This PDF file contains the front matter associated with SPIE Proceedings Volume 8347, including the Title Page, Copyright information, Table of Contents, Introduction, and Conference Committee listing.

Spun-cast concrete poles have been increasingly used in power line support in U.S. during the past decade. Dynamic behaviors of these pole structures are critical design considerations due to the wind and conductor effects. However, free vibration of pole structures has rarely been studied and existing design guidelines do not provide clear information associated with pole natural frequencies. To build-up knowledge in pole vibration, analyses of concrete poles of various sizes and classes were performed numerically. The finite element models were verified with experimental modal data from several poles. Based on the study, empirical relations between geometric parameters and pole natural frequencies were developed, which are very basic information for health monitoring of power lines.

This paper presents a new methodology that is built upon existing hardware such as shaker force generator and accelerometers that are both portable and convenient to use for a variety of civil and mechanical structures. Our key idea is to use a moving load that is placed successively at a number of locations on the structure, and measure the corresponding frequency responses. These frequency response measurements will then be used to extract the structural properties. Our new methodology so called mass response method enables the direct extraction of the equivalent stiffness and mass of the critical members of a structure without using a priori information of the structure. A number of case studies are carried out to demonstrate the accuracy and efficiency of its usage in structural health monitoring applications. Furthermore, the uncertainty introduces to this methodology is also investigated and discussed.

This paper presents a study on the seismic response trends evaluation and finite element model updating of a reinforced concrete building monitored for a period of more than two years. The three storey reinforced concrete building is instrumented with five tri-axial accelerometers and a free-field tri-axial accelerometer. The time domain N4SID system identification technique was used to obtain the frequencies and damping ratios considering flexible base models taking into account the soil-structure-interaction (SSI) using 50 earthquakes. Trends of variation of seismic response were developed by correlating the peak response acceleration at the roof level with identified frequencies and damping ratios. A general trend of decreasing frequencies was observed with increased level of shaking. To simulate the behavior of the building, a three dimensional finite element model (FEM) was developed. To incorporate real in-situ conditions, soil underneath the foundation and around the building was modeled using spring elements and non-structural components (claddings and partitions) were also included. The developed FEM was then calibrated using a sensitivity based model updating technique taking into account soil flexibility and non-structural components as updating parameters. It was concluded from the investigation that knowledge of the variation of seismic response of buildings is necessary to better understand their behavior during earthquakes, and also that the participation of soil and non-structural components is significant towards the seismic response of the building and these should be considered in models to simulate the real behavior.

In this study, a linear model with frequency dependent structural property was used to generate the corresponding frequency response function and dynamic stiffness for selected dynamic problems where certain nonlinearity can be resulted from time/space varying characteristics of the bridge vibrations. Derivation of the proposed formula is based on the vibration theory of the elementary member with frequency dependent elastic properties, in which Modulus of Elasticity can be interpreted as serial and parallel connections of springs and dashpots. This paper first describes the use of the proposed formulation to reasonably depict the nonlinear cable vibration associated with the varying tension forces over time. The proposed formulation can also be used to simulate flexural vibration of damage beams in which the elastic property involves certain space varying or time varying characteristics. Simple numerical/experimental data were next used to demonstrate and confirm the potential application of such simulation idea. Consequently, it is concluded that such assessment model with frequency dependent parameters can be practically feasible and serve as a useful tool in the spectral analysis regarding dynamic problems of slender bridge members.

The objectives of this study were to investigate interaction of a parabolic acoustic reflector with leaky stress waves in air-coupled IE testing, and to develop an optimal geometry of the acoustic reflector. The resulting acoustic reflector will be used as a part of an air-coupled impact-echo device for delamination detection in concrete bridge decks. The study was conducted on a series of 2D finite element (FE) models. The models included both solid concrete plate and air domains. The models were developed to investigate interaction of leaky stress waves (in particular, S1 resonance mode in Lamb waves) with a parabolic reflector. A series of parametric studies was conducted to determine the optimal geometry of parabolic reflectors (cylinders). The main variables were the rim angle and the width of the reflectors, and location of air-coupled sensors. Furthermore, numerical simulations using 2D FE models, including delamination defects in concrete decks, were conducted to verify the optimal parabolic reflector is effective in enhancing the amplitude of S1 resonance modes in Lamb waves corresponding to the various depths of delamination defects. Finally, the results clearly demonstrate that the optimal parabolic domes can significantly improve signal-to-noise ratio in the air-coupled IE measurements. This will increase the feasibility of air-coupled sensing in actual impact echo testing on concrete bridge decks.

An effective multisensor data fusion and visualization framework is proposed for accurate localization and effective visualization of delamination in concrete bridge decks based on impact echo (IE) nondestructive evaluation method. The fusion rules are developed by analyzing the spatial distribution of surface motion resulting from mechanical impacts applied at different locations based on numerical simulation. The proposed approach can process, integrate and interpret the data from a series IE source-receiver arrays to improve the accuracy and reliability of delamination characterization for bridge decks. The visualization approach provides an intuitive way for users to visualize the internal defects of concrete bridge decks.

Traditional multi-reference impact testing (MRIT) has the merit to identify not only the structural modal parameters but also structural flexibility, however, it requires a large number of sensors mounted on the entire structure which leads to expensive experiment cost. A new mobile impact testing method is proposed in this article for a more efficient flexibility identification of bridges. In the proposed method, the structure under investigation is subdivided into smaller substructures which are tested independently. Then the experimental data collected from all sub-structures are integrated by taking the interface measurement as a reference for flexibility identification of the entire structure. The new impact testing method only requires limited instrumentation, thus it can be performed rapidly and efficiently. Especially, the signal processing procedure developed in the proposed method is able to identify the full flexibility matrix of the entire structure from the sparse FRF matrices of the sub-structures. Numerical and experimental examples studied successfully verify the effectiveness of the proposed method by comparing its results with those from the traditional MRIT method for structural flexibility identification and deflection prediction.

Fiber-optic accelerometers have attracted great attention in recent years due to the fact that they have many advantages over electrical counterparts because all-fiber accelerometers have the capabilities for multiplexing to reduce cabling and to transmit signals over a long distance. They are also immune to electromagnetic interference. We propose and develop a compact and robust photonic crystal fiber (PCF) Mach-Zehnder interferometer (MZI) that can be implemented as an accelerometer for measurements of vibration and displacement. To excite core mode to couple out with cladding modes, two long-period gratings (LPGs) with identical transmission spectra are needed to be written in an endless single-mode PCF using a CO2 laser. The first LPG can couple a part of core mode to several cladding modes. After the light beams travel at different speeds over a certain length of the core and cladding, the cladding modes will be recoupled back to the core when they meet the second LPG, resulting in interference between the core mode and cladding modes. Dynamic strain is introduced to the PCF-MZI fiber segment that is bonded onto a spring-mass system. The shift of interference fringe can be measured by a photodetector, and the transformed analog voltage signal is proportional to the acceleration of the sensor head. Based on simulations of the PCF-MZI accelerometer, we can get a sensitivity of ~ 0.08 nm/g which is comparable with fiber Bragg grating (FBG) accelerometers. The proposed accelerometer has a capability of temperature insensitivity; therefore, no thermal-compensation scheme is required. Experimental results indicate that the PCF-MZI accelerometer may be a good candidate sensor for applications in civil engineering infrastructure and aeronautical platforms.

Proactive aging management of nuclear power plant passive components requires technologies to enable monitoring and accurate quantification of material condition at early stages of degradation (i.e., pre-macrocrack). Acoustic emission (AE) is well-suited to continuous monitoring of component degradation and is proposed as a method to monitor degradation during accelerated thermal fatigue tests. A key consideration is the ability to separate degradation responses from external sources such as water spray induced during thermal fatigue testing. Water spray provides a significant background of acoustic signals, which can overwhelm AE signals caused by degradation. Analysis of AE signal frequency and energy is proposed in this work as a means for separating degradation signals from background sources. Encouraging results were obtained by applying both frequency and energy filters to preliminary data. The analysis of signals filtered using frequency and energy provides signatures exhibiting several characteristics that are consistent with degradation accumulation in materials. Future work is planned to enable verification of the efficacy of AE for thermal fatigue crack initiation detection. While the emphasis has been placed on the use of AE for crack initiation detection during accelerated aging tests, this work also has implications with respect to the use of AE as a primary tool for early degradation monitoring in nuclear power plant materials. The development of NDE tools for characterization of aging in materials can also benefit from the use of a technology such as AE which can continuously monitor and detect crack initiation during accelerated aging tests.

To evaluate the potential of detecting leakage of water pipes using ground-penetrating radar (GPR), a lab experiment is conducted as well as numerical modeling. In the experiment, an artificial 'leakage' is put under, beside and above a pipe buried in dry soil, simulating different leakage locations. By scanning such an experimental model using commercial GPR, more understanding is gained regarding the signature of leakage in GPR profile. Compared to a distinct hyperbola as shown in GPR profile of intact pipes, the leakage zone is disturbed by the wave reflections caused by saturated soil. Furthermore, a numerical model is constructed to simulate such a phenomenon. Maxwell's equations, permittivity distribution of dry and saturated soil, and artificial absorbing boundary conditions are the three key points of such a model. Numerically simulated results seem to be in agreement with experimental results. And the signature of leakage is also visible in the simulated GPR profile. Therefore, GPR survey seems to be promising as an efficient and nondestructive remote leakage detection approach. And the effects of background inhomogeneity and ground-surface roughness can be investigated in future using such an experimental or simulation approach.

This paper presents a micro-sized Linear Polarization Resistance (μLPR) corrosion sensor for Structural Health Management (SHM) applications. The μLPR sensor is based on conventional macro-sized Linear Polarization Resistance (LPR) sensors with the additional benefit of a reduced form factor making it a viable and economical candidate for remote corrosion monitoring of high value structures, such as buildings, bridges, or aircraft. An experiment was conducted with eight μLPR sensors and four test coupons to validate the performance of the sensor. The results demonstrate the effectiveness of the sensor as an efficient means to measure corrosion. The paper concludes with a brief description of a typical application where the μLPR is used in a bridge cable.

A reconfigurable and portable wireless reader has been designed for embedded passive Electronic Structural Surveillance (ESS) sensors, used to monitor corrosion in infrastructure systems. The passive ESS sensors have been developed and proven effective in monitoring localized defects in their environment. They are interrogated by inductively coupled magnetic field of a reader coil. The input impedance of the reader coil is monitored to determine whether a corrosion threshold has been reached. We have previously used an impedance analyzer to obtain the impedance data. Such systems have good sensitivity and moderate speed but are bulky and heavy. The new reader approach presented in this paper is designed addressing the need of portability, sensitivity and read range. The reader electronics is implemented on a reconfigurable National Instruments (NI) modular transceiver platform, capable of software defined radio. The design employs a reflectometer, which is implemented using a 3-port directional coupler and a single coil as both the driver and reader, along with the transceiver. The NI transceiver is used to generate a swept frequency input signal and analyze reflected signal from the reader, which is related to the input impedance of our ESS sensor. The configuration of the reader coil is optimized for reader range and sensitivity. We have acquired analog data using this design, showing that the real-time reader system facilitates especially fast detection and long read ranges for threshold-only sensing.

This paper describes the ongoing research efforts to develop a novel class of low-cost, unpowered, wireless sensors for detecting corrosion of reinforcement in concrete structures. The sensors are powered through magnetic coupling between an external reader coil and an embedded sensor. Measured AC impedance is used to interpret the state of the embedded sensor. The sensors are envisioned to be placed during construction and interrogated as part of routine inspections. The sensor prototype incorporates a sacrificial corroding element that is placed entirely outside the sensor components and interacts with the resonant circuit by inductive coupling and shielding of the magnetic fields. As the resistance of the sacrificial element increases due to corrosion, the measured frequency response changes gradually indicating corrosion initiation within concrete. In this paper the potential for detecting multiple levels of corrosion damage is demonstrated.

Results of an experimental evaluation of nano/micro inorganic composites are presented in this paper. Alkali alumino silicates matrices reinforced with nano/micro fibers were used to repair (glue) fractured concrete prisms and test them in three point bending. Further, shear strength of matrices were also obtained using push-up tests. The variables evaluated were mix composition, temperature and specimen size. It is observed that flexural tensile strength of 1000 psi can be achieved from the developed matrices. In some instances when repaired broken prisms were tested, the failure occurred by creation of a new fracture surface. The developed matrices had the fluidity to fill very thin delamination, which can be pumped to reach delamination through small drilled holes. The results show that the compositions obtained in this study have excellent potential for application involving the repair of delamination.

Composite materials like carbon fiber reinforced plastics (CFRP) are used more and more in commercial applications and offer several attractive ways for tailored solutions. However, for many safety issues these materials require adequate nondestructive testing. The extension of the ultrasound technique for nondestructive purpose with laser technology brings new possibilities into the production processes for example manufacturing of small complex components with the capability of an inline observation. One problem with laser based ultrasound is the conventional Gaussian beam shape and an inappropriate thermal penetration when using for example a YAG-laser, which is usually destructive for the properties of the material under test. We describe the successful implementation of laser-based ultrasound using a Liquid Crystal on Silicon (LCoS) spatial light modulator for beam shaping. A LCoS display optimized as phase-only modulator with 8-bit phase level addressing is used to adapt the intensity dispersal of the laser to a predetermined spatial light distribution for nondestructive optoacoustic interaction with CFRP materials in the thermoelastic regime.

Carbon fiber (CF)-plastic composites are expected from the view point of light weighting vehicle structures. The CF/thermoset plastic laminates have low damage resistance to out-of-plane impact as a problem to be solved, because they behave as a low strength inter-laminar as compared with high-strength in fiber direction. Accordingly it is strongly desired to develop CF-composite materials based thermoplastics that have higher toughness than thermoset, for vehicle use. The present paper describes investigation of impact damages through thermoelastic stress analysis (TSA). Lowvelocity impact test using drop weight was conducted on stitched non-crimp-fabric CF/NY6 composite specimens. Stress distribution of the specimens under impact loading was monitored by a lock-in thermography system from the opposite side of the impact direction. The instrumentation system, which had a focal plane array detector, provided a succession of thermoelastic stress information as a sequence of TSA images at a high rate. The measured stress distribution agreed well with a theoretical. And also, selecting a contour feature of the stress distribution determined with a suitable level conformed approximately to the internal damage image that was processed from the TSA images obtained before and after impact.

The advancement of composite materials in aircraft structures has led to on increased need for effective structural health monitoring (SHM) technologies that are able to detect and assess damage present in composites structures. The work presented in this paper is interested in understanding using self-sensing piezoelectric wafer active sensors (PWAS) to conduct electromechanical impedance spectroscopy (EMIS) in glass fiber reinforced plastic (GFRP) to perform structures health monitoring. PWAS are bonded to the composite material and the EMIS method is used to analyze the changes in the structural resonance and anti-resonance. As the damage progresses in the specimen, the impedance spectrum will change. In addition, multi-physics based finite element method (MP-FEM) is used to model the electromechanical behavior of a free PWAS and its interaction with the host structure on which it is bonded. The MPFEM permits the input and the output variables to be expressed directly in electric terms while the two way electromechanical conversion is done internally in the MP_FEM formulation. To reach the goal of using the EMIS approach to detect damage, several damages models are generated on laminated GFRP structures. The effects of the modeling are carefully studied through experimental validation. A good match has been observed for low and very high frequencies.

Carbon fiber based materials are used in many lightweight applications in aeronautical, automotive, machine and civil engineering application. By the increasing automation in the production process of CFRP laminates a manual optical inspection of each resin transfer molding (RTM) layer is not practicable. Due to the limitation to surface inspection, the quality parameters of multilayer 3 dimensional materials cannot be observed by optical systems. The Imaging Eddy- Current (EC) NDT is the only suitable inspection method for non-resin materials in the textile state that allows an inspection of surface and hidden layers in parallel. The HF-ECI method has the capability to measure layer displacements (misaligned angle orientations) and gap sizes in a multilayer carbon fiber structure. EC technique uses the variation of the electrical conductivity of carbon based materials to obtain material properties. Beside the determination of textural parameters like layer orientation and gap sizes between rovings, the detection of foreign polymer particles, fuzzy balls or visualization of undulations can be done by the method. For all of these typical parameters an imaging classification process chain based on a high resolving directional ECimaging device named EddyCus® MPECS and a 2D-FFT with adapted preprocessing algorithms are developed.

Designing an attachment structure that is both novel and meets the system requirements can be a difficult task especially for inexperienced designers. This paper presents a design methodology for concept generation of a "parent/child" attachment system. The "child" is broadly defined as any device, part, or subsystem that will attach to any existing system, part, or device called the "parent." An inductive research process was used to study a variety of products, patents, and biological examples that exemplified the parent/child system. Common traits among these products were found and categorized as attachment principles in three different domains: mechanical, material, and field. The attachment principles within the mechanical domain and accompanying examples are the focus of this paper. As an example of the method, a case study of generating concepts for a bridge mounted wind energy harvester using the mechanical attachment principles derived from the methodology and TRIZ principles derived from Altshuller's matrix of contradictions is presented.

Sensors with long lifetimes are ideal for infrastructure monitoring. Miniaturized sensor systems are only capable of storing small amounts of energy. Prior work has increased sensor lifetime through the reduction of supply voltage , necessitating voltage conversion from storage elements such as batteries. Sensor lifetime can be further extended by harvesting from solar, vibrational, or thermal energy. Since harvested energy is sporadic, it must be detected and stored. Harvesting sources do not provide voltage levels suitable for secondary power sources, necessitating DC-DC upconversion. We demonstrate a 8.75mm³ sensor system with a near-threshold ARM microcontroller, custom 3.3fW/bit SRAM, two 1mm² solar cells, a thin-film Li-ion battery, and integrated power management unit. The 7.7μW system enters a 550pW data-retentive sleep state between measurements and harvests solar energy to enable energy autonomy. Our receiver and transmitter architectures benefit from a design strategy that employs mixed signal and digital circuit schemes that perform well in advanced CMOS integrated circuit technologies. A prototype transmitter implemented in 0.13μm CMOS satisfies the requirements for Zigbee, but consumes far less power consumption than state-of-the-art commercial devices.

This work presents an alternative design of a rotating energy harvester, which possesses the capability of powering electronic sensors and wireless sensor networks within vehicle. This energy harvester design is based on magnetostatic coupling between a stationary circular-arc hard magnet array and rotating magnetic solenoids, which consists of a unique core with high permeability (μr>10,000) to significantly increase the output power density. A prototype of this rotating energy harvesting system has been fabricated and demonstrated on a rotating wheel at speeds from 10 to 60 miles/hour (mph). Test of the prototype equipped with energy storage circuit and wireless transmission board on actual vehicle has been carried out. Results of different rotating frequencies show average power densities from 1 to 5 W/cm3. A numerical and experimental study of powering a real-time wireless tire pressure monitoring system (TPMS) reveals that the energy harvester design generates constant and steady power sufficient for continuous operation of the TPMS.

Small format aerial photography (SFAP) with low flying technique is proposed for damage evaluation of bridge decks. High resolution images obtained using under-belly photography can be used to quantify the various bridge deck problems. The conventional truck-mount or vehicle-mount deck imaging technologies require a large number of image samples. Hence the physical scanning is time consuming and it is also challenging consider the size and location of a bridge. Aerial imaging overcomes these issues, but they face different kinds of challenges that are posed by obstacles such as shadow from trees, power lines and vehicles, signs and luminaries structures. The image resolution uncertainty, which is a function of the pilot skills and flying conditions, may also add additional challenges to aerial imaging technique. Hence different image processing tools have to be integrated into a single package to achieve the desired task. This paper summarizes the challenges faced and the preliminary results are presented and discussed.

Previous visual damage detection on bridge structure based on eye-ball method is arbitrary and time-consuming for bridge management due to its heuristic nature. Commercial remote sensing (CRS), which has remarkable applications for geometric quantification, is suggested to supplement visual bridge inspection. Ground-based LIDAR is one of the remote sensing tools that have been successfully used in bridge evaluation. Most of the early measurement algorithms are developed based on the spatial information contained from the LIDAR data; this paper explores the potential of applying another important feature of the scan data: the reflectivity, to enhance the defect detection program. The addition of reflectivity in damage diagnostics is particularly useful for defect detection of curved surfaces. A damaged joint area and concrete beam were selected to verify the method. The study shows that the reflectivity of the LIDAR could be used to support the automatic defect detection in bridges by combining it with the current position-based only image processing algorithms.

Time of flight diffraction and imaging (TOFDI) is based on time of flight diffraction (TOFD); it adds cross-sectional imaging to examine the bulk of a sample. Multiple wave modes are generated by a pulsed laser beam, ablative source and are received by a sparse array of non-contact electromagnetic acoustic transducers (EMATs). A B-scan is formed from multiple data captures (A-scans), with time and scan axes, and colour representing amplitude. B-scans may contain horizontal lines from surface waves propagating directly from emitter to receiver, or via a back-wall reflection, and angled lines after reflection off a surface edge. A Hough transform (HT), modified to deal with the constraints of a Bscan, can remove such lines. A parabola matched filter has been developed to identify features in the B-scan caused by scattering from point-like features, reducing them to peaks. The processed B-scan is processed further to form a crosssectional image, enabling detection and positioning of multiple defects. Phase correlation of camera images is used to track the relative position between transducer and sample to sub-pixel precision.

A naturally cracked aircraft stabilizer former has been examined. By using surface shear horizontal diagnostic acoustic waves and a multi-point detection approach, a fretting crack, 0.2-inch long, 0.03-inch deep and at 0.06-inch to a rivet hole has been clearly identified. The proposed approach provides a simple way to interpret sensor output without imposing demanding transducer performance requirements.

The Applied Physics group at the Pacific Northwest National Laboratory (PNNL) in Richland, WA has evaluated a method for waterless/liquidless coupling of ultrasonic energy from planar ultrasonic contact transducers to irregular test surfaces for ultrasonic non-destructive evaluation applications. Dry couplant material placed between a planar transducer face and a curved or uneven steel or plastic surface allows for effective sound energy coupling and preserves the integrity of the planar transducer sound field by serving as an acoustic impedance matching layer, providing good surface area contact between geometrically dissimilar surfaces and conforming to rough and unsmooth surfaces. Sound fields radiating from planar ultrasonic contact transducers coupled to curved and uneven surfaces using the dry coupling method were scanned and mapped using a Pinducer receiver connected to a raster scanner. Transducer sound field coverage at several ultrasonic frequencies and several distances from the transducer contact locations were found to be in good agreement with theoretical beam divergence and sound field coverage predictions for planar transducers coupled to simple, planar surfaces. This method is valuable for applications that do not allow for the use of traditional liquid-based ultrasonic couplants due to the sensitivity of the test materials to liquids and for applications that might otherwise require curved transducers or custom coupling wedges. The selection of dry coupling material is reported along with the results of theoretical sound field predictions, the laboratory testing apparatus and the empirical sound field data.

Machine parts often contain components which experience relative motion during service. Relative motion between surfaces causes fatigue crack, wear and eventual surface deterioration. Acoustic emission based machinery condition monitoring is a method which can potentially be used to monitor the state of damage present on surfaces during service. This research deals with changes that occur in the characteristics of acoustic emission signals due to altering surface roughness and texture caused by friction loading. A test fixture was used to simulate friction between surfaces of comparable surface finish and obtain acoustic emission signals generated in the process. The different characteristics of signal waveforms obtained at different instances during the test were examined. It was shown that some features like amplitude and duration of the waveforms are sensitive to surface wear.

Early damage detection of bridge has been an important issue for modern civil engineering technique. Existing bridge inspection techniques used by State Department of Transportation (DOT) and County DOT include visual inspection, mechanical sounding, rebound hammer, cover meter, electrical potential measurements, and ultrasonics; other NDE techniques include ground penetrating radar (GPR), radiography, and some experimental types of sensors. Radar technology like GPR has been widely used for the bridge structure detection with a good penetration depth using microwave energy. The system to be presented in this paper is a different type of microwave sensing technology. It is focus on the subsurface detection and trying to find out detail information at subsurface (10 cm) with high resolution radar imaging from a flexible standoff distance. Our radar operating frequency is from 8-12 GHz, which is different from most of the current GPR systems. Scanning array antenna system is designed for adjustable beamwidth, preferable scanning area, and low sidelobe level. From the theoretical analysis and experimental results, it is found that the proposed technique can successfully capture the presence of the near-surface anomaly. This system is part of our Multi- Modal Remote Sensing System (MRSS) and provides good imaging correlations with other MRSS sensors.

In this paper we present a new methodology for theoretical, numerical and experimental investigations of various 2D arrays' topologies. The theoretical evaluation is performed using frequency-dependent structure transfer function that affects propagation of Lamb waves (LWs) through the dispersive medium and enables investigation of the arrays' performance for a defined excitation signal. The numerical simulations are conducted using local interaction simulation approach (LISA) implemented on the NVIDIA R CUDA R graphical processing unit (GPU), which considerably accelerates 3D simulations of LWs propagation in a short time period. Finally, scanning laser vibrometer is used to sense the LWs excited by PZT transducers, in multiple points corresponding to the locations of the 2D array elements. In this way performance of various array architectures in the reception mode can be evaluated experimentally without the need of physical prototype - a change of topology requires only straightforward modification of the measurement points' distribution at the tested plate.

Early detection of corrosion can help reduce the cost of maintenance and extend the service life of structures. Acoustic emission (AE) sensing has proven to be a promising method for early detection of corrosion in reinforced concrete members. A test program is presented composed of four medium-scale prestressed concrete T-beams. Three of the beams have a length of 16 ft. 4 in. (4.98 m), and one is 9 ft. 8 in. (2.95 m). In order to corrode the specimens a 3% NaCl solution was prepared, which is representative of sea salt concentration. The beams were subjected to wet-dry cycles to accelerate the corrosion process. Two of the specimens were pre-cracked prior to conditioning in order to examine the effect of crack presence. AE data was recorded continuously while half-cell potential measurements and corrosion rate by Linear Polarization Resistance (LPR) were measured daily. Corrosion current was also being acquired constantly to monitor any change in the concrete resistivity. Results indicate that the onset of corrosion may be identified using AE features, and were corroborated with measurements obtained from electrochemical techniques. Corroded areas were located using source triangulation. The results indicate that cracked specimens showed corrosion activity prior to un-cracked specimens and experienced higher corrosion rates. The level of corrosion was determined using corrosion rate results. Intensity analysis was used to link the corrosion rate and level to AE data.

Antisymmetric flexural (ASF) modes are guided acoustic waves propagating along a wedge-shaped wave guide with their energy tightly confined near the tip. Motivated by the potential application of employing ASF modes in inspecting defects in machine tool blades with sharp edges, this study is focused in investigating the behaviors of ASF modes propagating along the wedge tips with defect. More specifically, we investigate the quantitative behaviors of ASF reflection and transmission while the ASF modes interact with a defect along a wedge tip. This investigation includes numerical simulations with finite element analysis and experimental measurements with a laser ultrasound technique. Defect parameters including depth and width are discussed regarding to their influences on the reflection coefficient (RC) and transmission coefficient (TC). The RC is found to increase as the ratio between the defect depth and the ASF wavelength increases, while the TC decreases.

A sound field beam mapping exercise was conducted to further understand the effects of coarse-grained microstructures found in cast austenitic stainless steel (CASS) materials on phased array ultrasonic wave propagation. Laboratory measurements were made on three CASS specimens with different microstructures; the specimens were polished and etched to reveal measurable grain sizes, shapes, and orientations. Three longitudinal, phased array probes were fixed on a specimen's outside diameter with the sound field directed toward one end (face) of the pipe segment over a fixed range of angles. A point receiver was raster scanned over the surface of the specimen face generating a sound field image. A slice of CASS material was then removed from the specimen end and the beam mapping exercise repeated. The sound fields acquired were analyzed for spot size, coherency, and beam redirection. Qualitative analyses were conducted between the resulting sound fields and the microstructural characteristics of each specimen.

As asphalt pavements age and deteriorate, recurring pothole repair failures and propagating alligator cracks in the asphalt pavements have become a serious issue to our daily life and resulted in high repairing costs for pavement and vehicles. To solve this urgent issue, pothole repair materials with superior durability and long service life are needed. In the present work, revolutionary pothole patching materials with high toughness, high fatigue resistance that are reinforced with nano-molecular resins have been developed to enhance their resistance to traffic loads and service life of repaired potholes. In particular, DCPD resin (dicyclopentadiene, C₁₀H₁₂) with a Rhuthinium-based catalyst is employed to develop controlled properties that are compatible with aggregates and asphalt binders. In this paper, a multi-level numerical micromechanics-based model is developed to predict the mechanical properties of these innovative nanomolecular resin reinforced pothole patching materials. Coarse aggregates in the finite element analysis are modeled as irregular shapes through image processing techniques and randomly-dispersed coated particles. The overall properties of asphalt mastic, which consists of fine aggregates, asphalt binder, cured DCPD and air voids are theoretically estimated by the homogenization technique of micromechanics. Numerical predictions are compared with suitably designed experimental laboratory results.

The potholes and alligator cracks in the asphalt pavement of our country's roadways have become an annoying part of our daily life. In order to reinstate and maintain our pavement infrastructure integrity and durability, we have identified dicyclopentadiene (DCPD) resin for this purpose due to its unique properties - low cost, low viscosity at beginning and ultra-toughness after curing, chemical compatibility with tar, tunable curing profile due to catalyst design. DCPD resin can penetrate into high porous pavement area to reinforce them and block water or moisture seeping channels. It also can strongly bond the pothole patches with original pavement, and hold them together for a whole. With the catalyst design, DCPD could apply for all the weather, cold or hot, wet or dry. In this paper, we will investigate the DCPD reinforcement for cold mix and hot mix for pothole repair, as well as the bonding strength improvement between repair materials and original pavement, and show that DCPD is promising materials for application in reinforced pothole patching materials.

Video health monitoring of large road networks requires the repeated collection of surface images to detect the defects and their changes over time. Vehicle mounted video equipment can easily collect the data, but the amount of data that can be collected in a single day prohibits interactive or semi-automated processing schemes as they would also not be cost-effective. A new approach that is fully automated to detect road surface defects from large amounts of highresolution grayscale images is presented. The images are collected with a vehicle-mounted rear-facing 5MP video camera complemented by GPS based positioning information. Our algorithm starts by correcting the images for radial and angular distortion to get a bird's-eye view image. This results in images with known dimensions (consistent in width per pixel) which allow data to be accurately placed on geo-referenced maps. Each of the pixels in the image is labeled as crack or non-crack using a Markov Random Field (MRF) approach. The data used for testing and training are disjoint sets of images collected from the streets of Boston, MA, USA. We compare our road surface defect detection results with other techniques/algorithms described in the literature for accuracy and robustness.

This work presents a method for assessing pavement surface condition using measurements from a microphone mounted underneath a moving vehicle. Such measurements will include tire-generated sound, which carries much information about the road condition, as well as noise generated by the wind and vehicle. The proposed method uses Principal Component Analysis (PCA) to extract the tire-generated sound from the noisy measurements. The analysis begins with acoustic pressure measurements made over constant and known road conditions. Fourier transforms are taken over various time windows and a PCA is performed over the resulting vectors, yielding to a set of principal component vectors for that road condition. Each road condition is characterized by a set of principal component vectors. These vector sets are used to analyze measurements from a road with unknown road conditions by finding the vector set that best represents the acoustic measurements from that road. Successful applications of this method are demonstrated by accurate estimations of the mean texture depth (MTD) of pavement directly from acoustic measurements.

This paper presents a real-time structural damage identification method for aircraft with flight condition variations. The proposed approach begins by identifying the dynamic models under various test conditions from time-domain input/output data. A singular value decomposition technique is then used to characterize and quantify the parameter uncertainties from the identified models. The uncertainty coordinates, corresponding to the identified principal directions, of the identified models are computed, and the residual errors between the identified uncertainty coordinates and the estimated uncertainty coordinates of the health structure are used to identify damage status. A correlation approach is applied to identify damage type and intensity, based on the difference between the identified parameters and the estimated parameters of the healthy structure. The proposed approach is demonstrated by application to the Benchmark Active Controls Technology (BACT) wind-tunnel model.

The aim of this paper is to present methods for enhancing damage visualization in structures based on wave propagation phenomenon. The method utilizes filtering and processing of full wavefield acquired by the laser vibrometer. Laser vibrometer allows to register full wavefield in elements of a structure instead of single point measurements acquired by e.g. piezoelectric sensor. In this way new possibilities for Nondestructive Evaluation arise enabling visualization of elastic waves interacting with various types of damages. Measurements obtained with a scanning laser vibrometer can be combined with effective signal and imaging processing algorithms to support damage identification. In this paper new method for wave filtering of propagating waves is tested on both numerical results and experimental data obtained from laser vibrometry measurements of composite plates. Processing of signals registered at a rectangular grid of measurement points covering inspected area of the plate involve 2D DFFT (Discrete Fast Fourier Transform), wavenumber filtering and inverse DFFT. As a result new damage index is proposed and compared with other methods like RMS and frequency-wavenumber filtering.

This paper reports the application of a non-linear impedance technique under a low-frequency vibration to detect structural defects of contact type such as fatigue crack. If the contact-type damage is developed within the structure due to the low-frequency dynamic load, the vibration can cause the fluctuation of structural impedance nonlinearly because of the contact acoustic nonlinearity (CAN). This nonlinear effect can lead to amplitude modulation and phase modulation of the current flow. The nonlinear characteristics of the structural impedance can be extracted by observing coupled electromechanical impedance of a piezoelectric active sensor and a nonlinear wave modulation spectroscopy. For experiment, a low-frequency vibration is applied to a notched coupon at a certain natural frequency by a shaker so that the nonlinear fatigue crack can be formed artificially at the notch tip. Then, the nonlinear features are extracted based on a self-sensing impedance measurement from a host structure under a low-frequency vibration. Damage metric is established based on the nonlinear fluctuation of the impedance due to the CAN.

Piezoelectric devices have gained popularity due to their low complexity, low mass and low cost as compared with other high temperature technologies. Despite these advantages, currently piezoelectric sensors for high temperatures are limited by the temperature limits of piezoelectric materials and electrodes to under 1000°C. During this study, a sensor capable of operating in temperatures up to 1250°C has been developed. The shear mode design is featured with low profile and insensitive to mass-loading effects. Because current electrode materials cannot withstand temperatures above 1000°C for an extended period, an electrode-less design was implemented. This sensor prototype was tested at temperatures ranging from room temperature to 1250°C in the frequency range of 100-300Hz, showing stable performance. In addition, when tested for an extended dwelling time, the accelerometer demonstrated very stable behavior once it reached a steady operation at 1250°C.

This paper describes an image processing algorithm in support of infrared based nondestructive testing. The algorithm aims at analyzing the raw thermal infrared images obtained by using the nondestructive evaluation method of the laser spot thermography. In the study presented in this paper, a laser was used to scan a test specimen through the generation of single pulses. The temperature distribution produced by this thermoelastic source was measured by an infrared camera and processed with a two-stage algorithm. In the first stage few statistical parameters were used to flag the presence of damage. In the second stage the images that revealed the presence of damage were processed computing the first and second spatial derivative. Two spatial filters were also used to enhance contrast, and to locate and size the defect. The algorithm was experimentally validated by scanning the surface of a CFRP and a GFRP composite plate with induced defects.

We used high-speed full-spectrum interrogation of a Fiber Bragg Grating (FBG) sensor to measure dynamic strain in different sensor packages in real-time. In this effort we performed solenoid impact tests on a variety of sensor mounting structures made with FR4, steel, and carbon fiber composite materials. Full spectrum FBG interrogation at 40 kHz repetition rate was the key that allowed us to measure and compare dynamic strain in the structures, with measurement resolution on the sub-millisecond scale. With this interrogation method we were able to measure the full character of the dynamic strain including the strain non-uniformity and distribution manifested in peak-splitting and spectrum broadening. Results showed that the FR4 board with soft epoxy responded with a maximum dynamic strain on the order of 3000 micro-strain. Adding hard materials such as steel and graphite fiber composite reduced the strain about 7 times. However, the FR4 board mounted in a free-floating configuration using hard epoxy reduced the maximum strain to a value below the noise threshold of the full spectrum interrogation configuration. Here we proposed using edge detection method of FBG interrogation due to its increased strain sensitivity which enabled us to further analyze the critical results obtained by full spectrum interrogation. We also proposed using edge detection to measure sensor strain in real time for the purpose of filtering out the strain noise from useful signal. We will use the results and data obtained with both methods to analyze and enhance the performance of our electric field sensors in environments of high static and dynamic strain.

Health monitoring of civil structures is a process that aims at diagnosing and localizing structural damages. It is typically conducted by visual inspections, therefore relying vastly on the monitoring frequency and individual judgement of the inspectors. The automation of the monitoring process would be greatly beneficial by increasing life expectancy of civil structures via timely maintenance, thus improving their sustainability. In this paper, we present a sensing method for automatically localizing strain over large surfaces. The sensor consists of several soft capacitors arranged in a matrix form, which can be applied over large areas. Local strains are converted into changes in capacitance among a soft capacitors matrix, permitting damage localization. The proposed sensing method has the fundamental advantage of being inexpensive to apply over large-scale surfaces. which allows local monitoring over large regions, analogous to a biological skin. In addition, its installation is simple, necessitating only limited surface preparation and deployable utilizing off-the-shelf epoxy. Here, we demonstrate the performance of the sensor at measuring static and dynamic strain, and discuss preliminary results from an application on a bridge located in Ames, IA. Results show that the proposed sensor is a promising health monitoring method for diagnosing and localizing strain on a large-scale surface.

Real-time monitoring of fracture critical steel bridges can potentially enhance inspection practices by tracking the behavior of the bridge. Significant advances have occurred in recent years on the development of robust hardware for field monitoring applications. These systems can monitor, process, and store data from a variety of sensors (e.g. strain gages, crack propagation gages etc.) to track changes in the behavior of the bridge. Thus, for a long-term monitoring system to be successful, the reliability of gages that are to be monitored for several years is very important. This paper focuses on the results of a research study focused on developing a wireless monitoring system with a useful life of more than 10 years. An important aspect of the study is to identify strain gages and installation procedures that result in long lives as well as characterizing the effect of temperature fluctuations and other environmental factors on the sensor drift and noise. In long-term monitoring applications, slight sensor drift and noise can build up over time to produce misleading results. Thus, a wide variety of gages that can be used to monitor bridges have been tested for over a year through environmental tests. The environmental tests were developed to determine the durability of the gages and their protective coatings (e.g. zinc-based spray, wax and silicon, etc.) against humidity, sun exposure and other environmental effects that are expected in long-term bridge monitoring applications. Moreover, fatigue tests were performed to determine the fatigue category of the weldable gages and to reveal any debonding issues of the bondable gages. This paper focuses on the results of laboratory tests on gage durability that were conducted as part of a research project sponsored by the National Institute of Standards and Technology (NIST).

Real-time, monitoring systems can enhance the bridge inspection process by providing data for estimating the health of the bridge and potentially notifying bridge owners of problems between inspection visits. A low-power, wireless, strain data acquisition device has recently been developed to acquire dynamic strain data. Strain gages can be used to monitor the number and size of stress cycles in fatigue-sensitive members. From the cycle count, Palmgren-Miner's rule can be used to determine an effective stress range. The remaining fatigue life can then be calculated and compared to existing conditions and the age of the bridge. Because damage is expected to escalate over time, more frequent inspections may be needed when a bridge approaches its fatigue life. The strain node can be programmed in LabVIEW WSN to detect critical events or perform a rainflow analysis. To aid in system interaction, a software interface will be designed to allow for automated processing and transmission of data to a cloud server, thereby allowing engineers and bridge owners to access the data from anywhere so as to make informed decisions when prioritizing inspections. This paper will present the development of the strain node and the software interface.

Early detection of fatigue crack-growth in steel structures is an ongoing challenge. Furthermore, characterization of the different stages of the fatigue lifecycle using NDE techniques is particularly difficult. AE systems have been shown to serve as early damage detection mechanisms in bridge structures. This technology, however, is fraught with noise problems and complex datasets that are difficult to interpret. This paper attempts to design and implement a data mining scheme that can classify raw AE datasets into discrete clusters using an improved variant of the popular k-means clustering algorithm. The datasets are then augmented with the class label found during clustering, and a series of rules are inferred using a C4.5 decision tree classification algorithm. An implementation of the data mining scheme is coded in MATLAB®, with data from PAC® AE systems as the input. In order to validate this procedure, data from a pencil lead break test with a concurrent noise source is fed into the data mining program. Classification using the decision tree is compared to manual classification of the pencil lead break hits. The resulting decision tree is then applied to a similar dataset in order to evaluate the generality of the resulting rule sets. Once validated, the data mining program is applied to data belonging to a steel fatigue crack-growth test. Results of this classification are discussed, and possible improvements to the data mining scheme are suggested.

The Acoustic Emission (AE) technique plays a progressively significant role in the field of non-destructive testing (NDT) especially in structural health monitoring (SHM). Acoustic emissions are commonly defined as transient elastic waves in a material caused by the of localized stress release. In using AE for structural diagnostics, noise has always been a potential barrier. AE can be produced from sources not related to material damage including traffic or friction. The major challenge is the differentiation of signals relevant to the purpose of the monitoring - such as crack growth in a member - from noise of various origins. This paper deals with noise discrimination and introduces a novel approach for noise interpretation in AE data. AE activities recorded in field and lab environments for concrete and steel specimens are investigated in this study. Approaches for clustering and separation of AE signals based on multiple features extracted from experimental data are presented.

The influence of mechanical noise in an AE testing still obscures its successful application in monitoring various structures and systems. While advances in pattern recognition algorithms are helpful to differentiate relevant data from captured noise, the algorithms fail if the characteristics of relevant data are unknown. The ability to accurately model elastic waves using numerical methods offer a potential to understanding of frequency content of elastic waves. However, the oscillatory nature of the wave equation requires fine meshing for a stable numerical approximation using classical finite element models. Considering the size of civil structures, numerical modeling of full scale geometry is not feasible. In this study, spectral element approach is implemented for modeling elastic waves in sub-scales. The transfer function of a typical piezoelectric sensor is taken into consideration for identifying the output signal detected by the AE sensor in relation to the input signal and the transfer function of the medium. The approach is demonstrated for 1D and 2D structures and compared with conventional finite element model using COMSOL Multiphysics program. The comparison includes numerical efficiencies and computation times of spectral element and classical finite element.

This paper discusses the development status of a self-powered wireless sensor node for steel and concrete bridges monitoring and prognosis. By the end of the third year in this four-year cross-disciplinary project, the 4-channel acoustic emission wireless node, developed by Mistras Group Inc, has already been deployed in concrete structures by the University of Miami. Also, extensive testing is underway with the node powered by structural vibration and wind energy harvesting modules developed by Virginia Tech. The development of diagnosis tools and models for bridge prognosis, which will be discussed in the paper, continues and the diagnosis tools are expected to be programmed in the node's AVR during the 4^th year of the project. The impact of this development extends beyond the area of bridge health monitoring into several fields, such as offshore oil platforms, composite components on military ships and race boats, combat deployable bridges and wind turbine blades. Some of these applications will also be discussed. This project was awarded to a joint venture formed by Mistras Group Inc, Virginia Tech, University of South Carolina and University of Miami by the National Institute of Standards and Technology through its Technology Innovation Program Grant #70NANB9H007.

The emergence of cost-effective sensing technologies has now enabled the use of dense arrays of sensors to monitor the behavior and condition of large-scale bridges. The continuous operation of dense networks of sensors presents a number of new challenges including how to manage such massive amounts of data that can be created by the system. This paper reports on the progress of the creation of cyberinfrastructure tools which hierarchically control networks of wireless sensors deployed in a long-span bridge. The internet-enabled cyberinfrastructure is centrally managed by a powerful database which controls the flow of data in the entire monitoring system architecture. A client-server model built upon the database provides both data-provider and system end-users with secured access to various levels of information of a bridge. In the system, information on bridge behavior (e.g., acceleration, strain, displacement) and environmental condition (e.g., wind speed, wind direction, temperature, humidity) are uploaded to the database from sensor networks installed in the bridge. Then, data interrogation services interface with the database via client APIs to autonomously process data. The current research effort focuses on an assessment of the scalability and long-term robustness of the proposed cyberinfrastructure framework that has been implemented along with a permanent wireless monitoring system on the New Carquinez (Alfred Zampa Memorial) Suspension Bridge in Vallejo, CA. Many data interrogation tools are under development using sensor data and bridge metadata (e.g., geometric details, material properties, etc.) Sample data interrogation clients including those for the detection of faulty sensors, automated modal parameter extraction.

Signal identification including noise filtering and reduction of acquired signals is needed to achieve efficient and accurate data interpretation for remote acoustic emission (AE) monitoring of in-service steel bridges. Noise filtering may ensure that genuine hits from crack growth are involved in the estimation of fatigue damage and remaining fatigue life. Reduction of the data quantity is desirable for the sensing system to conserve energy in the data transmission and processing procedures. Identification and categorization of acquired signals is a promising approach to effectively filter and reduce AE data in the application of bridge monitoring. In this study an investigation on waveform features (time domain and frequency domain) and relevant filters is carried out using the results from AE monitored fatigue tests. It is verified that duration-amplitude (D-A) filters are effective to discriminate against noise for results of steel fatigue tests. The study is helpful to find an appropriate AE data filtering protocol for field implementations.

Monitoring of fatigue cracking in bridges using a combined passive and active scheme has been approached by the authors. Passive Acoustic Emission (AE) monitoring has shown to be able to detect crack growth behavior by picking up the stress waves resulting from the breathing of cracks while active ultrasonic pulsing can quantitatively assess structural integrity by sensing out an interrogating pulse and receive the structural reflections from the discontinuity. In this paper, we present a comparative study of active and passive sensing with two types of transducers: (a) AE transducers, and (b) embeddable piezoelectric wafer active sensors (PWAS). The study was performed experimentally on steel plates. Both pristine and damaged (notched) conditions were considered. For active sensing, pitchcatch configuration was examined in which one transducer was the transmitter and another transducer acted as the receiver. The ping signal was generated by the AE hardware/software package AEwin. For passive sensing, 0.5-mm lead breaks were executed both on top and on the edge of the plate. The comparative nature of the study was achieved by having the AE and PWAS transducers placed on the same location but on the opposite sides of the plate. The paper presents the main findings of this study in terms of (a) signal strength; (b) signal-to-noise (S/N) ratio; (c) waveform clarity; (d) waveform Fourier spectrum contents and bandwidth; (e) capability to detect and localize AE source; (f) capability to detect and localize damage. The paper performs a critical discussion of the two sensing methodologies, conventional AE transducers vs. PWAS transducers.

The primary goal of Army Prognostics & Diagnostics is to develop real-time state awareness technologies for primary structural components. In fatigue-critical structural maintenance, the probabilistic structural risk assessment (PSRA) methodology for fatigue life management using conventional nondestructive investigation (NDI) has been developed based on the assumption of independent inspection outcomes. When using the emerging structural health monitoring (SHM) systems with in situ sensors, however, the independent assumption no longer holds, and the existing PSRA methodology must be modified. The major issues currently under investigation are how to properly address the correlated inspection outcomes from the same sensors on the same components and how to quantify its effect in the SHM-based PSRA framework. This paper describes a new SHM-based PSRA framework with a proper modeling of correlations among multiple inspection outcomes of the same structural component. The framework and the associated probabilistic algorithms are based on the principles of fatigue damage progression, NDI reliability assessment and structural reliability methods. The core of this framework is an innovative, computationally efficient, probabilistic method RPI (Recursive Probability Integration) for damage tolerance and risk-based maintenance planning. RPI can incorporate a wide range of uncertainties including material properties, repair quality, crack growth related parameters, loads, and probability of detection. The RPI algorithm for SHM application is derived in detail. The effects of correlation strength and inspection frequency on the overall probability of missing all detections are also studied and discussed.

This paper presents the implementation of the Finite Element (FE) model updating for a skewed highway bridge using real-time sensor data. The bridge under investigation is a I-275 crossing in Wayne County, Michigan. The bridge is instrumented with a wireless sensory system to collect the vibration response of the bridge under ambient vibrations. The dynamic characteristics of the bridge have been studied through the field measurements as well as a high-fidelity FE model of the bridge. The developed finite element model of the bridge is updated with the field measured response of the bridge so that the FE computed and field measured modal characteristics of the bridge match each other closely. A comprehensive sensitivity analysis was performed to determine the structural parameters of the FE model which affect the modal frequencies and modal shapes the most. A multivariable sensitivity-based objective function is constructed to minimize the error between the experimentally measured and the FE predicted modal characteristics. The selected objective function includes information about both modal frequencies and mode shapes of the bridge. An iterative approach has been undertaken to find the optimized structural parameters of the FE model which minimizes the selected objective function. Appropriate constraints and boundary conditions are used during the optimization process to prevent non-physical solutions. The final updated FE model of the bridge provides modal results which are very consistent with the experimentally measured modal characteristics.

Vehicle/structure interaction is extremely important in determining the structural performance of highway bridges. However, an accurate prediction of the generated vibrations and forces requires a high-fidelity nonlinear 3D model which is sufficiently representative of the actual vehicle and bridge structure. In spite of all the computational advancements, there are still many technical difficulties to obtain a converging solution from a coupled highly nonlinear and highly damped vehicle/structure models. This paper presents an iterative uncoupled approach to obtain an accurate estimation of the vehicle/structure interaction. The multi-axle vehicle is simulated using a nonlinear 3D multibody dynamics model. The bridge model also contains several nonlinear components to accurately model the bridge behavior. The vehicle/bridge interaction results are obtained through an iterative solution by exchanging the outputs of two uncoupled nonlinear models. A convergence criterion is selected to obtain a reliable solution after several of these iterations. Finally, a reduced-order model of the bridge is developed using a state-space model. The linear reduced-order model of the bridge is coupled with the nonlinear vehicle model to improve the solution time of the analysis. The results are in a very good agreement with the iterative uncoupled approach.

The United States is suffering from an aging civil infrastructure crisis. Key to recovery are rapid inspection technologies like that being investigated by the VOTERS project (Versatile Onboard Traffic Embedded Roaming Sensors), which aims to outfit ordinary road vehicles with compact low-cost hardware that enables them to rapidly assess and report the condition of roadways and bridge decks free of driver interaction. A key piece of hardware, and the focus of this paper, is a 24 GHz millimeter-wave radar system that measures the reflectivity of pavement surfaces. To account for the variability of real-world driving, such as changes in height, angle, speed, and temperature, a sensor fusion approach is used that corrects MWR measurements based on data from four additional sensors. The corrected MWR measurements are expected to be useful for various characterization applications, including: material type; deterioration such as cracks and potholes; and surface coverage conditions such as dry, wet, oil, water, and ice. Success at each of these applications is an important step towards achieving the VOTERS objective, however, this paper focuses on surface coverage, as whatever covers the driving surface will be most apparent to the MWR sensor and if not accounted for could significantly limit the accuracy of other applications. Contributions of the paper include findings from static lab tests, which validate the approach and show the effects of height and angle. Further contributions come from lab and in-field dynamic tests, which show the effects of speed and demonstrate that the MWR approach is accurate under city driving conditions.

Reinforced concrete marine structures are highly vulnerable to corrosion due to chloride ion attack; the severity of the attack being dependent on, among other factors, the prevailing climatic condition. The aggressiveness of the warm marine environment of Florida has led to the premature deterioration of numerous bridges and building along the coastline. This paper describes a methodology for structural assessment of concrete bridges while incorporating analysis uncertainty. The procedure includes the use of visual, electrochemical and non-destructive methods in order to define the cause and the level of concrete deterioration. A probabilistic mechanistic model is used to generate the distribution of the time to corrosion initiation based on statistical models of the governing parameters obtained from field data. The proposed methodology is applied to predict the time to corrosion initiation and predict the residual service life of the reinforcing steel in the concrete girders of the Geiger Bridge in Key West, FL.

A self-deicing road system consisting of a carbon nano-fiber polymer (CNFP) thermal source, an AlN-ceramic insulated encapsulation layer, a multiwall carbon nanotube (MWCNT)/cement-based thermal conduction layer and a thermally insulated substrate was proposed in this study. The effects of ambient temperature, heat flux density and ice thickness on the deicing of the self-deicing system were investigated in chilled. The efficiency, repeatability, cost and feasibility of the self-deicing road system in both deicing and snow-melting applications were analyzed. Indices for evaluating the deicing or snow-melting performance of the self-deicing road system were adopted in this study.

Highway bridges are vital links in the transportation network in the United States. Identifying possible safety problems in the approximately 600,000 bridges across the country is generally accomplished through labor-intensive, visual inspections. Ongoing research sponsored by NIST seeks to improve inspection practices by providing real-time, continuous monitoring technology for steel bridges. A wireless sensor network with a service life of ten years that is powered by an integrated energy harvester is targeted. In order to achieve the target ten-year life for the monitoring system, novel approaches to energy harvesting for use in recharging batteries are investigated. Three main sources of energy are evaluated: (a) vibrational energy, (b) solar energy, and (c) wind energy. Assessing the energy produced from vehicular-induced vibrations and converted through electromagnetic induction is the focus of this paper. The goal of the study is to process acceleration data and analyze the vibrational response of steel bridges to moving truck loads. Through spectral analysis and harvester modeling, the feasibility of vibration-based energy harvesting for longterm monitoring can be assessed. The effects of bridge conditions, ambient temperature, truck traffic patterns, and harvester position on the power content of the vibrations are investigated. With sensor nodes continually recharged, the proposed real-time monitoring system will operate off the power grid, thus reducing life cycle costs and enhancing inspection practices for state DOTs. This paper will present the results of estimating the vibration energy of a steel bridge in Texas.

Acoustic emission (AE) technique is an effective method in the nondestructive testing (NDT) field of civil engineering. During the last two decades, Fiber reinforced polymer (FRP) has been widely used in repairing and strengthening concrete structures. The damage state of FRP strengthened concrete structures has become an important issue during the service period of the structure and it is a meaningful work to use AE technique as a nondestructive method to assess its damage state. The present study reports AE monitoring results of axial compression tests carried on basalt fiber reinforced polymer (BFRP) confined concrete columns and three-point-bending tests carried on BFRP reinforced concrete beams. AE parameters analysis was firstly utilized to give preliminary results of the concrete fracture process of these specimens. It was found that cumulative AE events can reflect the fracture development trend of both BFRP confined concrete columns and BFRP strengthened concrete beams and AE events had an abrupt increase at the point of BFRP breakage. Then the fracture process of BFRP confined concrete columns and BFRP strengthened concrete beams was studied through RA value-average frequency analysis. The RA value-average frequency tendencies of BFRP confined concrete were found different from that of BFRP strengthened concrete beams. The variation tendency of concrete crack patterns during the loading process was revealed.

Asce's survey shows that 80%--90% bridge damage were associated with fatigue and fracture problems. With the operation of vehicle weight and traffic volume increases constantly, the fatigue of welded steel bridge is becoming more and more serious in recent years. A large number of studies show that most prone to fatigue damage of steel bridge is part of the welding position. Thus, it's important to find a more precise method to assess the fatigue life of steel bridge. Three kinds of fatigue analysis method is commonly used in engineering practice, such as nominal stress method, the local stress strain method and field intensity method. The first two methods frequently used for fatigue life assessment of steel bridge, but field intensity method uses less ,and it widely used in fatigue life assessment of aerospace and mechanical. Nominal stress method and the local stress strain method in engineering has been widely applied, but not considering stress gradient and multiaxial stress effects, the accuracy of calculation stability is relatively poor, so it's difficult to fully explain the fatigue damage mechanism. Therefore, it used strain field intensity method to evaluate the fatigue life of steel bridge. The fatigue life research of the steel bridge based on the strain field method and the fatigue life of the I-section plate girder was analyzed. Using Ansys on the elastoplastic finite element analysis determined the dangerous part of the structure and got the stress-strain history of the dangerous point. At the same time, in order to divide the unit more elaborate introduced the sub-structure technology. Finally, it applies K.N. Smith damage equation to calculate the fatigue life of the dangerous point. In order to better simulating the actual welding defects, it dug a small hole in the welding parts. It dug different holds from different view in the welding parts and plused the same load to calculate its fatigue life. Comparing the results found that the welding defect in different parts had different influence on the fatigue life. Simultaneously, it based on S-N curve the I-shaped beam and combined with Palmgren - Miner linear cumulative damage theory to calculate the fatigue life of the dangerous part. The corresponding calculation results proved the superiority of the strain field intensity method.

This paper summarizes ongoing work on applying passive magneto-inductive (MI) waveguides as wireless sensor arrays to monitor corrosion in infrastructure systems. The passive uniformly-spaced sensor array provides a low-cost and quick method to detect the onset of corrosion in concrete structures using a noninvasive approach. The embedded sensors communicate with neighboring sensors through inductive coupling. The corrosion information is interpreted based on both frequency and time domain characteristics. Bandpass characteristics in the frequency domain and received reflected time domain waves are investigated to locate the defects along the wireless sensor array. Using the relationship between the relative positions of defects and MI waveguide performances, a new combined technique to determine location of defects has been developed and proven to provide both improved sensitivity and defect location capability.

Designing an attachment structure that is both novel and meets the system requirements can be a difficult task especially for inexperienced designers. This paper presents a design methodology for concept generation of a "parent/child" attachment system. The "child" is broadly defined as any device, part, or subsystem that will attach to any existing system, part, or device called the "parent." An inductive research process was used to study a variety of products, patents, and biological examples that exemplified the parent/child system. Common traits among these products were found and categorized as attachment principles in three different domains: mechanical, material, and field. The attachment principles within the mechanical domain and accompanying examples are the focus of this paper. As an example of the method, a case study of generating concepts for a bridge mounted wind energy harvester using the mechanical attachment principles derived from the methodology and TRIZ principles derived from Altshuller's matrix of contradictions is presented.

A health monitoring approach is investigated for hydrokinetic turbine blade applications. In-service monitoring is critical due to the difficult environment for blade inspection and the cost of inspection downtime. Composite blade designs have advantages that include long life in marine environments and great control over mechanical properties. Experimental strain characteristics are determined for static loads and free-vibration loads. These experiments are designed to simulate the dynamic characteristics of hydrokinetic turbine blades. Carbon/epoxy symmetric composite laminates are manufactured using an autoclave process. Four-layer composite beams, eight-layer composite beams, and two-dimensional eight-layer composite blades are instrumented for strain. Experimental results for strain measurements from electrical resistance gages are validated with theoretical characteristics obtained from in-house finite-element analysis for all sample cases. These preliminary tests on the composite samples show good correlation between experimental and finite-element strain results. A health monitoring system is proposed in which damage to a composite structure, e.g. delamination and fiber breakage, causes changes in the strain signature behavior. The system is based on embedded strain sensors and embedded motes in which strain information is demodulated for wireless transmission.

An image processing approach is investigated which has low computational complexity and which uses nearinfrared imaging. The target application is a surveillance system for pedestrian traffic. Near-infrared light has potential benefits including non-visible illumination requirements. An image-processing algorithm for monitoring pedestrians is implemented in outdoor and indoor environments with frequent traffic. The image sets consist of persons walking in the presence of foreground as well as background objects at different times during the day. The complex, cluttered environments are highly variable, e.g. shadows and moving foliage. The approach consists of thresholding an image and creating a silhouette of selected objects in the scene. Filtering is used to eliminate noise. The computational results using MATLAB© show that the algorithm can effectively manipulate near-infrared images and that effective filtering is possible even in the presence of system noise and environmental clutter. The potential for automated surveillance based on near-infrared imaging and neural-network based feature processing is discussed.

A surveillance-centric video compression algorithm is discussed that exploits a background model, motion estimation, truncated difference correction, and entropy encoding. The algorithm's architecture allows tradeoffs between image quality and compression to target regions of salient activity. A set of window-based filters and heat diffusion PDEs is examined for impact on compression ratio and signal quality. Results show that filtering techniques are effective at reducing certain contributions to the data stream with minimal impact on image quality. Results from other compression codecs are included for comparison. The test set comprises a diverse range of surveillance scenes featuring vehicular and pedestrian traffic.

Sensor networks have various communication and security architectural concerns. Three approaches are defined to address these concerns for sensor networks. The first area is the utilization of new computing architectures that leverage embedded virtualization software on the sensor. Deploying a small, embedded virtualization operating system on the sensor nodes that is designed to communicate to low-cost cloud computing infrastructure in the network is the foundation to delivering low-cost, secure sensor networks. The second area focuses on securing the sensor. Sensor security components include developing an identification scheme, and leveraging authentication algorithms and protocols that address security assurance within the physical, communication network, and application layers. This function will primarily be accomplished through encrypting the communication channel and integrating sensor network firewall and intrusion detection/prevention components to the sensor network architecture. Hence, sensor networks will be able to maintain high levels of security. The third area addresses the real-time and high priority nature of the data that sensor networks collect. This function requires that a quality-of-service (QoS) definition and algorithm be developed for delivering the right data at the right time. A hybrid architecture is proposed that combines software and hardware features to handle network traffic with diverse QoS requirements.

Authors had developed an image reconstruction algorithm that can accurately reconstruct images of flaws from data obtained using conventional ECT sensors few years ago. The developed reconstruction algorithm is designed for data which is assumed to be obtained with spatial uniform magnetic field on the target surface. On the other hand, the conventional ECT sensor author used is designed in such a manner that when the magnetic field is imposed on the target surface, the strength of the magnetic field is maximized. This violation of the assumption ruins the algorithm simplicity because it needs to employ complemental response functions called"LSF"for long line flaw which is not along original algorithm design.In order to obtain an experimental result which proves the validity of original algorithm with only one response function, the authors have developed a prototype sensor for magnetic flux leakage testing that satisfy the requirement of original algorithm last year. The developed sensor comprises a GMR magnetic field sensor to detect a static magnetic field and two magnets adjacent to the GMR sensor to magnetize the target specimen. However, obtained data had insufficient accuracy due to weakness of the strength of the magnet. Therefore author redesigned it with much stronger magnet this year. Obtained data with this new sensor shows that the algorithm is most likely to work well with only one response function for this type probe.

Currently, the United States has over 3.5 million⁴ linear feet of large diameter water pipes failing prematurely. Methods of pipe repair generally involve very intrusive excavation and replacement of existing pipe sections that can be slow, detrimental to society, and in a lot of cases impossible. A novel new approach of repair is under development that utilizes the latest technology in automated robotics to effectively retrofit the pipes with carbon fiber. By utilizing this technology, many of the problems associated with existing repair methods can be mitigated.

Multi-function sensing and imaging devices, GPS, communication and computing devices are being ubiquitously used in field by engineers in civil engineering and emergence response practice. Field engineers, however, still have difficulty to balance between ever-increasing data collection demand and capacity of real-time data processing and knowledge sharing. In addition, field engineers usually work collaboratively in a geospatially large area; however, the existing sensing and computing modalities used in the field are not designed to accommodate this condition. In this paper, we present a solution framework of collaborative mobile sensing and computing (CMSC) for civil infrastructure condition assessment, with the Android-based mobile devices as the basic nodes in the framework with a potential of adding other auxiliary imaging and sensing devices into the network. Difficulties in mixed C++ and Java code programming that are critical to realize the framework are discussed. With a few prototypes illustrated in this paper, we envisage that the proposed CMSC framework will enable seamless integration of sensing, imaging, real-time processing and knowledge discovery in future engineers-centered field reconnaissances and civil infrastructure condition assessment.

The paper presents a method for investigating the stress-induced changes in ultrasonic wave speeds at room temperature in rail steel. The pulse echo method is used to measure the wave speed accurately. All of the second-order and thirdorder elastic constants are calculated from the measured acoustoelastic data. A comparison of the strain-induced elastic constant at room temperature is also conducted with previous measurement results.