This PDF file contains the front matter associated with SPIE Proceedings Volume 10169, including the Title Page, Copyright information, Table of Contents, Introduction, and Conference Committee listing.

Electromagnetic imaging enables researchers and engineers to assess the surface and subsurface condition of concrete structures using radar and microwave sensors. Among existing radar imaging methods, synthetic aperture radar (SAR) imaging offers flexible resolution for various purposes in condition assessment. In this paper, two novel SAR image processing techniques are reported for the subsurface condition assessment of FRP(fiber reinforced polymer)-strengthened concrete systems; mathematical morphology (MM) and the K-R-I transform. Glass FRP (GFRP) and carbon CFRP (CFRP) strengthened concrete cylinders are used as examples. From our experimental results, it is found that both techniques are capable of quantifying SAR images for condition assessment. It is also found that Euler’s number and the coefficient of correlation of K-R-I curves of SAR images can be used for monitoring subsurface changes in FRP-concrete systems.

Fiber Reinforced Polymer or Plastic (FRP) composites have been rapidly increasing in the aerospace, automotive and marine industry, and civil engineering, because these composites show superior characteristics such as outstanding strength and stiffness, low weight, as well as anti-corrosion and easy production. Generally, the advancement of materials calls for correspondingly advanced methods and technologies for inspection and failure detection during production or maintenance, especially in the area of nondestructive testing (NDT). Among numerous inspection techniques, microwave sensing methods can be effectively used for NDT of FRP composites. FRP composite materials can be produced using various structures and materials, and various defects or flaws occur due to environmental conditions encountered during operation. However, reliable, low-cost, and easy-to-operate NDT methods have not been developed and tested. FRP composites are usually produced as multilayered structures consisting of fiber plate, matrix and core. Therefore, typical defects appearing in FRP composites are disbondings, delaminations, object inclusions, and certain kinds of barely visible impact damages. In this paper, we propose a microwave NDT method, based on synthetic aperture radar (SAR) imaging algorithms, for stand-off imaging of internal delaminations. When a microwave signal is incident on a multilayer dielectric material, the reflected signal provides a good response to interfaces and transverse cracks. An electromagnetic wave model is introduced to delineate interface widths or defect depths from the reflected waves. For the purpose of numerical analysis and simulation, multilayered composite samples with various artificial defects are assumed, and their SAR images are obtained and analyzed using a variety of high-resolution wideband waveforms.

This paper explores a low-rank and sparse representation based technique to remove the clutter produced by rough ground surface for air-coupled ground penetrating radar (GPR). For rough ground surface, the surface clutter components in different A-Scan traces are not aligned on the depth axis. To compensate for the misalignment effect and facilitate clutter removal, the A-Scan traces are aligned using cross-correlation technique first. Then the low-rank and sparse representation approach is applied to decompose the GPR data into a low-rank matrix whose columns record the ground clutter in A-Scan traces upon alignment adjustment, and a sparse matrix that features the subsurface object under test. The effectiveness of the proposed clutter removal method has been evaluated through simulations.

The lack of validated nondestructive evaluation (NDE) techniques for examination during and after additive manufacturing (AM) component fabrication is one of the obstacles in the way of broadening use of AM for critical applications. Knowledge of electromagnetic properties of powder (e.g. feedstock) and solid AM metal components is necessary to evaluate and deploy electromagnetic NDE modalities for examination of AM components. The objective of this research study was to develop and implement techniques for measurement of powder and solid metal electromagnetic properties. Three materials were selected - Inconel 625, duplex stainless steel 2205, and carbon steel 4140. The powder properties were measured with alternate current (AC) model based eddy current technique and direct current (DC) resistivity measurements. The solid metal properties were measured with DC resistivity measurements, DC magnetic techniques, and AC model based eddy current technique. Initial magnetic permeability and electrical conductivity were acquired for both powder and solid metal. Additional magnetic properties such as maximum permeability, coercivity, retentivity, and others were acquired for 2205 and 4140. Two groups of specimens were tested along the build length and width respectively to investigate for possible anisotropy. There was no significant difference or anisotropy when comparing measurements acquired along build length to those along the width. A trend in AC measurements might be associated with build geometry. Powder electrical conductivity was very low and difficult to estimate reliably with techniques used in the study. The agreement between various techniques was very good where adequate comparison was possible.

Ground penetrating radar (GPR) has been shown to be an effective device for detecting buried objects that have little or no metal content, such as plastic, ceramic, and concrete pipes. In this paper, buried non-metallic object detection is evaluated for different antenna elevation angles and heights using a bistatic air-launched GPR. Due to the large standoff distance between antennas and the ground surface, the air-launched GPR has larger spreading loss than the hand-held GPR and vehicle-mounted GPR. Moreover, nonmetallic objects may have similar dielectric property to the buried medium, which results in further difficulty for accurate detection using air-launched GPR. To study such effects, both GPR simulations and GPR laboratory experiments are performed with various setups where antennas are placed at different heights and angles. In the experiments, the test surface areas are configured with and without rocks in order to examine surface clutter effect. The experimental results evaluate the feasibility and effectiveness of bistatic air-launched GPR for detecting buried nonmetallic objects, which provide valuable insights for subsurface scanning with unmanned aerial vehicle (UAV) mounted GPR.

Civil engineering structures such as bridges, buildings, and tunnels continue to be used despite aging and deterioration well past their design life. In 2013, the American Society of Civil Engineers (ASCE) rated the state of the U.S. bridges as mediocre, despite the $12.8 billion USD annually invested. Traditional inspection and monitoring techniques may produce inconsistent results, are labor intensive and too time-consuming to be considered effective for large-scale monitoring. Therefore, new structural health monitoring systems must be developed that are automated, highly accurate, minimally invasive, and cost effective. Three-dimensional (3D) digital image correlation (DIC) systems possess the capability of extracting full-field strain, displacement, and geometry profiles. Furthermore, as this measurement technique is implemented within an Unmanned Aerial Vehicle (UAV) the capability to expedite the optical-based measurement process is increased as well as the infrastructure downtime being reduced. These resulting integrity maps of the structure of interest can be easily interpreted by trained personal. Within this paper, the feasibility of performing DIC measurements using a pair of cameras installed on a UAV is shown. Performance is validated with in-flight measurements. Also, full-field displacement monitoring, 3D measurement stitching, and 3D point-tracking techniques are employed in conjunction with 3D mapping and data management software. The results of these experiments show that the combination of autonomous flight with 3D DIC and other non-contact measurement systems provides a highly valuable and effective civil inspection platform.

Unmanned aerial vehicles (UAVs) play increasing roles in structure health monitoring. With growing mobility in modern Internet-of-Things (IoT) applications, the health monitoring of mobile structures becomes an emerging application. In this paper, we develop a UAV-carried vision-based monitoring system that allows a UAV to continuously track and monitor a mobile infrastructure and transmit back the monitoring information in real- time from a remote location. The monitoring system uses a simple UAV-mounted camera and requires only a single feature located on the mobile infrastructure for target detection and tracking. The computation-effective vision-based tracking solution based on a single feature is an improvement over existing vision-based lead-follower tracking systems that either have poor tracking performance due to the use of a single feature, or have improved tracking performance at a cost of the usage of multiple features. In addition, a UAV-carried aerial networking infrastructure using directional antennas is used to enable robust real-time transmission of monitoring video streams over a long distance. Automatic heading control is used to self-align headings of directional antennas to enable robust communication in mobility. Compared to existing omni-communication systems, the directional communication solution significantly increases the operation range of remote monitoring systems. In this paper, we develop the integrated modeling framework of camera and mobile platforms, design the tracking algorithm, develop a testbed of UAVs and mobile platforms, and evaluate system performance through both simulation studies and field tests.

It has been a long research and engineering pursuit to create lightweight and mechanically robust and energy efficient materials with interconnected porosity. These cellular materials are desirable for a broad range of applications including structural components, lightweight transportation, heat exchange, catalyst supports, battery electrodes and biomaterials. However, the required outstanding properties have remained elusive on lightweight materials (<10kg/m3), constrained by the inherent coupling of material properties and the lack of suitable processes to generate these artificial materials. For example, graphene aerogels have among the lowest record densities ~1kg/m^3, but their strength have been degraded to tens to hundreds of Pascal (<10^-8 of that of carbon nanotubes). The attainment of low density has come with a price --- significant reduction of bulk scale properties. We present the design, manufacturing and defect tolerance study of a new class of ultralight, three-dimensional multi-functional architected materials. These 3D bulk metamaterials (polymer, metal, ceramic and combinations thereof) possess weight density comparable to that of carbon aerogel, but with over 10^4 higher stiffness and strength. By designing and studying their hierarchical architectures, material compositions and feature sizes spanning multiple length-scales, we create a wide range of decoupled material properties such as programmable stiffness, tunable strength and fracture toughness as well as programmable possion ratio. With the possibility of incorporating precise control of topological architectures across length-scale sets as well as prediction and optimization of their defect tolerance, we enter into a paradigm where nanoscale material properties can be harnessed and made accessible in large scale objects, opening a wide range of applications of these materials in energy, health care and flexible electronics.

Aluminum alloys have been the dominant materials for aerospace construction in the past fifty years due to their light weight, forming and alloying, and relative low cost in comparison to titanium and composites. However, in recent years, carbon fiber reinforced polymers (CFRPs) and honeycomb materials have been used in aircrafts in the quest to attain lower weight, high temperature resistance, and better fuel efficiency. When these two materials are coupled together, the structural strength of the aircraft is unparalleled, but this comes at a price, namely galvanic corrosion. Previous experimental results have shown that when CFRP composite materials are joined with high strength aluminum alloys (AA7075-T6 or AA2024-T3), galvanic corrosion occurs at the material interfaces, and the aluminum is in greater danger of corroding, particularly since carbon and aluminum are on the opposite ends of the galvanic series. In this paper, we explore the occurrence of the recognizable precursors of galvanic corrosion when CFRP plate is coupled to an aluminum alloy using SS-304 bolts and exposed to environmental degradation, which creates significant concerns for aircraft structural reliability. The galvanic corrosion software package, BEASY, is used to simulate the growth of corrosion in the designed specimen after which a microwave non-destructive testing (NDT) technique is explored to detect corrosion defects that appear at the interface of this galvanic couple. This paper also explores a loaded waveguide technique to determine the dielectric constant of the final corrosion product at the Q-band millimeter-wave frequency range (33-50 GHz), as this can be an invaluable asset in developing early detection strategies.

Inflatable structures for space habitat are highly prone to damage caused by micrometeoroid and orbital debris impacts. Although the structures are effectively shielded against these impacts through multiple layers of impact resistant materials, there is a necessity for a health monitoring system to monitor the structural integrity and damage state within the structures. Assessment of damage is critical for the safety of personnel in the space habitat, as well as predicting the repair needs and the remaining useful life of the habitat. In this paper, we propose a unique impact detection and health monitoring system based on hybrid nanocomposite sensors. The sensors are composed of two fillers, carbon nanotubes and coarse graphene platelets with an epoxy matrix material. The electrical conductivity of these flexible nanocomposite sensors is highly sensitive to strains as well as presence of any holes and damage in the structure. The sensitivity of the sensors to the presence of 3mm holes due to an event of impact is evaluated using four point probe electrical resistivity measurements. An array of these sensors when sandwiched between soft good layers in a space habitat can act as a damage detection layer for inflatable structures. An algorithm is developed to determine the event of impact, its severity and location on the sensing layer for active health monitoring.

Track defects are a major safety concern for the railroad industry. Among different track components, insulated rail joints, which are widely used for signaling purposes, are considered a weak link in the railroad track. Several joint-related defects have been identified by the railroad community, including rail wear, torque loss, and joint bar breakage. Current track inspection techniques rely on manual and visual inspection or on specially equipped testing carts, which are costly, timeconsuming, traffic disturbing, and prone to human error. To overcome the aforementioned limitations, the feasibility of utilizing impedance-based structural health monitoring for insulated rail joints is investigated in this work. For this purpose, an insulated joint, provided by Koppers Inc., is instrumented with piezoelectric transducers and assembled with 136 AREA rail plugs. The instrumented joint is then installed and tested at the Facility for Accelerated Service Testing, Transportation Technology Center Inc. The effects of environmental and operating conditions on the measured impedance signatures are investigated through a set of experiments conducted at different temperatures and loading conditions. The capabilities of impedance-based SHM to detect several joint-related damage types are also studied by introducing reversible mechanical defects to different joint components.

Carbon nanotube (CNT)-embedded polymer solution can be inkjet-printed into a thin sheet consisting uniform morphology and consistent electrical properties. When subjected to a loading scheme, the thin film’s inherent electrical property changes in tandem with the deformation. This unique property makes CNT thin films the appropriate candidate for strain sensing applications. Recent studies on characterizing the gage factor of CNT-embedded thin films are limited to learning the materials resistance change along the loading direction only. However, research interests on strain measurement of a structure have shifted from point-based interrogation to spatial strain-state monitoring. In this study an attempt to characterize its anisotropic resistivity was carried out. The resistivity-strain constitutional relation of an inkjet-printed CNT thin film is established based on theories for semi-conductive materials. The 2D elastoresistivity properties were characterized via the Montgomery method. It is observed that the change in resistivity in both directions are exhibiting linear trend to their strains in the same direction, but the thin film is more sensitive toward compressive strains. The final result of this study has inspired future research on fully characterizing the thin film’s elastoresistivity under different loading situations, and the way to characterize shear elastoresistivity shall also be reconsidered.

In fiber reinforced composite materials, the modes of damage accumulation, ranging from microlevel to macro-level (matrix cracks development, fiber breakage, fiber-matrix de-bonding, delamination, etc.), are complex and hard to be detected through conventional non-destructive evaluation methods. Therefore, in order to assure the outstanding structural performance and high durability of the composites, there has been an urgent need for the design and fabrication smart composites with self-damage sensing capabilities. In recent years, the macroscopic forms of carbon nanotube materials have been maturely investigated, which provides the opportunity for structural health monitoring based on the carbon nanotubes that are integrated in the inter-laminar areas of advanced fiber composites. Here in this research, advanced fiber composites embedded with laminated carbon nanotube layers are manufactured for damage detection due to the relevant spatial electrical property changes once damage occurs. The mechanical-electrical coupling response is recorded and analyzed during impact test. The design and manufacturing of integrating the carbon nanotubes intensely affect the detecting sensitivity and repeatability of the integrated multifunctional sensors. The ultimate goal of the reported work is to develop a novel structural health monitoring method with the capability of reporting information on the damage state in a real-time way.

A new online resistance spot weld non-destructive evaluation (NDE) technique based on infrared (IR) thermography has been developed. It is capable of both real-time online (during welding) and post-weld online/offline (after welding) inspections. The system mainly consists of an IR camera and a computer program with proprietary thermal imaging analysis algorithms integrated into existing production lines. For real-time inspection, the heat flow generated from the welding process (with temperature exceeding 1000°C) is monitored by the IR camera. For post-weld inspection, a novel auxiliary heating device is applied to locally heat the weld region, resulting in temperature changes on the order of 10°C, and the transmitted heat flow is monitored. Unlike the conventional IR NDE method that requires surface coating to reduce the influence of unknown emissivity, the new method can be applied on as-is bare metal surface thanks to the unique “thermal signatures” extracted from infrared thermal images, which positively correlates to weld quality with a high degree of confidence. The new method can be used to reliably detect weld size, surface indents and defects such as cold weld with sufficient accuracy for welds made from various combinations of materials, thickness, stack-up configuration, surface coating conditions and welding conditions.

Carbon fiber composites experience sudden, catastrophic failure when exposed to sufficient stress levels and provide no obvious visual indication of damage before they fail. With the commercial adoption of these high-performance composites in structural applications, a need for in-situ monitoring of their structural integrity is paramount. Therefore, ways in which to monitor these systems has gathered research interest. A common method for accomplishing this is measuring through-thickness resistance changes of the composite due to the fact that carbon fiber composites are electrically conductive. This provides information on whole-body stress levels imparted on the composite and can help identify the presence of damage. However, this technique relies on the carbon fiber and polymer matrix to reveal a resistance change. Here, an approach is developed that increases damage detection sensitivity. This is achieved by developing a facile synthesis method of integrating semiconducting nanomaterials, such as silicon carbide, into carbon fiber sizing. The piezoresistive effect exhibited by these nanomaterials provides more pronounced resistance changes in response to mechanical stress as compared to carbon fiber alone. This is investigated through fabricating a unidirectional composite and subsequently monitoring the electrical resistance during mechanical testing. By establishing this route for integrating nanomaterials into carbon fiber composites, various nanomaterials can see future composite integration to realize novel properties.

Two-stage aluminum conductor steel-reinforced (ACSR) compression connectors are extensively used in US overhead transmission lines. The connectors are made by crimping a steel sleeve onto a steel core and an aluminum sleeve over electrical conducting aluminum strands. The connectors are designed to operate at temperatures up to 125°C, but their performance is increasingly degrading because of overloading of lines. Currently, electric utilities conduct routine line inspections using thermal and electrical measurements, but these methods do not provide information about the structural integrity of connectors.

In this work, structural health monitoring (SHM) of compression connectors was studied using electromechanical impedance (EMI) analysis. Lead zirconate titanate (PZT)-5A was identified as a smart material for SHM. A flexible high-temperature bonding layer was used to address challenges in PZT integration due to a significant difference in the coefficients of thermal expansion of PZT and the aluminum substrate. The steel joint on the steel core was investigated because it is responsible for the ultimate tensile strength of the connector. Tensile testing was used to induce structural damage to the joint, or steel core pullout, and thermal cycling introduced additional structural perturbations. EMI measurements were conducted between the tests. The root mean square deviation (RMSD) of EMI was identified as a damage index. The use of steel joints has been shown to enable SHM under simulated conditions. The EMI signature is sensitive to variations in structural conditions. RMSD can be correlated to the structural health of a connector and has potential for use in the SHM and structural integrity evaluation.

The use of concrete structures has made its long-term performance crucial for the safe operation of commercial nuclear power plants (NPPs), especially with license period extensions to sixty years and possibly beyond. Unlike most metallic materials, reinforced concrete used in NPPs is a heterogeneous material, a composite with a low-density matrix, a mixture of cement, sand, aggregate and water, and a high-density reinforcement, made up of steel rebar or tendons. This structural complexity makes nondestructive evaluation (NDE) a challenging task. While the standard Synthetic Aperture Focusing Technique (SAFT) is adequate for many defects with shallow concrete cover, some defects that are located under deep concrete cover are not easily identified using the standard SAFT techniques. For many degradation mechanisms, particularly defects under deep cover, the use of advanced signal processing techniques is required. A variety of test specimens were evaluated using several advanced signal processing techniques ranging from a large specimen representative of a NPP containment wall (2.134 m x 2.134 m x 1.016 m) with twenty embedded defects, to specimens with accelerated alkali-silica reaction (ASR), and specimens with freeze-thaw damage. The first technique examined in this paper generates frequency banded SAFT reconstructions using wavelet packet decomposition and reconstruction. While the frequency banded SAFT reconstructions show a vast improvement over the standard SAFT for defects under deep cover, a second technique, Model Based Iterative Reconstruction (MBIR), has been initiated to address the limitations of the frequency banded SAFT (such as multiple reflections for a single defect).

Additive Manufacturing provides the opportunity to fabricate components of nearly limitless complexity compared to that of traditional manufacturing techniques. However, thermal gyrations imparted into the material from the passing of the heat source cause challenges in fabricating complex structures with the proper process parameters. While the thermal history of the material can be simulated, validating the simulations requires access to thermal data generated through in-situ process monitoring. While generation of in-situ thermal data seems trivial, acquiring and developing reliable calibrations for metallic materials is difficult due to the physical state of the material transitioning from powder to liquid to a solid. To be discussed is the methodology taken to integrate IR in-situ process monitoring within the electron beam melting process and the approach developed to accurately correlate a materials emissivity to temperature during the build process. Further the wealth of information contained within the thermal data will be discussed in the context of understanding of microstructural evolutions within the material during the build process, identification of material defects, and ability to determining the similarity/repeatability of builds fabricated with identical processing parameters as based only on the thermal signature of the build.

This study compares different approaches for imaging the internal architecture of graphite/epoxy composites using backscattered ultrasound. Two cases are studied. In the first, near-surface defects in a thin graphite/epoxy plates are imaged. The backscattered waveforms were used to produce peak-to-peak, logarithm of signal energy, as well as entropy images of different types. All of the entropy images exhibit better border delineation and defect contrast than either the peak-to-peak or the logarithm of signal energy. The best results are obtained using the joint entropy of the backscattered waveforms with a reference function. Two different references are examined. The first is a reflection of the insonifying pulse from a stainless steel reflector. The second is an approximate optimum obtained from an iterative parametric search. The joint entropy images produced using this reference exhibit three times the contrast obtained in previous studies. These plates were later destructively analyzed to determine size and location of near-surface defects and the results are found to agree with the defect location and shape as indicated by the entropy images. In the second study, images of long carbon fibers (50% by weight) in polypropylene thermoplastic were obtained as a first step toward ultrasonic determination of the distributions of fiber position and orientation.

Fourier transform infrared (FTIR) spectroscopy is an information-rich method that reveals chemical bonding near the surface of polymer composites. FTIR can be used to verify composite composition, identify chemical contaminants and expose composite moisture content. Polymer matrix changes due to thermal exposure including loss of additives, chain scission, oxidation and changes in crystallinity may also be determined using FTIR spectra. Portable handheld instruments using non-contact reflectance or surface contact attenuated total reflectance (ATR) may be used for nondestructive evaluation (NDE) of thermal aging in polymer and composite materials of in-service components. We report the use of ATR FTIR to track oxidative thermal aging in ethylene-propylene rubber (EPR) and chlorinated polyethylene (CPE) materials used in medium voltage nuclear power plant electrical cable insulation and jacketing. Mechanical property changes of the EPR and CPE materials with thermal degradation for correlation with FTIR data are tracked using indenter modulus (IM) testing. IM is often used as a local NDE metric of cable jacket health. The FTIR-determined carbonyl index was found to increase with IM and may be a valuable NDE metric with advantages over IM for assessing cable remaining useful life.

Composite materials pose a complex problem for ultrasonic nondestructive evaluation due to their unique material properties, greater damping, and often complicated geometry. In this study, we explored acoustic wavenumber spectroscopy (AWS) as a means of rapid inspection of laminate and honeycomb composites. Each aerospace sample was tested at different ultrasonic frequencies using steady-state excitation via a piezo electric actuator. We measured the velocity response of the composite at each pixel via a raster scan using a laser Doppler vibrometer. We were able to detect radial inserts along corners, delamination, and facing-core separation by analyzing local amplitude and wavenumber responses. For each honeycomb composite, we excited the sample at the first resonant frequency of the individual cells. The local mode shape for each cell was extracted from the local amplitude response. Analyzing local amplitude and phase responses for each cell provided an accurate indication as to the presence, size, shape, and type of defect present in the composite. We detected both delamination and deformation of cells within a honeycomb composite. For the laminar composites, we analyzed the non-resonance steady-state response at several excitation frequencies.

Combinatorial material research offers fast and efficient solutions to identify promising and advanced materials. It has revolutionized the pharmaceutical industry and now is being applied to accelerate the discovery of other new compounds, e.g. superconductors, luminescent materials, catalysts etc. Differing from the traditional trial-and-error process, this approach allows for the synthesis of a large number of compositionally diverse compounds by varying the combinations of the components and adjusting the ratios. It largely reduces the cost of single-sample synthesis/characterization, along with the turnaround time in the material discovery process, therefore, could dramatically change the existing paradigm for discovering and commercializing new materials. This talk outlines the use of combinatorial materials approach in the material discovery in transportation sector. It covers the general introduction to the combinatorial material concept, state of art for its application in energy-related research. At the end, LBNL capabilities in combinatorial materials synthesis and high throughput characterization that are applicable for material discovery research will be highlighted.

Density functional theory (DFT) simulations solve for the electronic structure of materials starting from the Schrödinger equation. Many case studies have now demonstrated that researchers can often use DFT to design new compounds in the computer (e.g., for batteries, catalysts, and hydrogen storage) before synthesis and characterization in the lab. In this talk, I will focus on how DFT calculations can be executed on large supercomputing resources in order to generate very large data sets on new materials for functional applications. First, I will briefly describe the Materials Project, an effort at LBNL that has virtually characterized over 60,000 materials using DFT and has shared the results with over 17,000 registered users. Next, I will talk about how such data can help discover new materials, describing how preliminary computational screening led to the identification and confirmation of a new family of bulk AMX2 thermoelectric compounds with measured zT reaching 0.8. I will outline future plans for how such data-driven methods can be used to better understand the factors that control thermoelectric behavior, e.g., for the rational design of electronic band structures, in ways that are different from conventional approaches.

In this study, acoustic emission (AE) tests were conducted to detect and locate wire fracture in strands that are widely used in cable-stayed and suspension bridges. To effectively separate fracture signals from unwanted noises, distinct features of fracture, fracture-induced echo, and artificial tapping signals as well as their dependence on loading levels are characterized with short-time Fourier transform. To associate fracture scenarios with their acoustic features, two 20-foot-long (~6.1 m) 270 ksi (~1,862 MPa) steel strands of seven wires were tested with one wire notched off at center and support, respectively, up to 90% of its cross section area by 10% increment. Up to 80% reduction in cross section area of the notched wire, each strand was loaded to 20 kips (~89 kN) corresponding to 35% of the minimum breaking strength and the acquired AE parameters such as hits, energy, and counts were found to change little. With a reduction of 90% of the section area of one wire, both strands were found to be fractured under approximately 16.5 kips (~73.4 kN). The hits, energy, and counts of AE signals were all demonstrated to suddenly change with the fracture of the notched wire. However, only the counts of AE signals distributed over the length of the strands allow the localization of fracture point. The frequency band of fracture signals is significantly broader than that of either fracture-induced echo or artificial tapping noise. The time duration of artificial tapping noises is substantially longer than that of either fracture or fracture-induced echo. These distinct characteristics can be used to effectively separate fracture signals from noises for wire fracture detection and localization in practice.

The three-span steel-arch-steel-girder Jiaxian Bridge was newly constructed in 2010 to replace the former one that has been destroyed by Typhoon Sinlaku (2008, Taiwan). It was designed and built to continue the domestic service requirement, as well as to improve the tourism business of the Kaohsiung city government, Taiwan. This study aimed at establishing the baseline model of Jiaxian Bridge for hazardous scenario simulation such as typhoons, floods and earthquakes. Necessities of these precaution works were attributed to the inherent vulnerability of the sites: near fault and river cross. The uncalibrated baseline bridge model was built with structural finite element in accordance with the blueprints. Ambient vibration measurements were performed repeatedly to acquire the elastic dynamic characteristics of the bridge structure. Two frequency domain system identification algorithms were employed to extract the measured operational modal parameters. Modal shapes, frequencies, and modal assurance criteria (MAC) were configured as the fitting targets so as to calibrate/update the structural parameters of the baseline model. It has been recognized that different types of structural parameters contribute distinguishably to the fitting targets, as this study has similarly explored. For steel-arch-steel-girder bridges in particular this case, joint rigidity of the steel components was found to be dominant while material properties and section geometries relatively minor. The updated model was capable of providing more rational elastic responses of the bridge superstructure under normal service conditions as well as hazardous scenarios, and can be used for manage the health conditions of the bridge structure.

A novel d36-type piezoelectric wafer fabricated from lead magnesium niobate-lead titanate (PMN-PT) is explored for the generation of in-plane horizontal shear waves in plate structures. The study focuses on the development of a linear phased array (PA) of PMN-PT wafers to improve the damage detection capabilities of a structural health monitoring (SHM) system. An attractive property of in-plane horizontal shear waves is that they are nondispersive yet sensitive to damage. This study characterizes the directionality of body waves (Lamb and horizontal shear) created by a single PMN-PT wafer bonded to the surface of a metallic plate structure. Second, a linear PA is designed from PMN-PT wafers to steer and focus Lamb and horizontal shear waves in a plate structure. Numerical studies are conducted to explore the capabilities of a PMN-PT-based PA to detect damage in aluminum plates. Numerical simulations are conducted using the Local Interaction Simulation Approach (LISA) implemented on a parallelized graphical processing unit (GPU) for high-speed execution. Numerical studies are further validated using experimental tests conducted with a linear PA. The study confirms the ability of an PMN-PT phased array to accurately detect and localize damage in aluminum plates.

Electrical impedance tomography (EIT) has been recently applied as a structural health monitoring (SHM) technique to many different kinds of structures. In short, EIT is an algorithm that reconstructs the spatial conductivity response of a conductive body using only voltage measurement along its boundaries. For a conductive structure with its electrical properties being sensitive to damages and/or strains, mapping the distribution of its conductivity allows one to obtain its corresponding damage and/or strain distribution. To date, the EIT inverse problem has been solved using different techniques. This study compared the performance of two different approaches using four evaluation criteria. The first technique is based on EIDORS, which is an open-source EIT solver based on the maximum a posteriori (MAP) approach. It can rapidly, using a one-step linear approach, evaluate the relative impedance change of a given region when a baseline measurement (i.e., the response collected under its initial state) is provided. The second approach is a two-step iterative shrinkage thresholding (TwIST) method that compresses a signal’s sparsity in preserving sharp edges of an image. Both methods were evaluated using a 16-electrode 2D square shape with a simulated “point” damage at different locations. The evaluation results suggested that TwIST outperforms MAP in terms of the resolution and accuracy of the reconstructed results, and MAP wins over TwIST in causing minor shape deformation and less ringing. Results from both methods exhibit position-dependency. These results are significant in promoting EIT becoming a powerful technique for in situ health monitoring.

Global structural monitoring strategies for steel truss bridges have the challenges as the influence of boundary conditions on the comparison of predicted and measured properties, and the insensitivity of current methods to small flaws. It is important to consider the damage mechanisms and their influences to structural behavior in the design process. In this paper, the truss optimization is linked with periodic structure design such that each periodic unit (repetitive truss section) has distinct dispersion curve that can be monitored in time for the presence of damage. The numerical model of periodic unit is performed for pristine and cracked conditions. The changes in dispersion behavior with the increase of damage are noted. A section of the truss is built in the laboratory, and the dispersion of periodic unit is obtained using impulse response method in order to reduce the influence of boundary conditions. The changes of dispersion curve of periodic cell with the increase of damage are compared with the numerical results. The proposed design strategy integrates the damage detection philosophy to the design stage, and increases the reliability of nondestructive evaluation method.

Stochastic subspace identification (SSID) is a first-order linear system identification technique enabling modal analysis through the time domain. Research in the field of structural health monitoring has demonstrated that SSID can be used to successfully retrieve modal properties, including modal damping ratios, using output-only measurements. In this paper, the utilization of SSID for indirectly retrieving structures’ stiffness matrix was investigated, through the study of a simply supported reinforced concrete beam subjected to dynamic loads. Hence, by introducing a physical model of the structure, a second-order identification method is achieved. The reconstruction is based on system condensation methods, which enables calculation of reduced order stiffness, damping, and mass matrices for the structural system. The methods compute the reduced order matrices directly from the modal properties, obtained through the use of SSID. Lastly, the reduced properties of the system are used to reconstruct the stiffness matrix of the beam. The proposed approach is first verified through numerical simulations and then validated using experimental data obtained from a full-scale reinforced concrete beam that experienced progressive damage. Results show that the SSID technique can be used to diagnose, locate, and quantify damage through the reconstruction of the stiffness matrix.

By using three, or more, electronic distance measurement (EDM) instruments, such as commercially available laser trackers, in an unconventional trilateration architecture, 3-D coordinates of specialized retroreflector targets attached to cardinal points on a structure can be measured with absolute uncertainty of less than one part-permillion. For example, 3-D coordinates of a structure within a 100 meter cube can be measured within a volume of a 0.1 mm cube (the thickness of a sheet of paper). Relative dynamic movements, such as vibrations at 30 Hz, are typically measured 10 times better, i.e., within a 0.01 mm cube. Measurements of such accuracy open new areas for nondestructive testing and finite element model confirmation of stiff, large-scale structures, such as: buildings, bridges, cranes, boilers, tank cars, nuclear power plant containment buildings, post-tensioned concrete, and the like by measuring the response to applied loads, changes over the life of the structure, or changes following an accident, fire, earthquake, modification, etc. The sensitivity of these measurements makes it possible to measure parameters such as: linearity, hysteresis, creep, symmetry, damping coefficient, and the like. For example, cracks exhibit a highly non-linear response when strains are reversed from compression to tension. Due to the measurements being 3-D, unexpected movements, such as transverse motion produced by an axial load, could give an indication of an anomaly–such as an asymmetric crack or materials property in a beam, delamination of concrete, or other asymmetry due to failures. Details of the specialized retroreflector are included.

This study attempted to investigate the self-sensing capability of Portland cement composites in sensing temperature and detecting damages through the measurements of materials’ thermoelectric properties. Specimens were made of Ordinary Portland Cement (OPC) with the water to cement ratio of 0.4. Temperature sensing property was characterized at various ages of the specimens from 28 to 49 days and at dried/moisturized conditions. It was found there exists an approximately linear relationship between temperature differences (ΔT) and the measured thermoelectric potentials, which is known as the Seebeck effect. This linearity was observed to be varied but able to be characterized for cement pastes at different ages and water saturation conditions. Mechanical loading that introduced different types and degrees of damages also translated into the variations of thermoelectric properties. Specifically, different types of compressive loads were tested for comparison. The study results have shown that Seebeck coefficient dropped with introduced damages, and restored with the subsequent re-curing as well as the continued cement hydration. Mild and moderate damages can be partially or fully restored, while severe damages that have resulted in significant drop of the Seebeck coefficients would restrain the self-restoration. Determination of the damage threshold was not yet revealed in this study, while it was shown obviously there existed one. Our investigation results indicated that characterizing the self-sensing capability of Portland cement composites is achievable through the measurements of thermoelectric properties. This study, in particular, has showcased the temperature sensing and damage detection capability.

This paper outlines a framework for quantifying and optimizing the value of information from structural health monitoring (SHM) technology deployed on large infrastructure, which may sustain damage in a series of earthquakes (the main and the aftershocks). The evolution of the damage state of the infrastructure without or with SHM is presented as a time-dependent, stochastic, discrete-state, observable and controllable nonlinear dynamical system. The pre-posterior Bayesian analysis and the decision tree are used for quantifying and optimizing the value of SHM information. An optimality problem is then formulated how to decide on the adoption of SHM and how to manage optimally the usage and operations of the possibly damaged infrastructure and its repair schedule using the information from SHM. The objective function to minimize is the expected total cost or risk.

In this paper two methods of damage localization previously proposed by the authors are combined to smooth the possible drawbacks and boost the advantages each of them. The Modal Interpolation Method (IM), recently proposed, is based on a damage feature defined in terms of the loss of smoothness (that is local increases of curvature) of the modal shapes induced by a local reduction of stiffness. Herein the combination of the IM with the Curvature Evolution Methods (CEM) is proposed. The CEM is based on the use of a Band-Variable Filter able to extract from recorded responses the nonlinear response of one mode of vibration enabling the detection of possible changes of a properly defined damage feature, during a single earthquake. In the CEM the modal curvature is assumed as damage feature. The combination of the two methods CEM and IM is carried out using the Band-Variable Filter to extract the nonlinear response of the structure and assuming as a damage feature the variation of the interpolation error computed at different times during the strong motion.

The validation of the combined approach, named Interpolation Evolution Method (IEM), is carried out on a full scale experimental benchmark tested on the UCSD-NEES shake table.

We describe the feasibility of a nondestructive evaluation (NDE) method for concrete based on the propagation of highly nonlinear solitary waves (HNSWs) along a one-dimensional chain of spherical particles placed in contact with the concrete to be tested. The chain is part of a built-in transducer designed and assembled to excite and detect HNSWs. The method exploits the dynamic interaction between the particles and the concrete. The hypothesis is that the interaction depends on the stiffness of the concrete and influences the time of flight and amplitude of the solitary pulses reflected at the transducer/concrete interface, and traveling within the chain. The results show that the time of flight is monotonically dependent upon the modulus of elasticity of the concrete and that the transducers designed and assembled in this study are reliable and repeatable. In the future, the proposed NDE method may potentially serve as a cost-effective tool for the rapid evaluation of existing concrete structures.

Photogrammetric methods such as structure from motion (SFM) have the capability to acquire accurate information about geometric features, surface cracks, and mechanical properties of specimens and structures in civil engineering. Conventional approaches to verify the accuracy in photogrammetric models usually require the use of other optical techniques such as LiDAR. In this paper, geometric accuracy of photogrammetric modeling is investigated by studying the effects of number of photos, radius of curvature, and point cloud density (PCD) on estimated lengths, areas, volumes, and different stress states of concrete cylinders and panels. Four plain concrete cylinders and two plain mortar panels were used for the study. A commercially available mobile phone camera was used in collecting all photographs. Agisoft PhotoScan software was applied in photogrammetric modeling of all concrete specimens. From our results, it was found that the increase of number of photos does not necessarily improve the geometric accuracy of point cloud models (PCM). It was also found that the effect of radius of curvature is not significant when compared with the ones of number of photos and PCD. A PCD threshold of 15.7194 pts/cm³ is proposed to construct reliable and accurate PCM for condition assessment. At this PCD threshold, all errors for estimating lengths, areas, and volumes were less than 5%. Finally, from the study of mechanical property of a plain concrete cylinder, we have found that the increase of stress level inside the concrete cylinder can be captured by the increase of radial strain in its PCM.

Synthetic aperture radar (SAR) imaging of construction materials offers civil engineers an opportunity to better assess the condition of aging civil infrastructures such as reinforced concrete (RC) structures. Corrosion of steel rebar in RC structures is a major problem responsible for their premature failure and unexpected collapse. In this paper, SAR imaging is applied to the quantitative assessment of corroded steel rebar in free space as the first step toward the use of SAR imaging for subsurface sensing of aging RC structures. A 10 GHz stripmap SAR system was used inside an anechoic chamber. The bandwidth of the radar system was 1.5 GHz. Steel rebar specimens were artificially corroded to different levels by regularly applying a mist of 5% NaCl solution for different durations of time in order to simulate the condition of natural corrosion. Two sizes (No. 3 and No. 4) of steel rebar were used in this research. Different orientations of steel rebar were considered. Corrosion level was determined by measuring the mass loss of corroded steel rebar specimens. From our results, feasibility of SAR images for the condition assessment of corroded steel rebar was experimentally demonstrated. It was found that the presence of surface rust on corroded steel rebar reduces the amplitude in SAR images. The SAR image of corroded steel rebar also exhibited a distribution of SAR amplitudes different from the one of intact steel rebar. In addition, it was also found that there is an optimal range for the condition assessment of corroded steel rebar in free space. In our experiment, the optimal range was determined to be 30.4 cm.

Interest in the concept of self-sensing structural materials has grown in recent years due to its potential to enable continuous low-cost monitoring of next-generation smart-structures. The development of cement-based smart sensors appears particularly well suited for monitoring applications due to their numerous possible field applications, their ease of use and long-term stability. Additionally, cement-based sensors offer a unique opportunity for structural health monitoring of civil structures because of their compatibility with new or existing infrastructure. Particularly, the addition of conductive carbon nanofillers into a cementitious matrix provides a self-sensing structural material with piezoresistive characteristics sensitive to deformations. The strain-sensing ability is achieved by correlating the external loads with the variation of specific electrical parameters, such as the electrical resistance or impedance. Selection of the correct electrical parameter for measurement to correlate with features of interest is required for the condition assessment task. In this paper, we investigate the potential of using altering electrical potential in cement-based materials doped with carbon nanotubes to measure strain and detect damage in concrete structures. Experimental validation is conducted on small-scale specimens including a steel-reinforced beam of conductive cement paste. Comparisons are made with constant electrical potential and current methods commonly found in the literature. Experimental results demonstrate the ability of the changing electrical potential at detecting features important for assessing the condition of a structure.

In this work, a new ultrasound nondestructive testing (NDT) method based on laser-generated Lamb wave detection was proposed for high temperature (HT) NDT. Lamb waves were introduced to a stainless steel plate by the Nd:YAG pulsed laser at one point and detected by aluminum nitride (AlN) transducer at a distant position. The fundamental symmetric (S₀) and antisymmetric (A₀) mode Lamb waves were successfully propagated in the thin stainless steel plate. The time-of- flight (TOF) of the S₀ and A₀ mode waves proportionally increased with the distance (D) between the laser source and the sensor, and almost no attenuation of the amplitude was observed. For the HT NDT experiment, AlN single crystal was adopted as the ultrasonic sensor material due to its high thermal resistance of the dielectric and piezoelectric constants at the elevated temperature up to 800 °C. The combination of non-contact, portable laser source as a Lamb wave generator and temperature-robust NDT sensor made of AIN has shown its great capability to detect the Lamb waves at elevated temperatures.

Acoustic metamaterials are periodic and composite structures that can block, direct and strengthen propagating elastic waves. They are periodic elastic composites made of two or more materials with different elastic properties. The periodic structure can exhibit certain band gaps that are used to manipulate wave field. In this research, the periodic and composite structure is made of aluminum plate and rubber cylinders manufactured using 3D printing. The ability to block and redirect elastic waves is numerically and experimentally demonstrated. Wave field focusing reduces the wave attenuation, which allows increasing the distance of acoustic sensors for damage detection in large-scale structures.

The development of low-cost bonded assembly of composite aerospace structures ideally requires an NDE method to detect the presence of poor quality, weak bonds or kissing bonds. Such interfaces can introduce nonlinearity as a result of contact nonlinearity where an ultrasonic wave is distorted when it interacts with the interface. In general, the nonlinear elastic behaviour of these interfaces will generate harmonics but they can be lost among the harmonics generated by other nonlinearities present in the experimental system. The technique developed in this research is a non-collinear method; this involves the interaction of two ultrasonic beams, and it allows the removal of virtually all system nonlinearity except for that produced in the region where the two beams overlap. The frequencies of the two beams and the angle between are varied during the experiment. By measuring the nonlinear mixing response as these two parameters are swept through a ‘fingerprint’ of the nonlinear properties in the interaction region can be obtained. This fingerprint has been shown to contain information about the bulk material and the interface status. Work is ongoing to understand which features in the fingerprints reliably correlate with particular material or interface properties. To build this understanding a greatly simplified kissing bond, a compression loaded aluminium-aluminium interface, has been tested. Modelling of the nonlinear behaviour of the aluminium interface has also been conducted.

Elastic wave velocities as a function of applied stress are analysed in multilayered and 1-D phononic structures. The analysis is conducted by the means of the acoustoelasticity theory for isotropic elastic structures with application of this theory to stable formulation of stiffness and hybrid matrix methods for the eigenvalue analysis in the stressed elastic structures. The reformulated matrix methods are used for obtaining modal solutions, reflection and transmission coefficients for different multilayered media cases. Floquet wave analysis is presented for the stressed 1-D phononic structures. The analysis is supported by numerical examples.

In reinforced concrete (RC) structures, corrosion of steel rebar introduces internal stress at the interface between rebar and concrete, ultimately leading to debonding and separation between rebar and concrete. Effective early-stage detection of steel rebar corrosion can significantly reduce maintenance costs and enable early-stage repair. In this paper, ultrasonic detection of early-stage steel rebar corrosion inside concrete is numerically investigated using the finite element method (FEM). Commercial FEM software (ABAQUS) was used in all simulation cases. Steel rebar was simplified and modeled by a cylindrical structure. 1MHz ultrasonic elastic waves were generated at the interface between rebar and concrete. Two-dimensional plain strain element was adopted in all FE models. Formation of surface rust in rebar was modeled by changing material properties and expanding element size in order to simulate the rust interface between rebar and concrete and the presence of interfacial stress. Two types of surface rust (corroded regions) were considered. Time domain and frequency domain responses of displacement were studied. From our simulation result, two corrosion indicators, baseline (b) and center frequency (f_c) were proposed for detecting and quantifying corrosion.

High Energy Wide Area Blunt Impact (HEWABI) due to ground service equipment can often occur in aircraft structures causing major damages. These Wide Area Impact Damages (WAID) can affect the internal components of the structure, hence are usually not visible nor detectable by typical one-sided NDE techniques and can easily compromise the structural safety of the aircraft. In this study, the development of an NDI method is presented together with its application to impacted aircraft frames. The HEWABI from a typical ground service scenario has been previously tested and the desired type of damages have been generated, so that the aircraft panels could become representative study cases. The need of the aircraft industry for a rapid, ramp-friendly system to detect such WAID is here approached with guided ultrasonic waves (GUW) and a scanning tool that accesses the whole structure from the exterior side only. The wide coverage of the specimen provided by GUW has been coupled to a differential detection approach and is aided by an outlier statistical analysis to be able to inspect and detect faults in the challenging composite material and complex structure. The results will be presented and discussed with respect to the detection capability of the system and its response to the different damage types. Receiving Operating Characteristics curves (ROC) are also produced to quantify and assess the performance of the proposed method. Ongoing work is currently aimed at the penetration of the inner components of the structure, such as shear ties and C-frames, exploiting different frequency ranges and signal processing techniques. From the hardware and tool development side, different transducers and coupling methods, such as air-coupled transducers, are under investigation together with the design of a more suitable scanning technique.

Carbon fiber reinforced polymer (CFRP) composites are increasingly used in aerospace applications due to its superior mechanical properties and reduced weight. Adhesive bonding is commonly used to join the composite parts since it is capable of joining incompatible or dissimilar components. However, insufficient adhesive or contamination in the adhesive bonds might occur and pose as threats to the integrity of the plane during service. It is thus important to look for suitable nondestructive testing (NDT) techniques to detect and characterize the sub-surface defects within the CFRP composites. Some of the common NDT techniques include ultrasonic techniques and thermography. In this work, we report the use of the abovementioned techniques for improved interpretation of the results.

Probability of detection (POD) analysis is used in assessing reliably detectable flaw size in nondestructive evaluation (NDE). MIL-HDBK-1823 and associated mh18232 POD software gives most common methods of POD analysis. In this paper, POD analysis is applied to an NDE method, such as eddy current testing, where calibration is used. NDE calibration standards have known size artificial flaws such as electro-discharge machined (EDM) notches and flat bottom hole (FBH) reflectors which are used to set instrument sensitivity for detection of real flaws. Real flaws such as cracks and crack-like flaws are desired to be detected using these NDE methods. A reliably detectable crack size is required for safe life analysis of fracture critical parts. Therefore, it is important to correlate signal responses from real flaws with signal responses form artificial flaws used in calibration process to determine reliably detectable flaw size.

Effects of foundation stiffness on the linear vibrations of wind turbine systems are of concerns for both planning and construction of wind turbine systems. Current study performed numerical modeling for such a problem using linear spectral finite elements. The effects of foundation stiffness were investigated for various combinations of shear wave velocity of soil, size of tower base plate, and pile length. Multiple piles are also included in the models such that the foundation stiffness can be analyzed more realistically. The results indicate that the shear wave velocity of soil and the size of tower base plate have notable effects on the dominant frequency of the turbine-tower system. The larger the lateral dimension, the stiffer the foundation. Large pile cap and multiple spaced piles result in higher stiffness than small pile cap and a mono-pile. The lateral stiffness of a mono-pile mainly depends on the shear wave velocity of soil with the exception for a very short pile that the end constraints may affect the lateral vibration of the superstructure. Effective pile length may be determined by comparing the simulation results of the frictional pile to those of the end-bearing pile.

Currently more and more people concerned about the safety of major public security. Public participant urban infrastructure safety monitoring and investigation has become a trend in the era of big data. In this paper, public participant urban infrastructure safety protection system based on smart phones is proposed. The system makes it possible to public participant disaster data collection, monitoring and emergency evaluation in the field of disaster prevention and mitigation. Function of the system is to monitor the structural acceleration, angle and other vibration information, and extract structural deformation and implement disaster emergency communications based on smartphone without network. The monitoring data is uploaded to the website to create urban safety information database. Then the system supports big data analysis processing, the structure safety assessment and city safety early warning.

The paper provides discussion on optimizing probability of detection (POD) demonstration experiments using point estimate method. The optimization is performed to provide acceptable value for probability of passing demonstration (PPD) and achieving acceptable value for probability of false (POF) calls while keeping the flaw sizes in the set as small as possible. POD Point estimate method is used by NASA for qualifying special NDE procedures. The point estimate method uses binomial distribution for probability density. Normally, a set of 29 flaws of same size within some tolerance are used in the demonstration. Traditionally largest flaw size in the set is considered to be a conservative estimate of the flaw size with minimum 90% probability and 95% confidence. The flaw size is denoted as α_90/95PE. The paper investigates relationship between range of flaw sizes in relation to α₉₀, i.e. 90% probability flaw size, to provide a desired PPD. The range of flaw sizes is expressed as a proportion of the standard deviation of the probability density distribution. Difference between median or average of the 29 flaws and α₉₀ is also expressed as a proportion of standard deviation of the probability density distribution. In general, it is concluded that, if probability of detection increases with flaw size, average of 29 flaw sizes would always be larger than or equal to α₉₀ and is an acceptable measure of α_90/95PE. If NDE technique has sufficient sensitivity and signal-to-noise ratio, then the 29 flaw-set can be optimized to meet requirements of minimum required PPD, maximum allowable POF, requirements on flaw size tolerance about mean flaw size and flaw size detectability requirements. The paper provides procedure for optimizing flaw sizes in the point estimate demonstration flaw-set.

Nondestructive evaluation (NDE) method reliability can be determined by a statistical flaw detection study called probability of detection (POD) study. In many instances, the NDE flaw detectability is given as a flaw size such as crack length. An alternate approach is to use a more complex flaw size parameter. Earlier models by the author did not include scattering effects in detection of cracks. X-ray flaw size parameter model, given here, investigates one of scattering effects namely specular reflectivity of low energy x-rays impinging on crack faces at grazing angle. Reflectivity of x-rays at low grazing angle to crack faces is almost 100%. If crack faces are smooth and flat, the grazing angle x-rays channel between the crack faces. The paper models the specular reflection to study its effect on contrast of x-ray image. The channeling of x-rays can improve x-ray image contrast significantly. Normalized exposure and image width are used to calculate the flaw size parameter. Reflectivity of grazing angle x-rays can be used to improve x-ray crack detectability in thin low density materials.

Weight optimization of structures can result in lower stiffness and less internal damping, causing the structure to become excessively prone to vibration. To overcome this problem, active or smart materials are implemented. The coupled electromechanical properties of smart materials, used in the form of piezoelectric ceramics in this work, make these materials well-suited for being implemented as distributed sensors and actuators to control the structural response. The smart structure proposed in this paper is composed of a cantilevered steel beam, an adhesive or bonding layer, and a piezoelectric actuator. The static deflection of the structure is derived as function of the piezoelectric voltage, and the outcome is compared to theoretical and experimental results from literature. The relation between the voltage and the piezoelectric moment at both ends of the actuator is also investigated and a reduced finite element model of the smart structure is created and verified. Finally, different linear controllers are implemented and its ability to attenuate the vibration due to the first Eigen frequency is demonstrated.

The non-dispersive fundamental shear horizontal (SH0) and torsional [T(0,1)] waves are extremely useful in guidedwave-based inspection techniques. However, excitation of SH0 and T(0,1) waves using piezoelectrics is always a challenge. In this work, firstly, a newly defined face-shear d24 PZT wafer is proposed to excite and receive SH0 wave mode. The d24 wafer is in-plane poled and its working electric field is applied along another orthogonal in-plane direction. Both finite element simulations and experiments show that single SH0 mode can be excited by using the d24 wafer along two orthogonal directions (0° and 90°). Then an omnidirectional SH0 wave piezoelectric transducer (OSHPT) is developed which consists of a circular array of twelve face-shear d24 trapezoidal PZT elements. Results show that the proposed OSH-PT exhibits good omnidirectional properties, no matter it is used as a SH0 wave transmitter or receiver. Finally, the development of a T(0,1) wave transducer for pipes based on a ring array of d24 PZT elements is described. Both finite element simulations and experiments show that the d24 elements ring can excite single T(0,1) mode and suppress all the unwanted non-axisymmetric modes. This work may greatly promote the applications of SH0 and T(0,1) waves in nondestructive testing (NDT) and structural health monitoring (SHM).

This paper proposes an innovative sensing system for high temperature (up to 150°C) I-beam crack detection. The proposed system is based on the piezoelectric effect and laser sensing mechanisms, which is proved to be effective at high temperature environment (up to 150°C). Different from other high temperature SHM approaches, the proposed sensing system is employing a piezoelectric disk as an actuator and a laser vibrometer as a sensor for remote detection. Lab tests are carried out and the vibrational properties are studied to characterize the relationship between crack depth and sensor responses by analyzing the RMS of sensor responses. Instead of utilizing a pair of piezoelectric actuator and sensor, using the laser vibrometer will enable 1) a more flexible detection, which will not be limited to specific area or dimension, 2) wireless sensing, which lowers the risk of operating at high temperature/harsh environment. The proposed sensing system can be applied to engineering structures such as in nuclear power plant reactor vessel and heat pipe structures/systems.

There is considerable demand for structural health monitoring (SHM) at locations where there are substantial radiation fields such as nuclear reactor components, dry cask storage canister, irradiated fuel assemblies, etc. Piezoelectric wafer active sensors (PWAS) have been emerged as one of the major SHM sensing technologies. In order to use PWAS to perform SHM in nuclear environment, radiation influence on sensor and sensing capability needs to be investigated to assure the reliability of the PWAS based method. Radiation may cause degradation or even complete failure of sensors. Gamma radiation is one of the major radiation sources near the nuclear source. Therefore, experimental investigation was completed on the gamma radiation endurance of piezoelectric sensors. The irradiation test was done in a Co-60 Gamma Irradiator. Lead Zirconate Titanate (PZT) and Gallium Orthophosphate (GaPO4) PWAS were exposed under gamma radiation at 100 Gy/hr rate for 20 hours. Electro-mechanical (E/M) admittance signatures and electrical capacitance were measured to evaluate the PWAS performance before and after every 4 hours exposure to gamma radiation. PWAS were kept at room temperature for 6 days after each 4 hours radiation exposure to investigate the effect of time on PWAS by gamma radiation. It was found that, PZT-PWAS show variation in resonance frequency for both in plane and thickness mode E/M admittance. Where, the changes in resonance amplitudes are larger for PZT-PWAS. GaPO4-PWAS E/M impedance/admittance spectra don’t show any reasonable change after gamma irradiation. A degradation behavior of electrical properties in the PZT-PWAS was observed. Capacitance value of PZT-PWAS decreases from 3.2 nF to 3.07 nF after exposing to gamma radiation for 20 hours at 100Gy/hour. This degradation behavior of electrical properties may be explained by the pinning of domain walls by some radiation induced effect. GaPO4-PWAS doesn’t show reasonable degradation in electrical properties. GaPO4 has good radiation endurance, although amplitude sensitivity is relatively low.

The research objective was to evaluate Ordinary Portland Cement concrete subject to various elevated temperatures. Single OPC concrete mixture with water to cementitious (w/c) equal to 0.45 was proportioned. Concrete specimens were cast and placed in the curing tank in which water was saturated with calcium hydroxide. After ninety days of moist-cure, three elevated temperatures, namely 300, 600, and 900-°C, were carried out upon hardened concrete specimens. Furthermore, two post-damaged curing conditions were executed to recover damaged concrete specimens: one was to recure under 23°C with 50% humidity in a controlled environmental chamber and the other was to recure in the same curing tank. Acoustic emission apparatus coupled with the splitting tensile test was utilized and found able to assess damaged concrete. Before concrete subject to elevated temperatures, the development of indirect tensile strength versus displacement diagram fit well with the tendency of AE energy release. It was found there was a large amount of AE energy released when stress and displacement diagram developed about 40-50%. As such could be identified as the onset of first fracture and the plain concrete generally exhibited a quasi-brittle fracture with two major series of AE energy dissipations; however when concrete specimens were subject to elevated temperatures, the damaged concrete specimens displayed neither fracture pattern nor the “double-hump” AE energy dissipation in comparison with those of plain concrete.

In general the ultrasonic techniques have been used to determine the mechanical properties of materials on based of their relationship with metallurgical characteristics. In this research work, the relationship between ultrasonic velocity and phased array and the microstructure of steel pipeline welded joints is investigated. Measurements of ultrasonic wave velocity were made as a function of the location across the weld. Hardness measurements were performated in an attempt to correlate with ultrasonic response. In addition, the coarse and dendritic grain structure of the weld material is extreme and unpredictably anisotropic. Thus, due to the acoustic anisotropy of the crystal itself weld material of studied joints is anisotropic, too. Such structure is no longer direction-independent to the ultrasonic wave propagation; therefore, the ultrasonic beam deflects and redirects and the wave front becomes distorted. Thus, the use of conventional ultrasonic testing techniques using fixed beam angles is very limited and the application of conventional ultrasonic phased array techniques becomes desirable.