Ultrasonic Nondestructive Evaluation Research Articles

ULTRASONIC INTERROGATION TECHNIQUE FOR DETECTING HATCH ANGLE VARIATIONS IN ADDITIVE MANUFACTURING BY PHONONIC LATTICE STRUCTURES

Abstract Additive Manufacturing/3D Printing (AM/3DP) has revolutionized part production by enabling the creation of intricate internal structures and complex geometries from diverse materials directly from digital design files. Among powder-based metal AM/3DP methods, Selective Laser Melting (SLM) is widely used in advanced applications such as biomedical devices and aerospace parts. Despite considerable progress in AM/3DP and SLM, at present, challenges in print quality persist, and vast resources for post-production quality assessment are allocated. The quality of SLM prints is influenced by various process and design parameters, such as the accuracy of hatch angle deposition, laser intensity/power, scanning speed of the laser beam, print line spacing, layer depth, printing chamber conditions, and the material's physical and chemical properties. Direct ultrasonic Non-Destructive Evaluation (NDE) offers comprehensive internal inspection and real-time data acquisition ability; however, in AM/3DP it faces severe limitations due to a build's intricate internal and external geometric features. In the current study, we present a Phononic Crystal Artifact (PCA)-based real-time ultrasonic NDE quality monitoring framework and show offline its utility in detecting and evaluating hatch angle variations, a critical process parameter. A PCA is substantially simpler and smaller than the actual build but represents its critical geometric and structural intricacies and mechanical properties. The current offline study demonstrates that hatch angle variations can be monitored from ultrasonic responses' spectral modal frequency peaks and wave dispersion relations.

Study on surface waves for detection of fatigue cracks in railway joint bars

The current method of inspecting railway joint bars involves the use of high-resolution cameras to detect fatigue cracks that have undergone significant cracking exposed to the surface. The novelty of the work presented in this paper discusses the development and application of non-contact ultrasonic surface wave approach to detect and characterize near-surface fatigue cracks in the head of the railway joint bars which is not usually accessible for inspection. Simulated cracks were implanted in the head of the two different used joint bars to assess the capabilities of the ultrasonic nondestructive evaluation (NDE) surface wave approach. One of the joint bars was implanted with 3.175 mm and 6.35 mm cracks in length, while the other joint bar was implanted with 12.7 mm and 25.4 mm cracks in length. Despite the complex geometry of railway joint bars, the laboratory proof-of-concept testing conducted in an immersion water tank demonstrated that the developed non-contact surface wave approach successfully detected implanted cracks in both joint bars. The results obtained from the study indicate that a 0.5 MHz ultrasonic transducer provided the best sensitivity for detecting implanted cracks compared to 1 MHz and 2.25 MHz transducers. Similarly, test results obtained with a 0.5 MHz ultrasonic transducer, launching a surface wave from an accessible area to an inaccessible area of the joint bar (where the implanted cracks were located) yielded a significantly higher signal-to-noise ratio (SNR) than the 1 MHz and 2.25 MHz transducer.

Defect detection using integration of ultrasonic least-squares reverse time migration and generative adversarial network

ABSTRACT Accurate detection and characterisation of defects in high-density polyethylene (HDPE) materials are important for the safety of industrially critical structures. Ultrasonic non-destructive evaluation (UNDE) has proven to be a powerful tool for detecting and characterising defects in engineered materials. However, efficient and high-precision defect imaging in these highly attenuating materials remains a significant challenge for UNDE. Least-squares reverse time migration (LSRTM) offers the potential to reconstruct high-precision images of reflectivity. Yet, the conventional LSRTM iteratively updates the reflectivity model by minimising the data residuals, making it computationally expensive. In this paper, an efficient ultrasonic LSRTM algorithm within a deep learning framework is proposed. Building upon this, a generative adversarial network (GAN) is integrated to further enhance the reconstruction results by reducing artefacts in the images. Simulation and experimental results show that the proposed ultrasonic LSRTM-GAN can generate high-quality images, effectively enabling precise defect detection in HDPE.

Ultrasonic Rough Crack Characterization Using Time-of-Flight Diffraction With Self-Attention Neural Network.

Time-of-flight diffraction (ToFD) is a widely used ultrasonic nondestructive evaluation (NDE) method for locating and characterizing rough defects, with high accuracy in sizing smooth cracks. However, naturally grown defects often have irregular surfaces, complicating the received tip diffraction waves and affecting the accuracy of defect characterization. This article proposes a self-attention (SA) deep learning method to interpret the ToFD A-scan signals for sizing rough defects. A high-fidelity finite-element (FE) simulation software Pogo is used to generate the synthetic datasets for training and testing the deep learning model. Besides, the transfer learning (TL) method is used to fine-tune the deep learning model trained by the Gaussian rough defects to boost the performance of characterizing realistic thermal fatigue rough defects. An ultrasonic experiment using 2-D rough crack samples made by additive manufacturing is conducted to validate the performance of the developed deep learning model. To demonstrate the accuracy of the proposed method, the crack characterization results are compared with those obtained using the conventional Hilbert peak-to-peak sizing method. The results indicate that the deep learning method achieves significantly reduced uncertainty and error in rough defect characterization, in comparison with traditional sizing approaches used in ToFD measurements.

Ultrasonic evaluation of wire arc additively manufactured parts with heterogeneous microstructure

Abstract In Wire Arc Additive Manufacturing (WAAM) components manufactured by gas metal arc welding strategy, periodically alternating patterns of fine- and coarse-grained microstructures develop along the building direction, depending on the temperature evolution. Ultrasonic non-destructive evaluation relies on the scattering of waves from defects. In the material microstructure, ultrasound waves are also scattered at the grain boundaries as grain noise. The work presents a study on the influence of heterogeneous microstructure in WAAM on defect detectability during ultrasonic inspections. The study used a 2D finite element model to simulate ultrasound wave propagation in the material microstructure represented by a surface element from electron backscatter diffraction scans. Side-drilled holes were introduced in the material as defects. Phased array was used to perform full matrix capture and obtain ultrasound image through total focusing method, with dynamic focusing capability to inspect the heterogeneous microstructure. The study analysed the defect echoes and noises using the signal-to-noise ratio (SNR) to assess its defect detectability. While defects were well detected, the SNR values differ by 10% for defects at various positions along the building and transverse directions in the heterogeneous microstructure.

Ultrasonic Non-Destructive Testing and Evaluation of Stainless-Steel Resistance Spot Welding Based on Spiral C-Scan Technique.

In order to achieve the non-destructive testing and quality evaluation of stainless-steel resistance spot welding (RSW) joints, a portable ultrasonic spiral C-scan testing instrument was developed based on the principle of ultrasonic pulse reflection. A mathematical model for the quality evaluation of RSW joints was established, and the centroid of the ultrasonic C-scan image in the nugget zone of the RSW was determined based on the principle of static moment. The longest and shortest axes passing through the centroid in the image were extracted, and the ratio of the longest axis to the shortest axis (RLS) factor and the average of axis (AOA) factor were calculated, respectively, to evaluate the quality of the joint. To study the effectiveness of the detection results, tensile tests, and stereo analysis were conducted on the solder joints after sampling. The results indicate that this detection method can realize online detection and significantly improve the detection efficiency; the detection value of internal defect size is close to the true value with an error of 0.1 mm; the combination of RLS and AOA factors can be used to evaluate the mechanical properties of RSW joints. This technology can be used to solve the NDT, evaluate problems of RSW joints, and realize engineering applications.

Research on ultrasonic non-destructive evaluation algorithm for ultimate tensile strength of stainless-steel welded pipe welds based on width learning

ABSTRACT The regression prediction between ultrasonic signal and ultimate tensile strength of stainless-steel pipe weld is studied in this paper. First, ultrasonic signals were collected from the weld of AISI304 austenitic stainless steel welded pipe sample, and its ultimate tensile strength was tested. The data sets of ultrasonic signal and ultimate tensile strength of weld were constructed. The random forest algorithm is used to extract the characteristic value set of the ultrasonic signal set of the welding seam and reduce the dimension of the characteristic value set. Then, the set of eigenvalues after dimensionality reduction is input into the Bayesian BLS network for training. The results of the training were compared with those of other regression models. The results show that the model established by Bayes BLS algorithm is feasible and reliable to predict the ultimate tensile strength of stainless-steel pipe weld. The results also show that the model established by the Bayesian BLS algorithm has high accuracy and stability in predicting the ultimate tensile strength of stainless-steel pipe weld. This method can be used to predict the ultimate tensile strength of welds in different types of materials.

Nondestructive Evaluation and Residual Property Assessment of Impacted Nylon/carbon-Fiber Additively Manufactured FFF Components Using Four-Point Bend and Ultrasonic Testing

ABSTRACT Fusion-based material extrusion additive manufacturing, commonly known as fused filament fabrication (FFF), is a layer-by-layer manufacturing process known for creating custom components, specializing in complex geometries, with applications in the aerospace, automotive, medical, as well as many other industries. Due to the critical nature of these industries, it is imperative to understand the relationship between the AM material in question, the nature of the resultant damage, and the impact of these two parameters on the future performance of the component. The purpose of this study is to investigate the relationship between low-velocity impact and the resultant damage in common functional FFF materials and to develop methods of visualizing that damage using ultrasonic nondestructive evaluation. Coupons of a nylon feedstock infused with and without 10% chopped carbon fiber were fabricated using an Essentium HSE printer and impacted at various energies. The extent of the damage was visualized using ultrasonic testing (UT), in which significant internal cracking was observed. Four-point bend testing was utilized to compare behavior of the material prior to impact at a lower impact energy (3J), and a higher impact energy causing visual fracture (7J). X-ray CT was also performed on two samples to validate UT findings.

Use of Non-Destructive Ultrasonic Techniques as Characterization Tools for Different Varieties of Wine.

In this work, we have verified how non-destructive ultrasonic evaluation allows for acoustically characterizing different varieties of wine. For this, a 3.5 MHz transducer has been used by means of an immersion technique in pulse-echo mode. The tests were performed at various temperatures in the range 14-18 °C. The evaluation has been carried out studying, on the one hand, conventional analysis parameters (velocity and attenuation) and, on the other, less conventional parameters (frequency components). The experimental study comprised two stages. In the first, the feasibility of the study was checked by inspecting twelve samples belonging to six varieties of red and white wine. The results showed clearly higher ultrasonic propagation velocity values in the red wine samples. In the second, nine samples of different monovarietal wine varieties (Grenache, Tempranillo and Cabernet Sauvignon) were analyzed. The results show how ultrasonic velocity makes it possible to unequivocally classify the grape variety used in winemaking with the Cabernet Sauvignon variety having the highest values and the Grenache the lowest. In addition, the wines of the Tempranillo variety are those that present higher values of the attenuation coefficient, and those from the Grenache variety transmit higher frequency waves.

Quantitative Measurement and Evaluation of High-Resolution Ultrasonic Sound Fields using a Novel Automated Ultrasonic Immersion Scanner

Ultrasonic probes are an integral part of the automated ultrasonic non-destructive testing and evaluation (NDT&E) systems to detect and size the defects in a wide range of structural materials in production lines. A complete quantitative assessment of the performance characteristics of an application-specific UT probe is needed to be evaluated on the basis of the international standard DIN EN ISO 22232-2. This requirement of full assessment not only improves the quality assurance of the manufactured probes by evaluating the acceptance criteria but also provides the useful technical information to the end-user to optimize the automated ultrasonic testing on-site. In addition, the evaluation of probe characteristics should be carried periodically throughout their service life. In this work, we developed a novel high-precision ultrasonic immersion scanner to evaluate the full ultrasonic probe characteristics which include the squint angle measurement in three different reference planes (XY, XZ, and YZ), RF-signal and its frequency spectrum at water-steel interface, focal distance, focal range, focal width, focal length and also the angle of beam divergence in different planes of the sound field distribution. In the newly developed UT immersion scanner, for the first time, we successfully integrated the high-precision Hexapod with six axes to achieve a few micrometer (~15 µm) spatial-resolution in the measured sound field patterns and a good angular resolution (~0.05°) in the squint angle measurement. In addition, we used a verified UT instrument in accordance with the standard DIN EN ISO 22232-1 to obtain more accurate amplitude values (±0.5 dB) while scanning a test block. The automated scanning, data acquisition, evaluation, visualization and the automated test report generation are carried based on the standard DIN EN ISO 22232-2. The measured sound beam characteristics of both focused and non-focused application-specific ultrasonic probes with center frequencies ranging from 0.2 - 15 MHz using the pulse-echo technique on a 3 mm half-ball steel reflector are presented. In addition, the measured sound beams of an application-specific 5 MHz multi-element transmit-receive (TR) probe using the 3 mm flat-bottomed-hole (FBH) reflector in a steel reference plate are discussed. Finally, the quantitative analysis of the measured sound field results and the acceptance criteria in accordance with DIN EN ISO 22232-2 are discussed.

Evaluating Diffusion Models for the Automation of Ultrasonic Nondestructive Evaluation Data Analysis

We develop decision support and automation for the task of ultrasonic non-destructive evaluation data analysis. First, we develop a probabilistic model for the task and then implement the model as a series of neural networks based on Conditional Score-Based Diffusion and Denoising Diffusion Probabilistic Model architectures. We use the neural networks to generate estimates for peak amplitude response time of flight and perform a series of tests probing their behavior, capacity, and characteristics in terms of the probabilistic model. We train the neural networks on a series of datasets constructed from ultrasonic non-destructive evaluation data acquired during an inspection at a nuclear power generation facility. We modulate the partition classifying nominal and anomalous data in the dataset and observe that the probabilistic model predicts trends in neural network model performance, thereby demonstrating a principled basis for explainability. We improve on previous related work as our methods are self-supervised and require no data annotation or pre-processing, and we train on a per-dataset basis, meaning we do not rely on out-of-distribution generalization. The capacity of the probabilistic model to predict trends in neural network performance, as well as the quality of the estimates sampled from the neural networks, support the development of a technical justification for usage of the method in safety-critical contexts such as nuclear applications. The method may provide a basis or template for extension into similar non-destructive evaluation tasks in other industrial contexts.

Ultrasonic Nondestructive Evaluation of Composite Bond Strength: Quantification through Bond Quality Index (BQI)

This article presents a concept, materials, and methods to devise a Bond Quality Index (BQI) for assessing composite bond quality, approximately correlating to the respective bond strength. Interface bonding is the common mechanism to join two composite structural components. Ensuring the health and quality of the bond line between two load-bearing composite structures is crucial. The article presents the classification and data-driven distinction between two types of bond lines between similar structural components. The interface bonds in composite plates were prepared using polyester peel ply and TX-1040 nylon peel ply. For all the plates, ultrasonic inspection through scanning acoustic microscopy (SAM) (>10 MHz) was performed before and after localized failure of the plate by impinging energy. Energy was impinged 0–10 J/cm2 of in the 16-ply plates, and 0–25 J/cm2 were impinged in 40-ply plates. Followed by bond failure and SAM, a new parameter called the Bond Quality Index (BQI) was formulated using ultrasonic scan data and energy data. The BQI was found to be 0.55 and 0.45, respectively, in plates with polyester peel ply and TX-1040 nylon peel ply bonds. Further, in 40-ply plates with polyester peel ply resulted in a BQI equivalent to 3.49 compared to 0.75 in plates with a TX-1040 nylon peel ply bond. Currently, the BQI is not normalized; however, this study could be used for AI-driven normalized BQIs for all types of bonds in the future.

Early detection of steel tube welded joint failure using SPC-I nonlinear ultrasonic technique

Welding is a commonly used method for joining two or more parts together in steel construction. Various defects in weld regions such as cracks, pores, and slag inclusion can be present from the beginning, generated during the welding process, or can be developed while in service. Such defects are the weak spots that degrade the structure’s quality and can lead to structural failures. Therefore, early detection of these defects in welded joints, before visible cracks appear, is very important. Using appropriate ultrasonic non-destructive testing and evaluation (NDT&E) techniques, one can detect these defects and take remedial actions to prevent catastrophic structural failures. Guided acoustic wave-based techniques have been proven to be effective for damage detection in steel pipes and rods. Several studies have previously attempted to detect damage in steel tubes using guided ultrasonic waves. Unlike earlier attempts which mostly focused on conventional linear ultrasonic techniques, a relatively new nonlinear ultrasonic technique called sideband peak count-index (SPC-I) is carried out in this research. For this investigation, cast steel components and round hollow structural sections are welded together, and a four-point bending test is conducted under fatigue loading. The welded joints are continuously monitored in real time using strain gages and lead zirconate titanate (PZT) transducers. The PZT transducers are used to generate and receive guided acoustic waves. The signal is propagated through the specimen in a single-sided transmission mode setup. The strain gage readings and the nonlinear ultrasonic parameter, the SPC-I values, are monitored simultaneously. The results obtained from the nonlinear ultrasonic NDT&E measurements are compared with the data obtained from the strain gages to determine the robustness and reliability of the SPC-I technique for monitoring welded joints. This investigation also shows the potential effectiveness of the nonlinear ultrasonic parameter SPC-I for early detection of weld failure.

Ultrasonic evaluation of additively manufactured components with embedded structures

In recent years, the use of ultrasonic nondestructive evaluation (NDE) for in situ and ex situ assessment of Additive Manufacturing (AM) parts has garnered interest due to its proficiency in defect detection and material characterization. This study focuses on evaluating the ability to resolve internal structures created by AM and hybrid AM using ultrasonic NDE as well as assessing the impact of microstructure heterogeneity. For this purpose, first the parameter space for laser powder bed fusion (LPBF) of SS316L is mapped in a Lumex Avance 25 system. Based on this parameter mapping, optimal process parameters are identified and sets of process parameters are selected to vary the thermal history of the samples, while minimizing the influence of porosity. Two groups of samples are printed with these parameter sets: a solid group of samples, and a group with internal structures, such that each internal structure sample has an equivalent solid sample. Measurements of ultrasonic velocity, attenuation, and backscatter amplitude are collected and compared against the intended geometry to assess the impact of non-optimal processing on the ability to resolve internal structures with ultrasound. The viability and limitations of using ultrasound to assess internal features created with AM are discussed.

Degradation monitoring of multilayer ceramic capacitors during high accelerated lifetime testing using ultrasound

Multilayer ceramic capacitors (MLCCs) are vital circuitry components where long-term stability at high temperature and fields is critical to device operation. High accelerated lifetime testing (HALT) statistically investigates reliability and lifetime of MLCCs through exposure to temperatures and voltages exceeding normal operating conditions. The long-term reliability of the dielectric layers in MLCCs strongly depends on potential variability in the dielectric microstructure, such as cracking, which can be challenging to detect. Nondestructive ultrasonic evaluation is sensitive to microstructural changes through measurements of wave scattering. This work uses high frequency (100 MHz) focused ultrasonic scattering methods to nondestructively monitor structural and microstructural changes in MLCCs from the pristine to the failed state during HALT to understand structural origins of electrical failure. Printed circuit board mounted MLCCs were electrically and ultrasonically characterized in a pristine state and during various degraded states before and after electrical failure under HALT. Evidence of damage pre-HALT was ultrasonically indicated by high attenuation regions on the ultrasonic maps suggesting that the mounting process may induce damage. The high attenuation regions in the pristine samples evolved throughout HALT indicating that the damage in the pristine state might be the spatial origin of part failure, which underscores the impact and importance of detection of structural defects on the reliability of MLCCs.

Determination of the anisotropy in mechanical properties of laser powder bed fusion Inconel 718 by ultrasonic testing

ABSTRACT This study aims to investigate the effects of build direction on the as-fabricated microstructure and mechanical properties of Inconel 718 specimens manufactured via the Laser Powder Bed Fusion (L-PBF) technique. The microstructures and mechanical properties of the specimens were characterized via SEM, EBSD,ultrasonic wave velocity measurements, hardness and tensile tests. For the as-fabricated condition, the highest tensile strength (1114 MPa) was obtained with the horizontally built specimens while the vertically built ones have the highest 40% elongation. The computational analysis produced results that closely aligned with the measured yield strength values of L-PBFed samples. Additionally, a strong correlation was observed between the hardness values and longitudinal ultrasound velocity of L-PBF Inconel 718 specimens. Consequently, the non-destructive ultrasonic evaluation provided valuable insights into the anisotropy of mechanical properties, complementing information obtained from conventional tensile tests.

Utilizing the derivative of unwrapped phase in ultrasonic nondestructive evaluation of elastic properties of polymer filaments.

Polymer filaments represent the fundamental materials employed in fused filament fabrication additive manufacturing. This paper uses an innovative nondestructive evaluation technique for gauging the elastic properties of these polymer filaments. The method hinges on acoustic wave scattering theory, wherein a polymer filament is immersed in water and exposed to an incident acoustic wave. The waves scattered from the cylinder contain crucial information concerning the elastic properties of the filament. To extract these properties, an inverse method is applied which compares the resonance frequencies of the scattered signal with those anticipated based on a theoretical model. To improve the performance of this method in identifying the resonance frequencies, the derivative of the unwrapped phase within the backscattered pressure spectrum is analyzed. This is an advantageous approach as it can be equally applied to both experimental and theoretical pressure spectra, simplifying the task of identification of resonance frequencies considerably. The method's effectiveness is exemplified through its application to an aluminum rod followed by its application to two polymer filaments. Comparing the elastic constants of the polymer filaments determined through the proposed method with values reported in the literature underscores the method's capability to accurately measure the elastic constants of polymer filaments.

Ultrasonic evaluation of wire-to-terminal joints: integrating XGBoost machine learning with finite element feature analysis

ABSTRACT A new scheme for ultrasonic non-destructive evaluation of wire-to-terminal joints was developed in this study. A finite element simulation model of 2D porous media based on X-CT images of an NG sample was proposed to analyse acoustic scattering. The simulation signal features were extracted in the time domain, frequency domain, and time-frequency domain, and entropy analysis was conducted to explore the relationship between different characteristic values and porosity, thereby revealing prominent trends in these features. By controlling parameters, 28 welding samples labelled OK and NG were produced, and their echoes were acquired by an ultrasonic Full Matrix Capture (FMC) system. Features of the full matrix signals were extracted, and the combined XGBoost machine learning was used to classify the quality and order the attribution of features. The result highlighted the significance of the waveform factor, margin factor, and kurtosis which are consistent with simulation results. The accuracy of weld quality identification can reach 84%. The three factors may be performance criteria for ultrasonically welded wire-to-terminal joints.

Ultrasonic Features for Evaluation of Adhesive Joints: A Comparative Study of Interface Defects.

Ultrasonic non-destructive evaluation in pulse-echo mode is used for the inspection of single-lap aluminum adhesive joints, which contain interface defects in bonding area. The aim of the research is to increase the probability of defect detection in addition to ensuring that the defect sizes are accurately estimated. To achieve this, this study explores additional ultrasonic features (not only amplitude) that could provide more accurate information about the quality of the structure and the presence of interface defects. In this work, two types of interface defects, namely inclusions and delaminations, were studied based on the extracted ultrasonic features in order to evaluate the expected feasibility of defect detection and the evaluation of its performance. In addition, an analysis of multiple interface reflections, which have been proved to improve detection in our previous works, was applied along with the extraction of various ultrasonic features, since it can increase the probability of defect detection. The ultrasonic features with the best performance for each defect type were identified and a comparative analysis was carried out, showing that it is more challenging to size inclusion-type defects compared to delaminations. The best performance is observed for the features such as peak-to-peak amplitude, ratio coefficients, absolute energy, absolute time of flight, mean value of the amplitude, standard deviation value, and variation coefficient for both types of defects. The maximum relative error of the defect size compared to the real one for these features is 16.9% for inclusions and 3.6% for delaminations, with minimum errors of 11.4% and 2.2%, respectively. In addition, it was determined that analysis of the data from repetitive reflections from the sample interface, namely, the aluminum-adhesive second and third reflections, that these contribute to an increase in the probability of defect detection.

Simulations and experimentation of ultrasonic wave propagation and flaw characterisation for underwater concrete structures

ABSTRACT Ultrasonic non-destructive evaluation of concrete submerged in water is a complex phenomenon that has important implications for the durability and safety of marine structures such as bridges, piers and offshore platforms. The scattering of ultrasonic waves inside concrete materials with aggregate size comparable to the ultrasound wavelength often limits the interpretation of inspection results. To enhance the understanding of ultrasonic wave propagation inside the underwater concrete, numerical simulations using the finite element method (FEM) with the Transient Acoustics-Piezoelectric Interaction application mode of Multiphysics software package have been developed. This study focuses on developing a 2D numerical model to reproduce and illustrate the propagation of ultrasound in seven types of underwater concrete test blocks with various types of inclusions and voids embedded inside it. The B-Scan 2D images of the concrete test blocks were acquired using the simulated data and compared with experimental results acquired using an in-house developed four-channel ultrasonic imaging system. Both simulation and experimental results showed a good resemblance, indicating that B-Scan imaging can be applied to identify and characterise various types of defects and inclusions in underwater concrete structures, providing better assessment of the material than conventional ultrasonic pulse velocity (UPV) method.