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Paper is a composite of fibers, air and additives where the fiber/fiber joints keep the network structure together. A study was undertaken to establish the link between the properties of the contact zone between fibers and paper performance under mechanical loading. The contact zone between fibers was investigated using light microscopy. A staining technique was developed for evaluating the influence of surface charge on fiber/fiber joint strength. The joint strength was linearly correlated with paper tensile strength and with the average amplitude of the acoustic events measured by acoustic emission testing. The fiber surface conformability was improved by changing the surface charge. This resulted in increased fiber/fiber joint strength as the relative contact area became larger. Increasing the molecular adhesion in the contact zone with the aid of strength additives also improved the fiber/fiber joint strength. [ABSTRACT FROM AUTHOR]

Ageing power systems infrastructure and concerns about climate change have increased interest in the next generation of grid infrastructure, known as the smart grid (SG). This study studies a particularly critical SG application: intelligent monitoring of power transformers for the early detection of insulation failure. Specifically, the focus is on the use of machine learning algorithms to distinguish between different types of partial discharges, which are closely correlated with insulation failure. Measurements made using acoustic emission sensors are used to train and test different classification algorithms. In an earlier study, high classification accuracies were achieved using training and test datasets collected under similar measurement conditions. However, under different conditions, classification accuracy was greatly reduced. Experiments using the latest classification techniques were performed, producing significant improvements in classification accuracy. A possible reason for these results could be a form of overfitting, and further experiments were conducted to test this hypothesis. [ABSTRACT FROM AUTHOR]

The article presents the discussion on Insight's current awareness service covering British and international publications, conference proceedings, and multimedia products.

Moisture content of rock/coal can change its mechanical properties and absorption capacities, which can directly affect gas diffusivity, change the stress distribution and hence cause significant impacts on the overall gas or coal extraction process. Observation of the water penetration process and water distribution in the coal matrix will be beneficial for the understanding of the fluid-solid coupling mechanism in hydraulic fracturing, aquifer cracking and coal seam infusion. However, the observation of water penetration process and the determination of water distribution mode were hard to be non-destructively achieved as coal is a non-uniform, inhomogeneous and un-transparent material. µ-CT imaging, which is based on variation of X-ray attenuation related to the density and atomic composition of the scanned objects, enables a four-dimensional (spatial-temporal) visualise of the heterogeneous and anisotropic coal samples. The primary aim of this paper is extending the application of µ-CT imaging to explore the moisture penetration and distribution within coal samples during water infusion process, which has been reported by very little literature. The working principle and procedures of CT imaging was firstly introduced. Then, the determination equation of moisture distribution based on density profile was established. The CT determined moisture content has been compared with weighting method for verification. The paper has demonstrated that µ-CT can be used for non-destructively imaging the moisture distribution within coal samples. [ABSTRACT FROM AUTHOR]

In the practical production environment, the complexity and variability of hydroelectric units often result in a need for more fault data, leading to inadequate accuracy in fault identification for data-driven intelligent diagnostic models. To address this issue, this paper introduces a novel fault diagnosis method tailored for unbalanced small-sample states in hydroelectric units based on the Wasserstein generative adversarial network (W-GAN). Firstly, the fast Fourier transform is used to convert the signal from the time domain to the frequency domain to obtain the spectral data, and the W-GAN is trained to generate false spectral data with the same probability distribution as the real fault data, which are combined with the actual data and inputted into the 1D-CNN for feature extraction and fault diagnosis. In order to assess the effectiveness of the proposed model, a case study was conducted using actual data from a domestic hydropower plant, and the experimental results show that the sample features can be effectively enriched via data enhancement performed on small-sample data to improve the accuracy of fault diagnosis, which verifies the effectiveness of the method proposed in this paper. [ABSTRACT FROM AUTHOR]

The Special Collection on Accelerated Bridge Construction is available in the ASCE library (https://ascelibrary.org/page/jbenf2/accelerated bridge construction). In this technique, a new bridge superstructure is constructed on an offset from the existing bridge, then the existing bridge superstructure is demolished and the new bridge superstructure is slid in place over the existing substructure or a new substructure, which is built underneath the existing bridge prior to sliding the new bridge superstructure. For repairing bridge columns, Farzad et al. ([9]), in their paper entitled "Retrofitting of bridge columns using UHPC", propose an innovative technique to repair damaged bridge columns by the use of thin layers of UHPC, which are applied to column concrete substrates. The bridge towers utilized segmental construction for each pier leg with steel pier caps; in addition, prefabricated deck panels with cast-in-place closure joints were utilized in the bridge superstructure. [Extracted from the article]

The combination of acoustic emission and electrical potential monitoring methods holds promise for monitoring and warning of rock bursts due to its comprehensive reflection of the damage process. However, the response features during the creep failure process remain unclear. In this paper, a coal creep test was conducted using a combination of electric potential and acoustic emission monitoring. The response characteristics were analyzed, their multifractal characteristics were analyzed, and the joint response mechanism was explored. This research demonstrated a significant correlation among acoustic emission and electrical potential signals and creep deformation and failure. At the start of loading, a brief increase in both signals was observed. As deformation progressed, the signals became steady, and their intensity and fluctuation notably increased during accelerated creep failure. Quantitative analysis of acoustic emission count rates and electric potential intensity during creep processes revealed a quadratic relationship of acoustic emission count rates with stress and strain variations, in addition to an exponential correlation with mean electric potential intensity. Additionally, the statistical analysis of the multifractal characteristics before coal sample instability and failure revealed consistent trends in the characteristic values of Δα and Δf(α), with initial decrease followed by slight fluctuations, culminating in a sudden abnormal change preceding failure. Finally, leveraging the mechanisms of acoustic emission and electrification under load, this study discusses the multifractal characteristics of acoustic-electric signals and verifies their complementary roles in accurately predicting coal rock creep failure. These studies provide essential theoretical groundwork and references for improving dynamic disaster monitoring in coal mines. [ABSTRACT FROM AUTHOR]

The rockburst risk prediction based on microseismic (MS) data is an important research task in deep mine safety prevention. However, the lack of systematic research on explicit prediction indexes and the waste of a large amount of unlabeled data are still two main problems that hinder the development of rockburst prediction. In this paper, the acoustic emission (AE) event distribution at each coal rock deformation and failure stage is studied based on the laboratory experiment. The spatial-temporal evolution of rockburst in MS data of coal mine fields is explored. Based on systematic research of the AE and MS distribution features considering the physical logic of coal rock mass failure, nine different rockburst prediction indexes are employed to describe the MS data features before rockburst. Then, according to the rockburst prediction indexes, a new self-supervision rockburst risk prediction algorithm is constructed, consisting of the pre-trained model and fine-tuning model with the same encoder and decoder structure. The pre-trained model is trained with unlabeled MS data to automatically learn rockburst prediction index features by reconstructing the masked indexes. Based on the pre-trained encoder and decoder parameters, the fine-tuning model is trained with the labeled MS data to predict rockburst risk. A large number of experiments show that the proposed rockburst prediction self-supervision algorithm is far superior to previous algorithms, by effectively utilizing unlabeled data. The ablation experiment also proves the validity of the studied rockburst prediction indexes. [ABSTRACT FROM AUTHOR]

This paper describes the Santos Basin Underwater Soundscape Monitoring Project (PMPAS-BS), a Brazilian ocean soundscape monitoring initiative. The main objective of the project is to quantify and assess hydroacoustic noise of anthropogenic origin in a large sedimentary basin extending from 23° S to 28° S on the southeastern Brazilian continental margin of the South Atlantic Ocean. Noise associated with oil and gas (O&G) exploration and production activities is the primary target, but this oceanic region also has busy shipping lanes for commercial, military, and fishing vessels. The two main hubs of Brazil’s export and import of goods by sea are located in this region: Santos and Rio de Janeiro ports. The project has three measurement components: mobile monitoring based on gliders and drifting acoustic profilers, fixed shallow-water monitoring based on acoustic measurements at coastal stations near shipping lanes associated with exploration and production activities in the Santos Basin, and fixed oceanic monitoring based on deep-water mooring lines equipped with passive autonomous acoustic recorders near production units, shipping lanes, and areas with lower intensity of O&G activities (pristine or reference sites). Numerical modeling of anthropogenic underwater acoustic noise has also been included as a fourth project component. The PMPAS-BS covers an area of more than 251,000 km² and uses several instruments with different methods and sensors for acoustic measurements. Its results provide current sound levels over a very large region of the western South Atlantic, both in areas more and less affected by anthropogenic activities. [ABSTRACT FROM AUTHOR]

In order to cope with climate change and achieve the goal of carbon neutrality, the use of carbonization technology to enhance the performance of cement-based materials and achieve the purpose of carbon sequestration has become a very promising research direction. This paper considers the use of CO2NBW as mixing water for cement-based materials, aiming to improve the carbonization efficiency of materials to achieve the goal of carbon neutrality. This time, the effect of CO2NBW on cementitious filling materials under different aggregate fractal dimensions was studied through uniaxial compression tests and acoustic emission technology. The effect of CO2NBW on the mechanical properties and crack evolution of the material was discussed. The results showed that CO2 nanobubbles significantly improved the strength of cemented filling materials under different fractal dimensions, and the uniaxial compressive strength was most significantly improved by 23.04% when the fractal dimension was 2.7824. In addition, the characteristics of acoustic emission ring counts and energy parameters indicate that CO2 nanobubbles help improve the overall pore structure of the sample, affecting the macroscopic strength. However, the addition of CO2 nanobubbles reduces the limit energy storage ratio of elastic strain energy, which indicates that excessive CO2 concentration may affect the hydration reaction of the cementing material. [ABSTRACT FROM AUTHOR]

Coal power plants have been a major source of undesirable emissions. Despite the technological advancements in renewable energies, coal units are still in-service in many developed and developing countries due to their reliability, adequacy, and flexibility for power delivery. There are some promising technologies for cleaner operation during power production from coal, including supercritical boiler (SC) design and carbon capture and storage (CCS), however, the challenging in innovating effective methods is still open to expand the boundary of knowledge in this speciality. This paper introduces a novel and simple method for reducing CO2 emissions and improving the dynamic responses of a 600 MW SC coal power plant by Artificial Neural Network (ANN) technique. A wide-range data-driven feedforward ANN model has been identified and verified for the various operations recorded as closed-loop data-sets, which covers all situations of startup, once-through mode, and even emergency shutdown of the unit. The closed-loop SC plant model has been augmented with an inverse multivariable coordinate NN controller, developed by analogous learning algorithm to improve the plant automation. With precisely selected setpoints, as operational rules, of temperature, pressure, and earliest possible power demand signals, the automated SC plant has been capable to operate with lower coal consumption - and thus lower emissions – than the existing operation strategy during startup, normal operation, and emergency shutdown modes. The improvement in dynamic responses have been quantified through simulations with comparison with existing performance, which have resulted in an overall average reduction of 2.143 Kg/s in coal consumption. [ABSTRACT FROM AUTHOR]

Here, it is investigated the results of the implementation of an interferometric optical fiber acoustic sensor based on fiber Bragg grating (FBG). It is investigated the importance of different types of interferometer configurations as Michelson or Mach-Zehnder interferometers on the signal to noise ratio. It is also considered the role of polymer coating on the increasing of signal to noise ratio. The results show the Michelson interferometer setup using polymer packaging causes an increasing signal to noise ratio. This latter configuration is used in a field set up in shallow water for acoustic signal detection in the range of 0.5-5 kHz. The goal of this paper is to extract acoustical signals using optical signals via optical sensors and demodulation methods. [ABSTRACT FROM AUTHOR]

This paper investigates a 1.7 mm diameter ultra-weak fiber Bragg grating (UWFBG) hydrophone towed array cable for acoustic direction finding. The mechanism of the underwater acoustic waves received by this integrated-coating sensitizing optical cable is deduced, and it is shown that the amplitude of its response varies with the direction of the sound wave. An anechoic pool experiment is carried out to test the performance of such a hydrophone array. The test array is a selection of six sensing fibers, each of which is coiled into 9 cm diameter fiber ring suspended in the water to receive acoustic signals. An average sensitivity of −141.2 dB re rad/μPa at frequencies from 2.5 kHz to 6.3 kHz was achieved, validating the detection of the azimuth of underwater acoustic waves. The ultra-thin towing cable system, with free structure, high sensitivity, and underwater target-detection capability has demonstrated great potential for future unmanned underwater vehicle (UUV) applications. [ABSTRACT FROM AUTHOR]

The use of ocean sensors is crucial for exploration of the ocean and harnessing the potential of its resources. However, conventional ocean sensors are limited by their fabrication techniques, which result in sensors that are large in size, have high-power consumption requirements, and involve complex deployment processes. However, fulfilling observation requirements in the harsh marine environment presents a formidable challenge for these devices. Microelectromechanical system (MEMS) technologies offer a promising solution that will enable development of a new generation of ocean sensors that offer superior performance. This paper focuses on MEMS-based ocean sensors that have been designed to measure both essential physical parameters and fundamental processes within the marine environment, including the ocean's conductivity, temperature, and depth, ocean currents, ocean turbulence, earthquakes, seafloor deformation, and ocean acoustic signals. The fundamental designs of these sensors, including their working principles, structures, properties, and fabrication procedures, are illustrated in the individual sections. The paper also discusses the important challenges that MEMS ocean sensors may encounter, along with their prospects for future development. By highlighting the potential of MEMS-based ocean sensors, this review aims to contribute to the development of more efficient and reliable ocean observation systems. [ABSTRACT FROM AUTHOR]

Universal circuit breakers are crucial devices in power systems, and the accuracy of their fault diagnosis is vital. However, existing diagnostic models suffer from low feature extraction rates and low diagnostic accuracy. In this paper, we propose a novel approach for fault diagnosis of universal circuit breakers based on analyzing vibration signals generated during the closing operation. Firstly, the vibration signal was decomposed into multiple modal components using Variable Mode Decomposition (VMD), and the modal components were subjected to time and frequency domain feature extraction. Then, the extracted features were fused and normalized to construct a training dataset for the proposed model. We propose a Deep Belief Network (DBN) diagnostic model based on the Whale Optimization Algorithm (WOA), where the WOA is employed to optimize the hyperparameters of the DBN. Experimental results demonstrate that the proposed VMD and WOA-DBN model achieved an average accuracy of 96.63%. This method enhanced the accuracy of feature extraction from vibration signals and outperformed traditional diagnostic models when using a single vibration signal for fault diagnosis of universal circuit breakers. It provides a novel solution for early fault diagnosis of universal circuit breakers. [ABSTRACT FROM AUTHOR]

This study developed a noise-reduction method for acoustic logging array signals using a deep neural network algorithm in the time-frequency domain. Initially, we derived analytical solutions for the received waveforms when the acoustic logging tool was positioned either at the centre or eccentrically within the borehole. To simulate the received waveforms across various formations, we developed a real-axis integration algorithm. Subsequently, we devised a noise-reduction algorithm workflow based on a convolutional neural network and configured the structure and parameters of the U-net using TensorFlow. To address the scarcity of open datasets, we established both signal and noise datasets. The signal dataset was generated using theoretical simulation encompassing various model parameters, while the noise dataset was collected during tool testing and downhole operations. The trained model demonstrated substantial noise-reduction capabilities during validation. To validate the effectiveness of the algorithm, we applied noise reduction to actual data collected during downhole operations in a TangGu oil field, yielding impressive results across different types of noisy data. Therefore, the U-net-based time-domain noise-reduction algorithm proposed in this paper holds the potential to significantly improve the quality of acoustic logging array signals. [ABSTRACT FROM AUTHOR]

This paper presents a new approach to detecting the presence of water on a road surface, employing an acoustic vector sensor. The proposed method is based on sound intensity analysis in the frequency domain. Acoustic events, representing road vehicles, are detected in the sound intensity signals. The direction of the incoming sound is calculated for the individual spectral components of the intensity signal, and the components not originating from the observed road section are discarded. Next, an estimate of the road surface state is calculated from the sound intensity spectrum, and the wet surface detection is performed by comparing the estimate with a threshold. The proposed method was evaluated using sound recordings made in a real-world scenario, and the algorithm results were compared with data from a reference device. The proposed algorithm achieved 89% precision, recall and F1 score, and it outperforms the traditional approach based on sound pressure analysis. The test results confirm that the proposed method may be used for the detection of water on the road surface with acoustic sensors as an element of a smart city monitoring system. [ABSTRACT FROM AUTHOR]

This paper presents an extensive review of the most effective and modern monitoring methods for electrical power lines, with particular attention to high-voltage (HV) and medium-voltage (MV) systems. From a general point of view, the main objective of these techniques is to prevent catastrophic failures by detecting the partial damage or deterioration of components and allowing maintenance operations to be organized. In fact, the protection devices commonly used in transmission and distribution networks guarantee the location of faults, such as short-circuits, putting the non-functioning branch of the network out of service. Nowadays, alongside these devices, it is possible to introduce new intelligent algorithms capable of avoiding the total loss of functionality, thus improving the reliability of the entire network. This is one of the main challenges in modern smart grids, which are characterized by the massive integration of renewable energy sources and a high level of complexity. Therefore, in the first part of this paper, a general overview of the most common protection devices is proposed, followed by an analysis of the most modern prevention algorithms. In the first case, the coordination of the relays plays a fundamental role in obtaining the fault location with a high level of selectivity, while in the field of preventive analysis, it is necessary to address the implementation of artificial intelligence methods. The techniques presented in this paper provide a comprehensive description of the different monitoring approaches currently used in distribution and transmission lines, highlighting the coordination of protection relays, the computational algorithms capable of preventing failures, and the influence of the distributed generation in their management. Therefore, this paper offers an overview of the main diagnostic techniques and protection devices, highlights the critical issues that can be overcome through the introduction of artificial intelligence, and describes the main prognostic methods, focusing on their invasive level and the possibility of operating directly online. This work also highlights the main guidelines for the classification and choice between the different approaches. [ABSTRACT FROM AUTHOR]

Underground reservoirs in coal mines, consisting of goafs (By goaf, we mean the space that remains underground after the extraction of valuable minerals), are commonly utilized for mine water storage and drainage, with their primary load-bearing structures being the "roof–coal pillar" systems. Consequently, this structure must endure the repeated immersion behavior resulting from fluctuations in the mine water level, resulting in the risk of geological disasters. This paper analyzes the variation in mechanical properties of sandstone–coal composite samples after repeated immersion cycles through axial loading tests. The results indicate that the water content of the sample exhibits a notable and rapid increase with each successive immersion cycle. This corresponds to a decrease in the stress threshold and modulus parameters of the samples. Moreover, the acoustic emission signals serve as indicators of the softening characteristics of the samples. With the increase in immersion cycles, there is an augmentation in both the frequency and extent of shear cracks. The non-linear failure characteristics of the samples become more pronounced. Consequently, water significantly weakens the cementing material between rock grains. Both sandstone and coal display a decrease in deformation resistance capabilities at a macroscopic level. The constitutive model of the composite sample was improved based on the degradation characteristics of mechanical strength and strain energy parameters, which offers enhanced accuracy in analyzing the degradation process caused by water immersion. This paper offers a crucial theoretical foundation for comprehending the deterioration evolution characteristics of the "roof–coal pillar" bearing structure affected by repeated immersion. [ABSTRACT FROM AUTHOR]

A two-dimensional unsteady seepage model for coal using a finite element program is developed, and the temporal variations of key factors such as water pressure and hydraulic gradient are analyzed in this paper. Additionally, the triaxial rock mechanical experiment and utilized pneumatic fracturing equipment on raw coal samples to investigate both hydraulic and pneumatic fracturing processes are conducted. Through these experiments, the relationship between pressure and crack formation and expansion are examined. The analysis reveals that the pore pressure gradient at the coal inlet reaches its peak during rapid surges in water pressure but diminishes over time. Conversely, the pore pressure gradient at the outlet side exhibits a gradual increase. Hydraulic fracturing is most likely to occur at the water inlet during sudden increases in water pressure. Besides, as the permeability of coal decreases, the duration for seepage stabilization prolongs due to the intensified pore pressure gradient resulting from sudden increases in water pressure. Moreover, an extended period of high hydraulic gradient further increases the risk of hydraulic fracturing. The experimental findings indicate that coal samples initially experience tensile failure influenced by water and air pressure. Subsequently, mode I cracks form under pressure, propagating along the fracture surface and becoming visible. The main types of failure observed in hydraulic and pneumatic fracturing are diametrical tensile failure, and the development of fractures can be categorized into three distinct stages, which contains the initial stage characterized by slight volume changes while water pressure increases, the expansion stage when pressure reaches the failure strength, and the crack closure stage marked by little or even decreasing volume changes during pressure unloading. The acoustic emission signal accurately corresponds to these three stages. [ABSTRACT FROM AUTHOR]

Top-coal structure detection is an important basis for realizing effective mining in fully mechanized cave faces. However, the top-coal structure is very complex and often contains multi-layer gangues, which seriously influence the level of effective mining. For these reasons, this paper proposes a novel multi-frequency ground-penetrating radar (GPR) data-fusing method through a joint sliding window and wavelet transform weighting method to accurately detect the top-coal structure. It possesses the advantages of both high resolution and great detection depth, and it can also integrate multi-frequency GPR data into one composite profile to interpret the internal structure information of top coal in detail. The detection procedure is implemented following several steps: First of all, the multi-frequency GPR data are preprocessed and aligned through a band-pass filter and a zero offset elimination method to establish their spatial correspondences. Secondly, the proposed method is used to determine the time-varying weight values of each frequency GPR signal according to the wavelet energy proportion within the sliding window; also, the edge detection algorithm is introduced to improve the fusion efficiency of the wavelet transform so as to realize the effective fusion of the multi-frequency GPR data. Thirdly, a reflection intensity model of multi-frequency GPR signals traveling in the top-coal is established by using the stratified identification method, and then, the detailed top-coal structure can be inversely interpreted. Finally, the quantitative evaluation criteria, information entropy (IE), space–frequency (SF) and Laplacian gradient (LG), are used to evaluate the multi-frequency GPR data fusion's effectiveness in laboratory and field environments. The experimental results show that, compared with the genetic, time-varying and wavelet transform fusion method, the fusion performance of the presented method possesses higher values in the IE, SF and LG evaluation criteria, and it also has both the merits of high resolution and great detection depth. [ABSTRACT FROM AUTHOR]

Carbon-fiber-reinforced polymer (CFRP) composites are widely used in lightweight structures because of their high specific strength, specific modulus, and low coefficient of thermal expansion. Additionally, the unidirectionally arrayed chopped strand (UACS) laminates have excellent mechanical properties and flowability, making them suitable for fabricating structures with complex geometry. In this paper, the damage process of UACS quasi-isotropic laminates under tensile load was tested using acoustic emission detection technology. The mechanical properties and damage failure mechanism of UACS laminates were studied combined with finite element calculation. By comparing and analyzing the characteristic parameters of acoustic emission signals such as amplitude, relative energy, and impact event, it is found that acoustic emission behavior can accurately describe the damage evolution of specimens during loading. The results show that the high-amplitude signals representing fiber fracture in continuous fiber laminates are concentrated in the last 41%, while in UACS laminates they are concentrated in the last 30%. In UACS laminates, more of the damage is caused by matrix cracks and delamination with medium- and low-amplitude signals, which indicates that UACS laminates have a good suppression effect on damage propagation. The stress–strain curves obtained from finite element analysis agree well with the experiment results, showing the same damage sequence, which confirms that the model described in this research is reliable. [ABSTRACT FROM AUTHOR]

In this paper, ordinary Portland cement, ultrafine cement, polyurethane, and epoxy resin were selected as typical grouting materials. Grouting simulation tests were first conducted to prepare the grouted concrete crack sample. The effect of concrete crack parameters (i.e., crack aperture and roughness), grout water–cement ratio, and grouting pressure on the water-plugging performance of different grouting materials was explored through the impermeability test. The microstructure of grouted concrete cracks was analyzed by means of scanning electron microscopy (SEM) and computed tomography (CT), and the difference in water-plugging performance of different grouting materials was explained at the micro level. The results show that the impermeability of the four grouting materials was ranked as follows: Epoxy resin > polyurethane > ultra-fine cement > ordinary Portland cement. The concrete cracks grouted by epoxy resin have the highest plugging failure water pressure and the lowest permeability, which is the optimal grouting material. The effectiveness of crack grouting in water-plugging was directly proportional to the grouting pressure, provided the pressure did not exceed a certain value. When the pressure surpassed the threshold, the increase in pressure did not have a significant impact on the water plugging performance. For the two cement-based materials, the threshold pressure was 1 MPa, while for the other two chemical grouts, it was 2 MPa. The two cement-based grouts with a water–cement ratio of 0.8 showed optimal water-plugging performance. The water-plugging performance of ordinary Portland cement paste, ultra-fine cement pastes, and polyurethane grout was negatively correlated with crack aperture and positively correlated with crack roughness. However, the water-plugging performance of epoxy resin grout was not affected by crack aperture or roughness. [ABSTRACT FROM AUTHOR]

Thermal exchange of underwater water mass caused by marine heat wave is a hot point of research recently. In particular, because the water temperature observation along hot water mass transportation is hard work. Acoustic tomography is an advanced method to measure water temperature variations via sound signal transmission with multi-station network sensing. The 5 kHz frequency acoustic tomography used for observing water temperature variations caused by ocean heat waves is interesting work. In this paper, the numerical simulation of hot water mass is completed first, then floatation and diffusion of hot water mass in a simulation are monitored by acoustic tomography. A new inversion optimization method is proposed to obtain hot water mass transportation variations at two-dimensional temperature vertical profile. The proposed inversion method adds a regularized mode matrix and the optimization method adds the model correlation matrix to improve the results quality. The accuracy of inversion optimization results is compared and discussed, where the mean temperature error is less than 0.4 °C. Sensing water temperature variation of marine heat waves is verified via acoustic signal transmission and improved inversion optimization method. The water dynamical process observation is an application of acoustic tomography, which can be further used observe underwater environmental characteristics. [ABSTRACT FROM AUTHOR]

Studying the mechanical properties of rock–concrete combined body is crucial to ensure the safety and stability of engineering structures. In this paper, laboratory tests and numerical simulations are used to investigate the mechanical properties of the sandstone–concrete combined body. Uniaxial compression tests and an acoustic emission monitoring system are used to analyze the failure characteristics of the sandstone–concrete sample and to validate the accuracy of the numerical model. The mechanical properties of the composite body were further analyzed by integrating energy and damage theories. The results of the sandstone–concrete study suggest that the combined sandstone–concrete body exhibits synergistic deformation and failure when subjected to uniaxial compression. The peak stress and elastic modulus fall between those of sandstone and concrete. The interface's shape causes the stress in the y-direction to transition from tensile stress to compressive stress. Energy is stored before reaching the peak stress and released after reaching the peak stress. The damage curve indicates that the damage increases gradually with the strain, and it results in plastic failure. In the numerical simulation of triaxial compression, the stress and displacement at the interface are evenly distributed. Compared to uniaxial compression, the energy of each component is higher and shows a linear positive correlation with confining pressure. Additionally, the rate of energy dissipation increases with higher confining pressure. The damage variable also increases with the increase in confining pressure, and the plastic failure process is also apparent under triaxial compression. [ABSTRACT FROM AUTHOR]

From a passive satellite remote sensing point of view, the richest set of information on aerosol properties can be obtained from instruments that measure both intensity and polarization of backscattered sunlight at multiple wavelengths and multiple viewing angles for one ground pixel. However, it is challenging to exploit this information at a global scale because complex algorithms are needed with many fit parameters (aerosol and land/ocean reflection), based on online radiative transfer models. So far, two such algorithms have demonstrated this capability at a global scale: the Generalized Retrieval of Atmosphere and Surface Properties (GRASP) algorithm and the Remote sensing of Trace gas and Aerosol Products (RemoTAP) algorithm. In this paper, we present a detailed comparison of the most recent versions of RemoTAP and GRASP. We evaluate both algorithms for synthetic observations, for real PARASOL (Polarization and Anisotropy of Reflectances for Atmospheric Science coupled with Observations from a Lidar) observations against AERONET (Aerosol Robotic Network) for common pixels, and for global PARASOL retrievals for the year 2008. For the aerosol optical depth (AOD) over land, both algorithms show a root mean square error (RMSE) of 0.10 (at 550 nm). For single scattering albedo (SSA), both algorithms show a good performance in terms of RMSE (0.04), but RemoTAP has a smaller bias (0.002) compared to GRASP (0.021). For the Ångström exponent (AE), GRASP has a smaller RMSE (0.367) than RemoTAP (0.387), mainly caused by a small overestimate of AE at low values (large particles). Over ocean both algorithms perform very well. For AOD, RemoTAP has an RMSE of 0.057 and GRASP an even smaller RMSE of 0.047. For AE, the RMSEs of RemoTAP and GRASP are 0.285 and 0.224, respectively. Based on the AERONET comparison, we conclude that both algorithms show very similar overall performance, where both algorithms have stronger and weaker points. For the global data products, we find a root mean square difference (RMSD) between RemoTAP and GRASP AOD of 0.12 and 0.038 over land and ocean, respectively. The largest differences occur over the biomass burning region in equatorial Africa. The global mean values are virtually unbiased with respect to each other. For AE the RMSD between RemoTAP and GRASP is 0.33 over land and 0.23 over ocean. For SSA, we find much better agreement over land (bias = - 0.01, RMSD = 0.043 for retrievals with AOD > 0.2) than over ocean (bias = 0.053, RMSD = 0.074). As expected, the differences increase towards low AOD, over both land and ocean. We also compared the GRASP and RemoTAP AOD and AE products against MODIS. For AOD over land, the agreement of either GRASP or RemoTAP with MODIS is worse than the agreement between the two PARASOL algorithms themselves. Over ocean, the agreement is very similar among the three products for AOD. For AE, the agreement between GRASP and RemoTAP is much better than the agreement of both products with MODIS. The agreement of the latest product versions with each other and with AERONET improved significantly compared to the previous version of the global products of GRASP and RemoTAP. The results demonstrate that the dedicated effort in algorithm development for multi-angle polarimetric (MAP) aerosol retrievals still leads to substantial improvement of the resulting aerosol products, and this is still an ongoing process. [ABSTRACT FROM AUTHOR]

Traditional marine monitoring can be a resource‐intensive process that often covers a network of sampling stations where data are collected manually by divers, or discretely using in situ water samples at different depths at fixed positions followed by laboratory analysis. As such, environmental status is often reported after a delay of months or years. However, things are set to change for the better. Recent advances in technologies, such as remote sensing, machine learning techniques, modeling for non‐experts, acoustic monitoring, and intelligent integration of modeling and sensor measurements will revolutionize the future of marine environmental monitoring and monitoring systems. This special series touches upon some of the new technologies and models that may be an integrated part of ecosystem assessment and management in the future. Although technologies are being developed and integrated for marine monitoring around the world, the integration with ecosystem models is still in the early days. Still, this series highlights inspirational examples of the time ahead of us. Integr Environ Assess Manag 2022;18:888–891. © 2022 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC). Key Points: Papers in the special series show advances in various technologies. [ABSTRACT FROM AUTHOR]

Several methods to localise sources of vibrations have been established in the literature. A great amount of those methods are based on databases with features of known impact positions. Great effort needs to be put into highly expensive experiments that deliver those databases. In this paper, we propose several simulation techniques that may replace the expensive experiments for source localisation. The paper compares the localisation accuracy of simulated and experimental data for two different localisation approaches, the reference database method and neural networks. Both methods process signal arrival time differences from several positions on the structure. The methods are exemplarily applied to a complex small-scale structure from the automotive industry: The small dimensions of the brake disk hat and the inclusion of holes is a challenging task for the accuracy of the applied localisation techniques. Results show that simulated data can replace experimentally gained data well in case of the reference database method, whereas the neuronal networks approach should stick to experimentally gained data. The evaluations show that, despite the small dimension, the relative localisation accuracy is within accepted ranges of literature. [ABSTRACT FROM AUTHOR]

The method of backfill in underground mining is important for ground control as well as material recycling and energy efficiency. Even though extensive testing and field studies of backfill have been conducted, less is known about the detailed damage and fracturing that occurs directly at the rock/backfill interface. In this paper, cylindrical specimens containing an inner diameter of backfill and an outer diameter of rock (RB) were tested under triaxial compression. Acoustic emissions (AE) were used throughout testing, and X-ray computed tomography (CT) scanning was conducted before loading was applied and after the specimens had failed. The high-resolution CT images were then converted into point clouds to isolate the fractures and visualize them in three dimensions. The point clouds clearly show that fracturing occurred both in the rock and along with the contact between rock and backfill, while very little fracturing was found to occur in the backfill. Based on the point cloud and AE results, a unique evolution of fracturing is found to occur that includes two stages of shear fracturing in the rock, tensile fracturing along with the rock/backfill interface, and final tensile fracturing in the rock after delamination from the backfill, all of which contributed to the nonlinear stress–strain response. This paper presents a novel approach for investigating the initiation and propagation of 3D fractures in laboratory testing and can offer a useful reference for further studies on the mechanics of bi-material structures. [ABSTRACT FROM AUTHOR]

The increasing uncertainties in power systems have brought non-negligible influences on the dynamic behaviors. An accurate and efficient simulation method considering the effects of stochastic disturbances is of critical importance for the analysis of the dynamic performance of power systems. In this paper, a methodology for the simulation of stochastic transients in power systems is developed based on frequency shifting theory. The stochastic differential equations describing the stochastic process of parameter migration are represented through analytic signals. The frequency shifting operation is introduced. The Fourier spectra of analytic signals are shifted to reduce their maximum frequency contents, thereby permitting a larger time-step in time-domain simulation in accordance with Shannon's sampling theory. Through the trapezoidal Milstein scheme, the stochastic differential equations with shifted analytic signals are discretized. Branch companion models that process analytic signals for the simulation of stochastic transients are formulated. The numerical properties of branch models are further examined. The analysis of test cases demonstrates that the proposed method can be used to represent stochastic transients caused by parameter migrations accurately and efficiently. [ABSTRACT FROM AUTHOR]

The global shale gas resources are huge and have good development prospects, but shale is mainly composed of nanoscale pores, which have the characteristics of low porosity and low permeability. Horizontal drilling and volume fracturing techniques have become the effective means for developing the shale reservoirs. However, a large amount of mining data indicate that the fracturing fluid trapped in the reservoir will inevitably cause hydration interaction between water and rock. On the one hand, the intrusion of fracturing fluid into the formation causes cracks to expand, which is conducive to the formation of complex fracture networks; on the other hand, the intrusion of fracturing fluid into the formation causes the volume expansion of clay minerals, resulting in liquid-phase trap damage. At present, the determination of well closure time is mainly based on experience without theoretical guidance. Therefore, how to effectively play the positive role of shale hydration while minimizing its negative effects is the key to optimizing the well closure time after fracturing. This paper first analyzes the shale pore characteristics of organic pores, clay pores, and brittle mineral pores, and the multi-pore self-absorption model of shale is established. Then, combined with the distribution characteristics of shale hydraulic fracturing fluid in the reservoir, the calculation model of backflow rate and shut-in time is established. Finally, the model is validated and applied with an experiment and example well. The research results show that the self-imbibition rate increases with the increase in self-imbibition time, and the flowback rate decreases with the increase in self-imbibition time. The self-imbibition of slick water is the maximum, the self-imbibition of breaking fluid is the minimum, and the self-imbibition of mixed fluid is the middle, and the backflow rates of these three liquids are in reverse order. It is recommended the shut-in time of Longmaxi Formation shale is 17 days according to the hydration and infiltration model. [ABSTRACT FROM AUTHOR]

Safety is the primary guarantee for achieving coal mine production. The degree of water in the overlying rock of the coal seam has a significant impact on the mechanical strength of the rock, which can lead to subsidence, roof collapse, and rock burst in the mining area. Therefore, it is important to study the law of waterrich damage and deterioration of coal seam overlying rock, as well as the characteristics of bursting liability to prevent and control mining disasters. This paper aims to investigate the change in compressive strength, elastic modulus, and bursting liability of coal measure strata under different water content and their relationship with lithology, particle size, pore characteristics, and mineral characteristics. We carried out uniaxial compression tests on drilled and prepared samples of coal measure strata in the east of Ordos City. We also monitored the acoustic emission characteristics of the rock failure process under different water content. The results demonstrate that, in the dry state, the compressive strength of siltstone >fine sandstone >medium sandstone >coarse sandstone. As the water content increases, the rock transitions from brittle to plastic, and the compressive strength, elastic modulus, and bursting liability gradually decrease. The stress-strain curve changes from a single peak to bimodal and multimodal, and the active degree of acoustic emission events decreases, especially the low-value ringing count. Calcareous cementation, clay minerals, and chlorite exhibit strong softening properties when subjected to water, while the grain skeleton (comprising quartz, feldspar, mica) and siliceous cementation displays weak softening properties in such conditions. The most significant is the mechanical strength deterioration of siltstone containing a clay matrix. The research findings can provide reference and theoretical support for safe mining practices in coal mines. [ABSTRACT FROM AUTHOR]

In this paper, the instantaneous rock burst test of Beishan granite is carried out by using a deep rock burst simulation test system and an acoustic emission monitoring system. The acoustic emission data were monitored in real time during the test. The variation of the number and energy of acoustic emission events was studied, and the distribution characteristics of rock burst debris were analyzed. Based on plate and shell mechanics, the failure process of surrounding rock is discussed from the perspective of structural stability. The results show that (1) when the vertical stress reaches 171.31 MPa, the specimen is destroyed and the number of acoustic emission events and cumulative absolute energy before the specimen is destroyed increase sharply. (2) The debris generated by rock burst is mainly composed of slab debris, flaky debris, and thin flaky debris, accounting for 93.53% of the total debris. (3) When the length or height of the rock slab is constant, the maximum tensile stress in the rock slab decreases nonlinearly with the increase of rock slab thickness. For the same size of the rock slab, the farther away from the roadway wall, the greater the maximum tensile stress in the rock slab. (4) When the thickness of the rock slab is constant, the maximum tensile stress in the rock slab increases nonlinearly with the increase of height to thickness ratio K. When the ratio of height to thickness K is constant, the maximum tensile stress in the rock slab increases with the increase of rock slab thickness h. (5) With the increase of covering depth, the critical failure thickness of the rock slab decreases nonlinearly and the surplus energy increases nonlinearly. [ABSTRACT FROM AUTHOR]

The main purpose of this study was to understand the failure mechanism of fly ash fiber–reinforced asphalt specimens under uniaxial compression loading and splitting loading, respectively. The variation of acoustic emission (AE) parameters in the acoustic emission tests during this fracture process was analyzed. The results showed that under uniaxial compression, the failure process of the fiber asphalt specimens could be divided into four stages: the formation of internal microcracks, microcrack propagation, rapid crack propagation, and finally, failure. Shear failure is the main failure form of asphalt specimens, and with the gradual increase of fiber content, the failure mode of specimens gradually changes from shear failure to shear-tensile failure. The correlation analysis between peak value and frequency of acoustic emission parameters shows that there are three frequency bands of fly ash fiber asphalt specimen, namely, 0–30, 30–60, and 150–200 kHz, which correspond to the initial dislocation failure of the interface between aggregate and asphalt mortar, the fracture failure of the interface between fly ash fiber and asphalt mortar, and the complete dislocation failure of the interface between aggregate and asphalt mortar. In recent years, acoustic emission technology has been widely used in the field of nondestructive testing of cement concrete and bridge structures. Nevertheless, the damage identification methods commonly used in asphalt pavement, such as the computational simulation method and image processing method, have low working efficiency, large error, and lack of dynamic perception of the whole damage process, which limits their applicability in practical engineering applications. In this paper, acoustic emission technology has been employed to characterize the damage and crack propagation law of fiber asphalt specimens under various stress states. Through the analysis of the evolution characteristics of acoustic emission signal parameters, the fracture damage characteristics of fiber asphalt samples under different stresses are invested. The research results are of great significance for the popularization and application of acoustic emission technology in the field of nondestructive testing of asphalt pavement. [ABSTRACT FROM AUTHOR]

In order to promote sustainable energy development and reduce the impact of fossil fuels on the environment, it is crucial to strengthen the development and utilization of clean and renewable geothermal energy. Liquid nitrogen fracturing, as an emerging waterless fracturing technology, has outstanding advantages in rock fracturing effect and thermal exchange ability with hot dry rock and is more environmentally friendly. In order to evaluate the influence of liquid nitrogen on the mechanical properties, acoustic emission characteristics, and cross-sectional crack propagation characteristics of granite at different initial temperatures, this paper carried out three-point bending tests and acoustic emission detection on granite treated by high-temperature heating and liquid nitrogen cooling. Finally, based on the cross-sectional scanning test, the expansion characteristics of microcracks in granite were analyzed. The results show that the higher the initial temperature of granite, the stronger the cold impact of liquid nitrogen on granite, and the faster the rock's mechanical performance declines. The acoustic emission ringing count is closely related to the development of microcracks in granite, and as the initial temperature of granite increases, the more ringing counts there are, indicating that the huge temperature difference induces more microcracks inside the rock. In addition, the cold impact of liquid nitrogen can effectively promote the fracturing of granite. After liquid nitrogen treatment, the fractal dimension of the granite cross-section increases, the shape of the cross-section becomes rough, and many micropores appear. This study can provide a scientific basis for the engineering application of liquid nitrogen fracturing technology. [ABSTRACT FROM AUTHOR]

Cleaning is one of the most important steps in the harvesting process, and the prolonged and high-load operation of the vibrating sieve can decrease its reliability. To uncover the structural flaws of the cleaning sieve in the crawler combine harvester and establish a foundation for quality inspection, this paper proposes a method for durability testing and analysis using vibration and strain signals. Via the modal analysis of the cleaning sieve, the most susceptible areas for fault signals are identified. Subsequently, a specialized test rig exclusively designed for the examination of the durability of the cleaning sieve is constructed. After following 96 h of uninterrupted operation, the vibration plate of the cleaning sieve sustains damage, resulting in atypical noise. A signal analysis reveals that the primary vibration signal of the cleaning sieve primarily consists of a fundamental frequency of 5 Hz, corresponding to the driving speed, as well as a frequency doubling signal of 50 Hz. After the occurrence of damage, the peak amplitude of the received vibration signal increases by over 86.3%. Furthermore, the strain gauge sensor situated on the support plate of the rear sieve detects anomalous signals with frequencies exceeding 300 Hz, which are accompanied by a considerable rise in the power spectral density. This research has significant importance for enhancing the service life of the cleaning sieve and optimizing the overall machine efficiency. [ABSTRACT FROM AUTHOR]

Application of CFRP to the industrial field is expanding and acoustic emission testing (AT) is utilized for some applications. In this paper, possible problems that may cause when AE testing is applied to CFRP components with curved fibers are discussed based on the previous author's paper about ultrasonic propagation in CFRPs. It was concluded that the AE amplitude has a potential to be highly affected by the location of AE sensors on the components. It is also noted that general AE source location algorithm cannot be applied for this kind of materials in some cases since shortest path from AE source to AE sensor are varied with the position on the components. [ABSTRACT FROM AUTHOR]

Traditionally, underwater acoustic modems and positioning systems were developed for military and Oil & Gas industries, that require deep water deployments and extremely reliable systems, focusing on high power expensive systems and leaving the use of low-cost devices only attractive for academic studies. Conversely, recent developments of low-cost unmanned vehicles, such as remotely operated vehicles (ROVs) and autonomous underwater vehicles (AUVs), suitable for shallow water coastal missions, and the need of sensors network deployments for measuring water quality and studying the effect of climate change in coastal areas, called to the need of low-cost and low-power acoustic modems and positioning systems that are gaining more and more momentum to date. The use of these devices can enable a wide set of applications, often based on low-cost AUV swarm formations, where an acoustic link between the vehicles is required to coordinate the mission, perform the maneuvers, and maintain the formation along the time. Moreover, they can make environmental wireless sensor deployment cost effective by substituting wired systems. Underwater positioning systems, usually used in large-scale operations, can be finally applied to small-scale application thanks to the reduction in costs, at the price of a lower transmission and positioning range and precision. While in open-sea application this performance reduction is a huge limitation, in river, lagoon, port and lake deployments this is not an issue, given that the extremely shallow water and the presence of many obstacles would deteriorate the acoustic signal anyway, not allowing long range transmissions even with expensive and sophisticated acoustic devices. In this paper, we review the recent developments of low-cost and low-power acoustic communication and positioning systems, both analyzing University prototypes and new commercial devices available in the market, identifying advantages and limitations of these devices, and we describe potential new applications that can be enabled by these systems. [ABSTRACT FROM AUTHOR]

As one of the widespread physical phenomena in the global ocean system, the ocean front has a very important influence on underwater sound propagation. Firstly, this paper systematically reviews several methods for the detection of ocean fronts in the past decades, including traditional oceanographic methods, artificial intelligence methods, and acoustic methods, highlighting the advantages and disadvantages of each method. Next, some modeling studies of ocean fronts are reported in this paper. Based on the above research, we pay more attention to research progress on the acoustic effects of ocean fronts, including simulation analysis and experimental research, which has also been the focus of underwater acousticians for a long time. In addition, this paper looks forward to the future development direction of this field, which can provide good guidance for the study of ocean fronts and their acoustic effects in the future. [ABSTRACT FROM AUTHOR]

Perfluorinated compounds (PFCs) are a novel type of environmental pollutant with a specific structure. PFCs have become a global concern due to their environmental persistence and biotoxicity properties. In this paper, we review the hazardous effects, detection technologies, and treatment methods of PFCs. We present the current status of PFCs pollution in water, the atmosphere, soil, and organisms. Moreover, we show that PFCs have toxic effects, such as hepatotoxicity, neurotoxicity, immunotoxicity, endocrine disruption, and reproductive and developmental toxicity. Six sample pretreatment techniques and four assays for PFCs are listed in this paper. This review focuses on the analysis of the treatment methods for PFCs, such as physical adsorption, microbial degradation, photochemical oxidation, electrochemical oxidation, acoustic oxidation, Fenton oxidation, and so on. We systematically analyze the treatment effects, removal mechanisms, and future directions of various technologies to provide support and suggestions for PFCs pollution control technologies. [ABSTRACT FROM AUTHOR]

Understanding the acoustic repertoire of a species is crucial for comprehending its ecology and can also provide a valuable tool in the analysis of passive acoustic monitoring data. Despite being the most abundant seal species in the Arctic, the call repertoire of ringed seals (Pusa hispida) remains poorly studied. This paper aims to provide a comprehensive and quantitative description of the calls produced by ringed seals. Data collection occurred in May 2022 near Ulukhaktok in the Western Canadian Arctic. Acoustic recorders were deployed in cracks in the sea ice that were regularly used by ringed seals as haul-out areas. All calls were counted and classified into one of three categories: yelps, barks and growls. High-quality calls were further analysed with ten acoustic parameters calculated for each signal. Cluster and classification and regression tree (CART) analyses were used to assess if the visual classification of calls was supported by the acoustic parameters calculated. The cluster and CART analyses affirmed the presence of all three distinct call types in the ringed seal acoustic repertoire. Classification of unseen calls using the CART model demonstrated an accuracy of 98%. The findings presented here serve as foundational information on the acoustic repertoire of ringed seals. [ABSTRACT FROM AUTHOR]

To achieve the actual situation of water pressure stabilization during underground and tunnel water inrush disasters, the team independently developed a stable water pressure test system and conducted fracture and failure tests on fissured rock masses under the coupling effect of 1MPa stable water pressure and stress and without water pressure. Combined with data collected by acoustic emission instruments, the mechanical characteristics of fracture and failure, crack propagation mechanism, and acoustic emission response mechanism of fissured rock masses under the coupling effect of stable hydraulic pressure and stress were studied. The results showed that throughout the entire experimental process, the hydraulic pressure remained continuously stable, with a decrease of only 0.14%; The variation pattern of peak strength of fissured rock mass with increasing crack inclination angle under stable hydraulic pressure changes from a decrease and then an increase in the absence of hydraulic pressure to an increasing trend; The crack propagation length of low angle fissured rock mass is generally higher than that of high angle fissured specimens. The longer propagation path increases the range and effect of hydraulic pressure, and the initial crack propagation length of fissured rock mass under hydraulic pressure is also significantly longer than that of specimens without hydraulic pressure; During the loading process, both the acoustic emission ringing count and damage variable can be divided into four stages. From the cumulative total number of acoustic emission ringing counts, it can be seen that during the loading process, the total number of acoustic emission ringing in fissured rock masses subjected to hydraulic pressure is significantly lower than that of specimens without hydraulic pressure, and the trend is also relatively stable. [ABSTRACT FROM AUTHOR]

Frequent mining operations significantly disturb the security of deep weakly cemented rock roadways in western mining areas, constituting one of the primary causes of deformation, instability, and failure within the coal‐rock body. In this paper, dynamic uniaxial compression tests of soft rock‐coal combinations under low‐frequency disturbance with different cyclic amplitudes were conducted based on acoustic emission to elucidate fracture modes. The findings are as follows: Different cycle amplitudes manifested significant degradation effects on the soft rock‐coal combination. With increasing cycle amplitude, the proportion of tensile cracks initially decreased before subsequently increasing, demonstrating a general upward trajectory. The sudden increase in the acoustic emission RA value, the large decrease in the b‐value, and AE counts reaching the peak mean that failure and destabilization of the specimen begin to occur. The results of this study will furnish theoretical direction for dynamic disaster monitoring and early warning in soft rock mines located in western mining regions. [ABSTRACT FROM AUTHOR]

The Underwater Wireless Sensor Network (UWSN) is capable of supporting a wide range of low-data-rate acoustic sensor networks, as well as scalability and energy-efficient routing algorithms. Furthermore, because of the lower bandwidth and longer propagation delays, energy consumption is a major concern with underwater networks. Because radio transmissions are unstable in deep water, a UWSN often communicates via acoustic channels. UWSN features create constraints on data packet transmission and energy-efficient routing. The hardest challenge is creating an effective routing protocol for UWSNs that uses sensor node localization. There have been several routing algorithms reported for identifying nodes via a localization process. This paper proposes a novel vector-based forwarding (NVBF) and efficient depth-based routing (DBR) protocol to provide robust, scalable, and energy-efficient routing. Efficient DBR is a stochastic model that can survive even in acoustic channels with substantial transmission loss. An adjacent node table is created to decrease the energy consumption and end-to-end delay by limiting the adjacent node request generated every single time. The redundant packet transmission is reduced by creating a packet queue which also minimizes the energy. The NVBF algorithm uses a random waiting time to overcome the collision that occurs while sending the acknowledgment packets. Based on the previous sender's depth and the depth of the own node, the DBR makes packet transmission decisions. The experiments are conducted using the NS3 simulator and the efficiency of the proposed approach is evaluated in terms of propagation delay, network lifetime, energy consumption, and delivery ratio. When compared to the existing techniques such as DBR, VBF, and energy-efficient DBR (EDBR), the proposed methodology offers improvement up to 40% and 30% in terms of propagation delay and delivery ratio. [ABSTRACT FROM AUTHOR]

Studies show that sediment erosion is one of the main factors attributing to hydraulic turbine failure. The present paper represents an investigation into acoustic vibration signals generated by the water flow impacting the hydraulic turbine runner under three different operating conditions. Collected signals were denoised using the ICEEMDAN-wavelet threshold method, and then the spectral characteristics and sample entropy characteristics of the signals for the three operating conditions were analyzed. The results show that when clean water flows through the hydraulic turbine, the sample entropy reaches its smallest values and the dominant frequency component in the spectrogram is 59.39 Hz. When transitioning from clean water to the flood flow containing 2–4 mm sediment particles, the sample entropy is increasing and a high-frequency component higher than 59.39 Hz becomes the prominent frequency of the spectrogram. Meanwhile, the formation of high-frequency components increases with the sand-containing particle size. Based on the spectral characteristics and sample entropy characteristics of the acoustic vibration signals under different operating conditions, it can provide a reference for the sand avoidance operation of the hydraulic turbine during flood season. In addition, it provides a supplement to the existing hydraulic turbine condition's monitoring systems and a new avenue for subsequent research on early warning of hydraulic turbine failure. [ABSTRACT FROM AUTHOR]