In general, the nonlinear behavior of an elastic wave in isotropic hyperelastic solids with quadratic nonlinearity depends on five independent elastic constants, namely, the three third-order elastic constants and two second-order elastic constants. In this article, we show that such nonlinear behavior can be described fully by only three independent non-dimensional parameters if the wave motion is two-dimensional. Furthermore, if the motion is a plane wave, only two independent non-dimensional parameters are needed to fully describe the nonlinear behavior of the wave. These results are useful for conducting numerical simulations and for interpreting experimental measurement data.

Bent-ray tracing ultrasound computed tomography (USCT) is a promising technique for breast cancer screening which quantitatively provides speed-of-sound (SOS) distribution in human breasts. In this modality, SOS images are reconstructed with an iterative process to match the measured time-of-flights and the ones predicted by Eikonal equation solved with the fast marching method (FMM). The Eikonal equation is meant to be applied in SOS heterogeneous media and its evaluation with FMM is an computational expensive process. However, in USCT, the object is placed in a homogeneous coupling medium. Thus, the acoustic environment is formed by two parts, the homogeneous background (coupling medium) and the heterogeneous object. In this work, we leverage this strong a priori information and propose a method to accelerate SOS image formation for bent-ray tracing USCT. We show that, given the boundary information of the object, Eikonal equation only needs to be evaluated in a limited area covering the object. For that, the partial FMM and the associated ray-tracing strategy are proposed to reduce the computational cost of the forward modeling. We also managed to restrict image reconstruction area inside the object for improved convergence rate of the optimization. Both the simulation and phantom imaging experiments with ring transducer arrays demonstrated that the proposed method reduces the reconstruction time in an object size dependent manner. For the object occupying 20.3% to 56.3% of the image field of the ring array, we observed 30.1%-61.9% reduction in image reconstruction time without sacrificing the image quality, compared to classical method. The proposed strategy can be adopted for fast SOS imaging with bent-ray tracing USCT to improve patient throughput for breast cancer screening.

The utilization of conventional longitudinal transducers in the field of ultrasonic liquid processing is constrained by limitations in radiation area and directional characteristics. These limitations can be addressed through the implementation of mode conversion techniques. However, an expanded radiation area may also result in reduced acoustic radiation intensity. To mitigate this issue, this study proposes an Acoustic Black Hole Ultrasonic Radiator (ABHUR) designed to enhance ultrasound intensity and thereby achieve high-efficiency radiation. The proposed ABHUR comprises a Bolted Langevin-type Transducer (BLT) and a Curved Acoustic Black Hole (CABH) ring. A theoretical model, based on the transfer matrix method, is developed to analyze the in-plane vibrational behavior of the CABH ring, and its validity is confirmed through Finite Element Method (FEM) simulations. The underwater vibrational and sound field distribution properties of the ABHUR are investigated using FEM and compared with two alternative radiators employing longitudinal-bending (L-B) and longitudinal-radial (L-R) modes. Owing to the unique properties of the Acoustic Black Hole structure (ABHs), which amplify bending wave amplitudes and concentrate energy, the ABHUR operating in L-B mode demonstrates superior ultrasound intensity. Furthermore, a prototype of the ABHUR is fabricated, and a series of three experiments are conducted to validate the operational feasibility of the proposed system.

To address the challenges in ultrasonic processing for large capacity liquids, improving the electroacoustic conversion efficiency, expanding the radiation direction, and enhancing the uniformity of the sound field have become imperative and focal objectives in the design of high-power ultrasonic transducers. Hence, a novel push-pull slotted tube ultrasonic transducer (PSTUT) based on longitudinal-bending mode conversion has been proposed. The PSTUT is composed of four key parts: two sandwich transducers, two stepped horns, two end caps, and a slotted tube radiator. By applying push-pull longitudinal excitation, the caps produce longitudinal bending vibration, while the arc-shaped plates produce radial bending vibration, capable of achieving efficient, uniform, and omnidirectional ultrasound radiation. Based on the principle of electromechanical analogy and the theory of Timoshenko beams, the electromechanical equivalent circuits of the uniform beam in bending vibration and the PSTUT in coupled vibration are established. The frequency response of the PSTUT is validated by the finite element method simulations and experiments. The vibration analysis demonstrates that adjusting the size of the circular slotted tube radiator can control both the range and intensity of radial radiation. Simulated and experimental results show that the PSTUT exhibits satisfactory 3D-omnidirectional radiation capability and improved sound field uniformity in water. The proposed PSTUT offers a promising solution to overcome the bottleneck in ultrasonic liquid treatment technology.

Multimodal ultrasonic guided wave (UGW) signal reconstruction technology can accurately separate individual modes, providing more comprehensive and precise information for material nondestructive testing. However, the accuracy of existing reconstruction techniques heavily depends on the precision and completeness of time-frequency (TF) ridge extraction. To address this challenge, this paper proposes a TF energy segmentation reconstruction method without relying on complete TF ridge extraction, as traditionally required. This approach introduces an adaptive noise variance estimation Bayesian filter to extract the TF ridges under unknown noise distribution, particularly in regions where TF ridges intersect or overlap. By using the extracted TF ridges as references, the energy segmentation method directly separates and reconstructs UGW modes from the TF representation even when the extracted TF ridges are incomplete. This is because the proposed method can automatically retrieve the energy of each mode with a region growing algorithm from the time domain and frequency domain so that both modes with rapidly changing instantaneous frequency or group delay can be recovered, while the traditional method can only separate modes from a single domain. Numerical simulations and photoacoustic-guided wave experiments validate the effectiveness of the proposed method, achieving reconstruction accuracies of 96.9% and 92.5% for the simulated and experimental signals, respectively.

Pipe wall loss assessment is crucial in oil and gas transportation. Ultrasonic guided wave is an effective technology to detect pipe defects. However, accurately inverting weak-feature defects under limited view conditions remains challenging due to constraints in transducer arrangements and inconsistent signal characteristics. This paper proposes a stepwise inversion method based on feature compensation and network reconstruction through deep learning, combined with high-order helical guided waves to expand the imaging view and achieve high-resolution imaging of pipe defects. A forward model was established using the finite difference method, with the two-dimensional Pearson correlation coefficient and maximum wall loss estimation accuracy defined as imaging metrics to evaluate and compare the method. Among 50 randomly selected defect samples in the test set, the inversion model achieved a correlation coefficient of 0.9669 and a maximum wall loss estimation accuracy of 96.65 %. Additionally, Gaussian noise was introduced to assess imaging robustness under pure signal, 5 dB, and 3 dB conditions. Laboratory experiments validated the practical feasibility of the proposed method. This approach is generalizable and holds significant potential for nondestructive testing in cylindrical waveguide structures represented by pipes.

In many industrial processes, accumulation of fouling can lead to decreased production efficiency by weakening the flow in pipes or causing additional friction on the ships' hulls. To detect the fouled areas for descaling, ultrasonic guided waves (UGWs) can be utilized. Usually, this is carried out by coupling phased array collars of contact transducers onto the pipe. This can cause problems if the coupling changes over time, the temperature of the pipe is too high or the sensors need to be relocated. Here, we demonstrate how fouling can be detected without contact sensors, by using a pulse laser and a laser Doppler vibrometer. Furthermore, by employing broadband laser excitation, we are able to define the fouling attenuation coefficient and investigate the frequency dependencies of fouling-induced attenuation.

Advancement of computation nondestructive evaluation (CNDE) creates an opportunity to visualize predicted signals received by sensors and may aid the development of artificial intelligence (AI) for NDE 4.0. However, traditional methods face limitations for crack propagation and guided wave propagation simulation, simultaneously. Modeling crack propagation using mesh-based method requires remeshing and implementation of cohesive zone model to name a few alternatives. Multiple meshfree methods have also been implemented for crack propagation but did not immediately translate to simulate the guided waves that are used to interrogate the cracks under nondestructive evaluation (NDE) framework. Ultrasonic CNDE with new era of Machine Learning (ML)/AI requires understanding the signals and its physics-based features when the guided waves propagate to interact with the crack while the crack is simultaneously growing at different time scales. To enable the future of physics to be informed and physics driven ML/AI this article presents a framework of CNDE where guided wave propagation and crack propagation are simultaneously simulated without remeshing and creates an enabling approach for the future AI implementation. A few successful case studies are presented for feasibility demonstration. Detailed flowcharts are presented for easy implementation of the method for the ultrasonic NDE community.

SAW (surface acoustic wave)-based microfluidics is fast becoming a recognised method for isolating and concentrating particles given its capacity for safe and label-free particle manipulation. However, widespread adoption of acoustofluidics for clinical and industrial applications is hindered by its limited capability handling submicron particles. Smaller particles, which are primarily influenced by the acoustic streaming effect, can be captured and enriched by streaming-induced vortices. This study investigated the role of microchannel cross-sectional geometry on the streaming patterns in an acoustically actuated volume and the behaviour of particles in it, in an effort to address the size limitation. Different regimes of particle trapping behaviour were observed and identified, and its dynamics explained using the competing outward centrifugal and inward inertial lift forces. These observations led to a proposed model of particle behavior in a vortex. The study found sloped sidewalls intensify streaming flows and concentration effect. Additionally, the individual vortices were observed becoming more/less affinitive to particles of a certain size, i.e. particles of different sizes were observed settling in distinct streaming vortices. This type of enhanced size-selective capturing behaviour can enable enrichment and binary separation of submicron particle mixtures, with a greater yield and purity than conventional rectangular microchannels.

This study aims to explore the feasibility of a deep learning approach to correct the distortion caused by the skull, thereby developing a transcranial adaptive focusing method for safe ultrasonic treatment in opening of the blood-brain barrier (BBB). However, aberration correction often requires significant computing power and time to ensure the accuracy of phase correction. This is due to the need to solve the evolution procedure of the sound field represented by numerous discretized grids. A combined method is proposed to train the phase prediction model for correcting the phase accurately and quickly. The method comprises pre-segmentation, k-Wave simulation, and a 3D U-net-based network. We use the k-Wave toolbox to construct a nonlinear simulation environment consisting of a 256-element phased array, a small piece of skull, and water. The skull sound speed sample combining with the phase delay serves as input for the model training. The focus volume and grating lobe level obtained by the proposed approach were the closest to those obtained by the time reversal method in all relevant approaches. Furthermore, the mean peak value obtained by the proposed approach was no less than 77% of that of the time reversal method. In this study, the computational cost of each sample's phase delay was no more than 0.05 s, which was 1/200th of the time reversal method. The proposed method eliminates the complexity of numerical calculation processes requiring consideration of more acoustic parameters, while circumventing the substantial computational resource demands and time-consuming challenges to traditional numerical approaches. The proposed method enables rapid, precise, and adaptive transcranial aberration correction on the 3D skull-based conditions, overcoming the potential inaccuracies in predicting the focal position or the acoustic energy distribution from 2D simulations. These results show the possibility of the proposed approach enabling near-real-time correction of skull-induced phase aberrations to achieve transcranial focus, thereby offering a novel option for treating brain diseases through temporary BBB opening.

Bulk-driven acoustic streaming flows induced by two different high-powered ultrasonic sources in air have been measured and characterised using particle image velocimetry (PIV). These time-averaged flows are driven by the attenuation of the acoustic energy, and appear as jets in the direction of the acoustic propagation. Langevin horns and a focussed array of transducers, which operate at acoustic frequencies of f≈27 kHz and f=40 kHz respectively, were used to create high pressure acoustic fields, with local sound pressure levels of over 160 dB. The magnitude of the acoustic streaming flows that resulted from the Langevin horn and the focussed array were up to V≈0.15m/s and V≈0.2m/s respectively. For a given peak acoustic pressure, the focussed array yielded higher acoustic streaming velocities due to the increased acoustic attenuation at the higher driving frequency. The shape of the acoustic field was found to govern the shape of the acoustic streaming velocity field, with the Langevin horn producing a wider jet with a more gradual velocity increase and decay than the focussed array. The focussed array induced a streaming velocity field where the maximum velocity occurred at a similar location to the peak acoustic pressure. Experimental PIV results were compared to a numerical model based on assumed weak non-linearity in which the attenuation of the first order pressure drives the streaming. The numerical model was able to predict the streaming velocity field with good qualitative and reasonable quantitative agreement.

Coal seam water injection can effectively improve the water content of the coal seam and control the dust pollution in the mining process from the source. In this paper, we investigate the changes in internal fracture structure and water transport in coal samples by double treatment of surfactant and ultrasonic wave on anthracite samples. Ultrasonic treatment of coal samples immersed in water and observation of the difference in wetting characteristics before and after treatment. The results demonstrate that the primary fracture in the coal samples expands within 4-5 h of ultrasonic stimulation, a new fracture with an opening between 10 and 15 µm is generated during the stimulation process and the permeability of the coal samples increases by four to eight times compared with the untreated one. It is worth noting that water can fully penetrate the newly formed fracture during the ultrasonic intervals. Ultrasound can make surfactants dissolve better, but the thermal and cavitation effects of ultrasound can also inhibit the effect of surfactants in promoting water absorption in coal. The results guide future research and development of ultrasonic-enhanced water injection technology in coal seams.

PCA reconstruction-based techniques are widely used in guided wave structural health monitoring to facilitate unsupervised damage detection. The measurement interval of collecting evaluation data significantly influences the correlation among the data points, impacting principal component values and, consequently, the accuracy of damage detection. Despite its importance, there has been limited research on the selection of suitable components and measurement intervals to reduce false alarms. This paper seeks to develop strategies for identifying the optimal number of principal components and measurement intervals for PCA reconstruction-based damage detection methods. Our results indicate that the patterns of change in reconstruction coefficients, based on the number of components used in PCA reconstruction and the measurement interval for collecting evaluation data, are effective indicators for determining the optimal principal components and measurement intervals for damage detection, without using any damage information. The effectiveness of the indicators for determining optimal components and measurement intervals is validated using evaluation sets collected under uncontrolled and dynamic monitoring conditions, with measurement intervals ranging from 86 to 8600 s per measurement.

In this work, the spatiotemporal pressure field of MHz-focused ultrasound is measured using a background-oriented schlieren technique combined with fast checkerboard demodulation and vector tomography (VT-BOS). Hydrophones have been commonly employed to directly measure the local pressure in underwater ultrasound. However, their limitations include that they disturb the acoustic field and affect the measured pressure through the spatial averaging effect. To overcome such limitations, we propose VT-BOS as a non-contact technique for acoustic field measurements using only a background image and a camera. In our experiments, VT-BOS measures focused acoustic fields with a focal width of 1.0 mm and a frequency of 4.55 MHz, capturing traveling, reflected, and standing waves. We discuss three key features of this approach: (1) the temporal evolution of pressure measured by VT-BOS and hydrophones, (2) the differences in computational cost and spatial resolution between VT-BOS and other techniques, and (3) the measurement range of VT-BOS. The results demonstrate that VT-BOS successfully quantifies spatiotemporal acoustic fields and can estimate the hydrophones' spatial averaging effect over a finite area. VT-BOS measures pressure fields of several MPa with high spatiotemporal resolution, requiring less computational and measurement time. It is used to measure pressure amplitudes from 0.4 to 6.4 MPa, with the potential to extend the range to 0.3-201.6 MPa by adjusting the background-to-target distance. VT-BOS is a promising tool for measuring acoustic pressure in the MHz and MPa ranges, critical for applications such as vessel flow measurement and hydrophone calibration.

In this paper, a previously developed theoretical model for the ultrasonic elastic wave scattering, based on the Stanke and Kino model and applicable to both 2D and 3D single-phase untextured polycrystals, is extended to microstructures with elongated grains. The effect of elongated grains on wave attenuation and phase velocity induced by scattering is investigated, highlighting similarities and discrepancies between the 2D and 3D cases. Additionally, 2D and 3D finite element (FE) models are developed to compare and validate the theoretical predictions under fixed assumptions. The morphology of the numerical polycrystalline samples is characterized using a multi-exponential two-point correlation (TPC) function which, when incorporated with the theoretical model, enables a more direct and accurate comparison. The FE models demonstrate excellent quantitative agreement with the theoretical predictions and, moreover, support the wave propagation's directional dependency in the stochastic scattering region and the 2D-3D dimensionality dissimilarities in the Rayleigh region. It is shown that 2D attenuation can predict 3D behavior in the stochastic limit and provide insights into the estimation of 3D grain morphology in the Rayleigh limit.

Pulse-echo ultrasonic techniques play a crucial role in assessing wall thickness deterioration in safety-critical industries. Current approaches face limitations with low signal-to-noise ratios, weak echoes, or vague echo patterns typical of heavily corroded profiles. This study proposes a novel combination of Convolution Neural Networks (CNN) and Transformer Neural Networks (TNN) to improve thickness gauging accuracy for complex geometries and echo patterns. Recognizing the strength of TNN in language processing and speech recognition, the proposed network comprises three modules: 1. pre-processing CNN, 2. a Transformer model and 3. a post-processing CNN. Two datasets, one being simulation-generated, and the other, experimentally gathered from a corroded carbon steel staircase specimen, support the training and testing processes. Results indicate that the proposed model outperforms other AI architectures and traditional methods, providing a 5.45% improvement over CNN architectures from NDE literature, a 1.81% improvement over ResNet-50, and a 17.5% improvement compared to conventional thresholding techniques in accurately detecting depths with a precision under 0.5λ.

Due to the development of new materials and advanced manufacturing technologies, the application of large-scale composite structures has become increasingly widespread. Ensuring the safe and stable operation of such structures presents new challenges across various application domains. Addressing the limitations of existing guided wave structural health monitoring methods for online damage monitoring in large-scale structures, such as cumbersome equipment setup, insufficient signals coverage, and difficulties in processing massive data, a method for sub-area collaborative guided-wave-based structural damage monitoring and severity assessment based on sparse sensing is proposed. By employing a sparse sensing array layout, the structure is divided into multiple monitoring sub-areas with arranged sensing arrays to reduce overall complexity. The characteristic responses of the guided wave signals from different sub-areas are extracted to construct feature sub-spaces. Support vector machines are adopted to construct evaluation sub-networks in each feature sub-space, enabling regional monitoring. Additionally, an improved D-S evidence fusion algorithm is applied to fuse the decision-layer inputs from each evaluation sub-network, effectively utilizing the feature information from multiple sub-areas and enhancing the accuracy of damage severity assessment for large-scale structures. Experimental results on typical composite structure specimens demonstrate that by fusing the support vector machine evaluation results from each sub-area, the accuracy of damage severity assessment reaches 97.5%, with uncertainties in the severity assessment below 5%.

Extending the depth of focus is necessary in many scenarios. Recent progress in ultrasonic applications demands various kinds of foci and poses challenges to science and technologies. Here, we propose to connect individual foci forming an ultrasonic needle beam (UNB) through complex amplitude encoding with super-units. Two phase distributions are encoded into one metalens through super-units, which realizes a complex-amplitude modulation and achieve multifocal points in space. The performance of the metalens can be improved by adjusting the parameters of super-units. Both simulations and experiments have demonstrated that the metalens designed through the proposed method can efficiently produce single or twin UNBs. Our work has potential applications in biomedical treatment and imaging, remote communication, and nondestructive detection.

Laser ultrasound is well suited to monitor metal additive manufacturing processes. Pulse laser-generated Rayleigh waveforms evolve with propagation distance due to material nonlinearity, making them a powerful tool for nondestructive evaluation, particularly for assessing microstructure. Unlike narrow-band Rayleigh waves, where the relative acoustic nonlinearity parameter is commonly used to evaluate material degradation, a pulse laser generates broadband unsymmetrical V-shaped waveforms whose spatial evolution we have characterized by a steepness parameter. Thermal aging precipitates multiple phases (including γ and γ) in Inconel718 samples that we documented by X-ray diffraction. These precipitates are associated with increased material nonlinearity. Comparing waveform spatial evolution, through changes in steepness, in samples before and after thermal aging revealed significant sensitivity to the material state. Thus, the technique has strong potential to provide unique insight into a material's microstructure and the mechanical properties dictated by that microstructure.

High-pressure, broadband, and miniatured ultrasound emitters are urgently needed in biomedical imaging and treatment as well as non-destructive detection. In this work, we report a laser generated ultrasonic photoacoustic transducer (LGUPT) based on an ultra-thin layer of MXene (TiCT) nanosheets. Under the excitation of 532nm nanosecond laser pulses, the amplitude of the generated sound pressure can reach 8.7MPa, with a bandwidth of 17.4MHz at the irradiation intensity of 17.72mJ/cm. The photoacoustic conversion efficiency of the 1.2μm-thick MXene film/PDMS transducer was found to be 1.21×10, which is among the highest values reported to date. The MXene thin film can also be drop-casted on the curved surface of a focusing lens. The amplitude of the sound pressure signal can reach 25.3 MPa and the bandwidth 19.7MHz at a pulse laser energy of 28.12mJ/cm. The width of the focal spot at -3 dB of maximum amplitude was found in the range of 0.14mm for the optical lens based LGUPT under the condition of a laser spot diameter of 15mm by theoretical simulation. The water processable focusing LGUPT demonstrated excellent ultrasonic cavitation effect on the tissue mimicking agar plate. Our experimental and theoretical work highlights the potential of ultra-thin MXene film based LGUPTs for high precision photoacoustic therapy, integrated imaging and sensing instruments.

Fullerenes have exhibited excellent performance in solar cells, electric transducer and catalysts. The rather high absorption coefficient, combined with its low specific heat capacity, as well as hydrophobicity and antioxidant, are key features for applications in acoustic emission (AE), which has never been reported. Here, we fabricate and characterize a flexible an AE source based on the fullerenes-polydimethylsiloxane (PDMS) composite. By controlling the composite concentration or thickness, the center frequency can be changed in laser ultrasound excitation. The assembled transducer simultaneously achieves relatively wide frequency range (10-dB bandwidth>10 MHz) and efficient laser ultrasound conversion (1.13×10). The mechanical robustness of the AE source is also quantitatively characterized in water. Notably, compared to graphene nano-flakes, the fullerenes exhibit a more than threefold increase in excitation amplitude. Owing to high-intensity ultrasound excitation of the fullerenes-PDMS composite, the structure characteristics of centimeter-scaled physical models are clearly resolved by irradiating the material as a laser-ultrasound source. To construct a compact fiber-optic exciter, the fullerenes-PDMS film is additionally applied to a fiber end via dip coating. The findings suggest that fullerenes possess significant competitive advantages as a high-efficiency AE source in the field of ultrasound applications.