This PDF file contains the front matter associated with SPIE Proceedings Volume 9805, including the Title Page, Copyright information, Table of Contents, Introduction, and the Conference Committee listing.

Detection, localization, and characterization of impact damage in composites using in situ transducers are important objectives for the aerospace industry to both reduce maintenance costs and prevent failures. A network of piezoelectric transducers spatially distributed over an area of interest is one practical configuration for utilizing guided waves to accomplish these objectives. Detecting and localizing barely visible impact damage with such a sparse array has been demonstrated in prior work, and improvements in localization were demonstrated by incorporating fairly crude estimates of scattering patterns in the imaging algorithms. Here we obtain more estimates of scattering patterns from a simulated defect by employing baseline subtraction of wavefield data recorded in a circle centered at the scatterer. Scattering patterns are estimated from the wavefield residual signals before and after simulated damage is introduced and the estimated scattering patterns are then incorporated into sparse array imaging via the minimum variance imaging method. Images created with different scattering patterns are compared and the efficacy of the methodology is assessed.

The aim of this paper is to present aspects of Lamb wave propagation in randomly oriented short fiber reinforce composites with delamination. Prediction of elastic constants is based on mechanics of composites, rule of mixture and total mass balance tailored to the spectral element mesh composed of 3D brick elements. Piezoelectric excitation as well as glue layer are taken into account. Complex full wave field includes multiple reflections at short fibers. This wave pattern is also obtained by the use of laser vibrometry confirming good quality of the model. Further studies are related to symmetrical and non-symmetrical delamination in respect to the thickness of the composite plate. Square delamination of the side length 10 mm is investigated. It has been found that reflections from delamination are mostly superimposed with reflections coming from short fibers. Hence, delamination detection by direct analysis of wave propagation pattern on the surface of the plate is ineffective. However, adaptive wavenumber filtering method overcome these difficulties and enables not only to detect the delamination but also is helpful for delamination size estimation. Moreover, the method is more effective if the full wavefield measurements are acquired on the surface of the plate which is closer to the delamination.

Guided wave (GW) Structural Health Monitoring (SHM) allows to assess the health of aerostructures thanks to the great sensitivity to delamination and/or debondings appearance. Due to the several complexities affecting wave propagation in composites, an efficient GW SHM system requires its effective quantification associated to a rigorous statistical evaluation procedure. Probability of Detection (POD) approach is a commonly accepted measurement method to quantify NDI results and it can be effectively extended to an SHM context. However, it requires a very complex setup arrangement and many coupons. When a rigorous correlation with measurements is adopted, Model Assisted POD (MAPOD) is an efficient alternative to classic methods. This paper is concerned with the identification of small emerging delaminations in composite structural components. An ultrasonic GW tomography focused to impact damage detection in composite plate-like structures recently developed by authors is investigated, getting the bases for a more complex MAPOD analysis. Experimental tests carried out on a typical wing composite structure demonstrated the effectiveness of modeling approach in order to detect damages with the tomographic algorithm. Environmental disturbances, which affect signal waveforms and consequently damage detection, are considered simulating a mathematical noise in the modeling stage. A statistical method is used for an effective making decision procedure. A Damage Index approach is implemented as metric to interpret the signals collected from a distributed sensor network and a subsequent graphic interpolation is carried out to reconstruct the damage appearance. A model validation and first reliability assessment results are provided, in view of performance system quantification and its optimization as well.

This paper presents the phased array beamforming and imaging using guided waves in anisotropic composite laminates. A generic phased array beamforming formula is presented, based on the classic delay-and-sum principle. The generic formula considers direction-dependent guided wave properties induced by the anisotropic material properties of composites. Moreover, the array beamforming and imaging are performed in frequency domain where the guided wave dispersion effect has been considered. The presented phased array method is implemented with a non-contact scanning laser Doppler vibrometer (SLDV) to detect multiple simulated defects at different locations in an anisotropic composite plate. The array is constructed of scan points in a small area rapidly scanned by the SLDV. Using the phased array method, multiple simulated defects at different locations are successfully detected. Our study shows that the guided wave phased array method is a potential effective method for rapid inspection of large composite structures.

The vibration mode shapes are often used to identify damage of bridges because the mode shapes are not only important modal properties but also sensitive to damage. However, the key issue is how to conveniently obtain the mode shapes of a bridge in service. Traditional methods invariably require installation of instruments on the bridge for collection of dynamic responses for constructing mode shapes, which are both costly and inconvenient. Therefore a method is developed to construct the mode shapes of simply supported bridges based on Hilbert Transform using only vehicle acceleration response for identification of the location of damage. Firstly, an algorithm is devised to construct the mode shapes by using the dynamic responses extracted from a moving vehicle under impact excitation. Then, based on these intermediate results, the coordinate modal assurance criterion in conjunction with suitable wavelets is used to identify the location of damage. Compared with the traditional methods, the proposed method uses only the information from the moving vehicle. Moreover, additional impact excitation on the vehicle helps to excite the bridge. This helps to improve the accuracy by overcoming the adverse effects of measurement noise and road surface roughness, which leads to high accuracy of damage detection. To verify the feasibility of the proposed method, some numerical studies have been carried out to investigate the effects of measurement noise, road surface roughness and multiple locations of damage on the accuracy of results.

Monitoring a complex structure has gained popularity worldwide to ensure safety and longevity of the structure. Structural Health Monitoring (SHM) systems have been employed for highway bridges to increase the effectiveness of their in-service inspection, to help measure its degradation or damage, and hence, to ensure it’s safe and reliable operation. SHM may also be employed during the construction of a structure in order to ensure the safety and performance of the construction process. Monitoring during construction can also help designers compare the actual behavior of a structure with design models especially because of increasing development of accelerated or otherwise novel construction techniques. Analyzing the behavior of a structure at different stages of construction may also help later define some of the abnormal responses during the lifespan of a bridge. This paper overviews the SHM system of the Ironton-Russell Bridge, Ohio at the construction stage of its substructure. The stages involved in monitoring such as instrumentation of sensors, acquiring data from the sensors, data processing that includes a warning system, static analysis of the data collected and website are detailed in this paper. In addition to this, the effect of construction events as observed by the sensor data for the substructure is analyzed in detail thus validating the capability of the monitoring system.

Structural temperatures and their uneven distributions have significantly negative effects on bridges. It is very important to accurately calculate the structural temperatures. Structural temperatures are deeply affected by the surrounding weather conditions, and the environmental wind is a critical factor. In this study, the wind effects on the thermal analysis of bridges are investigated using numerical simulation. Frist, the traditional theory and method are briefly introduced to show the important effects of wind on structural heat transfer analysis. Then, a new approach is proposed to take account of the wind effects for temperature analysis of bridges. At last, numerical study based on the finite element transient heat transfer analysis of a box-girder bridge is carried out and discussed to verify the proposed method. The results indicate that the proposed method is more reasonable than the traditional methods. This method can be easily implemented in practice for temperature analysis of bridges.

Singularity expansion method (SEM) is a system identification approach with applications in solving inverse scattering problems, electromagnetic interaction problems, remote sensing, and radars. In this approach, the response of a system is represented in terms of its complex poles; therefore, this method not only extracts the fundamental frequencies of the system from the signal, but also provides sufficient information about system's damping if its transient response is analyzed. There are various techniques in SEM among which the generalized pencil-of-function (GPOF) is the computationally most stable and the least sensitive one to noise. However, SEM methods, including GPOF, suffer from imposition of spurious poles on the expansion of signals due to the lack of apriori information about the number of true poles. In this study we address this problem by proposing sparse generalized pencil-of-function (SGPOF). The proposed method excludes the spurious poles through sparsity-based regularization with ℓ₁-norm. This study is backed by numerical examples as well as an application example which employs the proposed technique for structural health monitoring (SHM) and compares the results with other signal processing methods.

Because of social background, such as repeated large earthquakes and cheating in design and construction, structural health monitoring (SHM) systems are getting strong attention. The SHM systems are in a practical phase. An SHM system consisting of small number of sensors has been introduced to 6 tall buildings in Shinjuku area. Including them, there are 2 major issues in the SHM systems consisting of small number of sensors. First, optimal system number of sensors and the location are not well-defined. In the practice, system placement is determined based on rough prediction and experience. Second, there are some uncertainties in estimation results by the SHM systems. Thus, the purpose of this research is to provide useful information for increasing reliability of SHM system and to improve estimation results based on uncertainty analysis of the SHM systems. The important damage index used here is the inter-story drift angle. The uncertainty considered here are number of sensors, earthquake motion characteristics, noise in data, error between numerical model and real building, nonlinearity of parameter. Then I have analyzed influence of each factor to estimation accuracy. The analysis conducted here will help to decide sensor system design considering valance of cost and accuracy. Because of constraint on the number of sensors, estimation results by the SHM system has tendency to provide smaller values. To overcome this problem, a compensation algorithm was discussed and presented. The usefulness of this compensation method was demonstrated for 40 story S and RC building models with nonlinear response.

This study investigates a new probabilistic strategy for model updating using incomplete modal data. A hierarchical Bayesian inference is employed to model the updating problem. A Markov chain Monte Carlo technique with adaptive random-work steps is used to draw parameter samples for uncertainty quantification. Mode matching between measured and predicted modal quantities is not required through model reduction. We employ an iterated improved reduced system technique for model reduction. The reduced model retains the dynamic features as close as possible to those of the model before reduction. The proposed algorithm is finally validated by an experimental example.

The importance of the structural health monitoring system for tall buildings is now widely recognized by at least structural engineers and managers at large real estate companies to ensure the structural safety immediately after a large earthquake and appeal the quantitative safety of buildings to potential tenants. Some leading real estate companies decided to install the system into all tall buildings. Considering this tendency, a pilot project for the west area of Shinjuku Station supported by the Japan Science and Technology Agency was started by the author team to explore a possibility of using the system to provide safe spaces for commuters and residents. The system was installed into six tall buildings. From our experience, it turned out that viewing only from technological aspects was not sufficient for the system to be accepted and to be really useful. Safe spaces require not only the structural safety but also the soundness of key functions of the building. We need help from social scientists, medical doctors, city planners etc. to further improve the integrity of the system.

To assess the health of buildings, maximum inter-story drift angle is recognized as an important indicator. If we have to estimate maximum inter-story drift angle very precisely, we need to install accelerometers on all floors. However, it is not realistic due to the cost. In many methods to estimate the response using small number of accelerometers, the excitation (input) is assumed to be available. However, in some cases, some sensors including the input sensor may not be available. Thus, in this paper, we propose a method for the estimating inter-story drift angle using small number of accelerometers without knowing input information. The proposed method is based on two assumptions. One is that the response is represented by the superposition of the response of only lower modes. The other is that mode vectors and participation factors are available from the structural design model. Based on the assumption, first, we estimate modal frequencies and damping ratios using the subspace method from obtained acceleration data. Second, we decompose observed acceleration data to each mode by solving simultaneous equations using pseudo-inverse matrix. Third, we calculate mode response by focusing on the vibration equation of each mode. It was verified that this method could successfully estimate the modal response as well as the inter-story drift angles.

Acoustic emission is a vital non-destructive testing technique and is widely used in industry for damage detection, localisation and characterization. The latter two aspects are particularly challenging, as AE data are typically noisy. What is more, elastic waves generated by an AE event, propagate through a structural path and are significantly distorted. This effect is particularly prominent for thin elastic plates. In these media the dispersion phenomenon results in severe localisation and characterization issues. Traditional Time Difference of Arrival methods for localisation techniques typically fail when signals are highly dispersive. Hence, algorithms capable of dispersion compensation are sought. This paper presents a method based on the Time - Distance Domain Transform for an accurate AE event localisation. The source localisation is found through a minimization problem. The proposed technique focuses on transforming the time signal to the distance domain response, which would be recorded at the source. Only, basic elastic material properties and plate thickness are used in the approach, avoiding arbitrary parameters tuning.

A number of techniques are available for acoustic source localization in isotropic plates without knowing the material properties of the plate. However, for a highly anisotropic plate acoustic source localization requires some knowledge of the plate material properties or its group velocity profile. In absence of this information one requires a large number of sensors to predict the acoustic source point in the plate. All proposed techniques for acoustic source localization with a few sensors assume the straight line propagation of waves from the source to the receiving sensor with an average group velocity when the plate material properties are not known. However, this assumption is not true for an anisotropic plate. Although the currently available techniques work well for weakly anisotropic plates since the wave path does not deviate significantly from the straight line propagation they fail miserably for highly anisotropic plates.

In this paper acoustic source is localized in an anisotropic plate when non-circular wave front is generated. Direction vectors of wave fronts are obtained from the Time-Difference-Of-Arrivals (TDOA) at three sensors placed in a cluster. Four such direction vectors are then utilized in geometric vector analysis to accurately obtain the acoustic source location. The proposed technique is illustrated on an orthotropic plate that generates rhombus shaped wave front. It should be noted that the proposed technique does not require wave propagation along a straight

Nonlinear elastic guided waves find application in various disciplines of science and engineering, such as non- destructive testing and structural health monitoring. Recent recognition and quantification of their amplitude- dependent changes in spectral properties has contributed to the development of new monitoring concepts for mechanical structures. The focus of this work is to investigate and predict amplitude-dependent shifts in Lamb wave dispersion curves. The theory for frequency/wavenumber shifts for plate waves, based on a Lindstedt-Poincaré perturbation approach, was presented by the authors in previous years. Equivalently, spectral properties changes can be seen as wavelength contraction/elongation. Within the proposed framework, the wavelength of a Lamb wave depends on several factors; e.g., wave amplitude and second-, third- and fourth-order elastic constants, and others. Various types of nonlinear effects are considered in presented studies. Sensitivity studies for model parameters, i.e. higher-order elastic constants, are performed to quantify their influence on Lamb wave frequency/wavenumber shifting, and to identify the key parameters governing wavelength tuning.

Targeting quantitative estimate of fatigue damage, a dedicated analytical model was developed based on the modal decomposition method and the variational principle. The model well interprets the contact acoustic nonlinearity induced by a “breathing” crack in a two-dimensional scenario, and the nonlinear characteristics of guided ultrasonic waves (GUWs) (e.g., reflection, transmission, mode conversion and high-order generation) when GUWs traversing the crack. Based on the model, a second-order reflection index was defined. Using the index, a fatigue damage evaluation framework was established, showing demonstrated capacity of estimating the severity of fatigue damage in a quantitative manner. The approach, in principle, does not entail a benchmarking process against baseline signals pre-acquired from pristine counterparts. The results obtained using the analytical modeling were compared with those from finite element simulation, showing good coincidence. Limitations of the model were also discussed.

Precursor damage state quantification can be helpful for safety and operation of aircraft and defense equipment’s. Damage develops in the composite material in the form of matrix cracking, fiber breakages and deboning, etc. However, detection and quantification of the damage modes at their very early stage is not possible unless modifications of the existing indispensable techniques are conceived, particularly for the quantification of multiscale damages at their early stage. Here, we present a novel nonlocal mechanics based damage detection technique for precursor damage state quantification. Micro-continuum physics is used by modifying the Christoffel equation. American society of testing and materials (ASTM) standard woven carbon fiber (CFRP) specimens were tested under Tension-Tension fatigue loading at the interval of 25,000 cycles until 500,000 cycles. Scanning Acoustic Microcopy (SAM) and Optical Microscopy (OM) were used to examine the damage development at the same interval. Surface Acoustic Wave (SAW) velocity profile on a representative volume element (RVE) of the specimen were calculated at the regular interval of 50,000 cycles. Nonlocal parameters were calculated form the micromorphic wave dispersion curve at a particular frequency of 50 MHz. We used a previously formulated parameter called “Damage entropy” which is a measure of the damage growth in the material calculated with the loading cycle. Damage entropy (DE) was calculated at every pixel on the RVE and the mean of DE was plotted at the loading interval of 25,000 cycle. Growth of DE with fatigue loading cycles was observed. Optical Imaging also performed at the interval of 25,000 cycles to investigate the development of damage inside the materials. We also calculated the mean value of the Surface Acoustic Wave (SAW) velocity and plotted with fatigue cycle which is correlated further with Damage Entropy (DE). Statistical analysis of the Surface Acoustic Wave profile (SAW) obtained at different fatigue cycles was performed to extract the useful information about the damage state. This study has potential to investigate progressive damage evolution and to quantify at different fatigue cycles.

This paper presents a parallelized modeling technique for the efficient simulation of nonlinear ultrasonics introduced by the wave interaction with fatigue cracks. The elastodynamic wave equations with contact effects are formulated using an explicit Local Interaction Simulation Approach (LISA). The LISA formulation is extended to capture the contact-impact phenomena during the wave damage interaction based on the penalty method. A Coulomb friction model is integrated into the computation procedure to capture the stick-slip contact shear motion. The LISA procedure is coded using the Compute Unified Device Architecture (CUDA), which enables the highly parallelized supercomputing on powerful graphic cards. Both the explicit contact formulation and the parallel feature facilitates LISA’s superb computational efficiency over the conventional finite element method (FEM). The theoretical formulations based on the penalty method is introduced and a guideline for the proper choice of the contact stiffness is given. The convergence behavior of the solution under various contact stiffness values is examined. A numerical benchmark problem is used to investigate the new LISA formulation and results are compared with a conventional contact finite element solution. Various nonlinear ultrasonic phenomena are successfully captured using this contact LISA formulation, including the generation of nonlinear higher harmonic responses. Nonlinear mode conversion of guided waves at fatigue cracks is also studied.

This paper deals with analysis of guided waves mode conversion phenomenon in fiber reinforced composite materials. Mode conversion phenomenon may take place when propagating elastic guided waves interact with discontinuities in the composite waveguide. The examples of such discontinuities are sudden thickness change or delamination between layers in composite material. In this paper, analysis of mode conversion phenomenon is based on full wave-field signals. In the full wave-field approach signals representing propagation of elastic waves are gathered from dense mesh of points that span over investigated area of composite part. This allow to animate the guided wave propagation. The reported analysis is based on signals resulting from numerical calculations and experimental measurements. In both cases defect in the form of delamination is considered. In the case of numerical research, Spectral Element Method (SEM) is utilized, in which a mesh is composed of 3D elements. Numerical model includes also piezoelectric transducer. Full wave-field experimental measurements are conducted by using piezoelectric transducer for guided wave excitation and Scanning Laser Doppler Vibrometer (SLDV) for sensing.

Crack propagation and branching are modeled using nonlocal peridynamic theory. One major advantage of this nonlocal theory based analysis tool is the unifying approach towards material behavior modeling - irrespective of whether the crack is formed in the material or not. No separate damage law is needed for crack initiation and propagation. This theory overcomes the weaknesses of existing continuum mechanics based numerical tools (e.g. FEM, XFEM etc.) for identifying fracture modes and does not require any simplifying assumptions. Cracks grow autonomously and not necessarily along a prescribed path. However, in some special situations such as in case of ductile fracture, the damage evolution and failure depend on parameters characterizing the local stress state instead of peridynamic damage modeling technique developed for brittle fracture. For brittle fracture modeling the bond is simply broken when the failure criterion is satisfied. This simulation helps us to design more reliable modeling tool for crack propagation and branching in both brittle and ductile materials. Peridynamic analysis has been found to be very demanding computationally, particularly for real-world structures (e.g. vehicles, aircrafts, etc.). It also requires a very expensive visualization process. The goal of this paper is to bring awareness to researchers the impact of this cutting-edge simulation tool for a better understanding of the cracked material response. A computer code has been developed to implement the peridynamic theory based modeling tool for two-dimensional analysis. A good agreement between our predictions and previously published results is observed. Some interesting new results that have not been reported earlier by others are also obtained and presented in this paper. The final objective of this investigation is to increase the mechanics knowledge of self-similar and self-affine cracks.

Attractive properties of guided waves provides very unique potential for characterization of incipient damage, particularly in plate-like structures. Among other properties, guided waves can propagate over long distances and can be used to monitor hidden structural features and components. On the other hand, guided propagation brings substantial challenges for data analysis. Signal processing techniques are frequently supported by numerical simulations in order to facilitate problem solution. When employing numerical models additional sources of errors are introduced. These can play significant role for design and development of a wave-based monitoring strategy. Hence, the paper presents an investigation of numerical models for guided waves generation, propagation and sensing. Numerical dispersion analysis, for guided waves in plates, based on the LISA approach is presented and discussed in the paper. Both dispersion and modal amplitudes characteristics are analysed. It is shown that wave propagation in a numerical model resembles propagation in a periodic medium. Consequently, Lamb wave propagation close to numerical Brillouin zone is investigated and characterized.

Carbon fiber laminate composites, consisting of layers of polymer matrix reinforced with high strength carbon fibers, are increasingly employed for aerospace structures. They offer advantages for aerospace applications, e.g., good strength to weight ratio. However, impact during the operation and servicing of the aircraft can lead to barely visible and difficult to detect damage. Depending on the severity of the impact, delaminations can occur, reducing the load carrying capacity of the structure. Efficient structural health monitoring of composite panels can be achieved using guided ultrasonic waves propagating along the structure. The guided ultrasonic wave (A0 Lamb wave mode) scattering at delaminations was modelled using full three-dimensional Finite Element (FE) simulations. The influence of the delamination size was systematically investigated from a parameter study. The angular dependency of the scattered guided wave amplitude was calculated using a baseline subtraction method. A significant influence of the delamination width on the guided wave scattering was found. The sensitivity of guided waves for the detection of barely visible impact damage in composite panels has been predicted.

Helical guided waves in pipelines are studied under the effects of pressurization stresses from a contained liquid. The pipeline is approximated by an “unwrapped” plate waveguide, and a transfer matrix method is used to solve for guided wave velocity and attenuation dispersion curves in a multilayered plate waveguide subject to an arbitrary triaxial state of initial stress. The matrix-based model is able to incorporate both elastic and viscoelastic solid materials, as well as approximate non-uniform distributions in initial stress through the thickness of a waveguide. Experiments on a steel pipe filled with pressurized water are carried out to validate the modeling approach.

Local interaction simulation approach (LISA) is a highly parallelizable numerical scheme for guided wave simulation in structural health monitoring (SHM). This paper addresses the issue of simulating wave propagation in unbounded domain through the implementation of non-reflective boundary (NRB) in LISA. In this study, two different categories of NRB, i.e., the non-reflective boundary condition (NRBC) and the absorbing boundary layer (ABL), have been investigated in the parallelized LISA scheme. For the implementation of NRBC, a set of general LISA equations considering the effect from boundary stress is obtained first. As a simple example, the Lysmer and Kuhlemeyer (L-K) model is applied here to demonstrate the easiness of NRBC implementation in LISA. As a representative of ABL implementation, the LISA scheme incorporating the absorbing layers with increasing damping (ALID) is also proposed, based on elasto-dynamic equations considering damping effect. Finally, an effective hybrid model combining L-K and ALID methods in LISA is developed, and guidelines for implementing the hybrid model is presented. Case studies on a three-dimensional plate model compares the performance of hybrid method to that of L-K and ALID acting independently. The simulation results demonstrate that best absorbing efficiency is achieved with the hybrid method.

A full-scale lower wing panel made of composite material has been designed, manufactured and sensorised within the European Funded research project named SARISTU. The authors contributed to the whole development of the system, from design to implementation as well as to the impacts campaign phase where Barely Visible and Visible Damages (BVID and VID) are to be artificially induced on the panel by a pneumatic impact machine. This work summarise part of the experimental results related to damages production, their assessment by C-SCAN as reference NDT method as well as damage detection of delimitations by a guided waves based SHM. The SHM system is made by customized piezoelectric patches secondary bonded on the wing plate acting both as guided waves sources and receivers. The paper will deal mostly with the experimental impact campaign and the signal analyses carried out to extract the metrics more sensitive to damages induced. Image reconstruction of the damages dimensions and shapes will be also described based mostly on the combination of metrics maps over the plate partial surfaces. Finally a comparison of damages maps obtained by the SHM approach and those obtained by “classic” C-SCAN will be presented analyzing briefly pros and cons of the two different approached as a combination to the most effective structural maintenance scenario of a commercial aircraft.

Non-cumulative higher and sub-harmonic Lamb wave mode generation as a result of partial-debond of piezoelectric wafer transducers (PWT) bonded onto an Aluminium plate, is numerically investigated and experimentally validated. The influence of excitation frequency on the extent of nonlinearity due to clapping mechanism of the partially-debonded PWTs is discussed. A set of specific frequency range is arrived at based on the Eigen-value and Harmonic analyses of PWTs used in the model. It is found that, at these frequencies, which are integral multiple of the first width-direction mode of a PWT, significantly higher amplitudes of higher-harmonics are observed. It is also seen that at specific debond-positions and lengths, sharp sub-harmonics in addition to higher-harmonics are present. Signal processing is carried out using Fast Fourier transform, which is normalized for comparisons.

Modeling and simulating guided wave propagation in complex, geometric structures is a topic of significant interest in structural health monitoring. These models have the potential to benefit damage detection, localization, and characterization in structures where traditional algorithms fail. Numerical modelling (for example, using finite element or semi-analytical finite element methods) is a popular approach for simulating complex wave behavior. Yet, using these models to improve experimental data analysis remains difficult. Numerical simulations and experimental data rarely match due to uncertainty in the properties of the structures and the guided waves traveling within them. As a result, there is a significant need to reduce this uncertainty by incorporating experimental data into the models. In this paper, we present a dictionary learning framework to address this challenge. Specifically, use dictionary learning to combine numerical wavefield simulations with 24 simulated guided wave measurements with different frequency-dependent velocity characteristics (emulating an experimental system) to make accurate, global predictions about experimental wave behavior. From just 24 measurements, we show that we can predict and extrapolate guided wave behavior with accuracies greater than 92%.

A method based on the use of enhanced filtered Hilbert envelope of the wave signal was developed in order to monitor the height of condensed water through the wall of steam pipes having dynamic flow conditions. A prototype testbed was designed and fabricated in this study to simulate the dynamic flow conditions including the air stream flowing above the water and bubble induced disturbance. A dual-transducer was used to perform the test as a basis for the multiple transducers system to facilitate the detectability and reliability for long term monitoring of the condensed water height in dynamic conditions. The results demonstrated that the method of measuring the water height using multiple-transducer system employing the developed novel signal processing technique is an efficient and accurate tool for practical applications.

In recent years, ultrasonic guided waves gained attention for reliable testing and characterization of metals and composites. Guided wave modes are excited and detected by PZT (Lead Zirconate Titanate) transducers either in transmission or reflection mode. In this study guided waves are excited and detected in the transmission mode and the phase change of the propagating wave modes are recorded. In most of the other studies reported in the literature, the change in the received signal strength (amplitude) is investigated with varying degrees of damage while in this study the change in phase is correlated with the extent of damage. Feature extraction techniques are used for extracting phase and time-frequency information. The main advantage of this approach is that the bonding condition between the transducer and the specimen does not affect the phase while it can affect the strength of recorded signal. Therefore, if the specimen is not damaged but the transducer-specimen bonding is deteriorated then the received signal strength is altered but the phase remains same and thus false positive predictions for damage can be avoided.

The efficacy of asphalt rejuvenator on restoring the properties of oxidatively aged asphalt was tested via a non-collinear ultrasonic subsurface wave mixing technique modified for field use. Longitudinal transducers were mounted on angle wedges to generate subsurface dilatational waves to allow for pavement evaluation when there is only access to one side. Because in the field the asphalt concrete (AC) pavement properties (i.e., ultrasonic velocities and attenuations) are unknown, a pre-determined fixed incident angle (based on the AC mixture type) was used, which allows for practical implementation in the field. Oxidative aged AC specimens were coated with rejuvenator (10% by weight of the binder) and left to dwell for varying amounts of time. Once the dwell time reached the desired amount, the specimen was immediately ultrasonically tested. The frequency ratio, f₂/f₁, at which the interaction took place and the normalized nonlinear wave generation parameter, β/β₀, were recorded and compared against a reference plot. It was observed that the rejuvenator had the effect of restoring the nonlinear properties to those corresponding to a virgin sample after a sufficient amount of dwell time. The ability of the rejuvenator to fully penetrate and act on the binder was observed to be dependent on the porosity and aggregate structure, and thus varied for each specimen. As a result, some portions of the binder were restored to a greater extent than others. This non-uniform nature was captured via the nonlinear ultrasonic technique.

The paper discusses the use of wideband excitation in nonlinear vibro-acoustic modulation technique (VAM) used for damage detection. In its original form, two mono-harmonic signals (low and high frequency) are used for excitation. The low frequency excitation is typically selected based on a modal analysis test and high frequency excitation is selected arbitrarily in the ultrasonic frequency range. This paper presents a different approach with use of wideband excitation signals. The proposed approach gives the possibility to simplify the testing procedure by omitting the modal test used to determine the value of low frequency excitation. Simultaneous use of wideband excitation for high frequency solves the ambiguity related to the selection of the frequency of acoustic wave. Broadband excitation signals require, however, more elaborate signal processing methods to determine the intensity of modulation for a given bandwidth. The paper discusses the proposed approach and the related signal processing procedure. Experimental validation of the proposed technique is performed on a laminated composite plate with a barely visible impact damage that was generated in an impact test. Piezoceramic actuators are used for vibration excitation and a scanning laser vibrometer is used for noncontact data acquisition.

This paper presents a damage visualization technique using a fully noncontact laser ultrasonic measurement system and a synchronized scanning strategy. The noncontact laser ultrasonic measurement system is composed of a Q-switched Nd:YAG laser for ultrasonic wave generation and a laser Doppler vibrometer (LDV) for ultrasonic wave detection. The laser beams for ultrasonic wave generation and detection are shot on the target structure with a constant and tiny distance, and these two laser beams are synchronously moved over the scanning area. Compared with conventional laser scanning strategies, the ultrasonic responses detected through the synchronized scanning strategy owns a much higher and more stable signal to noise ratio and the scanning time can be significantly reduced with less time averaging. By spatial comparison in the scanning area, damage can be detected and visualized without relying on baseline data obtained from the pristine condition of the target structure. In this paper, the developed technique is validated by visualization hidden corrosion in a steel straight pipe and a steel elbow pipe.

Numerical tools, which are used to simulate complex phenomena for models of complicated shapes suffer from either long computational time or accuracy. Hence, new modeling and simulation tools, which could offer reliable results within reasonable time periods, are highly demanded. Among other approaches, the nonlocal methods have appeared to fulfill these requirements quite efficiently and opened new perspectives for accurate simulations based on crude meshes of the model's degrees of freedom. In the paper, the preliminary results are shown for simulations of the phenomenon of temperature-dependent crack-wave interaction for elastic wave propagation in a model of an aluminum plate. Semi-nonlocal finite differences are considered to solve the problem of thermoelasticity - based on the discretization schemes, which were already proposed by the authors and taken from the previously published work. Numerical modeling is used to examine wave propagation primarily in the vicinity of a notch. Both displacement and temperature fields are sought in the investigated case study.

The concept of the coiling up space, based on which artificial structures could exhibit extreme acoustic properties, such as high refractive index, double negativity, near-zero index, etc., have been investigated intensively recently due to the fascinating underlying physics and diverse potential applications [1-3]. One of the most important functionality is the ability to shrink bulky structures into deep sub-wavelength scale. It is therefore intuitive to prospect that the concept of coiling up space, if could be extended into the perforated system, will benefit to significantly reduce the total thickness while keeping total absorption. Conventional acoustic absorbers require a structure with a thickness comparable to the working wavelength, resulting major obstacles in real applications in low frequency range. We present a metasurface-based perfect absorber capable of achieving the total absorption of acoustic wave in extremely low frequency region. The metasurface possessing a deep sub-wavelength thickness down to a feature size of ~ lambda/223 is composed of a perforated plate and a coiled coplanar air chamber. Simulations based on fully coupled acoustic with thermodynamic equations and theoretical impedance analysis are utilized to reveal the underlying physics and the acoustic performances, showing an excellent agreement. Our realization should have high impact on amount of applications due to the extremely thin thickness, easy fabrication and high efficiency of the proposed structure. References 1. Z. Liang and J. Li, Phys. Rev. Lett. 108, 114301 (2012). 2. Y. Li, B. Liang, X. Tao, X. F. Zhu, X. Y. Zou, and J. C. Cheng, Appl. Phys. Lett. 101, 233508 (2012). 3. Y. Xie, W. Wang, H. Chen, A. Konneker, B. I. Popa, and S. A. Cummer, Nat. Commun. 5, 5553 (2014).

We illustrate the design of acoustic metasurfaces based on geometric tapers and embedded in thin-plate structures. The metasurface is an engineered discontinuity that enables anomalous refraction of guided wave modes according to the Generalized Snell’s Law. Locally-resonant geometric torus-like tapers are designed in order to achieve metasurfaces having discrete phase-shift profiles that enable a high level of control of refraction of the wavefronts. Results of numerical simulations show that anomalous refraction can be achieved on transmitted anti-symmetric modes (A0) either when using a symmetric (S0) or anti-symmetric (A0) incident wave, where the former case clearly involves mode conversion mechanisms.

Sorting microparticles (or cells, or bacteria) is significant for scientific, medical and industrial purposes. Research groups have used lithium niobate SAW devices to produce standing waves, and then to align microparticles at the node lines in polydimethylsiloxane (PDMS, silicone) microfluidic channels. The “tilted angle” (skewed) configuration is a recent breakthrough producing particle trajectories that cross multiple node lines, making it practical to sort particles. However, lithium niobate wafers and PDMS microfluidic channels are not mechanically robust. We demonstrate “tilted angle” microparticle sorting in novel devices that are robust, rapidly prototyped, and manufacturable. We form our microfluidic system in a rigid polymethyl methacrylate (PMMA, acrylic) prism, sandwiched by lead-zirconium-titanate (PZT) wafers, operating in through-thickness mode with inertial backing, that produce standing bulk waves. The overall configuration is compact and mechanically robust, and actuating PZT wafers in through-thickness mode is highly efficient. Moving to this novel configuration introduced new acoustics questions involving internal reflections, but we show experimental images confirming the intended nodal geometry. Microparticles in “tilted angle” devices display undulating trajectories, where deviation from the straight path increases with particle diameter and with excitation voltage to create the mechanism by which particles are sorted. We show a simplified analytical model by which a “phase space” is constructed to characterize effective particle sorting, and we compare our experimental data to the predictions from that simplified model; precise correlation is not expected and is not observed, but the important physical trends from the model are paralleled in the measured particle trajectories.

Acoustic emission (AE) caused by the growth of fatigue crack were well studied by researchers. Conventional approaches predominantly are based on statistical analysis. In this study we focus on identifying geometric features of the crack from the AE signals using physics based approach. One of the main challenges of this approach is to develop a physics of materials based understanding of the generation and propagation of acoustic emissions due to the growth of a fatigue crack. As the geometry changes due to the crack growth, so does the local vibration modes around the crack. Our aim is to understand these changing local vibration modes and find possible relation between the AE signal features and the geometric features of the crack. Finite element (FE) analysis was used to model AE events due to fatigue crack growth. This was done using dipole excitation at the crack tips. Harmonic analysis was also performed on these FE models to understand the local vibration modes. Experimental study was carried out to verify these results. Piezoelectric wafer active sensors (PWAS) were used to excite cracked specimen and the local vibration modes were captured using laser Doppler vibrometry. The preliminary results show that the AE signals do carry the information related to the crack geometry.

Acoustic emission is widely used for monitoring pressure vessels, pipes, critical infrastructure, as well as land, sea and air vehicles. It is one of dominant approaches to explore material degradation under fatigue and events leading to material fracture. Addressing a recent interest in structural health monitoring of space vehicles, a need has emerged to evaluate material deterioration due to thermal fatigue during spacecraft atmospheric reentry. Thermal fatigue experiments were conducted, in which aluminum plates were subjected to localized heating and acoustic emission was monitoring by embedded and conventional acoustic emission sensors positioned at various distances from a heat source. At the same time, surface temperature of aluminum plates was monitored using an IR camera. Acoustic emission counts collected by embedded sensors were compared to counts measured with conventional acoustic emission sensors. Both types of sensors show noticeable increase of acoustic emission activity as localized heating source was applied to aluminum plates. Experimental data demonstrate correlation between temperature increase on the surface of the plates and increase in measured acoustic emission activity. It is concluded that under particular conditions, embedded piezoelectric wafer active sensors can be used for acoustic emission monitoring of thermally-induced structural degradation.

In the application of Structural Health Monitoring (SHM), processing the online-acquired data plays a very important role, among which wavelet transform is an outstanding tool and compared to Fourier transform, it handles the nonstationary behaviors in the time series in an adaptive fashion. When dealing with time-variant data, there are uncertainties from numerous resources inherent to the feature estimation, such as measurement noise, operational and environmental variability, hardware limitation, etc. The corruption from uncertainty will make the data interpretation ambiguous and thereby dramatically degrades the decision quality with regard to the occurrence, location, severity, and extent of damages. This paper derives a probabilistic model to quantify analytically the uncertainty of wavelet transform feature as a random variable, and variance is derived analytically in this work. Considering central limit theorem, Gaussian probability density function characterizes the distribution and this has been validated via Monte Carlo testing. By fully characterizing the uncertainty, the damage detection implementations may be facilitated with a quantified false alarm rate and miss catch rate.

Automated defect detection from optical images is an efficient non-destructive evaluation technique for surface and structure health inspection. Background subtraction is a widely-used technique for automated defect detection. In background subtraction, an image of the part with no defect, called background image, is generated and subtracted from the defective part image; the resulted large differences are then considered as defects. In this paper, a new background generation technique is proposed that allows for efficient defect detection at a low-computational load. In this technique, a defect-free region is generated by approximately locating defects and removing them from the original image. The resulted defect-free region is now used to generate the background. The procedure and performance of the algorithm is illustrated by an example.

Carbon Fibre Reinforced Polymers (CFRP) are more and more used in many branches of industry. Researchers are developing numerous techniques of non-destructive assessment of the structures made out of CFRP such as guided waves, ultrasonics, laser induced fluorescence and others. In this research we focus on electromechanical impedance (EMI) technique. In this technique a piezoelectric sensor is either surface mounted or embedded into investigated host structure. The electrical quantities of the sensor are measured for wide frequency range. Due to piezoelectric effect the electrical response of the sensor is related to mechanical response of the structure to which the sensors is bonded to. In the reported research impedance spectra in the vicinity of the transducer thickness mode were investigated as well as the lower frequency range. The spectra that were analysed were gathered from samples with surface treatment such as thermal degradation and samples adhesively bonded with film adhesive with symmetric and unsymmetric bond. Moreover, the samples with modified adhesive bonds were investigated. These spectra for different cases were compared with reference measurement results gathered from pristine samples. Numerical indexes for comparison of the EMI characteristics were proposed. The comparison of the indexes was also conducted. In the experimental part of the research the piezoelectric transducer was mounted at the sample surface. Measurements were conducted using HIOKI Impedance Analyzer IM3570.

Conventionally, structural health monitoring (SHM) has been primarily concerned with sensing, identifying, locating, and determining the severity of damage present in a structure that is in a static state. Instead, this study will investigate adapting the impedance SHM method to rapidly evaluate a mechanical system during a dynamic event. Also in contrast to conventional SHM, the objective is not to detect damage but instead to detect changes in the boundary conditions as they occur during a dynamic event. Rapid detection of changes in boundary conditions in highly dynamic environments has the potential to be used in a wide variety of applications, including the aerospace, civil, and mining industries. A key feature of this work will be the use of frequency ranges higher than what is typically used for SHM impedance measurements, in the range of several MHz. Using such high frequencies will allow for faster measurements of impedance, thus enabling the capture of variations in boundary conditions as they change during a dynamic event. An existing analytical model from the literature for electromechanical impedance based SHM will be utilized for this study.

The paper illustrates a general equation in a new form, which allows calculating the characteristic frequencies of any kind of epicyclic gear sets with a ring, a sun, and planets. Moreover, presented equation takes into account corrected teeth (i.e. where the equality 2P+S=R is not fulfilled). This happens when gearboxes contain gears where corrected teeth procedure was adopted during designing stage. Presented solution can refine the configuration modules of the Condition Monitoring Systems (CMS) in such a way that allows to configure systems into larger groups than now available, i.e. multistage gear sets systems with epicyclic gears. Such CMS are capable of early mechanical faults detection, which prevents from costly critical repairs. For instance, fault detection of wind turbines is typically based on vibration and process signals analysis. Illustrated possible enhancement of configuration module is the basis for determining the energy bands in the spectra and envelope spectra in the process of identifying characteristic frequencies caused by gear defects.

This paper verified a generic and efficient assessment concept for probabilistic fatigue life management. The concept is developed based on an integration of damage tolerance methodology, simulations methods^{1, 2}, and a probabilistic algorithm RPI (recursive probability integration)^3-9 considering maintenance for damage tolerance and risk-based fatigue life management. RPI is an efficient semi-analytical probabilistic method for risk assessment subjected to various uncertainties such as the variability in material properties including crack growth rate, initial flaw size, repair quality, random process modeling of flight loads for failure analysis, and inspection reliability represented by probability of detection (POD). In addition, unlike traditional Monte Carlo simulations (MCS) which requires a rerun of MCS when maintenance plan is changed, RPI can repeatedly use a small set of baseline random crack growth histories excluding maintenance related parameters from a single MCS for various maintenance plans. In order to fully appreciate the RPI method, a verification procedure was performed. In this study, MC simulations in the orders of several hundred billions were conducted for various flight conditions, material properties, and inspection scheduling, POD and repair/replacement strategies. Since the MC simulations are time-consuming methods, the simulations were conducted parallelly on DoD High Performance Computers (HPC) using a specialized random number generator for parallel computing. The study has shown that RPI method is several orders of magnitude more efficient than traditional Monte Carlo simulations.

In this work, the system design, integration, and wind tunnel experimental evaluation are presented for a bioinspired self-sensing intelligent composite unmanned aerial vehicle (UAV) wing. A total of 148 micro-sensors, including piezoelectric, strain, and temperature sensors, in the form of stretchable sensor networks are embedded in the layup of a composite wing in order to enable its self-sensing capabilities. Novel stochastic system identification techniques based on time series models and statistical parameter estimation are employed in order to accurately interpret the sensing data and extract real-time information on the coupled air flow-structural dynamics. Special emphasis is given to the wind tunnel experimental assessment under various flight conditions defined by multiple airspeeds and angles of attack. A novel modeling approach based on the recently introduced Vector-dependent Functionally Pooled (VFP) model structure is employed for the stochastic identification of the "global" coupled airflow-structural dynamics of the wing and their correlation with dynamic utter and stall. The obtained results demonstrate the successful system-level integration and effectiveness of the stochastic identification approach, thus opening new perspectives for the state sensing and awareness capabilities of the next generation of "fly-by-fee" UAVs.

Flexible and wearable sensors for human monitoring have received increased attention. Besides detecting motion and physical activity, measuring human vital signals (e.g., respiration rate and body temperature) provide rich data for assessing subjects’ physiological or psychological condition. Instead of using conventional, bulky, sensing transducers, the objective of this study was to design and test a wearable, fabric-like sensing system. In particular, multi-walled carbon nanotube (MWCNT)-latex thin films of different MWCNT concentrations were first fabricated using spray coating. Freestanding MWCNT-latex films were then sandwiched between two layers of flexible fabric using iron-on adhesive to form the wearable sensor. Second, to characterize its strain sensing properties, the fabric sensors were subjected to uniaxial and cyclic tensile load tests, and they exhibited relatively stable electromechanical responses. Finally, the wearable sensors were placed on a human subject for monitoring simple motions and for validating their practical strain sensing performance. Overall, the wearable fabric sensor design exhibited advances such as flexibility, ease of fabrication, light weight, low cost, noninvasiveness, and user comfort.

A sensitive fluid viscosity and flow measurement device using optical intensity based sensing is presented. The sensing principle makes use of the damping characteristic of a vibrating optical fiber probe with approximate hinge-free end configuration. The viscosity and mass flow are determined by measuring the vibration of a sinusoidally excited tapered optical fiber under different flow conditions. By measuring the frequency response of the fiber probe, viscosity and mass flow can be deduced from the damping coefficient of the response. The concepts and experimental data presented demonstrate and refine the sensing process of the proposed system.

Ultrasonic inspection of multiple-rivet-hole lap joint cracks has been introduced using combined analytical and finite element approach (CAFA). Finite element analyses have been performed on local damage area in spite of the whole large structure and transfer function based analytical model is used to analyze the full structure. “Scattered cube” of complex valued wave damage interaction coefficient (WDIC) that involves scattering and mode conversion of Lamb waves around the damage is used as coupling between analytical and FEM simulation. WDIC is captured for multiple angles of incident Lamb mode (S0 and A0) over the frequency domain to analyze the cracks of multiple-rivet-hole lap joint. By analyzing the scattered cube of WDICs over the frequency domain and azimuthal angles the optimum parameters can be determined for each angle of incidence and the most sensitive signals are obtained using WaveformRevealer2D (WFR2D). These sensitive signals confirm the detection of the butterfly cracks in rivet holes through the installment of the transmitting and sensing PWASs in the proper locations and selecting the right frequency of excitation.

Fiber Bragg grating (FBG) sensors offer a significant advantage for structural health monitoring due to their ability to simultaneously monitor both static and dynamic strain while being durable, lightweight, capable of multiplexing, and immune to electro-magnetic interference. Drawing upon the benefits of FBG sensors, this research explores the use of a series of long-gage fiber optic sensors for damage detection of a structure through dynamic strain measurements and curvature analysis. Typically structural monitoring relies upon detecting structural changes through frequency and acceleration based analysis. However, curvature and strain based analysis may be a more reliable means for structural monitoring as they show more sensitivity to damage compared to modal parameters such as displacement mode shapes and natural frequency. Additionally, long gage FBG strain sensors offer a promising alternative to traditional dynamic measurement methods as the curvature can be computed directly from the FBG strain measurements without the need for numerical differentiation. Small scale experimental testing was performed using an aluminum beam instrumented with a series of FBG optical fiber sensors. Dynamic strain measurements were obtained as the aluminum beam was subjected to various loading and support conditions. From this, a novel normalized parameter based on the curvature from the dynamic strain measurements has been identified as a potential damage sensitive feature. Theoretical predictions and experimental data were compared and conclusions carried out. The results demonstrated the potential of the novel normalized parameter to facilitate dynamic monitoring at both the local and global scale, thus allowing assessment of the structures health.

Structural Health Monitoring seeks to characterize the performance of a structure from combinations of recorded sensor data and analytic techniques. Temperature is normally considered noise in this analysis, obstructing the goal measuring the elastic response of the structure. While these elastic loads do help characterize a portion of structural behavior, the thermal loads on a structure can induce comparable strains to these elastic loads. Characterizing a relationship between the temperature of the structure and the resultant strain and displacement can provide a deep understanding of the structural condition. In order to begin characterizing this 3-dimensional relationship, time periods with relatively steadystate, uniform temperature distributions need to be identified from the measured data. These periods of uniform temperature distribution in the structure show a thermal response as free as possible from thermal gradients across the structure. These steady-state periods help create a signature of the structure when analyzed with the relevant strain and displacement measurements of the structure. An algorithm for finding these uniform distributions was created to identify these desirable time periods with data of interest. Finding time periods with a completely uniform temperature distribution can be unreasonable, so a suitable temperature interval was chosen to produce a set of data with a reasonable approximation to a uniform distribution, while still providing a large enough set of data to produce meaningful results. These time intervals provide the necessary temperature, strain, and displacement measurements to characterize a signature for the structure, providing a more in-depth analysis in SHM.

In structural sensing applications, wireless sensing systems have drawn great interest owing to faster installation process and lower system cost compared to the traditional cabled systems. As a new-generation wireless sensing system, Martlet features high-speed data acquisition and extensible layout, which allows easy interfacing with various types of sensors. This paper presents a field test of the Martlet sensing system installed at an in-service pre-stressed concrete highway bridge on SR113 over Dry Creek in Bartow County, Georgia. Four types of sensors are interfaced with Martlet in this test, including accelerometers, strain gages, strain transducers and magnetostrictive displacement sensors. In addition, thermocouples are used to monitor the temperature change of the bridge through the day. The acceleration, strain and displacement response of the bridge due to traffic and ambient excitations are measured. To obtain the modal properties of the bridge, hammer impact tests are also performed. The results from the field test demonstrate the reliability of the Martlet wireless sensing system. In addition, detailed modal properties of the bridge are extracted from the acceleration data collected in the test.

Temperature monitoring has been of increased importance in recent years due to the need for temperature measurements in order to compensate other measurement parameters, such as strain, and the increased attention to understanding thermal behaviors of structures in order to assess their performance and condition. To ensure the accuracy of thermal compensation and study of thermal behavior, reliable long-term temperature measurements are required. In this paper, two methods that are aimed at validating long-term temperature measurements are created and their application is presented. The methods differ in the type of data they use for the purpose of validation. The first method relies on the existence of two independent temperature sensors at the same location. Validation is performed by comparing the measurements from the two sensors to one another, and discrepancies between the two data sets indicate malfunction or drift in at least one of the sensors. The second method is applicable to the more general case where only one temperature sensor is available at a given location. The method thus utilizes ambient temperature data from a nearby weather tower to validate measurements from the sensor. The two methods are applied to temperature measurements from FBG sensors installed on Streicker Bridge on the Princeton University campus. The methods successfully identified and characterized malfunction and drift in some of the sensors and confirmed stable measurements in other sensors.

By definition, the neutral axis of a loaded composite beam structure is the curve along which the section experiences zero bending strain. When no axial loading is present, the location of the neutral axis passes through the centroid of stiffness of the beam cross-section. In the presence of damage, the centroid of stiffness, as well as the neutral axis, shift from the healthy position. The concept of neutral axis can be widely applied to all beam-like structures. According to literature, a change in location of the neutral axis can be associated with damage in the corresponding cross-section. In this paper, the movement of neutral axis near locations of minute damage in a composite bridge structure was studied using finite element analysis and experimental results. The finite element model was developed based on a physical scale model of a composite simply-supported structure with controlled minute damage in the reinforced concrete deck. The structure was equipped with long-gauge fiber optic strain and temperature sensors at a healthy reference location as well as two locations of damage. A total of 12 strain sensors were installed during construction and used to monitor the structure during various loading events. This paper aims to explain previous experimental results which showed that the observed positions of neutral axis near damage locations were higher than the predicted healthy locations in some loading events. Analysis has shown that finite element analysis has potential to simulate and explain the physical behavior of the test structure.

The utilization of asphalt rejuvenator, and its effectiveness for restoring thermal and mechanical properties was investigated via Disk-shaped Compact Tension (DC(T)) and acoustic emission (AE) testing for determining mechanical properties and embrittlement temperatures of the mixtures. During the DC(T) testing the fracture energies and peak loads were used to measure the resistance of the rejuvenated asphalt to low temperature cracking. The AE testing monitored the acoustic emission activity while the specimens were cooled from room temperature to -40 °C to estimate the temperature at which thermal cracking began (i.e. the embrittlement temperature). First, a baseline response was obtained by obtaining the mechanical and thermal response of virgin HMA samples and HMA samples that had been exposed to oxidative aging for 36 hours at 135°C. The results showed the virgin samples had much higher peak loads and fracture energies than the 36 hours aged samples. Acoustic Emission showed similar results with the virgin samples having embrittlement temperatures 10 °C cooler than the 36 hours aged specimens. Then, overaged for 36 hours specimens were treated different amounts of rejuvenator (10%, 15%, and 20% by weight of binder content) and left to dwell for increased amount of time periods varying from one to eight weeks. It was observed that the AE results showed an improvement of embrittlement temperature with increasing with the dwell times. The 8 weeks specimens had cooler embrittlement temperatures than the virgin specimens. Finally, the low temperature effects on fracture energy and peak load of the rejuvenated asphalt was investigated. Rejuvenator was applied (10% by weight of binder) to specimens aged 36 hours at 135 °C, and the dwell time was varied from 1 to 4 weeks. The results showed that the peak loads were restored to levels of the virgin specimens, and the fracture energies improved to levels beyond that of the virgin specimens. The results also showed a general trend of improvement for the AE testing of the embrittlement temperature.

Smart sensors based on Optical fiber Bragg gratings (FBGs) are suitable for structural health monitoring of dynamic strains in civil, aerospace, and mechanical structures. In these structures, dynamic strains with high frequencies reveal acoustic emissions cracking or impact loading. It is necessary to find a practical tool for monitoring such structural damages. In this work, we explore an intelligent system based on a reflective semiconductor optical amplifier (RSOA)- FBG composed as a fiber cavity for measuring dynamic strain in intelligent structures. The ASE light emitted from a RSOA laser and reflected by a FBG is amplified in the fiber cavity and coupled out by a 90:10 coupler, which is demodulated by a low frequency compensated Michelson interferometer using a proportional-integral-derivative (PID) controller and is monitored via a photodetector. As the wavelength of the FBG shifts due to dynamic strain, the wavelength of the optical output from the laser cavity shifts accordingly, which is demodulated by the Michelson Interferometer. Because the RSOA has a quick transition time, the RSOA- FBG fiber cavity shows an ability of high frequency response to the FBG reflective spectrum shift, with frequency response extending to megahertz.

In the field of non-destructive evaluation of structures, 2D and 3D imaging of internal flaws is a critical task. Defect imaging allows making informed follow-up decisions based on the morphology of the flaw. This paper will present advances in ultrasonic tomography for the 2D and 3D visualization of internal flaws in solids. In particular, improvements to the conventional tomographic imaging algorithms have been made by utilizing a mode-selective image reconstruction scheme that exploits the specific displacement field, respectively, of the longitudinal wave modes and the shear wave modes, both propagating simultaneously in the test volume. The specific mode structure is exploited by an adaptive weight assignment to the ultrasonic tomographic array. Such adaptive weighting forces the imaging array to look at a specific scan direction and better focus the imaging onto the actual flaw (ultrasound reflector). Moreover, the introduction of a global matched coefficient, computed through the matching of measured and expected times of flight for each pixel, is illustrated. The benefits deriving from the application of this coefficient to conventional imaging frameworks are shown. This study shows that the adaptive weighing based on wave structure and the integration of the global matched coefficient improve image contrast and resolution compared to a conventional ultrasonic imaging technique based on a delay-and-sum or minimum variance distortionless method. Results will be shown from experimental tests of simulated flaws in solids.

This work addresses the severe lack of literature in the area of modal analysis for multi-metric sensing. The paper aims at providing a step by step tutorial for performance of modal analysis using Fiber Bragg Grating (FBG) strain sensors and Laser Doppler Vibrometer (LDV) for displacement measurements. The paper discusses in detail the different parameters which affect the accuracy of the experimental results. It highlights the often implied, and un-mentioned problems, that researchers face while performing experiments. The paper tries to bridge the gap between the theoretical idea of the experiment and its actual execution by discussing each aspect including the choice of specimen, boundary conditions, sensors, sensor position, excitation mechanism and its location as well as the post processing of the data. The paper may be viewed as a checklist for performing modal analysis in order to ensure high quality measurements by avoiding the systematic errors to creep in.

The objective of this study is to develop an RGB-D (video + depth) camera that provides three-dimensional image data for use in the haptic feedback of a robotic underwater ordnance recovery system. Two camera systems were developed and studied. The first depth camera relies on structured light (as used by the Microsoft Kinect), where the displacement of an object is determined by variations of the geometry of a projected pattern. The other camera system is based on a Time of Flight (ToF) depth camera. The results of the structural light camera system shows that the camera system requires a stronger light source with a similar operating wavelength and bandwidth to achieve a desirable working distance in water. This approach might not be robust enough for our proposed underwater RGB-D camera system, as it will require a complete re-design of the light source component. The ToF camera system instead, allows an arbitrary placement of light source and camera. The intensity output of the broadband LED light source in the ToF camera system can be increased by putting them into an array configuration and the LEDs can be modulated comfortably with any waveform and frequencies required by the ToF camera. In this paper, both camera were evaluated and experiments were conducted to demonstrate the versatility of the ToF camera.

Corrosion of steel is one of the most important durability issues in reinforced concrete (RC) structures because aggressive ions such as chloride ions permeate concrete and corrode steel, consequently accelerating the destruction of structures, especially in marine environments. There are many practical methods for corrosion monitoring in RC structures, mostly focusing on electrochemical-based sensors for monitoring the chloride ion which is thought as one of the most important factors resulting in steel corrosion. In this work, we report a fiber-optic chloride chemical sensor based on long period gratings inscribed in a photonic crystal fiber (PCF) with a chloride sensitive thin film. Numerical simulation is performed to determine the characteristics and resonance spectral response versus the refractive indices of the analyte solution flowing through into the holes in the PCF. The effective refractive index of the cladding mode of the LPGs changes with variations of the analyte solution concentration, resulting in a shift of the resonance wavelength, hence providing the sensor signal. This fiber-optic chemical sensor has a fast response, is easy to prepare and is not susceptible to electromagnetic environment, and can therefore be of use for structural health monitoring of RC structures subjected to such aggressive environments.

A technique is presented for imaging acoustic nonlinearity within a specimen using ultrasonic phased arrays. Acoustic nonlinearity is measured by evaluating the difference in energy of the transmission bandwidth within the diffuse field produced through different focusing modes. The two different modes being classical beam forming, where delays are applied to different element of a phased array to physically focus the energy at a single location (parallel firing) and focusing in post processing, whereby one element at a time is fired and a focused image produced in post processing (sequential firing). Although these two approaches are linearly equivalent the difference in physical displacement within the specimen leads to differences in nonlinear effects. These differences are localized to the areas where the amplitude is different, essentially confining the differences to the focal point. Direct measurement at the focal point are however difficult to make. In order to measure this the diffuse field is used. It is a statistical property of the diffuse field that it represents the total energy in the system. If the energy in the diffuse field for both the sequential and parallel firing case is measured then the difference between these, within the input signal bandwidth, is largely due to differences at the focal spot. This difference therefore gives a localized measurement of where energy is moving out of the transmission bandwidth due to nonlinear effects. This technique is used to image fatigue cracks and other damage types undetectable with conventional linear ultrasonic measurements.

In recent decades, the I-beam has become one of the most important engineering structural components being applied in areas such as mechanical, civil, and constructional engineering. To ensure safety and proper maintenance, an effective and accurate structural health monitoring method/system for I-beams is urgently needed. This paper proposes a smart sensing system for I-beam crack detection that is based on the energy diffusivity (attenuation) between two individual piezoelectric transducers (PZTs). Sensor (one of the PZTs) responses are analyzed and applied to characterize the health status of the I-beam. Lab experiments are carried out for effective evaluation of this approach in structural health monitoring. The characteristics of crack distribution are studied by calculating and analyzing the energy diffusivity variation of the sensor responses to artificially cuttings to the I-beam. Moreover, instead of utilizing an actuator and a sensor, the system employs a couple of PZTs sensors, which offer the potential for in-field, in situ sensing with the sensor arrays. This smart sensing system can be applied in railway, metro, and iron-steel structures for I-beam health monitoring applications.

Many envision that in the near future the application of Unmanned Aerial Vehicles (UAVs) will impact the civil engineering industry. Use of UAVs is currently experiencing tremendous growth, primarily in military and homeland security applications. It is only a matter of time until UAVs will be widely accepted as platforms for implementing monitoring/surveillance and inspection in other fields. Most UAVs already have payloads as well as hardware/software capabilities to incorporate a number of non-contact remote sensors, such as high resolution cameras, multi-spectral imaging systems, and laser ranging systems (LIDARs). Of critical importance to realizing the potential of UAVs within the infrastructure realm is to establish how (and the extent to which) such information may be used to inform preservation and renewal decisions. Achieving this will depend both on our ability to quantify information from images (through, for example, optical metrology techniques) and to fuse data from the array of non-contact sensing systems. Through a series of applications to both laboratory-scale and field implementations on operating infrastructure, this paper will present and evaluate (through comparison with conventional approaches) various image processing and data fusion strategies tailored specifically for the assessment of highway bridges. Example scenarios that guided this study include the assessment of delaminations within reinforced concrete bridge decks, the quantification of the deterioration of steel coatings, assessment of the functionality of movement mechanisms, and the estimation of live load responses (inclusive of both strain and displacement).

Current bridge deck condition assessments using ground penetrating radar (GPR) requires a trained analyst to manually interpret substructure layering information from B-scan images in order to proceed with an intended analysis (pavement thickness, concrete cover, effects of rebar corrosion, etc.) For example, a recently developed method to rapidly and accurately analyze air-coupled GPR data based on the effects of rebar corrosion, requires that a user “picks” a layer of rebar reflections in each B-scan image collected along the length of the deck. These “picks” have information like signal amplitude and two way travel time. When a deck is new, or has little rebar corrosion, the resulting layer of rebar reflections is readily evident and there is little room for subjectivity. However, when a deck is severely deteriorated, the rebar layer may be difficult to identify, and different analysts may make different interpretations of the appropriate layer to analyze.

One highly corroded bridge deck, was assessed with a number of nondestructive evaluation techniques including 2GHz air-coupled GPR. Two trained analysts separately selected the rebar layer in each B-scan image, choosing as much information as possible, even in areas of significant deterioration. The post processing of the selected data points was then completed and the results from each analyst were contour plotted to observe any discrepancies. The paper describes the differences between ground coupled and air-coupled GPR systems, the data collection and analysis methods used by two different analysts for one case study, and the results of the two different analyses.

Reinforced concrete decks are in most cases the fastest deteriorating components of a bridge due to the multitude of influencing factors: direct traffic loading and environmental effects, maintenance activities (salting), etc. Among many deterioration types, corrosion-induced deterioration is the most common problem in reinforced concrete decks. The study concentrates on the condition assessment of bridge decks using complementary NDE techniques. The assessment has three main components: assessment of corrosive environment and corrosion processes, and assessment with respect to the deck delamination. The study concentrates on a complementary use of five NDE techniques: impact echo (IE) to detect and characterize delamination, ground penetrating radar (GPR) to describe the corrosive environment and detect delamination, and electrical resistivity (ER) to estimate the corrosion rate by measuring concrete resistivity. The ability of the NDE methods to objectively characterize deterioration progression is illustrated by the results from NDE surveys of 10 bridges of different ages in New Jersey during a period of one year. The deterioration progression is illustrated by condition maps and condition indices. As demonstrated in the paper, multiple deterioration models are developed utilizing the proposed methodology, which shows high potential for development of more realistic deterioration and life cycle cost models for bridge decks.

Modern remote sensing technologies have enabled the creation of high-resolution 3D point clouds of infrastructure systems. In particular, photogrammetric reconstructions using Dense-Structure-from-Motion algorithm can now yield point clouds with the necessary resolution to capture small-strain displacements. By tracking changes in these point clouds over time, displacements can be measured, leading to strain and stress estimates for long-term structural evaluations. This study determines the accuracy of a comparative point cloud analysis technique for measuring deflections in high-resolution point clouds of structural elements. Utilizing a combination of a recently developed point cloud generation process and localized nearest-neighbors cloud comparisons, the analytical technique is designed for long-term field scenarios and requires no artificial tracking, targets, and camera calibrations. A series of flexural laboratory experiments were performed in order to test the approach. The results indicate sub-millimeter accuracy in measuring the vertical deflection, making it suitable for the small-displacement analysis of a variety of large-scale infrastructure systems. Ongoing work seeks to extend this technique for comparison with as-built and finite element models.

Advanced fiber reinforced composite materials are becoming the main structural materials of next generation of aircraft because of their high strength and stiffness to weight ratios, and excellent designability. As key components of large composite structures, joints play important roles to ensure the integrity of the composite structures. However, it is very difficult to analyze the strength and failure modes of composite joints due to their complex nonlinear coupling factors. Therefore, there is a need to monitor, diagnose, evaluate and predict the structure state of composite joints. This paper proposes a multi-field coupled sensing network for health monitoring of composite bolted joints. Major work of this paper includes: 1) The concept of multifunctional sensor layer integrated with eddy current sensors, Rogowski coil and arrayed piezoelectric sensors; 2) Development of the process for integrating the eddy current sensor foil, Rogowski coil and piezoelectric sensor array in multifunctional sensor layer; 3) A new concept of smart composite joint with multifunctional sensing capability. The challenges for building such a structural state sensing system and some solutions to address the challenges are also discussed in the study.

Recently, data-driven models for Structural Health Monitoring (SHM) have been of great interest among many researchers. In data-driven models, the sensed data are processed to determine the structural performance and evaluate the damages of an instrumented structure without necessitating the mathematical modeling of the structure. A framework of data-driven models for online assessment of the condition of a structure has been developed here. The developed framework is intended for automated evaluation of the monitoring data and structural performance by the Internet technology and resources. The main challenges in developing such framework include: (a) utilizing the sensor measurements to estimate and localize the induced damage in a structure by means of signal processing and data mining techniques, and (b) optimizing the computing and storage resources with the aid of cloud services. The main focus in this paper is to demonstrate the efficiency of the proposed framework for real-time damage detection of a multi-story shear-building structure in two damage scenarios (change in mass and stiffness) in various locations. Several features are extracted from the sensed data by signal processing techniques and statistical methods. Machine learning algorithms are deployed to select damage-sensitive features as well as classifying the data to trace the anomaly in the response of the structure. Here, the cloud computing resources from Amazon Web Services (AWS) have been used to implement the proposed framework.

In this study, Mg-doped CdS nanostructure was deposited onto anodic aluminum oxide (AAO) membrane substrate using sol-gel spin coating method. The AAO membrane was prepared by a two-step anodization process combined with pore widening process. The morphology, chemical composition, and structure of the spin- coated CdS nanostructure have been studied. The morphology of the fabricated AAO membrane and the deposited Mg-doped CdS nanostructure was investigated using scanning electron microscopy (SEM). The SEM of AAO illustrates a typical hexagonal and smooth nanoporous alumina membrane with interpore distance of ~ 100 nm, the pore diameter of ~ 60 nm. SEM of Mgdoped CdS shows porous nanostructured film of CdS nanoparticles. This film well adherents and covers the AAO substrate. The energy dispersive X-ray (EDX) pattern exhibits the signals of Al, O from AAO membrane and Mg, Cd, and S from the deposited CdS. This indicates the high purity of the fabricated membrane and the deposited Mg-doped CdS nanostructure. Using X-ray diffraction (XRD) pattern, Scherrer equation was used to calculate the average crystallite size. Additionally, the texture coefficients and density of dislocations were calculated. The fabricated CdS/AAO was applied to detect glucose of different concentrations. The proposed method has some advantages such as simple technology, low cost of processing, and high throughput. All of these factors facilitate the use of the prepared films in sensing applications.

Rotor is a core component of rotary machinery. Once the rotor has the damage, it may lead to a major accident. Thus the quantitative rotor damage detection method based on piezoelectric impedance is studied in this paper. With the governing equation of piezoelectric transducer (PZT) in a cylindrical coordinate, the displacement along the radius direction is derived. The charge of PZT is calculated by the electric displacement. Then, by the use of the obtained displacement and charge, an analytic piezoelectric impedance model of the rotor is built. Given the circular boundary condition of a rotor, annular elements are used as the analyzed objects and spectral element method is used to set up the damage detection model. The Electro-Mechanical (E/M) coupled impedance expression of an undamaged rotor is deduced with the application of a low-cost impedance test circuit. A Taylor expansion method is used to obtain the approximate E/M coupled impedance expression for the damaged rotor. After obtaining the difference between the undamaged and damaged rotor impedance, a rotor damage detection method is proposed. This method can directly calculate the change of bending stiffness of the structural elements, it follows that the rotor damage can be effectively detected. Finally, a preset damage configuration is used for the numerical simulation. The result shows that the quantitative damage detection algorithm based on spectral element method and piezoelectric impedance proposed in this paper can identify the location and the severity of the damaged rotor accurately.

Structural Health Monitoring (SHM) is a technology that can evaluate the extent of the deterioration or the damage of the building quantitatively. Most SHM systems utilize only a few sensors and the sensors are placed equally including the roof. However, the location of the sensors has not been verified. Therefore, in this study, the optimal location of the sensors is studied for estimating the inter-story drift angle which is used in immediate diagnosis after an earthquake. This study proposes a practical optimal sensor location method after testing all the possible sensor location combinations. From the simulation results of all location patterns, it was proved that placing the sensor on the roof is not always optimal. This result is practically useful as it is difficult to place the sensor on the roof in most cases. Modal Assurance Criterion (MAC) is one of the practical optimal sensor location methods. I proposed MASS Modal Assurance Criterion (MAC*) which incorporate the mass matrix of the building into the MAC. Either the mass matrix or the stiffness matrix needs to be considered for the orthogonality of the mode vectors, normal MAC does not consider this condition. The location of sensors determined by MAC* was superior to the previous method, MAC. In this study, an important knowledge of the location of sensors was provided for implementing SHM systems.

A stochastic model based on Markov random field is proposed to model the spatial distribution of vehicle loads on longspan bridges. The bridge deck is divided into a finite set of discrete grid cells, each cell has two states according to whether the cell is occupied by the heavy vehicle load or not, then a four-neighbor lattice-structured undirected graphical model with each node corresponding to a cell state variable is proposed to model the location distribution of heavy vehicle loads on the bridge deck. The node potential is defined to quantitatively describe the randomness of node state, and the edge potential is defined to quantitatively describe the correlation of the connected node pair. The junction tree algorithm is employed to obtain the systematic solutions of inference problems of the graphical model. A marked random variable is assigned to each node to represent the amplitude of the total weight of vehicle applied on the corresponding cell of the bridge deck. The rationality of the model is validated by a Monte Carlo simulation of a learned model based on monitored data of a cable-stayed bridge.

This paper designed a special acoustic metamaterial 3D Kagome lattice sandwich plate. Dispersion properties and vibration responses of both traditional plate and metamaterial plate are investigated based on FEA methods. The traditional plate does not have low-frequency complete bandgaps, but the metamaterial plate has low-frequency complete bandgap (at 620Hz) coming from the symmetrical local cantilever resonators. The bandgap frequency is approximate to the first-order natural frequency of the oscillator. Complex wave modes are analyzed. The dispersion curves of longitudinal waves exist in the flexural bandgap. The dispersion properties demonstrate the metamaterial design is advantageous to suppress the low-frequency flexural wave propagation in lattice sandwich plate. The flexural vibrations near the bandgap are also suppressed efficiently. The longitudinal excitation stimulates mainly longitudinal waves and lots of low-frequency flexural vibration modes are avoided. Furthermore, the free edge effects in metamaterial plate provide new method for damping optimizations. The influences of damping on vibrations of the metamaterial sandwich plate are studied. Damping has global influence on the wave propagation; stronger damping will induce more vibration attenuation. The results enlighten us damping and metamaterial design approaches can be unite in the sandwich plates to suppress the wave propagations.

Applications of composite materials in aerospace structures is increasing due to the outstanding properties, however, monitoring such composite structures exposed to harsh environments is still a posing issue. Low Earth orbit space structures are exposed to property degradation and damage from high-degree vacuum, ultraviolet radiation, thermal cycling, and atomic oxygen attack which are detrimental to composite materials. In this study, FBG sensors for embedding in CFRP composite plates in different thickness locations to provide health and damage monitoring of the material exposed to such environments regarding the overall health of the material with a focus on the exposed surface are explored in comparison to conventional FBG sensors.

In bridge construction, geometry control is critical to ensure that the final constructed bridge has the consistent shape as design. A common method is by predicting the deflections of the bridge during each construction phase through the associated finite element models. Therefore, the cambers of the bridge during different construction phases can be determined beforehand. These finite element models are mostly based on the design drawings and nominal material properties. However, the accuracy of these bridge models can be large due to significant uncertainties of the actual properties of the materials used in construction. Therefore, the predicted cambers may not be accurate to ensure agreement of bridge geometry with design, especially for long-span bridges. In this paper, an improved geometry control method is described, which incorporates finite element (FE) model updating during the construction process based on measured bridge deflections. A method based on the Kriging model and Latin hypercube sampling is proposed to perform the FE model updating due to its simplicity and efficiency. The proposed method has been applied to a long-span continuous girder concrete bridge during its construction. Results show that the method is effective in reducing construction error and ensuring the accuracy of the geometry of the final constructed bridge.

A piezoceramic based sensor consisting of embedded Lead Zirconate Titanate (PZT) patch is developed for assessing the progression of hydration and evolution of properties of cement mortar. A method for continuous assessment of cement mortar with different water to cement ratios after casting is presented. The method relies on monitoring changes in the electromechanical (EM) conductance of a PZT patch embedded in mortar. Changes in conductance are shown to sensitively reflect the changes in the mechanical impedance of the cementitious material as it transforms from fluid to solid state.

Extensive research is currently underway across the world for employing piezo sensors for biomedical health monitoring in view of their obvious advantages such as low cost,fast dynamics response and bio-compatibility.However,one of the limitations of the piezo sensor in bonded mode based on the electro-mechanical impedance (EMI) technique is that it can cause harmful effects to the humans in terms of irritation ,bone and skin disease. This paper which is in continuation of the recent demonstration of non-bonded configuration is a step towards simulating and analyzing the non-bonded configuration of the piezo sensor for gauging its effectiveness using FEA software. It has been noted that the conductance signatures obtained in non-bonded mode are significantly close to the conventional bonded configuration, thus giving a positive indication of its field use.

Structural health monitoring (SHM) is emerging as a vital tool to help civil engineers improve the safety, maintainability, and reliability of critical structures and assists infrastructure owners with timely information for the continued safe and economic operation of their structure. SHM involves implementing a strategy that identifies and characterizes damage or undesirable performance in engineering structures. The goal of this research project was to determine the smallest strains measurable using standard digital image correlation (DIC) based SHM equipment. This practical investigation that had strong ties to the industry was motivated by damage observed in a real-world bridge, which was initially undetected. Its early detection would have led to reduced repair costs. To accomplish the aforementioned goal, tests were performed on a laboratory specimen that replicated a steel beam-to-column connection of the concerned bridge, involving progressively loading it in a manner in which it was loaded in the actual bridge, while simultaneously measuring the strains that developed in it using the aforementioned DIC-based equipment and software. Under the controlled conditions in the laboratory, the minimum resolution of the state-of-the-art system used in this investigation was determined. Due to the challenges faced in making these small-strain measurements even under highly controlled laboratory conditions, it was concluded that it is currently unrealistic to use the existing DIC technology in a real-world situation to measure strains as small as those that would need to be measured to detect the onset of damage in bridge connections. More work needs to be done in this area.