# DIAGNOSTIC AND PROOF LOAD TESTS ON BRIDGES

EDITED BY : Fikret Necati Catbas and Eva Lantsoght PUBLISHED IN : Frontiers in Built Environment

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ISSN 1664-8714 ISBN 978-2-88966-212-8 DOI 10.3389/978-2-88966-212-8

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# DIAGNOSTIC AND PROOF LOAD TESTS ON BRIDGES

Topic Editors:

Fikret Necati Catbas, University of Central Florida, United States Eva Lantsoght, Universidad San Francisco de Quito, Ecuador

Citation: Catbas, F. N., Lantsoght, E., eds. (2020). Diagnostic and Proof Load Tests on Bridges. Lausanne: Frontiers Media SA. doi: 10.3389/978-2-88966-212-8

# Table of Contents

Piotr Olaszek and Joan Ramon Casas

*32 Structural Health Monitoring of a Cable-Stayed Bridge Using Regularly Conducted Diagnostic Load Tests*

Hadi T. Al-Khateeb, Harry W. Shenton , Michael J. Chajes and Christos Aloupis

*44 Stop Criteria for Flexure for Proof Load Testing of Reinforced Concrete Structures*

Eva O. L. Lantsoght, Yuguang Yang, Cor van der Veen, Dick A. Hordijk and Ane de Boer

*58 Experimental Determination of the Longitudinal Pier Stiffness of a Long Railway Viaduct*

Marc Wenner, Thomas Meier, Frederik Wedel, Gregor Schacht and Steffen Marx

Vahid Shahsavari, Maryam Mashayekhi, Milad Mehrkash and Erin Santini-Bell

Eva O. L. Lantsoght, Ane de Boer, Cor van der Veen and Dick A. Hordijk

Jacob Wittrup Schmidt, Sebastian Thöns, Medha Kapoor, Christian Overgaard Christensen, Svend Engelund and John D. Sørensen

*169 Non-destructive Testing of a 100-Year-Old Reinforced Concrete Flat Slab Bridge*

Patryk J. Wolert, Marek K. Kolodziejczyk, J. Michael Stallings and Andrzej S. Nowak

*181 Bridge Load Testing for Identifying Live Load Distribution, Load Rating, Serviceability and Dynamic Response*

Chuanzhi Dong, Selcuk Bas, Marwan Debees, Ninel Alver and F. Necati Catbas

*195 Bridge Load Rating Through Proof Load Testing for Shear at Dapped Ends of Prestressed Concrete Girders*

Y. Edward Zhou and Mark R. Guzda

# Editorial: Diagnostic and Proof Load Tests on Bridges

#### Eva O. L. Lantsoght 1,2 \*

1 Politécnico, Universidad San Francisco de Quito, Quito, Ecuador, 2 Concrete Structures, Department of Engineering Structures, Civil Engineering and Geosciences, Delft University of Technology, Delft, Netherlands

Keywords: proof load test, diagnostic load test, Editorial, load distribution, shear, flexural strength

#### **Editorial on the Research Topic**

#### **Diagnostic and Proof Load Tests on Bridges**

The load testing of bridges is a practice as old as bridge engineering. In the past, load testing was used when a new bridge was built and was a means of demonstrating that the structure was safe for the traveling public. Over time, engineers have developed different practices for load testing, many of which follow on from these traditions as they are based on practical experience, a practice that has influenced current codes and guidelines for load testing. These codes and guidelines use limits based on experience, which may differ across countries, and which may not directly be related to the philosophy of the safety of these design codes. Procedures for the field testing of new and existing bridges have been developed, and over time the range of applications of load tests have grown significantly from simply demonstrating that a bridge is safe for use to determining particular aspects of structural behavior, such as the contribution of non-structural elements (barriers, curbs, etc.) to the overall stiffness of the structure, or transverse load distribution.

#### Edited by: Xin Ruan,

Tongji University, China

#### Reviewed by:

David De Leon, Universidad Autónoma del Estado de México, Mexico

#### \*Correspondence:

Eva O. L. Lantsoght<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Bridge Engineering, a section of the journal Frontiers in Built Environment

Received: 23 July 2020 Accepted: 14 September 2020 Published: 15 October 2020

#### Citation:

Lantsoght EOL (2020) Editorial: Diagnostic and Proof Load Tests on Bridges. Front. Built Environ. 6:586704. doi: 10.3389/fbuil.2020.586704

There are two main types of load test, diagnostic load tests and proof load tests. Diagnostic load testing is used to evaluate and update the analytical models for the design and assessment of bridges. For new bridges, diagnostic tests can be used to demonstrate that the bridge behaves as designed. For existing bridges, diagnostic tests can be used to update the model that is employed for some sort of decision-making, for example determining the load rating of the bridge, load permits for special loads. Proof load testing is used to demonstrate that a given bridge can safely carry the loads prescribed by the governing code or a specification. A load corresponding to the load combination prescribed by the governing code or specification is applied to the bridge. If the bridge can carry this load without signs of distress, the test is considered to show that the bridge can fulfill specified load requirements.

This Research Topic includes a number of case studies, examples of the load testing of bridges, and discusses potential ways of expanding knowledge of the subject. One of the ways in which load testing has evolved is in terms of the tools that are used to interpret optimal field test results. A contribution by Commander shows the evolution of diagnostic load testing in the US. This article shows how the lines between field testing, structural health monitoring, and non-destructive testing have been blurred, and how these techniques are becoming more and more intertwined. The author illustrates how a bridge engineer can select the right tools in response to test objectives and discusses emerging technologies. From a European perspective, a study by Olaszek and Casas offers practical advice for static and dynamic load tests. This article examines the factors that can result in errors in interpreting test results compared to target values or values derived from a numerical model. Such errors can lead to errors in bridge assessment, and ultimately, wrong decisions.

Another contribution by Shahsavari et al. considers the synergy between structural health monitoring and load testing using the Memorial Bridge as a case study. This bridge has a structural health monitoring system in place, and the study examines the bridge using numerical models. A load test was carried out to calibrate the finite element models and to define post-processing and decision-making tools related to structural performance. Al-Khateeb et al. explore the combination of structural health monitoring and load testing based on the Indian River Inlet Bridge, which has been subject to six load tests since 2012. The authors focus on how a structural health monitoring system can be valuable for repeat diagnostic load tests, giving insights into bridge performance. The authors indicate how repeated diagnostic load tests form an integral aspect of the bridge operation and maintenance strategy. In another case study, Duvnjak et al. discuss a damaged steel railway bridge in Croatia, which was monitored during strengthening works. In this example load testing was used to update the finite element of the bridge, to evaluate its ability to carry the design loads, and to determine the dynamic parameters of the structure.

In recent years load testing is often combined with finite element modeling. Wolert et al. detail a case study of a 100 year-old reinforced concrete flat slab bridge, of which no plans, reinforcement details, or records from the time of construction are available. The contribution shows how the field test results were used to develop a field-verified finite element model of the structure, after which the structure could be load rated. In another article, Lantsoght, de Boer et al. show the advantages and challenges associated with combining proof load testing results and non-linear finite element results, based on the case study of Viaduct De Beek. When compared to linear finite element modeling, the presented method requires more time and effort but may result in a sharper assessment and avoid unnecessary strengthening actions.

Nowadays, load tests on new bridges are not required before they open. However, for bridges using novel materials or structural systems, it is good practice to conduct a load test to verify its performance upon completion of construction. Alahmari et al. present a case study that involved the diagnostic and proof load testing of a prestressed concrete bridge using high performance concrete girders in span 2 and locally developed ultra-high performance concrete girders in span 1. These field tests allowed for a direct comparison between the high performance concrete girders and ultra-high performance concrete girders. Additionally, the test results provided a baseline of performance, and repeated tests can be used to study durability and possible changes in load distribution over time. Hernandez and Myers report another case study in which diagnostic load testing was conducted on a bridge with self-consolidating concrete (SCC) girders and high-strength self-consolidating concrete girders. The focus of the study is the transverse load distribution, and the results from the field test are compared to distribution factors obtained with a finite element model and AASHTO LRFD Bridge Design Specifications. The authors show that the distribution factors from AASHTO LRFD result in larger values than the field test and that no difference in behavior can be observed between the SCC and conventional concrete members.

Wenner et al. show the results of load testing of the Itz Valley Railway Viaduct. The goal of this case study was to determine the longitudinal pier stiffness, to show whether load testing can also be used to learn more about the properties of the substructure. For this purpose, diagnostic load tests and breaking tests were carried out, and the results of these experiments were compared to numerical predictions. Diagnostic load tests can be used to identify composite action, as demonstrated by the three case studies presented in Yarnold et al.. In many existing bridges the level of composite action may be unknown, and the authors explored how load testing can be used to identify composite action, discussing the advantages and disadvantages of these diagnostic load tests. Dong et al. show a case study of a concrete highway bridge, where a static load test was used to determine the live load distribution factor and the load rating factor, and the characteristics of the model were determined through the use of different truck-load and speed cases. Zhou and Guzda show a case study of proof load testing on a prestressed girder bridge, where uncertainties arose with regard to the shear capacity of the dapped ends of the prestressed girders.

Over time, the importance of measurements during load testing has also increased. While traditional load testing may be limited to a single deflection measurement, one can now find reports from load tests with more elaborate instrumentation, which can address a number of elements of structural behavior. When undertaking proof load testing, the importance of measurements lies is connected to verifying the stop criteria, as shown by Lantsoght, Yang et al.. This research study examines current stop criteria for proof load tests for flexure, and derives new stop criteria for strain and crack width to avoid a flexural failure during a proof load test. The proposed stop criteria were verified by field tests and the results from laboratory experiments.

To align the safety philosophy of design codes with the practice of bridge load testing, concepts of structural reliability are combined with load testing. Schmidt et al. show how concepts of structural reliability can be used to develop an approach to probabilistic decision analysis. This approach encompasses two parts: (1) providing a basis for decision-making during a proof load test to ensure a safe and efficient execution; and (2) identifying efficient strategies for bridge reclassification, accounting for the available information obtained for load testing, monitoring, and modeling.

The papers in this Research Topic present practical insights into the current state of bridge load testing and show how this practice has evolved.

### AUTHOR CONTRIBUTIONS

The author confirms being the sole contributor of this work and has approved it for publication.

### ACKNOWLEDGMENTS

I am grateful for the contributions of my topic co-editor, Prof. Catbas to the success of this collection of articles. I appreciate all contributions of the authors and sincerely value the time and effort of the authors in preparing these articles. I would also like to thank all review editors who contributed to this Research Topic, as well as the associate editors who helped managing the manuscripts. Finally, I would like to thank Prof. Casas for suggesting this Research Topic and his advice and guidance during the development of this collection of articles.

**Conflict of Interest:** The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2020 Lantsoght. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Identification of Composite Action Through Truck Load Testing

#### Matthew Yarnold1 \*, Thomas Golecki 2 and Jeffrey Weidner 3

*1 Zachry Department of Civil Engineering, Texas A&M University, College Station, TX, United States, 2 Pennoni Associates, Intelligent Infrastructure Systems, Philadelphia, PA, United States, 3 Department of Civil Engineering, The University of Texas at El Paso, El Paso, TX, United States*

The continual increase of truck weights on our transportation system is a growing concern among bridge engineers. The load carrying capacity of the structures within the system must withstand this ever-growing demand. For multi-girder steel bridges, the load carrying capacity is heavily influenced by the presence of composite action between the girders and the concrete deck slab. While detailing to ensure reliable composite action is typically included in new designs, for many existing structures, the owner may not fully know the level of composite action. This may be due to administrative issues like insufficient original construction drawings or mechanical issues like breakdown of the shear transfer components. Even in situations where composite action was not intended there exists some partial interaction due to chemical bond and friction. Clearly understanding the presence and reliability of composite action in multi-girder structures is key to managing these structures effectively. This paper explores how load testing has been utilized to identify the level of composite action for existing bridges. The challenges associated with field identification of composite action are presented. In addition, three case studies of truck load testing are discussed. The first case utilized uncontrolled ambient truck measurements of an instrumented structure to field determine the composite behavior. The second and third cases perform a controlled load test with variations in truck weights and positions. Overall, the paper illustrates the advantages and disadvantages of truck load testing for identification of composite action and provides recommendations for future studies.

Keywords: load testing, composite action, bridges, capacity, neutral axis

## INTRODUCTION

Bridge load testing is a valuable method engineers utilize for the evaluation of existing structures. Typically, load testing is implemented when analytical rating methods indicate insufficient vertical load capacity. There are two general forms of bridge load testing. The first is diagnostic testing. Diagnostic testing includes the measurement of load effects in bridge members and compares these results with an analytical model (AASHTO, 2018). The tests allow for model calibration and more accurate structural analysis (typically through load ratings). Proof testing is the second form of load testing. In this case, loads that exceed the desired operational load level are applied to the bridge and observations are made to determine if the bridge carries these loads without damage. Loads are applied in increments and the bridge is monitored to provide an early warning of possible distress or non-linear behavior (AASHTO, 2018).

#### Edited by:

*Eva Lantsoght, Universidad San Francisco de Quito, Ecuador*

#### Reviewed by:

*Michael Chajes, University of Delaware, United States Osman Eser Ozbulut, University of Virginia, United States*

> \*Correspondence: *Matthew Yarnold<EMAIL_ADDRESS>
#### Specialty section:

*This article was submitted to Bridge Engineering, a section of the journal Frontiers in Built Environment*

Received: *01 October 2018* Accepted: *21 November 2018* Published: *07 December 2018*

#### Citation:

*Yarnold M, Golecki T and Weidner J (2018) Identification of Composite Action Through Truck Load Testing. Front. Built Environ. 4:74. doi: 10.3389/fbuil.2018.00074*

Substantial research has been performed on bridge load testing that specifically address composite action. National Cooperative Highway Research Program (NCHRP) funded a study (Report 306) to correlate bridge load capacity estimates with test data (Burdette and Goodpasture, 1988). A section of the project was dedicated to unintended composite action in beam and slab bridges. Eleven comprehensive experimental studies were compiled that included laboratory and field tests to ultimate capacity. The results indicated that the bond between the beam and deck slab was the most important factor in determining whether a bridge built non-composite could be counted on to act composite. Even though this bond was shown to be very effective in transmitting horizontal shear, the reliability was questioned. It also concluded that the degree of composite action is difficult to quantify and should be regarded as a 'bonus'.

NCHRP 12-28(13)A was another large study on nondestructive load testing (Lichtenstein, 1993). The study indicated that without mechanical shear connection, some composite action exists between the beams and deck slab due to friction and chemical bond. Similar to the prior NCHRP study, it found that chemical bond had significantly more of an effect on composite behavior compared to friction. They indicate that, except for a field test, there is no practical way to ascertain if bond exists and that if the "top flange of a girder is partially embedded in the deck slab, the bond resistance is very effective in promoting the composite action." Bakht and Jaeger (1992) found exception to this during their ultimate load test where the top flanges were partially embedded and no mechanical connection to the deck was provided. In their test, the composite action that existed at service loads broke down at loads approaching failure and did not achieve the ultimate strength of the fully composite section. NCHRP 12-28(13)A presents recommended bond strengths for bridges not load tested. In addition, an analytical method is provided for calculating proof load levels from the results of diagnostic testing.

Chajes et al. (1997) performed experimental diagnostic load testing on a steel girder bridge that was designed as noncomposite. Five factors were presented for consideration of unintended composite action in a load rating. This include the current condition, past traffic history, future traffic, structural redundancy and potential for future non-destructive testing. In the bridge they studied, composite action was recommended for the final rating with a higher frequency of inspections to be performed that examine the deck-girder interface.

Jauregui et al. (2000) evaluated two non-composite steel girder bridges through testing to failure. Partial composite action was not only measured through girder strains, but horizontal girderslab differential displacements. Partial composite action was observed with more composite action present in the exterior girders due to the larger curb and railing. Heavier load had no significant impact on the load distribution and partial composite action of the girder. The transverse load position of the test trucks had a larger impact on the composite behavior.

Work by Barker et al. (1999) for the Missouri Department of Transportation aimed to quantify field test behavior for rating steel girder bridges. The study indicates that unintended composite action may not be reliable during the bridge's service life. As a result, an approach is presented for removal of measured composite action for load rating purposes. Other more recent studies have also evaluated unintended composite action through diagnostic load testing such as Breña et al. (2013), James and Yarnold (2017), and Sigurdardottir and Glisic (2013).

The presented study aims to further the state-of-knowledge with regard to field identification of composite action of steel girder bridges using load testing. An emphasis was placed on quantifying the variability of neutral axis locations and the resulting level of composite action between the beams and deck slab. This research was conducted through three case studies that includes three bridges, designed non-composite, composite, and composite only in the positive moment regions, respectively. Conclusions and recommendations are provided from these three case studies along with review of substantial prior research.

### INFLUENCE OF COMPOSITE BEHAVIOR

Truck load testing has repeatedly shown to provide information that can significantly increase the understanding of a structures live load behavior. For a conventional steel girder bridge, there are several areas of uncertainty where a load test can provide refined information. This includes:

The focus of this paper is the composite behavior between the girders and concrete deck slab. For structures where composite action is in question, load testing can provide valuable information. Two general situations are confronted in a live load test of a girder bridge. The first is a bridge where the girders were not mechanically connected to the deck slab. The intention of the designer is to produce non-composite behavior where the girders and slab act independently, as shown in **Figure 1C**. However, in reality there is some form of partial composite action due to the chemical bond and friction between the girders and deck. The partial composite and full composite strain distributions are illustrated in **Figures 1A,B**, respectively. The second situation is a bridge where mechanical connection of the girders to the deck slab was originally provided. Nevertheless, the concrete deck slab may be degraded or there may be fatigue issues of the shear studs. In this case, a fully composite strain distribution may have been assumed, but in reality slip is occurring producing a partially composite situation.

Identifying the level of composite action can substantially influence the assessment of vertical load capacity of a bridge (typically expressed through load ratings), fatigue life estimate or serviceability checks. Most load tests on assumed non-composite bridges have concluded the structure was composite to some degree, which can increase the load rating (e.g., Chajes et al., 1997; Breña et al., 2013; James and Yarnold, 2017). As stated earlier, the reliability of this composite action at ultimate strength is questionable (Bakht and Jaeger, 1992; Barker, 2001). Therefore, bridge owners differ in their willingness to accept full or partial composite action for ultimate strength without quantifiable interface shear strength for bridges with unknown connection details.

To further illustrate the impact of composite action between the steel girders and concrete deck slab, a sensitivity study was conducted by the authors to determine the ultimate (plastic) moment capacity of a section as a function of varying levels of composite action. The horizontal shear transferred between the girders and slab (V') was varied for the girder geometry shown later in each case study, denoted here as CS1, CS2, and CS3. Each case study has different girder dimensions, girder spacing and deck slab thickness. They cover a wide range of configurations. Overall, the purpose of the sensitivity study is to illustrate the relative increase in flexural capacity for different levels of composite action. The specific results for each case study are provided in section Case Studies.

The sensitivity study was performed by setting an interface shear force between non-composite, zero interface shear, and fully composite, when interface shear matches the minimum of the steel or concrete strength. In practice this level of composite behavior is determined by the relative stiffness of the interface. This ratio (V'/V) can be considered the level or percentage of composite action. The ultimate strength is then computed as follows. Because the steel section is considered to be at yield stress throughout the cross section, and the net axial force is assumed to be zero, the interface shear is essentially the net axial force in the deck. A neutral axis location can then be found which balances the tension and compression. Finally, the depth of the compression region is determined by assuming a rectangular stress block at 0.85f'c through a thickness necessary to produce a net compression value equal to the assumed interface shear. This stress distribution is then used to determine the resulting flexural moment, i.e., partially composite capacity (M) of the section.

**Figure 2** illustrates the relative results, where Mfc is the fully composite flexural capacity, V is the fully composite shear force, the minimum of AsFy and 0.85f'c bets where As is the steel cross-sectional area and Fy is the steel yield stress f'c is concrete strength, ts is slab thickness and be is the effective deck width. In Case Study 1, the composite section is governed by the steel section, meaning it has a relatively thick deck. The other two case studies are governed by the slab. Because of this, the

change in strength from non-composite to fully composite is more significant for the Case Study 1 cross section. The flexural capacity is roughly 100% greater for the fully composite vs. the non-composite condition in CS1 and roughly 50% greater for CS2 and CS3. Overall, the non-linear relationship shown in **Figure 2** indicates that even a relatively small amount of shear transfer can provide a significant increase in moment capacity, especially for cross sections with thicker decks.

### CHALLENGES FOR FIELD IDENTIFICATION OF COMPOSITE ACTION

Measurement of composite action through field instrumentation is more challenging than one might expect. The conventional approach is to measure the longitudinal strain response at multiple positions along the height of a girder cross-section. These measurements are then utilized to identify the neutral axis. It can be observed in **Figure 1** that the neutral axis changes with the composite nature of the system. The increase in composite action causes the neutral axis to move up the cross-section, resulting in a more efficient section. Some studies have measured the relative slip between the girders and deck to identify composite action. However, this has achieved only limited success. The main challenges associated with identifying the neutral axis and resulting level of composite action are listed below followed by a brief discussion of each. Recommendations for dealing with these challenges are included at the end of the paper.

### Environmental Conditions

Typically, a load test is conducted over a short period in time. As the duration of measurements increase, the level of uncertainty increases due to varying environmental conditions. These conditions can naturally change the behavior. For example, the stiffness of an asphalt wearing surface varies with temperature change. In addition, moisture and humidity can cause corrosion that further restrains bearings producing additional axial force effects.

### Material Properties

The material properties of concrete and steel can vary from the original design drawings. These properties may have a significant impact on the composite action, both in stiffness and strength. The strength of the concrete is of importance as it affects the plastic neutral axis and total moment capacity of the section. Concrete strength is understood to vary with time resulting in a challenge to predict. The stiffness of the material is also of interest, as it will affect the elastic neutral axis location. In addition, calculation of the transformed section properties using the modular ratio will vary. However, material properties should have minimal impact on the variability of composite action over a short timeframe.

### Geometry

Many aspects of the geometry are a challenge. The uncertainty will vary based on the quality of plans available. For field identifying composite action, the deck and girder dimensions are critical. This partly relates back to environmental conditions and if the dimensions have changed over time. Steel girders can have corrosion-induced section loss with breakdown of the paint system. The deck thickness could be different than the plans due to the initial construction, rehabilitations or wear on the top surface from traffic. In addition, the haunch thickness might not be stated on drawings and typically varies in the field, as well as at changes in girder geometry such as cover plates. This is a critical dimension as it determines the "moment arm" between the girder and the deck, and therefore effects both stiffness and strength of the composite section. Additionally, steel sections embedded into the deck can be considered to have a negative haunch. Care should be taken when using traditional capacity equations with these sections as the geometry may make these inapplicable.

The overall geometry of the bridge system adds further aspects to consider. Curved, skewed or even straight bridges in some cases can produce out-of-plane bending or torsion in the girders that must be considered. Another geometric aspect that complicates field testing is the barriers. This and any other elements cast on the deck (sidewalk, median, etc.) can heavily influence the results.

### Test Setup

Selection of the local strain gauge locations in each girder crosssection is a major decision for the load test. The literature shows a variety of arrangements. Overall, the design of an instrumentation system needs to consider both composite and non-composite behaviors as a possibility. Placement of a gauge near the neutral axis can produce minimal response. In this situation, it is difficult to confirm the gauge functionality and confirm results with a poor signal-to-noise ratio.

The global spatial resolution needed to identify composite action is another difficult question when designing the instrumentation. The number of cross-sections along a given girder and/or number of girders to instrument can significantly vary based on the objectives of the load test, type of structure and the resources of the project.

Load magnitude is also something that should be considered for evaluating composite action. At higher load levels the response can be non-linear (Lichtenstein, 1993), increasing the complexity for data interpretation. However, the AASHTO Manual for Bridge Evaluation does not recommend conducting load tests outside the linear elastic range (AASHTO, 2018). In addition, the load position can have an impact on composite action and should be considered (Jauregui et al., 2000). The effective slab width can vary with different load levels due to the transverse spread of the load.

Other challenges for testing can be sensor noise and sensor orientation errors. The gauge resolution varies based on the manufacturer and model selected. The greater the resolution the more difficult it will be to identify reliable strain profiles. The orientation of the sensor can be an issue in harsh environments. If care is not taken to align the sensors parallel to the longitudinal axis of the girders, then this must be accounted for in the future data interpretation.

## CASE STUDIES

Presented below are three case studies demonstrating different methods for identification of composite action and the resulting variability of the level of composite action observed. Case Study I illustrates a load test that utilized ambient traffic data to evaluate composite action where no mechanical connection was provided between the girders and deck slab. Case Study II presents a controlled proof load test for a structure designed with shear studs. Finally, Case Study III also conducted the evaluation through a controlled load test, but shear studs are only provided for the positive moment region of the two span continuous girders.

## Case Study I

### Background and Motivation

The first case study structure is a three span highway bridge, located in Tennessee, USA. The two lane rural bridge, constructed in 1975, spans a total of 40 m (131 ft) and includes eight steel girders, spaced at approximately 1.0 m (40.3 in), with no skew. **Figure 3** shows a typical section of the structure along with the girder numbers.

The motivation to use this structure as a test bed is primarily due to the uncertain composite action present between the steel girders and concrete deck slab. No mechanical connectors (e.g., shear studs) are shown on the design drawings. However, the top flange of the girders is embedded within the deck slab. The owner preferred to consider the bridge as composite, prior to field testing.

### Approach

The approach to identify the level of composite action was to instrument two girders (#2 and #4) with the configuration shown in **Figure 4**. Then measurements were recorded during ambient traffic (uncontrolled) for 10 days with a trigger threshold of 20 µε in either girder. Note that ambient temperature changes induce variations in strain so the trigger threshold was based off a moving average. In the post-processing phase, a zeroing algorithm was implemented so only the relative strain measurements were used for each truck event.

Vibrating wire (VW) strain gauges (SG) were utilized for this study (Geokon Model 4000), which has a resolution of 1.0 µε. **Figure 5** shows a photo of one instrumented girder. Campbell Scientific data acquisition equipment was used (CR3000) with dynamic vibrating wire analyzers (CDM-VW305). This allowed for a sampling rate of 50 Hz, which was more than sufficient for the relatively slow vehicle speeds. Power was provided through a 90-watt solar panel that charged a 12-volt battery.

### Results

The Case Study I Bridge exhibited composite behavior under ambient loading. This was determined from over 150 recorded truck events (each response >20 µε) over the 10 days of measurements. The largest response was 104 µε in strain gauge #5 (SG5). **Figure 6** shows the time history plot from this data set (unfiltered). This plot illustrates the quality of data recorded. In addition, the paired response from SG1/SG2 and SG5/SG6 indicates minimal out-of-plane bending was induced.

The conventional approach for identification of the neutral axis using ambient truck traffic is to plot the strain gauge profiles during a significant truck event. Then these lines are projected to find the vertical axis intercept. **Figure 7** represents measurements from the average of SG5 and SG6 along with SG7 and SG8 over different time intervals during the largest truck events. The height of the girder is 533 mm (21 in) so the neutral axis is clearly in the deck slab indicating composite behavior despite having no shear studs. This would be the common conclusion drawn for most load tests. However, the results from a single truck event are deceiving and do not illustrate the variability of the field identified neutral axis.

To comprehensively evaluate the composite nature of the structure, the neutral axis was projected for all truck events at both girders. The objective was to quantitatively determine the distribution of neutral axis location and the variability in composite action. **Figure 8** provides the overall results. The left side of the figure shows the strain profile for each truck event for both girders (over 300 strain profiles). The projected neutral axis location (y-axis intercept) is also identified. A wide spread of results can be observed. As a frame of reference the plastic neutral axis of the composite section (PC), elastic neutral axis of the composite section (EC), and the neutral axis of the noncomposite section (NC) are provide in the center of the figure. In addition, the right side of **Figure 8** provides a histogram of the neutral axis locations. The data indicates a mean neutral axis location of 534 mm (21 in) with a standard deviation of 52 mm (2.1 in), thus a coefficient of variation (COV) of 0.10. The magnitude of loading subjected to the bridge was in the elastic range so the comparison of measured neutral axis should be with EC and NC. The results indicate composite behavior under service level truck loading. The variability comes from a number of uncertainties (many discussed earlier in the paper). In this particular case some of the primary uncertain parameters are the concrete material properties and fixity of the bearings (which can induce axial force), and the presence of a large concrete barrier near one of the measured girders. Conclusions and recommendations taking into account these results are provided at the end of the paper.

### Case Study II Background and Motivation

The second case study focuses on a typical highway structure in the eastern United States. The structure is a multi-span, simplysupported steel multi-girder bridge with varying span geometries (i.e., straight, skewed, and straight-skewed combination, as shown in **Figure 9**) and lengths [ranging between 21 and 40 m (70 and 130 feet)]. The adjacent twin spans were built in 1983 and include variable, built-up section properties. The structure was designed composite with 152 mm (6 in) tall, 19 mm (3/4 in) diameter shear studs in groups of two to three at a spacing of 380 to 530 mm (15 to 21 inches).

This bridge was selected for field testing for several reasons. Unlike the other case studies presented herein, this test was not conducted specifically to determine whether the bridge behaved in a composite fashion, nor was the test specifically conducted to load rate the structure. The bridge was selected for an international study on bridge assessment. As the bridge was going to be accessed by numerous teams of researchers from around the globe, access was a critical driver. Additionally, the bridge exhibited many performance problems that are common on many operating structures in the United States (e.g., fatigue cracking, bearing deterioration, deck and joint deterioration), making it an ideal candidate for the international study. For the sake of simplicity, testing was limited to one span (identified on **Figure 9**) of a total of eight available spans.

### Approach

The instrumentation and testing approach utilized for the structure was in line with the overarching goal of the international study which was to conduct a round robin test on single structure using best practices from other countries. The results presented here were to be considered the "ground-truth." The instrumentation was laid out in a grid, with the following general desired outcomes:

**Figure 10** illustrates the instrumentation plan, with sensor configurations at each node that allows for data interpretation at the system, component, and material levels. To that end, each main grid location had two or three longitudinal strain gages to identify demand on the cross section, and level of composite action, as these are good indicators of both system and component level behavior.

The strain sensors were 25.4 mm (1 in) weldable, quarter bridge strain gages from Hitec Products. The sensors were installed per manufacturer specifications on the top of one side of the bottom flange, and 508 mm (20 in) up the height of the web, as shown in **Figure 11**. The budget for the testing did not allow for sensors on both sides of the flange and web, and the time on site prevented installation of sensors on the bottom of the bottom flange. This sparse cross-sectional instrumentation creates uncertainty related to both axial force and out-of-plane bending, but unavoidable in this situation. Due to the unique geometry, each girder has a different overall length with different start and end points for flange transitions on the top and bottom flanges, shown generally in **Figure 12**. This results in seven different cross-section configurations out of a total of 12 instrumented locations. Testing itself consisted of three load stages of three to six dump truck at various load levels, and positions across the deck. The final load level achieved exceeded the proof level load as required by the AASHTO Manual for Bridge Evaluation (AASHTO, 2018), meaning the test served as a proof level load test. Note that after each load stage, the sensor outputs returned to zero, indicating an elastic test.

### Results

Longitudinal strains at each location were plotted vs. position on the height of the cross-section. The strain profile was assumed to be linear, and extrapolated to the neutral axis. This analysis was carried out for each load level and load position on the bridge. **Figure 13** shows the linearity plots, a girder cross-section with the location of the elastic neutral axis (EC), plastic neutral axis (PC), and non-composite elastic neutral axis (NC) plotted for reference, and a histogram for experimental neutral axis location

at all load stages for the sensors along Girder 1 (the longest exterior girder). These sensors produce consistent composite results across load levels and positions, with the experimental mean occurring almost directly at the composite elastic neutral axis.

The responses at three quarter span for Girder 3 are shown in **Figure 14**. At this location, it can be observed that the neutral axis location is shifted toward the elastic, non-composite neutral axis which indicates a partial loss of composite action. Given that all load levels and positions produced neutral axis location results consistently between the elastic composite and non-composite neutral axis locations, it can be concluded that there was a reduction in composite action at this location that was not observed along Girder 1. This can be concluded in spite of the uncertainty stemming from the sparse crosssectional instrumentation. There is additional uncertainty in the distribution of neutral axis location which may stem from material properties, load location and magnitude, the presence of non-structural components, as well as the aforementioned outof-plane behavior and axial components. At the cross-sectional level, much of this could be reduced by adding additional sensors along the height of the girder and on both sides of the flange and web. In practice, the spatial variation of composite action observed here makes a strong case for a dispersed instrumentation grid where it may be infeasible to heavily instrument every cross-section location.

### Case Study III

### Background and Motivation

The third case study bridge consists of a two-span continuous structure with spans of roughly 24.4 m (80 ft). The concrete deck is supported on nine kinked steel girders with a spacing that varies from 2.20 m (7 ft 2.5 in) to 2.05 m (6 ft 8.75 in). The variable girder spacing is the result of a tapering lane from an

FIGURE 9 | Plan view schematic of Case Study II bridge showing varying span geometry, direction of traffic (red arrows) and test span.

onramp right before the bridge. The girders are supported by a fixed bearing at the center pier and by expansion bearings at the ends. The concrete deck was initially 190 mm (7.5 in) thick, rehabilitation drawings indicate the top 50 mm (2 in) has been removed and replaced with a 65 mm (2.5 in) thick concrete overlay. A typical girder elevation is shown in **Figure 15**. Note that the positive moment regions are designed as composite with shear studs while the negative moment regions have no shear studs and are indicated as non-composite.

### Approach

A load test of this structure was carried out with the intent of capturing moment distribution among the girders to compute a more accurate load rating. In order to achieve this, two cross

sections of the bridge were instrumented with Geokon Model 4000 vibrating wire strain gauges (**Figure 16**). Each girder in the cross section was instrumented as shown in **Figure 17**. The placement of three gauges on the cross section was selected to measure primary bending strains while being able to exclude any out-of-plane moment of the girder webs. This instrumentation also allows for an evaluation of composite action of each girder by linearly projecting strain values to find the neutral axis. Results presented herein focus on composite action, rather than moment distribution.

The load test was conducted using three axle dump trucks with their rear axles placed at quarter-span locations in each lane. Multi-truck cases were also considered, by placing all three trucks side by side at quarter span locations, and by placing one truck at the center of each span in the same lane. A total of 31 different vehicle placement locations were included in the load test using empty dump trucks. The trucks were then loaded with salt and all tests were repeated. This provided some indication of response linearity while maintain the vehicle configuration. In addition, the variability of composite action with load level was evaluated.

### Results

Load test results are shown in **Figures 18**, **19** as strain profiles in each of the nine instrumented girders in the positive and negative

moment regions, respectively for load cases which generated at least 10 µε in the bottom flange. From **Figure 18** it is seen that the positive moment region is primarily composite. The neutral axis locations are consistently near the bottom of the top flange with a coefficient of variation (COV) of 0.07. The negative moment region (**Figure 19**) also behaves with essentially composite behavior in most girders but with a wider variation, COV of 0.13. In both **Figures 18**, **19** reference lines are drawn indicating the location of the non-composite neutral axis (NC), elastic neutral axis (EC), and plastic neutral axis (PC). The first interior girders are the closest to non-composite with neutral axis locations in the upper half of the web, but in all other girders, the neutral axis location is near the bottom of the top flange. The lack of shear studs in the negative moment region did not create non-composite behavior in this region. Rather, the reinforced concrete deck stiffness in tension and bond to girders was adequate to exhibit essentially composite behavior. Both regions show an average neutral axis location between the theoretical elastic and plastic neutral axes. Comparing this data between the full and empty trucks (approximately twice the total loading) shows linear behavior, and similar neutral axis trends.

## CONCLUSIONS

The level of composite action between the steel girders and deck slab can have a significant impact on the assessment of vertical load capacity. Truck load testing has been utilized to field identify composite action (or lack thereof) for bridges with capacity concerns. The literature and three case studies performed as part of this research have shown varying degrees of success for reliably identifying the composite nature of girder bridges. Even simple structures, such as Case Study I, show appreciable variability in the results.

Variability in field identified composite action results comes from a wide range of parameters. These include environmental conditions, material properties, geometry and the test setup itself. Reducing uncertainty due to environmental conditions is typically mitigated through relatively short test durations. Material property uncertainties can be addressed with specimen testing (e.g., concrete cylinder tests) or non-destructive evaluation techniques. The desired accuracy and resources of the project will dictate if this should be performed. Uncertainties associated with the geometry and the test setup itself can be dealt with through carefully designed field measurement strategies. General recommendations are provided below as a result of a substantial literature review and the three case studies performed.

### RECOMMENDATIONS

These recommendations are intended to provide a strategy for field identification of composite action using truck load testing. Recommendations are provided for local measurement of the girders, global measurement across the structure, truck loading, and data processing. These recommendations are intended to be comprehensive and minimize uncertainties to a significant extent, while maintaining a realistic instrumentation plan. The authors realize resources, access, etc. vary per project and all components described below may not be addressed (similar to the case studies). However, it is beneficial to understand the capabilities of different test setups for planning and future data interpretation.

### Local Measurement

The girder cross-sections instrumented should address the potential for out-of-plane bending and signal-to-noise levels. Out-of-plane bending is more prevalent in curved and skewed structures; however, it may not be negligible for girders with slender elements. Therefore, it is recommended to place sensors on opposite sides of the flange and web (**Figure 20**). This allows future averaging of the data. Note that if resources are limited the bottom flange can be instrumented at the center of the bottom. The setup utilized for Case Study II is not recommended because it was susceptible to issues with out-of-plane bending.

Measurement signal-to-noise ratios can be an issue if sensors are placed near the neutral axis. The design of an instrumentation system should consider both composite and non-composite behaviors as a possibility, therefore measuring strain in the upper half of the web or on the bottom of the top flange (for interior girders) can inadvertently locate a gauge near the neutral axis

producing very little response. This makes it difficult to confirm the gauge functionality. The minimal response also introduces more error in the projection of the strain profile to identify the neutral axis.

For example, it is recommended for a steel interior girder with a symmetric section to implement strain gauges on both sides of the top surface of the bottom flange along with a pair of gauges on the web at approximately 1/3 the girder depth (d) from the bottom flange. **Figure 20A** illustrates this setup with the sensors shown in red. Ideally, another gauge pair would be placed at 2/3 the web depth if resources allow (**Figure 20A** blue sensors). For the exterior girder, it is recommended to move the web gauges up the height of the web due to the presence of a barrier (**Figure 20B** red sensors). Even minimal composite action will move the neutral axis high on the section so signal-tonoise should be adequate at that location. This should allow for better linear interpolation and identification of the neutral axis, minimizing the effects of sensor noise. Again, a second pair of gauges may be placed on the web if resources allow (**Figure 20B** blue sensors).

Note that if the girders are not symmetric due to different flange sizes, then the web gauges should be adjusted accordingly to avoid potential neutral axis locations.

### Global Measurement

Spatial location of the instrumented girder cross-sections is a critical aspect of the load test. It is recommended to provide locations that have sufficient response (e.g., mid-span of a simple span structure). The literature shows that this is commonly applied with the exception of tests that had access restrictions. The spatial resolution of the testing is also important and widely varies among studies. It is recommended to instrument at least two different girders and to provide measurements at a minimum of two different bridge crosssections for identification of composite action. Following the local measurement recommendation provide above, that would equate to a minimum of 16 strain gauges. This is very realistic to incorporate into a load test.

The girders can be subjected to axial forces from live loading in cases where the bearings are restrained. The eccentricity of the support conditions can induce axial forces from vertical loading. In these cases, it is recommended to consider placement of another strain gauge setup near the end of the girder to minimize flexure. This should allow for measurement of the axial contribution (Barker, 2001). Another option to identify the bearing stiffness is to leave the setup but include thermistors to measure the temperature changes. Then record measurements throughout several days and compare the thermal input with the strain responses (Yarnold and Dubbs, 2015). Mechanical strain measurements will indicate the magnitude of boundary condition restraint.

### Truck Loading

For a controlled truck load testing (diagnostic or proof) it is recommended to vary the truck magnitudes and positions. There is variability in the data and it is best to have statistically sufficient data for future processing. The final truck weight should be well above service load levels. As stated earlier, the reliability of the composite action results are up to the magnitude of test truck. It is recommended to utilize the heaviest truck that can safely be justified for the test.

If controlled truck load testing is not possible, then ambient data can be utilized as illustrated in Case Study I. The results are more limiting in that the magnitude of vehicles crossing the structure are not controlled. In addition, the vehicle weight is not known for each recorded truck event. However, estimates can be back-calculated. Another option worth considering in this situation is to orchestrate a heavy vehicle to make passes across the structure with the bridge operational. This will supplement the ambient data and ensure several truck events with sufficient response.

### Data Processing

Once strain data is acquired, care should be taken in data processing to ensure accuracy in the analysis. Depending on the location of loading and the location of instrumentation,

### REFERENCES

there may be test data with very low magnitude responses, as in the case studies above. Data points of less than a specific threshold strain in the bottom flange are not used because poor signal quality can introduce errors in locating the neutral axis. It is also recommended to choose a consistent axis system between all instrumented locations that is maintained through changes in cross section configuration. Selecting the bottom of web as a reference location avoids the need to adjust the height of gauges relative to different bottom flange thicknesses. This is another benefit to instrumenting on the top of the bottom flange. Lastly, care should be taken in computing cross section parameters such as reference neutral axis locations and section strengths, especially when the cross section configuration is non-standard. For example, when the top flange is embedded in the deck, this is essentially a negative haunch which may invalidate some of the standardized equations.

### AUTHOR CONTRIBUTIONS

All authors have contributed to the contents within this paper. The lead for Case Study I, II, and III was MY, JW, and TG, respectively. The literature review was mostly performed by MY. Statistical analysis and figure development was primarily conducted by TG. All the authors developed the overall challenges, conclusions, and recommendations.

### FUNDING

Case Study I was an internally funded study by the first author. Case Study II was supported by the United State Federal Highway Administration (FHWA). Case Study III was funded by the Maryland Department of Transportation (MDTA). The open access publishing fees for this paper have been covered by the Texas A&M University Open Access to Knowledge Fund (OAKFund), supported by the University Libraries and the Office of the Vice President for Research.

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2018 Yarnold, Golecki and Weidner. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Practical Considerations Regarding Results From Static and Dynamic Load Testing of Bridges

Piotr Olaszek 1 \* and Joan Ramon Casas 2

1 Road and Bridge Research Institute, Warsaw, Poland, 2 Department of Civil and Environmental Engineering, Universitat Politècnica de Catalunya-BarcelonaTech, Barcelona, Spain

Bridge tests are a helpful tool for bridge assessment and evaluation. Both in the case of a static and dynamic load testing, each element of the test: the load selection and application, the creation of a numerical model to follow the progress of the test or to check the validity of the test results, the measurement process itself and the comparative analysis of experimental results and calculations could be a source of errors in the bridge final evaluation if these errors and uncertainties are not properly considered. The article presents some of the most important factors that may bring errors in the interpretation of the test results and their comparison to targeted values or values derived from a numerical model. This, at the end, may result in the adoption of decisions that are not accurate and appropriate. The selected sources of feasible errors are presented with the division into static and dynamic loading tests. The presented examples of bridge load testing show how the use of improper test methods could lead to significant errors in bridge assessment and evaluation and, consequently, to wrong decisions.

#### Edited by:

Eva Lantsoght, Universidad San Francisco de Quito, Ecuador

#### Reviewed by:

Pavel Ryjácek, ˇ Czech Technical University, Czechia Jeffrey Scott Weidner, The University of Texas at El Paso, United States

> \*Correspondence: Piotr Olaszek<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Bridge Engineering, a section of the journal Frontiers in Built Environment

Received: 13 November 2018 Accepted: 24 January 2019 Published: 11 February 2019

#### Citation:

Olaszek P and Casas JR (2019) Practical Considerations Regarding Results From Static and Dynamic Load Testing of Bridges. Front. Built Environ. 5:11. doi: 10.3389/fbuil.2019.00011 Keywords: bridges, diagnostic, proof, static, dynamic, load testing, errors, uncertainty

## INTRODUCTION

The role of the test loading research in the bridge management system is significant in the world. The publication (Casas, 2006; Wi´sniewski et al., 2012) presented the current situation and future trends related to the assessment of the condition and bearing capacity of a structure. The importance of diagnostic test loading was emphasized to be the most accurate tool to assess the structure's bearing capacity. The method of bridge bearing capacity assessment which integrates analytical methods with experimental tests is particularly useful and is verified by test loading research (Wang et al., 2011).

The basic division of test loading is made on the basis of the load variations in time:

There are three types of tests distinguished due to the method and purpose of testing:

Regardless of the type of bridge tests and the purpose of performing these tests, it should be strongly taken into account that the test results are always subject to undesired errors. The impact of these errors on the outcome of the final evaluation of the bridge depends on many factors. An important element of the research is to find the causes of errors and to estimate their influence on the final uncertainty of the bridge evaluation, or to try to avoid them by taking the appropriate solutions during the execution and analysis of the test results.

Analyzing the causes of errors related to various elements of the bridge evaluation process by a loading test, some of them appear during the preparation and execution of the test, meanwhile others are derived in the posterior analysis of the results. We can distinguish the following causes:

The individual errors may be random or systematic. Based on the recognition of error sources, it is possible to estimate the uncertainty of individual elements of the loading test (Guide, 2010).

**Figure 1** presents a block diagram of static test loading process during diagnostic tests of a bridge structure with marked sources of the bridge assessment uncertainty, while **Figure 2** shows analogous scheme in case of dynamic test loading. The diagrams were developed by analogy or on the basis of the diagram presented in the norm (ISO 18649, 2004).

### UNCERTAINTY DURING LOAD TESTING

Moon and Aktan (2006) discuss the state of the art related to the structural identification of constructed civil systems. They pointed out that constructed civil systems cannot be isolated from sources of uncertainty during the structural identification process. Dynamic and static load testing is one of common experimental technologies applied for structural identification. In Goulet and Smith (2013) is presented the fact when system identification methodologies are used to interpret measurement data taken from structures, uncertainty dependencies are in many cases unknown due to model simplifications and omissions.

In this article, attention is paid to some errors of the preliminary measurement data analysis that may bring errors in the interpretation of the test results and their comparison to

targeted values or values derived from a numerical model. Many of those kinds of errors are not dealt with in other publications.

The notion of measurements uncertainty is relatively wellknown and often taken into account. All factors should be taken into consideration while analyzing the uncertainty of tests.

In the case of static tests, load application can last for long time periods and, therefore, the environmental effects with their inherent uncertainty should be considered in the analysis. For dynamic tests, although environmental, and other external effects will almost not affect the results of a particular test, due to the short time of application of the load, other uncertainties regarding the load level, load frequency,. . . must be considered. This is particularly true in the case that the excitation is achieved by means of vehicle passages or by ambient vibration (wind, ambient traffic,. . . .). Of course, it should be noted that for the particular test at a defined point in time, the dynamic characteristics of the bridge have been determined under specific environmental conditions and may be different under different conditions of temperature and humidity. Therefore, appropriate corrections should be carried out when comparing dynamic parameters obtained in particular tests performed in different times of the year.

The execution of a numerical model to design the test and to analyse the results afterwards is also subject to several uncertainties regarding the mechanical properties of the materials as well as the inherent simplifications assumed in the modeling.

While selecting measurement methods for the static load testing it is important to consider not only the measurements uncertainty, but also the possibilities of making an analysis of the structure's displacements in on-line mode. The load is applied in accordance to a loading scheme and held for a certain time period. The duration of the test and the accuracy of the results will depend on the time the load should be held until stabilization of the outputs. The early removal of the load before the permanent or stationary value is reached can lead to important errors.

### UNCERTAINTY OF MEASUREMENTS AND THEIR RESULTS ANALYSES

At the beginning it is necessary to mention one of the basic rules of metrology—completely accurate measurements do not exist in practice their results are affected by errors whose sources are of numerous characters. Taylor (1997) points out that errors in scientific measurements are not mistakes, you cannot eliminate them by being very careful. The best you can hope to do is to ensure that errors are as small as reasonably possible and to have a reliable estimate of how large they are.

A measurement makes sense only when the inaccuracy of its result can be determined. It is possible to assess the uncertainty of individual measurements on the basis of recognized sources of errors, and this is widely known and applied (Guide, 2010). Basic error categories related to measurement equipment include:

process; that error can be decreased by applying adjustment curve instead of straight line;

The authors' own experience leads to the conclusion that the errors directly related to the measurement equipment are not the basic measurement-related reason of possible inappropriate assessment of a bridge. Other reasons might be more significant, for example those related to environmental conditions or, in the case of displacement measurements, to the selected point of reference (considered as of null displacement).

There are various systems of transmitting the displacements of the examined girder to the point of the sensor location which are used in case of the measurement of displacements and application of mechanical sensors located in the area under the tested span. The most popular ones include:

In the first system, errors were observed resulting from not taking into account the change in the force pulling the wire from the stretched spring and the change in the wire length resulting from that. The errors related to not taking into account the change in the wire length height—all resulting from the changes in temperature—can be observed in all the systems.

In case of the measurement of displacements by geodetic methods considerable errors can result from taking only a tripod (of a total station or a leveling instrument) as a reference point, without control readout of prisms or reference level staff.

Environmental errors are connected with the state of surrounding conditions during the tests. In case of static load tests temperature can have a particular impact on the measurement system as well as on the measured levels. In case of dynamic load tests, any errors caused by temperature changes during the tests can be ignored due to basically short time of the performed tests. However, it should be analyzed carefully the comparison of results from dynamic tests carried out at different times during the year. Temperature and humidity may affect the value of the dynamic parameters that are usually taking for damage detection.

In case of static load testing considerable errors might be also related to an error in determining the bridge stabilization time while identifying the permanent and elastic values (it will be discussed in detail on the example of static tests in chapter 4).

Other errors include the use of simplifications such as determining the deflection of girders only on the basis of the measurement of their displacements without any correction taking into account the displacement of the bearing points. This is important when conducting tests with a considerable level of load (proof loading tests) and comparing the deflection values obtained during the measurements with the calculated values.

In case of dynamic load testing the reasons of possible inappropriate bridge structure assessment are more complex. They result from two sources: one related to the incorrect or simplified method of research/measurements and the other related to the incorrect or simplified analysis of the measurements results. In addition, it should be noted that considerable errors might also be caused by difficulties in distinguishing the global and local responses of the bridge structure. This applies to both methods of research/measurements and methods of measurements results analysis.

The authors' experience shows that in case of measuring the accelerations by means of accelerometers the errors related to wrong selection of filters as well as the influence of local elements vibrations might be of dominating character, as discussed in detail on the first example of dynamic tests in chapter 4).

The last 30 years have been the time of intensive development of digital measurement methods and digital signal processing, which especially contributed to the development of dynamic load testing. The application of the digital measurement methods as well as the digital signal processing can have both positive and negative influence on the results of assessing a bridge structure.

The positive influence can be observed mainly in:

	- eliminate the influence of the noise on the registered measurement signals,
	- use digital filtration,
	- make spectral analysis of the measured signals,

Negative influence, i.e., increased measurement error uncertainty, of applying the digital measurement methods and digital signal processing can be observed, for example, in:

FIGURE 3 | The road bridge view—the extreme span at the foreground; from Olaszek (2015) permission was granted by The Committee on Civil Engineering and Hydroengineering of the Polish Academy of Sciences.

## LOAD TEST EXAMPLES

The presented examples concern practical cases where the use of improper test methods could lead to significant errors in bridge evaluation if not properly detected. The first case concerns static load testing in a highway bridge and shows how significant errors in the bridge evaluation may appear when analyzing the bridge deflection stabilization time while identifying the permanent and elastic values. The next two cases concern dynamic load testing of two railway bridges. The second example shows that in case of measuring the accelerations by means of accelerometers the errors related to wrong selection of filters as well as the influence of local elements vibrations might be of dominating character in the comparison to the results of the analytical calculation. The third example shows how significant errors in the bridge evaluation could appear when estimating the quasistatic value of the displacements registered during train rides at speeds close to the maximum ones instead of the speed of approximately 10 km/h.

### Example of Static Load Testing

The tested bridge consists of three simply supported spans with span length of 29.00 + 21.20 + 29.00 m. It had to undergo repair because of its poor technical condition with destroyed wooden deck and limitation of carrying capacity to 3.5 tones. The structure of the bridge after its repair is shown in **Figure 3**. The presented case took place at the extreme spans. Each of the spans consist of three steel double-tie girders to which the bottom flanges and cross bars making a grate are added. During repair a composite-reinforced concrete deck slab was made on the steel span girders. All steel joints were designed as friction joints with high strength friction grip bolts (**Figure 4**).

During the first static test in the original repaired bridge, significant deflection values were observed at the end span right after two trucks entered the bridge. However, since the registered

FIGURE 4 | Bottom view of the extreme span–visible details of the added structure during the renovation; from Olaszek (2015) permission was granted by The Committee on Civil Engineering and Hydroengineering of the Polish Academy of Sciences.

measured deflection values were considerably lower in relation to the calculated ones, two more trucks were introduced. Because of the registered increment deflection values (**Figure 5A**), the test was stopped before these values got stabilized. It was possible to determine only the permanent value of the displacement dpv; which attained a very large value.

The correct diagnosis of the observed bridge behavior and the stop of the load test before an irreversible damage was made in the bridge, was given on the basis of continuous and on-line observation of the deflections– time history. Summing up the results from the measurements and the information provided by the Contractor, it could be stated that the Contractor made compression joints with incomplete carrying capacity. Fortunately, the test was stopped and the spans were unloaded. If the process of loading had been continued, clearances between the bolts of friction joints and the holes in structure elements could have disappeared. On the basis of the above analysis the repair of the joints was made—independent welded joints were introduced between structure elements which until that moment had been connected with frictional joints. More details about the load testing and the analysis of inappropriate behavior of the structure are presented in Olaszek et al. (2014b).

A second load test was conducted after the joints had been repaired. Test results proved that after the repair the structure worked properly. Exemplary deflection time history during test load of an extreme span is presented in **Figure 5B** and it is characterized by a fast stabilization of displacements both after applying a load and after removing it. It was possible to determine the elastic values of the displacement dev and the permanent values of the displacement dpv. In this case, the permanent value of the displacement dpv was very small, close to zero.

In the presented case (the first test loading), we can see an exceptional behavior where significant deflection increments and no tendency of displacements stabilization after the application of the load were observed. On the contrary during the test after repair we can see very fast stabilization of displacements both after applying a load and after removing it. During execution of the static load testing on different type of bridges different speeds of stabilization can be observed. This is a very important factor to take into account in the execution of a static diagnostic load test and the duration of the test and the accuracy of the results will depend on the time the load should be hold until stabilization of the outputs. The early removal of the load before the permanent or stationary value is reached is a common error that can lead to important errors of the test results and adoption of wrong decisions. A more detailed presentation of different speeds of stabilization for different types of concrete and steel bridges is available in Olaszek and Casas (2019).

### Examples of Dynamic Load Testing

The first example of the dynamic load testing is a bridge that consists of two structures each one for a single railway line. Each bridge was designed as a steel free-ends truss with parallel chords (**Figure 6**). Bottom chords consist of two plate girders with composite reinforced concrete ballast pan. The truss structure was welded and riveted. The span length is 93.00 m. Railway track is the characteristic feature of this viaduct, because the track is curved over the whole length of the span with a radius of curvature R = 2,600 m (**Figure 7**). The problem of modeling dynamic analysis of high-speed trains running over curved in-plan bridges was presented in literature (Xia et al., 2008; Dimitrakopoulos and Zeng, 2015). The presented here example is related to the issue of comparing the measured acceleration values with the values determined analytically. The reliability of this comparison can be assumed if the measured acceleration values correspond only to the vibrations of the structure elements

FIGURE 6 | Lateral view of the first presented railway bridge; from Olaszek (2015) permission was granted by The Committee on Civil Engineering and Hydroengineering of the Polish Academy of Sciences.

FIGURE 7 | View of the bridge from the railroad level-visible curved railway track; from Olaszek (2015) permission was granted by The Committee on Civil Engineering and Hydroengineering of the Polish Academy of Sciences.

that are included in the calculations. As a rule, dynamic structure calculations do not take into account elements such as railway tracks, barriers, rails, etc. Even if an acceleration transducer is located very carefully, undesired vibrations of the elements excluded from the calculations can be registered. The main vibration frequencies of these elements are as a rule higher than the fundamental frequencies of girders, and reliable comparison to the calculated values can be possible only after using proper filtration of the registered acceleration time history.

The numerical model of the bridge (**Figure 8**) was a threedimensional frame comprised of elements with 6 degrees of freedom in node (Olaszek et al., 2013). All elements of truss and the cross beams of the deck were modeled as 1-D beam elements. The composite reinforced concrete deck was also modeled as a grid of beam elements. The model consists of 249 nodes and 526 elements. The weight of additional components such as ballast,

sleepers, track and balustrades was estimated and distributed between the elements of deck model.

The mobile load (inertial, sprung) was modeled as concentrated forces moving on the structure. Due to the fact that horizontal forces should always be combined with vertical railway traffic load, the calculations were executed in two steps. In the first case the calculation was executed for a straight track, and in the second case for curved track with given radius. In the second case the components involved in the action of horizontal forces were added to the vector of vertical action.

The bridge model was calibrated to deflection time histories and later on the accelerations were computed with the calibrated model. It was necessary to predict acceleration time histories to check the maximally acceptable value of the acceleration of the bridge at different speeds of a train (EN, 2003, 2005).

The comparative analysis of the displacement time history measured during a train ride at 200 km/h and determined analytically with the numerical model explained above, shows high compliance of the measurement results with the calculation results–about 99%. The example of measured and calculated time histories of vertical displacements for drive of a special train (two locomotives and four passenger railcars placed between them) with the speed of 200 km/h are shown in **Figure 9**.

Significantly, different compliance appears when comparing the acceleration time history registered and determined with the theoretical model at the same point of the tested structure girder during the same train ride. The ratio of the extreme measured positive and negative acceleration amplitudes to the calculated ones was between 131 and 288% in case of using a 20 Hz Bessel filter signal measurement during the test (**Figure 10A**). This important difference resulted from the high frequency vibrations in the measured time history (**Figure 10B**). The most probable reason of the lack of the high frequency content in the calculated acceleration time history is the non-modeling of tracks and barriers. After using a 10 Hz Bessel filter a ratio close to the displacement compliance was obtained—in the range from 103 to 112% (**Figure 10C**). This example is a proof of the

FIGURE 10 | Comparison of the acceleration time history measured during train passage at 200 km/h (the same as in Figure 9) and determined analytically: (A) acceleration measured using 20 Hz Bessel low-pass filter and acceleration calculated without any filters; (B) frequency spectrum from the measured and calculated time history from (A); (C) measured and calculated accelerations after using 10 Hz Bessel low-pass filter.

importance of using proper filters while measuring and analyzing the bridge vibration accelerations and also about the need of accurate theoretical models to obtain the predicted values, or, the importance of knowing perfectly the main limitations of the models due to the adopted hypotheses and simplifications of the reality. A more detailed presentation of the importance of using proper filters while measuring and analyzing the bridge vibration accelerations is presented in Olaszek (2015).

The second example of the dynamic load testing is also a bridge with two parallel structures each for a single railway line. Each structure is a steel arch bridge with reinforced concrete bridge deck. The span length is 75 m and the height of the arch is 15 m (**Figure 11**). The hangers are made from steel bars and welded to the arch and tie of the arch (**Figure 12**). During the acceptance diagnostic load test high values of the dynamic amplification factor were observed, which resulted from the bridge's dynamic susceptibility. The bridge shows a high level of vibration in the hangers both for forced and free vibration cases. An example of the recorded time-histories of the horizontal accelerations of hangers for two passages (10 and 200 km/h) of a special train are shown in **Figure 13**. We can see there how accelerations largely increase with the speed and also different behavior is observed between along and crosswise accelerations depending on the train speed. Similar excessive vibrations of the hangers caused by resonance during train passages are presented in Andersson and Karoumi (2012).

This example presents a possible application of digital signal processing techniques for extrapolation of measurement results during dynamic testing of high-speed railway bridges. Different methods were tested to estimate the quasi-static value of the displacement on the basis of the displacements registered during the train rides at the speeds close to the maximum ones instead of the speed of approximately 10 km/h. The error of using different alternatives was investigated.

The real values of the dynamic amplification factors dav should be calculated as:

$$d\_{av} = \frac{d\_{vma}}{d\_{vsta}}$$

where dvmax is extreme deflection value at speed of vmax and dvsta is extreme deflection value at speed of vsta.

The dynamic tests were conducted using a special train consisting of two locomotives and four passenger railcars placed between them. The train rides were at speeds from vsta = 10 km/h to vmax = 200 km/h, with intermediate speeds of vi= 80, 120, 160, and 180 km/h. The examples of measured time-histories of the vertical displacement at ¼ span length (the point with the maximum deflections) during the train passage with speeds v10 and v200 are presented in **Figure 14A**.

The quasi-static displacement time-history d(vsta,t) was made on the basis of the displacements time-history d(vmax,t) registered during the train ride at the maximum permissible speed vmax = 200 km/h.

In case of road bridges, the method of obtaining quasi static displacements history by means of filtering was presented in Paultre et al. (1992). According to this publication, a low pass digital filter, applied to the recorded data, is used to smooth out the dynamic frequencies in the signal. The filtering can be done with a moving average filter or finite-impulse response filters. The

FIGURE 12 | View of the bridge from the railroad level–visible hangers made from steel bars.

applied filter must have a passband of f pb frequency:

$$f\_{\mathbb{P}^b} = \frac{\nu}{L}$$

where v is the vehicle speed, L is the span length. The stopband with a cut-off frequency f co must be below the bridge's first fundamental frequency f F1:

$$f\_{pb} < f\_{c0} < f\_{F1}$$

In order to analyse the effectiveness of the filtering method in the case of railway bridges, three types of low pass filters, significantly different in frequency characteristics, were tested (Smith, 2003; Lyons, 2011):

The results in case of the Bessel Filter, FIR filter and Moving Average Filter were analyzed using the method of successive approximations (filtering using variable cut-off frequency) in order to get no free vibration in the filtered signal. **Figure 14B** present examples of train passage results obtained after using Bessel, FIR filters and Moving average filter with the cut-off frequencies to get no free vibration in the filtered signal. The extreme level of displacements registered during the train ride at 10 km/h is also shown. The best result (≈0% relative deviation) was obtained by using the FIR filtration and the worst result (−83% relative deviation) was obtained after using the moving average. The dynamic amplification factor determined on the basis of train rides at 10 and 200 km/h was 1.23. After the filtration used to estimate the quasi-static value two filters gave overvalued values of the dynamic amplification factor equal to 1.85 and 7.19 and one estimated value is close to the real value. A more detailed presentation of different methods of extrapolation for dynamic tests in railway bridges is presented in Olaszek and Casas (2019).

### HOW TO MANAGE WITH UNCERTAINTIES AND ERRORS IN BRIDGE LOAD TESTING

As shown in the previous chapters, uncertainty and errors are inherent to the execution and analysis of results from bridge load tests. If this is not taken appropriately, it may derive in wrong decisions regarding the bridge safety (lack of stiffness,. . . .) and/or serviceability (excess of vibration, permanent deflections, dynamic amplification factor,. . . .). The first step to avoid such errors is by knowing them. In this sense, the experience given by a large number executed tests provides a valuable background. The experiences shown in the present paper and others, are of extreme value regarding the adoption of measures in particular tests and finally they may be the basis for the adoption of a Guideline for correct tests execution and analysis. Of course, the final objective would be the derivation of Standards and Codes.

Standardization is an essential element of the tests. Standard (ISO/IEC 17025, 2017), used by research laboratories, specifies the general requirements for the competence, impartiality and consistent operation of laboratories. Research laboratories which want to have their competences confirmed by accreditation issued by an authorized accreditation unit in a given country must apply this norm. Currently, its version of 2005 is in force, and from 2020 its version of 2017 will become effective—which is regulated internationally by ILAC [International Laboratory Accreditation Cooperation (ILAC, 2018)].

Important elements of the Standard (ISO/IEC 17025, 2017) are, among others, related to:

Interlaboratory comparisons are carried out as an important check for assuring the quality of tests and the avoidance of errors. Olaszek et al. (2014a) presented interlaboratory comparisons which enabled to verify the methods of measuring bridge deflections used by laboratories. The examination proved that the system of transmission of displacements of the tested girder to the transducer location point by means of a wire and a weight is appropriate for both static and dynamic load tests, but only in the case of low frequency vibrations. The system does not work in case of higher frequencies of vibrations and strong impulse functions.

The norm was elaborated in order to guarantee the quality of research in all kinds of laboratories. It does not take into account the specifics of bridge load testing. Because of that, a document (Polish Centre for Accreditation, 2017) was developed in Poland which includes specific requirements related to bridge tests, such as:

The document was developed in cooperation with the Accreditation Expert Group for laboratories which carry out tests of engineering structures, especially bridges. The document was reviewed by the Ministry of Infrastructure and Construction, General Directorate for National Roads and Highways and Polish State Railways S.A. Similar initiatives would be of interest in order to eliminate sources of errors both in the acquisition, analysis and comparison of results in bridge load tests carried out by different laboratories worldwide.

### CONCLUSIONS

The paper presents the practical considerations regarding several sources of error in the execution and analysis of results from static and dynamic load testing of bridges. Attention was paid to different reasons of uncertainty of bridge evaluation during load testing. At the case of measurements, it is possible to assess the uncertainty of individual measurements based on recognized sources of error. The main causes of errors related to different measurement methods are presented.

The use of improper test methods could lead to significant errors in bridge evaluation. This is shown in the three examples of load testing described in the paper. The first case from static load testing shows how significant errors in the bridge evaluation may appear when analyzing the bridge deflection stabilization time while identifying the permanent and elastic values. The next examples are from dynamic load testing. The second one shows how in the case of measuring the accelerations by means of accelerometers significant errors in the bridge evaluation may appear due to wrong selection of filters. The third example shows how significant errors in the bridge evaluation could appear during determination dynamic amplification factor by estimating the quasi-static value of the displacements from records obtained at high speeds.

The application of appropriate international standards or national regulations, based on compendium of experiences as the ones shown in the paper, becomes necessary to correctly manage the uncertainties and errors in bridge load testing and to compare results provided by different agents or laboratories. In fact, the same experimental records can derive on very different testing results due to the application of different techniques. These techniques should, therefore, be properly calibrated to avoid any presence of errors.

Not all aspects from load testing are adequate for standardization. But at least, the standardization should primarily include the load levels, the range and the accuracy of measurements and the methods of preliminary data analysis. Because of different types, situations and state of tested bridges, the standardization is difficult to apply and in some cases could not go beyond the application of sound engineering judgement rules based on the background built after many years of experience.

### AUTHOR CONTRIBUTIONS

PO and JC prepared the conception of the paper. PO prepared examples of bridge testing and wrote the first draft of the manuscript. JC wrote sections of the manuscript and edited final revision. Both authors read and approved the submitted version.

### REFERENCES

### ACKNOWLEDGMENTS

Many thanks to all colleagues from the Bridge Structure Research Laboratory at Road and Bridge Research Institute for their active participation in the research work and to Waldemar Szaniec from the Kielce University of Technology for providing the results of calculations of the second railway bridge.

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2019 Olaszek and Casas. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Structural Health Monitoring of a Cable-Stayed Bridge Using Regularly Conducted Diagnostic Load Tests

Hadi T. Al-Khateeb1 , Harry W. Shenton III 2 , Michael J. Chajes 2 \* and Christos Aloupis 2

*1 Jacobs Engineering, New York, NY, United States, 2 Department of Civil and Environmental Engineering, University of Delaware, Newark, DE, United States*

The management and maintenance of cable-stayed bridges represents a major investment of human and financial capital. One possible approach to reducing the cost while simultaneously improving the process is by utilizing structural health monitoring (SHM) systems to enable diagnostic load tests to be regularly and efficiently conducted. The Indian River Inlet Bridge (IRIB), a 533-m long cable stayed bridge, was opened for traffic in 2012. From the very early stages of the design process, the Center for Innovative Bridge Engineering (CIBrE) at the University of Delaware (UD) worked with the Delaware Department of Transportation (DelDOT) and their design-build team of Skanska and AECOM to plan and install a comprehensive structural health monitoring (SHM) system. The SHM system is a fiber-optic based design with more than 120 sensors of varying type distributed throughout the bridge. The system, which not only collects data continuously during normal operation, has also been utilized during regularly scheduled controlled diagnostic load tests being used to monitor ongoing bridge performance. This paper presents results from a unique series of six diagnostic load tests which have been performed over the first 6 years of the bridge's service life (just prior to the bridge's opening, and then again at 6 months, 1, 2, 4, and 6 years). The results of this extended set of diagnostic load tests have enabled the bridge's baseline performance to be rigorously established. This in turn has provided the opportunity to develop a process for conducting future biennial tests to and adding their results to an evolving database, thereby enhancing DelDOT's ability to operate and maintain the bridge.

Keywords: diagnostic, load, test, structural, health, monitoring, cable-stayed, bridge

## INTRODUCTION

In order to ensure the structural integrity of a bridge throughout its life, it is essential that the structural components of the bridge are routinely inspected and evaluated. Inspections results and ensuing evaluations are used to classify the physical and functional condition of the bridge. The data generated from observational inspections are qualitative and rely on the inspector's experience, skill, and primarily focus on components of the bridge that can be readily seen. Other evaluation methods can be used, along with visual techniques, to improve the load rating process such as non-destructive evaluation technologies of bridge load testing. In a bridge load test, instruments such as strain gauges tilt meters, deflection devices, or other instruments are strategically located and attached to the bridge. A load, typically a heavily loaded vehicle, is then placed or driven across the bridge and the bridge response is measured.

#### Edited by:

*Joan Ramon Casas, Universitat Politecnica de Catalunya, Spain*

#### Reviewed by:

*Matthew Yarnold, Texas A&M University, United States Tianyou Tao, Southeast University, China*

> \*Correspondence: *Michael J. Chajes<EMAIL_ADDRESS>
#### Specialty section:

*This article was submitted to Bridge Engineering, a section of the journal Frontiers in Built Environment*

Received: *29 September 2018* Accepted: *11 March 2019* Published: *29 March 2019*

#### Citation:

*Al-Khateeb HT, Shenton HW III, Chajes MJ and Aloupis C (2019) Structural Health Monitoring of a Cable-Stayed Bridge Using Regularly Conducted Diagnostic Load Tests. Front. Built Environ. 5:41. doi: 10.3389/fbuil.2019.00041*

Bridge load tests are often categorized into the categories of (1) proof tests, (2) diagnostic tests, and (3) in-service tests. Proof load tests are used in verifying the load carrying capacity of the bridge. A truck, weighing the load the bridge is intended to be able to carry safely, crosses the bridge. If the load crosses the bridge without damage and within the designated acceptable stress range, it was deemed as proof the bridge can carry the load. Diagnostic load tests are used to quantify a bridges response to heavy loads, and the response is then used to either directly evaluate the bridge or calibrate a numerical model which is in turn used to evaluate the bridge. In an in-service load test, instrumentation is used to measure the response of the bridge due to ambient traffic over a specified amount of time. Statistical analyses are then used to correlate the collected data to the traffic loading. In all of these different types of load tests, the response of the bridge to the load is used to determine an acceptable load rating for the bridge, and that rating is ultimately compared to the rating calculated using conventional methods.

The following publication provide both guidelines for using load tests to evaluate bridges as well as provide numerous applications (Pinjarkar et al., 1990; Fu and Tang, 1992; Moses et al., 1994; Lichtenstein, 1995; Nowak and Saraf, 1996; Chajes et al., 1997, 1999, 2000; Fu et al., 1997; NCHRP, 1998; The Institution of Civil Engineers, 1998; AASHTO, 2003; Chajes and Shenton, 2006; Schiff et al., 2006; Jeffrey et al., 2009; Hosteng and Phares, 2013; Olaszek et al., 2014; Peiris and Harik, 2016; Al-Khateeb et al., 2018). Most recently, Bayraktar et al. (2017), has employed static and dynamic field testing on a cablestayed bridge.

Historically, bridges have undergone "one-off " load tests for specific reasons (i.e., low rating, damage, load carrying capacity validation, numerical model validation, assessment of repair effectiveness, lack of construction drawings, etc.) and have been instrumented with temporary sensors for a specific test. As such, there is little documented history of owners conducting a series of controlled load tests to quantify and monitor bridge health. This paper documents the initiation of a long-term monitoring program involving regularly conducted load tests used in combination with other long-term monitoring, all performed utilizing a comprehensive SHM system.

SHM has been a topic of intense research for some time; an early review of research in this area can be found in Doebling et al. (1996). The literature review was updated through 2001, in Sohn et al. (2003). Carden and Fanning (2004) also provided an updated review on vibration based SHM, picking up where Doebling et al. (1996) left off. More recent updates on SHM research include Das et al. (2016), Mesquita et al. (2016), and Seo et al. (2016). Finally, Li and Ou (2016) provide a detailed review of SHM of cable-stayed bridges which is particularly relevant here. Their paper includes a list of significant cable-stayed bridges that have installed on them SHM systems; many are located in Asia. The paper outlines the many uses for SHM data in the operation and maintenance of a cable-stayed bridge including the use of diagnostic load tests.

SHM systems have primarily been used for long-term inservice monitoring. In this paper, the focus is on demonstrating how SHM systems can make it possible to collect data during regularly performed diagnostic load tests.

Delaware's Indian River Inlet Bridge (IRIB), a cable-stayed bridge located in southern Delaware, has a permanent array of instruments that were installed in the form of a structural health monitoring system. Immediately after the IRIB was opened to traffic, a series of diagnostic load tests were conducted to establish the "healthy condition" or baseline behavior of the bridge. Additional diagnostic load tests or "physicals" have been conducted every 2 years to create an evolving "health record" for the bridge. To date, six load tests have been performed. This paper presents the methodology employed to build a comprehensive health record of the IRIB from biennial diagnostic load tests conducted utilizing the bridge's SHM system.

### DESCRIPTION OF THE CABLE-STAYED BRIDGE AND THE STRUCTURAL HEALTH MONITORING SYSTEM

The following sections provide both details of the IRIB bridge and of the installed SHM system. More extensive descriptions can be found in Shenton et al. (2017a,b).

### Cable-Stayed Bridge Description

The Charles W. Cullen Bridge at the Indian River Inlet, also called the Indian River Inlet Bridge (IRIB), is a 1,749 ft (533 m) long cable-stayed bridge with a 948 ft (289 m) main span and two 397 ft (121) m back spans. The bridge was designed using a combination of precast and cast-in-place reinforced concrete. The bridge is 105 ft (32 m) in width with two lanes of traffic and a shoulder in each direction. A 11 ft 9 ¾ in (3.6 m) wide pedestrian walkway is located on the east side of the bridge. This causes the centerline of the roadway to shift toward the west edge girder. The bridge is fixed at the north pylon but is free to expand at the south pylon and the abutments.

The deck is comprised of two edge girders, transverse floor beams spaced at 11 ft 9 ¾ in (3.6 m) on center, and a cast-inplace deck. The continuous cast-in-place edge girders are roughly rectangular in shape with dimensions of 5 ft 7/8 in (1.8 m deep) and 4 ft 11 in (1.5 m wide). The 8 ½ in (21.6 cm) thick cast-inplace deck has 1 5/8 in (4.13 cm) of latex modified concrete as a wearing surface. The bridge has two twin pylons that reach a height of 248 ft (75.6 m) above the ground. The pylons have a hollow box cross-section that is uniform below the deck level and above deck level tapers to the top of the pylon. There is a total of 152 stays, 38 per pylon. Nineteen stays emanate from each side of the pylons and are anchored to the edge girder on 24 ft (7.3 m) centers. The stay cables consist of seven wire strands in bundles of 19–61. The strands are waxed and encapsulated in high-density polyethylene sheathing. The stays are enclosed in a helical highdensity polythene pipe with a raised helical strake to minimize the potential for wind-rain induced vibrations.

Construction of the bridge started in 2009 with the driving of the piles for the pylons. The bridge was opened to limited traffic in the winter of 2012 and was completed and opened

to full traffic in May of 2012. Additional details of the bridge design and construction can be found in Delaware Department of Transportation (2019) and Nelson (2011).

### Structural Health Monitoring System

The IRIB bridge was built with a fiber-optic SHM system installed throughout the full length of the bridge to monitor a variety of types of structural response. The system includes seven different types of sensors, with a total of 144 individual sensors installed on the bridge (**Figure 1**). The different sensors are designed to measure the structural response of the bridge under various environmental loads and live load conditions. They include:

All of the sensors are optical sensors, with the exception of the anemometers and 10 of the chloride sensors, which are conventional analog devices (Shenton et al., 2017a).

The SHM system operates 24/7. During operation two basic types of data are collected: "monitor" data and "event" data. Monitor data is collected continuously at both low and high frequency. For low frequency data, a single average sensor reading, computed from data taken at 125 Hz over a 10 min period, is recorded. For high frequency data, the data is continuously recorded at 25 Hz. The monitor data is used to quantify the response due to ambient live loads and well as to monitor long-term, gradual variations in bridge behavior. These long-term variations might be due to daily or seasonal thermal variations or slow degradation due to environmental effects or sustained load. In particular, ongoing data from SHM system is being used to evaluate long-term effects including cable forces (using cable vibrations), bearing condition (using bearing displacements), bridge ratings (using strain gauges), bridge deflections (using inclinometers), and thermal response (using multiple types of sensors). These applications have been outlined in Chajes et al. (2018).

### USING A SERIES OF DIAGNOSTIC TESTS TO MONITOR BRIDGE HEALTH

As mentioned, the SHM system is being used to monitor longterm response of the bridge due to ambient traffic and thermal changes/wind effects. However, none of this response data is due to controlled loads. While it would typically be very expensive to instrument and test a long-span bridge using controlled loads, even one time, by leveraging the existence of the permanent SHM system, it has become possible to conduct an ongoing series of controlled and calibrated diagnostic tests on the IRIB. While the predominant stresses long-span bridges come from dead loads, calibrated live load tests can be effectively used to assess change in bridge response and associated change in condition. In order to accurately and effectively evaluate the response of the bridge over time using the diagnostic load tests, a set of standard test procedures and the determination of the baseline response of the bridge that represents the "healthy" condition must first be determined. Doing this involves; (1) establishing a standard testing protocol, (2) establishing the baseline loading and baseline response, and (3) establishing key response parameters for future comparison.

### Establishing Test Protocol

The determination of testing protocols takes place before any testing occurs. It involves, among other lesser details, determining the number of trucks to be used to load the bridge,

their weight, the configurations (or passes) to be used to load the bridge, the number of passes, the timing of the test, and the required traffic control. Also included is whether the load passes will be static (stationary trucks or applied loads), pseudostatic (trucks moving at a slow crawl), or dynamic (trucks moving at full-speed).

### Establishing Baseline Loading and Baseline Response

To establish the baseline loading and baseline response, a series of diagnostic load tests should be conducted a few months apart over the first year of service of the bridge. The first test should be conducted as close to the completion of bridge construction as possible. The remaining tests should be conducted when time dependent effects, such the increase in strength and stiffness of the concrete, concrete creep and shrinkage and associated pre-stressed losses, and any other ongoing changes that will affect bridge response, are believed to have stabilized. For some bridges this might take 6 months to a year after the bridge construction is completed. When comparing the response from these preliminary tests, one can look at both the nature of the time-history response due to the slowly moving truck loading or the magnitude of sensor data. While one should not expect perfect correlation, if the comparison of results from these initial tests are consistent and within an established variability of the data, the baseline test can be selected. The earliest test during which the bridge response is deemed to have stabilized will be selected as the baseline. While initial baseline tests may utilize a wide variety of load passes, based on evaluating the results from each pass, a baseline set of load passes should be determined. This baseline set of load passes should be the minimum number of passes that will yield comprehensive response results, and is called the "baseline loading." The response resulting from the baseline loading is called the "baseline response." The test for which these baseline results come is called the "baseline test."

### Establishing Key Parameters for Future Evaluation

While a large number and wide distribution of sensors may be needed to ensure that a comprehensive record of bridge response is captured, to simplify comparisons of future response to the baseline response, it is useful to identify a smaller number of key sensors for use in initial comparisons. If the comparisons indicate changes in response has occurred, the use of a more extensive set of sensors can then be employed. The key sensors will typically be those located at regions associated with maximum load effects. The key locations can be defined based on analytical results from the design process (such as locations that govern the load rating), as well as from the recorded response data from the initial load tests. At the key locations, both time histories and peak response resulting from various load passes can be used to make the initial evaluation of response compared to the baseline. For the IRIB bridge, the key sensors (see **Figure 2**) will be the strain gauges located on the west and east edge girder at midpsan (S-W7/8 and S-E7/8), at the controlling location (S-W21/22 and S-E21/22), as well as the strain gauge located in pylon 6 west just above the deck level (S-W24S). The controlling location is the longitudinal location along the edge girder that governs the bridge load rating. This happens to be at the quarter point of the backspan, and is within a few meters of strain gauges S-W21/22 and S-E21/22 (see **Figure 2**). The governing computed load rating is 1.17 (Al-Khateeb, 2016).

Other parameters that can be used to evaluate structural response are computed parameters such as the summation of girder strains across the bridge cross-section, load distribution factors, or girder neutral axis location. Which particular response parameters to use will depend on the specific bridge being evaluated.

## DIAGNOSTIC LOAD TESTS CONDUCTED ON THE IRIB

The following sections describe the series of six diagnostic load tests that were conducted over the first 6 years of operation of the IRIB and used to both establish the baseline response and track the condition of the bridge over time.

### Testing Protocol

A final testing protocol for how the load tests should be conducted and what passes should be included was determined

#### TABLE 1 | Baseline loading.

after the initial three load tests were completed and evaluated. The final protocol included the minimum number of passes that should be conducted during each load test in order to assess bridge's condition. During several of the tests, extra passes were conducted to examine specific phenomena, however will not be discussed here as they were for independent focused research studies.

The final test protocol is comprised of 16 slow crawl passes. The first 12 passes involve single trucks traveling in one of the four travel lanes or one of the two shoulders. Next, two four truck passes involve trucks in a side-by-side formation traveling in the four travel lanes. Finally, two six truck passes involve trucks in a side-by-side formation across all six lanes (travel and shoulders). The pass number, pass identifier, truck formations, and direction of travel are given in **Table 1** and pass configurations are shown in **Figure 3**. During the load tests, live loads are applied using up to six test trucks with a maximum combined weight of roughly 380 kips (1,690 kN). To minimize thermal effects during the testing period, all tests have been conducted at night, generally starting no earlier than 10 pm. This also minimizes traffic disruption. A complete load test report is submitted to DelDOT following each test.

### Load Tests Conducted

Six diagnostic load tests have been conducted on the IRIB bridge since it was built. The initial test coincided with the opening of the bridge to full traffic. The next two tests were performed after 6 months of service and after 1 year of service (these three were used to establish the baseline). Following the initial three tests, ongoing tests have been conducted to provide response data at 2-year intervals. Thus, far, the 2, 4, and 6-years tests have been completed. DelDOT's plan is to continue conducting these biennial diagnostic tests as they will become increasingly valuable as the bridge ages. One important question that should be asked is whether the SHM system is robust enough to last years into the future when changes in bridge condition is much more likely to be seen. This is a very valid concern. To address this concern fiber optic sensors were selected as they are known for their excellent durability. Furthermore, the strain sensors are

embedded in the concrete and this should increase the chances of their survival. Redundancy of sensor locations has been built into the system, and DelDOT is allocating ongoing funds to actively replaced sensors that have stopped working or don't have reliable measurements. There is also a plan to duplicate the key sensors by installing additional surface mounted sensors. However, until such long-term demonstration projects play out, we cannot know for sure that the systems will remain useable, and only by doing this can we learn how to design and implement SHM systems that will have long service lives.

### Baseline Diagnostic Load Tests

As described, the first three load tests were all performed within the first year of service of the bridge and were used to establish the baseline response. Details of these three tests are summarized next.

### **Load test 1—April 30, 2012**

In the first load test, conducted right before the bridge was fully opened to traffic, four trucks were used. The average truck weight was 63.5 kips (282 kN). A total of 17 passes were made in this first load test, 15 slow crawl passes and two dynamic passes. The first four passes were single truck passes and were all conducted using the same truck in each of the four travel lanes. Next, six passes were made with two trucks in specified formations. Finally, five passes were made in which all four trucks were placed in different formations. The dynamic, or high-speed, tests were conducted with all four trucks traveling at ∼55 mph (88.5 km/h) with approximately a 100 ft. (30.5 m) interval between each truck.

### **Load test 2—November 28, 2012**

After analyzing the results of the first load test, and reviewing the test procedures, a decision was made to add two more trucks in load test 2. By doing this all four travel lanes and both shoulders could be loaded simultaneously, thereby creating the maximum possible loading across the width of the bridge. The average truck weight for this test was 62.4 kips (282 kN).

A total of 25 passes were made in the second load test, 23 slow crawl passes and two dynamic passes. The first six passes were single truck passes in each of the four lanes and two shoulders. Next, eight two-truck passes were made in different formations and alignments. This was followed by two, three-truck passes, and then five four-truck passes. Finally, six trucks were used to make two passes in a side-by-side formation. The dynamic, or high-speed, tests were conducted with all four trucks traveling at ∼55 mph (88.5 km/h) with approximately a 100 ft. (30.5 m) interval between each truck.

### **Load test 3—May 9, 2013**

In the third load test, conducted 1 year after the bridge was fully opened to traffic, six trucks were used, with an average truck weight of 60.2 kips (268 kN). During this test, nine distinct pass configurations were used, and each pass configuration was repeated (repeatability of data is an important step in data validation). A total of 18 passes were made in the third load test, 16 slow crawl passes and two dynamic passes. The first 12 passes were single truck passes in each of the four lanes and two shoulders. Next, two four truck passes were made with the trucks in a side-by-side formation and two six-truck passes were made with the trucks in a side-by-side formation. Finally, the dynamic, or high-speed tests, were conducted with a single truck traveling at approximately 55 mph (88.5 km/h) in southbound slow lane.

### Diagnostic Load Tests Used to Monitor the Bridge's Health

As described earlier, the next three load tests were performed at 2-year intervals. Details of these three tests are summarized next.

### **Load test 4—May 7, 2014**

The fourth load test, conducted 2 years after the bridge was fully opened to traffic, was conducted following the standard test protocol with an average truck weight of 63.4 kips (282 kN). This test included additional passes with specific research objectives. In addition to the standard 16 slow crawl passes described in the protocol, there were also two dynamic, or highspeed, tests conducted with a single truck traveling at ∼55 mph (88.5 km/h) in southbound slow lane. In addition, a couple of passes were conducted multiple times (six times) to assist in the quantification of measurement variability. Finally, at one point during the testing, the bridge was closed to traffic for 5 min and ambient measurements were taken to further assist in quantifying low-level sensor "noise."

#### **Load test 5—May 18, 2016**

The fourth load test, conducted 4 years after the bridge was fully opened to traffic, was conducted following the standard test protocol with an average truck weight of 63.1 kips (281 kN). This test included additional passes with specific research objectives. In addition to the standard 16 slow crawl passes described in the protocol, this test included 10 additional passes. A total of 26 passes were conducted, 20 slow crawl passes and 6 dynamic passes. The first 18 passes were identical to the 16 included in protocol. To better assess the effect of the high-speed passes, dynamic passes were made of a single truck in the southbound shoulder, in the southbound fastlane, in the northbound fast-lane, and in the northbound slow lane. Theses dynamic, or high-speed tests, were conducted with trucks traveling at approximately 55 mph (88.5 km/h). Finally, to simulate long trucks and their effect, additional passes were made using a two-truck train in the southbound slowlane (twice), a three-truck train in the southbound slow-lane, and a four-truck train in the southbound slow-lane (all of these passes were conducted with the truck trains moving at a crawl speed).

### **Load test 6—June 6, 2018**

Finally, the sixth load test, conducted 6 years after the bridge was fully opened to traffic, was identical to third load test (the standard 16 slow crawl passes described in the protocol plus two dynamic passes) with an average truck weight of 62.1 kips (276 kN).

### RESULTS

The following sections contain (1) a review the baseline response and associated response parameters that were established based on the first three load tests, (2) an evaluation as to how the response during the ensuing three load tests (years 2, 4, and 6) compares to the baseline response, and (3) a qualitative assessment as to how the response of the bridge has varied over time. Ongoing work is being conducted to determine at what level do individual changes in response, or a changing trend in response represent changes in bridge behavior. This work is aimed at establishing how severe a change in condition must be before the response parameters are "significantly" affected. Having data from this series of six tests has been very useful for the ongoing sensitivity evaluation.

### Baseline Response

The baseline response was found from the three tests conducted within the first year of service of the bridge. From the second test (6 months) on, it was found that the bridge response stabilized. As such, the second load test was deemed to be the baseline test, and results from that test have been defined as the baseline results. The following will serve as a summary of those results.

### Post-processing and Interpreting Data

Before looking at individual load test results, it is important to note that the same procedure was used to post-process test results from each test. For each sensor, the time-history record was first "zeroed" by taking the average of the first 25 data points and subtracting that value from the entire time history. In this way any initial offset in the record was eliminated. Next a moving average was computed using a window of 1.6 s (25 data points for data recorded at 15.6 Hz). This smoothing was performed to eliminate the inherent low-level noise in the sensor data. Finally, the maximum and minimum (i.e., peak) values of the record were determined.

When interpreting the results, it is important to note that strains, and associated stresses, with a positive value indicates

TABLE 2 | Baseline response peak strain.

tension. That means that maximum positive strains indicate the largest live-load tensile strain recorded and maximum negative strains indicate the largest live-load compression strain recorded. One should further note that having a live-load tensile strain/stress during the test does not necessarily mean that the element is in a state of net tension, as there can be a large initial compression component due to pre-stressing or posttensioning that keeps the element in net compression. Where live load stress is reported, it is obtained by multiplying strain by Young's modulus of 29,000 ksi (200 GPa) for steel and 5,164 ksi (35.6 GPa) for concrete. For the concrete, the Young's modulus is based on an average compressive strength of 8,240 psi (56.8 MPa) determined from the tests of cylinders made during the concrete pours.

### Baseline Peak Values

**Table 2** shows the baseline peak strains for the key sensors for single, four, and six truck passes. For girder sensors, odd numbers indicate top sensors, where we will focus on peak negative values and even numbers indicate bottom sensors where we will focus on peak positive values. In the table, the peak positive values for the top sensors, and peak negative values for the bottom sensors are not shown as they are not significant compared to the other peaks. Gauge S-W24S is a pylon sensor and both positive (tension) and negative (compression) peaks are of similar magnitude and are both shown. The pass identifier for each peak value is given in parentheses.