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A complete simulation chain for the laser-based generation of a microfocus-size gamma ray beam of multi-MeV energy range able to produce radiographic images has been developed. The major interactions needed to obtain such a beam are treated individually. Particle-in-cell is used to study the generation of the electron beam through laser wake-field acceleration (LWFA), and Geant4 is employed for the Bremsstrahlung photon emission and for testing the imaging capabilities of the generated gamma beam. The paper presents detailed discussions about the implementation of each simulation, along with the results obtained. The structure of the article walks through the LWFA of up to 100 MeV electron beam, followed by its attenuation through a tantalum foil generating a 300 μ m spot size photon beam, later used for imaging of a thick lead test-object, assessing a 100 μ m resolution, and confirming the simulated imaging setup suitability for non-destructive testing applications of thick high-density objects. An analysis of the quality control parameters for the generated image along with discussions of possible improvements is also included. [ABSTRACT FROM AUTHOR]

Mode coupling and conversion between longitudinal and transverse modes are ubiquitous and universal in elastic waves, presenting a challenge in realistic applications such as nondestructive evaluation and geological exploration, where independent and separate manipulation of each mode is demanded. In this article, we propose a design of elastic metalens that can realize a high-efficiency focusing for the longitudinal wave and a V-shaped converging pattern for the transverse wave at the same time. The metalens is constructed from a metagrating, where each meta-atom has a simple configuration and renders high diffraction efficiency even for large steering angles, enabled by concurrent utilization of grating diffraction theory and advanced optimization algorithms. Interestingly, an arbitrary energy splitting ratio between the reflected longitudinal and transverse waves can be obtained by precisely controlling the coupling strength and conversion efficiency between them, providing improved flexibility and adaptability to various application environments. Two illustrative examples with a sharp focusing effect and tailored conversion efficiency are explicitly demonstrated, with a 50/50 energy splitting ratio between the longitudinal and transverse waves in the first case, and a 70/30 ratio in the second one. [ABSTRACT FROM AUTHOR]

The targeted concentration of acoustic waves has significant implications for industrial nondestructive testing, ultrasound diagnosis, and medical treatment. Most conventional sound-focusing metasurfaces suffer from an untunable focus, narrow bandwidth, and fixed geometric configurations, which severely constrain their practical utility. In this paper, we propose a reconfigurable acoustic coding metasurface composed of two coding units with high transmittance and transmitted phases of 0 and π for realizing tunable and broadband sound focusing. Through the straightforward manipulation of each unit structure and alterations in the coding sequences, precise control of the focus position across the entire working plane is attainable, enabling both tunable axial-axis and off-axis sound-focusing effects. Moreover, the sound-focusing performance of the proposed metasurface is excellent within a broad frequency range from 3000 to 5500 Hz. The experimental results are consistent with theoretical expectations and numerical simulations. This work lays a practical foundation for the design of acoustic devices for tunable and broadband sound focusing. [ABSTRACT FROM AUTHOR]

This work follows on from studies carried out by Jiles and Atherton on magnetic hysteresis and on the magnetomechanical effect. The Jiles–Atherton equation, which models the rate of change of magnetization with respect to stress, was solved numerically in the forward and reverse directions for stress up to 90 MPa, suggesting that stressing carbon steel will cause a lasting change in the magnetization of the sample. This was confirmed experimentally by measuring the B-field in proximity to samples of C45 steel while undergoing tensile stress, with the pattern of magnetization suggesting that the magnetic domains reorient themselves in the geomagnetic field when stressing loosens their pinning. A further experiment on two samples confirms this, with the B-field around the samples showing strong changes according to their orientation in the geomagnetic field at the time of the stressing. This work has relevance to the non-destructive testing of steel structures such as pipelines, and the relevance of the experiments to this work is considered, as well as future prospects. [ABSTRACT FROM AUTHOR]

Background: Wheat (Triticum aestivum L.) is an important grain crops in the world, and its growth and development in different stages is seriously affected by saline-alkali stress, especially in seedling stage. Therefore, nondestructive detection of wheat seedlings under saline-alkali stress can provide more comprehensive technical support for wheat breeding, cultivation and management. Results: This research focused on moisture signal prediction and classification of saline-alkali stress in wheat seedlings using fusion techniques. After collecting and analyzing transverse relaxation time and Multispectral imaging (MSI) information of wheat seedlings, four regression models were used to predict the moisture signal. K-Nearest Neighbor (KNN) and Gaussian-Naïve Bayes (GNB) models were combined with fivefold cross validation to classify the prediction of wheat seedling stress. The results showed that wheat seedlings would increase the bound water content through a certain mechanism to enhance their saline-alkali stress. Under the same Na concentration, the effect of alkali stress on moisture, growth and spectrum of wheat seedlings is stronger than salt stress. The Gradient Boosting Decision Regression Tree model performs the best in predicting wheat moisture signals, with a coefficient of determination (R2P) of 0.98 and a root mean square error of 109.60. It also had a short training time (1.48 s) and an efficient prediction speed (1300 obs/s). The KNN and GNB demonstrated significantly enhanced predictive performance when classifying the fused dataset, compared to using single datasets individually. In particular, the GNB model performing best on the fused dataset, with Precision, Recall, Accuracy, and F1-score of 90.30, 88.89%, 88.90%, and 0.90, respectively. Conclusions: Under the same Na concentration, the effects of alkali stress on water content, spectrum, and growth of wheat were stronger than that of salt stress, which was more unfavorable to the growth of wheat. The fusion of low-field nuclear magnetic resonance and MSI technology can improve the classification of wheat stress, and provide an effective technical method for rapid and accurate monitoring of wheat seedlings under saline-alkali stress. [ABSTRACT FROM AUTHOR]

This document is a calendar of upcoming conferences, workshops, and symposiums related to materials and corrosion. The events cover a wide range of topics and will be held in different countries around the world. Some of the topics include heat treatment, corrosion control, electric steelmaking, copper alloys, sustainable development, condition monitoring, thermal spray coatings, and solar structure durability. The document provides contact information and links for more information about each event. [Extracted from the article]

Stepped repair, scarf patch repair, and patch repair are important in terms of repair techniques. The composite plate repair process starts after damage zone determination either by the unaided eye or nondestructive testing (NDT) techniques. This study investigates design cases for the stepped repairs of damaged fiber-reinforced composite materials. Before preparing steps for repair, the material around the damage zone is removed. In the stepped repair, it needs extra care to ensure that the repair plies overlap each other properly in the cut. Different cases are performed considering different step sizes. 5, 10, and 15 mm step sizes are used. The damages are given to the produced fiber-reinforced composite laminates using the Quasi-static indentation (QSI) method. Using QSI high-velocity impact simulation can be done. To get damage characteristics well-known damage test method is issued. Different span-to-punch diameter ratio (SPR) values were also used to compare different damage sizes. As a result, High ratio strength recovery was obtained using the longer step size. Maximum penetration force was reduced by nearly % 6-7 and maximum stress reduction was obtained by nearly % 8-9 for the 15 mm step size repaired composites. Among the all cases, case-1 has the highest strength recovery and case-5 has the lowest. For SPR 2, The average ultimate force value of specimens repaired with case-1 was maintained at nearly 94%. For SPR 4, repairs carried out using case-1 maintain more than 95% of damage resistance. [ABSTRACT FROM AUTHOR]

Metal additive manufacturing (MAM) technology provides a direct and efficient way for large-scale, integrated, and sophisticated engineering components in the aerospace field. Non-destructive testing (NDT) technique has been proven to be a significant method for quality evaluation of MAM components without destructing the integrity and performance of the components. However, it is still a challenging task that how to accurately and efficiently achieve the quality evaluation of large-scale and complex MAM engineering components using NDT technique. Nowadays, most studies mainly focus on the quality evaluation of small specimens or simple structure components, with comparatively less on the assessment of large-scale or complex engineering components. Thus, this review briefly introduced three urgent demands for quality evaluation of as-fabricated large or complex structure components and eight conventional NDT techniques possibly used for the quality detection of MAM. Four main challenges and future development trends in NDT technique are discussed in detail according to testing ability, data processing ability, and test standards. Among the future development trends, the application of machine learning and digital twins in NDT technique are the most promising method for intelligent detection and quality prediction of components. This work aims to provide a insight to enlarge the application of engineering components fabricated by MAM. [ABSTRACT FROM AUTHOR]

Images of titanium alloy welds detected by time-of-flight diffraction (TOFD) have problems, including large noise signals and many interference streaks around the defects, all of which seriously limit the accuracy and effectiveness of defect recognition. Existing image denoising methods lack the knowledge of the noise characteristics of TOFD images of titanium alloy weld and the preprocessing experience of technicians in the field. In addition, it is difficult to select the parameters of the preprocessing methods, and they are easily influenced by the level of technical personnel, resulting in low efficiency and poor consistency in preprocessing. To address these problems, we proposed a denoising method based on the combination of wavelet band features and deep-learning theory for TOFD images of titanium alloy weld. First, based on the wavelet preprocessing method and the experience of nondestructive testing (NDT) technicians, we constructed an image pair dataset consisting of the original TOFD images of titanium alloy weld and the desired target images to realize the accumulation of engineers' preprocessing knowledge. Second, we constructed a multiband wavelet feature fusion U-net image denoising model (WU-net) and designed a loss function under three constraints of image consistency, image texture information consistency, and structural similarity. This model was able to learn to achieve end-to-end adaptive denoising for TOFD images of titanium alloy weld. Third, we illustrated and validated the effectiveness of TOFD image preprocessing for titanium alloy weld. The results showed that the proposed method effectively eliminated TOFD image noise and improved the accuracy of defect recognition. [ABSTRACT FROM AUTHOR]

The wire to terminal joints are prepared using ultrasonic welding and find extensive application in various fields, such as new energy vehicles and aerospace. Traditionally, tensile strength tests have been employed for welding quality inspection. However, this study proposes an automatic nondestructive evaluation scheme to overcome the inefficiency and destructiveness associated with tensile testing. To achieve this, a 5 MHz/32-element array ultrasound probe is utilized for ultrasound detection and signal acquisition from two groups of joints categorized as OK (good quality) and NG (poor quality) based on their welding quality. Signal processing techniques including short-time Fourier transform, wavelet transform, and Gramian angular field are applied to convert one-dimensional time series into two-dimensional signal feature maps. Convolutional neural networks such as VGGNet, ResNet, DenseNet, and MobileNet are utilized for the classification of two-dimensional signal feature maps. The comprehensive evaluation of different feature maps and combinations of neural networks is conducted from various perspectives including network complexity, recognition accuracy, memory consumption, and inference time. The study findings indicate that wavelet transform feature maps achieve the highest accuracy across diverse neural networks, reaching up to 95% accuracy in VGGnet13 despite higher associated costs. In MobileNet-Small and ShuffleNet-V2 networks, the accuracy stands at approximately 85%, accompanied by faster inference times and lower costs. Considering all factors holistically, the combination of wavelet transforms feature maps with MobileNet and ShuffleNet demonstrates superior cost-effectiveness and suitability for ultimate deployment and application on mobile devices facilitating automated non-destructive assessment of wire to terminal joints quality. [ABSTRACT FROM AUTHOR]

The performance of machine learning algorithms is conditioned by the availability of training datasets, which is especially true for the field of nondestructive evaluation. Here we propose one reconfigurable specimen instead of numerous reference specimens with known, unchangeable defect properties, which are usually complicated to fabricate. It consist of a shape memory polymer foil with temperature-dependent Young's modulus and ultrasound attenuation. This open a possibility to generate a reconfigurable defect by projecting a heating laser in the form of a short line on the specimen surface. Ultrasound is generated by a laser pulse at one fixed position and detected by a laser vibrometer at another fixed position for 64 different defect positions and 3 different configurations of the specimen. The obtained diversified datasets are used to optimize the neural network architecture for the interpretation of ultrasound signals. We study the performance of the model in cases of reduced and dissimilar training datasets. In our first study, we classify the specimen configurations with the defect position being the disturbing parameter. The model shows high performance on a dataset of signals obtained at all the defect positions, even if trained on a completely different dataset containing signals obtained at only few defect positions. In our second study, we perform precise defect localization. The model becomes robust to the changes in the specimen configuration when a reduced dataset, containing signals obtained at two different specimen configurations, is used for the training process. This work highlights the potential of the demonstrated machine learning algorithm for industrial quality control. High-volume products (simulated by a reconfigurable specimen in our work) can be rapidly tested on the production line using this single-point and contact-free laser ultrasonic method. [ABSTRACT FROM AUTHOR]

Deep Learning (DL) has emerged as a pivotal modelling tool in various domains because of its proficiency in learning distributed representations. Numerous DL algorithms have recently been proposed and applied to non-destructive testing (NDT) methods in agriculture. This study aimed to review the state-of-the-art applications of DL algorithms in NDT by analysing the application of DL to specific NDT applications and highlighting their contributions and challenges. It first presents a comprehensive overview of various NDT techniques that have been combined with DL in agricultural product evaluation, and then briefly describes their applications in diverse NDT tasks, such as image classification, object detection, image retrieval, and semantic segmentation. Second, this study addresses the ongoing challenges associated with data collection and fusion, model complexity, computational requirements, and robustness. Finally, future research directions are examined, underscoring the potential of novel neural network architectures and cross-disciplinary collaborations. This review aims to provide a clear understanding of the current state of DL-based NDT in agricultural product examinations and its prospects for the future. © 2017 Elsevier Inc. All rights reserved. Detailed visual map of the survey, illustrating the depth and breadth of the research field and the survey's comprehensive approach to the topic. The central concept: deep learning-based non-destructive testing (NDT) in agriculture branches out into multiple sections. The sections represent the technical aspects, such as deep learning techniques and NDT methods, the challenges in the field, future research directions, the potential impacts on agriculture sector, and the ethical implications of AI use in agriculture. [Display omitted] • Data structures of non-destructive methods input into neural network are summarised. • Metrics for the deployment of deep learning models are discussed. • Tailored DL architectures and cross-disciplinary collaboration are key direction. • Data issues, model complexity, and model robustness are main challenges. [ABSTRACT FROM AUTHOR]

The use of Lamb waves within a guided wave (GW)–based scheme holds promise toward monitoring and nondestructive evaluation (NDE) of plate structures. Their short wavelength enables interaction with small defects and they can travel long distances, thus offering extensive spatial coverage. In boosting the performance of these schemes for more advanced damage identification tasks, such as precise damage localization and quantification, the fusion of measurement data with models is advantageous. Such a hybrid scheme, which relies on the inclusion of engineering models, is hampered by the short wavelengths of GW-based schemes. Short wavelengths require a fine discretization of numerical models in space and in time, which results in high computational costs. In alleviating this issue, we propose a reduced-order model (ROM) relying on exploitation of the frequency response function (FRF) principle, which is parameterized with respect to the positioning of local defects. Through appropriate coordinate transformations, the surrogate, constructed based on the matching pursuit (MP) algorithm, can exploit the mechanical properties of the wave so that only a small amount of training simulations are needed. The efficacy of the proposed surrogate is demonstrated in a synthetic inverse setting, using a particle swarm optimization (PSO) strategy. [ABSTRACT FROM AUTHOR]

This paper attempts to evaluate the change in the behavior of the acoustic waves associated with flexure cracks developed in rubberized concretes in a subfreezing environment. Seven normal and rubberized concrete mixtures were developed with different compositions. Prism samples from each mixture were tested at two temperatures (25°C and −20°C) under a four-point monotonic flexure test while being monitored via two attached acoustic emission (AE) sensors to collect the emitted AEs till failure. The AE signal characteristics such as signal amplitudes, number of hits, and cumulative signal strength (CSS) were collected and used for three AE parameter-based analyses: b-value, intensity, and rise time–amplitude (RA) analysis. Analyzing the acoustic activity revealed micro- and macrocracks nucleation, which were found to be associated with a noticeable spike in CSS, historic index [H(t)], severity (Sr) values, and a significant dip in the b-values. In addition, cold temperature was found to increase the micro- and macrocracking onset load and time regardless of mixture composition. Besides, mixtures with a lower C/F, less crumb rubber (CR) content, and/or smaller rubber particle size witnessed higher micro- and macrocrack load and time thresholds. Noticeably, the AE signal attenuation effect caused by the high CR content (up to 30%) at 25°C was significantly relieved when samples were tested at −20°C. Three charts were developed to classify the cracking level based on the values of the intensity analysis parameters [H(t) and S] and RA analysis. Practical Applications: Infrastructure failures can cause severe economic losses and fatalities, but luckily they can be avoided through regular inspections with the aid of nondestructive testing and subsequent repairs. Aging structures need more inspections to detect potential deficiencies, whereas newly constructed ones can safely undergo fewer inspections and preserve resources. Data from nondestructive testing programs can optimize inspection schedules. When it comes to hard-to-reach structures in extreme weather, acoustic emission (AE) has the potential to be a more suitable nondestructive testing technique over other conventional methods. Some concerns were raised regarding the effectiveness of the AE technique for applications involving novel construction materials such as rubberized concrete, because rubber particles have noticeable acoustic absorption capacities that may affect the parameters of the AE waves and impact the posttesting analysis. Another concern was the influence of cold temperature on the AE wave characteristics due to the change in concrete microstructure at low temperatures. This study aimed at addressing these concerns by utilizing AE analysis to highlight the onset of micro- or macrocracks in rubberized concrete mixtures exposed to cold temperatures. Three user-friendly charts are presented that can advise on inspection decisions based on whether deterioration has reached a certain level. [ABSTRACT FROM AUTHOR]

The aim of this paper is to investigate the possibility of using two different methods together to detect more accurately and to evaluate thermal defects in the envelope of agricultural buildings. The structure of heated agricultural buildings is significantly influenced by the characteristics of the indoor environment (aggressive gaseous and liquid substances, high humidity, higher heating temperatures, etc.). In this study, research has been conducted that synergistically combines two methods for the evaluation of thermal defects, where the structure is evaluated using infrared thermography and at the same time described as a numerical model for a more detailed identification of envelope defects and thermal bridges. The study confirmed that in agricultural building structures, thermal defects are most commonly found in the areas of window lintels, ceiling and bracing structures, window and door joints, and foundation and floor joints, while the proposed combination of the two methods for assessing thermal defects in structures demonstrated superior performance in terms of accuracy and detail of results obtained compared to the standard partial use of only one of these methods. [ABSTRACT FROM AUTHOR]

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Three Dimensional Concrete printing (3DCP) stands at the forefront of modern construction methodologies, also named additive manufacturing, offering unparalleled time, cost, and labour savings compared to conventional approaches. The evaluation of fresh state parameters like extrudability and buildability through a specialised concrete extruder, combined with a methodical layer-by-layer deposition, ensures structural stability by precisely strengthening each layer. Mechanical strength evaluations highlight the printed material’s anisotropic nature, revealing extreme reductions of Fy = 27.94%, Fx = 19.07%, and Fy = 16.33% in compression, flexural, and split tensile strengths, respectively, compared to cast specimens. This emphasises the importance of direction-specific mechanical testing in understanding material behaviour completely. Non-destructive testing (NDT) methods, like Ultrasonic Pulse Velocity (UPV) testing, are crucial for the qualitative assessment of the integrity and mechanical strength of concrete structures, including both printed and cast specimens, by establishing a strong correlation with compressive strength without causing any damage. Limited research indicates that the microstructure of the material plays a significant role in its mechanical strength, particularly in printed specimens. This claim is reinforced by mercury intrusion porosimetry (MIP) results, which reveal that printed specimens have slightly higher overall porosity, concentrated between 1 µm and 0.1 µm, while cast specimens show higher porosity in pores smaller than 0.1 µm. [ABSTRACT FROM AUTHOR]

We used an optomechanical sensor to study the ultrasound generated by manually operated piezoelectric spark igniters. These low-energy sparks produce short-duration acoustic shock-wave pulses, with sub-microsecond rise times and frequency content extending well beyond 2 MHz in air. The same source–receiver combination was then used to demonstrate broadband characterization of solid (polymer and glass) plates in a simple setup, where single spark events yielded high signal-to-noise ratio data without the need for critical alignment. This setup also enabled us to estimate pressure excursions approaching 105 Pa at millimeter-scale distances from the spark. The results are in large part made possible by the small size, wide bandwidth, and high sensitivity of the optomechanical sensor and might be of interest for air-coupled ultrasound applications in nondestructive testing. [ABSTRACT FROM AUTHOR]

With the rapid development of mobile devices, electronic products, and electric vehicles, lithium batteries have shown great potential for energy storage, attributed to their long endurance and high energy density. In order to ensure the safety of lithium batteries, it is essential to monitor the state of health and state of charge/discharge. There are commonly two methods for measuring lithium batteries: destructive testing and non-destructive testing. Destructive testing is not suitable for in situ or non-destructive analysis as it can cause irreversible deformation or damage to the battery. Herein, this review focuses on three non-destructive testing methods for lithium batteries, including ultrasonic testing, computer tomography, and nuclear magnetic resonance. Ultrasonic testing is widely used in crack and fatigue damage detection. X-ray computer tomography and neutron tomography have gained increasing attention in monitoring the health status of lithium batteries. Nuclear magnetic resonance can be used to conduct in situ and ex situ detection. In this review, non-destructive testing of lithium batteries is summarized, including the current status, achievements, and perspectives of this technology. [ABSTRACT FROM AUTHOR]

In this study, an ultrasonic guided wave system that can be used to detect broken tubes in stainless steel tube bundle structures (e.g., heat exchangers) with fairly narrow spacing between the tubes was designed. The interval between the tubes was 1.5 mm, and the thickness of the strip with a transducer that can be inspected by passing between the tubes was designed to be 1 mm. The damaged specimen was filled with water, and it was confirmed that the signal amplitude was smaller than that of the normal specimen filled with air. The ultrasonic properties of stainless steel were analyzed using the developed system, and it is expected that this will contribute to breakage inspection for tube bundles with narrow spacing. [ABSTRACT FROM AUTHOR]

The detection of impact and depth defects in Glass Fiber Reinforced Polymer (GFRP) composites has been extensively studied to develop effective, reliable, and cost-efficient assessment methods through various Non-Destructive Testing (NDT) techniques. Challenges in detecting these defects arise from varying responses based on the geometrical shape, thickness, and defect types. Long Pulse Thermography (LPT), utilizing an uncooled microbolometer and a low-resolution infrared (IR) camera, presents a promising solution for detecting both depth and impact defects in GFRP materials with a single setup and minimal tools at an economical cost. Despite its potential, the application of LPT has been limited due to susceptibility to noise from environmental radiation and reflections, leading to blurry images. This study focuses on optimizing LPT parameters to achieve accurate defect detection. Specifically, we investigated 11 flat-bottom hole (FBH) depth defects and impact defects ranging from 8 J to 15 J in GFRP materials. The key parameters examined include the environmental temperature, background reflection, background color reflection, and surface emissivity. Additionally, we employed image processing techniques to classify composite defects and automatically highlight defective areas. The Tanimoto Criterion (TC) was used to evaluate the accuracy of LPT both for raw images and post-processed images. The results demonstrate that through parameter optimization, the depth defects in GFRP materials were successfully detected. The TC success rate reached 0.91 for detecting FBH depth defects in raw images, which improved significantly after post-processing using Canny edge detection and Hough circle detection algorithms. This study underscores the potential of optimized LPT as a cost-effective and reliable method for detecting defects in GFRP composites. [ABSTRACT FROM AUTHOR]

Defects occurring during the welding process of metal structural components directly affect their overall strength, which is crucial to the load-bearing capacity and durability of the components. This signifies the importance of accurate measurement and assessment of weld strength. However, traditional non-destructive testing methods such as ultrasonic and non-contact camera inspection have certain technical limitations. In response to these issues, this paper analyzes the detection principle of weld strength, revealing that weld defects reduce the effective area of the structural bearing section and cause stress concentration around them. Through repeated experimental data analysis of samples, strain distribution data along the one-dimensional direction caused by defects such as slag inclusion and porosity were obtained. Experimental results show that this method can identify defect types in welds, including slag inclusion, porosity, and unevenness, and accurately measure the location and size of defects with a precision of 0.64 mm, achieving qualitative analysis of weld defects. Additionally, by deploying distributed optical fiber sensors (DOFS) at different vertical distances along the weld direction, the propagation law of stress induced by different types of weld defects on samples was thoroughly analyzed. This further validates the advantages of this method in weld strength detection, including high spatial resolution, high sensitivity, and non-destructive measurement. [ABSTRACT FROM AUTHOR]

High-strength bolts are crucial load-bearing components of wind turbine towers. They are highly susceptible to fatigue cracks over long-term service and require timely detection. However, due to the structural complexity and hidden nature of the cracks in wind turbine tower bolts, the small size of the cracks, and their variable propagation directions, detection signals carrying crack information are often drowned out by dense thread signals. Existing non-destructive testing methods are unable to quickly and accurately characterize small cracks at the thread roots. Therefore, we propose an ultrasonic phased array element arrangement method based on the Fermat spiral array. This method can greatly increase the fill rate of the phased array with small element spacing while reducing the effects of grating and sidelobes, thereby achieving high-energy excitation and accurate imaging with the ultrasonic phased array. This has significant theoretical and engineering application value for ensuring the safe and reliable service of key wind turbine components and for promoting the technological development of the wind power industry. [ABSTRACT FROM AUTHOR]

With the increasing demand for high-performance leisure boat propellers, this study explores the development of high-strength aluminum alloy propellers using the low-pressure die-casting (LPDC) process. In Part I of the study, we identified the optimal alloy compositions for Al-6Zn-2Mg-1.5Cu propellers and highlighted the challenges of hot tearing at the junction between the hub and blades. In this continuation, we developed a coupled thermal fluid stress analysis model using ProCAST software to optimize the LPDC process. By adjusting casting parameters such as the melt supply temperature, initial mold temperature, and curvature radius between the hub and blades, we minimized hot tearing and other casting defects. The results were validated through simulations and practical applications, showing significant improvements in the quality and structural integrity of the propellers. Non-destructive testing using X-ray CT confirmed the reduction in internal defects, demonstrating the effectiveness of the simulation-based approach for alloy design and process optimization. [ABSTRACT FROM AUTHOR]

Grouting technology is the primary method for repairing cracks in earthen sites. However, there has been a long-standing lack of effective methods for evaluating grouting effectiveness. This paper proposes a field evaluation method based on P-wave velocity. This method explicitly discusses two scenarios where the P-wave velocity of the grout is either higher or lower than that of the soil, using the depth ℎ of the "hypothetical crack" as the evaluation indicator. The experimental results indicate that specimens with 20% and 40% defects show increases in ℎ values of 0.0113 m and 0.0166 m, respectively. Laboratory tests have demonstrated that this method can accurately evaluate grouting effectiveness and is not affected by the P-wave velocity of the soil. The application of this evaluation method to three typical earthen sites resulted in more reliable and easily quantifiable evaluation outcomes. By considering the width of grout, the method provides a more intuitive comparison of reparation effectiveness. The study demonstrates the feasibility of the proposed method, thereby facilitating effective crack reparation in earthen sites. [ABSTRACT FROM AUTHOR]

Using sparse matrix for total focusing method (TFM) imaging can improve computational efficiency in non-destructive testing (NDT). In sparse matrix design, binary particle swarm optimisation (BPSO) and genetic algorithm (GA) often fall into local optimal solution, and the computational efficiency decreases significantly with the expansion of array scale. In this paper, a discrete war strategy optimisation (DWSO) is proposed to realise sparse array ultrasonic imaging. This method uses equidistant scatter mapping to real-number encode the array position and limit the search range. Then, the fitness function is constructed with low side lobe peak and narrow main lobe width to obtain the optimal array element distribution. Experiments on standard test block demonstrate the DWSO algorithm has a narrower main lobe width and lower side lobe peaks than BPSO and GA. The imaging time of the sparse array constructed by this algorithm is reduced by more than 65% compared with the full array. As array scale grows, the running time variation of the proposed method is reduced by 73.2% and 77.3% compared with GA and BPSO, which has good adaptability and provides theoretical support for real-time defect detection. [ABSTRACT FROM AUTHOR]

This study aimed to determine the effects of production parameters such as wood species and timber strength classes on some mechanical properties of CLT panels using both non-destructive and destructive methods. Additionally, the study compared the strength values obtained from non-destructive and destructive testing methods on CLT panels and elucidated the relationship between them through regression analyses. CLT panels were produced using spruce and alder timbers, as well as hybrid panels formed from combinations of these two wood species. According to the TS EN 338 standard, the C and D strength classes of the timbers were determined non-destructively using an acoustic testing device. Among the timbers whose strength classes were determined, a total of 6 different strength classes were selected for spruce and alder. The bending strength, modulus of elasticity, and screw withdrawal force tests were performed on the CLT panel groups both non-destructive and destructive. As a result of the regression analyzes, the determination coefficient (R2) between non-destructive screw withdrawal force and destructive bending strength values varied between 0.6135–0,9997. Moreover, the R2 value calculated between non-destructive and destructive modulus of elasticity values for CLT panels was found to be between 0.7076–0.9997. [ABSTRACT FROM AUTHOR]

For buckwheat, the optimal harvest period is difficult to determine—too early or too late a harvest affects the nutritional quality of buckwheat. In this paper, physical and chemical tests are combined with a method using near-infrared spectroscopy nondestructive testing technology to study buckwheat harvest and determine the optimal harvest period. Physical and chemical tests to determine the growth cycle were performed at 83 days, 90 days, 93 days, 96 days, 99 days, and 102 days, in which the buckwheat grain starch, fat, protein, total flavonoid, and total phenol contents were assessed. Spectral images of buckwheat in six different harvest periods were collected using a near-infrared spectral imaging system. Four preprocessing methods (SNV, S-G, DWT, and the normaliz function) and three dimensionality reduction algorithms (IVSO, VCPA, VISSA) were used to process the raw buckwheat spectral data, and the full and eigen spectra were established as a random forest (RF). Random forest (RF) and Least Squares Support Vector Machine (LS-SVM) classification models were used to determine the full and eigen spectra, respectively, and the optimal model for the buckwheat single harvest period was determined and validated. Through physical and chemical tests, it was concluded that the 90-day harvest buckwheat grain protein, fat, and starch contents were the highest, and that the total flavonoid and total phenolic contents were also high. The SNV preprocessing method was the most effective, and the feature bands extracted using the IVSO algorithm were more representative. The IVSO-RF model was the best discriminative model for the classification of buckwheat in different harvest periods, with the correct rates of the training and prediction sets reaching 100% and 96.67%, respectively. When applying the IVSO-RF model to the buckwheat single harvest period to verify the classification, the correct rate of the training set for each harvest period reached 96%, and that of the prediction set reached 100%. Near-infrared spectroscopy combined with the IVSO-RF modeling method for buckwheat harvest period detection is a rapid, nondestructive classification method. When this was combined with physical and chemical analyses, it was determined that a growth cycle of 90 days is the best harvest period for buckwheat. The results of this study can not only improve the quality of buckwheat crops but also be applied to other crops to determine their optimal harvest period. [ABSTRACT FROM AUTHOR]

X-ray CT imaging is an important three-dimensional non-destructive testing technique, which has been widely applied in various fields. However, segmenting image voxels as discrete material compositions may lose information below the voxel size. In this study, six samples with known volume fractions of compositions were imaged using laboratory micro-CT. Optical microscopic images of the samples reveal numerous small particles of compositions smaller than the CT voxel size within the samples. By employing the equivalent energy method to determine the X-ray beam energy for sample imaging experiments, data-constrained modelling (DCM) was used to obtain the volume fractions of different compositions in the samples for each voxel. The results demonstrated that DCM effectively captured information about compositions occupying CT voxels partially. The computed volume fractions of compositions using DCM closely matched the known values. The results of DCM and four automatic threshold segmentation algorithms were compared and analyzed. The results showed that DCM has obvious advantages in processing those samples containing a large number of particles smaller than the CT voxel size. This work is the first quantitative evaluation of DCM for laboratory CT image processing, which provides a new idea for multi-scale structure characterization of materials based on laboratory CT. [ABSTRACT FROM AUTHOR]

Adhesive joints are some of the oldest inseparable connections, and were used much earlier than other non-separable connections (e.g., welded, soldered). Adhesives are widely used in the manufacture of vehicles, household appliances, aircraft, and medicine. One disadvantage of adhesive joints is their long bonding time (amounting, for example, to 72 h for polyurethane adhesives used in bus roof bonding), and another is their production of harmful waste. Tapes that are adhesive coated on both sides are increasingly being used to join parts during production. Such tapes have lower strength than traditional adhesives, but their bonding time is much shorter. In addition, the amount of waste remaining after production is minimized. Tapes, like adhesives, dampen vibrations well and seal the materials being joined. The purpose of this study was to evaluate the influence of selected factors on the quality of tape–steel sheet joints and to assess the possibility of testing acrylic tape–steel sheet joints using ultrasonic methods. It was found that the preparation of a surface for bonding has a significant effect on the quality of the joint, and it was confirmed that non-destructive evaluation of the quality of the tested joints by the ultrasonic method is possible. The decibel drop in the height of the first and fifth pulses obtained on the screen of the ultrasonic defectoscope was proposed as an ultrasonic measure. The highest-quality joints were characterized by a measure in the range of 12 dB, lower-quality areas of about 8 dB, and tape-free areas of about 5 dB. At the same time, it was noted that in the case of proper surface preparation, there was cohesive failure of the joint during breakage. [ABSTRACT FROM AUTHOR]

The use of infrared thermography (IRT) for non-destructive testing (NDT) of large aerospace composites, such as carbon fibre reinforced polymer (CFRP), is often limited by the narrow field of view infrared cameras. This paper experimentally investigates the big-sized CFRP specimens with simulated debonding defects using a robot-based dynamic optics scanning infrared thermography (RDOS-IRT) method to meet these issues. Then, static pulse IRT and RDOS-IRT were performed, and the processing performance of different algorithms (pulsed phase thermography, PPT; total harmonic distortion, THD; matched filtering, MF; and supervised dimensionality reduction, SDR) on pulsed IRT was discussed. A combination of pseudo-static matrix reconstruction (FSMR) algorithm and static image sequence processing algorithm is innovatively adopted to improve the defect detection performance of RDOS-IRT results. The experiments show that the RDOS-IRT method with FSMR and static image sequence processing algorithm is effective; moreover, it has almost a similar detection ability compared to the traditional static pulse IRT method in practical applications and saves more time. Results show that the signal-to-noise ratio (SNR) of the repeated defects is not differentiated, and the detection effect is similar. Therefore, the RDOS-IRT method is a reliable tool for NDT tasks on big-sized CFRP specimens and can be practically applied in an industrial setting for high detection efficiency. [ABSTRACT FROM AUTHOR]

The parameters of the ultrasonic phased array transducer are composed of frequency, array element width, array element spacing, and number of array elements, and their reasonableness is crucial for improving the detection performance of small defects, by optimizing its key parameters to complete the precise regulation to achieve more efficient acoustic field focusing and steering ability, thus optimizing the application of industrial nondestructive testing (NDT). The study firstly derives a mathematical model of focusing and steering of multi-element sound field based on the unit far-field sound pressure equation; numerically analyzes the effects of different elemental parameters on the focusing and steering performance of the PAUT by using MATLAB software; and simulates the optimized parameter conditions by combining with the COMSOL Multiphysics software, to demonstrate the improvement effect on the detection performance of small defects; finally, the optimized parameters are verified by experimental methods. The practical effect of the parameter optimization is verified by experimental methods, and the experimental results confirm the theoretical predictions, show substantial improvement in defect detection, and further strengthen the application value of the theoretical model. In this study, a parameter optimization method based on the combination of theory and multiple simulation software is proposed for the first time, which clearly elaborates the challenges of small defect detection by optimizing the transducer parameters in practical engineering applications, and deepens the theoretical basis of phased array ultrasound (PAUT) technology in industrial inspection, emphasizes the key role of parameter optimization in PAUT applications, and provides a strong theoretical and experimental support. [ABSTRACT FROM AUTHOR]

Magnetic flux leakage (MFL) testing is an important way of non-destructive testing, preventing some major accidents of hoist equipment by identifying the damage of wire ropes, whereas, in some working conditions such as mines and oil wells, the inevitable vibration and harsh environment will generate noise and interfere with the MFL signal, which makes it difficult to identify the damage. As a classification network, convolutional neural network is positive in recognition accuracy and noise resistance, but it is hardly used in the damage identification of wire rope. To improve the recognition accuracy of damage identification under strong noise background, we propose a method of wire rope damage identification via Light-EfficientNetV2 and MFL image. First, the MFL signal is segmented and rearranged to form the MFL image, and then, the image is classified by Light-EfficientNetV2. Then, to improve the efficiency, we reduce the layers of EfficientNetV2 to make it lighter. Finally, the availability of this method is proved by the validation set. Within five neural networks, the recognition accuracy of Light-EfficientNetV2 is the highest. Moreover, as the noise intensity increases, the recognition accuracy of Light-EfficientNetV2 is higher than EfficientNetV2, which has important value in the application of the wire rope damage identification under strong noise background. [ABSTRACT FROM AUTHOR]

In hot rolling mills, failure of work rolls is a major concern as it adversely affects mill operations and impacts production. These rolls fracture or spall due to many different reasons. Analysis of failed or spalled roll materials and actual rolling conditions in service are therefore necessary to understand the roll failure mechanism. The hot strip mill referred here consists of two stands in a roughing mill and seven stands in a finishing mill. HSS cast iron rolls are used in the primary strands of finishing mill for the rolling of cast slabs into HR sheets. This present case study describes the spalling of one of the finishing stand non-forged work rolls, and the analysis carried out using destructive as well as non-destructive testing techniques. The spalled roll showed fatigue arrest marks in a smooth continuous path along the circumferential direction. Characteristic features of the fracture surface were like those of surface-initiated spalling which is known as ribbon fatigue spalling. The fracture or spalled region was analysed using ultrasonic tests to identify the origin of the crack. A sample was also collected from the crack origination location where multiple cracks/fire cracks were observed. A detail micro-structural as well as SEM/EDS characterization of the fire cracks was done to understand the mechanism of spalling. The analysis revealed that fire cracks originated from the development of localized thermal stresses on the roll surface. These cracks resulted the roll spalling in operation. [ABSTRACT FROM AUTHOR]

The lowest-order shear horizontal (SH0) guided wave in a plate is crucial for nondestructive testing and structural health monitoring due to its nondispersive nature. However, mode conversion at the interface for the SH0 wave complicates the received information and increases the difficulty of signal analysis. In this work, an elastic metasurface is proposed to suppress mode conversion at the interface and to reflect the SH0 wave directionally. The metasurface comprises a series of rectangular elements with a specific phase gradient covering the 2 π phase range. The effectiveness of the proposed metasurface is confirmed through finite element simulations and experimental validation. The results indicate that the metasurface can significantly reduce the amplitude of the reflected lowest-order symmetric Lamb wave when compared to the reflection without the metasurface, while simultaneously allowing the reflected SH0 wave to propagate at the designed angle. Furthermore, the metasurface maintains its functionality for SH0 wave with incident angles varying from 0° to 25°. This study provides a viable approach for suppressing mode conversion and modulating the reflection behavior of SH0 wave, which is expected to find applications in nondestructive testing and structural health monitoring. [ABSTRACT FROM AUTHOR]

In contrast to conventional non-destructive testing (NDT) and non-destructive evaluation (NDE) methodologies, including radiography, ultrasound, and eddy current analysis, coplanar capacitive sensing technique emerges as a novel and promising avenue within the field. This paper endeavors to elucidate the efficacy of coplanar capacitive sensing, also referred to as capacitive imaging (CI), within the realm of NDT. Leveraging extant scholarly discourse, this review offers a comprehensive and methodical examination of the coplanar capacitive technique, encompassing its fundamental principles, factors influencing sensor efficacy, and diverse applications for defect identification across various NDT domains. Furthermore, this review deliberates on extant challenges and anticipates future trajectories for the technique. The manifold advantages inherent to coplanar capacitive sensing vis-à-vis traditional NDT methodologies not only afford its versatility in application but also underscore its potential for pioneering advancements in forthcoming applications. [ABSTRACT FROM AUTHOR]

Reuse in new buildings of structural concrete components from demolitions holds the potential for avoiding the use of raw materials to produce new components, including cement for new castings. Reuse rates are high in the circular economy; however, reusing structural components requires documentation of the properties to equate the safety of using reused and new components. Yet, there is no structured or recognized way to perform the documentation. This paper discusses a framework for the documentation requirements for structural concrete, stating the need for documenting the mechanical properties, concrete heterogeneity, and corrosion status of the reinforcement. The possibility is explored for documenting the required properties while the components are in the donor building by use of non-destructive test (NDT) methods. Such use of NDT methods is new. A comprehensive literature survey on the indirect literature, where NDT methods are used to demonstrate similar concrete properties though related to other purposes, is conducted. The overall conclusion is that the use of NDT methods has the potential to document the requested properties before reuse. The next steps towards implementation of NDT for documenting the properties of structural concrete components for reuse involve research in combined NDT methods and the development of AI systems for data interpretation. [ABSTRACT FROM AUTHOR]

This study proposes a fractal damage calculation method that understands the blasting damage laws at the macroscopic, mesoscopic, and microscopic scales of rock. The findings indicated that the binary graph derived from the Moments algorithm can represent minute cracks and exhibit less noise within the image. This makes the algorithm suitable for identifying and extracting macroscopic damage. A three-dimensional (3D) reconstruction technique offers visualization of the macroscopic rock damage following an explosion. The extent of this damage is quantitatively assessed using the box dimension. In addition, a multifractal method is introduced to comprehensively evaluate the macroscopic and mesoscopic damage to rock post-blasting. The multifractal dimension calculations analysis reveals that the mesoscopic damage to rock following blasting is a significant factor in the overall blasting damage. The box dimension presents a straightforward, macroscopic evaluation method for assessing 3D macroscopic fractures. On the other hand, the multifractal dimension can more accurately evaluate the macroscopic cracks and mesoscopic damage resulting from blasting. Both methods emphasize different aspects and are equally effective for assessing blasting damage. Highlights: This study proposes a fractal damage calculation method that understands the blasting damage laws at the macroscopic, mesoscopic, and microscopic scales of rock. The box dimension is a straightforward macroscopic evaluation method for assessing 3D macroscopic fractures. The multifractal dimension more accurately evaluates the macroscopic cracks and mesoscopic damage from blasting. After ordinary charge initiations, blasting damage exhibited a bimodal distribution along the borehole's axis, peaking in the charging section. [ABSTRACT FROM AUTHOR]

Damage detection in structurally reinforced concrete elements is a vital topic for structural health monitoring and for assessing the capacity of reinforced concrete members. In this regard, many destructive tests exist that allow technical experts to evaluate the damage to a structural member. Such techniques are often employed for damage assessment after a natural disaster or a man-made event to assess the structural integrity and prioritize the locations that require urgent repair work. The researcher was successful in developing a testing methodology using nondestructive testing to identify internal damage in reinforced concrete elements by linking the delay in ultrasonic wave propagation to the initiation, development, and progression of cracks in the concrete surrounding the steel reinforcement. It was observed during experimentation that using the proposed methodology of gradual loading and comparing the speed of travel of the ultrasonic pulse velocity to the undamaged elements, the researcher was successful in identifying and localizing the internal cracked portions in the structural concrete member. Twelve reinforced concrete elements with full-size tension, compression, and shear reinforcements were tested to validate the proposed nondestructive test methodology. Direct and indirect methods of investigation were employed for testing purposes. From the performed experiments on reinforced concrete members, it was concluded that the proposed nondestructive testing methodology can be successfully applied in structural capacity assessment. The data collected from on-site investigations can be used for minimizing repair and strengthening work. In-addition an in-depth sensitivity analysis was conducted using the Latin hypercube sampling method to understand the influence of each variable on the ultrasonic pulse velocity test results. A purely random combination of parameters was adopted for the sensitivity analysis. Through the analysis, it was concluded that concrete strength played the most influential role in the ultrasonic pulse velocity testing followed by concrete cover, bar diameter and wave path length. [ABSTRACT FROM AUTHOR]

Ground penetrating radar (GPR) technology is used for nondestructive testing of roads. It relies on the processing and analysis of electromagnetic waves reflected due to the differences in dielectric properties encountered by electromagnetic pulses during propagation for road quality assessment and detects distresses. The moisture content of the asphalt mixture in asphalt pavement undergoes dynamic changes, affecting the pavement's relative humidity (RH). This alteration in RH has a direct impact on the dielectric properties of the asphalt mixture, thus influencing the accuracy of GPR road detection. Therefore, it is essential to quantify the relationship between RH and the dielectric properties of asphalt mixtures. This study utilized electromagnetic field theory to establish the correlation between air dielectric constant and RH. Dielectric constant tests were performed on commonly used single-phase component materials (limestone, 70# asphalt, SBS-modified asphalt) of asphalt mixtures and different types (asphalt type, asphalt-aggregate ratio, nominal maximum aggregate size) of asphalt mixtures under varying RH. The study quantified the impact of RH on the dielectric properties of asphalt mixtures and developed a CRIM optimization dielectric model that incorporates the RH effect. The research results showed that the dielectric constants of air, limestone, asphalt, and asphalt mixtures increase with the increase in RH. Specifically, the dielectric constants of air and asphalt mixtures exhibit a linear relationship with RH. Moreover, the increase in the dielectric constant of 70# asphalt with RH is greater than that of SBS-modified asphalt. Under identical conditions, reducing the impact of RH on the dielectric properties of asphalt mixtures can be achieved by increasing the asphalt-aggregate ratio, decreasing the nominal maximum particle size of the aggregates, or utilizing SBS-modified asphalt. The CRIM optimization model yielded an overall average relative error of 3.33% for calculating the dielectric constants of different types of asphalt mixtures under the influence of RH, representing at least a 1.67% improvement compared to classical models and the improved model proposed from existing literature. The research outcomes provide significant guidance for enriching and developing the fundamental theory as well as detection evaluation technology of GPR. [ABSTRACT FROM AUTHOR]

The environmental friendliness, good thermal performance and sustainable development of rammed earth structures have attracted the attention of numerous researchers and engineers in recent years. Nevertheless, the fire safety of rammed structures has not been extensively studied. The primary objective of this study is to investigate the mechanical properties of stabilized and unstabilized rammed earth exposed to direct fire under short elapsed time and high temperatures using a kiln. Rammed earth specimens with various mix designs were prepared and then exposed to high temperatures. Afterward, destructive and nondestructive tests were performed. Additionally, microstructural analysis was preceded to evaluate the change in chemical composition and microstructural of rammed earth specimens. The majority of the stabilized specimens exhibited thermal instability at 700°C. These specimens lost up to 85% of their compressive strength and 15% of their weight and change in their chemical composition. Under direct fire exposure, the rammed earth's mechanical properties were not greatly impacted due to the short elapsed time. Compressive strength was increased in unstabilized (clay) RE specimens. A correlation between destructive and nondestructive properties was proposed. This study can be considered in the mix design of RE that experiences high temperatures. [ABSTRACT FROM AUTHOR]

Records of pile lengths are not available for several hundred high-mast light towers (HMLTs) throughout the state of Minnesota. The foundation systems, typically steel H-piles or concrete-filled steel pipe piles connected to a triangular concrete pile cap, risk overturning in the event of peak wind loadings if the foundation piles are not sufficiently deep to provide the designed uplift capacity. Without prior knowledge of the in situ pile lengths, an expensive tower foundation retrofit or replacement effort would need to be undertaken. However, the development of a nondestructive screening tool to determine the in situ pile length—compared with replacing or retrofitting all towers with unknown foundation geometries—would potentially provide significant cost savings. The main goal of the research is the development of nondestructive evaluation testing techniques for determining in situ pile lengths using steady-state vibration and hammer-impact seismic testing. The foundation testing protocol involves (1) a preliminary site investigation to determine the shallow subsurface geometry and orientation of the foundation pile cap, (2) the use of seismic cone penetrometer (SCP) attached to a cone penetration test rig to capture the induced steady-state and impact waveforms, and (3) data-driven analysis of field testing results to determine the pile lengths. [ABSTRACT FROM AUTHOR]

The thickness of the bonding interface changes after the structure has been subjected to tensile load, thereby affecting the strength of the bonding structure. It is necessary to monitor the evolution of the bonding interface thickness under tensile load. Through terahertz time-domain spectroscopy imaging and scale-invariant feature transform image processing, the thickness variation of three interfaces of 150 silicon-based adhesive structures under tensile load were analyzed. It was determined that variation at the edge was larger than that in the middle area. The research results also provide data support for the bonding structure health monitoring systems. [ABSTRACT FROM AUTHOR]

The article provides information on Insight's current awareness service, which includes a database covering various non-destructive testing (NDT) techniques and related fields, and details how users can access literature, technical reports, and standards through various institutions.

Acoustic emission (AE) is a non-destructive testing technique, and establishing correlations between AE signals and material damage modes is one of its primary challenges. However, it is difficult to identify damage modes in ceramic matrix composites (CMCs) due to AE signal attenuation occurring after propagation and complex damage modes. In this study, AE signals generated by the breakage of C and SiC fibers were monitored at different distances and angles on the C/SiC plate. The attenuation of energy and the frequency spectra were analyzed. The Mel-frequency cepstral coefficient (MFCC) method was used to analyze the waveform data of AE signals and extract MFCC features. To identify the damage caused by C and SiC fiber breakage, AE parameter features and MFCC features were selected as inputs, and a fully connected neural network was constructed to train a supervised pattern recognition model. The results show that the MFCC feature has higher recognition accuracy than the traditional feature when AE is used for damage identification. [ABSTRACT FROM AUTHOR]

This document provides a comprehensive calendar of events for September, October, and November 2024. The events listed cover a wide range of topics in materials science and engineering, including corrosion, sustainable development, superalloys, nondestructive testing, and more. These events will be held in various countries around the world, such as France, Germany, Austria, Italy, the USA, Brazil, and China. The document includes contact information and links for each event, allowing library patrons to access further details. [Extracted from the article]