This PDF file contains the front matter associated with SPIE Proceedings Volume 7983, including the Title Page, Copyright information, Table of Contents, Introduction, and the Conference Committee listing.

This paper will include discussions on fundamental principles and market forces associated with the upcoming revolution in ultrasonic guided waves. A literature survey is also outlined covering some selected major developments this past decade. A few applications in pipe, rail, bonding and composites, imaging and tomography, ultrasonic vibration, de-icing, structural health monitoring, gas entrapment, and non-linear methods are treated to provide an idea of where we are heading with ultrasonic guided waves.

The development of techniques capable of evaluating deterioration of reinforced concrete (RC) structures is instrumental to the advancement of techniques for the structural health monitoring (SHM) and service life estimate for constructed facilities. One of the main causes leading to degradation of RC is the corrosion of the steel reinforcement. This process can be modeled phenomenologically, while laboratory tests aimed at studying durability responses are typically accelerated in order to provide useful results within a realistic period of time. To assess the condition of damage in RC, a number of nondestructive methods have been recently studied. Acoustic emission (AE) is emerging as a nondestructive tool to detect the onset and progression of deterioration mechanisms. In this paper, the development of accelerated corrosion and continuous AE monitoring test set-up for RC specimens are presented. Relevant information are provided with regard to the characteristics of the corrosion circuit, continuous measurement and acquisition of corrosion potential, selection of AE sensors and AE parameter setting. The effectiveness of the setup in detecting and characterizing the initiation and progression of the corrosion phenomenon is discussed on the basis of preliminary results from small-scale, pre-cracked RC specimens, which are representative of areas near the clear cover in typical RC bridge members.

Aluminum alloy 7075-T6 is a commonly used material in aircraft industry. A crack usually initiates at the edge of a fastener hole, and it can affect the maintenance schedule and reduce the life of an aircraft structure significantly. The fatigue property of the material has been researched widely to develop methods and models for predicting fatigue crack growth under random loading. From the point of damage tolerance design, the inspection technique of a crack for an aircraft structure is very important because it can be used to determine the inspection period of the aircraft structure. The acoustic emission (AE) technique is a nondestructive testing (NDT) method that is able to monitor damage initiation and progression in real time. Understanding the early stage of AE signature due to the damage progression using small scale laboratory samples requires non-traditional data analysis approaches. In this study, 1mm thick Al-7075-T6 plates were tested under monotonic and fatigue loading. The initiation of damage progression using AE data was identified based on improved linear location algorithm and the result was verified using elasto-plastic finite element model. The improved location algorithm integrates dispersive characteristics of flexural waves and threshold independent approach to pick up the wave arrival time. In this paper, AE results in comparison with FE model under monotonic and fatigue loading will be presented. The comparison of traditional and improved location approaches will be shown. The approach for implementing the laboratory scale results in the large scale field testing will be discussed.

A system is being developed to monitor in-service deterioration of reinforced concrete (RC) in highway bridges. The system includes the monitoring of acoustic emission (AE). To develop a preliminary understanding of AE source mechanisms and their causes while also getting closer to the challenges of separating relevant AE from noise, a 6ft long RC test article was monitored in the outdoors environment of a New Jersey summer. There were indications of daily swings in the AE rate, coinciding with the daily swings in temperature. However this correlation was not consistent or reproducible. As the monitoring was extended into the winter and the test site was buried in snow, the AE rate dropped drastically. It was concluded that temperature changes were instrumental in stimulating AE from this damaged concrete. Implications for the formulation of AE evaluation criteria are discussed. Also, the summer swings provoked consideration of the underlying stress field, the fractal nature of the heterogeneous material and the stochastic AE phenomenon. An analysis of calm time distributions yielded results similar to those found by Abe and Suzuki for earthquake time distributions. Analysis of this kind may help to differentiate relevant AE from some kinds of noise.

Internal-frost damage is one of the major problems affecting the durability of concrete in cold regions. This paper presents micromechanics models and innovative sensor technologies to study the fundamental mechanisms of frost damage in concrete. The crystallization pressure due to ice nucleation with capillary pores is the primary cause of internal-frost damage of concrete. The crystallization pressure of a cylinder pore was formulated using interface energy balance with thermodynamics equations. The obtained crystallization pressure on the pore wall was input for the fracture simulation with the developed Extended Finite Element Model (XFEM). The XFEM fracture simulation on a homogeneous beam sample with a vertical cylinder pore leads to a straight line. The XFEM simulation was also conducted on the generated digital sample. The simulation results were favorable compared with the middle-notched single edge beam bending specimen due to the open-mode fracture behavior in both cases. An innovative Time-Domain Reflectometry (TDR) sensor was developed to nondestructively monitor the freezing process. The experimental data shows that the TDR sensor signals can detect the freezing degree, an important input parameter to micromechanics models. These studies indicate that the developed micromechanics models and TDR sensor techniques can be used by the practitioners to evaluate internal-frost damage of concrete. Future work will incorporate the TDR sensor measurements into micromechanics models to real-time predict the internal-frost damage process in concrete specimens. The predicted freeze-thaw damage process will be verified with acoustic emission detection.

Robotic drilling is the basic process for the non-destructive rehabilitation (NDR) system in the Automated Non-destructive Evaluation and Rehabilitation System (ANDERS) for bridge decks. In this paper, we present a study and testing of a concrete drilling process that is used for robotic drilling process for bridge decks repair. We first review the ANDERS and NDR design. Then we present the experimental setup for the drilling process study. A set of testing experiments are performed considering drilling process parameters such as drill bit size, drill rotating speed, drill thrust force and types of concrete composites. Based on the experiments and analysis, we identify and find that the optimal set of drilling process parameters for the ANDERS application is 1/4-inch bit size, drill rotational speed of 1500 rpm and thrust force around 35 lbs. We also demonstrate that the monitoring of drill feeding displacement and thrust force cannot be used to detect and identify the cracks in bridge decks.

Results related to the development of an inorganic matrix that is suitable for filling narrow cracks and thin delaminations on bridge decks are presented in this paper. Almost all the repair materials currently available for these types of repairs are organic polymer based matrices. These matrices create a discontinuity in the modulus of elasticity and water permeability. These discontinuities result in the failure of repairs within about five years. The matrix used in the current investigation has a modulus of elasticity and permeability characteristics that are similar to the concrete used in the bridge decks. The primary properties investigated were: bonding to cracked surfaces, flow characteristics, ease of application, and mechanical characteristics. This paper discusses these properties, matrix performance and matrix viability for use in automated nondestructive robotic delivery system to fill delaminations and narrow/hairline crack in bridge decks.

The nondestructive evaluation (NDE) of bridge decks often requires a combination of different methods for deterioration identification and characterization. Each individual NDE method also needs the responses of an array of spatially distributed sensors to better detect damages. Proper interpretation techniques are needed to effectively integrate data from different NDE technologies and sensor arrays of a single NDE method. A hybrid multisensor data fusion framework is presented in the paper for the NDE of bridge decks. The multisensor data fusion approach process, integrate and interpret the data from multisensor data of a single NDE method and a combination of various NDE technologies in a way that improves the accuracy and reliability of deterioration identification and characterization.

Durability is generally described as the ability of a material to maintain its physical and mechanical properties over time. In reinforced concrete (RC) structures, concrete is the ideal material to protect the steel reinforcement given its high alkalinity. In environments subjected to highly aggressive conditions, mostly due to the presence of chlorides, concrete may lose its protective characteristics and allow for accelerated ageing. Concrete degradation and steel reinforcement corrosion are phenomena closely connected. The aim of this research work is the characterization of the relationship between steel reinforcement corrosion and concrete degradation under accelerated ageing in a 3% sodium chloride solution. The method of linear polarization is used for identification of the corrosion rate of the steel bar. Additionally, the values of concrete residual strength are obtained, and correlated to both the corrosion rate and width of concrete cracks. Finally, the prediction of the concrete cover useful life is estimated.

From automobile industry to aerospace, thermoformed composites are more and more in use. Thermoplastics offer a number of attractive applications in commercial use like short production times, tailored solutions, recyclability and lower cost. The thermoforming process allows for producing carbon fiber-reinforced parts in a wide range of different geometric shapes. On the other hand this benefit requires a demanding nondestructive testing procedure especially for security relevant parts. A contactless method which is able to fulfil this requirement is the extension of the ultrasound technique with laser technology. It opens up new opportunities for quality assessment during manufacturing like inspection of complex surfaces including small radii, remote observation and nondestructive testing of hot items directly after the thermal forming process. We describe the successful application of laser-based ultrasound on small complex thermoformed composite parts (Cetex® PPS). Cetex consists of semicrystalline polyphenylene sulfide thermoplastics providing outstanding toughness and excellent chemical and solvent resistance. It is qualified in aircraft industry for multiple structural applications. For instance, Cetex is used in the Airbus A380 engine air intakes and the wing fixed leading edge (J-Nose). We investigated several test samples with intentionally introduced defects. The smallest flaw size detected was 2 mm in diameter for delaminations and 6 mm in diameter for porosity.

To improve the inspection result repetition and reliability of manual ultrasonic method in NDT field, a portable ultrasonic apparatus based on the phased array inspection technology is developed in paper. The apparatus is small, integrated and portable, which can perform the shear wave and longitudinal wave detection, automatically transmit and receive sound wave, accomplish data acquisition in real time, provide many imaging modes, and give comments of the damage. As designed, the apparatus can implement different algorithm of the ultrasonic phased array inspection technology. With proposed inspection scheme, a phased array reference block was practically detected in the lab. Experiment results indicate the portable ultrasonic apparatus can factually imaging the flaws position, and the size and shape of flaws are nearly consistent with the practical condition. Compared to the conventional ultrasonic testing system, the current apparatus works more efficiently and reliably in the flaw detection and evaluation.

Environment conditions such as temperature, humidity, traffic loadings and wind loadings cause changes in the identified dynamic properties of bridges, which will affect health diagnosis based on the mode frequencies in bridge structural health monitoring. This paper analyzed temperature effects on a rigid continuous bridge based on monitoring data from Aug. 2006 to Dec. 2006. First, temperature data calculating process from measured data is given and frequency time histories are graphed. Temperature effects on the bridge dynamic properties are divided into yearly temperature change and sunlight radiation. Then, theoretical eigenfrequency functions of a simply-supported uniform beam with and without axial force are provided to explain and distinguish temperature effects and constraints on characteristic frequencies. Relationship of measured temperature and frequencies data are drafted and linear correlations are found on the 1st and 3rd vertical frequencies. 2nd vertical frequency fluctuated cyclically in one day, caused by sunlight radiation and restrains.

Structural health monitoring (SHM) systems can provide valuable information for the evaluation of bridge performance. As the development and implementation of SHM technology in recent years, the data mining and use has received increasingly attention and interests in civil engineering. Based on the principle of probabilistic and statistics, a reliability approach provides a rational basis for analysis of the randomness in loads and their effects on structures. A novel approach combined SHM systems with reliability method to evaluate the reliability of a cable-stayed bridge instrumented with SHM systems was presented in this paper. In this study, the reliability of the steel girder of the cable-stayed bridge was denoted by failure probability directly instead of reliability index as commonly used. Under the assumption that the probability distributions of the resistance are independent to the responses of structures, a formulation of failure probability was deduced. Then, as a main factor in the formulation, the probability density function (PDF) of the strain at sensor locations based on the monitoring data was evaluated and verified. That Donghai Bridge was taken as an example for the application of the proposed approach followed. In the case study, 4 years' monitoring data since the operation of the SHM systems was processed, and the reliability assessment results were discussed. Finally, the sensitivity and accuracy of the novel approach compared with FORM was discussed.

Bridges are critical to the operation and functionality of the whole road networks. It is therefore essential that specific data is collected regarding bridge asset condition and performance, as this allows proactive management of the assets and associated risks and more accurate short and long term financial planning. This paper proposes and discusses a strategy for collection of data on bridge condition and performance. Recognizing that risk management is the primary driver of asset management, the proposed strategy prioritizes bridges for levels of data collection including core, intermediate and advanced. Individual bridges are seen as parts of wider networks and bridge risk and criticality assessment emphasizes bridge failure or underperformance risk in the network context. The paper demonstrates how more reliable and detailed data can assist in managing network and bridge risks and provides a rationale for application of higher data collection levels for bridges characterized by higher risk and criticality. As the bridge risk and/or criticality increases planned and proactive integration of structural health monitoring (SHM) data into asset management is outlined. An example of bridge prioritization for data collection using several bridges taken from a national highway network is provided using an existing risk and criticality scoring methodology. The paper concludes with a discussion on the role of SHM in data collection for bridge asset management and where SHM can make the largest impacts.

High-Speed Machining (HSM) spindles equipped with Active Magnetic Bearings (AMBs) have been envisioned to be capable of automated self-identification and self-optimization in efforts to accurately calculate parameters for stable high-speed machining operation. With this in mind, this work presents rotor model development accompanied by automated model-updating methodology followed by updated model validation. The model updating methodology is developed to address the dynamic inaccuracies of the nominal open-loop plant model when compared with experimental open-loop transfer function data obtained by the built in AMB sensors. The nominal open-loop model is altered by utilizing an unconstrained optimization algorithm to adjust only parameters that are a result of engineering assumptions and simplifications, in this case Young's modulus of selected finite elements. Minimizing the error of both resonance and anti-resonance frequencies simultaneously (between model and experimental data) takes into account rotor natural frequencies and mode shape information. To verify the predictive ability of the updated rotor model, its performance is assessed at the tool location which is independent of the experimental transfer function data used in model updating procedures. Verification of the updated model is carried out with complementary temporal and spatial response comparisons substantiating that the updating methodology is effective for derivation of open-loop models for predictive use.

The majority of damage in SiC/SiC ceramic matrix composites subjected to monotonic tensile loads is in the form of distributed matrix cracks. These cracks initiate near stress concentrations, such as 90° fiber tows or large matrix pores and continue to accumulate with additional stress until matrix crack saturation is achieved. Such damage is difficult to detect with conventional nondestructive evaluation techniques (immersion ultrasonics, x-ray, etc.). Monitoring a specimen's electrical resistance change provides an indirect approach for monitoring matrix crack density. Sylramic-iBN fiber- reinforced SiC composites with a melt infiltrated (MI) matrix were tensile tested at room temperature. Results showed an increase in resistance of more than 500% prior to fracture, which can be detected either in situ or post-damage. A relationship between resistance change and matrix crack density was also determined.

With increasing application of composite materials, real time monitoring of composite structures becomes vital for maintenance purpose as well as prevention of catastrophic failure. It has been reported that carbon nanotubes (CNTs) have excellent piezoresistive properties, which may enable a new generation of sensors in nano or micro scales. We report here a novel prototype of carbon nanotube yarn sensors with excellent repeatability and stability for in-situ structural health monitoring. The CNT yarn is spun directly from CNT arrays, and its electrical resistance increases linearly with tensile strain, which makes it an ideal strain sensor. Importantly, it shows repeatable piezoresistive behavior under repetitive straining and unloading. Yarn sensors show stable resistances at temperatures ranging from -196° to 110°. Neat yarn sensors are also embedded into resin to monitor the loading conditions of the composites. With multiple yarn sensor elements aligned in the composite, the crack initiation and propagation could be monitored. Yarn sensors could be easily incorporated into composite structures with minimal invasiveness and weight penalty to enable the structure has self-sensing capabilities.

Polyester resin based glass fiber reinforced composite panels obtained from a local windmill turbine blade part manufacturing company are used to evaluate the performance of inter-digital transducer (IDT) surface wave transducers. Interaction of surface waves with fiberglass layers is addressed in this work. Additionally, artificially created flaws such as cracks, impact damage and delamination are also studied in terms of amplitude changes in order to attempt to quantify the size, location and severity of damage in the test panels. As a potential application to the structural health monitoring (SHM) of windmill turbine blades, the coverage distance within the width of the sound field is estimated to be over 80 cm when a set of IDT sensors consisted of one transmitter and two receivers in a pitch-catch mode.

Simple and contactless methods for determining the health of metallic and composite structures are necessary to allow non-invasive Non-Destructive Evaluation (NDE) of damaged structures. Many recognized damage detection techniques, such as frequency shift, generalized fractal dimension and wavelet transform, have been described with the aim to identify, locate damage and determine the severity of damage. These techniques are often tailored for factors such as (i) type of material, (ii) damage patterns (crack, impact damage, delamination), and (iii) nature of input signals (space and time). In this paper, a wavelet-based damage detection framework that locates damage on cantilevered composite beams via NDE using computer vision technologies is presented. Two types of damage have been investigated in this research: (i) defects induced by removing material to reduce stiffness in a metallic beam and (ii) manufactured delaminations in a composite laminate. The novelty in the proposed approach is the use of bespoke computer vision algorithms for the contactless acquisition of modal shapes, a task that is commonly regarded as a barrier to practical damage detection. Using the proposed method, it is demonstrated that modal shapes of cantilever beams can be readily reconstructed by extracting markers using Hough Transform from images captured using conventional slow motion cameras. This avoids the need to use expensive equipment such as laser doppler vibrometers. The extracted modal shapes are then used as input for a wavelet transform damage detection, exploiting both discrete and continuous variants. The experimental results are verified using finite element models (FEM).

The quantification of variability in the mechanical behavior of metallic materials is important in the design and reliability assessment of mechanical components. A combination of experimental and computational approaches is often required to alleviate the experimental burden and lack of data in constructing a probabilistic formalism for material design. The present work aims at integrating material characterization and computational modeling for the evaluation of variability in the elastodynamic response of random polycrystals. First, a procedure is presented for simulation of random 2D polycrystalline microstructures from limited experimental data. Second, the capability of the numerical model in capturing the variation of the scattered waves due to the random heterogeneities is investigated by introducing a suitable quantity of interest characterizing the intensity of the fluctuations of the stochastic waveforms. Two important types of heterogeneities are considered. The first is the inherent heterogeneity due to the mismatch in the grain orientations. The second is the heterogeneity due to fine scale defects in the form of random intergranular micro-cavities. The numerical model presented in this paper can be useful for the interpretation of experimental ultrasonic measurements for random heterogeneous material. The result is also applicable to the validation of multiscale probabilistic models for material prognosis.

Composite materials are widely used in many applications for their high strength, low weight, and tailorability for specific applications. However, the development of robust and reliable methodologies to detect micro level damage in composite structures has been challenging. For composite materials, attenuation of ultrasonic waves propagating through the media can be used to determine damage within the material. Currently available numerical solutions for attenuation induce arbitrary damage, such as fiber-matrix debonding or inclusions, to show variations between healthy and damaged states. This paper addresses this issue by integrating a micromechanics analysis to simulate damage in the form of a fiber-matrix crack and an analytical model for calculating the attenuation of the waves when they pass through the damaged region. The hybrid analysis is validated by comparison with experimental stress-strain curves and piezoelectric sensing results for attenuation measurement. The results showed good agreement between the experimental stress-strain curves and the results from the micromechanics analysis. Wave propagation analysis also showed good correlation between simulation and experiment for the tested frequency range.

The role of coating in preserving the bonding between steel fibers and concrete is investigated in this paper. Straight types of fibers with and without chemical coating are used in steel fiber reinforced concrete mixes. The specimens are tested in bending with concurrent monitoring of their acoustic emission activity throughout the failure process using two broadband sensors. The different stages of fracture (before, during and after main crack formation) exhibit different acoustic fingerprints, depending on the mechanisms that are active during failure (concrete matrix micro-cracking, macro-cracking and fiber pull out). Additionally, it was seen that the acoustic emission behaviour exhibits distinct characteristics between coated and uncoated fiber specimens. Specifically, the frequency of the emitted waves is much lower for uncoated fiber specimens, especially after the main fracture incident, during the fiber pull out stage of failure. Additionally, the duration and the rise time of the acquired waveforms are much higher for uncoated specimens. These indices are used to distinguish between tensile and shear fracture in concrete and suggest that friction is much stronger for the uncoated fibers. On the other hand, specimens with coated fibers exhibit more tensile characteristics, more likely due to the fact that the bond between fibers and concrete matrix is stronger. The fibers therefore, are not simply pulled out but also detach a small volume of the brittle concrete matrix surrounding them. It seems that the effect of chemical coating can be assessed by acoustic emission parameters additionally to the macroscopic measurements of ultimate toughness.

Improper bonding of composite structures can result in close contact cracks under compressive stresses, called kissing bonds. These bond defects are very difficult to detect using conventional inspection techniques such as tap testing or local ultrasonic scanning and can lead to local propagation of damage if the structure is subjected to crack opening stresses. A method is investigated for identifying kissing bonds in composite material repairs based on vibration measurements. A damage feature of the kissing bond is extracted from the response of the input-output measurement that is a function of the structural path. This path exhibits local decoupling associated with the close contact cracks. Experimental vibration measurements from sandwich composite materials are presented along with the results of the damage detection algorithm for the healthy sections of the material and the kissing bond sections. A vibration based inspection technique could increase the ability to detect kissing bonds in composite material repairs while decreasing inspection time. Benefits of this method of identification over conventional techniques include its robust, objective damage detection methodology and the reduced requirement for specimen preparation and surface texture when compared to ultrasonic scanning.

The increase of terrorism and its global impact has made the determination of the contents of cargo containers a necessity. Existing technology allows non-intrusive inspections to determine the contents of a container rapidly and accurately. However, some cargo shipments are exempt from such inspections. Hence, there is a need for a technology that enables rapid and accurate means of detecting whether such containers were non-intrusively inspected. Non-intrusive inspections are most commonly performed utilizing high powered X-ray equipment. The challenge is creating a device that can detect short duration X-ray scans while maintaining a portable, battery powered, low cost, and easy to use platform. The Pacific Northwest National Laboratory (PNNL) has developed a methodology and prototype device focused on this challenge. The prototype, developed by PNNL, is a battery powered electronic device that continuously measures its X-ray and Gamma exposure, calculates the dose equivalent rate, and makes a determination of whether the device has been exposed to the amount of radiation experienced during an X-ray inspection. Once an inspection is detected, the device will record a timestamp of the event and relay the information to authorized personnel via a visual alert, USB connection, and/or wireless communication. The results of this research demonstrate that PNNL's prototype device can be effective at determining whether a container was scanned by X-ray equipment typically used for cargo container inspections. This paper focuses on laboratory measurements and test results acquired with the PNNL prototype device using several X-ray radiation levels.

Cargo containers onboard ships are widely used in the global supply chain. The need for container security is evidenced by the Container Security Initiative launched by the U.S. Bureau of Customs and Border Protection (CBP). One method of monitoring cargo containers is using low power wireless sensor tags. The wireless sensor tags are used to set up a network that is comprised of tags internal to the container and a central device. The sensor network reports alarms and other anomalies to a central device, which then relays the message to an outside network upon arrival at the destination port. This allows the port authorities to have knowledge of potential security or integrity issues before physically examining the container. Challenges of using wireless sensor tag networks for container security include battery life, size, environmental conditions, information security, and cost among others. PNNL developed an active wireless sensor tag platform capable of reporting data wirelessly to a central node as well as logging data to nonvolatile memory. The tags, operate at 2.4 GHz over an IEEE 802.15.4 protocol, and were designed to be distributed throughout the inside of a shipping container in the upper support frame. The tags are mounted in a housing that allows for simple and efficient installation or removal prior to, during, or after shipment. The distributed tags monitor the entire container volume. The sensor tag platform utilizes low power electronics and provides an extensible sensor interface for incorporating a wide range of sensors including chemical, biological, and environmental sensors.

Ultrasonic nondestructive examination (NDE) has a long and successful history of application across a wide array of industries, including nuclear, aerospace, and transportation sectors. In coarse-grained, cast Manganese (Mn) steel frog components, NDE/inspection challenges are encountered both in-field (after the frogs have been installed on a rail line) and at the manufacturing facilities during post-fabrication QA/QC activities. Periodically inherently flawed frogs are received from a manufacturer, and put into service, as most railroad operators do not have a means to conduct pre-service examinations on received components. Accordingly, there is a need for a pre-service inspection system that can provide a rapid, cost-effective and non-intrusive inspection capability for detection of defects, flaws, and other anomalies in frog components, in order to avoid premature initiation of cracks or failures of these components during service. This study focused on evaluating use of a volumetric phased-array ultrasonic testing (PA-UT) method to monitor fabrication quality assurance. In this preliminary assessment of using PA-UT, data were acquired at a frequency of 2.0 MHz on a known, flawed Mn steel frog component directly from a manufacturing facility. The component contained flaws commonly found as a result of the manufacturing process of these cast rail components. The data were analyzed and the anomalies were detected, localized and characterized. Results were compared against baseline radiographic data. A detection metric was reported in the form of signal-to-noise values.

A dense network of sensors installed in a bridge can continuously generate response data from which the health and condition of the bridge can be analyzed. This approach to structural health monitoring the efforts associated with periodic bridge inspections and can provide timely insight to regions of the bridge suspected of degradation or damage. Nevertheless, the deployment of fine sensor grids on large-scale structures is not feasible using wired monitoring systems because of the rapidly increasing installation labor and costs required. Moreover, the enormous size of raw sensor data, if not translated into meaningful forms of information, can paralyze the bridge manager's decision making. This paper reports the development of a large-scale wireless structural monitoring system for long-span bridges; the system is entirely wireless which renders it low-cost and easy to install. Unlike central tethered data acquisition systems where data processing occurs in the central server, the distributed network of wireless sensors supports data processing. In-network data processing reduces raw data streams into actionable information of immediate value to the bridge manager. The proposed wireless monitoring system has been deployed on the New Carquinez Suspension Bridge in California. Current efforts on the bridge site include: 1) long-term assessment of a dense wireless sensor network; 2) implementation of a sustainable power management solution using solar power; 3) performance evaluation of an internet-enabled cyber-environment; 4) system identification of the bridge; and 5) the development of data mining tools. A hierarchical cyber-environment supports peer-to-peer communication between wireless sensors deployed on the bridge and allows for the connection between sensors and remote database systems via the internet. At the remote server, model calibration and damage detection analyses that employ a reduced-order finite element bridge model are implemented.

This paper studies the problem of distributed computation over a wireless network of resource constrained sensor nodes. In particular, we focus our attention on sensor networks used for structural health monitoring. Within this context, the heaviest computation is to determine the singular value decomposition (SVD) to extract mode shapes (eigenvectors) of a structure. Compared to collecting raw vibration data and performing SVD at a central location, computing SVD within the network can result in a significantly smaller energy consumption and delay. Recent results have proposed methods to decompose SVD into components that can be carried out in a distributed way. The focus of this paper is to determine a near-optimal communication structure that enables the distribution of this computation and the reassembly of the final results, with the objective of minimizing energy consumption subject to a computational delay constraint. We show that this reduces to a generalized clustering problem; a cluster forms a unit on which a component of the overall computation is performed. We establish that this problem is NP-hard. By relaxing the delay constraint, we derive a lower bound to this problem. We also show that the optimal solution to the unconstrained problem has a simple structure that reveals insights into the solution of the original constrained problem. We then propose an integer linear program (ILP) to solve the constrained problem exactly as well as an approximate algorithm with a proven approximation ratio. We also present a distributed version of the approximate algorithm. Numerical results are presented.

To power distributed wireless sensor networks on bridges, traditional power cables or battery replacement are excessively expensive or infeasible. This project develops two power harvesting technologies. First, a novel parametric frequency-increased generator (PFIG) is developed. The fabricated PFIG harvests the non-periodic and unprecedentedly low frequency (DC to 30 Hz) and low acceleration (0.55-9.8 m/s²) mechanical energy available on bridges with an average power > 2 μW. Prototype power conversion and storage electronics were designed and the harvester system was used to charge a capacitor from arbitrary bridge-like vibrations. Second, an RF scavenger operating at medium and shortwave frequencies has been designed and tested. Power scavenging at MHz frequencies allows for lower antenna directivities, reducing sensitivity to antenna positioning. Furthermore, ambient RF signals at these frequencies have higher power levels away from cities and residential areas compared to the UHF and SHF bands utilized for cellular communication systems. An RF power scavenger operating at 1 MHz along with power management and storage circuitry has been demonstrated. It powers a LED at a distance of 10 km from AM radio stations.

A chloride ion selective thin film sensor is proposed for measuring chloride ion concentration, which is an environmental parameter correlated to corrosion. In this work, electrochemical polymerization of Polypyrrole (PPy) doped with chloride ions was achieved on the top of a carbon nanotube (CNT) thin film as a working electrode in an electrochemical cell. The underlying CNT layer conjugated with doped PPy thin film can form a multifunctional "selfsensing" material platform for chloride ion detection in a concrete environment. The paper presents the first type of work using CNT and PPy as hybrid materials for chloride ion sensing. Electrochemical polymerization of PPy results in oxidation that yields an average of one positive charge distributed over four pyrrole units. This positive charge is compensated by negatively-charged chloride ions in the supporting electrolyte. In effect, the chloride ion-doped PPy has become molecularly imprinted with chloride ions thereby providing it with some degree of perm-selectivity for chloride ions. The detection limit of the fabricated chloride ion-doped PPy thin film can reach 10^-8 M and selectivity coefficients are comparable to those in the literature. The reported work aims to lay a strong foundation for detecting chloride ion concentrations in the concrete environment.

In this paper, the development of a new variation of Engineered Cementitious Composite (ECC) that aims to combine tensile ductility with self-sensing ability is described. ECC is a new type of high-performance fiber reinforced cementitious composite that exhibits strain-hardening under applied tensile load while resisting fracture localization. The self-sensing ability is achieved by incorporating a small dosage of carbon black (CB) into the ECC system (hereafter known as CB-ECC) to enhance its piezoresistive behavior while maintaining its tensile strain-hardening behavior. The tensile stress-strain response of CB-ECC is studied with an emphasis on its tensile stress and strain capacity, as well as its cracking pattern. In addition, the piezoresistive behavior of CB-ECC under uniaxial tension is investigated. Specifically, the effect of carbon black content on the electrical properties of ECC including the sensitivity of changes in its bulk conductivity under applied tensile strain are explored in detail.

Due to earthquake effects, buildings often experience large strains, leading to progressive collapses. Monitoring and assessing the large strain condition of critical buildings is of paramount importance to post-earthquake responses and evacuations in earthquake-prone regions. However, few monitoring system can work under such harsh environments. For their unique attributes such as compactness, immunity to electromagnetic interference and capability integrated within various types of structures and materials, optical fiber sensors are especially attractive for quasi-distributed strain sensing purposes in harsh environments. Nevertheless, the dynamic range of strain measurements of an optical sensor is limited by the elasticity of the optical fiber. In this paper, a quasi-distributed optical fiber sensor network based on extrinsic Fabry-Perot interferometer (EFPI) and long-period fiber grating (LPFG) sensors for both large strain and high temperature measurements has been developed. The sensor network combined several inline EFPIs and LPFGs by various couplers. Each EFPI sensor in the sensor network system has the capacity of large strain measurement up to 12% and each LPFG sensor here has a temperature measurement range of up to 700°C. To obtain strain and temperature information for multiple locations more efficiently, a hybrid LPFG/EFPI optical fiber sensor based sensor network system has been studied in this paper. Experimental results demonstrate that the proposed quasi-distributed optical fiber sensor network system is capable for both large strain and high temperature measurements. Therefore, the proposed optical fiber sensor network system can be applied to monitor the quasi-distributed strain of civil infrastructure in harsh environments.

A significant technical advancement in distributed fiber optic strain sensors has been accomplished: Brillouin optical correlation domain analysis (BOCDA) provides a high spatial resolution and the smallest measurement interval due to Brillouin scattering stimulated by the correlation of two counter-propagating lightwaves. In a BOCDA-based system, the measurement position can be varied continuously by changing the modulation frequency, whereas other systems require a sophisticated A/D board for localizing the measurement position. In fact, 50 mm is the current limit of the measurement interval in conventional time-domain-based systems, because higher sampling rates are required to process information traveling at the speed of lightwaves. This paper presents an experimental study on cracked concrete specimen retrofitted with a ply of smart fabric; a fiber optic sensor (FOS) is woven into the fabric. The strain distribution along the sensing fiber is measured to detect the debonding of the smart fabric from the concrete specimen under loading, and the measured highly dense strain information obtained using BOCDA is found to potentially facilitate a better understanding of structural behavior.

Recent developments in fiber optic sensors for monitoring civil structures have been of great help for engineers dealing with these structures. After literature survey it is observed that while using fiber optic sensor system for health monitoring of civil structures not much attention is given to the core quality of the fiber, types of coating on fiber, implementing methodologies, handling of fiber optic sensors and their long term effect on reliability of the performance of the monitoring system. These issues are important because the structural conditions, stress level and environment in which fiber optic sensors are placed are different from telecommunication industry. In this paper issues related to long term structural health monitoring of civil structures are investigated. The issue of the fatigue property of optic fiber is discussed since reversal bending of the fiber may cause adverse effect on the light carrying capacity of the fiber. Other long term structural health monitoring (SHM) issues such as life of fiber, strain transfer process from fiber core to coating, calibration of fiber and selection of fiber are also discussed based on the experiments carried out for successful implementation of long term health monitoring of civil structures. The main objective of these experiments is to come up with comprehensive long term structural health monitoring system for strain measurement.

Long-period gratings (LPGs) have shown their significant promising applications in sensors owing to the attractive features that they posses such as small size, immunity for electromagnetic interference, geometric versatility, multiplexing capability, and resistance to corrosive and hazardous environments. Recent researches have revealed that LPGs written on the standard optical fibers could be used as a powerful sensing platform for structural health monitoring. In this work, we inscribe LPGs into SMF-28 optical fiber by focused-beam CO₂ laser, demonstrating as a refractive index sensor for nondestructive chemical detections in the civil infrastructures. Although evanescent-field based LPG sensors have been applied in quantitatively monitoring chemical analytes including moisture, chloride, and corrosion by-product, etc., the sensitivity, selectivity, and response time as well as thermo-stability of such sensors are still the issues for some special purposes. In order to improve those characteristics of the sensors, we propose two types of nano-film to be coated in grating region by electrostatic self-assembly (ESA) deposition processing. The primary coating does not affect on LPG transmission parameters such as resonance wavelength and its intensity that can be used for sensing, but it increases the sensitivity to refractive index change of surrounding material. The secondary coating is for selectively absorption of analyte molecule of interest. Response time of the nanofilm-coated LPG sensor is dependent on the analyte absorption and de-absorption rates as well as the thicknesses of the coating materials, which is also investigated. Multi-channel sensor system is being designed to monitor different analytes simultaneously, which is continuing to further explore the monitoring of structural health conditions through in situ measurements of corrosion in the concrete structures.

Stay cables are one of the most critical structural components of a cable-stayed bridge. However, stay cables readily suffer from fatigue damage, corrosion damage and their coupled effect. Thus, condition monitoring of stay cables is important to ensure the integrity and safety of a bridge. Glass Fibre Reinforced Polymer Optical Fibre Bragg Grating (GFRP-OFBG) cable, a kind of fibre Bragg grating optical sensing technology-based smart stay cables is used in this study. The application of the smart stay cables on the Tianjin Yonghe Bridge was demonstrated and the vehicle live load effect and fatigue effect of smart stay cables were evaluated based on field monitoring data. Furthermore, the life-cycle cost analysis method of the stay cables is established. Finally, based on the nonlinear reliability index deterioration model, the optimal design of stay cable with different reference period is evaluated.

A testing system contains an advanced vibrometer/interferometer device (AVID) and a high-speed electronic speckle pattern interferometer (ESPI) was developed. AVID is a laser Doppler vibrometer that can be used to detect single-point linear and angular velocity with DC to 20 MHz bandwidth and with nanometer resolution. In swept frequency mode, frequency response from mHz to MHz of the structure of interest can be measured. The ESPI experimental setup can be used to measure full-field out-of-plane displacement. A 5-1 phase shifting method and a correlation algorithm were used to analyze the phase difference between the reference signal and the speckle signal scattered from the sample surface. In order to show the efficiency and effectiveness of AVID and ESPI, we designed a micro-speaker composed of a plate with fixed boundaries and two piezo-actuators attached to the sides of the plate. The AVID was used to measure the vibration of one of the piezo-actuators and the ESPI was adopted to measure the two-dimensional out-of-plane displacement of the plate. A microphone was used to measure the acoustic response created by the micro-speaker. Driving signal includes random signal, sinusoidal signal, amplitude modulated high-frequency carrier signal, etc. Angular response induced by amplitude modulated high-frequency carrier signal was found to be significantly narrower than the frequency responses created by other types of driving signals. The validity of our newly developed NDE system are detailed by comparing the relationship between the vibration signal of the micro-speaker and the acoustic field generated.

Spectral Analysis for Surface Wave (SASW) is a widely practiced NDT method due to its ability to identify the shear velocity profile of subsurface layers. However, the SASW method is limited to point-to-point inspection because all data has to go through an inversion process, which is iterative and manual. Some automated iteration techniques were developed to improve the efficiency of inversion analysis. These attempts did not change the situation much because they were still based on the guess-and-check procedure incorporated with a forward analysis. In this paper, a new inversion analysis algorithm is proposed to estimate the shear velocity profile rapidly without performing conventional forward analysis. Unlike conventionally determining the dispersion curve with a stiffness matrix or something similar, the dispersion curve of a layered structure is assumed to be a weighted combination of the shear velocity profile. The weighting factors are determined according to the variation of particle displacement with depth for a specified wavelength of surface wave. Based on this assumption, a fast inversion algorithm is established to estimate the shear velocity profile from a given dispersion curve. No prior knowledge of the test site or personal expertise is needed because this method does not require the initial values of the layer depths and shear velocities. This new method allows the SASW method to be a fully automatic or even real-time reporting method for highway pavement detection. The accuracy of this fast inversion algorithm is verified by comparing the results to those of the conventional algorithm.

SASW (Spectral Analysis of Surface Waves) is practical and relatively effective in characterizing subsurface ground truth. According to the surface wave in the interesting range of frequency, some criteria for source-receiver configuration are employed and limit the applications. Challenges emerge when SASW is applied to study the surface wave involving multiple modes effect and when the source is near the receiver. In such cases, multiple modes effects and evanescent wave fields are present in array sensing and might weaken the inversion accuracy of pavement subsurface profile. In this work, these issues were investigated and a complex wave number estimation based method was proposed. The complex wave number was estimated by iterative linear exponential fitting from wave field model to response measurements. Evanescent wave for near field and multiple modes effects were focused in the proposed method. Finally, simulated signals from FEA model were processed to demonstrate the algorithm and the results were discussed.

A compact, high-performance, programmable Ground Penetrating Radar (GPR) system is described based on an impulse generator transmitter, a full waveform sampling single shot receiver, and high directivity antennas. The digital programmable pulse generator is developed for the transmitter circuit and both the pulse width and pulse shape are tunable to adjust for different modes of operation. It utilizes a step-recovery diode (SRD) and short-circuited microstrip lines to produce sub-nanosecond wide ultra-wideband (UWB) pulses. Sharp step signals are generated by periodic clock signals that are connected to the SRD's input node. Up to four variable width pulses (0.8, 1.0, 1.5, and 2.1 ns) are generated through a number of PIN switches controlling the selection of different microstrip lengths. A schottky diode is used as a rectifier at the output of the SRD in order to pass only the positive part of the Gaussian pulses while another group of short-circuit microstrips are used to generate amplitude-reversed Gaussian pulses. The addition of the two pulses results in a Gaussian monocycle pulse which is more energy efficient for emission. The pulse generator is connected to a number of UWB antennas. Primarily, a UWB Vivaldi antenna (500 MHz to 5 GHz) is used, but a number of other high-performance GPR-oriented antennas are investigated as well. All have linear phase characteristic, constant phase center, constant polarization and flat gain. A number of methods including resistive loading are used to decrease any resonances due to the antenna structure and unwanted reflections from the ground. The antennas exhibit good gain characteristics in the design bandwidth.

A novel low-cost low-complexity design based on Radar technology operating at millimeter wave is presented for the characterization of road surface conditions in real-time. At frequencies of 24-77 GHz the wavelength is long enough to obtain slight penetration in the top 1-2" of asphalt or concrete surface, but is also short enough to resolve details such as crack or pothole depth/etc. The Radar system operates by continuously outputting radiation and sampling the roadway-reflected radiation through a receiver-downconverter-sampler system. In initial laboratory testing, the received signal strength was observed to obey the inverse distance 1/R2 relationship. The received signal is further dependent on the incidence angle between the plane of the sensor and the plane of the roadway. One observation from this is the need of auxiliary sensors for determining the distance above the road surface as well as providing incident angle data. The sensor was further mounted on a movable cart used to measure the reflected signal on a variety of road surfaces (smooth, rough, surface defects, and environment factors such as various levels of moisture). By comparing measurements of the material after soaking to measurements in the dry state, there is substantial differentiation in measurements, which indicates the ability to measure the porosity of various materials. Lastly the sensor bandwidth provides the capability to measure surface roughness illustrated in the standard deviation of measurement data. On a macroscopic level, the aggregate in a roadway acts as a series of random scatterers and rough roadways or roadways with surface voids show a large variance between measurements of nearby points.

Detection of subsurface defects (e.g., delamination, cracking) using microwave/radar sensors (e.g., ground penetrating radar or GPR) is an important and promising technique for the effective and efficient maintenance of civil infrastructure. In this technique, reflected and scattered electromagnetic signals are typically collected and used for interpreting the size and property of subsurface damages. The objective of this paper is to investigate the feasibility of using finite measurements in the reflected signal for size estimation, through the geometric analysis of waveform. Simulated transient electromagnetic response was generated by finite difference time domain (FDTD) methods in two dimensional domain. A modulated Gaussian impulse at a center frequency of 3.5 GHz was used as the source. Rectangular delaminations with a width ranging from 3.048 cm to 16.256 cm and a thickness of 0.762 cm were considered. The depth of subsurface delamination was also studied. The curvature of reflected waveforms, obtained by three measurements, was used to correlate with the width of subsurface delamination. A relative width parameter was defined and used in the proposed equations for estimating the delamination width with less than 10% error. It is found that the relative width parameter is linearly proportional to the difference in waveform curvature. The proposed approach is potentially applicable to other subsurface defects with different shapes.

A new skewed two span continuous steel girder bridge was constructed and opened to traffic recently. This bridge uses high performance steel (HPS 100W) in the flanges of the negative moment region over the intermediate pier. For construction verification and long-term structural health monitoring purposes, a finite element (FE) model was developed for the bridge superstructure. Various field tests were performed to verify the model: 1) LiDAR scan, 2) static truck load tests, and 3) Laser doppler vibrometer testing. LiDAR scanner was introduced to gain geometrical information of the bridge in the real world. It was also used to measure girder deflections during load tests. The fundamental frequency of the bridge vibration was obtained by using a Laser doppler vibrometer. Both dynamic and static measurements are then used to update the FE model. This valid bridge superstructure FE model was provided to local DOT bridge engineers with the completion of this study.

Deck joint is important for a bridge - Any cost-effective evaluation methods that can help trace joint movements during frequent inspections will provide valuable data to bridge engineers. In this paper, 3D Terrestrial LiDAR and Aerial photography are being investigated as possible joint evaluation methods. The laser scanners record 3D positions of the surface points, generating high density point clouds. Aerial images taken by commercial DSLR cameras in a small airplane flying at 1000 feet, generates high resolution imagery. Both techniques have sub-inch pixel resolutions. Scanning results from bridges in both Florida and Alabama have shown that LiDAR and aerial imaging technologies are compatible techniques and can be applied in bridge deck joint performance evaluation. Moreover, both techniques have the potential to reduce the costs in bridge inspection.

This paper reports the outcomes of a study of the vehicle crossing effects on terrestrial LiDAR scan on highway bridges for underclearance measurements. Ground-based or vehicle-mount terrestrial LiDAR scanners, which recreate the bridge structure as 3D point cloud of thousands of position data points, have been found to be ideal for bridge clearance measurements. To determine the effects of ambient overhead vehicle crossing and seasonal temperature variation on clearance measurements, periodic monitoring of the Harris Road Bridge has been conducted. A simplistic but practical correlation analysis is performed which shows that operational LiDAR scanning is a viable technique for bridge clearance measurements.

Terrestrial 3D LiDAR scanner has been suggested as a remote sensing technique for existing and newly constructed bridges. Using high resolution laser, 3D LiDAR can populate a surficial area with millions of position data points. Bridge problems can benefit from LiDAR scan and current studies have found potential application including: bridge clearance, static deflection measurement and damage detection. The technique is especially useful when accurate measurement of bridge geometry cannot be achieved by traditional survey technique, especially when site topography is prohibitive. However, resolution is still one of the main reasons that limit the application of LiDAR technology for advance bridge monitoring. This paper discusses the reliability issues of such technique as well as the LiDAR based bridge monitoring methodologies. Several experimental results are presented to establish the sensitivities for different assessments.

As the nation's asphalt pavements age and deteriorate, the need for corrective measures to restore safety and rideability increases. The potholes and alligator cracks in the asphalt pavement of our country's roadways have become an annoying part of our daily life and no innovative technologies are available to improve the safety of US drivers, reduce the cost of road maintenance. We have identified a polymeric material, dicyclopentadiene (DCPD) resin, which can be cured by Grubb's catalyst and other commercially available catalysts to become an ultratough material with all the desired properties for pothole repair. We have characterized DCPD infiltration characteristics using non-destructive CT scan, and the mechanical properties using indirect tensile test under hot, cold or wet conditions. The preliminary results show that DCPD is a promising material for applications in reinforced pothole patching materials.

This paper provides a summary of ongoing research sponsored by the National Institute of Standards and Technology (NIST) that seeks to improve inspection practices for steel bridges by providing the technology and methodology for real-time monitoring. In order to reduce the time and cost of installing a monitoring system, the research team elected to use wireless communications within the sensor network. The investigation considered both IEEE 802.11 and IEEE 802.15.4 communications protocols and identified the latter as more practical for bridge monitoring applications. Studies were conducted to investigate possible improvements in the network performance using high-gain antennas. Results from experiments conducted outside and on bridges with different antennas are presented in this paper. Although some benefits were observed using high-gain antennas, the inconsistent performance and higher cost relative to the current stock, omni-directional antennas does not justify their use.

A passive sensor platform has been developed at the University of Texas at Austin to monitor corrosion of embedded reinforcement in concrete structures. The sensors are powered and interrogated in a wireless manner. Initial sensor designs used a sacrificial corroding steel wire to indicate the risk of corrosion within concrete. The wire was physically connected to the sensor circuitry and passed through the circuit protection layer. Consequently, it allowed contaminants to reach the circuit electric components causing corrosion and limiting the service life of the sensor. A novel sensor configuration that relies on wireless inductive coupling between a resonant circuit and the transducer element is presented. The non-contact design eliminates the breach concern and enhances the durability of the senor. Preliminary test results of the new design will be discussed in this paper.

Steel corrosion in concrete is a main cause of deterioration and early failure of concrete structures. A novel integration of electromagnetic heat induction and infrared (IR) thermography is proposed for nondestructive detection of steel corrosion in concrete, by taking advantage of the difference in thermal characteristics of corroded and non-corroded steel. This paper focuses on experimental investigation of the concept. An inductive heater is developed to remotely heat the steel rebar from concrete surface, which is integrated with an IR camera. Bare rebar and concrete samples with different cover depths are prepared. Each concrete sample is embedded with a single steel rebar in the middle, resulting an identical cover depth from the front and the back surfaces, which enables heat induction from one surface and IR thermogrphay from the other simultaneously. The impressed current method is adopted to induce accelerated corrosion on the rebar. IR video images are recorded during both heating and cooling periods. The test results demonstrate a clear difference in thermal characteristics between corroded and non-corroded samples. The corroded samples show higher rates of heating and cooling as well as a higher peak IR intensity than those of the non-corroded samples. This study demonstrates a potential for nondestructive detection of rebar corrosion in concrete.

The SCANSⁿ is a structural health monitoring (SHM) system is being developed by Acellent Technologies to monitor steel bridges. The required voltage of the system is 14.4 V for active scanning, and the power consumption is approximately 8 W. The investigated energy harvesting from both solar and thermal sources to recharge the lithium-ion battery of the system. A solar panel and a Thermal Electric Generator (TEG) are used to harvest ambient energy. The thermoelectric device is placed in a Fresnel dome to maximize the temperature gradient of the TEG. During shading of the solar panel, the TEG continues to supply power to the battery charger. Since the output voltages and currents of the solar and thermal energy harvesters vary significantly, the energy harvesting module is constructed by two buck-boost converters operating in parallel. Maximal Power Point Tracking (MPPT) is employed for the buck-boost converter for the solar panel, while a fixed duty cycle converter is used for the TEG due to substantially lower power compared with the solar panel. The system design and measured results of a prototype system are presented. Our prototype system successfully demonstrates that the SCANSⁿ system can be powered by the energy harvested from solar and thermal.

Thermographic techniques offer distinct advantages over other techniques usually employed to assess damage accumulation and propagation. Among the advantages of these techniques are the fully remote-non contact monitoring and their ability for full field imaging. Due to the transient nature of the heat transfer phenomenon, phase and lock-in techniques are of particular interest in order to increase the resolution of the signal or provide depth discrimination. Last but not least, when a structure is subjected to load, these techniques can be used in order to monitor the irreversible damage phenomena, as manifested by the local heat accumulation in the vicinity of the defect. This eliminates the need for external heat source, as any cyclic loading can induce the heat gradient necessary to pinpoint the defect accumulation and propagation. In the aforementioned context, lock-in thermography has been employed to monitor the delamination propagation in composites and the critical failure of bonded repairs when the materials are subjected to fatigue loading. Lock-in thermography proved successful in identifying debonding initiation and propagation as well in depicting the thermoelastic stress field around purposely induced discontinuities.

A combined ultrasound and thermography defect detection system using a raster scanned Q-switched laser as a source of heat and ultrasound has been developed for identifying surface breaking defects. Heat is generated on a sample surface by a laser source and the resultant thermal image is examined by a thermal imaging camera. This can be done using a cw or a pulsed laser, but for ultrasonic generation a pulsed laser beam is required. When a defect is present, the flow of heat in the sample is disturbed and a change in shape of the thermal spot on the sample's surface can be detected. The pulsed laser beam generates simultaneously an ultrasonic wave that can be detected by a suitable transducer, which in this case is an electromagnetic acoustic transducer (EMAT). The presence of a defect changes both the amplitude and frequency content of the received wave. Three dimensional finite element modelling of the interaction between Lamb waves and defects have been studied and compared with experimental data, in order to optimise source and detector positions around a defect. The approach can detect surface crack defects via the ultrasonic and thermography method in one measurement.