to the technological evolution observed
in the last years, several new technologies are now available to perform
effective geotechnical monitoring. Ranging from remote satellite systems to
contact apparatus today it is possible to perform a multi‐scale approach in
space and time, thus supporting management and decision making. In this
paper, three main categories of geotechnical monitoring are considered, on the
basis of the “monitoring purpose”, i.e. knowledge monitoring, control
monitoring and emergency monitoring. Furthermore, a STN (Space‐Time‐
Need) diagram is proposed as a simple graphic tool for the design of an
effective monitoring plan that accounts for both the technical capabilities of
the available monitoring technologies and the specific monitoring needs.
Keynote Lectures KN4
CSHM6 17
Keynote Lecture 4: 14:00, Friday, 27th May 2016
Lessons Learned from HBRC Infrastructure Testing Activities in Egypt
Zaki, M. A.
Head of Structures & Steel Construction Research Institute, HBRC, Egypt
As the structural health monitoring of infrastructure is based on field
measurements, it is crucial to transfer the technical personal experiences
learned through each field application to the relevant engineering
communities. Also as new trends in engineering learning are rapidly evolving
it is strongly suggested for SHM to benefit from possible tools to disseminate
personal practical expertise as a basic part in its science. Such personal
experiences form especially in SHM a deciding factor in the usefulness of a
whole campaign. This includes the capture of meaningful data and the
selection of optimum analyses options among other experiences which are
seldom found or easy to grasp through literature. Presented here is the modest
contribution of such knowledge from Egyptian field testing experiences on
infrastructure. The tested structures types include cable stayed roadway
bridges, railway bridges, buildings, guyed towers, wind turbine masts and
historical monuments. Presenting these case studies also gives an overview of
the local SHM activities in this part of the world. They are also meant to
encourage much larger practical lessons exchange between all parts of the
world.
Abstracts Session 1
18 CSHM6
S1-1
Recent Contributions to Strain-Based Structural Health Monitoring using Long-Gauge Fiber Optic Sensors – An Overview
Glisic, B.1, Sigurdardottir, D.H.1,2, Abdel-Jaber, H.1, Kliewer, K.1, Li, X.1, Reilly, J.1
1 Department of Civil and Environmental Engineering, Princeton University, Princeton NJ, USA
2 Ramboll, Stockholm, Sweden
Strain distributions are well‐known indicators of structural health condition
(SHM) and performance. Indeed, strain is one of the most monitored
parameters in structures since creation of the strain‐gauge in 1938, and
especially since development of embeddable vibrating‐wire strain sensor in
1958. Development of long‐gauge fiber optic sensors in early 1990’s, combined
with advancements in informatics technologies, transformed the strain
monitoring by enabling long‐term SHM at global, structural level. In recent
years, SHMlab at Princeton University has been focusing on creation of
systematic, universal, strain‐based SHM methods that can be used to assess
wide range of structural parameters relevant for evaluation of structural
health condition and performance. These parameters are location of the
neutral axis, deformed shape, prestressing force distribution, dynamic‐
curvature correlations, and temperature‐strain‐displacement correlations. For
each method, a set of algorithms for the implementation, as well as rigorous
evaluation of uncertainties is envisaged. The first three methods are currently
at advanced stage, while the two latter methods are at initial stage of creation.
This paper overviews these methods and presents the effectiveness of the first
three methods in real‐life settings.
Abstracts Session 1
CSHM6 19
S1-2
Damage Detection of Concrete Elements Retrofitted with TRM or FRP Jackets: A Comparison between Equivalent Strengthening Systems
Tzoura, E. A.1, Laory, I.2, Triantafillou, T. C.3, Choutopoulou, E.3, Kollia C.3, Basheer, P.A.M.1
1 School of Civil Engineering, University of Leeds, Leeds, LS2 9JT, UK
2 School of Engineering, University of Warwick, Coventry, CV4 7AL, UK
3 Department of Civil Engineering, University of Patras, Patras, GR-26500, Greece
This paper presents the experimental procedure for damage detection on
concrete cylinders retrofitted with TRM (textile‐reinforced mortar) or FRP
(fiber‐reinforced polymer) jackets. The strengthening systems were equivalent
so that a direct comparison of the results were possible. A comparison
between the two composite materials (TRM and FRP) was made according to
their behaviour in damage detection. For the damage detection of the elements
an innovative wireless measurement system was used. For this purpose lead
zirconate titanate (PZT) transducers were externally placed on the retrofitted
elements. Measurements of the voltage across the PZT transducers were
obtained at various strain values during the experimental procedure. The
variation of the voltage measurements indicated the propagation of the
damage which was quantified by two damage indices, which were compared.
It is concluded that the sensitivity in damage detection of the PZT transducers
in combination with the proposed measurement system is quite high.
However, damage detection at an early stage is mainly dependent on the load
and deformation capacity of the element and not on the strengthening material
itself.
Abstracts Session 1
20 CSHM6
S1-3
A Framework for Rail Integrity Assessment Based on Rolling Vertical Deflection Measurements
Nafari, S.F.1, Gül, M.1, Cheng, J.J.R.1
1 Department of Civil & Environmental Engineering, University of Alberta, Canada
The rolling deflection measurement system developed at the University of
Nebraska‐ Lincoln (commercially known as MRail technology) under the
sponsorship of Federal Railroad Administration is one of the most recent
technologies that have potential to provide a practical approach for estimating
track stiffness and rail bending stresses along large rail networks. MRail
measures the relative vertical distance (referred to as Yrel) between the rail
surface and the rail/wheel contact plane at a distance of 1.22 m from the
nearest wheel to the sensor system. This paper presents some of the results
from our ongoing project, which aims to develop a framework for quantifying
track modulus and rail bending stress based on Yrel measurements. Within
this study, a detailed finite element model was developed to simulate
stochastic nature of track modulus. Data generated using the FEM was then
used to investigate the correlation of the relative vertical deflection with the
track modulus and rail bending moment when foundation stiffness is variable.
It was shown that different mathematical models and approaches can be
developed to estimate track modulus and rail bending stresses using Yrel
measurements.
Abstracts Session 1
CSHM6 21
S1-4
Ambient Vibration Analysis of a Strategic Base Isolated Building
Bongiovanni, G.1, Buffarini, G.1, Clemente, P.1, Saitta, F.1, Serafini, S. 1, Felici, P.2
1 ENEA, Casaccia Research Centre, Rome, Italy
2 Umbria Region, Perugia, Italy
The experimental dynamic analysis of a base isolated building is analysed. It
was carried out in the framework of its dynamic characterization. The building
has a hemispherical shape with three floors and an underground floor. The
superstructure is formed by ten arch elements equally spaced along the
perimeter, connected by a ring beam at the top springing and by three other
ring beams at the three floors. A prestressed concrete cylinder, containing all
the facilities, is suspended at the top ring. It is connected to the other floors
and continues down in the underground floor without other supports. The
lower floor, at the diameter plane of the dome, is composed by ribbed plate. At
the lower springing of the ten arches the superstructure is supported by ten
isolation devices, which transfer the loads to the foundations. These are
composed by concrete plinths supported by four piles. The height of the
building is 22 m, the diameter at the base is 31 m. The recorded data revealed a
behaviour quite different from the expected one under strong seismic events
due to the different stiffness of the rubber bearings.
Abstracts Session 1
22 CSHM6
S1-5
Monitoring Wooden Warren Truss Hangars to Extend their Design Life
Locklin, L.1, Orellana, J.2, Akhras G.2
1Civil Engineering Cell Commander,1 ESU Canadian Armed Forces, Kingston, Canada
2Center for Smart Materials and Structures, Royal Military College, Kingston, Canada
The Canadian Forces (CF) maintains close to 80 wooden Warren truss
buildings that were initially constructed as temporary structures during the
World War II Era. Within a few months of construction, significant shrinkage
and cracking began to take place. Various repairs and inspection methods
have been tried over the years but the remaining structures continue to pose
structural integrity concerns. Regular inspections are not sustained and
recommended repairs are often costly and over conservative. A Structural
Health Monitoring (SHM) system is applied to extend the design life and
improve the safety of these structures.
This work investigated applicable methods of SHM in order to attain an
understanding of the long‐term performance under service load as well as
detect and identify the severity of damage. The evaluation of various sensor
types and methods of data collection are reviewed in order to develop and
select a suitable SHM system. Electrical strain gauges have been in place since
2012 and Fiber optic sensors have been recently installed. The current SHM
system is fixed on three of the eleven trusses. This paper presents the results of
the preliminary study and its conclusions.
Abstracts Session 1
CSHM6 23
S1-6
Dynamic Monitoring System for Utility-Scale Wind Turbines: Damage Detection and Fatigue Assessment
Oliveira, G.1, Magalhães, F.1, Cunha, Á.1, Caetano, E. 1
1 CONSTRUCT/ViBest, Faculty of Engineering (FEUP), University of Porto, Portugal
Wind turbines are designed to last about 20 years. However, at the end of this
period, information regarding the actual structural condition of the wind
turbine is reduced or even null. Considering the heavy upfront investment for
the installation of a turbine, the possibility of extend its life period may
represent an opportunity to increase the profitability of the operation. In that
sense, a dynamic monitoring system is being developed by the Laboratory of
Vibrations and Structural Monitoring (ViBest, www.fe.up.pt/vibest) of FEUP
for implementation on utility‐scale wind turbines. This monitoring system,
based on automated techniques of Operational Modal Analysis (OMA), aims
to deliver important information regarding the actual condition of the wind
turbine: early detection of structural changes (i.e. damage) and evaluation of
fatigue condition of the support structure.
Following an automated processing methodology, this system may represent
an important tool for considering different strategies about the extension of
the design life time of wind turbine structures.
Abstracts Session 1
24 CSHM6
S1-7
Large Scale Parallel Neural Network for Structural Damage Identification
Park, K.T.1, Darsono, D.1, Torbol, M.1
1 School of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea
This study attempts a new damage identification approach for civil structures.
The method uses a wireless sensor network to record the dynamic behaviour
of the structures. After the entire signals from the sensor network are
synchronized, an auto regressive (AR) analysis of varying model order
computes the AR coefficients from the signals. The AR coefficients obtained
are used to conduct eigen‐value realization analysis (ERA) for obtaining the
experimental modal properties of the system. A large scale neural network
takes the AR coefficients as input, and it computes the submatrix scaling
factors (SSF) associated with an equivalent parametric finite element model.
The SSFs identify the damaged elements within a structure but the neural
network has to be trained to obtain reliable SSF results. The training process is
done by comparing the experimental modal properties and the FEM modal
properties. Because the process includes the huge size of neural network with
a large number of AR coefficients a normal sequential algorithm is not suitable
for solving this problem. Instead, a parallel neural network is built on graphic
processing units (GPU) to exploit superfast computational performance of it.
Abstracts Session 1
CSHM6 25
S1-8
Compressive Sensing for Wireless Sensors and Sensor Networks in Structural Health Monitoring
Bao, Y. and Li, H.
Center of Structural Health Monitoring and Control, School of Civil Engineering, Harbin Institute of Technology, Harbin, 150090, China
Wireless sensor technology‐based structural health monitoring (SHM) has
been widely investigated recently. This paper presents the new developments
and applications of compressive sensing (CS) for wireless sensors and sensor
networks‐based SHM in our research group. Frist, the group sparse
optimization based CS for data sampling and recovery of wireless sensor
network is introduced. Then, the lost data recovery for wireless sensors is
presented. CS provides a data loss recovery technique, which can be
embedded into smart wireless sensors and effectively increases wireless
communication reliability without re‐transmitting the data; the promise of this
approach is to reduce communication and thus power savings. To embed into
the smart sensor, a method called random demodulator is employed to
provide memory and power efficient construction of the random sampling
matrix. The program is embedded into the Imote2 smart sensor platform and
tested in a series of sensing and communication experiments and field tests.
Lastly, the fast moving wireless sensing technique is presented. For the fast
moving wireless data transmission, the Doppler effects are the main reason
causing data packet loss. A field test on a cable‐stayed bridge is performed to
valid the ability of the CS‐based robust wireless data transmission approach in
obtaining high‐quality data for the fast‐moving wireless sensing technique.
Abstracts Session 2
26 CSHM6
S2-1
Instantaneous Curvature in Bridge Damage Detection
Sevillano, E.1, OBrien, E.J.1, Martinez, D.1
1 School of Civil, Structural & Environmental Engineering, University College Dublin, Dublin 4, Ireland
Among all the Structural Health Monitoring (SHM) recent methods found in
literature, drive‐by monitoring has demonstrated to be promising for damage
detection purposes, particularly in bridges. As curvatures can be derived from
displacement measurements taken by this method, they can also be used for
damage detection, which has already been successfully demonstrated. This
paper describes the use of Instantaneous Curvature (IC) for that purpose.
Once the absolute displacements of the bridge are measured, damage location
and quantification can be obtained through IC when having a moving
reference over a bridge.
In this paper, a bridge is represented by a finite element model of a Euler‐
Bernoulli beam. A Half‐Car model of a vehicle is used to represent a Traffic
Speed Deflectometer (TSD), a drive‐by monitoring vehicle. Damage is
represented as a loss of stiffness in different parts of the bridge and 1 %
measurement noise is added. A generic road profile is also considered.
Healthy and damaged states of the bridge are compared in order to validate
the method.
Abstracts Session 2
CSHM6 27
S2-2
Analysis of Load Test on Composite I-Girder Bridge
Huseynov, F.1,2, Brownjohn, J. M. W.3, OBrien, E.J.2, Hester, D.4
1 Full Scale Dynamics Ltd, Sheffield, UK
2 School of Civil & Structural Engineering, University College Dublin, Dublin, Ireland
3 College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK
4 School of Planning, Architecture and Civil Engineering, Queen’s University Belfast, Belfast, UK
This paper showcases the importance of field testing in efforts to deal with the
deteriorating infrastructure. It demonstrates a load test performed on a
healthy but aging composite reinforced concrete bridges in Exeter, UK. The
bridge girders were instrumented with strain transducers and static strains
were recorded while a four‐axle, 32 tonne lorry remained stationary in a single
lane. The results obtained from the field test were used to calculate transverse
load distribution factors (DFs) of the deck structure for each loading case.
Additionally, a 3‐D finite element model of the bridge was developed and
calibrated based on field test data. Similar loading cases were simulated on the
analytical model and behaviour of the structure under static loading was
studied. It was concluded that the bridge support conditions had changed
throughout its service life, which affected the superstructure load distribution
characteristics. Finally, DFs obtained from analysis were compared with
factors provided in Design Manual for Roads and Bridges Standard
Specification for similar type of bridges.
Abstracts Session 2
28 CSHM6
S2-3
Sources of Errors Identified in Fatigue Assessment of Ageing Steel Bridge Integrating BWIM System
Faraz, S. 1, Helmi, K. 2, Algohi, B. 1, Bakht, B. 1, Mufti, A. 1
1 Department of Civil Engineering, University of Manitoba at Winnipeg, Canada
2 The Arab Academy for Science, Technology and Maritime Transport, Alexandria, Egypt
Manitoba has many ageing steel bridge structures on its highway network that
are facing increased axle loads, speed and traffic intensity, all of which will
accelerate the deterioration process. An immediate replacement or
rehabilitation is not feasible for the existing structures which have already
approached their expected service life. The residual life of these types of
structures, or their component is estimated by conducting a fatigue evaluation
and damage assessment.
Field measurements are very accurate in estimating fatigue loading. This
paper discusses a case study of fatigue assessment on an ageing bridge
structure in Winnipeg, Manitoba, which integrates Bridge Weigh in Motion
(BWIM) system. The South Perimeter Bridge (SPB) is instrumented with SHM
system which is used to perform BWIM and fatigue analysis of the steel girder
bridge. The identified sources of error in fatigue evaluation integrating BWIM
system would improve the accuracy of fatigue analysis using monitoring data.
Abstracts Session 2
CSHM6 29
S2-4
Monitoring and Evaluation of a Stayed Bridge during a Structural Failure
Carrion, F.J.1, Quintana, J.A.1, Crespo, S.E.1
1 Instituto Mexicano del Transporte, Sanfanidla, Querétaro, MEXICO
The Rio Papaloapan Bridge in Mexico is a stayed structure that has reported
structural problems that required extra rehabilitation and a SHM system for
continuous remote monitoring. The main problems were identified as
structural deficiencies in the constitutive material and welding of the upper
anchorage elements of the cables; these failures are cause of potential fractures
and loosening of cables. In June 2015, a new failure was presented due to a
defective weld; thus, from the monitoring system it was possible to reproduce
the structural behaviour of the bridge during and after this event. Although
the SHM doesn’t have the ability to prevent this type of failures, the value of
the information from the monitoring before, during and after the cable´s
release, was very valuable to evaluate the overall effect on the structural
integrity, to decide immediate preventive actions, and to verify the
effectiveness of the rehabilitation to recuperate the initial condition. This paper
describes how the problem was addressed from the information collected
from the SHM system and shows the benefits and value of monitoring
considering this type of event.
Abstracts Session 2
30 CSHM6
S2-5
Workshop on Bridge Health Monitoring for the ‘End of Service Life’ of Bridges
Peelen, W.H.A.1, Klatter, L.2, Brownjohn, J.M.W.3
1 Rijkswaterstaat, 3526 LA Utrecht, Netherlands
2 TNO, 2628 XE Delft, Netherlands
3 University of Exeter, EX4 4QF, United Kingdom
Ageing infrastructure poses a new challenge for Road Authorities (RA) with
significant parts of road networks reaching end of service life (EoSL) in the
coming decades. At the same time a high level network performance is
required, loads are increasing and budgets are limited. The scientific
communities of bridge management and Structural Health Monitoring (SHM)
aim to develop technologies to help RA to tackle these problems.
One issue is that RA strategies to deal with these EoSL issues and their
requirements in terms of information needed are not well specified or
formulated, and they differ widely. On the other hand SHM development is
mostly technology driven and communication between RA and SHM
developers and practitioners is limited.
To address this situation, Rijkswaterstaat, Netherlands (RWS) organised a
two‐day workshop in October 2015. To begin, an overview of the EoSL
strategies of four different RA were presented and an analysis of the
information needs performed. Next, relevant reference projects (case studies)
of bridge monitoring were presented by practitioners and researchers. Finally,
these projects were analyzed in break‐out groups with respect to their
relevance for the EoSL information requirements, in terms of present
applicability (useful applications), future capability (technology development)
and long term (research agenda). The presentation will summarise key
observations and outcomes from the meeting.
Abstracts Session 2
CSHM6 31
S2-6
The Influence of Varying Temperature on Measures of Bridge Health Monitoring - Problem Description and Possible Accounting Approaches
Baessler, M.1 and Hille, F.1
1 Bundesanstalt für Materialforschung und–prüfung (BAM), Berlin, Germany
It is widely recognized that the dynamics of large civil structures, such as
bridges or offshore structures, is significantly affected by temperature and
other environmental influences. The most significant effect on the structural
stiffness is due to temperature variations and especially due to the thermal
gradients within the structures cross section. For civil engineering structures,
changes in the dynamic response produced by varying environmental
conditions can be equivalent or greater than the ones produced by damage.
Therefore, handling the environmental effects has become a major research
field for global Structural Health Monitoring. A number of methods and
techniques have been developed for addressing this issue for different civil
engineering application examples.
An additional question is if temperature changes of stiffness correlate with a
change in safety level of the structures bearing capacity which has to be
discussed case dependent.
In our contribution we show the result of an extensive literature review on the
matter of varying temperature, describing the characteristic effects on the
structure as well as the various approaches to that issue, including the
experiences our work group has gained in the last 20 years of SHM on civil
engineering structure.
Abstracts Session 2
32 CSHM6
S2-7
Field Testing of a Drive-By Monitoring System for Transport Infrastructure utilising GPS
McGetrick, P.J., Hester, D., Lydon, M., Amato, G., Taylor, S.E.
School of Planning, Architecture and Civil Engineering, Queen’s University Belfast, UK
Ageing and deterioration of infrastructure is a challenge facing transport
authorities. In particular, there is a need for increased bridge monitoring in
order to provide adequate maintenance prioritise allocation of funds and
guarantee acceptable levels of transport safety. Existing bridge structural
health monitoring (SHM) techniques typically involve direct instrumentation
of the bridge with sensors and equipment for the measurement of properties
such as frequencies of vibration. These techniques are important as they can
indicate the deterioration of the bridge condition. However, they can be labour
intensive and expensive due to the requirement for on‐site installations. In
recent years, alternative low‐cost indirect vibration‐based SHM approaches
have been proposed which utilise the dynamic response of a vehicle to carry
out “drive‐by” pavement and/or bridge monitoring. The vehicle is fitted with
sensors on its axles thus reducing the need for on‐site installations.
This paper investigates the use of low‐cost sensors incorporating GPS for
implementation of the drive‐by system in practice, via field trials. The
effectiveness of global positioning technologies are evaluated and compared
for this system in terms of accuracy, cost and ease of use. These include
professional GPS/GLONASS systems and smartphone location applications &
systems.
Abstracts Session 2
CSHM6 33
S2-8
Ground Penetrating Radar in Built Structures (Bridges, Docks, Airport Runways, Railway Lines): Successes and Failures
Ruffell, A.1, Taylor, S.E.2, Hughes, D.2
1 Geography, Archaeology & Palaeoecology, Queen’s University Belfast, N.Ireland
2 School of Planning, Architecture, and Civil Engineering, David Keir Building, Queen's University Belfast, Northern Ireland
Ground penetrating radar (GPR) is common in the survey of built
infrastructure. This presentation uses GPR in some novel contexts in terms of
deployment on freshwater, using transmitted waves in historic bridges and in
conjunction with other technology such as sonar, thermal imaging, resistivity
and ultrasound. The presentation will concentrate on case studies including
historic bridges, freshwater and marine docks, runways in South Africa and
Colorado and railway lines in the UK and France. Sometimes GPR does not
work well, and this is usually predictable if a full desktop study of geology,
soils, historical maps and data sources, plus pre‐survey reports are provided,
saving time and money. Some unusual applications of GPR in an engineering
context will be provided.
Abstracts Session 3
34 CSHM6
S3-1
Critical Aspects when using Total Stations and Laser Scanners for Geotechnical Monitoring
Lienhart, W.
Institute of Engineering Geodesy and Measurement Systems, Graz University of Technology, Austria
Modern geotechnical monitoring is based on a variety of surface based and
integrated sensors. This article discusses the potential but also the limitations
of total stations and laser scanners in monitoring of civil infrastructure and
natural phenomena. We report about our experiences gained in long term
monitoring projects and discuss the impact of the setup location, the signal
travel path and the target. Although, modern instruments are capable of
measurements with accuracies of a few millimetre or better, neglecting error
sources like temperature dependence of the tilt sensor, orientation of the used
prism and refraction can easily cause errors of several millimetres or even
centimetres.
Abstracts Session 3
CSHM6 35
S3-2
Photogrammetric and Conventional Deformation Monitoring of an Existing Tunnel while a New Cross-Passage Tunnel is Excavated
through its Concrete Lining for AWAKE Project at CERN
Alhaddad, M.1, Di-Murro, V.1,2, Acikgoz, S.1, Soga, K.1, Morton, R. F.2, Weber, R.3
1 Department of Engineering, University of Cambridge, Cambridge, UK
2 The European Organisation for Nuclear Research (CERN), Geneva, Switzerland
3 Principal Tunnel Engineer, ATKINS, Surrey, UK
This publication presents a monitoring case study of a cross‐passage
excavation through two existing concrete‐lined tunnels at The European
Organisation for Nuclear Research (CERN). The existing tunnels are
significantly different in size (3 m and 9 m diameter) and are approximately 3
meters apart, extrados to extrados. The connection was built through the
Molassic geological zone, which is known for its favourable ground conditions
for tunnelling (notwithstanding its susceptibility to heave and swell over
time). Design and modelling for such complex construction scenarios is not
straightforward and predictions of stress flow lines during the opening can
vary, depending on the numerous assumptions that designers make.
It is therefore crucial to plan an effective monitoring system to safeguard the
existing tunnels and to understand their behaviour for future proposals. Three
monitoring systems were tested to record the movements and deformations of
the smaller diameter tunnel, the findings of which are presented in this paper.
The three monitoring systems are: conventional tape extensometer readings,
laser scanning and a new photogrammetric movement detection technique
developed at University of Cambridge called CSattAR.
Abstracts Session 3
36 CSHM6
S3-3
Aged Embankment Characterisation using Non-Invasive Geophysics
Gunn, D.1, Dashwood, B.1, Chambers, J.E.1, Dijkstra, T.1, Uhlemann, S.1, Swift, R.1 Kirkham, M.1 & Donohue, S.2
1 Engineering Geology, British Geological Survey, Nottingham, UK
2 Intelligent Infrastructure Group, School of Planning, Architecture, and Civil Engineering, David Keir Building, Queen's University Belfast, Northern Ireland
Rapid, non‐invasive surface wave and resistivity surveys were used to
develop embankment ground models exhibiting structures consistent with
cut‐fill construction methods. An associated ground investigation confirmed
these structures to be related to the distribution of materials from local
cuttings. Inter‐clast voids, cracks and impact damaged lithoclasts were
identified in thin sections of these materials and are believed to be from the
original construction. Further fabric‐disruption in the form of lath‐shaped
ghost voids and mineralised rosettes were considered to result from fluid
transport controlled by the material distribution arising from the end‐tipping
construction method. This study from the Great Central Railway suggests
ageing is related to groundwater flow deep into a Victorian embankment.
Heterogeneous structures controlling dynamic moisture variation and
engineering property changes were identified using surface wave and
resistivity surveys. Repeat resistivity surveys indicated moisture movement
through these structures. Surface wave surveys offer a viable means of
monitoring the long term deterioration in stiffness conditions associated with
ageing and a potential basis to identify condition thresholds for use in
geotechnical asset life‐cycle planning.
Abstracts Session 3
CSHM6 37
S3-4
Non-Invasive Geophysics for the Water Content Monitoring of Earthen Embankments
Utili, S.1
1 School of Engineering, University of Warwick, Coventry, UK
The use of electrical conductivity measurements from a non‐invasive hand
held electromagnetic probe is showcased to monitor the water content of
earthen embankments at routine inspections. A methodology to convert the
electrical conductivity measurements from the electromagnetic device into
water content values is illustrated. The methodology requires the use of a few
geotechnical probes installed in at least two cross‐sections of the embankment
for a relatively short time to calibrate the electrical conductivity – water
content relationship.
The values of water content converted from the conductivity measurements
according to the proposed procedure were found to be in very good
agreement with measures of water content from soil samples retrieved in situ
even at times well beyond the calibration period.
Abstracts Session 3
38 CSHM6
S3-5
Settlement-Induced Damage Monitoring of a Historical Building Located in a Coal Mining Area using PS-InSAR
Bejarano-Urrego, L.1, Verstrynge, E.1, Van Balen, K. 1, Wuyts, V.2, Declercq, P.Y.3
1 Building Materials and Building Technology Division, Civil Engineering Department. KU Leuven, Belgium
2 Department of Cultural Heritage in Flanders
3 Royal Belgian Institute of Natural Sciences (RBINS), Geology Department
Persistent Scatterer Interferometric Synthetic Aperture Radar (PS‐InSAR) is a
remote sensing technique used to detect and monitor surface displacement
(uplift or subsidence) by comparing sequential satellite radar images.
Persistent scatterer of interest can be identified on these radar images allowing
the tracking of movement through time. This technique is gaining importance
due to unique features such as its cost‐effectiveness, millimetre accuracy, no
need of equipment installation in‐situ, coverage of large areas, as well as the
possibility of analysing past monitoring data. In this paper, PS‐InSAR is
implemented to investigate the damage that occurred at the Saint Vincent’s
church due to differential settlements during and after the coal mining activity
in Zolder, Belgium, which stopped in 1992. The aim of the work is to relate the
displacements measured on reflection points located on the structure with the
damage registered during that period, taking into account the local geology
(faults) of the site. Satellite images for this zone are available from 1992 to 2000
(ERS‐1/2) and from 2003 to 2010 (Envisat) with an image every 35 days. PS‐
InSAR results, in the area of the church, show that during 1991‐2001 the soil
presented settlements about ‐4.0 mm/year; however, during 2003‐2010 the soil
presented uplift about 5.6 mm/year, presumably caused by mine water rise.
Abstracts Session 3
CSHM6 39
S3-6
Geotechnical Monitoring - Case Studies
Doherty, P.1
1 Gavin and Doherty Geosolutions Ltd.
With the introduction of Eurocode based design, the use of geotechnical
monitoring is gaining increasing momentum on commercial projects. Accurate
analysis of soil‐structure interaction remains a challenge for the industry,
which introduces opportunities to use the observational method. A series of
case studies will be introduced which have adopted different geotechnical
monitoring schemes to determine the performance of a range of structure.
Case Study 1 – Flood Defence Seepage Analysis: this case study involved the
design of a flood defence wall and a seepage barrier to protect lands adjacent
to a very flashy river. A suite of piezometric monitoring was undertaken to
assess the variation in water levels and to simulate the impact of different
flood defence solutions. The combined results of the seepage analysis and
dynamic monitoring demonstrated that a cut‐off wall was not required.
Case Study 2 – Basement Movement Monitoring: Basement construction
across London is at a record high and many of these structures are in close
proximity to neighbouring buildings creating significant movement risks. This
case study examines a residential basement where the observational method
was applied to good effect by utilising inclinometer and survey data.
Case Study 3 – Offshore Structural Monitoring: This case study introduces
accelerometer based monitoring to analyse the soil response of a novel
offshore jacket platform. The results demonstrated that the soil‐structure
interaction elements were several times stiffer than anticipated and that
conventional codes are overly conservatism.
Abstracts Session 3
40 CSHM6
S3-7
Geotechnical Monitoring of Infrastructure using Distributed Fibre Optic Sensing: Project Examples, Results and Limitations
Iten, M.1, Fischli, F.1 & Puzrin, A. M.2
1Marmota Engineering AG, Zurich, Switzerland
2 Institute for Geotechnical Engineering, ETH Zurich, Switzerland
An increasing number of infrastructures are built in areas prone to hazards,
such as unstable slopes and differential settlements. The affected areas mostly
have a large extension, which makes it particularly difficult to identify the
locations where the infrastructure is endangered. Distributed fibreoptic
sensors that are capable of providing monitoring data for thousands of
individual sections along a sensor of up to several kilometres of length can
reveal the possible threats over a large area. The concepts of using distributed
fibre‐optic sensors for this task have been extensively investigated, both
theoretically as well as in laboratory and field applications. However,
experience from commercial field applications has been rarely shared. This
paper focusses on practical experiences of commercial applications of
distributed fibre‐optic sensing in the geotechnical monitoring of infrastructure.
Project examples mainly from monitoring on landslides are described and the
results are discussed. The projects shared involve pipeline monitoring on a
creeping slope as well as the identification of shear surfaces and landslide
boundaries for various types of infrastructures, such as dams, villages and
roads. In addition, the advantages and limitations of the applied monitoring
method and data interpretation methods are discussed.
Abstracts Session 3
CSHM6 41
S3-8
Geotechnical Investigation and Basement Reinforcement of BEIAN Covered Bridge
Tang, Y.J.1,2
1 Department of Geotechnical Engineering, Tongji University, China
2 Key laboratory geotechnical and underground engineering (Tongji University), Ministry of education, China
Beian covered bridge, a stone bridge over 400 years, has long and wide cracks
in the piers and an abutment. A geotechnical investigation has been carried
out. The causes of the cracks were analyzed. A reinforcement scheme was
presented. This reinforcement scheme is followed the minimum intervention
principle and should be effective. The abutments are fixed by installing
permanent jacks. It is noteworthy that the adjacent abutment is excavated
before the permanent jacks are connected to the abutment with problem. The
piers are fixed by reinforced concrete belt.
Abstracts Session 4
42 CSHM6
S4-1
Statistical Hypothesis Test for Damage Detection of a Truss Bridge Utilizing a Damage Indicator from a Multivariate Autoregressive Model
Goi, Y.1 and Kim, C.W.1
1 Department of Civil and Earth Resource Engineering, Kyoto University, Kyoto, Japan
This study proposes a damage indicator (DI) automatically derived from a set
of multivariate autoregressive models estimated from ambient vibrations of
bridges. The DI evaluates a stochastic distance between a set of data from
healthy bridge and unknown test data. A statistical hypothesis testing based
on a probability distribution of the DI was conducted for damage detection. A
field experiment on a real steel truss bridge whose truss members were
artificially severed was conducted so as to investigate efficacy of the proposed
DI for damage detection. The experimental result showed the proposed DI
enables to detect damage of three different damage patterns clearly. Efficacy of
the proposed DI was also observed by comparing to the previously
investigated damage sensitive feature using the experimental data of the same
bridge.
Abstracts Session 4
CSHM6 43
S4-2
Strategies for Assessing the Structural Performance of Electric Road Infrastructures
Ceravolo, R.1, Miraglia, G.1, Surace C.1
1 Department of Structural, Geotechnical and Building Engineering, Politecnico di Torino, Italy
Wireless charging is an attractive technology that is expected to promote
customer acceptance of electric vehicles in urban environment because it can
improve convenience and sustainability. The dynamic properties and the long‐
term structural behaviour of these particular infrastructures call for in depth
investigations, in order to define specific requirements for the installation of
the system, as well as for its maintenance, lifecycle analysis and monitoring.
Currently, several technologies exist that integrate dynamic inductive
charging systems within the infrastructure, ranging from rails with box‐
section to buried solutions. A wide‐range discussion will be provided on how
to assess the structural performance of electric roads (e‐roads), including
numerical strategies for the estimation of their lifetime. Results of simulations
will be presented to compare e‐roads with traditional ones (t‐roads). Finally,
Structural Health Monitoring (SHM) strategies for e‐roads will be outlined.
Indeed, a SHM strategy integrated with lifecycle management is essential to
calibrate structural assessment and prediction, to optimise the maintenance of
infrastructure and, possibly, to operate infrastructure systems beyond their
original design life.
Abstracts Session 4
44 CSHM6
S4-3
System Identification Analysis using Ambient Vibration Testing for a Reinforced Concrete Building
Merino, Y.1 and Botero, J. C.2
1Civil Engineering Program, Engineering Faculty, University of Ibagué, Colombia
2Civil Engineering Program, School of Engineering, EAFIT University, Colombia
Implementation of techniques for vibration analysis of civil structures has
become a useful tool in structural health monitoring during last years to
identify dynamic response of these systems, especially for large buildings in
which strong external excitation cannot be practically applied. This study
focuses on the analysis of output data from structural vibration testing of a
reinforced concrete building, in order to identify its dynamic properties such
as frequencies, modal shapes and damping ratios, using non parametric
system identification techniques. Conventional spectral analysis of time
signals obtained from acceleration records is developed, as a response of the
structure to random vibrations generated by ambient conditions. Vibration
testing was performed by instrumentation of the building using an integrated
digital accelerometer network. The structure modal frequencies obtained from
spectral analysis of ambient vibration signals were verified with
representative frequencies from spectral correlation functions calculated for
low earthquake excitation, and finally compared with those obtained from an
analytical model. Results show coherence with dynamic parameters obtained
from other system identification techniques and reveal acceptable variations
with regard to values estimated from the mathematical models of the system.
Abstracts Session 4
CSHM6 45
S4-4
Health Monitoring of Steel Structure in Oil Refinery Plant
Hee, L.M.1 and Leong, M.S.1
1 Institute of Noise & Vibration, Universiti Teknologi Malaysia, Malaysia
This paper presents a case study of health monitoring of an aged steel
structure in a petroleum coke production plant in Malaysia. The steel structure
has been in operation for more than two decades and only of late, high
vibrations were reported and most severe during coke drilling process. As a
result, vibration investigation and Operational Deflection Shape (ODS)
analysis for that structure was deemed necessary and was undertaken to
quantify vibration severity and to obtain a visual insight to the nature of the
motions and problems. A concurrent vibration measurement of 36 channels
accelerometers mounted on the 45 m steel structure was undertaken. It was
found that ODS analysis has brought crucial insight to the problem as higher
motions were seen due to excessive excitations during coke drilling process in
Drum 2 as compared to Drum 1 drilling process. As a result, a visual
inspection at Drum 2 was carried out and evidence of loose nuts and cracks at
the drum foundation where Drum 2 hold down bolts are located was found. It
was concluded that looseness in the hold down bolts and cracks at the drum
foundation support ring was a major cause of the higher motions from Drum 2
during drilling process. ODS analysis successfully pinpointed the root cause of
the high vibration and thus enables the rectification works on the drum
foundation to be undertaken subsequently.
Abstracts Session 4
46 CSHM6
S4-5
Monitoring Based Fatigue Damage Prognosis of Wind Turbine Composite Blades under Uncertain Wind Loads
Zhang, C.1 and Chen, H.P.1
1 Department of Engineering Science, University of Greenwich, Chatham, Kent, ME4 4TB, UK
Lifecycle assessment of wind turbines is essential to improve their design, to
optimise maintenance plans and to prevent structure failures during the
design life with minimum interruptions. A critical element of wind turbines is
the composite blade due to uncertain cyclic wind loads with relatively high
frequency and amplitude typically in offshore environments. It is important to
detect the fatigue damage evolution in composite blades before the blades fail
catastrophically and destroy the entire wind turbines. This study presents a
methodology for analysing the fatigue failure probability of a wind turbine
composite blade by using monitoring based stochastic deterioration
modelling. On the basis of five minutes mean wind speed measurements, the
internal stresses can be obtained from finite element analyses, and failure
probabilities are predicted by stochastic gamma process fatigue damage
modelling over the design service life. A numerical example of a wind turbine
composite blade is investigated to show the applicability of the proposed
model. The results show that the stochastic fatigue damage modelling can give
reliable results for time‐dependent reliability analysis of the composite blades
of wind turbines.
Abstracts Session 4
CSHM6 47
S4-6
Abercorn Bridge – An Innovative Approach for Bridge Remediation
O’Higgins, C.1, McFarland, B.1, Callender, P.1, Taylor, S.E.2, Gilmore, D.1
1 McFarland Associates Ltd, Belfast, Northern Ireland
2 School of Planning, Architecture and Civil Engineering, Queen’s University Belfast, Northern Ireland
Abercorn Bridge was built in 1932. It is located in Newtownstewart, Northern
Ireland and is a ‘Hennebique Ferro’ integral reinforced concrete 4 span
viaduct. The structure, being of the order of 84 years old, was showing signs
of significant deterioration, so much so that one span was recommended for
demolition due to its particularly poor condition. However, an alternative
solution was proposed which offered to: retain all four spans; retain the
overall aesthetics of the bridge; restore additional load capacity; preserve the
bridge for at least a further 25 years; and reduce refurbishment costs. The
alternative solution was adopted, incorporating a structural health monitoring
system throughout the repair process. Detailed inspection and testing of the
bridge provided an accurate view of the bridge’s condition thus allowing a
concrete repair scheme, incorporating cathodic protection, to be designed. A
finite element analysis (FEA) model was created to allow the bridge to be more
rigorously analysed, particularly comparing its as‐built, deteriorated state and
refurbished conditions. Importantly, the FEA model indicated that the repair
scheme on its own was not sufficient to restore the required load capacity and
an innovative, lightweight, structural over‐slab was incorporated. This
“bespoke” over‐slab was among the first such projects to use a combination of
basalt reinforcement and lightweight aggregate concrete to create a strong yet
lightweight slab. To increase the confidence of the alternative, innovative
solution, Fibre Bragg Grating (FBG) sensors were used to: monitor the bridge
during repairs; ensure the structural behaviour was consistent with the FEA
model; and confirm that the over‐slab was working integrally with the bridge
deck beneath. A final load test was undertaken on completion of the Works to
ensure that the required load capacity had been achieved.
Abstracts Session 4
48 CSHM6
S4-7
Challenges Associated with Integrating a Corrosion Monitoring System into a Facility Wide Structural Health Monitoring System
Gooderham, T.1, John, G.1, Viles, S.1, Anderson, M.2
1 Intertek, 2 Strainstall
This paper will outline the challenges that have been faced with integrating dedicated
corrosion monitoring systems for reinforced concrete structures into a wider structural
health monitoring systems. In particular the challenge relating to the integrated of
embedded corrosion monitoring probes installed in the new Queensferry crossing
bridge in Scotland with the wider structural health monitoring sensors and
instrumentation. The objective of the overall exercise was to provide:
1. An integrated structural health monitoring system that provides remote
control of all the measurement nodes (corrosion and structural) via common
software platform.
2. Provide an integrated always live data stream for the structure.
3. Provide an intelligent Structural Health Monitoring system.
The data obtained from the integrated system will be used to provide life time
prediction models with the purpose of avoiding costly bridge closures with diversions
by providing an early warning indication of issues with the structure either internal to
the concrete corrosion issues, or external structural integrity issues.
The system supplied combines permanently connected measurement sensors and data
acquisition units with various structural health sensors across the bridge.
The paper will:
1. Outline the system and the challenges faced with integrating the corrosion
monitoring system that requires activity measurement activity at predefined
periods with traditional structural monitoring instrumentation that provides
continuous data, live and on‐demand.
2. Discuss the challenges regarding the methods of corrosion measurements
which are not‐plug‐and‐play compatible with current Structural Health
Monitoring instrumentation.
Abstracts Session 4
CSHM6 49
S4-8
Distributed Strain Monitoring of Tunnels
Paris, J.B.¹, Michelin, F.², Maraval, D.³, Lamour, V.4 & Medrano, C.5
1,2 Instrumentation Engineer, Cementys, Paris, France
3Optical Fiber Research Engineer, Cementys, Paris, France
4Chief Technical Officer – Chief Executive, Cementys, Paris, France
5 Business Development Manager, Cementys, Paris, France
Distributed strain monitoring of structures using optical‐fiber sensing is a new
technique which has opened new possibilities in tunnel survey. Cementys is
specialized in structural health monitoring to survey ageing infrastructures and
optimize maintenance. Our team developed a sensor called SensoluxTM® based
on Raman and Brillouin Optical Time Domain Reflectometry. The sensor cable
contains 4 optical fibers to measure the Brillouin (strain and temperature sensitive)
and the Raman (temperature sensitive only) scatterings.
The cable‐sensing is sensitive at each point of its length, with a spatial resolution of
0.5m, a precision of ±5μdef and a reach of several dozens of kilometres. The small
diameter of the sensor (2mm) makes it easy to integrate in tunnels by gluing the
optical cable in grooves carved on the concrete. The optical cable is thus protected
for long‐term monitoring and presents a low level of intrusiveness. Any
circumferential deformation of the structure is transmitted to the cable rings and
detected by the interrogators. The first measure is considered as the reference and
the following measures are compared with the first one to track relative motion.
Consequently, the initial stress of the cable due to gluing does not impact the
measures. The information can be retrieve from a long distance for real‐time
monitoring thanks to optical technologies which avoid interventions in tunnel. The
sensor measures the deformation (compression or expansion) of the concrete to
detect local damages as cracks or global motion such as convergence phenomenon.
Results can be represented by strain mapping in order to identify the disorder.
Abstracts Posters
50 CSHM6
P1
Application of Intelligent Structural Monitoring Based on IPv6
Hong, W.X.1, Fang, C.1,2, Yao, H.B.1, Li, L.J.1
1Nanjing Zhixing Information Technology Co., Ltd., Nanjing, China
2Tongji University, Shanghai, China
The project makes use of IoT, cloud computing, big data, mobile internet, 3D and
other advanced technologies as well as engineering structural models and expert
knowledge base, is mainly applied in intelligent transportation fields, and can
realize the following functions:
(1) The application integrates IoT technology with road & bridge monitoring
sensor devices to carry out wireless data collection on road & bridge structure,
traffic flow, vehicle operation and other information of the road & bridge, and
realizes real‐time sensing and intelligent analysis.
(2) The application makes use of cloud computing platform to memorize plenty of
data collected by the road & bridge monitoring system, which has rapid and
efficient processing capability over the structural and non‐structural data.
(3) The application applies big data technology to carry out real‐time processing
and analysis over the plenty of data on the cloud computing platform, and makes
use of expert knowledge base and road & bridge structural models to carry out
data mining, and realizes the real‐time assessment and auxiliary decision‐making
over road & bridge state and traffic condition.
(4) The cloud service release platform, through intelligent terminal, sends the
information to industrial managers and public, realizes intelligent traffic acts such
as road & bridge safety assessment, congestion warning and traffic guidance, and
raises people’s sensing capability on road & bridge state and traffic condition.
This application can solve the urgent needs of the industry, promote social
management and public service level, and is of great significance to the promotion
& application in transportation industry.
Abstracts Posters
CSHM6 51
P2
A Strain Correlation Based Damage Detection Framework for Railway Bridges
Azim, M. R.1, Renker, F.2, Gül, M.3, Cheng, J.J.R.4, Bindiganavile, V.5
1 Ph.D. Student & Graduate Research Assistant, Department of Civil & Environmental Engineering, University of Alberta, Canada.
2 University of Applied Sciences Leipzig, Germany, Graduate Research Assistant, University of Alberta, Canada.
3 Assistant Professor, Department of Civil & Environmental Engineering, University of Alberta, Canada.
4 Professor, Department of Civil & Environmental Engineering, University of Alberta, Canada.
5 Assistant Professor, Department of Civil & Environmental Engineering, University of Alberta, Canada.
Bridges are critical components of the railway infrastructure system and the majority of
these bridges are approaching their estimated design life. Day‐by‐day, the demands on
the bridges have been burgeoning both in terms of increased axis loads and operation
frequency. The principle goal of this on‐going study is to develop powerful health
monitoring and damage investigation strategies tailored for railroad bridges. In this
paper, we present our preliminary findings to build up a damage identification
framework based on strain measurements. Initially, a Finite Element Model (FEM) of a
railway bridge is developed to conduct numerical studies and gather strain data under
moving train for both baseline and damaged conditions. This info is scrutinized
utilizing a strain correlation based damage identification technique. The investigation
demonstrates the deviations in the correlation coefficients for locations of interest so
that damages (i.e., member strength and/or stiffness reduction, changes in boundary
conditions) could be identified and located. The relative severity of the damage can be
assessed by using the magnitude of the changes in the strain correlations. Assessing the
condition of railway bridges continuously in this manner is deemed valuable for the
infrastructure owners for developing economical and effective maintenance strategies.
Abstracts Posters
52 CSHM6
P3
Static and Dynamic Elastic Moduli of Historical Brick Masonry Subjected to Freeze-Thaw Cycles
Merli, F.1 and Tang, Y.J.2
1 Historic Building Rehabilitation, Engineering of Building Processes and System, University of
Bologna, Italy
2 Department of Geotechnical Engineering, Civil Engineering, Tongji University, China
The research is focused on influence of freeze‐thaw cycles on elastic modulus
of historic brick masonry subjected to compressive loading test. In order to
assess the relative decrease of the static elastic modulus during compressive
test, a series of masonry specimens were manufactured with historical bricks
and exposed to different number of freeze‐thaw cycles.
Moreover, strength decay of the masonry is investigated and analysing data
obtained during ultrasonic test (non‐destructive test). The aim of this step is to
obtain the dynamic elastic modulus.
The analysis shows that during initial loading, the static elastic modulus
grows, but at higher stress levels it decreases with increasing load. On the
other hand ultrasonic test, at higher stress levels, the dynamic modulus
continue to rise with increasing load.
However, results indicate that Young’s modulus decreases with the growth in
number of freeze‐thaw cycles.
Thanks to interpolation of the obtained data it will be possible to improve the
knowledge of the Elasticity modulus’ reduction of historic masonry subjected
to freeze‐thaw cycles and to enhance the thermo‐hydro‐mechanical model of
porous material.
Abstracts Posters
CSHM6 53
P4
Moving Force Identification as a Bridge Damage Indicator
Sevillano, E.1, OBrien, E.J.1, Fitzgerald P.C. 1
1 School of Civil Engineering, University College Dublin, Ireland
Visual inspections are the primary method today for ascertaining the
condition of bridges. Visual inspection involves problems such as human
objectivity and inconsistency between inspectors. Some methods of bridge
damage detection make use of the relationship between changes in stiffness or
mass and changes in first natural frequency of the bridge. Any change in the
natural frequency of the bridge might then indicate damage. Mode shapes
have also been used but are more difficult to infer from measurements.
This paper describes an alternative approach which uses an indirect indicator
of a change in bridge condition. Moving Force Identification (MFI) is an
algorithm that calculates the applied axle forces due to a passing vehicle. It is
an ill‐conditioned process that requires regularisation. It has been found that a
small amount of damage (loss of stiffness) in a bridge changes the calculated
force history quite significantly, i.e., MFI can be used as a bridge condition
indicator. This paper investigates the use of MFI in conjunction with bridge
deflection data obtained from high resolution cameras.
Presenting Authors
54 CSHM6
Akhras, G., Royal Military College of Canada, Kingston, Canada
Alhaddad, M., University of Cambridge, UK
Baessler, M., BAM, Berlin, Germany
Bao, Y., Harbin Institute of Technology, China
Bejarano‐Urrego, L., KU Leuven, Belgium
Brownjohn, J.M.W., University of Exeter, UK
Carrion, F.J., Instituto Mexicano del Transporte, Querétaro, Mexico
Catbas, F. Necati, University of Central Florida, Orlando, USA
Ceravolo, R., Politecnico di Torino, Italy
Clemente, P., ENEA, Rome, Italy
Doherty, P., Gavin and Doherty Geosolutions Ltd., Ireland
Glisic, B., Princeton University, USA
Gooderham, T., Intertek, Oxford, UK
Gül, M., University of Alberta, Canada
Gunn, D., British Geological Survey, Nottingham, UK
Hee, L.M., Universiti Teknologi Malaysia, Malaysia
Iten, M., Marmota Engineering AG, Zurich, Switzerland
Kim, C.W., Kyoto University, Japan
Klatter, L., TNO, Delft, Netherlands
Li, H., Harbin Institute of Technology, China
Lienhart, W., Graz University of Technology, Austria
Mazzanti, P., NHAZCA S.r.l. and Sapienza University of Rome, Italy
McGetrick, P.J., Queen’s University Belfast, Northern Ireland, UK
Merino, Y., University of Ibagué, Ibagué, Colombia
Merli, F., University of Bologna, Italy
Presenting Authors
CSHM6 55
Michelin, F., Cementys, Paris, France
Mufti ,A., University of Manitoba at Winnipeg, Canada
O’Higgins, C., McFarland Associates Ltd, Belfast, Northern Ireland, UK
OBrien, E.J., University College Dublin, Ireland
Oliveira, G., University of Porto, Portugal
Peelen, W.H.A., Rijkswaterstaat, Utrecht, Netherlands
Ruffell, A., Queen’s University Belfast, Northern Ireland, UK
Sevillano, E., University College Dublin, Ireland
Tang, Y.J., Tongji University, China
Torbol, M., UNIST, Republic of Korea
Tzoura, E.A., University of Leeds, UK
Utili, S., University of Warwick, Coventry, UK
Zaki, M.A., HBRC, Egypt
Zhang, C., University of Greenwich, Kent, UK
Author Index
56 CSHM6
A
Abdel-Jaber, H. ....................................... 18 Acikgoz, S. ................................................ 35 Akhras G. .................................................. 22 Algohi, B. .................................................. 28 Alhaddad, M. ........................................... 35 Amato, G. .................................................. 32 Anderson, M. ........................................... 48 Azim, M.R. ................................................. 51
B
Baessler, M. .............................................. 31 Bakht, B. .................................................... 28 Bao, Y. ................................................. 14, 25 Basheer, P.A.M. ....................................... 19 Bejarano-Urrego, L. ............................... 38 Bindiganavile, V. .................................... 51 Bongiovanni, G. ...................................... 21 Botero, J.C. ............................................... 44 Brownjohn, J.M.W. ......................... 27, 30 Buffarini, G. .............................................. 21
C
Caetano, E. ............................................... 23 Callender, P.............................................. 47 Carrion, F.J. .............................................. 29 Catbas, F.N. .............................................. 15 Ceravolo, R. .............................................. 43 Chambers, J.E. ......................................... 36 Chen, H.P. ................................................. 46 Cheng, J.J.R. ...................................... 20, 51 Choutopoulou, E. ................................... 19 Clemente, P. ............................................ 21 Crespo, S.E. .............................................. 29
Cunha, Á. .................................................. 23
D
Darsono, D. ............................................. 24 Dashwood, B. ......................................... 36 Declercq, P.Y. .......................................... 38 Dijkstra, T. ................................................ 36 Di-Murro, V. ............................................. 35 Doherty, P. ............................................... 39 Donohue, S. ............................................ 36
F
Fang, C. ..................................................... 50 Faraz, S. ..................................................... 28 Felici, P. ..................................................... 21 Fischli, F. ................................................... 40 Fitzgerald P.C. ........................................ 53
G
Gilmore, D. ............................................. 47 Glisic, B. .................................................... 18 Goi, Y. ........................................................ 42 Gooderham, T. ....................................... 48 Gül, M. ................................................ 20, 51 Gunn, D. ................................................... 36
H
Hee, L.M.................................................... 45 Helmi, K. ................................................... 28 Hester, D. .......................................... 27, 32 Hille, F. ...................................................... 31 Hong, W.X. ............................................... 50 Hughes, D. ............................................... 33 Huseynov, F. ........................................... 27
Author Index
CSHM6 57
I
Iten, M. ...................................................... 40 J
John, G. ..................................................... 48
K
Kim, C.W. .................................................. 42 Kirkham, M. ............................................. 36 Klatter, L. .................................................. 30 Kliewer, K. ................................................ 18 Kollia C. ..................................................... 19
L
Lamour, V. ............................................... 49 Laory, I. ..................................................... 19 Leong, M.S. .............................................. 45 Li, H. .....................................................14, 25 Li, L.J. ......................................................... 50 Li, S. ............................................................ 14 Li, X. ........................................................... 18 Lienhart, W. ............................................. 34 Locklin, L. ................................................. 22 Lydon, M. ................................................. 32
M
Magalhães, F. .......................................... 23 Maraval, D. .............................................. 49 Martinez, D. ............................................. 26 Mazzanti, P. ............................................. 16 McFarland, B. .......................................... 47 McGetrick, P.J. ........................................ 32 Medrano, C.............................................. 49 Merino, Y. ................................................. 44 Merli, F. ..................................................... 52
Michelin, F. .............................................. 49 Miraglia, G. ............................................... 43 Morton, R.F. ............................................. 35 Mufti, A. .................................................... 28
N
Nafari, S.F. ................................................ 20
O
O’Higgins, C. ........................................... 47 OBrien, E.J. ................................. 26, 27, 53 Oliveira, G. ............................................... 23 Orellana, J. ............................................... 22
P
Paris, J.B. ................................................... 49 Park, K.T. ................................................... 24 Peelen, W.H.A. ........................................ 30 Puzrin, A. M. ............................................ 40
Q
Quintana, J.A. .......................................... 29
R
Reilly, J. ..................................................... 18 Renker, F. .................................................. 51 Ruffell, A. .................................................. 33
S
Saitta, F. .................................................... 21 Serafini, S. ................................................ 21 Sevillano, E. ...................................... 26, 53 Sigurdardottir, D.H. .............................. 18 Soga, K. ..................................................... 35 Surace C. ................................................... 43 Swift, R. ..................................................... 36
Author Index
58 CSHM6
T
Tang, Y.J. ............................................ 41, 52 Taylor, S.E. .................................. 32, 33, 47 Torbol, M. ................................................. 24 Triantafillou, T.C. .................................... 19 Tzoura, E.A. .............................................. 19
U
Uhlemann, S. ........................................... 36 Utili, S. ........................................................ 37
V
Van Balen, K. ............................................ 38 Verstrynge, E. .......................................... 38 Viles, S........................................................ 48
W
Weber, R. .................................................. 35 Wuyts, V. ................................................... 38
Y
Yao, H.B. .................................................... 50
Z
Zaki, M.A. .................................................. 17 Zhang, C. .................................................. 46 Zhang, D. .................................................. 14 Zhou, W. ................................................... 14
CSHM6 59
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