Automatic flaw detection in sectoral scans using machine learning.

Phased array ultrasonic testing (PAUT) requires highly trained and qualified personnel to interpret and analyze images. It takes a solid understanding of wave propagation physics to comprehend the generated images. As such, the inspector's judgment and level of experience have a significant impact on the analysis's outcome. In addition, the procedure is prone to error and laborious. AI had shown to be effective in computer vision in a variety of classification and detection tasks. Regarding PAUT, studies have also demonstrated that machine learning may be able to identify defects with a level of accuracy that is on par or even superior to that of trained and qualified inspectors. Nonetheless, the use of computer vision in PAUT remains very limited. The primary cause of this is the challenge accessing large databases of labelled inspections. In fact, a considerable amount of training data is required for machine learning. While it is easy to access sizeable, labelled databases of MRI scans or photographs for instance, that is not the case in PAUT because inspection results are usually confidential. In this project, a large database was generated using mock-ups commonly used to train and evaluate inspectors. The different defects contained in these mock-ups were used to train a machine learning model. The data was acquired with several different probes centered at different frequencies. Each acquisition was performed using Full Matrix Capture (FMC). The post-processing of the data contained in the FMC allows to compute any sectoral scan from its focal laws. As a result, a comprehensive database composed of hundreds of thousands of sectoral scans was generated from these few FMC acquisitions. The completeness of this database facilitated robust training of a defect detection model for PAUT sectoral scans. The evaluation of the model demonstrated its ability to generalize even to defect types it had never been trained on. Furthermore, the detection performance remained consistent even in high noise conditions where the Contrast-to-Noise Ratio (CNR) was very low.

Surface breaking crack sizing method using pulse-echo Rayleigh waves.

Surface cracks are common in various industries. Eddy current testing (ECT) is commonly used for crack sizing but necessitates complex calibration standards and a highly trained inspector. Moreover, for large-area inspections, it requires additional scanning arrangements. In recent years the wedge technique-based Rayleigh wave crack sizing method has attracted significant research interest due to its unidirectional excitability. However, Rayleigh wave features generated at crack tips are often weak and masked under noise, and they mostly attenuate before reaching the receiving probe due to the couplant between the wedge-test specimen interface. Consequently, sizing the crack depth is difficult using a pulse-echo setup. This work presents a wedge-free pulse-echo Rayleigh wave method for surface crack sizing using a conventional phased array transducer. Eliminating the wedge removes a couplant layer leading to lower attenuation, enabling the transducer to capture crack tip features. This allows the sizing of surface cracks in pulse-echo using the time-of-flight (ToF) information. Furthermore, leveraging the phased array system, an averaging technique employed to the time trace signals captured by the transducer elements effectively averages out the other wave modes generated at crack geometries by the scattering of Rayleigh waves. This significantly minimizes sizing errors and enhances the signal-to-noise ratio (SNR). The performance of the proposed method is demonstrated through finite element simulations and experiments. Experiments with electric discharged machined (EDM) notches on test specimen surface at various angles and depths mimicking surface-breaking cracks show accurate sizing within a 5% error. The proposed method offers flexibility in performing inspections using a wide frequency range and can be easily applied to different materials using any conventional phased array transducer. This enhances its adaptability for industrial applications in the characterization of surface cracks.

An alternative Rayleigh wave excitation method using an ultrasonic phased array.

Ultrasonic Rayleigh waves have been employed for in-service NDT inspection in a wide range of industries for years. The excitation of Rayleigh waves can be achieved using a variety of methods, with the so-called wedge technique being the most widely used. Recent years have seen considerable research interest in surface crack detection and sizing using Rayleigh waves excited and detected with the wedge technique. However, in this method, Rayleigh waves experience transmission loss at the wedge interfaces. Moreover, the flexibility to generate Rayleigh waves on different waveguides using the same wedge is limited, as the wedge angle depends on the Rayleigh wave wavelength. This work demonstrates a method that provides an alternative Rayleigh wave excitation method. In this, a conventional ultrasonic phased array transducer is used. As there is an appropriate excitation delay between each piezoelectric element of the array transducer, Rayleigh waves can be generated in a wide range of materials using the same phased array transducer. The delay can be estimated based on the elementary pitch of the transducer and the Rayleigh wave velocity of the waveguide. The proposed Rayleigh wave excitation method is demonstrated through both experiments and FE simulations. Furthermore, a finite element model is used to better understand the features of the generated waves and to validate them through their characteristics as Rayleigh wave. A quantitative comparison between the proposed and existing methods is also presented. The directivity and beam divergence of the generated Rayleigh waves are quantified. The results obtained from experiments are in agreement with finite element simulations and demonstrate the possibility of unidirectional and selective excitation of Rayleigh waves through the proposed method. They also highlight the potential for this new excitation method to be used to develop new Rayleigh wave-based inspection methods.

Ultrasonic imaging using conditional generative adversarial networks.

The Full Matrix Capture (FMC) and Total Focusing Method (TFM) combination is often considered the gold standard in ultrasonic nondestructive testing, however it may be impractical due to the amount of time required to gather and process the FMC, particularly for high cadence inspections. This study proposes replacing conventional FMC acquisition and TFM processing with a single zero-degree plane wave (PW) insonification and a conditional Generative Adversarial Network (cGAN) trained to produce TFM-like images. Three models with different cGAN architectures and loss formulations were tested in different scenarios. Their performances were compared with conventional TFM computed from FMC. The proposed cGANs were able to recreate TFM-like images with the same resolution while improving the contrast in more than 94% of the reconstructions in comparison with conventional TFM reconstructions. Indeed, thanks to the use of a bias in the cGANs' training, the contrast was systematically increased through a reduction of the background noise level and the elimination of some artifacts. Finally, the proposed method led to a reduction of the computation time and file size by a factor of 120 and 75, respectively.

Ultrasonic Transducers for In-Service Inspection and Continuous Monitoring in High-Temperature Environments.

The inspection of structures operating at high temperatures is a major challenge in a variety of industries, including the energy and petrochemical industries. Operators are typically performing nondestructive evaluations using ultrasound to monitor component thicknesses during scheduled shutdowns, thereby ensuring safe operation of their plants. However, despite being costly, this calendar-based approach may lead to undetected corrosion, which can potentially result in catastrophic failures. There is therefore a need for ultrasonic transducers designed to withstand permanent exposure to high temperatures, so as to continuously monitor the remnant thicknesses of structures in real time. This paper discusses the design of a heat-resistant ultrasonic transducer based on a piezoelectric element. The piezoelectric material, the electrodes, the backing layer, the wires and the casing are presented in detail from the acoustic and thermal expansion point of view. Four transducers optimized for 3 MHz were manufactured and tested to destruction in different conditions: (1) 72-h temperature steps from room temperature to 750 ∘C, (2) thermal cycles from room temperature to 500 ∘C and (3) 60 days of continuous operation at >550 ∘C. The paper discusses the results, as well as the effect of temperature over time on the properties of the transducer.

Compressive Sensing Strategy on Sparse Array to Accelerate Ultrasonic TFM Imaging.

Phased array ultrasonic testing (PAUT) based on full matrix capture (FMC) has recently been gaining popularity in the scientific and nondestructive testing communities. FMC is a versatile acquisition method that collects all the transmitter-receiver combinations from a given array. Furthermore, when postprocessing FMC data using the total focusing method (TFM), high-resolution images are achieved for defect characterization. Today, the combination of FMC and TFM is becoming more widely available in commercial ultrasonic phased array controllers. However, executing the FMC-TFM method is data-intensive, as the amount of data collected and processed is proportional to the square of the number of elements of the probe. This shortcoming may be overcome using a sparsely populated array in transmission followed by an efficient compression using compressive sensing (CS) approaches. The method can therefore lead to a massive reduction of data and hardware requirements and ultimately accelerate TFM imaging. In the present work, a CS methodology was applied to experimental data measured from samples containing artificial flaws. The results demonstrated that the proposed CS method allowed a reduction of up to 80% in the volume of data while achieving adequate FMC data recovery. Such results indicate the possibility of recovering experimental FMC signals using sampling rates under the Nyquist theorem limit. The TFM images obtained from the FMC, CS-FMC, and sparse CS approaches were compared in terms of contrast-to-noise ratio (CNR). It was seen that the CS-FMC combination produced images comparable to those acquitted using the FMC. Implementation of sparse arrays improved CS reconstruction times by up to 11 folds and reduced the firing events by approximately 90%. Moreover, image formation was accelerated by 6.6 times at the cost of only minor image quality degradation relative to the FMC.

Characterization of the Elastic, Piezoelectric, and Dielectric Properties of Lithium Niobate from 25 °C to 900 °C Using Electrochemical Impedance Spectroscopy Resonance Method.

Lithium niobate (LiNbO3) is known for its high Curie temperature, making it an attractive candidate for high-temperature piezoelectric applications (>200 °C); however, the literature suffers from a paucity of reliable material properties data at high temperatures. This paper therefore provides a complete set of elastic and piezoelectric coefficients, as well as complex dielectric constants and the electrical conductivity, for congruent monocrystalline LiNbO3 from 25 °C to 900 °C at atmospheric pressure. An inverse approach using the electrochemical impedance spectroscopy (EIS) resonance method was used to determine the materials' coefficients and constants. Single crystal Y-cut and Z-cut samples were used to estimate the twelve coefficients defining the electromechanical coupling of LiNbO3. We employed an analytical model inversion to calculate the coefficients based on a linear superposition of nine different bulk acoustic waves (three longitudinal waves and six shear waves), in addition to considering the thermal expansion of the crystal. The results are reported and compared with those of other studies for which the literature has available values. The dominant piezoelectric stress constant was found to be e15, which remained virtually constant between 25 °C and 600 °C; thereafter, it decreased by approximately 10% between 600 °C and 900 °C. The elastic stiffness coefficients c11E, c12E, and c33E all decreased as the temperature increased. The two dielectric constants ϵ11S and ϵ33S increased exponentially as a function of temperature.

Simulation-Based Inversion for the Characterization of Adhesively Bonded Joints Using Ultrasonic Guided Waves.

Adhesively bonded structures are widely used to facilitate the manufacturing process and enhance the performance of critical components in the aerospace, automotive, and energy industries. The assessment of the bond layer using the propagation of ultrasonic guided waves has been extensively investigated in the literature using several different approaches. In this study, a finite element (FE) model was used to simulate the dispersion curves of the modes propagating in an aluminum/adhesive/aluminum bonded structure. The simulated dispersion curves were systematically compared with the experimental measurements to retrieve the shear modulus of the adhesive layer during its curing process. The optimization procedure was able to perform inversion with minimum prior knowledge of the adhesive layer properties. In general, the proposed FE-based forward model was able to match the experimental dispersion curves during curing. Notwithstanding some discrepancies observed in the early to intermediate state of curing, the predicted model parameters were in agreement within 6% of the values obtained by the reference methods. The optimal shear modulus was estimated at 1.55 GPa at the end of the curing, against a reference value of 1.47 GPa.

Lightweight and Amplitude-Free Ultrasonic Imaging Using Single-Bit Digitization and Instantaneous Phase Coherence.

In the field of ultrasonic nondestructive testing (NDT), the total focusing method (TFM) and its derivatives are now commercially available on portable devices and are getting more popular within the NDT community. However, its implementation requires the collection of a very large amount of data with the full matrix capture (FMC) as the worst case scenario. Analyzing all the data also requires significant processing power, and consequently, there is an interest in: 1) reducing the required storage capacity used by imaging algorithms, such as delay-and-sum (DAS) imaging and 2) allowing the transmission and postprocessing of inspection data remotely. In this study, a different implementation of the TFM algorithm is used based on the vector coherence factor (VCF) that is used as an image itself. This method, also generally known as phase coherence imaging, presents certain advantages, such as a better sensitivity to diffracting geometries, consistency of defect restitution among different views, and an amplitude-free behavior as only the instantaneous phase of the signal is considered. Some drawbacks of this method must also be mentioned, including the fact that it poorly reproduces planar reflectors and presents a lower signal-to-noise ratio (SNR) than amplitude-based methods. However, previous studies showed that it can be used as a reliable tool for crack-like defect sizing. Thus, a lightweight acquisition process is proposed through single-bit digitization of the signal, followed by a phase retrieval method based on the rising and falling edge locations, allowing to feed the phase coherence imaging algorithm. Simulated and experimental tests were first performed in this study on several side-drilled holes (SDHs) in a stainless steel block and then extended to an experimental study on angled notches in a 19.05-mm ( 3/4" )-thick steel sample plate through multiview imaging. Results obtained using the array performance indicator (API) and the contrast-to-noise ratio (CNR) as quantitative evaluation parameters showed that the proposed lightweight acquisition process, which relies on binary signals, allows a reduction of the data throughput of up to 47 times. This throughput reduction is achieved while still presenting very similar results to phase coherence imaging based on the instantaneous phase derived from the Hilbert transform of the full waveform. In an era of increasing wireless network speed and cloud computing, these results allow considering interesting perspectives for the reduction of inspection hardware costs and remote postprocessing.

Probe Standoff Optimization Method for Phased Array Ultrasonic TFM Imaging of Curved Parts.

The reliability of the ultrasonic phased array total focusing method (TFM) imaging of parts with curved geometries depends on many factors, one being the probe standoff. Strong artifacts and resolution loss are introduced by some surface profile and standoff combinations, making it impossible to identify defects. This paper, therefore, introduces a probe standoff optimization method (PSOM) to mitigate such effects. Based on a point spread function analysis, the PSOM algorithm finds the standoff with the lowest main lobe width and side lobe level values. Validation experiments were conducted and the TFM imaging performance compared with the PSOM predictions. The experiments consisted of the inspection of concave and convex parts with amplitudes of 0, 5 and 15 λAl, at 12 standoffs varying from 20 to 130 mm. Three internal side-drilled holes at different depths were used as targets. To investigate how the optimal probe standoff improves the TFM, two metrics were used: the signal-to-artifact ratio (SAR) and the array performance indicator (API). The PSF characteristics predicted by the PSOM agreed with the quality of TFM images. A considerable TFM improvement was demonstrated at the optimal standoff calculated by the PSOM. The API of a convex specimen's TFM was minimized, and the SAR gained up to 13 dB, while the image of a concave specimen gained up to 33 dB in SAR.

Ultrasonic assessment of osseointegration phenomena at the bone-implant interface using convolutional neural network.

Although endosseous implants are widely used in the clinic, failures still occur and their clinical performance depends on the quality of osseointegration phenomena at the bone-implant interface (BII), which are given by bone ingrowth around the BII. The difficulties in ensuring clinical reliability come from the complex nature of this interphase related to the implant surface roughness and the presence of a soft tissue layer (non-mineralized bone tissue) at the BII. The aim of the present study is to develop a method to assess the soft tissue thickness at the BII based on the analysis of its ultrasonic response using a simulation based-convolution neural network (CNN). A large-annotated dataset was constructed using a two-dimensional finite element model in the frequency domain considering a sinusoidal description of the BII. The proposed network was trained by the synthesized ultrasound responses and was validated by a separate dataset from the training process. The linear correlation between actual and estimated soft tissue thickness shows excellent R2 values equal to 99.52% and 99.65% and a narrow limit of agreement corresponding to [ -2.56, 4.32 µm] and [ -15.75, 30.35 µm] of microscopic and macroscopic roughness, respectively, supporting the reliability of the proposed assessment of osseointegration phenomena.

Towards using convolutional neural network to locate, identify and size defects in phased array ultrasonic testing.

Machine learning algorithms are widely used in image recognition. In Phased Array Ultrasonic Testing (PAUT), images are typically formed through constructive and destructive superpositions of signals backscattered from flaws or geometric features. However, all PAUT data acquisition schemes require several emissions and the duration of the acquisition may be too slow in high-speed manufacturing. In this study, the Faster R-CNN was used to identify, locate and size flat bottom holes (FBH) and side-drilled holes (SDH) in an immersed test specimen using a single plane wave insonification. The training was performed on segmented and classified data generated using GPU-accelerated finite element simulations. SDH and FBH of different diameters, depths and lateral positions were included in the training set. The thickness of the test specimen was also variable. An ultrasonic phased array probe of 64 elements was simulated. All elements of the phased array probe were fired at the same time and the time traces from each element were recorded. The individual time traces were concatenated to form a matrix, which was then used in the training. This inspection scenario enables fast acquisition of data at the expense of poor lateral resolution in the resulting image. The trained neural network was initially tested using finite element simulations. Results were assessed in terms of the intersection of the union (IoU) between the ground truth geometry and the predicted geometry. With the simulated cases, the thickness of the test specimen was detected in all cases. When using a 40% IoU threshold, the detection rate of the FBH was 87% while only 20% for the SDH. The smallest detected FBH had a 0.56 wavelength depth and a lateral extent of 1.04 wavelength. Drawing a box using the -6dB drop method around the FBH always led to an IoU under 15%. On average, the lateral extent of the FBH using the -6dB method was three times larger than the diameter predicted by the proposed method. Then, the training was continued with a small augmented dataset of experiments (equivalent to 3% of the simulated dataset). In experiments, the results show that the test specimen was always correctly identified. When using a 40% IoU threshold the experimental detection rate of the FBH was 70%. The smallest detected defect in experiments had a depth of 2 wavelengths.

Towards an Alternative to Time of Flight Diffraction Using Instantaneous Phase Coherence Imaging for Characterization of Crack-Like Defects.

Time of flight diffraction (TOFD) is considered a reliable non-destructive testing method for the inspection of welds using a pair of single-element probes. On the other hand, ultrasonic phased array imaging has been continuously developed over the last couple of decades, and now features powerful algorithms, such as the total focusing method (TFM) and its multi-view approach to rendering detailed images of inspected parts. This article focuses on a different implementation of the TFM algorithm, relying on the coherent summation of the instantaneous signal phase. This approach presents a wide range of benefits, such as removing the need for calibration, and is highly sensitive to defect tips. This study compares the sizing and localization capabilities of the proposed method with the well-known TOFD. Both instantaneous phase algorithm and TOFD do not take advantage of the signal amplitude. Experimental tests were performed on a ¾â€³-thick steel sample with crack-like defects at different angles. Phase-based imaging techniques showed similar characterization capabilities as the standard TOFD method. However, the proposed method adds the benefit of generating an easy-to-interpret image that can help in localizing the defect. These results pave the way for a new characterization approach, especially in the field of automated ultrasonic testing (AUT).

Effect of the Acoustic Impedance Mismatch at the Bone-Soft Tissue Interface as a Function of Frequency in Transcranial Ultrasound: A Simulation and In Vitro Experimental Study.

The transcranial Doppler (TCD) ultrasound is a method that uses a handheld low-frequency (2-2.5 MHz), pulsed Doppler phased array probe to measure blood velocity within the arteries located inside the brain. The problem with TCD lies in the low ultrasonic energy penetrating inside the brain through the skull, which leads to a low signal-to-noise ratio. This is due to several effects, including phase aberration, variations in the speed of sound in the skull, scattering, the acoustic impedance mismatch, and absorption of the three-layer medium constituted by soft tissues, the skull, and the brain. The goal of this article is to study the effect of transmission losses due to the acoustic impedance mismatch on the transmitted energies as a function of frequency. To do so, wave propagation was modeled from the ultrasonic transducer into the brain. This model calculates transmission coefficients inside the brain, leading to a frequency-dependent transmission coefficient for a given skin and bone thickness. This approach was validated experimentally by comparing the analytical results with measurements obtained from a bone phantom plate mimicking the skull. The average position error of the occurrence of the maximum amplitude between the experiment and analytical result was equivalent to a 0.06-mm error on the skin thickness given a fixed bone thickness. The similarity between the experimental and analytical results was also demonstrated by calculating correlation coefficients. The average correlation between the experimental and analytical results came out to be 0.50 for a high-frequency probe and 0.78 for a low-frequency probe. Further analysis of the simulation showed that an optimized excitation frequency can be chosen based on skin and bone thicknesses, thereby offering an opportunity to improve the image quality of TCD.

Deconvolution of ultrasonic signals using a convolutional neural network.

Successfully employing ultrasonic testing to distinguish a flaw in close proximity to another flaw or geometrical feature depends on the wavelength and the bandwidth of the ultrasonic transducer. This explains why the frequency is commonly increased in ultrasonic testing in order to improve the axial resolution. However, as the frequency increases, the penetration depth of the propagating ultrasonic waves is reduced due to an attendant increase in attenuation. The nondestructive testing research community is consequently very interested in finding methods that combine high penetration depth with high axial resolution. This work aims to improve the compromise between the penetration depth and the axial resolution by using a convolutional neural network to separate overlapping echoes in time traces in order to estimate the time-of-flight and amplitude. The originality of the proposed framework consists in its training of the neural network using data generated in simulations. The framework was validated experimentally to detect flat bottom holes in an aluminum block with a minimum depth corresponding to λ/4.

Ex Vivo Assessment of Cortical Bone Properties Using Low-Frequency Ultrasonic Guided Waves.

The early diagnosis of osteoporosis through bone quality assessment is a major public health challenge. Research in axial transmission using ultrasonic guided waves has shown the method to be sensitive to the geometrical and mechanical properties of the cortical layer in long bones. However, because of the asymmetric nature of cortical bone, the introduction of a more elaborate numerical model than the analytical plate and cylinder models, as well as its inversion, continues to be challenging. The aim of this article is, therefore, to implement a bone-like geometry using semianalytical finite-element (SAFE) modeling to perform the inverse characterization of ex vivo radii at low frequencies (< 60 kHz). Five cadaveric radiuses were taken from donors aged between 53 and 88 and tested using a typical axial transmission configuration at the middle of the diaphysis. The dispersion curves of the propagating modes were measured experimentally and then systematically compared with the solutions obtained with the SAFE method. For each sample, four parameters were estimated using a parameter identification procedure: 1) the bulk density; 2) the thickness; 3) the outer diameter; and 4) a shape factor (SF). The results showed a moderate agreement between the predicted bulk density and the average voxel value calculated from X-ray computed tomography images. Furthermore, a good agreement was observed between the geometrical parameters (thickness, outer diameter, and SF) and the reference images.

An ultrasonic guided wave excitation method at constant phase velocity using ultrasonic phased array probes.

High-order ultrasonic guided wave modes have recently been attracting interest in a variety of nondestructive testing applications, ranging from thickness gauging to bond characterization. Accurate control of the transmitted ultrasonic guided wave mode is paramount when working at frequencies above the cutoff of the first high-order mode. The high number of modes available makes this range of frequency-thickness products difficult to exploit in practice. Many papers and textbooks have showed that multielement probes, such as comb transducers, are able to target a specific wavelength which depends on the elementary pitch. This method can be enhanced by adding an elementary delay law. However, this method of excitation has major drawbacks as the areas of excitation in a dispersion curves depends on the frequency and the technique is not unidirectional. This paper demonstrate that a conventional phased array transducer for which the elementary pitch is small relative to the targeted wavelength is able to excite high order guided wave modes at a constant phase velocity (independently of the frequency). The aim is to excite different regions of the dispersion curves by controlling the input signal bandwidth and the angle of the generated beam. The paper describes the theoretical background and details the differences between the various methods of excitation of ultrasonic guided waves, especially with the comb transducer method. Finite element simulations are presented to verify the analytical predictions and quantify the unidirectional and diffraction properties of the transmitted beam. Experiments conducted on an aluminum plate show striking agreement with finite element simulations, including the possibility of exciting a single mode in a narrow region at high frequency-thickness products. Experiments conducted on a CFRP plate demonstrates that the method can be adapted to other materials.

Predictive Model for Designing Soft-Tissue Mimicking Ultrasound Phantoms With Adjustable Elasticity.

The use of mechanically representative phantoms is important for experimental validation in ultrasound (US) imaging, elastography, and image registration. This article proposes a model to predict the elastic modulus of a soft tissue-mimicking phantom based on two very easily controllable parameters: gelatin concentration and refrigeration duration. The model has been validated on small- and large-scale phantoms; it provides a good prediction of the elastic modulus in both cases (error < 16.2%). The tissue-mimicking phantom is made following a low-cost and simple fabrication procedure using commercial household gelatin with psyllium hydrophilic mucilloid fiber to obtain echogenicity. A large range of elastic properties was obtained (15-100kPa) by adjusting the gelatin concentration between 5% and 20% (g/mL) and the refrigeration time of the sample between 2 and 168 h, allowing to mimic normal and pathological human soft tissues. The phantom's acoustic properties (velocity, attenuation, and acoustic impedance) are also assessed using the American Institute of Ultrasound in Medicine (AIUM) standard.

Generalized Dynamic Analytical Model of Piezoelectric Materials for Characterization Using Electrical Impedance Spectroscopy.

Piezoelectric materials have the intrinsic reversible ability to convert a mechanical strain into an electric field and their applications touch our daily lives. However, the complex physical mechanisms linking mechanical and electrical properties make these materials hard to understand. Computationally onerous models have historically been unable to adequately describe dynamic phenomena inside real piezoelectric materials, and are often limited to over-simplified first-order analytical, quasi-static, or unsatisfying phenomenological numerical approaches. We present a generalized dynamic analytical model based on first-principles that is efficiently computable and better describes these exciting materials, including higher-order coupling effects. We illustrate the significance of this model by applying it to the important 3m crystal symmetry class of piezoelectric materials that includes lithium niobate, and show that the model accurately predicts the experimentally observed impedance spectrum. This dynamic behavior is a function of almost all intrinsic properties of the piezoelectric material, so that material properties, including mechanical, electrical, and dielectric coefficients, can be readily and simultaneously extracted for any size crystal, including at the nanoscale; the only prior knowledge required is the crystal class of the material system. In addition, the model's analytical approach is general in nature, and can increase our understanding of traditional and novel ferroelectric and piezoelectric materials, regardless of crystal size or orientation.

EMAT design for minimum remnant thickness gauging using high order shear horizontal modes.

Detection and sizing of corrosion are critical issues across many industries such as for the oil and gas industry or the petrochemical industry. Inspections may become difficult and time-consuming when the structures under inspection are only partially accessible such as for pipes under insulation or at pipe supports. It has been demonstrated in the literature that the cutoff frequency-thickness product of high order ultrasonic guided wave modes can be used in medium to long-range thickness gauging. As the thickness varies along an inspection line, the thickness variation acts as a low-pass filter for the high order ultrasonic guided wave modes. As the thickness drops below the cutoff frequency-thickness product of a given mode, this mode is filtered out of the propagating wave packet. The effectiveness of this technique depends on the number of excited modes and the width of the ultrasonic beam along the inspection line. Both of these parameters can easily be controlled using electromagnetic acoustic transducers (EMAT) for the excitation. Analytical and multiphysics finite element simulations were performed to optimize an EMAT that can excite enough modes to allow the measurement of the remnant thickness based on the number of modes propagating through a corroded area. The results were validated experimentally, and a thickness resolution of 2 mm was achieved in a 10 mm aluminum plate.