Successful in-situ monitoring of crack initiation and growth is a necessary prerequisite for applying ultrasonic methods to structural health monitoring. For conventional ultrasonic testing methods, a focused beam may be used to directly image the crack tip; however, this method is difficult to apply during fatigue testing because of access limitations and couplant contamination issues. However, ultrasonic sensors can be permanently attached to a specimen to detect signal changes due to crack initiation and growth if the wave path is properly directed through the area of critical defect formation. The dynamics of cracks opening and closing during the fatigue process modulate the amplitude of ultrasonic waves propagating across these crack interfaces. Thus, even very small cracks can be reliably detected using permanently mounted sensors if the ultrasonic response can be measured as a function of load. A methodology is presented here that uses this behavior to detect and monitor crack formation and growth. This methodology may also be applied to structures subjected to unknown dynamic loads by using the ultrasonic signal to both estimate the instantaneous dynamic load and interrogate the integrity of the structure. Essential to the success of this method is an initial calibration on the undamaged structure where ultrasonic response is measured as a function of known static load. Results are presented from several aluminum specimens undergoing low cycle fatigue tests, and the dynamic loading results are shown to be comparable to the static ones in terms of the response of the ultrasonic signal to crack progression.

The objective of this study is to experimentally evaluate the effects of the impact-induced damages of Carbon Fiber Reinforced Plastic (CFRP) laminated composites under no stress and pre-stress conditions such as (1) no loading, (2) compressive loading, and (3) tensile loading. The symmetrical 4-points bending apparatus was designed and manufactured for making the pre-stressed conditions. Four kinds of test specimens having laminate configurations of (012/θ20/012) were employed, wherein their ply angles (denoted as "θ") were 30°, 45°, 60°, and 90°. The test specimens were impacted with an air-gun type of impact apparatus. First, a strain change caused by the impact was measured. Second, a mechanical scanning acoustic reflection microscope (SAM: pulse-wave mode) was used to detect an interior damage (e.g., delamination) of the impact-induced specimens.

Recently a new structural health monitoring system that employs a "continuous acoustic emission sensor" and an embeddable local processor has been proposed. The development of a processor that integrates the functions of signal conditioning, feature extraction, data storage, and digital communication is currently in progress. A prototype of this local processor chip has been developed. The integration of a continuous sensor with an embeddable local processor can potentially enable an inexpensive method of monitoring large and complex structures using acoustic emission signals. Such a system can reduce the cost, complexity, and weight of the required instrumentation. It is potentially scalable to large and complex structures and could be integrated into the structural material. The success of the acoustic emission based structural health monitoring technique depends on its ability to discriminate between valid acoustic emission signals and ambient noise. In addition, the technique should be able to identify the damage mode from the acoustic emission waveforms. This paper focuses on the use of acoustic emission technique for the identification of failure modes in composite materials. Three types of failure modes in glass fabric epoxy composite laminates are considered. These are two types of delamination growth and transverse crack growth. Wavelet analysis is used to extract time frequency information from the acoustic emission signals. Different features of the waveform including the frequency components, Symmetric and Antisymmetric components, and amplitudes are used to classify the signals and identify the failure modes. The laboratory tests indicate that it is possible to distinguish the individual failure modes under consideration. It was also possible to filter out spurious AE signals that originate from extraneous sources using an appropriate choice of sensors and frequency components. An attempt is made to relate the rate of damage growth with the detected acoustic emission signal parameters.

Barkhausen noise (BHN) method seems a useful tecnique to non-destructive evaluation of martensite phase transformation of ferromagnetic shape memory alloy, which is used as the filler of our proposing "Smart Composite Board". The concept of design for "Smart Composite Board" which can combine the non-destructive magnetic inspection and shape recovery function in the material itself was formerly proposed. In the present study, we survey the possibility of Barkhausen noise (BHN) method to detect the transformation of microscopic martensite phase caused by stress-loading in Fe-30.2at%Pd thin foil, which has a stable austenite phase (fcc structure) at room temperature. The BHN voltage was measured at loading stress up to 100 MPa in temperature range of 300K to 373K. Stress-induced martensite twin was observed by laser microscope above loading stress of 25 MPa. A phase transformation caused by loading stress were analyzed also by X-ray diffraction. The signals of BHN are analyzed by the time of magnetization and the noise frequency. BHN caused by grain boundaries appears in the lower frequency range (1kHz-3kHz) and BHN by martensite twin in the higher frequency range (8kHz-10kHz). The envelope of the BHN voltage as a function of time of magnetization shows a peak due to austenite phase at weak magnetic field. The BHN envelope due to martensite twins creates additional two peaks at intermediate magnetic field. BHN method turns out to be a powerful technique for non-destructive evaluation of the phase transformation of ferromagnetic shape memory alloy.

The paper presents results of non-destructive testing of composite main rotor helicopter blade calibration specimens using the laser based optical NDE technique known as Shearography. The tests were performed initially using the already well established near real-time non-destructive technique of Shearography, with the specimens perturbed during testing for a few seconds using the hot air from a domestic hair dryer. Subsequent to modification of the shearing device utilized in the shearographic setup, phase stepping of one of the sheared images to be captured by the CCD camera was enabled and identical tests were performed on the composite main rotor helicopter blade specimens. Considerable enhancement of the images manifesting or depicting the defects on the specimens is noted suggesting that phase stepping is a desirable enhancement technique to the traditional Shearographic setup.

Dielectric spectroscopy has been developed as a non-destructive technique for assessment of moisture content and structural integrity of adhesively bonded joints. Knowledge of these parameters is particularly crucial for the aerospace industry, since environmental degradation of adhesive joints presents a major limit on their utilization. High and low frequency measurements have been carried out on joints assembled from CFRP adherend, and a commercially available adhesive (AF 163-2K). The samples have been aged in deionised water at 75oC to chart the effect water ingress has on bond durability. In addition, some joints have been exposed to cryogenic temperatures to mimic the conditions joints experience whilst an aircraft is in flight. In this way it has been possible to determine the extent of degradation caused by freezing of water within the joint structure. Dielectric behaviour of the joints was studied in both the frequency and in the time domain. Frequency domain analysis allows the amount and effects of moisture ingress in the bondline to be assessed, whereas the time domain highlights the onset of joint defects with increasing exposure time. Mechanical testing of the joints has been carried out to enable correlation between changes in strength and failure mechanism due to moisture ingress, with changes in the dielectric data. In addition, dielectric studies of the neat adhesive have been undertaken, as have gravimetric and dynamic mechanical thermal analysis. These have helped reveal the effects of ageing upon the adhesive layer itself.

In this study, the guided wave technique is applied to nondestructively assess the damage in various engineering materials, like alumina, laminated composites, and composite sandwiches. A combined theoretical, numerical and experimental investigation of the pulse-echo method using piezoelectric sensors and actuators is conducted. The dispersion effect of wave guides on these materials is first analyzed, and the transient propagation process of wave guides and its interaction with inside damages are then numerically simulated. The implementations of the pulse echo method are illustrated in experimental testing and damage detection of aluminum beams, carbon/epoxy laminated composite plates, and composite sandwich beams. In particular, the experimental results on damage detection of the composite sandwich beams are reported and discussed. As illustrated in this study, the pulse-echo method combined with piezoelectric material can be used effectively to locate damage in various engineering materials and structures.

We have developed a 'pitch-catch' low frequency-wideband Rayleigh wave EMAT system with a centre frequency of approximately 200kHz, extending to around 500kHz and study here its applicability to crack detection in the head of rail tracks. On the head of a rail, the generated waves are strictly speaking a type of guided wave mode as the propagation surface is not a flat halfspace. They propagate along the surface of the rail penetrating down to a depth of several millimetres. We have used this approach to demonstrate detection of gauge corner and longitudinal cracking in the rail head. On samples containing machined slots we have shown that crack depth can be estimated by measuring the proportion of the ultrasonic wave at a particular frequency that passes underneath the crack. The approach that we have used is fundamentally different to and has several advantages over conventional ultrasonic contact methods and should ultimately facilitate testing the rail head more thoroughly at higher speeds.

Accurate interpretation of data measurement is a major challenge for development of reliable and effective diagnostic system. This paper presents experimental results of a proposed damage identification candidate based on Lamb wave propagation analysis. Carbon/epoxy laminated composite plate specimens with various damage, i.e., delamination and impact damage, are evaluated. Damage location is extracted from the measured time history data of the propagated wave and the wave traveling time. Assuming the wave propagates with a constant speed, the summation of the distance from the transmitter to the damage and the distance from the damage to the receiver is constant. The possible damage location combining with the locations of the transmitter and receiver forms an elliptical path, where the locations of the transmitter and receiver serve as the foci of the ellipse. Piezoelectric transducers (PZTs) are used as the wave transmitters and receivers. Post-processing of the recorded signals using wavelet transform allows better isolation of the interested propagation mode and the extraction of the traveling time, which enhance the accuracy of damage localization. Results of the damage location estimation are presented.

An ultrasonic sensing system in which a fiber Bragg grating was used as an ultrasonic detector was constructed. The system utilizes wavelength-optical intensity modulation technique and includes a broadband light source, fiber Bragg gratings for sensing and filtering, as well as a photodetector. Feasibility of active sensing diagnosis by the system was examined. Ultrasonic Lamb wave generated by a piezoelectric device was propagated in a cross-ply CFRP with visible impact damage. Response of fiber Bragg grating sensor to Lamb wave propagated through damage area was compared with the reference response in intact area. In the active sensing diagnosis, the ultrasonic transmitter was excited by three kinds of signal to determine the optimal transmitter drive signal for impact damage detection. Compared with response in intact area, response to Lamb wave propagated through damage area demonstrated distinctive features. A spike signal proved to be optimal transmitter drive signal for impact damage detection of CFRP.

Corrosion of reinforced concrete is a chronic infrastructure problem, particularly in areas with deicing salt and marine exposure. To maintain structural integrity, a testing method is needed to identify areas of corroding reinforcement. For purposes of rehabilitation, the method must also be able to evaluate the degree, rate and location of damage. Towards the development of a wireless embedded sensor system to monitor and assess corrosion damage in reinforced concrete, reinforced mortar specimens were manufactured with seeded defects to simulate corrosion damage. Taking advantage of waveguide effects of the reinforcing bars, these specimens were then tested using an ultrasonic approach. Using the same ultrasonic approach, specimens without seeded defects were also monitored during accelerated corrosion tests. Both the ultrasonic sending and the receiving transducers were mounted on the steel rebar. Advantage was taken of the lower frequency (<250 kHz) fundamental flexural propagation mode because of its relatively large displacements at the interface between the reinforcing steel and the surrounding concrete. Waveform energy (indicative of attenuation) is presented and discussed in terms of corrosion damage. Current results indicate that the loss of bond strength between the reinforcing steel and the surrounding concrete can be detected and evaluated.

Vibration-based damage detection (VBDD) methods utilize measured changes in the dynamic characteristics of structural systems (natural frequencies, mode shapes, and damping characteristics) to indicate the presence and location of damage. Previous studies have demonstrated that small-scale damage can be reliably located in simple bridge systems when resonant harmonic loading is used as the excitation source for the VBDD measurements. In full-scale bridge applications, however, random loading due to traffic or wind is often more readily achievable. A numerical study was therefore undertaken to investigate the use of random loading for damage detection in a simple-span, slab-on-girder bridge deck. Transient dynamic analyses of a finite element model of the bridge deck subjected to randomly varying loading were performed for nine different simulated small-scale damage states. To reduce the inherent uncertainty arising from the random loading, averaged results from a large number of repeated random trials were used. Several factors that may influence the probability of successfully locating the damage were investigated, including the number of repeated random trials used, the distance from the damage to the nearest sensor, the proximity of the damage to simple supports, the severity of the damage and the presence of random measurement error. It was found that a large number of repeated random trials was required to achieve reasonable probabilities of successfully locating the damage; even then, reliable detection results were not guaranteed for all of the damage conditions considered. Based on these results, therefore, random excitation appears to be less reliable in VBDD than harmonic loading.

Vibration based damage identification (VBDI) techniques rely on the fact that damage in a structure reduces its stiffness and alters its global vibration characteristics. Measurement of changes in the vibration characteristics can therefore be used to determine the damage in the structure. The VBDI technique does not depend on a-priori information about the damage site; the vicinity of the damage need not be accessible; and often a limited number of sensors can be used to localize and quantify the damage. Unfortunately, most of the available damage identification algorithms fail when applied to practical structures due to the effect of measurement errors, uncertainties induced by environmental and boundary condition, the need to use incomplete mode shapes, mode truncation, and the non-unique nature of the solutions. Damage detection based on changes in modal characteristics can be treated as a pattern recognition problem. Artificial neural networks provide an ideal means of obtaining a solution to such a problem. This paper presents a new robust two-step algorithm for detecting the location and magnitude of damage. The technique uses principles of structural dynamics and artificial neural networks. A modal energy based vibration property, known as the damage index vector, is used as the input to the network. The proposed algorithm is used to detect simulated damage in a simple finite element model of a slab and girder bridge. The result shows that the proposed algorithm is quite effective in identifying the location and magnitude of damage, even in the presence of measurement errors in the input data.

A vibration-based damage detection method is presented, which updates a finite element model from measured eigenfrequencies and mode shapes. Changes in stiffness of individual elements are interpreted as damage. The update problem is ill-posed and needs therefore regularization. Tikhonov regularization is a well known regularization method for linear problems. However, the update problem is nonlinear and there are different ways to use Tikhonov regularization in the nonlinear case. The usual way is to linearize the update problem with the sensitivity matrix and then apply regularization in each iteration. This approach has the disadvantage that the regularization effect depends on the number of iterations and may get lost as the number of iterations increases. The problem has been discussed in the mathematical literature but is not widely recognized in the engineering community. The alternative way is to regularize the nonlinear problem and then linearize it. This results in an additional term in the update equation that guarantees that regularization is independent of the number of iterations. Both ways are applied to a two-story frame with simulated measurements. Generalized cross-validation, L-curves, and errors of the update parameters are compared. The simulations confirm that the algorithm characterized by "regularize, then linearize" gives superior results. This algorithm is finally applied to a real frame recently tested in the lab. The frame is part of a full-size structure that has been damaged by pseudo-dynamic tests simulating different earthquake levels.

This paper explores the use of unsupervised neural computation for event detection (ED) in structural health monitoring (SHM) systems. ED techniques are useful in SHM systems for minimizing the size of SHM data sets, and the costs associated with analyzing, transmitting and storing SHM data. The approach to ED explored here is adaptive, self-configuring and does not require detailed information about the structure being monitored. A neural network approach known as frequency sensitive competitive learning (FSCL) is used to model the sensor output of an SHM system. SHM system output states which disagree with the model learned are deemed "novel" and detected as SHM events. The FSCL-ED system is evaluated with SHM data from three structures including the Taylor Bridge, the Portage Creek Bridge and the Golden Boy Statue. Furthermore, this system is able to identify strain gauge events of 0.75, 12.5, 1.25 microstrain or smaller in the SHM measurement data from the Taylor Bridge, the Portage Creek Bridge, and the Golden Boy respectively. The FSCL-ED system is able to identify accelerometer events of .0045g, 0.0020g or smaller in the SHM measurement data from the Portage Creek Bridge, and the Golden Boy respectively. The FSCL-ED system is compared to a simplified event detection (S-ED) system, which does not use power spectral density estimation or unsupervised neural computation. The S-ED system is shown to be effective but less sensitive than the FSCL-ED system to SHM events. As well, the FSCL-ED system is better able to adapt to noisy environments.

Fibre reinforced polymer (FRP) laminates are used to rehabilitate concrete beams that do not possess the required ultimate flexural capacity. Because this is a new technology, there is a need to use structural health monitoring techniques in many of the field projects to verify their field performance and increase user confidence. This paper discusses the process of developing an SHM system for concrete beams with FRP flexural strengthening laminates. In the specific case of FRP laminates, debonding or delamination is a damage mechanism of specific concern. Through an experimental and theoretical study it is shown that strain monitoring would be the most effective technique for this application. Due to the need for a dense spatial resolution of sensors with low noise, Brillouin scatter or multi-Bragg grating style fibre optic sensors are suggested as the most appropriate for this application. A damage assessment methodology based of the shape of the laminate strain profile is established. While the precise methodology is specific to this application, the process of SHM system development discussed in the paper is adaptable to a wide range of field structures.

One of the key elements in a structural health monitoring system is the sensing element and data acquisition system. One type of fiber optic sensor used to measure strain is the fiber Bragg grating. Bragg gratings are fabricated using different methods. One method involves placing a mask pattern over the optical fiber and projecting UV light through it to change the refractive index of the core. However, before the grating is written into the core of the fibre, the outer fibre coatings must be stripped away either mechanically or chemically. Fibre Bragg gratings are then recoated after the grating has been written to maintain the strength and flexibility of the fibre by protecting the exposed glass from damage. Acrylate and polyimide are two types of recoat material typically used on fibre Bragg grating sensors. This work is a controlled comparison of polyimide and acrylate recoated fibres for Bragg grating strain sensors. The comparison was carried out using a tension test coupon with recoated FBG and electrical strain gauges bonded to its surface. The tension test specimen was made of cold rolled steel and was designed according to ASTM A30-97a standard. The dimensions were chosen such that three fibre optic sensors and a strain gauge can be attached on each side. The load was applied in 40 με steps until the strain reached approximately 200 µε. The load was then incrementally decreased back to zero. FBG sensors from 2 manufacturers were compared. For the first manufacturer the Acrylate coated sensors required a gauge factor is 0.75 in order for electrical and FBG strain readings to agree. For Polyimide coated sensors, the appropriate gauge factor was very close to the theoretically predicted value of 0.8. Using these gauge factors, the error between the first manufacturers sensor readings and the strain gauges was well within ±5µε. On the other hand, the second manufacturers sensors did not perform nearly as well. Their readings were substantially lower than the corresponding electrical strain gauges readings and varied from 7% to 13% below expected strain readings. This study demonstrates that bonded FBG sensors can reliably measure strain, but that not all manufacturers are producing recoated FBG sensors to the standard required for strain sensing in civil structures.

Structural health monitoring (SHM) activities in civil engineering grow at a rapid pace and mature in both research and field applications. Internet technology was successfully incorporated into structural health monitoring, which makes it possible to manage real-time sensing data and centralize the remote structural monitoring systems. With the increase in size and complexity of the monitored structures, more sensors and data acquisition equipment is involved. This paper addresses some specific issues related to long distance small signal transmission and Ethernet IP sharing between different devices. The issue of data volume versus storage space and communication bandwidth is discussed especially in the application of web camera image transfer and recording. The approaches are illustrated through reference to two current case studies, which include a bridge and a statue. It can be seen that these practical solutions employed by ISIS Canada are easy to implement and reduce the cost for the maintenance of SHM systems. The paper also discusses future activities and research needs related to the reliability and security of the SHM system.

As the design and construction of civil structures continue to evolve, it is becoming imperative that these structures be monitored for their health. In order to meet this need, the discipline of Civionics has emerged. Civionics is a new term coined from Civil-Electronics, which is derived from the application of electronics to civil structures. It is similar to the term Avionics, which is used in the aerospace industry. If structural health monitoring is to become part of civil structural engineering, it should include Civionics. It involves the application of electronics to civil structures and aims to assist engineers in realizing the full benefits of structural health monitoring (SHM). In past SHM field applications, the main reason for the failure of a sensor was not the installation of the sensor itself but the egress of the sensor cables. Often, the cables were not handled and protected correctly. For SHM to be successful, specifications must be written on the entire process, beginning with system design and concluding with data collection, interpretation, and management. Civionics specifications include the technical requirements for a SHM system which encompasses fibre optic sensors, cables, conduits, junction boxes and the control room. A specification for data collection and storage is currently being developed as well. In the spring of 2004 research engineers at the University of Manitoba constructed a full-scale second generation steel free bridge deck. The bridge deck is the first of its kind to fully incorporate a complete civionics structural health monitoring system to monitor the deck's behaviour during destructive testing. Throughout the construction of the bridge deck, the entire installation of the civionics system was carried out by research engineers simulating an actual implementation of such a system in a large scale construction environment. One major concern that consulting engineers have raised is the impact that a civionics system that uses conduit, junction boxes, and other electrical ancillary protection, will have when embedded and installed externally on full-scale infrastructure. The full-scale destructive testing of a second generation steel-free bridge deck using a civionics system designed and implemented following guidelines in a civioncs specification manual at the University of Manitoba will provide engineers with the information necessary to address the constructability and structural integrity issues. Civioncs combined with structural health monitoring will provide engineers with feedback necessary to aid in optimizing design techniques and understanding our infrastructures performance, behaviour and state of condition.

There are numerous successful applications of fibre-reinforced composites for strengthening the civil engineering infrastructure. Most of these repairs are being continuously or intermittently monitored for assessing their effectiveness and safety. The impact resonance method (IRM), a non-destructive technique, utilized in civil engineering exclusively for determining the dynamic concrete properties, could be a valuable and viable damage detection tool for structural elements. The IRM gives useful information about the dynamic characteristics of rectangular and circular concrete members such as beams and columns. In this experimental program, a 1.2-m-long reinforced concrete beam strengthened with a carbon fibre-reinforced polymer (CFRP) plate has been employed. The CFRP-strengthened beam has been loaded in fatigue for two million cycles at 3 Hz. The load amplitude was from 15 to 35% of the anticipated yielding load of the beam. Throughout fatigue testing the cycling was stopped for IRM measurements to be taken. The obtained data provided information about changes in modal properties such as natural frequencies of vibration. These results have shown the successful use of the IRM for detecting fatigue damage in concrete members strengthened with composites.

The Golden Boy statue was placed on top of the Manitoba Legislative Building in 1919 and has since served as a source of inspiration to all Manitobans. An inspection of this heritage structure was conducted in 2001and revealed that its steel supporting shaft had deteriorated significantly. A decision was made to take the statue down for restoration. A stronger, stainless steel shaft replaced the worn shaft and sensors including electrical strain gauges, accelerometers, fiber optic sensors and thermocouples were installed. Also, a web camera and wind meter were installed on the roof of the building. Data from the sensors and video feed from the web camera are available through the Internet to facilitate web-based Structural Health Monitoring (SHM) in real-time. The support shaft of the statue can be idealized as a single degree of freedom cantilever structure. Wind and acceleration data are used to estimate the strains experienced by the shaft near the base, which are then correlated with the actual strain recorded by the strain sensors. This correlation was difficult as the data contained various levels of measurement errors or noise, and the strain data must be isolated from the thermal strain. Finally, the observed strain was correlated with hourly peak wind velocities reported by Environment Canada and an empirical relationship between these quantities was established to obtain an estimate of the strain in the shaft based on wind velocity, which will detect malfunctions in the sensors or deterioration of the structure. The study provided an understanding of the statue's behavior under a range of wind speeds and confidence in the SHM system for continuous and long term monitoring. It established a baseline response and alternative methods for predicting the behavior of the statue that provide a foundation for comparison with future stages in the Structural Health Monitoring of the Golden Boy.

Vibration-based damage detection (VBDD) methods use changes to the dynamic characteristics of a structure (i.e. its natural frequencies, mode shapes, and damping properties) to detect the presence of damage and determine its location. The application of these methods to constructed civil engineering facilities is complicated by a number of factors unique to these structures. Despite the challenges, the development of reliable VBDD methods for constructed facilities has the potential for great benefit and cost savings to infrastructure owners. This paper focuses on the application of VBDD techniques based on changes to mode shapes to a two-span, slab-on-girder, integral abutment bridge in Saskatoon, Canada. The dynamic response of the bridge under ambient traffic loading has been measured periodically using temporarily installed accelerometers over a range of ambient temperatures. A detailed finite element (FE) model has been developed and calibrated to match the first three measured natural frequencies and mode shapes. This model was then used to simulate the dynamic response of the bridge as various states of small-scale damage were induced, and several VBDD techniques were applied to detect and locate the damage. Preliminary results show that the ambient temperature significantly influences measured natural frequencies. In addition, the presence and location of damage may be found using any of VBDD techniques. The performance of the techniques is influenced by the number of sensors used to characterize mode shapes, as well as by the procedures used to normalize the mode shapes.

A new design of distributed crack sensors is presented for the condition assessment of reinforced concrete (RC) structures during and immediately after an earthquake event. This study is mainly focused on the performance of cable sensors under dynamic loading, particularly their ability to memorize the crack history of an RC member. This unique memory feature enables the post-earthquake condition assessment of structural members such as RC columns, in which the earthquake-induced cracks are closed immediately after an earthquake event due to gravity loads and they are visually undetectable. Factors affecting the onset of the memory feature were investigated experimentally with small-scale RC beams under cyclic loading. Test results indicated that both crack width and the number of loading cycles were instrumental in the onset of the memory feature of cable sensors. Practical issues related to dynamic acquisition with the sensors were discussed. The sensors were proven to be fatigue resistant from the shake table tests of RC columns. They continued to show useful signal after the columns can no longer support additional loads.

Metal foams are expected to find use in structural applications where weight is of particular concern, such as space vehicles, rotorcraft blades, car bodies or portable electronic devices. The obvious structural application of metal foam is for light weight sandwich panels, made up of thin solid face sheets and a metallic foam core. The stiffness of the sandwich structure is increased by separating the two face sheets by a light weight foam core. The resulting high-stiffness structure is lighter than that constructed only out of the solid metal material. Since the face sheets carry the applied in-plane and bending loads, the sandwich architecture is a viable engineering concept. However, the metal foam core must resist transverse shear loads and compressive loads while remaining integral with the face sheets. Challenges relating to the fabrication and testing of these metal foam panels remain due to some mechanical properties falling short of their theoretical potential. Theoretical mechanical properties are based on an idealized foam microstructure and assumed cell geometry. But the actual testing is performed on as fabricated foam microstructure. Hence in this study, a high fidelity finite element analysis is conducted on as fabricated metal foam microstructures, to compare the calculated mechanical properties with the idealized theory. The high fidelity geometric models for the FEA are generated using series of 2D CT scans of the foam structure to reconstruct the 3D metal foam geometry. The metal foam material is an aerospace grade precipitation hardened 17-4 PH stainless steel with high strength and high toughness. Tensile, compressive, and shear mechanical properties are deduced from the FEA model and compared with the theoretical values. The combined NDE/FEA provided insight in the variability of the mechanical properties compared to idealized theory.

The spoilers on an aircraft are responsible for several tasks, including execution of roll maneuvers, lift dumping (aerodynamic "spoiling"), and braking. The examined spoiler is manufactured from carbon fiber reinforced composite material and is attached to the wing by four bearing hinges and one actuator hinge. Correct spoiler design involves knowledge of the loads acting on the spoiler, calculation of stresses and strains, and examination of possible failures. Additionally, the fatigue and damage tolerance evaluation of such a spoiler has to follow established certification protocols. This study defines a load cycle based on in-service loadings, including aerodynamic loading, wing bending, inertial loading, and actuator loading. A finite element model of the spoiler is used to calculate the reaction forces in the hinges and the strain in the carbon fiber components occurring during the load cycle. The Miner Rule is used to calculate the fatigue life of the hinges based on the computed stress. A damage tolerance evaluation is then performed assuming that different hinges have failed. Finally, a certification test for fatigue and damage tolerance evaluation of a spoiler is discussed.

Composite sandwich structures are important as structural components in modern lightweight aircraft, but are susceptible to catastrophic failure without obvious forewarning. Internal damage, such as disbonding between skin and core, is detrimental to the structures' strength and integrity and thus must be detected before reaching critical levels. However, highly directional low density cores, such as Nomex honeycomb, make the task of damage detection and health monitoring difficult. One possible method for detecting damage in composite sandwich structures, which seems to have received very little research attention, is analysis of global modal parameters. This study will investigate the viability of modal analysis techniques for detecting skin-core disbonds in carbon fiber-Nomex honeycomb sandwich panels through laboratory testing. A series of carbon fiber prepreg and Nomex honeycomb sandwich panels-representative of structural components used in lightweight composite airframes-were fabricated by means of autoclave co-cure. All panels were of equal dimensions and two were made with predetermined sizes of disbonded areas, created by substituting areas of Teflon release film in place of epoxy film adhesive during the cure. A laser vibrometer was used to capture frequency response functions (FRF) of all panels, and then real and imaginary FRFs at different locations on each plate and operating shapes for each plate were compared. Preliminary results suggest that vibration-based techniques hold promise for damage detection of composite sandwich structures.

A new method for signal processing of non-linear and non-stationary data, the Hilbert Huang Transform (HHT), offers insight into signals that cannot be achieved using conventional methods such as the Fourier transform and wavelet decompositions. This study investigates HHT as a potential tool for damage detection, to be eventually incorporated into a realistic structural health monitoring system. After a review of the method and supporting research, an analytical study begins to offer insight into the behavior of HHT. First, HHT is performed on simple sinusoid signals to see how it separates frequency content, then on the same signal with noise added. Finally HHT is performed on data generated from a numerical 8-degree-of-freedom mass-spring system with random burst excitation, where the stiffness of one spring can be decreased to simulate damage. The study finds that there is considerable variability associated with the implementation of HHT. Many variables, such as sampling frequency and overlapping frequencies, can affect the output of HHT drastically, possibly detracting from the value of the result. The method may, however, automatically separate noise from a signal. Application of HHT to the mass-spring system showed that there was only a noticeable pattern to the effect of damage when that damage became severe. However, the implementation process used may need to be more refined before final assessment can be made. Generally, the variability of HHT needs to be better quantified and understood so that a damage index can be derived based on the unique information that the method provides from signals. If this is possible, HHT could be an important tool for structural damage detection and health monitoring.

The nonlinear model of the cracked Jeffcott rotor is investigated, with the particular focus on study of rotor's vibrational response using tools of nonlinear dynamics. The considered model accounts for nonlinear behavior of the crack and coupling between lateral and torsional modes of vibrations. Load torque is applied to the rotor which is laterally loaded with a constant radial force (gravity force) and unbalance excitation. The co-existence of frequencies of lateral modes in the frequency spectra of torsional mode are characteristics of the coupling response of lateral and torsional vibrations. When only the lateral excitations are applied, vibration amplitude bifurcation plot with the shaft speed as a control parameter, demonstrates some speed ranges for which vibrations of the rotor dramatically increase. Furthermore, the torsional response amplitude at the same speed ranges also increases and chaotic behavior can be observed due to the lateral excitations. These phenomena cannot be observed for pure lateral vibration response with the torsionally rigid rotor assumption.

Developing health management and ultrasafe engine technologies are the primary goals of NASA's Aviation Safety Program. Besides improving safety, health monitoring can also reduce maintenance costs. A unique disk spin simulation system was assembled by the Nondestructive Evaluation (NDE) Group at NASA Glenn Research Center to verify and study a crack detection technique based upon observing center of mass changes of the rotor system using various sensing technologies. This paper describes the finite element analysis results of low cost, a 25.4 cm (10 in.) diameter, flat turbine disk used to evaluate the detection techniques by simulating typical cracks observed in turbine engine disks. Changes in radial tip displacement and center of mass are presented as a function of speed, crack size and location.

Techniques for quality control and health monitoring of aerospace composite structures must be reliable, nonintrusive and preferably, non-contacting. Quadrupole resonance (QR) spectroscopy can fill this need. Previously, we have demonstrated that Quadrupole Resonance can be used for nondestructive inspection of polymeric fiber-reinforced composites, which can be exploited for both in-service inspection and on-going structural health monitoring.1-6 In this paper we present an extension of this work, applying the QR method to the quality control of composite parts manufactured via pultrusion. In order to use the QR method for quality control of composite parts they must contain a small amount of tiny crystals of a QR active compound. These crystals are embedded in the part during the manufacture by blending it into the uncured resin. The QR active crystals sense any residual strains that may form inside the part during the manufacturing process. The crystals are interrogated via a single-side coil detector head, which transmits radio frequency (RF) pulses into the composite part. The strain-dependent QR response from the crystals is picked up by the same detector head. The results presented in this paper demonstrate that the QR method is very successful at distinguishing composites parts manufactured under optimal conditions from those that were manufactured with a misaligned die or at reduced temperatures. Both QR frequency and line widths were used as a distinguishing parameter.

Recently, an increased need for effective NDE tools for layered structures has been observed with the increased use of bonded structures (e.g. GLARE) and carbon fiber reinforced panels (CFRP) in modern aircraft constructions. NDE of multilayered airspace structures can be performed using ultrasonic spectroscopy which makes use of the information in the frequency domain generated due to the constructive and destructive interference of elastic waves. The paper presents a novel narrowband ultrasonic spectroscopy (NBS) technique which utilizes specially designed resonance transducers with carefully selected narrow frequency bands. The NBS is based on sensing electrical impedance of the piezoelectric transducer in the vicinity of its resonance. The theoretical model which enables predicting the resonance frequencies and modal shapes of the thickness mode resonances occurring in multi-layered structures is presented in the first part of the paper. The model includes the KLM equivalent circuit of a piezoelectric transducer used for sensing the resonances. Theoretical and experimental results are presented showing the relation of the impedance plane indications to the parameters of adhesive in aluminum sandwich structures. Results of the mechanized inspection CFRP specimens are presented in the second part of the paper.

Corrosion begins as moisture penetrates the protective barrier of a surface, starting an electrochemical process which over time leads to surface pitting. The combined action of mechanical stresses and corrosion induced pitting reduces structural integrity as the pits enlarge to form nucleation sites for surface cracks, which propagate into through-the-thickness cracks. In most cases, the total mass loss due to corrosion within the structure is small; however, significant reductions in mechanical strength and fatigue life can occur in the corroded material leading to advanced crack growth rates or fast fracture. Since the structural damage due to localized corrosion pitting is small and the crack growth rates may be large, traditional inspections methods and "find it and fix it" maintenance approaches may lead to catastrophic mechanical failures. Therefore, precise structural health monitoring of pre-crack surface corrosion is paramount to understanding and predicting the effect corrosion has on the fatigue life and integrity of a structure. In this study, the impedance method was experimentally tested to detect and quantify the onset and growth of pre-crack surface corrosion in beam and plate like structures. Experimental results indicate the method is an effective detection and tracking tool for corrosion induced structural damage in plates and beams. Additionally, impedance based monitoring of the corrosive effect on the piezoelectric sensors may serve as a useful tool for predicting corrosion growth rates on the surface of structures.

Recent progress on the development of optical fiber sensors for both static and dynamic characterization of new ceramic-matrix composite aerospace structural materials is presented. Optical fiber sensors are employed over electrical strain gage equivalents due primarily to their lower mass, all dielectric construction, and ability to survive much higher temperatures than traditional wire-based strain gage instrumentation. In addition, the fiber sensor design ensures that it is shielded from surface shear strains that typically lead to fatigue-induced failure of wire-filament gages exposed to dynamic loading.

Recent interest in bonded composite patch repair technology for aerospace systems is because this method can be carried out at a reduced cost and time and can easily be applied to complex geometric structures. This paper details the development of a dual stiffness/energy sensor for monitoring the integrity of a composite patch used to repair an aluminum structural component. The smart sensor has the ability to predict the elastic field of a given host structure based on the strain state of two sub-sensors integrated into the structure. The present study shows the possibility of using the sensor to deduce the local instantaneous host stiffness. Damaged structures are characterized by a reduction in their elastic stiffness that evolve from microstructural defects. A local smart sensor can be developed to sense the local average properties on a host. In this paper, sensors are attached to a structure and a modified Eshelby's equivalent inclusion method is used to derive the elastic properties of the host. An analytical derivation and a sensitivity analysis for the quasistatic application is given in a papers by Majed, Dasgupta, Kelah and Pines. A summary of the derivation of the dynamic Eshelby tensor is presented. This is of importance because damage detection in structures undergoing vibratory and other motions present a greater challenge than those in quasistatic motion. An in-situ health monitoring active sensor system for a real structure (an aluminum plate with an attached repair patch) under close-to real lifecycle loading conditions is developed. The detection of the onset of any damage to the structure as well as the repair patch and the subsequent monitoring of the growth of this damage constitute important goals of the system. Both experimental and finite element methods were applied. Experimental results are presented for tests of the aluminum plate with the repair patch under monotonic quasi-static and dynamic loading vibratory conditions. In summary, the study shows that smart bonded composite repair patches are very effective in the repair of thin aluminum structures since they are able to determine the integrity of the repair structure as well as the repair patch.

Terahertz NDE is being examined as a method to inspect the adhesive bond-line of Space Shuttle tiles for defects. Terahertz signals are generated and detected, using optical excitation of biased semiconductors with femtosecond laser pulses. Shuttle tile samples were manufactured with defects that included repair regions unbond regions, and other conditions that occur in Shuttle structures. These samples were inspected with a commercial terahertz NDE system that scanned a tile and generated a data set of RF signals. The signals were post processed to generate C-scan type images that are typically seen in ultrasonic NDE. To improve defect visualization the Hilbert-Huang Transform, a transform that decomposes a signal into oscillating components called intrinsic mode functions, was applied to test signals identified as being in and out of the defect regions and then on a complete data set. As expected with this transform, the results showed that the decomposed low-order modes correspond to signal noise while the high-order modes correspond to low frequency oscillations in the signal and mid-order modes correspond to local signal oscillations. The local oscillations compare well with various reflection interfaces and the defect locations in the original signal.

SiC/SiC composite materials targeted as turbine components for next generation aero-engines are being investigated at NASA Glenn Research Center. In order to examine damage mechanisms in these materials, SiC/SiC coupons were impacted with 1.59 mm diameter steel spheres at increasing velocities from 115 m/s to 400 m/s. Pulsed thermography, a nondestructive evaluation technique that monitors the thermal response of a sample over time, was utilized to characterize the impact damage. A thermal standard of similar material was fabricated to aid in the interpretation of the thermographic data and to provide information regarding thermography system detection capabilities in 2.4 mm thick SiC/SiC composite materials. Flat bottom holes at various depths with aspect ratios greater than 2.5 were detectable in the thermal images. In addition, the edges of holes at depths of 1.93 mm into the sample were not as resolvable as flat bottom holes closer to the surface. Finally, cooling behavior was characterized in SiC/SiC materials and used to determine impact damage depth within an 8.5% error of a known depth.

It's widely accepted that stress concentration and deformation caused by processing will induce local magnetic field abnormality. However, what role the geomagnetic environment act in this phenomenon is a problem causing people's concern all the time. In this paper, annealed samples were designed to remove the non uniform distribution of magnetic field resulted by processing; local stress concentration and deformation were implemented on samples by bending manually in magnetic-free space; comparison of magnetic aberration were made between the geomagnetic field and magnetic-free space after deformation. It was found that geomagnetic environment plays the leading effect on above magnetic abnormality phenomenon, and the magnitude of aberration was found to vary with materials, especially the carbon content.

The paper describes some new developments in the field of contactless and nondestructive determination of the layer and coating thickness on different substrates. 1) The first method is based on millimeterwaves which are emitted and re-ceived by a compact integrated radar sensor. 2) Another approach is based on thermal effects induced in the coating by flash heating or laser light heating. The temperature response of the test object is monitored by an infrared sensor. 3) With the help of an airborne ultrasonic transducer the thickness of powder coating, e.g. ceramics-coating on steel, can be determined contactlessly with an accuracy of better than 5 μm.

X-ray refraction is a relatively new technology for the characterization of inner surfaces or interfaces in structures. When an X-ray crosses an interface in an object, X-ray refraction occurs. The index of refraction, n=1-δ, where δ~1x10^-6 for typical X-ray energies, leads to refraction angles of several arc seconds. As the X-ray energy increases, the refraction angle decreases, making it more difficult to separate the refraction beam from the main X-ray beam. Most X-ray refraction work has used low energies, typically under 35 keV. The penetration of X-ray beams with energies below 35 keV is poor, limiting the method to low density objects or very small samples. It is desired to apply this method to larger samples of aerospace materials such as aluminum and titanium alloys and composite structures. The ability to nondestructively detect micro-porosity and crack initiation at length scales of 0.1 to 100 microns would greatly advance the understanding of the properties of these materials. In particular, this will enable the detection of very small cracks generated in the early stages of fatigue during a specimen life cycle. In our current work, we are evaluating the use of high energy polychromatic X-ray beams to generate refraction signals from material discontinuities. This paper includes the design and preliminary results for our high energy refraction system. We have demonstrated a refraction signal at boundaries using a filtered 120 kVp beam. We also discuss the limits to refraction analysis, and describe our plans for further development of our X-ray refraction system.

A bridge management system developed for the Mexican toll highway network applies a probabilistic-reliability model to estimate load capacity and structural residual life. Basic inputs for the system are the global inspection data (visual inspections and vibration testing), and the information from the environment conditions (weather, traffic, loads, earthquakes); although, the model takes account for additional non-destructive testing or permanent monitoring data. Main outputs are the periodic maintenance, rehabilitation and replacement program, and the updated inspection program. Both programs are custom-made to available funds and scheduled according to a priority assignation criterion. The probabilistic model, tailored to typical bridges, accounts for the size, age, material and structure type. Special bridges in size or type may be included, while in these cases finite element deterministic models are also possible. Key feature is that structural qualification is given in terms of the probability of failure, calculated considering fundamental degradation mechanisms and from actual direct observations and measurements, such as crack distribution and size, materials properties, bridge dimensions, load deflections, and parameters for corrosion evaluation. Vibration measurements are basically used to infer structural resistance and to monitor long term degradation.

As the damage diagnosis of bridge structure is highly nonlinear in nature, it is difficult to develop a comprehensive model taking into account all of the independent variables, such as the structural and environmental properties, using conventional modeling techniques. In this study, a method was introduced for damage diagnosis of bridge structure by integration of BP artificial neural network (ANN) and information fusion based on D-S evidential theory. The basic probability assignment functions for data fusion were constructed according to the demand of the damage diagnosis and the real conditions of the bridge structure. And an application example of the proposed method was demonstrated. The results showed that the integration of the two strategy can remove the shortcoming of BP ANN with remaining of its advantages and promote the identified veracity of the whole diagnosis system.

This paper discusses research to develop ultrasonic methods for materials characterization of an innovative new material known as Reactive Powder Concrete (RPC). Also known as Ultra-high performance concrete (UHPC), this relatively new material has been proposed for the construction of civil structures. UHPC mix designs typically include no aggregates larger than sand, and include steel fibers 0.2 mm in diameter and 12 mm in length. These steel fibers increase the strength and toughness of the UHPC significantly relative to more traditional concretes. Compressive strengths of 200 to 800 MPa have been achieved with UHPC, compared with maximum compressive strength of 50 to 100 MPa for more traditional concrete materials. Young’s modulus of 50 to 60 GPa are common for UHPC. However, the curing methods employed have a significant influence on the strength and modulus of UHPC. This paper reports on the development of ultrasonic methods for monitoring the elastic properties of UHPC under a series of curing scenarios. Ultrasonic velocity measurements are used to estimate the bulk elastic modulus of UHPC and results are compared with traditional, destructive methods. Measurements of shear moduli and Poisson's ratio based on ultrasonic velocity are also reported. The potential for the development of quality control techniques for the future implementation of UHPC is discussed.

A laser-ultrasonic technique is described to non-destructively determine residual stresses in metals such as those produced by shot peening. The method is based on monitoring the small ultrasonic velocity change of the laser-generated surface skimming longitudinal wave (LSSLW) propagating just below the surface. The main advantage of using LSSLW is that the effect of surface roughness induced by shot peening is greatly reduced compared to using surface acoustic waves (SAW). To improve resolution in the measurement of small velocity changes, a cross-correlation technique is used with a reference signal taken on the same but unstressed material in similar conditions. Also, the low-frequency SAW can be used to correct the LSSLW results when affected by minute changes in the path length during the measurements. The validity of the approach is demonstrated by measuring quantitatively the near surface stress in a four-point bending experiment with different levels of surface roughness. Then, scanning results on properly and improperly laser shock peened samples are reported. In particular, the LSSLW velocity variations for the properly peened samples clearly show an increase in the laser-peened area well indicative of a compressive stress.