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An original partial discharge generated in oil insulation identification methodology based on simultaneously conducted measurements using electrical method, ultra high frequency method and acoustic emission method is presented in the paper. Three different partial discharge model sources as well as measuring instruments commonly applied for partial discharge detection in electrical power transformers are yielded within a laboratory research. Total of 45 scenarios, including proposed spark gap configurations, selected supply voltage levels and UHF frequencies are analyzed during measurements series. Furthermore, form among total of 93 descriptors assigned for every applied partial discharge model source configuration there are 24 proposed as potentially useful for partial discharge identification applications with their 95% confidence bounds. Attempt of discriminative descriptors selection for partial discharge source analysis in on-site transformer applications as well as a proposal of unique descriptors according to every selected spark gap configuration that could be potentially useful for partial discharge identification purposes are the main purpose of the presented paper. The proposed methodology verification on a real life transformer with particular consideration of the selected descriptors potential utility in the fields of partial discharge detection and identification in electrical power industry applications confirmed a proposed methodology usefulness. [ABSTRACT FROM AUTHOR]

Abstract: An experimental investigation is performed and analyzed in order to examine the onset and evolution of damage processes in thin isotropic paper sheets made of mechanical pulp. A microscopy technique has been used to estimate the relative fraction of bond and fibre breaks. It has been found that the active damage mechanism is bond failure, hence supporting the assumption of an isotropic scalar valued damage variable. All experiments have been performed by simultaneous with the mechanical loading monitoring the acoustic emission activity. Three different experimental setups have been designed offering the possibility to analyze the influence of stress gradients, as well as different levels of the ratios between the in-plane normal stresses, on the onset of damage. It is concluded that stress gradients in the paper specimens have a large influence on the onset of damage. When stress gradients are present a non-local theory has to be used in the analysis. In this way compliance with an isotropic damage criterion is achieved. The characteristic length, determining the gradient sensitivity, has been found to be of the same order of magnitude as some average fibre length. To study the evolution of the damage processes, wide and short specimens have been loaded in tension resulting in stable damage processes. With the assumptions made regarding the mechanical behavior of the paper material after onset of damage, the damage and the cumulative number of acoustic events curve correlates very well. The experimentally obtained data is used to determine material parameters in a proposed damage evolution law. It is found that the assumed damage evolution law can, for isotropic paper materials with bond rupture as the prevalent failure mechanism, be further simplified as only one specific material dependent damage evolution parameter has to be determined in experiments. [Copyright &y& Elsevier]

This paper introduces a novel indirect tool condition monitoring (TCM) system for micro-milling brittle materials (glass and silicon) based on acoustic emission (AE) and cutting force signals. The milling experiments are also applied to a ductile material (steel) for comparison. Tool wear calibration is conducted to determine the three tool wear stages. The collected signals are processed in time, frequency, and time-frequency domains. Specific frequency subrange combinations of cutting force signals in three directions after wavelet packet decomposition show strong correlation to the tool wear stages, whilst processed AE signals are the secondary feature to the tool wear. A tool wear prediction model for each material is built based on all the chosen features and back propagation (BP) neural network. The prediction model is simply structured and highly efficient with the highest prediction accuracy of more than 95%. • A novel indirect tool condition monitoring system designed for micro-milling of brittle materials. • TCM system developed using the combination of acoustic emission and force sensors. • Special wavelet packet decomposition method was proposed for data processing. • High-accuracy tool wear prediction model was built and verified. [ABSTRACT FROM AUTHOR]

In this paper, the damage progression and fracture behavior in notched cross-ply SiC/SiC composites were investigated using the in situ digital image correlation (DIC) and acoustic emission (AE) techniques. Under tensile loading, the mechanical properties of composite's elastic modulus, proportional limit stress (PLS), ultimate tensile strength (UTS), and fracture strain were obtained for non-notched, single-hole, double-holes, and four-holes samples. Based on the analysis of composite's tangent modulus, the nonlinear tensile stress-strain curves were divided into three main domains, relating with internal multiple damage mechanisms observed using the in situ DIC and AE. Effects of the number and location of the circular holes on the full-filed composite's damage and strain evolution, AE energy and ring-down count were investigated. After tensile fracture, the composite's macro fracture morphology and micro damage mechanisms were observed under the scanning electronic microscopy (SEM). Numerical modeling of tensile damage and fracture process of different notched samples were conducted using the extend finite element method (XFEM). Relationships between the notch types, tensile mechanical properties, macro strain evolution, and micro damage mechanisms were established. [ABSTRACT FROM AUTHOR]

Hydrogen attack is the major failure cause of hydrogen equipment breakdown maintenance. Especially, common problems like cracks frequently occur but are challenging to find while operating, presenting an issue for safety and production. In the process of hydrogen damage evolution, a method for defect state recognition is proposed in this paper. Acoustic emission (AE) technology is used for inspecting the entire hydrogen charging process. The characteristic parameters including the counts and duration of the AE signals are first preprocessed, and the current damage states such as the dislocation propagation, and the occurrence of cracks are identified. Then, a deep learning convolutional neural network is used to create a hydrogen defect recognition (HDR) model with the input of a short-time Fourier transform for the feature vector extraction of various damage status AE signals. Finally, the hydrogen defect recognition experiment revealed that HDR is better in classification accuracy at 98.37% due to dislocation propagation and cracks identification. The study can provide an online damage recognition approach for damage state early warning and evaluation to guarantee hydrogen equipment safety operation. • Monitor the hydrogen damage process using acoustic emission detection technology. • Characteristics of the acoustic sources in hydrogen damage process are studied. • Neural network is used for hydrogen damage signal recognition and diagnosis. • STFT transform image is used as the neural network model input. [ABSTRACT FROM AUTHOR]

Bridges have become an essential part of our transport networks. Therefore, the issue of cable damage detection in bridge health monitoring, specifically through acoustic emission (AE) technology, is of paramount importance for the nation and its citizens. This paper extensively investigates and compares various bridge cable damage identification techniques applied to AE. It can be categorized into two major classes: conventional parameter identification and machine learning identification. For the former, the signal's own feature parameter identification technique and the signal's mathematical index identification method are reviewed, summarizing their pros and cons. For the latter, both unsupervised and supervised learning are extensively surveyed. This paper introduces insights from AE monitoring in other six research fields, such as rail crack monitoring, and presents a basic process. Finally, the directions and recommendations for future research are proposed, providing useful suggestions for research in bridge cable damage identification and related domains. [ABSTRACT FROM AUTHOR]

The acoustic emission (AE) technique allows monitoring damage in (reinforced) concrete in a non-destructive way by means of piezoelectric sensors attached to the material surface. This approach has disadvantages such as a decrease of the sensor coupling over time, high attenuation of AE waves in concrete, and difficulties in terms of sensor placement. Embedded AE sensors, so-called 'smart aggregates' (SA), can be a valuable addition or alternative to surface-mounted AE sensors. However, the embedment of sensors brings its own challenges. In this paper, the use of SA is investigated to monitor cracking of fiber reinforced concrete during a three-point bending test, and corrosion and related concrete cracking of reinforced concrete during an accelerated corrosion test. The novelty of the paper is the application of SA for passive AE monitoring during concrete degradation processes with a varying cracking behavior and crack orientation. Special emphasis is put on data filtering and localization of AE sources. The results show that, despite a higher level of wide-band noise for the SA sensors, they are able to detect and localize concrete cracking after dedicated filtering. Furthermore, the potential of SA sensors in early-stage detection of corrosion damage is demonstrated, offering enhanced possibilities for predictive maintenance of concrete structures. • Feasibility of smart aggregates for passive acoustic emission monitoring is studied. • Smart aggregates enable to detect and localize concrete cracks after post-filtering. • Potential of smart aggregates for rebar corrosion damage detection is demonstrated. [ABSTRACT FROM AUTHOR]

The magneto acoustic emission (MAE) technique is an emerging non-destructive testing (NDT) method that has shown potential for defect detection in the bulk of material, proven vital for the safety and integrity of the material. The MAE technique has shown promising results among modern non-destructive testing techniques for ferromagnetic materials. Although MAE technique is a long-established NDT method, it has the potential for further development. This paper provides an in-depth review of MAE signals' physical origin and characteristics, compares them with their counterpart, Magneto Barkhausen Noise (MBN), and explores data acquisition methods and applications, including specific case studies in material defect detection. The research gaps in the MAE technique are discussed, and the paper explores potential developments, highlighting future perspectives and possible improvements. [ABSTRACT FROM AUTHOR]

• High specific speed Francis turbine as an alternative to low specific speed Kaplan/semi-Kaplan/Propeller turbine. • Comprehensive experimental studies of the high specific speed Francis turbine. • Multi-aspect experimental approach to determining the Thoma cavitation number. • Comprehensive vortex visualization for various cavitation states in the draft tube. • Saddles were found on the performance characteristics for high guide vane opening angles. The paper presents comprehensive experimental research on a high specific speed model Francis turbine with a characteristic runner diameter of 250 mm under the head of 12 m. Essentially, the turbine was designed for use at heads between 10 and 50 m, which are typical for installations with low specific speed Kaplan turbines. The basic performance, cavitation and runaway characteristics of the machine, which were determined as a result of the work, are quite rarely available in the literature in the case of high specific speed Francis turbines. The turbine achieved the maximum efficiency of 91%, kinematic specific speed of 82, and relatively wide operation range, so that it can be attractive as an alternative to the low specific speed Kaplan, semi-Kaplan or propeller turbines. In result of the basic laboratory tests, the performance characteristics of the machine operation in a wide range of guide vane opening angles between 9° and 36° as well as the shell efficiency characteristics were determined. On the characteristics plotted vs. rotational speed, the saddle effect was identified for the guide vane opening angles with values greater than the optimal one (22°). During the operation of the machine in the area of saddles, the change in the flow rate took quite surprising patterns. The share of the turbine thrust torque in the total torque was also determined, the characteristics of which are also burdened with a similar saddle effect. In the case of cavitation tests, a multi-aspect approach to cavitation diagnostics was used to characterize the cavitation phenomenon from the viewpoint of various criteria. Following this approach, the signals of the draft tube wall acceleration, acoustic emission at the draft tube cone upper flange, and pressure fluctuations inside the draft tube were used. The determined cavitation characteristics indicate little cavitation susceptibility of the Francis turbine blade system, despite the presented turbine having been designed to operate at higher flow rates than the classic high head Francis turbines with long interblade channels. The cavitating flow in the draft tube, directly below the runner, was also visualized during the cavitation tests. The paper presents the results of visualization for all cavitation states at five selected settings of the guide vane opening angle (two states in Partial Load, two states in High Load area and one state in the Best Efficiency Point), thanks to which it was possible to track the development of vortices during pressure reduction in the flow system. The runaway coefficient was determined as a result of the runaway tests. The value of 1.497 was reached at the optimum guide vane opening angle. Additionally, the work also presents in detail the efficiency scale effects to be expected at prototype turbines, i.e. those intended for operation at a higher head and with larger runner diameters. The efficiency of the machine with a runner diameter of 1.5 m and working at a head of 50 m reaches ∼93%. The influence of water viscosity on the change in efficiency of the prototype turbine is also shown. The presented methodology can be used for the proper selection of turbines intended for hydropower plants and for the proper installation of the runner in respect to the tailwater level in order to avoid the phenomenon of cavitation erosion. [ABSTRACT FROM AUTHOR]

Low cycle fatigue cropping technology is a new type of cropping technology with advantages such as no chip waste and low load need. Numerous studies have shown that increasing the fatigue frequency or increasing the displacement load can improve the cropping efficiency, but at the same time, it will reduce the quality of the cross-section and cannot achieve a balance between high efficiency and high quality of cross-section. In response to this issue, this paper found the phenomenon of transition of fracture modes (from fatigue mode to tensile fracture mode) of 6061Al material in LCFC process, and proposed the Active Load Reducing Optimization Strategy for 6061Al in LCFC, which achieves a significant improvement in quality of cross-section with a slight loss of cropping efficiency. Firstly, this paper studied the crack fracture mechanism of 6061Al bar under different displacement loads in the LCFC process. It was found that the transition of crack propagation mode in 6061Al- LCFC process was the main reason for the increase in cross-section roughness. The crack propagation mode changed from fatigue propagation to tensile fracture propagation during the LCFC process, and the roughness of the area significantly increased under the tensile fracture propagation mode. Further research has found that the fundamental reason for the contradiction between the cropping efficiency and section quality of 6061Al is the change in time of crack propagation mode transition and tensile fracture zone area under different displacement loads. Finally, the LCFC process was modeled in a time dimension using acoustic emission(AE) technology, and it was divided into three stages according to the AE signals and the fracture mechanism. As a result, an active load reducing optimization strategy for LCFC process was developed to delay the occurrence of tensile fracture propagation modes. Experiments have shown that compared to the traditional LCFC cropping strategy using constant displacement loads, the active load reducing strategy proposed in this paper can reduce the proportion of tensile fracture area, achieve a significant improvement in quality of cross-section with a slight loss of cropping efficiency, thus achieving a balance between efficiency and section quality to some extent. At the same time, an LCFC process section quality efficiency evaluation index with dual weights of efficiency and section quality has been proposed, which can assist in selecting LCFC active load reducing strategy parameters with consideration of efficiency and section quality weights. [ABSTRACT FROM AUTHOR]

• Recycled aggregate has a negative effect on the mechanical properties of SPRAC, whereas hybrid fiber has a positive effect. • The cracks in SPRAC specimens all extend gradually from the bottom of the center to the top, and cracks are mainly tensile and shear cracks. • The b-values can be used to calculate early warning parameters for predicting SPRAC conditions. • The deformation of SPRAC under loading is analyzed using XTDIC software to investigate the crack initiation and extension. • The primary factor causing the SPRAC's mechanical qualities to deteriorate under bending load is the destruction of these zones. The engineering application of recycled aggregate concrete is significant for resource conservation and environmental protection. However, the applied range of recycled aggregate concrete is greatly limited due to microscopic defects such as microcracks in recycled aggregate. Steel-polypropylene fiber reinforced recycled concrete (SPRAC) makes up for the defects brought by recycled aggregate to a certain extent due to the action of hybrid fiber. To further promote the practical application of SPRAC, it is crucial to evaluate its damage-fracture mechanic's response mechanism under different hybrid fiber admixtures and recycled aggregate replacement rates. For this purpose, the following work is carried out in this paper: firstly, SPRAC beam specimens with different substitution rates of hybrid fiber and recycled aggregate were prepared; and the damage-fracture process of specimens under four-point bending load was monitored in real-time by using acoustic emission and digital image correlation techniques to analyze the influence of hybrid fiber and recycled aggregate on the flexural properties and damage-fracture characteristics of SPRAC; the inherent relationship between the acoustic emission rise time/amplitude (RA) and the average frequency (AF) is utilized to classify the crack type of SPRAC in the course of the data analysis; the b-value is also analyzed to assess the crack evolution process in SPRAC, and the corresponding warning thresholds are given.; strain and displacement fields on the specimen surface are analyzed using the digital image correlation; finally, the microscopic results of SPRAC are also given to better understand the damage-fracture evolution mechanism of SPRAC. Results show that the flexural strength and fracture toughness of SPRAC decreased nonlinearly with the increase of recycled aggregate content; on the contrary, the addition of hybrid fiber improved the mechanical properties of SPRAC. The study in this paper provides a new method to characterize the damage-fracture mechanism of SPRAC under bending loads quantitatively. It provides a reference for the engineering application of SPRAC. [ABSTRACT FROM AUTHOR]

• The ASABH is proposed to attenuate AE reflection waves at the boundary. • The influence of geometric parameters of the ASABH have been revealed. • Compared to ABH, the ASABH has higher security and better adaptability. • The ASABH has a good effect on reducing the AE boundary reflection. Acoustic emission (AE) technology plays a crucial role in dynamic nondestructive testing. To investigate material properties, friction characteristics, damage features, and acoustic source localization, AE tests are commonly conducted on metal or composite plates. However, the reflection of AE waves at the boundary often generates strong interference, significantly impacting AE test results. In response to this challenge, this paper introduces an innovative solution: an additional Spiral Acoustic Black Hole (ASABH) affixed to the test plate's boundary. The ASABH is designed to mitigate the reflection of AE signals, enhancing the signal-to-noise ratio collected by the sensor. The study begins by establishing a finite element model of the ASABH to validate its efficacy in reducing boundary reflection waves. Subsequently, the paper explores the impact of structural geometric parameters—such as length, residual thickness, power exponent, pitch, and extended length—on the reduction effect. The investigation also delves into the variation of attenuation degree when connecting the ASABH to plates with different relative thickness, relative widths, and materials. Finally, the effectiveness of the ASABH in attenuating structural boundary reflection waves is verified through pencil-lead breaking tests conducted on both metal and composite plates. Results indicate that the proposed ASABH effectively mitigates the reflection of AE waves at the structural boundary, demonstrating adaptability and providing valuable insights for ASABH design. [ABSTRACT FROM AUTHOR]

The wood industry demands advanced methods for material classification and workpiece characteristic modelling to enhance process monitoring and adaptive process control. This paper presents a sensor fusion approach that integrates data from acoustic emissions, airborne sound, and power consumption during the milling of solid wood and wood-based composites. The aims are to achieve accurate material classification and to model workpiece characteristics such as surface roughness or density. A design matrix was generated by extracting relevant features from the multimodal signals to serve as an input for the classification and regression algorithms. The tested classification approaches to differentiate between workpiece type demonstrated high precision with an average validation accuracy of 92.16 %. Regression models for predicting the surface roughness showed R 2 values between 0.79 and 0.97. The density could be predicted with R2 values between 0.84 and 0.98. As a conclusion, workpiece types could be classified and important workpiece properties during machining, such as surface roughness and density, could be well described by using information from multiple sensors during machining. [ABSTRACT FROM AUTHOR]

• This paper realized the damage characterization of CFRP/steel double-lap bonded joints based on AE and DIC. • This paper achieved the damage pattern identification of joints based on the decision tree algorithm. • This paper obtained the damage mechanisms of joints under different loading conditions. CFRP/steel joints are commonly used in construction and can cause unpredictable damage when subjected to external loading. However, it is still challenging to characterize the damage evolution behavior of joints under different loads. In this study, acoustic emission (AE) and digital image correlation (DIC) techniques are used to monitor the damaged state of joints, and a decision tree (DT) algorithm was proposed. From the monitoring results of AE and DIC, it can be found that the damage process of the joint is divided into three stages and is mainly accompanied by four damage modes, namely adhesive failure, cohesive failure, skin failure, and steel deformation. In addition, it also reveals that the AE signal is more sensitive to the early damage of the joint, while the DIC is more sensitive to the late damage of the joint. The identification results of the DT algorithm show that the main damage mechanisms of the joints under the tensile loading conditions are adhesive failure and cohesive failure, while the primary damage mechanism under the bending loading conditions is adhesive failure. The combination of these two techniques successfully enables the damage characterization of joints and provides a framework for analyzing the damage mechanisms of joints. [ABSTRACT FROM AUTHOR]

• This paper is focused on the damage assessment of concrete via acoustic emission and mesoscopic damage constitutive model. • The spatial distribution of AE events resembles the failure mode of concrete under uniaxial loading. • This paper related the theoretical mesoscopic damage with experimental macroscopic damage, which revealed that the macroscopic damage of concrete stemmed from mesoscopic fracture. • The AE energy was related both to the energy of fractured micro-elements and its derivative in the MDC model. This paper experimentally investigated the acoustic emission (AE) behavior of concrete specimens. By using the MTS810 servo hydraulic testing system and the multi-channel AE system, a series of specimens graded C40, C50, and C60 were loaded under uniaxial compression. The spatial distribution of the AE events, AE events rate, and AE energy rate were recorded. Additionally, a theoretical mesoscopic damage constitutive (MDC) model, which defines the theoretical mesoscopic damage variable as the ratio of the fractured micro-elements to the total micro-elements, was introduced. The results indicated that the spatial distribution of AE events resembled the shape of failure modes. Moreover, the theoretical mesoscopic damage calculated by the MDC model matched well with the observed experimental damage, represented by the AE events. This association not only related the theoretical mesoscopic damage with experimental macroscopic damage, but also revealed that the macroscopic damage of concrete stemmed from mesoscopic fracture. Additionally, the AE energy was related both to the energy of fractured micro-elements and its derivative in the MDC model. [ABSTRACT FROM AUTHOR]

This paper presents an experimental study of the seismic performance of austenitic stainless steel full-scale frames using the pseudo-static test method. The bottom single-span, two-storey substructure of the designed prototype frame was chosen as the test frame. Two full-scale frames were tested, one with a bolt-welded joint and the other with an extended end-plate joint. This paper is the first of two accompanying papers to this experimental study and focuses on the specimen design, testing details and global response of the stainless steel frame under cyclic loading. The test results were utilized to analyse the global response of the frames, encompassing failure mode, bearing capacity, deformation capacity, energy dissipation capacity, the overstrength factor, ductility factor and seismic response modification factor. The experimental findings suggest that the stainless steel frames with two joint types demonstrate consistent ability to dissipate energy during cyclic loading. The structure also performs well in terms of deformation, with uniform inter-storey deformation and no soft-storey detected. The maximum storey drift ratio of the frame is 7%. Prior to reaching a storey drift ratio of 2%, the frames with both joint types exhibit similar cumulative plastic deformation, stiffness degradation, and cumulative energy dissipation. • Two stainless steel full-scale frames were tested under two loading protocols. • Global seismic response of the tested frames was analyzed. • Acoustic emission monitoring technique was attempted for overall damage detection. • Overstrength, ductility and seismic response modification factors were calculated. [ABSTRACT FROM AUTHOR]

In this paper, triaxial loading and unloading tests under different conditions were carried out to explore the deformation and failure characteristics of hard rock marble, and the acoustic emission information of the test process was monitored synchronously to obtain the acoustic emission distribution characteristics. The test results show that: (1) when the confining pressure unloading rate is low, the rock yielding is more obvious, the damage peak is higher, and the Poisson effect is more obvious under loading and unloading, while when the unloading rate is high, it shows multi-stage damage; (2) there is a linear relationship between strain deviatoric stress flexibility and unloading rate, as the unloading rate accelerates, the circumferential and volumetric flexibility increases and the axial flexibility decreases; (3) the lower the unloading rate, the higher the confining pressure, and the main shear surface of the rock gathers a large number of tensile microcracks to form a shear zone, while the higher the unloading rate, the lower the confining pressure, and the main shear surface is thoroughly penetrated and ruptured; (4) acoustic emission can characterize the damage degree of marble in the process of loading and unloading, when the confining pressure is low, acoustic emission at the peak damage point appears sharp phenomenon, the overall damage increases with the accelerated rate of unloading, when the confining pressure is high, acoustic emission grows progressively, the overall damage decreases with the accelerated rate of unloading, the overall damage of the rock will appear " pre-peak to post-peak " hysteresis effect. [ABSTRACT FROM AUTHOR]

The oscillating-water-column (OWC) system is one of the most developed wave energy conversion technologies, and several prototypes have been deployed and tested on the sea. Noise emission is essential to this technology's long-term environmental impact assessment. The power take-off system of an OWC comprises a self-rectifying air turbine that directly drives an electrical generator. The paper compares the noise emission of a biradial turbine with that of a Wells turbine. The noise emission of the biradial turbine was measured at the Instituto Superior Técnico variable-flow test rig, while the Wells turbine data were collected in the literature. Acoustic measurement procedures followed the guidelines of the ISO 3746 Standard. A definition of specific noise level is used to compare the noise emission from geometrically similar air turbines or other air turbines performing the same duty. The results show that the noise levels of the biradial turbine are significantly lower than those of the Wells turbine at off-design conditions for the same pneumatic power. • Methodology for measuring noise emission from air turbines. • Experimental characterisation of the acoustic emission of a biradial turbine. • Use of a specific noise level to compare air turbines. • Comparison of noise emission of a biradial turbine with a Wells turbine. • Wells turbines are significantly noisier than biradial turbines at off-design conditions. [ABSTRACT FROM AUTHOR]

Rain erosion is a potential hazard for supersonic vehicles, with severe damage to materials that may be impacted by raindrops. In this paper, a series of impact tests of 413–572 m/s are carried out on a 3 mm-thick 2D C/SiC composite specimen using a single impact waterjet apparatus. The typical morphology of C/SiC specimen is obtained by single jet impact test. Under the multi-drop impact, the stress wave interaction is enhanced, and the internal damage of the specimen is severe, showing a funnel-shaped damage. Moreover, the C/SiC specimen is penetrated after 5 drops of impact. Quasi-static tensile tests were employed to quantify the post-impact strength of the specimen, during which the digital image correlation (DIC) method was used to obtain the strain value, at the same time acoustic emission (AE) signal was detected and processed by the K-Means to reveal the damage evolution. [ABSTRACT FROM AUTHOR]

Due to the limitation of the current preparation technology, there would inevitably be pores in the CMC structure. In this paper, the influence of pores on the failure behavior of CMC structure was studied by simulation and experiment. Based on the common phenomenon of irregular pores in CMC structure, two finite element models of CMC dovetail with and without pores were established as a comparison. The crack propagation process and the failure load of the dovetail model in contact with the mortise were predicted by the progressive damage method using the improved maximum strain criterion considering the damage coupling in different directions. On this basis, failure load and damage analysis of CMC dovetail were investigated using a unidirectional tensile test according to the digital image correlation method, acoustic emission, scanning electron microscope, and X-ray computed tomography, which were in good agreement with the predicted results. Both the experimental results and the comparison of the simulation results of the two models proved that the distribution of pores induced the formation and propagation of cracks, which led to the delamination in the middle of the CMC dovetail, ultimately significantly reducing the bearing capacity of the CMC dovetail. [ABSTRACT FROM AUTHOR]

Fiber-optic hydrophones based on optical fiber sensing and communication technology have developed rapidly in recent years. With the advantages of high sensitivity, small size, and large dynamic range, they are easy to detect underwater acoustic signals, showing great potential in the field of marine ecological protection. Researchers can monitor the marine ecological environment by recognizing underwater optical fiber sensing signals collected by fiber-optic hydrophones in real-time. Deep learning models can achieve high recognition accuracy, but they usually have large amounts of parameters that makes them difficult to be deployed in mobile terminals of marine survey ships. To solve the key problem, this paper discussed the design of the Deep Light-Weight Attention Residual Network (DLA-ResNet). It introduces the depth-wise separable convolution (DSC) and the convolutional block attention module (CBAM) into ResNet18 to make its performance better. ResNet18 is a two-dimensional convolutional network (CNN) model applying residual blocks. Experiments verify that the accuracy of DLA-ResNet improved from ResNet18 is increased by about 2.04% and its size is reduced by 85.67%. The proposed scheme in this paper realizes an average recognition rate of 96.50% for eight types of underwater optical fiber sensing signals in the application of marine ecological environment monitoring. Moreover, its model size is only 6.12 MB and it only takes 27.90 ms, which is available to meet the needs of reliability and effectiveness. [ABSTRACT FROM AUTHOR]

In this paper, acoustic emission (AE) monitoring technique was used to study the mechanical lifting mechanism of polyacrylonitrile (PAN) fibers on the CPB material under uniaxial compression and the specific energy characteristics and AE response characteristics and damage precursors during the damage of fiber tailings cemented backfill specimens with different ash-sand ratios. In this experiment, cemented paste backfill (CPB) and polyacrylonitrile fiber tailings cemented backfill (P-FTCB) specimens with 68% concentration and 1:6, 1:8, 1:10 and 1:12 ash-sand ratios were fabricated using PAN fibers. The study shows that the fracture arresting effect and bridging effect of PAN fibers inhibited the expansion of fracture development inside the CPB, thus enhancing the compressive strength and post-peak damage toughness of the CPB, while the fracture arresting effect and bridging effect of fibers depended on the fiber pull-out process, and the fiber pull-out process is divided into three stages: micro-slip stage, slip stage and detachment stage; the higher the ratio of ash-sand in P-FTCB specimens, the stronger the cementing force, the higher the energy required for material destruction, the greater the elastic strain energy that can be stored, and the greater the energy dissipated per unit volume; CPB specimens without fiber incorporation show a decreasing trend in AE parameters before damage; while P-FTCB specimens show a surge in AE parameters after the specimens reached their stress peaks under the effect of fiber fracture arrest; in addition, there is a significant relationship between the ratio of ash-sand of the filling material and its AE parameters: the AE energy parameters of CPB specimens and P-FTCB specimens increas as the ratio of ash-sand decreased. The results of the study can provide a reference basis for the use of P-FTCB materials in mines, and provide theoretical support for promoting the recycling of mine solid waste. [ABSTRACT FROM AUTHOR]

In the past decade, a lot of research has been conducted on the potential of carbon nanostructured materials to emit sound via thermoacoustics through both simulations and experiments. However, experimental validation of simulations for three-dimensional graphene (3D-C), which has a complicated 3D structure, has yet to be achieved. In this paper, 3D-C is synthesized via thermal chemical vapor deposition and its microstructure and quality tested using Scanning Electron Microscopy and Raman spectroscopy respectively. Then, a two temperature model is used to predict the effects of numerous parameters: frequency, input power, sample size, connection area, connection path, pores per inch, thickness, compression as well as the addition of a backing on the acoustic performance and temperature of the sample. The experimental results presented in this paper validate the predictions of the adopted two temperature model. The efficiency of 3D-C is then compared with results presented in other studies to understand how the presented 3D-C fared against ones from the literature as well as other carbon nanostructured materials. Image 1 [ABSTRACT FROM AUTHOR]

Ultrasonic assisted liquid phase exfoliation (ULPE) is a promising method for the large scale production of 2D materials. Currently, toxic solvents such as N-Methyl-2-pyrrolidone (NMP) are commonly used for the production of graphene. In this paper four solvents; three green solvents (water, ethanol and water/ethanol) plus NMP for comparison, were sonicated and examined in terms of their bubble dynamics and acoustic emissions. Advanced fundamental analysis was conducted using high-speed imaging synchronised with acoustic pressure measurements complemented by shadowgraphic photography of the emitted shockwaves, in order to determine a suitable eco-friendly solvent medium from a cavitation bubbles dynamics perspective. Thereafter, ULPE of graphite in the optimum solvent took place for 2 h under controlled ultrasonication parameters. The produced graphene samples were characterised by employing a series of techniques consisting of Ultraviolet–visible (UV–Vis) and Raman spectroscopy as well as transmission electron microscopy (TEM). A mixture of deionised water and ethanol was shown to produce a yield twice that of pure water, comprising of high quality few layer graphene (3–5 Ls) with an average area of ∼1.15 (μm)2 and stability of ∼78% for the duration of six months. This combination is a promising eco-friendly substitute for future commercial manufacturing of graphene. [Display omitted] [ABSTRACT FROM AUTHOR]

In this paper, nanoparticles obtained by Sol-gel method have been incorporated as a filler in glass fiber/polyester composite in order to improve the mechanical properties of the resulting material. This work covered on the characterization and the study of the polymer matrix with 5 wt.%nano TiO 2 , 5 wt.%nano Al 2 O 3 , 5 wt.%nano SiO 2.The results obtained revealed that sol-gel powders with a spherical morphology have excellent thermal stability. Acoustic emission analysis was used to investigate the microscopic damage mechanisms and progression in glass fiber reinforced nanocomposites. Thus, acoustic emission from four modes of approval has been identified: matrix cracking, matrix/fiber decohesion, delamination and fiber breakage. This study shows the increase of mechanical performance and the decrease of damage modes of @Polyester. From the SEM images, the good dispersion of nanofillers, absence of agglomerates, the good affinity with the improving of the interface compatibility were presented. [ABSTRACT FROM AUTHOR]

• Interaction between microcracking and the macrocrack opening in concrete is studied using DIC and AE techniques. • The study reveals a transient behaviour of macrocrack opening as microcracks are formed in the surrounding. • A fracture mechanics based approach is presented to consider the effects of micro-macro crack interaction. • An improved softening model is presented and local fracture energy is determined. During the fracture of concrete the formation of microcracks is a continuous process where new microcracks are formed in the vicinity of the macrocrack. As the fracture grows, these microcracks interact with the macrocrack and disrupt its smooth opening. In fracture mechanics based approaches; a smooth stress-crack opening softening behaviour is generally used to describe the local fracture process, where the effect of micro-macro crack interactions is lacking. This paper presents firstly an experimental study on the interaction between microcracking and the macrocrack opening (COD) in concrete using digital image correlation and acoustic emission techniques. The study reveals a transient behaviour of macrocrack opening as microcracks are formed in the surrounding. Based on the experimental results, the paper presents a new approach based on fracture mechanics to consider the effects of micro-macro crack interaction on the stress-crack opening softening behaviour. Local fracture energy is determined using the new softening model with micro-macro crack interaction for different geometrically similar sizes of the beams and at different locations on the crack profile. [ABSTRACT FROM AUTHOR]

The assessment of the location and the extension of cracks in roads is important for determining the potential level of deterioration in the road overall and in the infrastructure buried beneath it. Damage in a pavement structure is usually initiated in the tarmac layers, making Rayleigh waves ideally suited for the detection of shallow surface defects. In this work, the differences between the spectral images obtained with the Multichannel Analysis of Surface Waves (MASW) and the Multiple Impact of Surface Waves (MISW) are suggested for the first time to detect, locate and evaluate surface-breaking cracks in dispersive material, i.e. roads. Assessment of crack in roads is usually performed assuming constant velocity and non-dispersive behaviour of the material tested, limiting this approach to the very shallow layer of the road. The road is here holistically treated as a dispersive medium, supporting a paradigm-shifting approach to in situ crack evaluation. It is shown that surface-breaking cracks influence the content of the spectral images obtained with these two acoustic imaging techniques. Their differences are used for the first time for the in situ evaluation of the presence, the location and, in some cases, the extension of vertical cracks in roads. The study is conducted through numerical simulations, alongside experimental investigations. The paper describes two cases for which the cracking is internal and then external to the deployment of sensors. The method proposed in this paper proved to be successful for the in situ evaluation of cracks in asphalt, tackling the heterogeneities and dispersive behaviour of the material tested. [ABSTRACT FROM AUTHOR]

This paper aimed to reveal the damage mechanisms of sapphire by single grit scratch tests on C-plane, which would establish the basis of damage-free machining. The deformation and damage evolution experienced five stages with increasing cutting depth resulting from the combined effect of principle stresses and activated slip/twining systems. It was proved that subsurface and surface damages occur in ductile removal regime of sapphire, which were dominantly induced by high residual stress and the rhombohedral twinning on (10 1 ‾ 2) and ( 1 ‾ 102) , respectively. Three critical cutting depths for suppressing subsurface damage, surface damage and surface roughness were determined, respectively. These conclusions were also supported by the acoustic emission (AE) features both in time and frequency domains during scratching. This paper also undertook the theoretical study. An improved elastic stress field model has been established to understand the deformation and damage evolution in relation to cutting depth. [ABSTRACT FROM AUTHOR]

• Framework for cutting parameter optimization in turning nickel base super alloy is developed. • A machine vision and AE system is implemented for measuring response parameters to optimize the cutting process. • The proposed method could render better results at the arrived optimal cutting conditions. To select the optimal conditions of cutting which potentially characterizes status of tool wear, acoustic emission (AE) and machine vision signals have been used and the same is presented in this paper. Nimonic 75 is turned using carbide insert with titanium coating and Taguchi's L 27 array has been adopted for parametric optimization. Speed of spindle, feed and cutting depth being varied during experimentation and the tabulated data in terms of AE and machine vision signals have been analyzed further. The parameters such as wear area, perimeter, AE RMS and AE COUNT have been found responsive to tool wear and their relationship follows the time wear trend. Depth of cut is optimally constant in terms of the considered parameters whereas slight inexplicable variation in speed and feed has been observed and this inexplicit variation may be accounted for under noise, distortion and inconsistent illumination. At the obtained optimal cutting conditions machining was repeated and the results ascertained the correctness of the procedure adopted. In processing Nimonic75 using coated carbide insert, the results presented in this paper in terms of optimal parameters, could be used in the manufacturing sector that potentially enhances quality. Of all the non-traditional measuring techniques, machine vision and AE have proved better in measuring response parameters to optimize machining. [ABSTRACT FROM AUTHOR]

Rapid urbanizations impose increasing challenges on safety decompositions of those buildings that reached service life, so there is an urgent call for eco-friendly demolition methods. As a green demolition method, the technique of soundless cracking demolition agents (SCDAs) can effectively eliminate dust and noise pollution commonly encountered in conventional methods, and thus attract rising attention in light of increasing concerns for sustainable and low-carbon developments. Herein, this paper provides a state-of-art review of SCDAs and associated applications. SCDA, a powdery material, mainly consists of quicklime (CaO), which tends to expand significantly when mixed with water. The expansion properties of SCDAs are susceptible to internal and external factors, such as compositions, ambient temperature, mixing water temperature, and water/cement (W/C) ratio, restraint conditions, among others. Therefore, substantial efforts have been made to improve the expansion performance of SCDAs by regulating the abovementioned factors. The resulting expansion force from SCDA expansion can effectively crack brittle materials, e.g., concrete and rocks, the cracking process of which can be measured using strain gauges and Acoustic Emission (AE). More recently, digital image correlation and computed tomography have been employed to monitor the SCDA-induced cracking process, and the implementation of those new techniques promotes the observations of crack developments and underlying mechanisms. To gain a cost-effective application of SCDAs, extensive efforts have been undertaken to optimize the design in hole parameters. Accordingly, several empirical equations have been proposed for determinations of optimal hole parameters, but the application of the equations is restricted to particular conditions where they are proposed. Despite the successful usage of the SCDA technique in demolitions of construction structures, mining, unconventional gas and oil recovery, some limitations, namely hard rock fragmentation, precise numerical works and blowout, still need to be addressed for further applications. Overall, this paper gives a brief review of SCDAs, covering scopes of compositions, expansion properties, applications, inadequacies and prospects, deepening our understanding of SCDAs, and providing recommendations for future research priorities. • Factors influencing the expansion characteristics of SCDAs are analyzed. • Some new technologies for observing the process of crack development are presented. • The optimum usage of SCDA related to the hole design parameters is summarized. • Further work in the research and application of SCDA is proposed. [ABSTRACT FROM AUTHOR]

• The current similar simulation materials are featured with the contradiction between low strength and high rockburst tendency, thus being unable to simultaneously realize the qualitative rockburst of small size specimen and the impact damage restoration of large size model. Developed a new similar simulation material for coal with both low strength and strong rockburst tendency in this paper. • In this paper, we propose for the first time to develop similar simulation materials using water glass as binder, sodium silicofluoride as curing agent and talcum powder as aggregate. And the optimal doping of the new similar simulation material was obtained by orthogonal experiment and multiple linear regression method. • It was confirmed that the modulus index is a simplified evaluation index that can comprehensively evaluate rockburst. And according to the similarity criterion, the rockburst evaluation criteria of modulus index for similar simulation materials are obtained by deriving theoretical equations. • Micro-macroscopic experiments were utilized to monitor in real time the energy-temperature-strength synergistic change characteristics and similarities between this material and the coal with a strong RT. The feasibility of the material was confirmed in terms of physical parameters, degree of rockburst and homologous energy and temperature characteristics. • This study also revealed the multi-parameter precursor characteristics of rockburst damage in the specimen, which can lay a foundation for the prevention and study of impact ground pressure disaster. The current similar simulation materials (SSM) are featured with the contradiction between low strength and high rockburst tendency (RT), thus being unable to simultaneously realize the qualitative rockburst of small size specimen and the impact damage restoration of large size model. In this case, this study developed a new SSM of low strength and high RT by using water glass (WG) as cement, talcum powder (TP) as aggregate and adding curing agent sodium silicofluoride (SSF). Under the requirements of initial set volume shrinkage rate (IVSR), long-term volume decay rate (LVDR), uniaxial compressive strength (UCS) and modulus index (MI), the optimal ratios of SSF and TP were obtained 20% and 70% by orthogonal experiment and multiple linear regression method, respectively. Micro-macroscopic experiments such as uniaxial compression, scanning electron microscope (SEM), acoustic emission (AE) and Infrared thermal imager were utilized to monitor in real time the energy-temperature-strength synergistic change characteristics and similarities between this material and the coal with a strong RT. The experimental results show that: the UCS value of this material is 6.11 MPa and its MI is 11.57, which meets the requirements for low strength and high RT. Meanwhile it satisfies a certain similar proportionality between its physical parameters and those of coal. In the whole process of uniaxial compression, there are energy and temperature homologous changes in the characteristics of consistency, and both materials conform to the stress–strain phase law. The infrared radiation temperature displays a trend of "slowly decreasing-gradually warming-continuously cooling-suddenly warming-sharply cooling". The AE energy count rate shows a trend of "calm transition and sudden increase before and after the stress peak". All are characterized by strong RT. There is still some difference between the two specimens during energy and temperature changes, due to their different molding characteristics and load-bearing capacity. The feasibility of the material was confirmed in terms of physical parameters, degree of rockburst and homologous energy and temperature characteristics. Meanwhile, this study revealed the multi-parameter precursor characteristics of rockburst damage in the specimen, which can lay a foundation for the prevention and study of impact ground pressure disaster. [ABSTRACT FROM AUTHOR]

• The proposed method compares acoustic emission (AE) events and local crack kinematics. • The comparison is performed along cracks in shear test of full-scale concrete beams. • The number of AE events is related to the complete crack kinematics history. • Two distinctive types of relationships are found in tensile and compressive zones in the beams. • The contact area between two crack faces could essentially explain the relationships. Monitoring or identifying structural cracks is crucial for assessing the health of existing concrete structures. Key information about structural cracking encompasses the location of the crack and its kinematics, which include movements perpendicular and parallel to the crack face. Acoustic emission (AE) is a sensitive technique for detecting the location of internal concrete cracking. However, the state-of-the-art AE monitoring methods offer limited information on crack kinematics, restricting the use of AE in crack assessment. To bridge this gap, this paper uses a recently proposed AE data analysis method that quantifies the spatial distribution of AE events along a crack probabilistically. This method uses a parameter referred to as the probability density of AE events (pdAE). By combining pdAE and crack kinematics measured by digital image correlation in a series of real-scale concrete beam tests, this paper investigates the relationship between AE events and crack kinematics. The analysed cracks are generated by a combination of bending moment and shear forces, as commonly observed in real structural concrete members. We find that the amount of AE events is not only related to crack width (the crack movement perpendicular to the crack face), as most literature suggests, but also to the complete crack kinematics throughout the loading history of the member. We then provide a physical explanation for the observed relationships between concrete crack kinematics and the quantity of AE events. [ABSTRACT FROM AUTHOR]

• Multi-sensor fusing and soft computing in CO 2 leakage measurement. • Integration of BP-ANN, RF, and LS-SVM models. • Feature extraction and analysis of AE and temperature signals. • Effect of impurity gas on CO 2 leakage. CO 2 leakage from carbon capture and storage (CCS) networks may lead to ecological hazards, bodily injury and economic losses. In addition, captured CO 2 often contains impurities which affect the leakage behavior of CO 2. This paper presents a method for continuous and quantitative measurements of CO 2 leakage flowrate and the volume fraction of impurities by combining data-driven models with acoustic emission (AE) and temperature sensors. Three data-driven models based on artificial neural network (ANN), random forest (RF), and least squares support vector machine (LS-SVM) algorithms are established. The outputs from the three data-driven models are then integrated to give improved results. Experimental work was conducted on a purpose-built CO 2 leakage test rig under a range of conditions. N 2 was injected to the CO 2 gas stream as an impurity medium. Results show that the integrated model yields a relative error within ±4.0 % for leakage flowrate and ±3.4 % for volume fraction of N 2. [ABSTRACT FROM AUTHOR]

Fiber-reinforced plastic sandwich structures (FRPSSs) are increasingly used in marine applications thanks to their high levels of stiffness, lightweight, buoyancy and damage resistance to penetration and impacts. This paper investigates the effect of exposure to seawater conditions on mechanical behavior of FRPSSs with various core configurations loaded with indenters with different geometries. A new in-situ acoustic emission (AE) methodology is applied to monitor the moisture evolution process, while X-ray micro-computed tomography validated its influence on out-of-plane failure modes observed in quasi-static indentation experiments. Results indicate that AE velocity can effectively monitor the moisture uptake, serving as an in situ structural health monitoring approach. It was also revealed that the core configuration had a limited effect on moisture ingress. Samples exposed to sharp indentation exhibited the greatest decrease in load-bearing capacity (in excess of 50% in some cases) while that for blunt indentation was the lowest. This can be explained by reduced penetration forces resulting from matrix plasticization and degraded matrix/fiber interface, exacerbated by a smaller contact area. Also, early damage initiation and intensified damage progression were observed for sharp indenters after the seawater exposure. The core of FRPSSs significantly influenced localized damage in samples indented with conical and flat indenters, unlike those subjected to hemispherical ones. The seawater exposure adversely affected the energy absorption and penetration performance, enhancing macroscale damage mechanisms. These findings offer valuable insights for design and optimization of FRPSSs for marine applications. [ABSTRACT FROM AUTHOR]

• AE detection technique was introduced to explore the failure behavior of LIBs. • The effects of indenter diameter, SOC and capacity of LIB on failure process and failure mechanism were analyzed. • Failure modes inside the battery were identified according to the microscopic cross-sections and AE signals. • The compression process of the battery was divided into five stages based on force and acoustic responses. To understand the crashworthiness safety of lithium-ion battery (LIB) comprehensively, acoustic emission (AE) testing technology is introduced to explore the mechanical response and failure mechanism. In this paper, the compression process and failure behavior of 18650 LIBs under plane compression, local indentation and three-point bending are experimentally investigated. The effects of indenter diameter, state of charge (SOC) and capacity of the battery on the force-voltage-temperature responses are discussed in detail. The relation between the failure behavior and acoustic response of LIB is studied in combination with AE detection technique. The results show that the deformation of the battery can be divided into three stages before the failure, including the stress on the shell, compression on the internal gap and electrolyte, and stress on the whole. The failure inside the battery is caused by fold, shear fracture, local buckling and tensile break under different loading forms. The smaller the diameter of the indenter is, the lower bearing capacity at the point of failure is. High-SOC batteries experience higher forces and displacements at the failure point. High-capacity batteries have poor bearing capacity and are more prone to thermal runaway. AE signal can be detected at special points during the compression. Combined with the acoustic response of the battery, the whole deformation process is divided into five stages. The researches will provide a guidance for the failure detection and safety evaluation of LIBs. [ABSTRACT FROM AUTHOR]

The pressure stimulated current (PSC) signal emitted during the deformation and fracture processes of coal and rock materials holds significant importance for monitoring dynamic disasters in coal mines. However, the spatial response characteristics remain inadequately explored, posing significant challenges to the identification of risk-prone areas for underground dynamic disasters. To study the temporal and spatial response characteristics of PSC signal, the PSC response experiment in the failure process of raw coal under load was carried out, PSC signals from various spatial positions of coal were collected throughout the loading process. The results show that the sudden increase of axial PSC and the sudden decrease of transverse PSC appear with the sudden increase of acoustic emission (AE) hit rates, which is the main characteristic of the aggravation of coal internal fracture degree. The PSCs are closely related to the damage characteristics of the sample in terms of its corresponding position and drop time, which can better reflect the fracture concentration location of the coal sample. Building upon this foundation, the paper explained the internal factors contributing to variations in PSC spatial response characteristics of coal samples during load failure and emphasizes the inhibitory effect of crack development on PSC changes. • The variation trend of PSC signal corresponds well with loading process of coal. • There are obvious differences between axial and lateral PSCs. • The position of the mutation PSC corresponds to the damaged area of the coal. • The effect of coal crack on PSC variation is analyzed. [ABSTRACT FROM AUTHOR]

In this paper, the ductile fracture prediction method based on micromechanism of low yield point steel LY225 under cyclic loading is studied based on acoustic emission (AE) entropy. Firstly, the parameters of the cyclic void growth model (CVGM) were calibrated by a series of repeated loading tests of the circumferentially notched specimens, and then the quantitative relationship model between the cumulative AE entropy and the cyclic void growth index (CVGI) of LY225 under low-cycle fatigue load was established through reciprocating loading tests, real-time acoustic emission monitoring and finite element analysis of variable cross-section flat specimens. The cumulative AE entropy was used as the ductile fracture evaluation index to realize the prediction of ductile fracture under low-cycle fatigue load. Different from the monotonic tensile loading situation, when the material undergoes repeated loading, it will accumulate AE entropy according to the changes in VGI during the tensile and compressive cycles. Based on this, the quantitative relationship model between the cumulative AE entropy under cyclic loading and the cyclic void growth index CVGI has been revised. Finally, the micro element method was used to predict the cumulative AE entropy curve of the plastic zone of the variable cross-section flat plate specimen under repeated loading. The predicted curve was in good agreement with the experimental results, verifying the applicability and accuracy of the modified bilinear quantitative relationship model under low cycle fatigue loading. [Display omitted] • CVGM fracture parameters of LY225 steel are calibrated. • A quantitative damage evaluation method of LY225 steel under cyclic load based on AE monitoring technology is proposed. • A modified bilinear model between cumulative AE entropy and cyclic void growth index CVGI is established. • The proposed model can be used in quantitative damage evaluation and ductile fracture prediction. • The effectiveness of the model in more complex stress and strain state is verified by a series of tests. [ABSTRACT FROM AUTHOR]

• The fractal dimension of rock crushing particle size was studied by fractal theory. • The response characteristics of time–frequency domain parameters in rock failure process are analyzed by AE. • AE multi-parameters are calculated by critical slowing down theory to predict rock failure. The joint surfaces and size affect the mechanical behavior and failure precursors of shale. Therefore, this paper studies the mechanical behavior, the response characteristics of acoustic emission (AE) and critical slowing down (CSD) characteristics of AE for shale with different joint surfaces and size. The results show that with an increase in the number of joint surfaces and the size of the sample, the crack initiation stress, uniaxial compressive strength (UCS), peak strain, and fractal dimension decrease. During the plastic stage, the occurrence of a sharp rise in AE ringing count, RA, a low-frequency, high-amplitude AE signal, and a rapid drop in AF can be characteristics of impending sample failure. Variance and autocorrelation coefficients can be used to characterize the CSD phenomenon. The optimal window length and lag step are determined to be 400 and 100, respectively. The CSD characteristics of the autocorrelation coefficient and the variance of multi-AE parameters are obtained. The variance-based early warning time provides short-term early warning, while the autocorrelation coefficient-based early warning time provides early warning. The research results can provide theoretical references for the mechanical design and failure prediction of underground rock engineering. [ABSTRACT FROM AUTHOR]

[Display omitted] • An experimental setup was built up to collect the VILAES. • The wavelet scattering coefficients are selected as the features of the VILAES. • Relationship between scattering coefficients and leakage rate is determined. • Optimal wavelet scattering coefficients are extracted automatically. • A new multi-variable classification model for small leakage and small sample sizes. In order to achieve acoustic emission detection in valve internal leakage, it is essential to extract features, and establish an accurate mathematical model. Current valve internal leakage acoustic emission signal (VILAES) classification models mostly rely on human experience for selecting features, resulting in low accuracy for small leakage conditions. This paper combines the wavelet scattering transform (WST), Relief-F algorithm and AdaBoost.M1 algorithm, and proposes to use the optimal wavelet scattering coefficients as features to establish the VILAES classification model accurately for small leakage. Firstly, the first three order wavelet scattering coefficients of the VILAES are automatically extracted using WST and are transformed into one-dimensional features. Secondly, the Relief-F algorithm is employed to select the optimal feature subset. Finally, the optimal wavelet scattering coefficients and pressures are used as inputs to establish a classification model for VILAES and achieve an accuracy over 96.80% for small leakage. [ABSTRACT FROM AUTHOR]

Data-driven machine-learning models offer considerable promise for acoustic source localization. However, many existing models rely on training data that correlates time-of-flight (TOF) measurements with source locations, yet they struggle to handle the complexities arising from nonlinear wave propagation in materials with varying properties. Furthermore, these models overlook the noise and uncertainties inherent in real-world experiments when predicting outputs. This paper aims to bridge a gap in impact localization for such structures, particularly focusing on scenarios involving noisy field measurements. This study proposes a framework based on probabilistic machine learning to identify impact locations, utilizing wavelet scattering transform (WST) and Multi-Output Gaussian Process Regression (moGPR). WST extracts informative features from Lamb waves, capturing relevant signatures for training the probabilistic machine learning model, while moGPR estimates correlated impact location coordinates (x, y) while accounting for inherent uncertainties in the data. To assess the proposed method's performance in handling measurement uncertainties, an experiment was conducted using a CFRP composite panel instrumented with a sparse array of piezoelectric transducers. The results demonstrate that the probabilistic framework effectively addresses measurement uncertainties, enabling reliable source location estimation with confidence intervals and providing valuable insights for decision-making. • The research proposes a probabilistic ML framework for impact localization. • Methodology involves WST and moGPR for impact localization with confidence interval. • Results demonstrate improved accuracy of WST over TOF-based approaches • Experimental validation demonstrates its ability to handle measurement uncertainties [ABSTRACT FROM AUTHOR]

This paper reports an experimental investigation of a phase-gradient acoustic metasurface for duct acoustic applications, to evaluate the potential for attenuating acoustic modes and to understand the associated mechanism. The metasurface is a composite configuration where melamine foam as the main part includes a tunable wall. Given a target sound-absorbing frequency, a deeply sub-wavelength metasurface with a thickness-to-wavelength ratio of 1 / 6. 86 is achieved. The unique way of assembling annular metasurfaces offers the possibility of fabricating three different configurations, which are then tested in a duct acoustic rig with artificially generated modes. The performance is assessed through in-duct modal analysis and far-field measurements. The results indicate excellent mode attenuation performance of the designed metasurface at broadband frequencies. The numerical simulation suggests that the mechanism can be related to the conversion from the incident mode to the evanescent waves due to the metasurface. In addition, the effects of the mode suppression are enhanced with the increase of the mode order, which can be attributed to the fact that the performance of the metasurface is influenced by the modal incidence angle. Overall, the present work provides a fascinating noise control method for ducted propulsion systems, and aeroengines in particular. [Display omitted] • Designs of a deeply sub-wavelength metasurface with a thickness-to-wavelength ratio of 1/14.3 is achieved for duct acoustic applications. • A process of fabricating an annular metasurface is demonstrated. • The mode attenuation performance of the metasurface is evaluated under the incidence of controllable acoustic modes at broadband frequencies. • The sound absorption mechanism of the metasurface is revealed through simulations. [ABSTRACT FROM AUTHOR]

• The effects of high temperature and cyclic load on red sandstone were investigated. • The failure process of the specimen was analyzed in depth by AE and DIC technologies. • A crack classification model based on K-medoids and SVM algorithms was proposed. • The failure precursor characteristics were discussed by critical slowing down theory. This paper investigated red sandstone's acoustic emission (AE) and fracture characteristics under high temperature and cyclic load. The specimen's behavior throughout the process from stabilization to failure was systematically analyzed in terms of the distribution of AE activities, rupture scale, crack type, crack evolution, and failure mode. A crack classification model based on K-medoids and support vector machine (SVM) algorithms was proposed, and the optimal dividing line for tensile-shear cracks at different temperatures was determined as AF = 0.335 × R A + 76.890. The specimen's failure precursor information was recognized based on the critical slowing down theory. [ABSTRACT FROM AUTHOR]

With the exploitation of deeper underground resources with harsh working conditions and significant geotechnical issues, it is challenging to quantify the damage evaluation (especially anisotropic damage) of stressed rock materials. The insufficient understanding of anisotropic damage inside rock may result in unexpected hazard potential in rock engineering. However, most of the current acoustic emission (AE) data analysis is limited in the isotropic stage and AE-based damage characterisation has not been well integrated with the continuum damage mechanics. Therefore, by adopting multiple monitoring technologies such as ultrasonic wave velocity measurement, active AE location and passive AE tomography, the paper investigated the anisotropic damage characteristics of Gosford sandstone samples under triaxial compressive tests. Multiple parameters including AE event location, P wave velocity and AE energy were used to correlate microcracking with the internal rock damage during the loading process. The anisotropic damage variable was determined using the heterogeneous P wave velocity field obtained from passive AE tomography, based on both linear and non-linear stress strain relationships. The damage evolution is further investigated following the frameworks of thermodynamics and continuum mechanics. This study casts light on laboratory-scale anisotropic damage identification, which further improves the understanding of anisotropic damage evolution inside rock materials. • Identified anisotropic damage by AE tomography technologies. • Damage variables based on both linear and non-linear stress-strain relationships. • Identify damage evolution on the non-linear model. [ABSTRACT FROM AUTHOR]

The identification and visualization of airfoil noise sources are critical for comprehending the interplay between flow and acoustics, and for understanding the generation and propagation of sound. In this paper, we introduce an innovative method, specifically designed to identify and visualize flow-induced noise sources associated with airfoil noise. This approach employs cross power spectral density analysis to distinctly identify flow-induced noise sources. The data for our study comes from large-eddy simulations of a NACA 0012 airfoil, characterized by a Reynolds number of 4 × 10 5 , a Mach number of 0.058, and an angle of attack of 6.25 ∘. Different cross-spectrum formulations are examined and evaluated. The analysis includes a comparison of the cross-spectrum method's strengths and limitations relative to established data-driven approaches like dynamic mode decomposition (DMD) and spectral proper orthogonal decomposition (SPOD). We find that the cross-spectrum method provides both spectral magnitudes and phase topologies, allowing it to effectively compare sound intensities among various sources at specific frequencies, while retaining high-resolution spatiotemporal coherent flow and acoustic dynamics. One of the notable advantages of the cross-spectrum method over DMD or SPOD modes is its lesser reliance on extensive data manipulation in the form of large-size data matrix, making it a more efficient and user-friendly approach for practitioners, particularly when dealing with complex systems or high-dimensional datasets. This characteristic enhances its practicality and accessibility in the field of flow and acoustic visualization. Finally, the newly developed method is applied to three distinct flow transition scenarios to evaluate its proficiency in distinguishing acoustic generation and propagation mechanisms, depending on the specific transition case. [ABSTRACT FROM AUTHOR]

Investigating the mechanical behavior and damage patterns of ultra-thin-ply composite joints is essential for ensuring their widespread application in the aerospace field. It is currently an advanced method of exploring the damage patterns of composite joint structures via a combination of acoustic emission and machine learning algorithms. However, the existing research lacks the evaluation indexes for the determination of the number of damage categories, and on the other hand, the overlapping area and noise of the monitored damage data cannot be accurately identified. In this paper, load-bearing performance of ultra-thin-ply composite hybrid bonded/bolted interference-fit joints is studied, then the SDI(Structural Damage Index) evaluation index is proposed to quantitatively analyze the number of damage categories of the complex joints, and finally the adaptive optimization algorithm based on the credal partition for the complex joints of composite is studied. The experimental results demonstrate the accuracy and generalization of the SDI formulae, and the introduction of the credal partition that submits data where overlapping regions cannot be accurately identified to ensembles of special single classes (meta-clusters) obtains deeper insights into the damage data and improves identification and isolation of noise. • The mechanical properties of ultra-thin-ply HBBI joints were investigated. • An SDI evaluation index based on damage data is proposed. • SDI provides an analysis of the number of damage categories in joint structures. • Credit partition is introduced to design an adaptive optimization algorithm. • Credit partition provides more deeper insights into damage data. [ABSTRACT FROM AUTHOR]

• The heterogeneous granite model is constructed based on the cohesion model and the random polygon generation and delivery method. • The number of AE events, fracture energy, damage range, and peak strength rise with the offset distance of prefabricated cracks. • The fractal dimension of cracks is positively correlated with the accumulated AE energy. • The occurrence of transgranular and intergranular failure depends on the angle of the main crack and the mineral particles. Granite is a common surrounding rock in tunnels, nuclear waste repositories, and other underground engineering. It is essential to investigate granite's mechanical behavior and fracture mechanism at the mesoscale. In this paper, the three-point bending model considering granite meso -heterogeneity was constructed, and the three-point bending test and acoustic emission (AE) simulation were carried out under different crack sizes and porosities, different prefabricated fracture offset distances, and bedding conditions. The results show that large-size mineral particles and intrinsic fractures mainly determine the sample's crack propagation pattern. As the prefabricated crack's deviation distance increases, the sample's peak load, fracture energy, number of AE events, and internal damage range all gradually rise. The sample's crack propagation path has a distinct step shape due to bedding, and tensile fractures primarily occur in the through-layer crack, whereas shear fractures mainly occur at the bedding plane. The specimen's surface crack's fractal dimension is positively associated with the cumulative acoustic emission energy during the fracture process. The conclusion of the research can offer a theoretical foundation for analyzing the stability of the surrounding rock. [ABSTRACT FROM AUTHOR]

(1) The proposed MFC-PINN model takes the time-difference information and the time–frequency domain information as the multimodal inputs and by fusing the features extracted from the MLP and the CNN and under the constraints of the physics equations, it can achieve high-precision and robust planar localization of the AE source. (2) AE source planar localization experimental bench was constructed, and the datasets were produced by collecting the PLB signals from different locations of aluminum alloy plates, extracting the time-difference parameters and time–frequency domain maps. The complete, incomplete, and noise-containing datasets were produced to simulate the data situation under the actual working conditions, considering the difficulty of data acquisition, plate masking, and environmental noise. (3) The proposed model was evaluated using RMSExy, MEDPExy and probability density analysis. With the complete dataset, the model error is smaller than both TDOA and WER-CNN; with the incomplete dataset as well as SNR=5 dB, the model error is larger than TDOA; however, when the time-difference parameters are greatly affected (SNR=-5 dB), the model is more robust to noise than TDOA. (4) The TotalLoss weighting of 0.5:0.5 is the better choice and outperforms the other four proposed weightings. The results of error mean and ANOVA for different datasets in the sub-sampling cross-validation show that the proposed model performs consistently on the complete dataset and outperforms the PINN-MLP and CNN models on all datasets except the complete small dataset. The ablation study shows that removing any module leads to performance degradation of the MFC-PINN model, except for the small dataset. The MLP module has a greater impact on temporal information processing, and the CNN module has a smaller enhancement in localization results. [Display omitted] • MFC-PINN is proposed to enhance AE source localization accuracy for scarce data. • MFC-PINN employs formulas for constraints, merges MLP and CNN for localization. • MFC-PINN reduces data dependency, enhancing noise robustness vs. data-driven models. • MFC-PINN exhibits resilience to masking and noise, achieving an RMSExy of 24.1 mm. • Localized results are validated by weight analysis, cross-validation, ablation study. Aluminum alloys used in aerospace can be monitored for cracks using acoustic emission (AE) technology, ensuring structural safety. However, data-driven deep learning models for AE source planar localization of defects in aerospace aluminum alloy plates suffer from poor prediction ability for unknown data and require a large amount of data. Additionally, physical models are heavily influenced by noise. To address these challenges, this paper proposes a multimodal fusion convolutional physical information neural network (MFC-PINN) model that considers numerical-type and image features, improving the model's comprehensive performance and generalization ability. The model also uses physical equations as constraints, reducing the dependence on large amounts of data and improving the prediction ability for unknown data. MFC-PINN performs well on datasets in complete, incomplete, and noisy conditions, especially in predicting unknown data in high-noise conditions. The study ensures the reproducibility of experiments and the validity of modules through sub-sampling cross-validation and ablation study. [ABSTRACT FROM AUTHOR]

This paper aims to reveal the mechanical evolution and potential mechanism of Ultra-high Performance Concrete (UHPC) exposed to a complex temperature-variation environment typical of Liquefied Natural Gas storage tank. Herein, the effect of steel fiber geometries (straight and hooked-end) on flexural failure of UHPCs in the range of −170 °C ∼ 200 °C was studied, and dynamic fracture evolution during the loading process was tracked using acoustic emission (AE) test. Results indicated that the flexural strength of concrete specimen enhanced at −170 °C but diminished at 200 °C in the first cycle. For multiple cycles, its improved strength subsisted until the third cycle, after which gradually decreased. Moreover, the hooked-end fiber generally had superior strengthening and toughening effects than straight fiber, except for cryogenic temperature and third cycles tests. At cryogenic temperature, the freezing of pore moisture inside specimen enhanced the matrix strength and the interfacial bonding between the matrix and fibers. At elevated temperature, the thawing, diffusion and evaporation of moisture in concrete could induce matrix dehydration and weaken the bonding effect between interfaces. In varying exposure environments, the moisture migration would also undergo secondary hydration reactions with unreacted cement particles. Finally, using AE parameters to effectively record damage progression in UHPCs exposed to extreme temperatures was also highlighted. [ABSTRACT FROM AUTHOR]

This paper presents the design, fabrication, and testing of a dual-resonance acoustic emission (AE) sensor based on PMN-PT single crystal for partial discharge (PD) detection. The use of high-performance PMN-PT single crystal enhances the sensor sensitivity. Resonance peak coupling is utilized to increase the bandwidth of the sensor effectively. The effects of piezoelectric vibrator size, vibrator spacing, and external circuitry on the sensor output are analyzed using equivalent circuits and finite element models (FEM) for sensor design. After calibration, the self-made sensor has a peak sensitivity of 76.4 dB and a bandwidth of 20 kHz to 150 kHz, which meets the demand of PD detection. The PD detection experiments verify that the self-made sensors can accurately detect PD with a high signal-to-noise ratio of 15.8 dB. In the end, the reliability test proves that the sensors have good stability and temperature characteristics. Besides above sensor's performance improvement, our design has the great potential to reduce the sensor's cross section, resulting better suitability on curved surfaces. The feasibility of employing PMN-PT as a replacement for PZT in the fabrication of AE sensors is proven by these good test results. [Display omitted] • Utilize high-performance PMN-PT single crystal to enhance sensor sensitivity to 76.4 dB. • Employ resonance peak coupling to expand the sensor bandwidth, covering 20 kHz to 150 kHz. • Devise an original matching layer design method for low-frequency, wide-bandwidth applications. • Homemade sensors achieve high reliability and can detect partial discharge accurately with higher SNR. [ABSTRACT FROM AUTHOR]

During thermal barrier coatings (TBCs) service, high-temperature and vibration are environmental factors that cannot be ignored. The vibration fatigue damage mode of TBCs under operating conditions that couple vibrations with high temperatures is unclear. In this paper, a high-temperature vibration coupled environment simulator was developed to investigate the evolution of high-temperature vibration fatigue damage modes of LaZrCeO/7-YSZ(LZC/YSZ) TBCs under alternating loads by employing acoustic emission detection. The results show that in the initial fatigue stage, the damage appears as discrete micro-cracks formed by the initial defects in the TBCs. With the increase in the number of cycles, the initiation of transverse microcracks began to occur inside the LZC layer and at the LZC/YSZ interface. When the transverse microcracks accumulate to the critical value, the applied alternating loads accelerate the propagation of opening interfacial cracks. Finally, the columnar crystal structures of the ceramic layers fracture at different heights under cyclic loading by high-temperature vibrations. • A high-temperature vibration-coupled environmental simulator was developed. • Damage accumulation and failure of TBCs were monitored using acoustic emission. • Vibratory alternating loads accelerate the extension of opening interfacial cracks. [ABSTRACT FROM AUTHOR]