Field Testing Implementation of Vibration Based Damage Detection Techniques on a Scoured Coastal Bridge.

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Seracino).

Vibration based damage detection techniques were applied to an existing coastal bridge to

evaluate the ability of the methods to detect scour at the foundation as well as to determine

the practicality of using these testing methods in the field. A study of recent bridge failures

revealed that hydraulic damage is a leading cause of bridge failures in the United States.

Scour is a type of hydraulic damage that may result from a coastal storm. Scour occurs when

water current washes away compacted sediment from around bridge pilings. Methods have

been implemented in the field that visually inspect for scour or use underwater equipment. The true extent of damage caused by scour is not always visually observable. Also

underwater equipment can be laborious to install and operate and are prone to damage.

Vibration based damage detection techniques have been developed to successfully detect

damage in steel girders. This idea was translated into methods to evaluate an idealized

two-span steel bridge laboratory model for the presence and location of scour. The advantage of

using these testing methods is that the testing process can take place from the superstructure

and evaluate the response of the structure to determine the existence and location of damage.

Laboratory models cannot capture every feature of an existing structure, such as ambient

loading and various environmental conditions. Based on this, it was necessary for these

methods to be applied to an existing structure to evaluate the proposed methods ability to

detect scour.

The Northeast Creek Bridge in Jacksonville, N.C. was chosen to implement the field

monitoring techniques. A dive team visually observed scour at the foundation and

recommended the bridge be repaired. The bridge was monitored both before and after the

repair so the change in dynamic characteristics could be observed by applying the proposed

damage detection techniques. Accelerations of the bridge responding from an impact

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deflection and the change in the curvature of the flexibility based deflected shape. From data

analysis, it was observed that the flexibility based deflection method most accurately

identified the existence and location of scour.

A finite element model of the bridge was created to guide the selection of testing equipment.

The damage features were applied to the finite element model for comparison. It was

observed that all of the proposed methods were successful in indicating scour for the finite

element model. Based on this, the assumption was made that the curvature based methods

perform better with theoretical data than field data.

A main advantage of using vibration based damage detection techniques is that field

monitoring can be implemented quickly and easily following a coastal storm. It is not

necessary to have a finite element model for this method, which would be a time consuming

and costly task. It is however necessary for data sets to be available for a healthy bridge for

the methods to be applied. It is recommended to continuously monitor scour critical bridges

before and after coastal storms to track changes in dynamic characteristics that can indicate if

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by

Anna Katherine Harris Clark

A thesis submitted to the Graduate Faculty of North Carolina State University

in partial fulfillment of the requirements for the degree of

Master of Science

Civil Engineering

Raleigh, North Carolina

2013

APPROVED BY:

_______________________________ ______________________________

Dr. Rudolf Seracino Dr. Sami Rizkalla

Committee Chair

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DEDICATION

This work is dedicated to my father and mother, who have always had the highest hopes for

me, to my Great Aunt Ruby who supported, encouraged and believed in me, and to Frank

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BIOGRAPHY

Anna Katherine Harris Clark was born in Goldsboro, NC to Richard and Paula Harris. She

graduated from Greene Central High School as class valedictorian in 2006 and enrolled in the

North Carolina State University College of Engineering with much encouragement from her

N.C. State engineering alumni father and brother. During her undergrad career she

completed three co-op rotations working at ABB Power System division where she learned

the basics of the civil engineering design process. She also participated in Campus Crusade

for Christ and a Civil Engineering Study Aboard trip to Australia. She graduated Summa Cum Laude in December 2010 with a Bachelor of Science degree in Civil Engineering.

Following graduation, she began working towards her Master of Science degree in Civil

Engineering, specializing in Structural Engineering, under the guidance of Dr. Rudolf

Seracino. During graduate school, she worked as a research assistant. She plans to begin a

career as a Structural Engineer and eventually pursue her P.E. licenses following the

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ACKNOWLEDGMENTS

I am thankful to God and the relationship I have with him through Jesus Christ. He has

shared many great blessings with me.

I would like to thank Dr. Rudolf Seracino for providing me with many great academic

opportunities and guidance. Also, I would like to thank Dr. Adel Elsaid for his time, support

and advice throughout this project. I would like to express my appreciation to Dr. Sami

Rizkalla and Dr. Mohammad Pour-Ghaz for their participation in my advisory committee.

I would like to acknowledge the support of the Department of Homeland Security Coastal

Hazards Center of Excellence as well as its staff and fellow researchers. I would like to

thank the NCSU Constructed Facilities Laboratory staff and students whom aided in the

experimental testing, particularly Mr. Greg Lucier, Mr. Jerry Atkinson, Mr. Jonathan

McEntire, Mr. Guanglong Qu and Mr. Omar Mohamedian. Also, I sincerely thank the N.C.

DOT Division 3 Bridge Maintenance Engineers who truly made this research project

possible, particularly Mr. Trevor Carroll.

Finally, I thank my family and Frank who have always supported and encouraged me

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TABLE OF CONTENTS

List of Tables ... vii

List of Figures ... viii

Chapter 1. Introduction ...1

1.1 Structural Health Monitoring ...2

1.2 Research Significance ...3

1.3 Research Scope and Methodology ...4

1.4 Organization of the Thesis ...4

Chapter 2. Literature Review ...7

2.1 Introduction ...7

2.2 Review of Bridge Failures ...7

2.2.1 Storm Surge Bridge Failures ...9

2.2.2 Scour Damaged Bridges ...14

2.3 Methods for Monitoring Bridges for Scour ...21

2.3.1 Streambed Elevation Measuring Methods ...22

2.3.2 Fiber-Optic Sensors Bridge Monitoring ...25

2.3.3 Robot Assisted Bridge Monitoring ...29

2.3.4 Tiltmeters Monitoring ...30

2.4 Vibration Based Superstructure Monitoring Techniques ...32

2.5 Summary ...41

Chapter 3. Bridge Field Monitoring...42

3.2 Bridge Geometry ...43

3.3 Selecting Accelerometers ...45

3.4 Selecting Accelerometer Spacing ...47

3.5 Accelerometer Test Setup ...54

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3.7 Impact Load Test Setup ...60

3.8 Damaged Bridge Test ...62

3.9 Bridge Retrofit ...64

3.10 Repaired Bridge Test ...66

Chapter 4. Analysis of Field Data ...68

4.2 Frequency Response Functions ...68

4.3 Mode Shapes and Natural Frequencies ...72

4.4 Changes in Curvature of Mode Shapes ...87

4.5 Changes in Flexibility Deflection...94

4.6 Changes in Flexibility Curvature ...100

4.7 Damage Features Summary ...106

Chapter 5. Finite Element Model and Analysis of the Northeast Creek Bridge ...108

5.2 Finite Element Model Description ...108

5.3 Collection of Accelerations, Natural Frequencies and Horizontal Mode Shapes .112 5.4 Changes in Horizontal Mode Shape Curvature Damage Feature ...119

5.5 Changes in Flexibility Based Deflection ...125

5.6 Changes in Flexibility Based Curvature ...130

5.7 Damage Features Summary ...135

Chapter 6. Conclusions ...137

6.1 Summary of Findings ...137

6.2 Future Work Recommendations ...145

References ...147

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LIST OF TABLES

Table 2.1: Types of bridge failures from 1989 to 2000 [Wardhana et al., 2003] ...10

Table 4.1: Natural frequency in Hz for the first six mode shapes for each span and the

average in the healthy and scoured bridge condition ...80

Table 5.1: Finite element model natural frequencies for the repaired and scoured conditions

and percent change between both conditions ...118

Table 5.2: Percent change between repaired and scoured natural frequencies for the finite

element model and the field testing ...118

Table 5.3: Percent change between field testing and the finite element model natural

frequencies for the first 6 horizontal mode shapes ...119

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LIST OF FIGURES

Figure 2.1: Number of failed bridges distributed by year [Wardhana et al., 2003] ...8

Figure 2.2: Interstate-10 bridge failure resulting from Hurricane Ivan [Douglass et al., 2004]

...11

Figure 2.3: Soil washed away from the Bob Sykes Bridge abutment due to Hurricane Ivan

[Douglass et al., 2004] ...12

Figure 2.4: Little Lagoon bridge deck damage due to Hurricane Ivan [Douglass et al., 2004]

...12

Figure 2.5: Escambia County Road 191 Bridge repaired after Hurricane Ivan [Douglass et al.,

2004] ...13

Figure 2.6: Collapse of US 90 Bridge deck over Biloxi Bay Mississippi [Chen et al., 2009] 14

Figure 2.7: Localized scour at a pile due to Hurricane Ike [FEMA, 2009] ...15

Figure 2.8: Scour depth in a sand-bed stream over time [FHWA, 2001] ...17

Figure 2.9: Horseshoe vortex around the base of a piling causing local scour [FHWA, 2001]

...18

Figure 2.10: US 90 bridge in Bay St. Lewis experienced up to 4.5 meters of scour during Hurricane Katrina [Robertson et al., 2007] ...20

Figure 2.11: Echo sound transducer measuring streambed depth [Mueller et al., 1999] ...23

Figure 2.12: Fiber-optic sensor connected to rod implanted in riverbed [Zarafshan et al.,

2012] ...25

Figure 2.13: Barrier rod installation in streambed [Zarafshan et al., 2012] ...26

Figure 2.14: Scour levels recorded from sensor located near a bridge pier [Zarafshan et al.,

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Figure 2.15: Sensors on a bridge pier and the cross section of a sensor [Manzoni et al., 2011]

...28

Figure 2.16: UMV used to inspect Rollover Pass Bridge called a Sea-RAI USV [Murphy et al., 2011] ...29

Figure 2.17: Tiltmeter instrumentation plan [Briaud et al., 2011] ...31

Figure 2.18: Idealized two-span steel bridge laboratory model [Elsaid, 2011] ...34

Figure 2.19: CDF and MCDF values for the finite element model idealized two-span steel model [Elsaid, 2011] ...36

Figure 2.20: CDF and MCDF values for the idealized two-span steel laboratory model [Elsaid, 2011] ...37

Figure 2.21: Idealized two-span finite element model change in flexibility deflection for 24 inches of symmetrical scour [Elsaid, 2011] ...38

Figure 2.22: Idealized two-span laboratory model change in flexibility deflection for 24 inches of symmetrical scour [Elsaid, 2011] ...39

Figure 2.23: Change in curvature of flexibility based deflection between the finite element model with 24 inches of symmetrical scour and the healthy model [Elsaid, 2011] ...40

Figure 2.24: Change in curvature of flexibility based deflection between the laboratory model with 24 inches of symmetrical scour and the healthy model [Elsaid, 2011] ...40

Figure 3.1: Bridge selected for testing over the Northeast Creek in Jacksonville, NC ...42

Figure 3.2: Section of bridge deck and girders ...43

Figure 3.3: Details of the pier located in the Northeast Creek ...44

Figure 3.4: Vertical scour depths at each pile ...45

Figure 3.5: Triangular impact load used in the finite element model ...46

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Figure 3.7: Spacing of measurement points versus average mutual information of points

[Trendafilova et al., 2001] ...50

Figure 3.8: Three test setups of varying sensor spacing [Trendafilova et al., 2001] ...50

Figure 3.9: Histogram values for the first ten nodes ...52

Figure 3.10: Average mutual information values based on the finite element model ...53

Figure 3.11: Girders of the two spans at the center pier support ...54

Figure 3.12: Sensor spacing near center pier ...55

Figure 3.13: Accelerometer locations ...56

Figure 3.14: NCDOT Hydra-Platform truck used during testing ...57

Figure 3.15: (a) NI PXI-4496 High Channel Industrial Platform Module and (b) NI PXI-1033 5-Slot Chassis ...58

Figure 3.16: Computer and Data Acquisition System during testing ...59

Figure 3.17: Impact hammer model PCB 086D50 ...60

Figure 3.18: Impact locations ...61

Figure 3.19: Impact hammer used during testing ...62

Figure 3.20: Impact load (a) between sensors 6 and 7 and the resulting accelerations (b) at sensor 7 as recorded during the first test at this location on the first span during damaged testing ...64

Figure 3.21: Scoured piles exposed to the creek water ...65

Figure 3.22: Base board attached to the footing (a) jackhammer boards into the soil (b) attach vertical boards to the base board (c) to create formwork for the cementitious non-excavatable flowable fill ...66

Figure 4.1: Single input and single output system ...69

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Figure 4.3: MATLAB plot of the absolute value of the tfestimate function for the fourth test

on the first sensor on the second span of the damaged bridge with an impact between the

fourth and fifth sensor ...72

Figure 4.4: FRF versus frequency for the 10 sensors used on the fourth test of the second

span of the damaged bridge while impacting between the fourth and fifth sensor ...73

Figure 4.5: Dynamic amplification factors at different frequency ratios and damping ratios

[Zhou, 2006] ...75

Figure 4.6: FRF magnitude and phase angle versus frequency for sensors 3, 4 and 5 used on

the fourth test of the second span of the damaged bridge while impacting between the fourth

and fifth sensor ...77

Figure 4.7: Mode shapes 2 through 6 found from each span test for the scoured bridge ...82

Figure 4.8: Mode shapes 2 through 6 of each span extracted for the repaired bridge ...84

Figure 4.9: Complete 6 mode shapes for the center two spans of the scoured and repaired

bridge ...86

Figure 4.10: CDF calculated considering comparisons of horizontal mode shapes 1, 2 and 3

...89

Figure 4.11: CDF calculated considering comparisons of most scour sensitive horizontal

mode shapes 1, 3 and 5 ...89

Figure 4.12: CDF calculated considering comparisons of horizontal mode shapes 1, 2, 3, 4

and 5 ...90

Figure 4.13: CDF calculated considering comparisons of horizontal mode shapes 1, 2, 3, 4, 5 and 6 ...90

Figure 4.14: MCDF calculated considering comparisons of horizontal mode shapes 1, 2 and 3

...92

Figure 4.15: MCDF calculated considering comparisons of the most scour sensitive

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Figure 4.16: MCDF calculated considering comparisons of horizontal mode shapes 1, 2, 3, 4

and 5 ...93

Figure 4.17: MCDF calculated considering comparisons of horizontal mode shapes 1, 2, 3, 4,

5 and 6 ...93

Figure 4.18: Flexibility deflection for the scoured and repaired bridge as well as the absolute

difference between the two conditions considering the mass-normalized horizontal mode

shapes 1, 2 and 3 ...96

difference between the two conditions considering the most sensitive to scour

mass-normalized horizontal mode shapes 1, 3 and 5 ...97

shapes 1, 2, 3, 4 and 5 ...98

shapes 1, 2, 3, 4, 5 and 6 ...99

Figure 4.22: Flexibility deflection curvature for the scoured and repaired bridge as well as the

absolute difference between the two conditions calculated from the mass-normalized

horizontal mode shapes 1, 2 and 3 ...102

horizontal mode shapes most sensitive to scour 1, 3 and 5 ...103

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horizontal mode shapes 1, 2, 3, 4, 5 and 6 ...105

Figure 5.1: Three dimensional view of the scoured bridge finite element model with filled objects ...110

Figure 5.2: Center scoured pier of the finite element model ...111

Figure 5.3: Bridge deck view of the finite element model ...111

Figure 5.4: Three dimensional view of repaired bridge finite element model with outlined objects ...112

Figure 5.5: Node and impact locations ...113

Figure 5.6: Horizontal impact load used in the finite element model ...113

Figure 5.7: FRF magnitude and phase angle versus frequency for nodes 6, 7 and 8 on the second span of the scoured bridge finite element model showing a peak near 40 Hz ...115

Figure 5.8: The first six horizontal mode shapes extracted for the repaired and scoured bridge finite element models ...116

Figure 5.9: CDF values for horizontal mode shapes 1, 2 and 3 ...120

Figure 5.10: CDF values for horizontal mode shapes 1, 3 and 5 ...121

Figure 5.11: CDF values for horizontal mode shapes 1, 2, 3, 4 and 5 ...121

Figure 5.12: CDF values for horizontal mode shapes 1, 2, 3, 4, 5 and 6 ...122

Figure 5.13: MCDF values for horizontal mode shapes 1, 2 and 3 ...123

Figure 5.14: MCDF values for horizontal mode shapes 1, 3 and 5 ...123

Figure 5.15: MCDF values for horizontal mode shapes 1, 2, 3, 4 and 5 ...124

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Figure 5.17: Flexibility deflection for the scoured and repaired finite element model as well

as the absolute difference between the two for horizontal mode shapes 1, 2 and 3 ...126

as the absolute difference between the two for horizontal mode shapes 1, 3 and 5 ...127

as the absolute difference between the two for horizontal mode shapes 1, 2, 3, 4 and 5 ...128

as the absolute difference between the two for horizontal mode shapes 1, 2, 3, 4, 5 and 6 ..129

Figure 5.21: The curvature of the flexibility based deflection for the scoured and repaired bridge and the absolute difference between the two for mode shapes 1, 2 and 3 ...131

Figure 5.22: The curvature of the flexibility based deflection for the scoured and repaired

bridge and the absolute difference between the two for mode shapes 1, 3 and 5 ...132

bridge and the absolute difference between the two for mode shapes 1, 2, 3, 4 and 5 ...133

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Chapter 1. Introduction

Damage detection techniques that are accurate and easy to implement are vital to the health

of bridges in the United States following a meteorological event. The U.S. Department of

Transportation Bureau of Transportation Statistics reported in 2010 that 11.5% of all

highway bridges were structurally deficient and 12.8% were functionally obsolete.

Structurally deficient bridges are in need of repair because the expected load cannot be

carried, while functionally obsolete bridges are in need of immediate repair because their

intended design requirements cannot be met, according to The Association of American State Highway and Transportation Officials (AASHTO) 2009 Bottom Line Report. Wardhana et

al. [2003] completed a comprehensive study of bridge failures from 1989 to 2000 and

observed that hydraulic damage was a leading cause of bridge failures in the U.S.

representing nearly 53% of all bridge failures studied. Hydraulic damage is a common result

of coastal storms. Storm surges may occur during a storm due to a rapid rise in the level of

water. Strong wind-driven waves in combination with a storm surge apply heavy loads to a

bridge deck resulting in connection damage and possible bridge deck uplift [Douglass et al.,

2004]. The resulting strong currents also cause sediment to displace at the streambed level

resulting in scour of the pilings. The scour process is cyclic because sediment is removed

during a storm surge and as the water recedes, scour holes refill with displaced sediment

[FHWA, 2001]. This makes field monitoring for the existence and magnitude of scour

damage very difficult. The holes refilled with sediment are not compacted enough around

the pilings for the structure to receive the required support; therefore, measuring streambed

elevations may not be significant in capturing the full extent of scour [De falco and Mele,

2002]. Also the streambed elevation measurements can be altered due to the presence of

storm debris. Visual inspections may overlook the true magnitude of the damage if scoured

holes have been refilled with sediment. Monitoring methods that involve underwater

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techniques that avoid these common monitoring issues. This need has led to development of

methods that examine the change in vibration characteristics between damaged and healthy

structures [Doebling et al., 1996]. This study explores vibration based damage detection

techniques applied to a coastal bridge as a means to identify the existence of scour at the

pilings.

1.1 Structural Health Monitoring

The application of different field methods to monitor structures for scour is referred to as structural health monitoring. Structural health monitoring is defined as the process of

determining and tracking structural integrity and assessing the nature of damage [Chang et

al., 2003]. Global health monitoring methods are used to determine if damage is present in

the entire structure, while non-destructive evaluations are used as local health monitoring

methods to identify the exact location and extent of damage [Chang et al., 2003]. These two

types of methods are both vital to identifying damage in a structure; however, oftentimes

present a challenge when applying the methods because of attempts to identify local damage

by observing the global response of a structure [Mosavi, 2010]. Adams [2007] describes the

non-destructive evaluations as involving the identification of the loads on the structure,

resulting mechanical damage, the growth of the damage and the future performance of the structure’s components as the damage accumulates. These qualities can be assessed by

modeling the structure, obtaining measurements, data analysis and forming predictions.

Diagnostics is the identification of damage and aims to detect, locate and quantify damage.

This can be done through signal processing and feature extraction of the models measured

variability [Adams, 2007].

Damage alters a structures performance because of a permanent change in its mechanical

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the basis of using vibration based damage detection techniques. Gathering and analyzing the

changes in dynamic characteristics such as natural frequencies, damping ratios, mode shapes

and flexibility between damaged and healthy structures can be used to quantify the existence

and extent of damage [Elsaid, 2011]. There is an added challenge in that data from an

undamaged structure is necessary for comparisons with the damaged structure. Also the

modal characteristics collected must be accurate for the damage detection features to

successfully identify potential damage. Other aspects can alter vibration responses of a

structure such as varying temperature, moisture and loading [Mosavi, 2010].

1.2 Research Significance

This study is focused on the accuracy and practicality of using vibration based damage

detection methods to identify the existence and location of scour on an existing coastal

bridge. Monitoring for scour was chosen as a focus in this study because hydraulic damage

is a common cause of bridge failures and is not simple to identify. Vibration based damage

detection methods would require obtaining modal characteristics by accessing the

superstructure above water. No underwater investigations would be necessary which would

ease operator labor as well as protect equipment from possible water damage. Vibration

based monitoring would be able to assess the condition of the structure itself instead of

simply evaluating the condition of the damage. This is important since scour related damage

cannot always be visually observable. Vibration based methods have been applied to

theoretical finite element models and could successfully identify the existence and location of

damage; however, field application presents a variety of variables that cannot be captured in

a theoretical model, such as environmental conditions and ambient loading. It is necessary

for these methods to be applied to an existing structure in order to validate their ability to

detect the presence and location of scour. The output of this research aims to lead to a

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remaining strength of a bridge. Quickly identifying damage is essential for bridges that are

on critical evacuation or emergency response routes.

1.3 Research Scope and Methodology

In order to apply the vibration based damage features to an existing bridge, the dynamic

characteristics must be known of the healthy bridge as well as the dynamic characteristics of

the scoured bridge. A bridge was chosen for this study that had existing scour at the piles.

The damage was discovered by an underwater dive team. The inspectors recommended the bridge repair be made priority. The dynamic characteristics were collected from the bridge

while the piles were scoured and once again after the bridge had been repaired. The damage

features were applied based on the change in dynamic characteristics between the two

conditions. Accelerations resulting from an impact hammer were collected through field

monitoring and signal processing was used to determine the dynamic characteristics. The

dynamic characteristics analyzed include the natural frequencies, the curvature of the

horizontal mode shapes, the flexibility deflection of the structure and the curvature of the

flexibility deflection. A maximum in the change of dynamic characteristics should identify

the location of damage. A finite element model of the bridge was developed to assist in

selecting the equipment used to perform the monitoring. Damage features were extracted

using data from the finite element model. This was used to compare the effectiveness of the

damage features extracted from theoretical data compared to using data from an existing

coastal structure.

1.4 Organization of the Thesis

This thesis consists of six chapters describing the application of the proposed damage

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Chapter 2 discusses the current conditions of bridges in the United States and common

causes of failure. Scour is presented as a serious and difficult to identify type of bridge

damage that often results from coastal storms. The advantages and disadvantages of the

field application of different types of scour monitoring techniques are discussed. This

includes discussion of the development of vibration based damage techniques that can be

easily and quickly performed on a coastal structure following a storm.

Chapter 3 describes the bridge selected for field monitoring. The process of developing the

testing setup including the number and spacing of accelerometers is described. The selection of the accelerometers, impact hammer and data acquisition system is discussed. A

description of the repairs made to the bridge scour is presented. Discussion and comparison

of the two testing days on the scoured and repaired bridge is also included.

Chapter 4 presents the analysis results of the accelerations collected from the field

monitoring. The chapter also describes how the damage features were calculated. The raw

accelerations are processed through MATLAB and Excel to gather the frequency response

functions that correspond to natural frequencies and horizontal mode shapes of the structure.

The change in the horizontal mode shape curvature, the flexibility deflection and the

curvature of the flexibility deflection is demonstrated for the scoured and repaired bridge.

Discussion on the accuracy of the damage features is included.

Chapter 5 discusses the creation of the finite element model of the bridge. The process of

gathering accelerations and applying the damage features presented in Chapter 4 is discussed.

The challenges of building an accurate finite element model for existing bridges are

presented. This testing does not require a finite element model, so the related advantages are

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Chapter 6 concludes the findings from this study. This includes evaluation of the

effectiveness of the damage features ability to detect scour as well as the practicality of

implementing this type of testing on an existing structure. Also the finite element model and

related challenges are discussed. Future research recommendations are made as well in this

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Chapter 2. Literature Review

2.1 Introduction

Following coastal storms, scour of pilings is a major concern for coastal bridges in the United

States. This type of damage can be difficult to detect because it is not always visually

observable. Much research has been focused on developing scour monitoring techniques that

can be easily implemented in the field after a coastal storm. Vibration based damage

detection techniques have been developed to detect damage in various structures and could potentially be used to detect scour at the pilings of coastal structures. This chapter will

highlight scour as a critical concern to coastal bridges, explore different developed scour

monitoring techniques and consider vibration based damage techniques as an option for scour

monitoring.

2.2 Review of Bridge Failures

Proper detection of damage is critical to the health of bridges in the United States due to the

current condition of many bridges. The U.S. Department of Transportation Bureau of

Transportation Statistics reported in 2010 that there were 604,460 highway bridges in the

country. Of these bridges, 69,220 bridges were considered structurally deficient and 77,412

bridges were functionally obsolete being 11.5% and 12.8% of the total bridges, respectively.

The Association of American State Highway and Transportation Officials (AASHTO) 2009

Bottom Line Report defines structurally deficient bridges as structures that cannot carry the

expected load and are in need of repair. Functionally obsolete bridges are structures unable

to fulfill their design and require immediate repair. AASHTO is concerned with the age of

the majority of bridges in the US. Nearly half of all bridges are more than 40 years old and

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The most recent comprehensive study of bridge failures in the US was completed by

Wardhana et al. [2003] who examined 503 failed bridges occurring from 1989 to 2000 across

the country. The study classified failed bridges as structures or components of structures that

can no longer perform the function for which it was designed. The average age of the failed

bridges was 52 years and the bridges age ranged from under construction to 157 years. The

majority of the bridges studied were steel, concrete or timber. The most common category of

failures was beam/girder failures that made up 37.2% of the failures. Truss failures were also

common representing 23.1% of the total failures. Figure 2.1 shows the number of bridge

failures according to the year the failure occurred.

Figure 2.1: Number of failed bridges distributed by year [Wardhana et al., 2003]

Figure 2.1 shows a peak in bridge failures in 1993 with 112 failed structures. The peak is

attributed to flooding of the Mississippi and Missouri rivers and tributaries that caused bridge failures across Iowa, Minnesota and Missouri. The second highest peak in Figure 2.1

occurred in 1996 and is also attributed to flooding. Six of the ten states with the most failed

bridges were coastal states comprising of 36% of the total bridge failures. The National 55

46

31 ₂₈ 112 33 45 59 18 33 26 17 0 20 40 60 80 100 120

1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000

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Oceanic and Atmospheric Administration (NOAA) states that flooding is often a result of

coastal storms. Flooding causes more damage in the US than any other severe weather

related event and the damage due to flooding has increased greatly since the early 1990’s.

Table 2.1 lists the most common types of bridge failures from the Wardhana et al. [2003]

study. Hydraulic damage caused the majority of failures representing 52.88% of the total

failures with 32.8% of failures being related directly to flooding and 15.51% of failures from scour. Scour is defined as “erosion or removal of streambed or bank material from bridge

foundations due to flowing water, usually considered as long-term bed degradation, contraction and local scour” by the Federal Highway Administration. Based on this

definition, flooding and scour are closely related issues.

According to NOAA coastal counties only represent 17% of the nation’s land, but are home to half of America’s population. Coastal areas are at high risk of coastal storms, flooding,

coastal erosion and land subsidence. These hazards are a threat to infrastructure whose

function is critical for evacuations and emergency response during a coastal storm.

2.2.1 Storm Surge Bridge Failures

Douglass et al. [2004] studied bridge and road failures after Hurricane Ivan passed between

Florida and Alabama in 2004. The researchers observed that the majority of damage was due

to a combination of storm surge and waves on top of the storm surge. A storm surge is

defined as a rapid rise in the level of water that occurs during a storm. Figure 2.2 is the failed

portions of the bridge deck on Interstate-10 crossing the Escambia Bay arm of Pensacola

Bay. The damage is the result of a storm surge that raised the water level to the height of the

bridge deck so that large wave loadings impacted the bridge spans. The force impacting the

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Table 2.1: Types of bridge failures from 1989 to 2000 [Wardhana et al., 2003]

Failure causes and events Number of occurrences Percentage of total

Hydraulic 266 52.88

Flood 165 32.80

Scour 78 15.51

Debris 16 3.18

Drift 2 0.40

Others 5 0.99

Collision 59 11.73

Auto/truck 14 2.78

Barge/ship/tanker 10 1.99

Train 3 0.60

Other 32 6.36

Overload 44 8.75

Deterioration 43 8.55

General 22 4.37

Steel deterioration 14 2.78

Steel-corrosion 6 1.19

Concrete-corrosion 1 0.20

Fire 16 3.18

Construction 13 2.58

Ice 10 1.99

Earthquake 17 3.38

Fatigue-steel 5 0.99

Design 3 0.60

Soil 3 0.60

Natural Disaster 2 0.40

Miscellaneous/other 22 4.37

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Figure 2.2: Interstate-10 bridge failure resulting from Hurricane Ivan [Douglass et al., 2004]

Figure 2.3 shows the approach to the Bob Sykes Bridge abutments where the embankments

have been eroded due to exposure to storm surge and waves. From inspection of Figure 2.3

the former soil line is visible before the abutment soil washed away causing scour. Figure

2.4 is of the Little Lagoon bridge deck with damage caused by storm surge currents and

waves. Figure 2.5 is of the repaired Escambia County Road 191 Bridge that suffered from embankment erosion and deck damage due to storm surge current and wave forces.

Douglass et al. [2004] notes that each of these bridges are located very close to the ocean and

likely received a much higher combined force from the storm surge current and waves than

inland bridges experienced from flooding of rivers. Coastal bridges are at the frontline for

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Figure 2.3: Soil washed away from the Bob Sykes Bridge abutment due to Hurricane Ivan

[Douglass et al., 2004]

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Figure 2.5: Escambia County Road 191 Bridge repaired after Hurricane Ivan [Douglass et al.,

2004]

One year after Hurricane Ivan, Hurricane Katrina made landfall in the same region of the

country causing additional damage. Combined, the two storms cost an excess of 1 billion

dollars to rebuild coastal bridges [Chen et al., 2009]. Much like Hurricane Ivan, the failure

of most bridges resulted from waves in combination with storm surge current. Chen et al.

[2009] describes the increased force resulting from water rising to a level with strong winds

that generate waves over a short distance to strike the bridge superstructure causing both an

uplift force and horizontal force. The uplift force can exceed the weight of the bridge deck and the horizontal force can exceed the resistance of the connections of the deck to the piling

caps. This causes the deck to detach from the substructure. This is shown in Figure 2.6 in a

photograph of the failure of the US 90 bridge over Biloxi Bay in Mississippi during

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Figure 2.6: Collapse of US 90 Bridge deck over Biloxi Bay Mississippi [Chen et al., 2009]

Coastal storms are an obvious threat to coastal bridges, but sometimes the damage due to a

storm is less apparent. Identification of damage that is not clearly visible is essential in

assessing the condition of coastal structures after a meteorological event.

2.2.2 Scour Damaged Bridges

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result, soil becomes loosened and suspended by the flow of the water and washes away from

the site. The effect of scour is related to the velocity and turbulence of water as well as the

type of soil surrounding the foundation [FEMA, 2009]. Scour is often the resulting damage

due to a storm surge. Figure 2.7 shows localized scour at a foundation pile after Hurricane

Ike.

Figure 2.7: Localized scour at a pile due to Hurricane Ike [FEMA, 2009]

Difficulties arise when estimating the magnitude of scour occurring on underwater

foundations. This is due to the cyclic nature of the process that causes scour. Scour can be

very deep at the time of flooding and then as waters recede the scour holes can refill with

displaced sediment [FHWA, 2001]. Shallow foundations suffering from scour are subject to

collapse. Scour of deeper foundations may collapse the structure or experience uneven

vertical settlement of the structure along with lateral displacement from lateral loads. Also,

the unbraced length of the pilings is increased resulting in an increase of the bending moment

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The three main types of scour affecting most bridges include long-term degradation of the

river bed, general contraction scour at the bridge and local scour at the piers or abutments

[FHWA, 2001]. These three types of scour are independent from one another. Long-term

degradation refers to natural or man-made changes in the trend of the stream or watershed

that causes sediment to be displaced overtime and the elevation of the streambed is changed.

This type of scour can be identified by monitoring streambed elevations overtime. General

scour and local scour can be one of two conditions, clear-water scour or live-bed scour.

Clear-water scour occurs when no bed sediment material is transported except locally around

pilings. Live-bed scour is the transfer of bed material and is often cyclic because the scour hole develops during a flood and later refills as the storm surge water elevation falls. During

flooding, streams with coarse-bed material typically have clear-water scour when discharge,

the volume of water passing a point, is low. Live-bed scour happens at higher stream

discharges and clear-water discharge occurs as the flood subsides and the stream discharge

falls. The condition of scour can be determined based on the particle size of the streambed as

well as the velocity of the flow of the water. In sand-bed streams, most commonly found

near the coast, live-bed scour fluctuates between scour and refill with a maximum scour

depth about 30% higher than the equilibrium depth experienced between scour and refill.

For the same sand-bed, clear-water scour increases steadily overtime and will generally reach

a maximum of 10% greater scour depth than the live-bed equilibrium depth. This change in

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Figure 2.8: Scour depth in a sand-bed stream over time [FHWA, 2001]

Contraction scour occurs during a flood when the flow area of the body of water is decreased

resulting in an increase in average flow velocity. An increase in water velocity causes

sediment to be removed and relocated. Contraction scour may occur because of bridge

abutments or piers obstructing the area of flow. Contraction scour involves sediment

removal for typically all or most of the channel width. Live-bed contraction scour is

typically cyclic because soil washes out and falls back into place; therefore, it is difficult to

measure after a meteorological event. Clear-water scour often occurs locally around the piles

or abutments that are obstructing the flow of water. The acceleration of water around the

obstructions removes soil at the base by creating vortices. The type of vortex created around

the obstruction is known as the horseshoe vortex. The rate of transport of sediment from

around the base of the obstruction is greater than the transport rate in the surrounding flow

causing a scour hole to form. This action is demonstrated in Figure 2.9. As the size of the

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after the hole is formed will decrease creating equilibrium [FHWA, 2001]. Suspended

sediment may settle into the scour hole.

Figure 2.9: Horseshoe vortex around the base of a piling causing local scour [FHWA, 2001]

Local scour depth at piers and abutments is mainly governed by the velocity and depth of

flow, size and shape of the structure obstructing flow, size and gradation of the bed material,

angle between the flow and obstruction object, bed configuration and possible jams or debris

[FHWA, 2001]. Based on the many factors affecting scour, identifying the extent of scour is

difficult to determine or predict due to a coastal storm.

Researchers from the Naval Research Laboratory [Teague et al., 2006] placed moorings off

the coast in the Gulf of Mexico and took measurements of the change in sediment levels after

Hurricane Ivan passed over the location of six of the moorings. They observed a displacement of over 100 million cubic meters of sediment from the 35x15 km region

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wind stress and recorded depths of 360 mm and 320 mm of scour. This was caused by wave

velocities and wind currents occurring at the ocean floor that generated a vortex causing

sediment suspension and removal. Therefore, the forces from storm surge currents and

waves that threaten collapse of bridge decks are the same forces that act at the sediment level

and displace soil surrounding the substructure.

Robertson et al. [2007] observed that in Hurricane Katrina the majority of structures were

damaged due to uplift, excessive lateral loading, restraint failure, debris effects and scour.

The researchers observed extensive levels of scour around bridge abutments and piers in the Gulf Coast area that led to collapse or partial collapse of many of the structures. The type of

scour that affected most of the structures is called liquefaction-induced scour that occurred as

a result of a storm surge. As the name implies, the soil behaves like a viscous liquid and is

easily transported with the flow of water. Saturated sandy soil is subject to local

liquefaction-induced scour due to wave action. Figure 2.10 is the US 90 bridge in the town

of Bay St. Louis, about 30 miles from the Biloxi Bay Bridge in Figure 2.6. The Bay St.

Louis Bridge experienced extensive scour along the Mississippi coastline due to Hurricane

Katrina at a maximum depth about 4.5 meters. The approach to the abutments as well as the

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Figure 2.10: US 90 bridge in Bay St. Lewis experienced up to 4.5 meters of scour during

Hurricane Katrina [Robertson et al., 2007]

Just as scour can occur on coastal structures due to flood water, it can also be caused by tidal

fluctuation. Scour that occurs due to tide changes may occur in two directions, as opposed to

one main direction for scour occurring due to a storm surge. Structures in waterways

exposed to tidal change may experience increase in soil discharge from the foundations as the

waterway area increases with the tide [FHWA, 2001].

Hydraulic damage is the most frequent cause for bridge failures representing nearly half of

all failures [Wardhana et al., 2003]. Both uplift of bridge decks as well as scouring of

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Monitoring for scour was chosen as a focus for the Department of Homeland Security

because it is an issue that is not always visually observable. Proper identification of scour

damage immediately following a meteorological event is essential for emergency response

and recovery.

2.3 Methods for Monitoring Bridges for Scour

Much research is focused on developing methods to monitor scour because accurate

assessment of scour damage is difficult to determine. Flood water accelerates around an object blocking its flow, such as a pile, and removes sediment from around the base creating

scour. As the scour hole increases in size, the flow in the vortex decreases causing the

amount of sediment being displaced to decrease [FHWA, 2001]. The suspended sediment

may settle into the scour hole and will not be compacted enough to provide adequate

confinement for the pile. This action shows that simple measurements of sediment levels

after a flood may not be significant in fully capturing the extent of scour [De falco and Mele,

2002].

The US Geological Survey (USGS), the Federal Highway Administration (FHWA) as well as

various states Department of Transportation (DOT) organizations have invested in scour

related research. The USGS in collaboration with the FHWA have created a database of

scoured bridges across the US and have drafted documents and training materials with

recommendations for engineers facing scour related design problems. In addition to

government research, there have been many academic research programs related to scour

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2.3.1 Streambed Elevation Measuring Methods

Mueller et al. [1999] collaborated with the USGS to investigate scour monitoring methods

using sounding weights and echo sounders to measure the streambed elevation changes

during and after a flood. These two methods represent common portable streambed elevation

measuring devices. The streambed elevation is measured by observing the distance between

a known datum and the streambed.

The sounding weights are lowered and raised by a bridge crane or truck-mounted boom on the bridge deck to calculate the streambed depth. The weights used are typically 45 to 136

kilograms. This method could be used during a flood because the heavy weights will be able

to sink to the bottom despite strong water currents. The Red River flooded in May of 1990

and sounding weights were used to measure changes in the streambed. The weights were

able to successfully free-fall and measure the depth, while echo sounders were unsuccessful

because of extreme water turbulence and air entrainment. There are several significant

disadvantages to using this method. During a flood or shortly afterwards, operating a crane

on the bridge deck may be dangerous. During high currents, the weights may be swept

downstream while being lowered causing inaccurate measurements. It is critical for the

weights to drop with vertical precision for accurate measurements to be made. A general rule

for operators of this method is to disregard using weights if the depths are greater than 10 m

and velocities of flow are greater than 3 m/s. Also, debris can snag the line as the weight

descends. If the line breaks, the operators are at a safety risk and the weight may become

lost. This method is only able to capture the depth of scour, not the size of the scour hole.

The disadvantages of this system are significant, so the Mueller et al. explored using more

advanced echo sounders to measure the streambed depths [Mueller et al., 1999].

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reflect off of the streambed and back to the transducer. The researchers used modified water

skis to encase and navigate the transducer around the bridge pier as shown in Figure 2.11.

Figure 2.11: Echo sound transducer measuring streambed depth [Mueller et al., 1999]

The test setup performed well during three major floods because it created a small amount of

drag and was easy to control in turbulent water. An advantage of the echo sounders is that

measurements can be quickly recorded at many different points so the entire scour hole

measurements can be collected. Echo sounders are able to measure the depth to sediment for

depths larger than 3 m deep and water velocities less than 4 m/s. Echo sounders did not

perform well making continuous measurements during an intense flood because the signal

was vulnerable to high levels of turbulence and air entrainment. Also, echo sounders may

record faulty data if there is a large amount of suspended sediment in the water affecting the

recorded signal. The recorded data would also be altered by possible storm debris collected

around the pilings. As mentioned before, sediment can refill scour holes and not be

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would measure to where the sediment has settled and would not be able to provide any data

regarding the compaction of the sediment.

The magnetic sliding collar (MSC) system is an alternative method to examine the depth of a

streambed examined by researchers Nassif et al. [2002] in collaboration with the New Jersey

Department of Transportation. The MSC system is comprised of a steel pipe that is placed

vertically in the streambed and a sliding collar moves with the change in sediment elevation.

Magnets were attached to the collar and the resulting magnetic fields were monitored to

determine the depth of the collar in the sediment. This device may be used during a flood to measure the maximum depth of scour experienced. If sediment falls back into the scour hole,

the collar will be buried. The steel pile should be embedded into the sediment a minimum of

1 meter below the expected scour depth. The researchers implemented MSC devices at

several locations on the Matawan Bridge in New Jersey to monitor change in the sediment

levels over a time span of three and a half years. The bridge is subject to tidal changes and

possible storm surge from the Raritan Bay. No significant storms occurred over the three and

half years of monitoring the bridge; therefore, no change occurred in streambed elevations

indicating scour damage. Some disadvantages acknowledged by the researchers were that

the magnetic arrays used in the MSC had a spacing that limited the measurements to be

recorded to the nearest 6 inches. This is a large interval and on a smaller structure significant

scour levels may be overlooked. The researchers describe the installation of the MSC system

as extensive. While it can be installed from the superstructure, it requires a pneumatic post

driver to embed the steel pipe vertically 1 meter into the streambed. Aggravating scour

critical sediment may have negative consequences. Turbulent water current could make the

steel pipe installation more difficult considering the rod should be installed normal to the

steam bed surface. Also, the results recorded from the MSC could be altered by any floating

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2.3.2 Fiber-Optic Sensors Bridge Monitoring

Zarafshan et al. [2012] developed a method to monitor bridge piers and abutments for scour

by observing vibration characteristics of a sensor rod embedded into the streambed. The

method relies on the interaction between the sensor rod and the streambed material. There is

a relationship between the free length of the rod and the rod’s natural frequency; therefore, as

scour occurs the natural frequency of the rod will change. The fiber-optic Bragg grating

(FBG) dynamic sensor was used to determine the natural frequency of the rod. The FBG

sensor was chosen because it can be safely exposed to water as opposed to electrical sensors. FBG sensors were beneficial in this study because the sensors were small in size, immune to

electrical and electromagnetic noise, and recorded high resolution signals. Figure 2.12 shows

the rod, FBG sensor and fiber-optic cable implanted in the riverbed.

Figure 2.12: Fiber-optic sensor connected to rod implanted in riverbed [Zarafshan et al., 2012]

The researchers used this method to monitor a bridge over Salt Creek River in Illinois. The

bridge abutments and piers face upstream flow at a skewed angle and are at an increased risk

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of the piers and abutments before monitoring began. There were 14 sensors distributed

around the piers and abutments and each rod was embedded to a calibrated length. The

entire monitoring system included the sensors connected to a rod and a fiber-optic cable

routed to an optical interrogation unit that converted the signals of the sensor to vibration

responses, a computer to control the interrogation unit, data acquisition system for the

processing, as well as a cellular wireless modem connected to the field computer to

wirelessly transfer the real-time data to the laboratory. There was a concern for protecting

the rods in the streambed, so steel barrier rods were embedded around the sensor rod in an

effort to protect the sensors from floating debris. Figure 2.13 shows the barrier rods being installed.

Figure 2.13: Barrier rod installation in streambed [Zarafshan et al., 2012]

The scour levels were measured in real-time over a ten day period and it was observed that

the sensors were capable of monitoring scour as well as accumulation of the sediments.

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Figure 2.14: Scour levels recorded from sensor located near a bridge pier [Zarafshan et al.,

2012]

The sensors were able to successfully track the changes in sediment level, but it should be

noted that accumulation of sediment on a scoured bridge pier does not create additional

structural support to the bridge. Scour is dangerous because it alters the pier’s ability to

provide support to the structure, so it is important when monitoring scour to evaluate the

structural support provided by the compaction of sediment around the pilings. While the

barrier rods protected the sensors from major debris, smaller pieces of debris such as leaves

collected around the sensors and altered the recorded signal. The sensor rods had to be

regularly inspected and cleaned of any collecting debris for the recording signal to be

accurate. Regularly clearing debris would add labor to the monitoring process. Installing the

sensor rods underwater to a very specific depth would also be a laborious task. As discussed

earlier, a vortex can form around a water flow obstruction where the sediment is locally

removed. The sensor rod, barrier rods and any debris between the rods could act as a water

flow obstruction and experience local scour unrelated to scour created around the bridge pier.

Also, if a flood had occurred during the monitoring time frame, there would have been likely

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could have dislodged the sensor rod and the barriers. The sensors washing away would be a

costly mishap.

An alternate fiber-optic sensor method was developed by Manozi [2011] that used FBG

sedimeters to evaluate the temperature change along the depth of a bridge pier. The

temperature of sensors in the flowing water should be lower because of thermal resistance

compared to the sensors buried in the river bed. Figure 2.15 is a diagram of the sensors along

an underwater bridge pier.

Figure 2.15: Sensors on a bridge pier and the cross section of a sensor [Manzoni et al., 2011]

Laboratory tests proved that there was a temperature variant between the sensors in flowing

water and the sensors locating in the saturated soil. Plans are being made to apply the

monitoring method in the field. The researchers acknowledge there will be a challenge related to the vulnerability of the system when exposed to flowing water [Manzoni et al.,

2011]. As with the previously mentioned fiber-optic sensor method, it would be a costly

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Methods of evaluating scour above water will avoid most of these issues related to debris

interference or underwater damage to expensive equipment. Also, it is labor intensive to

properly install equipment underwater.

2.3.3 Robot Assisted Bridge Monitoring

Unmanned marine vehicles (UMV) were developed as an option for post-disaster bridge

inspections [Murphy et al., 2011]. The researchers evaluated the performance of a UMV’s

ability to inspect for damage on the Rollover Pass Bridge over the Galveston Bay three months after Hurricane Ike. The UMV should be able to inspect the bridge substructure for

damage and map the debris field by taking photographs. The results were compared to

inspections done previously by a dive team. The UMV used to inspect the bridge is shown in

Figure 2.16.

Figure 2.16: UMV used to inspect Rollover Pass Bridge called a Sea-RAI USV [Murphy et

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The UMV is operated by three people who each take a task to pilot the UMV, gather images

through the attached cameras or to act as a safety officer. Other engineers are involved by

collecting and observing data output. The UMV was successful in identifying debris and did not detect scour damage at the pilings. The UMV results were similar to the dive team’s

field inspection results. There are advantages to using the UMV compared to investigations

completed by a dive team. After a storm, divers inspecting a damaged structure may be at a

high danger risk which could be avoided by using a UMV. Also, human error is avoided as

the UMV is less likely to miss important details. Disadvantages observed by the researchers

include vulnerability of the UMV to extreme environmental conditions such as changes in tide or current. Large debris or changes in topography may act as an obstacle for the UMV

navigating the water. It is necessary for near-by boat ramps to be available and undamaged

for the UMV to be used [Murphy et al., 2011]. Similar to issues discussed for the fiber-optic

sensors, there are disadvantages to underwater investigations because equipment is subject to

damage or loss because of dynamic water leading to a very costly consequence. Also, visual

inspections may not be able to fully capture the damage of a structure. Connection damage

or scour vortices refilled with loose sediment are all dangerous forms of damage that are not

visually observable.

2.3.4 Tiltmeters Monitoring

Briaud et al. [2011] investigated an above water bridge monitoring system using tiltmeters to

measure changes in the angle of the bridge deck due to damage. The researches implemented

this testing method on a Guadalupe River Bridge in Texas that had existing scour due to a

flood of the river in 1998. The monitoring is aimed to identify if the condition was

worsening and the bridge was losing stability. Figure 2.17 shows the instrumentation plan on

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Figure 2.17: Tiltmeter instrumentation plan [Briaud et al., 2011]

Tiltmeters were installed in two directions to measure the angle change along the axis of

water flow and along the axis in the direction of traffic. A consistent reading from the

tiltmeters corresponds to a stable bridge. If the calculated threshold value was exceeded by

the tiltmeters, the bridge was at risk for losing stability and should be closed [Briaud et al.,

2011]. There are several advantages to monitoring scour above water, such as avoiding

equipment damage due to water exposure or harsh environmental conditions. Also,

accessing and installing equipment is less laborious if done from the bridge deck than below

water on the substructure. Tiltmeters are inexpensive, simple and reliable. Damage other

than scour may be identified by observing the tilt of the bridge deck. A concern with this

method is that once damage has been identified, the bridge deck has already displaced and

the structure is at risk for failure. A successful monitoring method should be able to identify

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2.4 Vibration Based Superstructure Monitoring Techniques

Tracking streambed elevation measurements, performing underwater investigations and

measuring tilt of the bridge deck are all scour monitoring methods that have previously been

implemented in the field. Most of the methods were considered successful in measuring the

amount of soil dislodged, but disadvantages exist in the field monitoring process. Ideally, a

field monitoring system should be developed that could determine if the structure is damaged

due to the presence of scour instead of quantitatively measuring the amount of scour. The

goal of monitoring is to make an assessment of the health of the structure. Furthermore, the field monitoring system should be easy to implement by an end-user, especially in the event

of an emergency. Underwater investigation techniques require specialized training that may

make monitoring immediately following an emergency event difficult. Monitoring the

bridge from the superstructure alone benefits the field monitoring operator. Also, it protects

the scour critical sediment surrounding the pilings from additional aggravation. Damage

detection techniques based on the dynamic characteristics resulting from vibrations of the

superstructure of the bridge is a developing scour monitoring system that satisfies the test

setup ideals. Zarafshan et al. [2012] performed an investigation of using fiber-optic sensor

rods embedded into the sediment around scour critical piles which uses the same vibration

response concept, but as previously discussed, it is difficult to implement underwater.

Considering the vibration response of the superstructure alone avoids underwater

interactions. Vibration based damage detection techniques were able to identify damage

successfully in theoretical and in some laboratory models and should be further investigated

by implementing in the field.

Mosavi [2010] investigated using vibration based damage detection techniques to identify the

location of damage in steel girders. He created an idealized two-span steel laboratory model

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locations. Random vibrations were recorded by 15 sensors along the length of the beam.

The collected vibrations were used to evaluate damage diagnosis patterns based on statistical

pattern recognition using time series models. The damage diagnosis patterns were based on

comparison between healthy beams and damaged beams. The Fisher criterion was applied to

the healthy and damaged beam vibrations and theoretically the highest Fisher criterion value

corresponded to the sensor most closely located to the damage in the beam. Mosavi found

that the methods were successful in identifying the general region of damage in the

laboratory tested beams. The change in natural frequency and vertical mode shapes between

the damaged and repaired beams was also investigated. Mosavi also observed that the natural frequencies gathered from the vibration response of the beam generally decreased for

damaged beams. Monitoring natural frequencies could identify the presence of scour;

however, it was observed these results were altered by temperature variations.

Based on Mosavi’s [2010] findings that vibration responses could be used to detect damage

in steel beams, Elsaid [2011] explored implementing vibration based damage detection

techniques to identify and locate scour in bridges. Elsaid created an idealized two-span steel

bridge laboratory model. The support between the two spans was extended to represent

different levels of scour as well as unsymmetrical scour. The model was mounted with

evenly spaced sensors and vibrations were recorded in response to an impact hammer.