This PDF file contains the front matter associated with SPIE Proceedings Volume 7982, including the Title Page, Copyright information, Table of Contents, and the Conference Committee listing.

Fibre optic sensors have been an important stimulus toward the realisation of the 'smart' structure since the concept became mooted over quarter of a century ago. Indeed without the prospect for the fibre optic 'nervous system' the practicality of achieving the smart structures goal would be significantly impaired. This paper endeavours to present a snapshot of the achievements which fibre based sensor technology has contributed to smart structures and identifies some of the ongoing needs for continued evolution in both the technology itself and, possibly even more important, in the users' perspective on the prospects which fibre optic sensing systems can offer. In particular the tools inherent in distributed sensing which is unique to the fibre optic platform, and in long chains of fibre Bragg gratings, are especially relevant.

A crack arrester has been recently developed to suppress crack propagation along the interface between the facesheet and the core of foam core sandwich structures. The crack arrester is a semi-cylindrical stiff material inserted into the interface. The crack arrester decreases an energy release rate at the crack tip by suppressing local deformation around the crack. If the arrested crack can be instantaneously detected, damage tolerance of foam core sandwich structures is dramatically improved. This study establishes an innovative crack detection technique using metal wires and fiber Bragg grating (FBG) sensors embedded at both edges of the arrester. Specific strain distribution induced by arresting the interface crack is first memorized by the metal wire and the consequent residual strain is then picked up by the FBG sensor as a damage signal. This study began by simulating sensor response to evaluate the feasibility of the proposed technique. A verification test was then conducted, confirming the spectral change of the FBG can indicate propagation direction and tip location of the arrested crack.

The recent progress in long range sensor based on Brillouin scattering has been summarized, the limitation on sensing length, spatial resolution, different approaches to improve the limitation have been discussed. Two examples on frequency division multiplexing (FDM) and time-division-multiplexing (TDM) to extend the sensing range of the distributed Brillouin sensor via BOTDA without inline amplifiers have been proposed and demonstrated. Using FDM concept we demonstrate a 75 km BOTDA with three types of 25 km fiber achieving a spatial resolution of 1.1 m and an accuracy of 1°C/20με at the end of 75 km, and a spatial resolution of 0.5 m and an accuracy of 0.7°C/14με at the end of 50 km. Using TDM technique, we demonstrate a 100 km sensing fiber of 0.6 m and 2 m spatial resolution at the end of 75 km, and at 100 km achieving a Brillouin frequency shift accuracy of 1.5 MHz, this is equivalent to 1.5°C temperature resolution and strain resolution of 30με, respectively.

In this paper, an overview of optical sensor development, testing and evaluation for several geotechnical monitoring applications is presented. Additionally, sensor integration and data interpretation are addressed as key influences to the overall success of the monitoring project. They should be taken into consideration already in the design stage. Particular focus is given on strain sensor development to minimize the slippage of the fiber inside the protection. For the first time, slippage progression monitoring by high spatially resolved Brillouin measurements is presented as a new tool for sensor testing and evaluation for geotechnical projects. The main findings of the study are that in a geotechnical monitoring project, special care has to be taken by choosing the sensor slippage properties, longitudinal stiffness and robustness, as well as in the design of the sensor system itself (fixation, gauge length and bond strength). With appropriate alignment of these factors, reasonable monitoring data can be obtained, as shown in the applications proposed in this manuscript.

Traditionally, distributed BOTDR technique is applied in the field of the structural heath monitoring (SHM) on the large scale. However, if the sensing length is relatively small, the number of valid sampling points on the sensing fiber will be quite limited. Therefore, how to pick out valid sampling points from a large amount of sampling points becomes a key to apply distributed BOTDR technique into the field of small-scale monitoring successfully. This paper presents the concepts of valid sampling points (VSPs), invalid sampling points (ISPs) and useless sampling points (USPs), proposes SRSI Method to select VSPs, derives the error theory of ISPs and analyzes the experimental data by SRSI Method, Peak Method and the error theory of ISPs in the temperature and strain monitoring tests. In the above tests, different sensing lengths of the fiber or spatial resolutions were set for comparison with each other. The test results show that SRSI Method, which can improve the accuracy of the test results effectively, is the better selecting method of VSPs than Peak Method, and especially, the number of VSPs on the sensing fiber is less, the SRSI Method is better. Meanwhile, the error theory of ISPs gives the error bound and a good explanation of the large errors of Peak Method.

Embedded sensors provide a high sensitivity to sub-surface damage due to their proximity to the damage features. In particular, fiber Bragg gratings (FBG) are easily embedded into laminates with a minimum of perturbation to the surrounding material microstructure. This paper summarizes some recent advances derived from full-spectral interrogation of FBG sensors for structural health monitoring and damage identification in composites. In particular we will present signals from the FBG reflected spectra that have been correlated to stress concentrations near crack tips, curing conditions during processing of composite laminates and the progression of delamination due to multiple low-velocity impacts in woven composite laminates and foam-core sandwich composites. Recent advances in interrogation systems for these sensors will also be discussed which have permitted dynamic evaluation of these parameters. Finally, spectral distortion can lead to errors in the interpretation of strain values from the peak wavelength measurement when peak waveforms are assumed. This distortion is highly dependent upon the local microstructure surrounding the sensor and therefore cannot be compensated a-priori through a calibration factor. This article demonstrates that full-spectral interrogation can provide sensor specific error compensation for these measurements. These results demonstrate the richness of information that can be obtained from full-spectral interrogation of FBG sensors in a complex, multiple stress component environment.

This work presents a statistical model for the propagation of noise through interferometric demodulation processes. Using the case of a 3×3 passive digital demodulation algorithm, an exact transfer function and its associated probability structure for intensity noise propagation through a fiber Bragg grating sensor interrogation system is derived. This new model is generalized to any input noise probability structure and includes the possibility of full or partial correlation among the demodulation input channels. This work then presents results for the specific case of Gaussian intensity noise (with and without channel correlations) and shows explicit interferometer phase influence on output noise statistical moments, which are important for signal-to-noise predictions. The demodulators nonlinear transfer function is shown to induce output bias as well as either attenuate or amplify output variance, depending upon the signal phase. Experimental data are provided to validate the model. This model generalizes to support predicting output noise levels in Bragg grating-based sensing systems.

Ultrasonic Lamb waves can be detected by various optical sensors, including polarimetric and FBG fibre sensors embedded within a sample plate. The difference between the responses of two types of optical fibre sensors, both positioned at different depths within a carbon fibre composite plate, to the first symmetric (S₀) and antisymmetric (A₀) Lamb waves are described. These responses illustrate the differences in internal strains and pressures characteristic of the two modes and may be used to identify phenomena such as mode conversion that might be caused by either structural features or damage within the material.

In this study we evaluate the measurements of a fiber Bragg grating (FBG) sensor subjected to a non-uniform static strain state and simultaneously exposed to vibration loading. The full spectral response of the sensor is interrogated in reflection at 100 kHz during two loading cases: with and without an added vibration load spectrum. The static tensile loading is increased between each test, in order to increase the magnitude of the non-uniform strain field applied to the FBG sensor. The spectral distortion due to non-uniform strain is observed to change once the sensor is exposed to a non-transient 150 Hz vibration spectrum. With high-speed full spectral interrogation, it is potentially possible to separate this vibration-induced spectral change from spectral distortions due to non-uniform strain. Such spectral distortion contains valuable information on the static damage state of the surrounding host material.

Fiber optic sensors have become widely used for structural health monitoring in recent decades. The aim of this research is to characterize the dynamic failure signals emitted in fiber reinforced polymer (FRP) stay cable and specimens using Fiber Bragg Gratings (FBGs) and two types of interferometric demodulation systems, namely Michelson interferometer (MI) and two-wave mixing interferometer (TWMI) for detection. Due to its one-dimensional form, only one FBG and the Michelson interferometer are used for damage monitoring in a carbon FRP stay cable under various types of loading. Michelson interferometer is capable of detecting frequency contents extending up to 500 kHz, where frequency contents below 250 kHz are categorized as matrix failure and those above 300 kHz corresponded to fiber failure. Two channels of FBGs are used with the TWM interferometer to track local damage in coupon-size FRP samples. Using TWM scheme, continuous and burst acoustic emission events are detected with frequency responses extending up to 125 kHz in coupon-size GFRP specimens, limited only by the sampling rate of the data acquisition system. The experimental results suggest that both types of FBG demodulation systems may be suitable for monitoring high frequency mechanical strains in civil structures, providing a tool for local structural damage detection.

This paper describes selected work in the area of fiber optic smart structures performed by the author and his colleagues at McDonnell Douglas, Blue Road Research and Columbia Gorge Research over the past 25 years. It is intended to provide an overview of some of the developments in the field and how it evolved over this time span. Application areas that will be addressed include aerospace, civil structures and composite materials.

With nearly one quarter of today's highway bridges rated as structurally deficient or functionally obsolete, it is ever more important to quantify the safe level of performance using in-situ structural health monitoring techniques. This paper discusses the experimental testing of a single simply supported span composite superstructure under various controlled progressive damage cases. The single span is part of a three span bridge located in northern New York. Using strain transducers mounted at the midspan and support locations, changes in load distribution factors and neutral axis locations are calculated to detect changes in load shedding behavior and structural capacity of the bridge span as diaphragm connections were severed and support conditions were altered to different levels. The results of the testing show that changes in the bridge response can be tracked as damage is introduced to the superstructure. The measurements are used to identify the diagnostic load testing parameters that can be used as structural health indicators that can in turn be used to complement current inspection protocols. Furthermore, the measurements also help provide a basis for future development of a performance index to be used in conjunction with existing condition rating measures for improved bridge condition assessment.

In this paper we present the design and test of printed strain sensors, which can be integrated in light-weight structures for monitoring purposes. We focus on composite structures consisting of metal substrate as well as insulating and conductive ink layers for sensing normal strain at the surface. Both, inkjet and screen printing technology are used to realize resistive topologies that can be evaluated using a Wheatstone bridge configuration. In a first step, we analyze electrical properties of functional inks: electrical impedance and breakdown electrical field strength in case of insulation inks, resistance in case of conducting inks. Silver and PEDOT:PSS based suspensions are printed as sensing layer. To determine the resistance change due to plastic deformation of the metal substrate, tensile tests are performed up to 30% strain and subsequent resistance change is measured. In a second step, the sensing effect of printed conductive structures is investigated. Resistive sensing topologies are designed for detecting longitudinal and transversal normal strain. Meander structures, which form single resistors as well as bridge configurations, are printed on test specimens and analyzed in a four-point bending set up. Performing loading and unloading cycles, gauge factor, cross sensitivity, nonlinearity and hysteresis error of the sensors are measured.

In structural health monitoring (SHM) systems for civil structures, signal compression is often important to reduce the cost of data transfer and storage because of the large volumes of data generated from the monitoring system. Compressive sensing is a novel data compressing method whereby one does not measure the entire signal directly but rather a set of related ("projected") measurements. The length of the required compressive-sensing measurements is typically much smaller than the original signal, therefore increasing the efficiency of data transfer and storage. Recently, a Bayesian formalism has also been employed for optimal compressive sensing, which adopts the ideas in the relevance vector machine (RVM) as a decompression tool, such as the automatic relevance determination prior (ARD). Recently publications illustrate the benefits of using the Bayesian compressive sensing (BCS) method. However, none of these publications have investigated the robustness of the BCS method. We show that the usual RVM optimization algorithm lacks robustness when the number of measurements is a lot less than the length of the signals because it can produce sub-optimal signal representations; as a result, BCS is not robust when high compression efficiency is required. This induces a tradeoff between efficiently compressing data and accurately decompressing it. Based on a study of the robustness of the BCS method, diagnostic tools are proposed to investigate whether the compressed representation of the signal is optimal. With reliable diagnostics, the performance of the BCS method can be monitored effectively. The numerical results show that it is a powerful tool to examine the correctness of reconstruction results without knowing the original signal.

The variation of the electrical properties of fiber reinforced polymers when subjected to load offer the ability of strain and damage monitoring. This is performed via electrical resistance and electrical potential measurements. On the other hand Carbon Nanotubes (CNTs) have proved to be an efficient additive to polymers and matrices of composites with respect to structural enhancement and improvement of the electrical properties. The induction of CNTs increases the conductivity of the matrix, transforming it to an antistatic or a conducting phase. The key issue of the structural and electrical properties optimization is the dispersion quality of the nano-scale in the polymer phase. Well dispersed CNTs provide an electrical network within the insulating matrix. If the fibers are conductive, the CNT network mediates the electrical anisotropy and reduces the critical flaw size that is detectable by the change in conductivity. Thus, the network performs as an inherent sensor in the composite structure, since every invisible crack or delamination is manifested as an increase in the electrical resistance. The scope of this work is to further exploit the information provided by the electrical properties with a view to identify strain variation and global damage via bulk resistance measurements. The aforementioned techniques were employed to monitor, strain and damage in fiber reinforced composite laminates both with and without conductive nanofillers.

With the advent and development of low-cost wireless structural health monitoring systems, the task of routinely assessing the in-service condition of highway bridges through distributed sensor-based measurements is an increasingly feasible component of bridge safety and management practice. Bridge monitoring encompasses placement of often a limited number of distributed sensors across a relatively large and complex structural system. Consequently, the selection of proper sensor locations is imperative to extraction of the most value from the recorded measurements. An experimental investigation is presented wherein sensor placement on the superstructure girders or primary beams is contrasted to the response measured on the surface of the bridge deck. The effect on the dataset richness, as evidenced by the modal content, is presented and conclusions regarding optimal placement for this structure type are presented. To affirm the plausibility of the observed responses and conclusions drawn, a finite element analysis is also performed on a model developed from the as-built drawings.

In wireless sensor networks (WSNs), locations of sensors play a critical role in many applications. For some applications, the nodes are constantly moving in the network. Therefore, the positions of nodes in mobile WSNs can not be determined by current static localization algorithms. To solve this problem, a new centralized localization algorithm called node cooperation based support vector machine localization (NCBSVML) algorithm for mobile wireless sensor networks is proposed. NCBSVML algorithm classified the network into many classes, and justifies which class is node in. Then the NCBSVML algorithm determines the node location by filtering the impossible locations based on new observations. Our approach does not require additional hardware and works even when the movement of anchors and nodes is uncontrollable. The properties of our technique are analyzed from simulations. Our scheme outperforms the best known mobile localization schemes in accuracy and precision under a wide range of conditions.

Fiber optic sensors are increasingly used because of their outstanding performance or if special requirements avoid the application of conventional electrical sensors. The scientific background for optical fiber sensors is well developed; however, the characteristic of sensors applied in rather harsh environment are almost always different from characteristics determined in laboratory or before its installation. In order to achieve long-term stable function and reliable measurement data after application and under harsh environmental conditions, guidelines for characterization and specification of sensor components are needed as well as methodologies for testing the sensor performance must be developed. Performance tests carried out revealed that there are still some restrictions with respect to long-term reliable use: first, some sensor products available on the market are not very often appropriately characterized, described and validated; second, application procedures are not always defined due to a lack of understanding the micromechanical issues in the interface zone between sensor and measuring object. Application procedures and profound knowledge of materials behaviour are necessary to get results from the sensor that can be reliably used. The paper describes first guidelines to prove the quality of fiber optic strain sensors, a testing facility developed for unbiased tests and certification of surface-applied sensors as well as result from comparison of commercially available strain sensors.

This paper demonstrates the value of D-type optical fibers (D-fibers) in a variety of sensing applications. The principal advantage of the D-fiber is that it allows for interaction with light traveling in the core of an optical fiber with materials or structures placed in contact with the fiber. This permits stimulus sensitive materials to be placed on the D-fiber to interact with the light in the core of the fiber. The presentation shows that this feature of D-fibers can be used to create alternatives to sensors formed in standard optical fibers for measuring temperature, strain, and shape change. In addition, D-fiber sensors have been fabricated to measure chemical concentrations, and electric fields.

Modern electronics are often shielded with metallic packaging to protect them from harmful electromagnetic radiation. In order to determine the effectiveness of the electronic shielding, there is a need to perform non-intrusive measurements of the electric field within the shielding. The requirement to be non-intrusive requires the sensor to be all dielectric and the sensing area needs to be very small. The non-intrusive sensor is attained by coupling a slab of non-linear optical material to the surface of a D shaped optical fiber and is called a slab coupled optical fiber sensor (SCOS). The sensitivity of the SCOS is increased by using an organic electro-optic (EO) polymer.

This paper provides a description of electric field sensing using the slab coupled optical fiber sensor (SCOS) with an emphasis on the detection electronics. This analysis includes estimated signal strength and the main noise sources. With all noise eliminated except for the shot noise in the photodetector, thermal noise in the terminating resistor, and the thermal noise in the low noise amplifier the theoretical sensitivity is calculated to be 0.85 V/m Hz^0.5. The signal is measured using an electrical spectrum analyzer and found to have a sensitivity of 1.34 V/m Hz^0.5.

The intensity distribution of a transmission from a single mode optical fiber is often approximated using a Gaussian-shaped curve. While this approximation is useful for some applications such as fiber alignment, it does not accurately describe transmission behavior off the axis of propagation. In this paper, another model is presented, which describes the intensity distribution of the transmission from a single mode optical fiber. A simple experimental setup is used to verify the model's accuracy, and agreement between model and experiment is established both on and off the axis of propagation. Displacement sensor designs based on the extrinsic optical lever architecture are presented. The behavior of the transmission off the axis of propagation dictates the performance of sensor architectures where large lateral offsets (25-1500 μm) exist between transmitting and receiving fibers. The practical implications of modeling accuracy over this lateral offset region are discussed as they relate to the development of high-performance intensity modulated optical displacement sensors. In particular, the sensitivity, linearity, resolution, and displacement range of a sensor are functions of the relative positioning of the sensor's transmitting and receiving fibers. Sensor architectures with high combinations of sensitivity and displacement range are discussed. It is concluded that the utility of the accurate model is in its predicative capability and that this research could lead to an improved methodology for high-performance sensor design.

In this paper, we consider advanced image processing and artificial intelligence based techniques for design of fiber optic statistical mode sensors. Output from an optical fiber exhibits a speckle pattern when projected on a flat surface, and intensity, size, and location of these speckles do change with external effects like pressure, temperature, vibration, etc. Statistical mode sensors reported in the literature use global image differencing or global correlation like approaches for sensor design. Namely, lots of localized information in the image is not taken into account, instead global difference and/or correlation are used for sensor construction. We propose the use of localized information with image processing techniques; generate more features, and analysis of these via artificial intelligence based methods. In this way, we can capture more information from the speckle pattern distribution, and hence design a better sensor.

The purpose of this study is to develop an innovative non-destructive methodology for analyzing the thermal effects in metallic materials caused by fatigue. Mechanical stresses induced by cyclic loading in the material cause heat release due to microstructural changes, which results in an increase of the material's temperature. The heat release was quantified as a function of fatigue cycles in carbon steel samples. Mechanical hysteresis phenomena were analyzed to identify the metrics of damage, which relates to thermal parameters characterizing the level of damage of the material as a function of fatigue cycles.

Acoustic Emission (AE) supplies information on the fracturing behavior of different materials. In this study, AE activity was recorded during fatigue experiments in metal CT specimens with a V-shape notch which were loaded in fatigue until final failure. AE parameters exhibit a sharp increase approximately 1000 cycles before than final failure. Therefore, the use of acoustic emission parameters is discussed both in terms of characterization of the damage mechanisms, as well as a tool for the prediction of ultimate life of the material under fatigue. Additionally, an innovative nondestructive methodology based on lock-in thermography is developed to determine the crack growth rate using thermographic mapping of the material undergoing fatigue. The thermographic results on the crack growth rate of aluminium alloys were then correlated with measurements obtained by the conventional compliance method, and found to be in agreement.

One of the most frequent problems in concrete structures is corrosion of metal reinforcement. It occurs when the steel reinforcement is exposed to environmental agents. The corrosion products occupy greater volume than the steel consumed, leading to internal expansion stresses. When the stresses exceed concrete strength, eventually lead to corrosion-induced cracking beneath the surface. These cracks do not show any visual sign until they break the surface, exposing the structure to more accelerated deterioration. In order to develop a methodology for sub-surface damage characterization, a combination of non destructive testing (NDT) techniques was applied. Thermography is specialized in subsurface damage identification due to anomalies that inhomogeneities impose on the temperature field. Additionally, ultrasonic surface waves are constrained near the surface and therefore, are ideal for characterization of near-surface damage. In this study, an infrared camera scans the specimen in order to indicate the position of potential damage. For cases of small cracks, the specimens are allowed to cool and the cooling-off curve is monitored for more precise results. Consequently, ultrasonic sensors are placed on the specified part of the surface in order to make a more detailed assessment for the depth of the crack. Although there is no visual sign of damage, surface waves are influenced in terms of velocity and attenuation. The combination of the NDT techniques seems promising for real structures assessment.

We have previously reported a novel Fiber Optic Acoustic Emission Sensor (FOAES), which was specially processed based on fused-tapered optical fiber coupler. The FOAES was packed with silica capillary tube so that it could be embedded in damage monitoring of composite materials. But the linear damage location of acoustic emission using double sensors had not been tried. In this paper, linear damage location experiments with double sensors were tested on aluminium plate and composite plate. The test results showed that linear damage position was identified within ±6.25 mm on aluminium plate and ±4.84 mm on composite plate.

In light of ongoing efforts to reduce weight but maintain durability, designers have examined the use of carbon composite materials for a number of aerospace and civil structures. Along with this has been the study of reliable sensing and monitoring capabilities to avoid catastrophic failure. Fiber Bragg Grating (FBG) sensors are known to carry several advantages in this area one of which is their proven ability to detect acoustic emission (AE) lamb waves of various frequencies. AE is produced in these materials by failure mechanisms such as resin cracking, fiber debonding, fiber pullout and fiber breakage. With such activity there is a noticeable change in Felicity Ratio (FR) in relation to the increase of accumulated damage. FR is obtained directly from the ratio of the stress level at the onset of significant emission and the maximum prior stress at the same AE event. The main objective of this paper is to record the FRs of a carbon/epoxy laminate using FBG sensors and establish its trend as a method for determining accumulated damage in a carbon composite structure.

In this research, the acoustic emissions from simulated crack growth and incremental crack growth in a cyclically loaded aluminum panel were detected by acoustic emission sensors. One of these sensors was comprised of an array of thin strips of piezoelectric material bonded to the specimen and electrically connected. The geometry of these sensor strip arrays and their orientation to the fracture site enabled the sensors to capture the shear component of the acoustic emission waveform. Cyclical loading was used to grow the crack, allowing sensor performance to be assessed in comparison to bonded and resonant sensors. The detection of the shear wave is of particular interest as the shear component of fretting events is often small, providing a possible means of discriminating between critical events (crack propagation) and sources of minimal concern (fretting). Shear modes were detected in the acoustic emissions from both the simulated crack growth and the crack growth due to cyclical loading.

To operate wind turbines safely and efficiently, condition monitoring for the main components are of increasing importance. Especially the lack of access to offshore installations increases inspection and maintenance costs. The current work at Fraunhofer IZFP Dresden in the field of monitoring of wind turbines is focused on the development of a condition monitoring system for rotor blades. A special focus lies on the application of optical technologies for communication and power supply. It is not possible to introduce electrical conductors into the rotor blade since it might cause tremendous damages by lightning. The monitoring concept is based on a combination of low frequency integral vibration monitoring and acoustic monitoring techniques in the frequency range between 10 and 100 kHz using guided waves. A joint application of acousto ultrasonics and acoustic emission techniques will be presented. Challenges and solutions of such a field test like sensor application, data handling and gathering as well as temperature variation are described.

Cast austenitic stainless steel (CASS) that was commonly used in U.S. nuclear power plants is a coarse-grained, elastically anisotropic material. In recent years, low-frequency phased-array ultrasound has emerged as a leading candidate for the inspection of welds in CASS piping, due to the relatively lower interference in the measured signal from ultrasonic backscatter. However, adverse phenomena (such as scattering from the coarse-grained microstructure, and beam redirection and partitioning due to the elastically anisotropic nature of the material) result in measurements with a low signal-to-noise ratio (SNR), and increased difficulty in discriminating between signals from flaws and signals from benign geometric factors. There is therefore a need for advanced signal processing tools to improve the SNR and enable rapid analysis and classification of measurements. This paper discusses recent efforts at PNNL towards the development and evaluation of a number of signal processing algorithms for this purpose. Among the algorithms being evaluated for improving the SNR (and, consequently, the ability to discriminate between flaw signals and non-flaw signals) are wavelets and other time-frequency distributions, empirical mode decompositions, and split-spectrum processing techniques. A range of pattern-recognition algorithms, including neural networks, are also being evaluated for their ability to successfully classify measurements into two or more classes. Experimental data obtained from the inspection of a number of welds in CASS components are being used in this evaluation.

The low energy-conversion efficiency in photoacoustic generation is the most critical hurdle preventing its wide applications. In recent studies, it was found that the selection of the energy-absorbing layer material and design of the acoustic generator structure both determine the photoacoustic conversion efficiency. The selection of the absorbing material is based on its optical, thermal, and mechanical properties. In this research, we calculated and compared the conversion efficiencies of six different absorbing film materials: bulk aluminum, bulk gold, graphite foil, graphite powder-resin mixture, gold nanospheres, and gold nanorods. The calculations were carried out by a finite element modeling (FEM) software, COMSOL Multiphysics. A 2D-axisymmetric model in COMSOL was built up to simulate a 3-layer structure: optical fiber tip, light absorbing film, and surrounding water. Three equations governed the thermo-elastic generation of ultrasonic waves: the heat conduction, thermal expansion and acoustic wave equations. In "thick-film" generation regime, majority of the laser energy is absorbed by the film and converted to high-frequency film vibration, and the vibration excites the ultrasound wave in the adjacent water, while the water would not be heated directly by the laser. From the results of this FEM simulation, the acoustic signal generated by gold nanosphere (or nanorod) film is over two times stronger than that generated by graphite powder-resin film of the same thickness. This simulation provides a strong support to the absorbing material selection for our proposed fiber ultrasound generator.

The present work has proposed a 2-D triangular high precision finite element (HPFE) based on Classical Laminated Plate Theory (CLPT). This high precision plate element with 38 degrees of freedom is used to obtain fundamental frequencies and the mode shapes of a passive composite plate. A standard FEM package-ABAQUS is used to verify the FEM code and to validate the results. The same element is subsequently used with piezoelectric sensory network to develop an active damping matrix that tends to suppress vibration. Control algorithm based on classical negative velocity feedback is used. Simulations are carried out on smart composite plates in time domain for effective vibration suppression. The effect of size and location of PVDF film on settling time and damping ratio at different control gains is studied. The high precision piezoelectric finite element is later used to identify damage signals in a ribbon-reinforced composite. In order to identify the damage, voltage profile is obtained for healthy and delaminated composite plates. A change in sensing voltage is observed at simulated damage locations in comparison to the healthy laminate for two different configurations used in the numerical analysis.

During the interpretation of the Lamb wave data, the main concern is often the arrival times of wave groups. Group arrival times determine the distance of the source or the reflector. The inspection of sensory signal envelopes is satisfactory to identify and localize defects. The S-transformation is proposed for isolating wave forms at their excitation frequency and obtaining their envelopes. To further minimize the storage and computational costs, reduction of the data size by down sampling (skipping 5 data points for each saved one) and compression via calculating the wavelet transformation three times are proposed. The data was reduced to 1/30th of its original size, while the reconstructed wavelet transformation had a less than 1% average error with respect to the down sized envelope signal.

Stainless Steel Metallic Pseudo Rubber (SSMPR) and Shape Memory Alloy Metallic Pseudo Rubber (SMAMPR) are novel porous materials with high elasticity and large restorable deformation, and they are also ideal material for three dimensional isolators or Shock Absorber Devices (SADs). However, the theories on the constitutive model of metallic rubber are seldom studied due to its complicated microstructure. A theory of contact micro-beams with equal section is presented in this study, in which the friction between the metal wires in metallic rubber is considered according to Coulomb's friction law. Firstly, the nonlinear rigidity of the micro-beams in the loading process is derived according to the simplified mathematical model. Then, the parameters in the theoretic model are also determined through establishing the relationship between the macro-structure and the micro-structure based on the law of mass conservation and the probability theory. Especially, the number of contact points between the surfaces of the micro-beams is estimated according to a mathematical function. Finally, combined with the finite element method, the results of normalized stress-strain relationships under compression are obtained and compared with the experimental data.

Applications of Linear Phased array concept have been extended from electromagnetic antennae to many other areas due to their capability to direct, magnify and pick up energy in and from desired directions. Apart from radar, optics and medical imaging, one such growing area is in the non-destructive testing of structures. The extensive use of linear array can be attributed to the attenuation of the waves generated in the structure due to inherent damping and loss in the materials and discontinuities. Linear phased arrays are used as actuator in ultrasonic imaging and diagnostics to magnify the energy at a given direction or point in the structure. In the present work the property of amplifying the wave generated in a particular direction is exploited and is studied on a carbon composite structure. Almost all of the existing imaging methods in context of phased array are based on through thickness and bulk wave modes. In the present research we employ Lamb wave which propagates in a doubly bounded media like structural panels. The spreading of energy in a composite laminate is studied in the form of lobe patterns obtained using amplitude of symmetric Lamb wave mode (S0) with a particular orientation of the linear array with fiber direction. The effect of damage in the form of a delamination in a CFRP composite plate on the lobe pattern is analyzed.

This paper presents experimental results and analysis for different fiber optic microbend sensor configurations by varying the type of fiber, the inner section length of hetero-core fiber, mechanical periodicity, and the number of corrugations. This is the first hetero-core microbend sensor reported in the literature. Hetero-core fibers are built by inserting a single-mode fiber into two multimode fibers. Again as a first in the literature, a new hetero-core type of multimode-multimode-multimode configuration was introduced. It was shown that, this novel triple multimode hetero-core configuration is more sensitive than ordinary optical fiber and the multimode-single mode-multimode configuration. Experimental results show that, as the number of corrugations increases, the sensitivity of the sensor increases. It has also been shown that decreasing the periodicity and the inner section length of the hetero-core fiber also increases the sensor sensitivity.