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Fiber‐reinforced polymers (FRP) feature high strength‐to‐weight ratio amongst the emerging class of natural composites. This paper presents the impact of the glass fiber on the tensile strength of the flax epoxy laminate. The mechanical behavior and damping characteristics of flax fiber reinforced polymer (FFRP) and the hybrid flax‐glass fiber reinforced polymer (HFRP) are experimentally investigated. Both the flax and hybrid FRPs are made using vacuum infusion process. The specimens without and with holes of 4, 5, and 6 mm in diameter are subjected to tensile test using acoustic emission monitoring and free vibration test. In the former testing, HFRP resulted in higher peak frequencies and cumulative counts. Also, the natural frequency and damping factor of HFRP vary proportionately with the hole size, as identified in the latter tests. Different damage mechanisms during the tensile test revealed that the presence of glass fibers in HFRP increased resistance for certain damage mechanisms. Highlights: Adding glass fiber to flax fiber reinforced polymer (FFRP) creates a hybrid FRP (HFRP) with increased resistance to damage and improved damping characteristics.HFRP exhibits a distinction in failure mechanisms compared to FFRP.The study utilizes acoustic emission (AE) to identify various damage mechanisms in the material, providing a more detailed information.The addition of glass fibers in HFRP leads to a more pronounced increase in damping factors. [ABSTRACT FROM AUTHOR]

Rockmass in deep mining is highly susceptible to large-scale collapses under high stress and blast-induced disturbances, leading to casualties and economic losses. To investigate the evolution characteristics of goaf instability and the types of seismic sources that induce instability, an experiment on goaf instability was designed under uniaxial compression conditions based on actual mining operations. The entire experimental process was monitored using digital image correlation analysis and acoustic emission monitoring. By calculating the digital speckle field on the surface of the rock specimen during the experiment, the evolution characteristics of the deformation and strain fields from the beginning of loading to complete failure were analyzed. The study explored the dynamic behavior of cracks from initiation to propagation and eventually inducing large-scale collapse. The results show that the instability process of the goaf begins with the formation of tensile cracks. As stress increases, shear cracks occur in the specimen, leading to macroscopic failure. Furthermore, based on the differences in overall microfracture types measured by RA-AF characteristic parameters during specimen failure, large amplitude acoustic emission events corresponding to the formation of dominant macroscopic cracks were selected, and the focal mechanisms of these events were inverted. The results indicate that shear failure sources are significantly more prevalent than tensile failure sources in acoustic emission events leading to goaf instability. These findings can provide useful guidance for the support design and the prevention and control of rockmass instability disasters. [ABSTRACT FROM AUTHOR]

In 2022, the authors presented the first stage of implementing a revised climate control strategy at the National Gallery of Victoria, monitoring collection object response in collaboration with the Getty Conservation Institute using acoustic emissions (AE) monitoring. The research and education, motivating factors, and interdepartmental alignment required for adopting the Bizot Green Protocol (BGP) were discussed, as well as the experimental design and set-up of the AE system on a large Flemish altarpiece in an active gallery. This second and concluding paper presents the results of the AE monitoring study along with energy used by the HVAC system for the gallery housing the AE monitoring study, during the transition from traditional environmental parameters through to broadened parameters as defined in the BGP. The project highlights the importance of understanding individual gallery and building behaviour as well as the HVAC system in place. In the case of the gallery housing the AE study, the implementation of BGP parameters resulted in smaller environmental fluctuations than expected. That HVAC energy efficiency could be improved with a relatively low impact on the gallery environment was an unexpected but welcome outcome. This case study describes some common challenges faced when considering such a change operationally, including resourcing and communication needs. Identifying points of resistance, framing problems clearly, and identifying common goals were essential to making progress. In this case, sustainability has compelled many stakeholders into alignment and enabled a shift in institutional culture. [ABSTRACT FROM AUTHOR]

Earlier experiments have shown that cyclic hydraulic fracturing (CHF) systematically reduces the monotonic breakdown pressure (MBP). However, cyclic injection also causes a significantly longer injection time to failure as compared to the monotonic injection tests and complex fracture propagation that is hard to predict. In this study, a different injection scheme employing rock fatigue behavior, named creep injection, was tested on granite cylinders. The creep injection creates continuous pressurization under a constant borehole pressure (CBP) with a pre-defined maximum value below the MBP. Three different pressure ratios (CBP/MBP) of 0.85, 0.9 and 0.95 were tested. We found that both the CHF and hydraulic fracturing with creep injection can reduce the breakdown pressure by ca. 15 ~ 20% without confining pressure. Two mechanisms could explain the reduction: the influence of fluid infiltration within the theory of linear poroelasticity and stress corrosion within the subcritical crack growth theory. The lifetime of the granite cores subjected to creep injection is comparable with previous CHF experiments employing the same pressure ratio. In addition, the lifetime increases logarithmically when the ratio of CBP/MBP is decreased. This relationship has a high regression coefficient of R2 = 0.97, and the lifetime can be well predicted using a stress corrosion index of 70. On the contrary, CHF shows a significantly larger variance in the lifetime with a regression coefficient of R2 = 0.19 and, therefore, is hard to predict. Our results also point out that the injection scheme can modify hydraulic fracture patterns, in terms of fracture aperture, branching, and fracture propagation. Highlights: Creep, cyclic, and monotonic injection are compared to understand the fatigue hydraulic fracturing of granite cores. Breakdown pressure was reduced and fracture branching was created through fatigue hydraulic fracturing. Fluid infiltration significantly affects hydraulic fracture propagation for long-duration fluid injection. The subcritical crack growth theory can well predict the lifetime of granite subjected to creep injection but not for cyclic injection. [ABSTRACT FROM AUTHOR]

Bi-adhesive repair method is one of several repair technologies that use the adhesive bonding approach for patch-repaired composites. However, these repairs are subject to matrix-cracking and interface debonding damage. Furthermore, a change in the length ratio (the length of the rigid adhesive region divided by the length of the overall repaired region) also produces a change in the damage modes, which has a significant impact on the repair performance. Hence, this study aims to evaluate the effects of four different length ratios (0, 0.2, 0.5, 1) on the behavior of damage evolution in bi-adhesive repaired composites. The acoustic emission damage identification and micro-CT characterization are carried out based on the machine learning method. A simple prediction method is employed to distinguish damage modes in bi-adhesive repaired composites, achieving a prediction accuracy over 90%. The results demonstrated that the length ratio has a substantial effect on matrix-cracking, fiber-matrix debonding, and their interaction in bi-adhesive repaired composites. These acquired characteristics information of acoustic emission signals provide insights into the impact of length ratio on the progression of damage evolution. Additionally, the visualization of interior damage offers insights into the variations in failure characteristics within distinct bi-adhesive repaired composites, thereby supporting the conclusions gained from acoustic emission studies. This research effectively achieves the real-time monitoring of damage modes in bi-adhesive repaired composites, contributing to the comprehension of the relationship between length ratio and damage mechanism. [ABSTRACT FROM AUTHOR]

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Fracture–cavity carbonate reservoirs account for a considerable proportion of oil and gas resources. Because of the complicated relationships between cavities, fractures and pores in these reservoirs, which are defined as cavity clusters, fracturing technology is employed to enhance their hydrocarbon productivity. However, almost all previous studies have just considered the effect of a single natural cavity or fracture on the propagation of a hydraulic fracture; therefore, the mechanism by which a hydraulic fracture interacts with a cavity cluster needs to be clarified. In this study, cavity clusters with different distributions were accurately prefabricated in synthetically made samples, and large-scale simulation equipment was employed to systematically perform fracturing experiments considering different horizontal differential stress levels. Meanwhile, the hydraulic fracture propagation behaviors were comprehensively analyzed through fracture morphology, fracturing curves, the complexity of the fracture network and acoustic emission monitoring. It was found that a natural fracture with a smaller approach angle is favorable in guiding a hydraulic fracture to a cavity. The fracturing curves were divided into the following four types: frequent fluctuations with "step-like" shapes, great fluctuations with slightly lower closure pressure, fluctuations with obviously lower closure pressure, and little fluctuations with obviously lower closure pressure. And different cavity cluster distributions play a dominant role in the complexity of generated hydraulic fracture networks. In addition, AE energy was used to judge the ease of crossing the cavity. The above findings indicated that for the actual exploration and exploitation of carbonate reservoirs, the geological exploration of different fracture–cavity structures in reservoirs would be required, and targeted fracturing engineering designs need to be carried out for different fracture–cavity carbonate reservoirs. [ABSTRACT FROM AUTHOR]

Rockmass in deep mining is highly susceptible to large-scale collapses under high stress and blast-induced disturbances, leading to casualties and economic losses. To investigate the evolution characteristics of goaf instability and the types of seismic sources that induce instability, an experiment on goaf instability was designed under uniaxial compression conditions based on actual mining operations. The entire experimental process was monitored using digital image correlation analysis and acoustic emission monitoring. By calculating the digital speckle field on the surface of the rock specimen during the experiment, the evolution characteristics of the deformation and strain fields from the beginning of loading to complete failure were analyzed. The study explored the dynamic behavior of cracks from initiation to propagation and eventually inducing large-scale collapse. The results show that the instability process of the goaf begins with the formation of tensile cracks. As stress increases, shear cracks occur in the specimen, leading to macroscopic failure. Furthermore, based on the differences in overall microfracture types measured by RA-AF characteristic parameters during specimen failure, large amplitude acoustic emission events corresponding to the formation of dominant macroscopic cracks were selected, and the focal mechanisms of these events were inverted. The results indicate that shear failure sources are significantly more prevalent than tensile failure sources in acoustic emission events leading to goaf instability. These findings can provide useful guidance for the support design and the prevention and control of rockmass instability disasters.

In this article, the results of the study on the physicochemical characteristics of some liquid organic matters on the kinetics of their high-temperature oxidation (combustion) were presented for the first time. These results were obtained by the method of acoustic emission spectrum from heat source. The research results of the amplitude-time characteristics (until cessation of combustion completely) and the frequency response functions (in a given frequency range) of oxidation (combustion) process of liquid organic matters showed that there are following unambiguous dependences: 1) the dependences of the number of the amplitude maximum of the frequency and time spectrum in a given frequency range, as well as of the fractal dimension of the received acoustic signal on the number of carbon atoms in the carbon frame of organic matters and their molar mass; and 2) the dependences of the time of beginning of the combustion (ignition) of primary cloud of organic matters vapors and the final combustion time of the primary cloud of organic matters vapors on the number of carbon atoms in the carbon frame of the organic matters and their partial vapor pressures. The practical aspect of using the results obtained is dictated by the need to develop standard samples of amplitude-time and amplitude-frequency characteristics, depending on the physicochemical and combustible properties of the organic matters. This is necessary for the data bank of the acoustic emission monitoring system to establish a fire hazardous state and make anti-crisis decisions at critical infrastructure facilities. [ABSTRACT FROM AUTHOR]

In this study, an embedded cement-based piezoelectric sensor based on a spherical piezoelectric ceramic shell was designed, fabricated, and characterized. Compared with the conventional piezoelectric acoustic emission sensor (PAES), which is based on sheet piezoelectric ceramics and can receive signals only in a specific direction, the novel embedded cement-based spherical piezoelectric sensor (CSPS) has the potential for omnidirectional signal reception. The frequency response range of the embedded CSPS, tested using the pencil-lead break test, is 70–600 kHz, which can meet the requirements of acoustic emission testing of concrete structures. Thus, the four-point bending test of the concrete beam was monitored using the acoustic emission technique. The concrete beams with two failure modes, bending and compression–shear failure, were created. During the four-point bending test, the CSPS embedded into the concrete beams and the commercial PAES externally placed on the surface of the concrete structure were used for acoustic emission monitoring. Data such as acoustic emission amplitude, b-value, and fractal dimension were measured using the embedded CSPS and analyzed and compared using the external commercial PAES. The results showed that the data measured using the embedded CSPS are highly consistent with those measured using the external PAES. Notably, at the late stage of the experiment, the number of low amplitude signals measured using the embedded CSPS was several times higher than that measured using the external PAES, which demonstrates that the sensitivity of the embedded CSPS is better than that of the external commercial PAES. Furthermore, the curve of the b-value and fractal dimension of the two kinds of sensors (the embedded CSPS and the external PAES) showed evident phased characteristics in different loading stages. In the bending failure test of the concrete beam, the trend of the curve of the fractal dimension can be divided into three stages, which correspond to the three stages of bending failure. Moreover, when the b-value keeps decreasing and becomes stable at a low level, it indicates that the concrete beam has entered the final yield failure stage. Furthermore, the transformation of each failure stage is accompanied by a sudden increase in energy. In the compression–shear failure test of the concrete beam, the steep drop in the b-value and fractal dimension indicates the development and connection of large fractures. Therefore, these indices dynamically reflect the evolution of structural damage and can be used as an early warning index for the final failure of the concrete beam. Compared with the acoustic emission location results calculated by the commercial PAES, the number of acoustic emission location results calculated using the embedded CSPS was greatly increased, which effectively improved the accuracy and sensitivity of damage location analysis.

In the framework of the STIMTEC and STIMTEC-X hydraulic stimulation experiments at the Reiche Zeche mine, Freiberg (Germany), we installed acoustic emission (AE) sensors for the recording of picoseismicity both conventionally using pneumatic coupling and experimentally like a hydrophone, i.e. the sensors were placed in the borehole without a further coupling system or cementing. We investigate performance measures of the hydrophone-like acoustic emission (HAE) sensors such as frequency bandwidth, sensitivity, first motion polarity, coupling and placement quality to assess the sensor's applicability in adaptive monitoring networks. HAE sensors can be paired with hydraulic equipment, especially with the double packer probe used for stimulation at the decametre scale because the monitored frequency content differs from injection-related noise. This offers a unique opportunity to improve the network geometry and consequently the quality of a seismic catalogue. We analyse the sensor characteristics using active ultrasonic transmission measurements from boreholes with different orientations in the rock volume, noise measurements preceding active centre punch hits in the access galleries and passive recordings of induced acoustic emission events. HAE sensors placed in water-filled boreholes show good sensitivity performance even without optimal coupling to the crystalline rock for recording distances up to 17 m. The HAE sensors record the wavefield adequately for first-arrival identification, polarity picking and amplitude characteristics but are less suitable for detecting S-waves. Due to the borehole geometry HAE sensors record waves with incidence angles from the side, resulting in opposite polarity compared to side-view AE sensors as observed in the field and lab. We discuss the advantages of adaptive monitoring networks with HAE sensors being optimally placed for each stimulation interval configuration anew to improve seismic event detection and quality of event hypocentre locations during hydraulic stimulations. We show that we are able to significantly reduce the azimuthal gap, halve the location uncertainties and improve the network coverage for the purpose of focal mechanism estimations. Highlights: An adaptive network comprising acoustic emission (AE) sensors installed both conventionally by pneumatic coupling and like hydrophones was used to significantly improve detection and localisation quality. Hydrophone-like AE-sensors placed in water-filled boreholes show good sensitivity performance for recording distances up to 17 m in crystalline rocks. Hydrophone-like AE-sensors can be combined with hydraulic equipment because the monitored frequency content differs from injection-related noises. Pairing of the hydrophone-like AE sensors with hydraulic equipment offers a simple yet effective means to improve the network geometry. [ABSTRACT FROM AUTHOR]

The timely diagnosis of defects at their incipient stage of formation is crucial to extending the life-cycle of technical appliances. This is the case of mechanical-related stress, either due to long aging degradation processes (e.g., corrosion) or in-operation forces (e.g., impact events), which might provoke detrimental damage, such as cracks, disbonding or delaminations, most commonly followed by the release of acoustic energy. The localization of these sources can be successfully fulfilled via adoption of acoustic emission (AE)-based inspection techniques through the computation of the time of arrival (ToA), namely the time at which the induced mechanical wave released at the occurrence of the acoustic event arrives to the acquisition unit. However, the accurate estimation of the ToA may be hampered by poor signal-to-noise ratios (SNRs). In these conditions, standard statistical methods typically fail. In this work, two alternative deep learning methods are proposed for ToA retrieval in processing AE signals, namely a dilated convolutional neural network (DilCNN) and a capsule neural network for ToA (CapsToA). These methods have the additional benefit of being portable on resource-constrained microprocessors. Their performance has been extensively studied on both synthetic and experimental data, focusing on the problem of ToA identification for the case of a metallic plate. Results show that the two methods can achieve localization errors which are up to 70% more precise than those yielded by conventional strategies, even when the SNR is severely compromised (i.e., down to 2 dB). Moreover, DilCNN and CapsNet have been implemented in a tiny machine learning environment and then deployed on microcontroller units, showing a negligible loss of performance with respect to offline realizations. [ABSTRACT FROM AUTHOR]

In this study, the failure behavior of laminated composite plates subjected to anticlastic bending is investigated. Anticlastic bending is a special case of bi-axial out-of-plane loading that produces predominantly twisting moment. A test fixture is designed to actualize anticlastic loading condition. Carbon-fiber-reinforced epoxy composite is selected as the material of the specimens. Totally nine different layup configurations are chosen and at least four specimens are tested for each configuration. Acoustic emission monitoring (AEM) is utilized to detect the first-ply-failure load and the accumulation of damage in the laminates. In this method, elastic waves resulting from initiation and progression of damage are detected, and then AE signals are processed to identify the failure modes and determine the first-ply-failure load. A finite element model is developed to simulate the anticlastic bending test. A code is developed using ANSYS parametric design language to predict the first-ply-failure loads using various failure criteria like Tsai-Wu, Hashin, and Puck. The experimental and numerical results are then compared. Relative strengths and weaknesses of the failure criteria in estimating failure of laminated composite plates under anticlastic bending are discussed. [ABSTRACT FROM AUTHOR]

Under the action of long-term service and external environment, asphalt pavement will have a variety of complex damage and destruction, affecting its service function and life. The biggest advantage of acoustic emission (AE) technology is that it can characterize and analyze the whole process of material damage and failure from the microscopic point of view. Therefore, the characterization and evaluation method of asphalt pavement materials based on the combination of AE technology (micro) and mechanical test method (macro) has attracted the attention of researchers. This paper reviews and summarizes the research status of AE technology in the performance characterization of asphalt pavement, classifies and details the application of AE technology in asphalt mixture and asphalt binder respectively, and puts forward the future research direction and key problems to be solved in this field. In future studies, researchers should pay attention to the generation and propagation mechanism of AE sources in asphalt pavement materials, and establish corresponding simulation methods to explore the AE characteristics inside asphalt pavement. The theoretical relationship between AE parameters and mechanical parameters should be established to characterize the pavement performance of asphalt mixture from different scales. Modern signal processing technology and algorithm should be applied to AE signal analysis and source location, and a variety of non-destructive testing methods should be integrated to evaluate the performance of asphalt pavement. In the field monitoring, filtering and de-noising methods should be adopted to obtain the AE signals that can reflect the pavement damage and fracture. [ABSTRACT FROM AUTHOR]

Laminar argillaceous limestone continental shale is an important oil reservoir in Jiyang Depression, Bohai Bay Basin of China. Affected by the laminar structure, the spatial propagation morphology of hydraulic fracturing is not clear. To reveal the propagation law of hydraulic fracturing pathway in laminar marl continental shale, the mineral content and basic rock mechanics test are firstly carried out on the cores from the wells in Jiyang Depression. Secondly the similar material cores with standard-size and large-size are manufactured and processed. Finally, combined with physical model experiments, acoustic emission and moment tensor inversion techniques, the hydraulic fracturing experiments on the large-size cores under different stress differences are conducted. The experimental results show that the in situ stress (confining stresses), laminar structure, and lithological distribution jointly affect the propagation mode of fractures. As the horizontal stress difference increases, the stimulated reservoir volume gradually decreases, and the number of shear fractures decreases accordingly. Macroscopically, the pump pressure curve shows obvious fluctuation in the case with lower horizontal stress difference, which is the external performance of hydraulic fracture initiation–obstruction–turning–penetrating–obstruction–turning. The content of brittle and plastic minerals has a significant impact on the fracture complexity, particularly the layers with high argillaceous content have a significant inhibitory effect on fracture propagation. The weakly cemented lamination or bedding plane is easy to capture the fracture and make it propagate along the bedding plane, thereby increasing the complexity of fracture network. The research results are expected to provide a theoretical reference for design and optimization of hydraulic fracturing parameter in continental shale oil exploration and development.

The durability of prestressed concrete structures built between the 1950s and 1980s is becoming a growing problem. One reason is the sensitivity to stress corrosion cracking of the prestressing steel. Failure of prestressing wires can result in collapse of the entire structure without premature indication by transverse bending cracks or considerable deformation. The response of a structure to significant number of prestressing wire breaks was studied on a bridge in Brandenburg, Germany. Two thirds of the prestressing wires in concentrated tendons of two girders were cut before the bridge was demolished. Acoustic Emission Analysis was used to detect the wire breaks. Thus, the number of wire breaks was correlated with results of other measurement techniques, in particular strain measurements on the girders. In preparation of the measurements, the acoustic properties of the bridge were determined and the suitability of Schmidt hammer impacts as an acoustic reference source was validated.

A series of experimental tests were performed in this study to evaluate the static and cyclic loading behaviour of steel reinforced concrete (RC) beam specimens configured in different sizes and steel corrosion levels. Acoustic emission (AE) and digital image correlation (DIC) measurements were carried out to monitor the loading process of these beams, with particular focus on examining the load-induced cracking behaviours and failure modes under the influence of reinforcement corrosion. Experimental findings revealed that, as a consequence of steel rust expansion and the corresponding reactionary confinement in concrete, a small amount of corrosion (approximately 6 % of steel mass loss in this study) increased load-bearing capacity of beam specimens by 8–12 %. Further increase of corrosion to 10–15 % was observed to have significantly changed the steel-concrete bond behaviour in the specimens, and subsequently alter the failure mode of the shear-critical specimens to flexure-controlled. Additionally, AE data analysis successfully revealed the concrete cracking modes in the specimens when loaded. Data analysis results suggested that the corroded specimens emitted AE signals with higher average frequency (AF) values but lower rise angle (RA) values in comparison to the control specimens, regardless of the variations in specimen type and monitoring setup. • Effect of corrosion on cracking and failure of RC beams were assessed by mechanical load integrated with AE and DIC. • Marginal increase of beam load-bearing capacity was observed for corrosion of up to 6% by steel mass loss. • Beam failure mode changed from shear-critical to flexure-controlled when corrosion was above 6%. • Regardless of specimen type and test setup, the corroded beams gave higher AF but lower RA values than the control beams. [ABSTRACT FROM AUTHOR]

The formation of exit burrs during the drilling of ductile metals such as aluminum is critical in precision manufacturing and manufacturing automation. Because drilling burrs are difficult to remove, methods to predict various burr types and/or implement burr minimization schemes that consider the various attributes of burrs must be devised. In this study, not only drilling process conditions, including feed, cutting speed, and drill diameter, but also an artificial neural network is implemented to predict the formation of burrs during the drilling of aluminum-7075, which is widely used in the aerospace and automobile industries. Based on the drilling conditions, the main exit burr characteristics, such as burr size and type, were classified experimentally. Three different types of exit burrs (uniform burrs, uniform burrs with caps, and transient burrs) were observed from the aluminum 7075 workpieces. The classification results were further analyzed using burr control charts and an empirical equation, which enables the understanding of the overall influence of the drilling conditions over the burr types. Moreover, acoustic emission (AE) sensor monitoring scheme was utilized to sample the sensitive time-series signals during drilling burr formation. Subsequently, burr types were predicted using artificial intelligence techniques, namely machining learning and deep learning. First, backpropagation (BP) neural networks were constructed using the drilling conditions and AE signals as input vectors. For a comparative prediction, a convolution neural network (CNN) was implemented to obtain spectrogram image inputs from the sampled AE data. The proposed scheme is useful in predicting drilling burr types by employing a sensitive sensor monitoring setup and advanced artificial intelligence techniques, where both prediction results are well matched with experimental results. In addition, the CNN model shows effectiveness for a commonly practiced manufacturing process as it predicts the burr types with better accuracy than the BP network model (0.9375 over 0.8571).

Selective laser melting (SLM) additive manufacturing overcomes the geometric limits of complex components produced with traditional subtractive methods, which has significant advantages in designing and manufacturing special-shaped components. However, due to the lack of adequate and effective process monitoring, it is difficult to ensure the reliability of as-built parts and the stability of the additive manufacturing process. Therefore, it is necessary to monitor the as-built part quality of the SLM process. An in situ quality monitoring method of acoustic emission (AE) based on machine learning and improved variational modal decomposition (VMD) is proposed in the present work. The VMD parameters are adjusted based on the whale optimization algorithm (WOA) and average energy entropy to realize the adaptive decomposition of the AE signals. Each sub-mode is evaluated according to the signal energy, the feature vector used for SLM printing quality prediction is extracted. Finally, the artificial neural network (ANN) and support vector machine (SVM) are employed for quality prediction. The improved VMD method is compared with empirical modal decomposition (EMD), aiming to verify the predictive validity of printing quality in the SLM process. The results show that predicting SLM printing quality based on improved VMD is better than the EMD method. Meanwhile, it is verified that online monitoring of SLM for improving printing quality can be achieved based on the AE technique. [ABSTRACT FROM AUTHOR]

Recent environmental guidance in the cultural heritage field reflects the increasingly important objectives of sustainability and reduced carbon footprint. New and revised guidance from organisations such as the Bizot Group, IIC/ICOM-CC, AICCM, and ASHRAE share common principles, including consideration of passive low-energy environmental control methods, adoption of realistic target conditions given the building envelope and exterior climate, and support for broader environmental parameters for many classes of objects. Motivated by an interest in energy savings and security, as well as broad organisational involvement and buy-in for implementing environmental change, the National Gallery of Victoria (NGV) in Melbourne, Victoria, is adopting the Bizot Green Protocol (BGP) for its collection and for outgoing loans. Initial NGV trials of a transitionary 'soft Bizot' setting – temperature between 20°C and 23°C with 24-hour fluctuations of no more than ±1.5°C and relative humidity between 46% and 56% with 24-hour fluctuations of no more than ±4% – demonstrated reduced energy use. The NGV and the Getty Conservation Institute are collaborating to examine object response during this environmental transition. In addition to visual monitoring of several works in the collection using macrophotography, acoustic emission (AE) monitoring will be carried out on a Flemish retable consisting of carved and polychromed wood and oil paint. AE monitoring is a highly sensitive technique that measures energy, in the form of transient elastic waves, released by and propagated through a material such as wood that has undergone brittle cracking. This has the potential benefit of detecting environmentally induced micro-changes in an object before damage is visible to the viewer. [ABSTRACT FROM AUTHOR]

The timely diagnosis of defects at their incipient stage of formation is crucial to extending the life-cycle of technical appliances. This is the case of mechanical-related stress, either due to long aging degradation processes (e.g., corrosion) or in-operation forces (e.g., impact events), which might provoke detrimental damage, such as cracks, disbonding or delaminations, most commonly followed by the release of acoustic energy. The localization of these sources can be successfully fulfilled via adoption of acoustic emission (AE)-based inspection techniques through the computation of the time of arrival (ToA), namely the time at which the induced mechanical wave released at the occurrence of the acoustic event arrives to the acquisition unit. However, the accurate estimation of the ToA may be hampered by poor signal-to-noise ratios (SNRs). In these conditions, standard statistical methods typically fail. In this work, two alternative deep learning methods are proposed for ToA retrieval in processing AE signals, namely a dilated convolutional neural network (DilCNN) and a capsule neural network for ToA (CapsToA). These methods have the additional benefit of being portable on resource-constrained microprocessors. Their performance has been extensively studied on both synthetic and experimental data, focusing on the problem of ToA identification for the case of a metallic plate. Results show that the two methods can achieve localization errors which are up to 70% more precise than those yielded by conventional strategies, even when the SNR is severely compromised (i.e., down to 2 dB). Moreover, DilCNN and CapsNet have been implemented in a tiny machine learning environment and then deployed on microcontroller units, showing a negligible loss of performance with respect to offline realizations.

Externally bonded fiber-reinforced polymer (FRP) composites are commonly used to retrofit concrete beams in shear. However, debonding failure limits the effectiveness of such a system. Mechanically anchored systems eliminate the debonding mode of failure, which maximizes the effectiveness of the retrofit system. This study investigates the effectiveness of using a modified mechanical anchor to strengthen concrete T-beams in shear. The fabrication and design details of this system are discussed. Three reinforced concrete (RC) T-beams were tested up to failure under a four-point bending test to assess the effectiveness of the proposed retrofit system. One beam was tested as a control beam, while two beams were strengthened in shear using mechanically anchored dry carbon fiber (CF) sheets. The tested beams were instrumented with conventional instruments to monitor the load, strain, displacement, and acoustic sensors to monitor the damage initiation, progression, and location. The modified mechanical anchor retrofit system increased the shear capacity by up to 22 %. The acoustic emissions (AE) monitoring of the tested T-beams was able to detect the locations of the cracks that caused the failure of the beams. [ABSTRACT FROM AUTHOR]

Laser-assisted machining has been studied for more than 30 years. However, the research is still in the laboratory research stage. The fundamental reason is that the constant plastic machining can not be realized. So, to realize the real-time pattern recognition of plastic machining state, brittle machining state and thermal damage state is the key to the success, and also the bottleneck problem to be solved. In this paper, a real-time recognition method of machining state by detecting the acoustic emission signal of machining process is proposed. The mapping relationship between the acoustic emission signal of laser-assisted machining of silicon nitride ceramics and the machining state is found. The energy ratio coefficient of the frequency band of 0 kHz ∼ 19.53125 kHz and the root mean square are extracted as the characteristic parameters used to characterize and identify the machining state. The pattern recognition model of machining state is constructed. [ABSTRACT FROM AUTHOR]

• A new separation rolling-sliding shear device for rock structural plane under true triaxial condition was developed. • An improved simplex acoustic emission spatial localization method was proposed to well reveal disturbance shear fracture evolution. • With connectivity increasing, disturbance shear strength and failure surface roughness of structural plane gradually decreases. • During disturbance shear fracture process, micro-tensile cracks dominate, and the micro-shear crack proportion continues to increase. • On the verge of disturbance shear failure, acoustic emission parameters (Dt , b -value, dominant frequency) change dramatically. The mechanisms, processes, and precursors of shear failure in rock structural planes under three-dimensional geostress and excavation disturbances are unclear, which poses challenges for disaster prediction and warning in underground rock engineering. Therefore, this study self-developed a new separation rolling-sliding shear device for rock structural plane under true triaxial condition, and proposed a true triaxial shear testing method to simulate the damage of rock structural plane induced by the three-dimensional geostress redistribution during engineering excavation and subsequent dynamic disturbance further triggering failure. True triaxial disturbance shear tests were conducted on intermittent structural planes with different connectivity. With connectivity increasing, disturbance shear strength and failure surface roughness of structural planes gradually decreases. An improved simplex acoustic emission spatial localization method was proposed to reveal disturbance shear fracturing evolution. During disturbance shear fracturing process, micro-tensile cracks dominate, and the proportion of micro-shear cracks continues to increase, showing a mixed tensile-shear fracture mechanism. Approaching to disturbance shear failure, the acoustic emission fractal dimension decreases rapidly then increases to the maximum value, the b -value decreases rapidly to less than 1, the rapid increase in LgN / b exceeds 3, and the low-frequency and high-amplitude dense fracture signal appears abundantly, which can be used as disturbance failure precursors of intermittent structural planes. [ABSTRACT FROM AUTHOR]

To address the challenges posed by the excessive exploitation of natural river sand, manufactured sand (MS) was used as a substitute material for natural sand to produce manufactured sand-based ultra-high performance concrete (UHPMC). This study aims to investigate the effects of MS replacement ratio, stone powder content, steel fiber content, and steel fiber shape on the fracture characteristics and damage evolution of UHPMC under tensile load through tensile tests combined with acoustic emission (AE) technology. The research results indicated that the stress-strain behavior of UHPMC could be divided into low strain hardening, low strain softening, and high strain softening. The tensile strength and energy absorption of the UHPMC were less correlated with MS replacement ratio. The tensile strength showed a trend of first increasing and then decreasing with the increase of stone powder content, and UHPMC with a 4% stone powder content presented the better tensile strength. The tensile damage process of UHPMC was mainly concentrated in the range of tensile strain from 0.0002 to 0.0025. The microstructure analysis of the UHPMC matrix revealed that an optimal amount of stone powder enhances the bond property between MS and mortar, thereby improving tensile performance. AE monitoring indicated that AE amplitude and AE energy provide sensitive identification capabilities for classifying the elastic state, strain hardening, and strain softening stages of UHPMC. The findings of this study contribute to understanding the fracture characteristics and damage evolution of UHPMC, promoting the engineering application of MS in ultra-high-performance concrete. • Fracture characteristics and damage evolution of UHPMC are evaluated by direct tensile tests and AE monitoring. • The developed UHPMC is categorized into low strain hardening, low strain softening, and high strain softening. • A stone powder content of 8% to 12% contributes to enhancing the compactness of the ITZ and achieving strain hardening. • AE amplitude demonstrates a satisfactory capability to identify the different damage stages of UHPMC under tension. [ABSTRACT FROM AUTHOR]

Void defects can reduce the mechanical properties of composites and increase the potential danger of composite components in service. The effects of various porosities on damage evolution behaviors of carbon fiber/epoxy composites are deeply investigated by combining the damage visualization and acoustic emission response. The results showed that the increased porosity accelerates the damage evolution from micro-scale to macro-damage. Acoustic signals in composites are captured in advance when the porosity is high, and the voids below the kink band accelerate matrix cracking and delamination, while specimens with low porosity easily cause fiber damage and fiber/matrix debonding. Additionally, applying extra pressure during the resin transfer molding process can decrease the porosity, but excessive extra pressure may result in an inverse result. The method combining acoustic emission and micro-CT can provide a reference for improving quality and the health monitoring of composites. [ABSTRACT FROM AUTHOR]

Based on the actual monitoring data of the acoustic emission (AE) ground pressure monitoring and positioning system, this paper introduces fractal theory and the multifractal detrended fluctuation analysis (MF-DFA) method to estimate the waveform multifractal spectrum of goaf rock acoustic emission signals and investigate multifractal time-varying response characteristics. The research results show that the wavelet hard thresholding method has the best noise reduction effect on the original signal, and the box counting dimension has a strong waveform identification effect. Before deformation damage occurs, fractal spectral width Δα shows an increase and then decrease and the fluctuation scale factor Δf(α) decreases and then increases. When damage occurs, fractal spectral width Δα decreases and then stabilizes and concentrates. Simultaneously, the fluctuation scale factor Δf(α) keeps decreasing until the lowest point, and then shows an increasing trend until it reaches a stable state. This study is of great significance to the stability evaluation and disaster early warning of mine goaf. [ABSTRACT FROM AUTHOR]

Founded on understanding of a slope's likely failure mechanism, an early warning system for instability should alert users of accelerating slope deformation behaviour to enable safety-critical decisions to be made. Acoustic emission (AE) monitoring of active waveguides (i.e. a steel tube with granular internal/external backfill installed through a slope) is becoming an accepted monitoring technology for soil slope stability applications; however, challenges still exist to develop widely applicable AE interpretation strategies. The objective of this study was to develop and demonstrate the use of machine learning (ML) approaches to automatically classify landslide kinematics using AE measurements, based on the standard landslide velocity scale. Datasets from large-scale slope failure simulation experiments were used to train and test the ML models. In addition, an example field application using data from a reactivated landslide at Hollin Hill, North Yorkshire, UK, is presented. The results show that ML can automatically classify landslide kinematics using AE measurements with the accuracy of more than 90%. The combination of two AE features, AE rate and AE rate gradient, enable both velocity and acceleration classifications. A conceptual framework is presented for how this automatic approach would be used for landslide early warning in the field, with considerations given to potentially limited site-specific training data. [ABSTRACT FROM AUTHOR]

• Verification of the monitoring effect of acoustic emission sensors arranged on the sheaths of the cables. • Preferred acoustic emission characterization parameters for monitoring damage to cables. • Quantitative expression of acoustic transmission coefficients for different thicknesses of sheaths. • A circumferential attenuation model of the cable was constructed. • The sensor arrangement method is proposed for the different damage signals of the cable. Cable is one of the important components of cable-stayed bridges, there are three common damages: broken wire, corrosion and fatigue. High-density polyethylene (HDPE) sheaths will induce the attenuation of acoustic emission (AE) signals of damage to cables. Therefore, three cables with different wire counts are used for AE monitoring. The relationship between the thickness and the AE transmittance coefficient of HDPE sheaths, and a circumferential AE attenuation model are established for each cable. According to the transmittance coefficient and circumferential attenuation model, a sensor arrangement method for monitoring the wire breakage, corrosion, and fatigue of cables is quantitatively given. The results show that the transmission coefficient linearly decreases with an increase in HDPE sheath thickness with a slope of approximately 0.012. The circumferential AE amplitude attenuation rates for the three types of cables are 9.9%, 18.74%, and 21.13%, respectively. Monitoring the wire breakage requires only one sensor; monitoring corrosion and fatigue damage only requires one sensor for the 61-strand cable, symmetrical-arrangement two sensors for cables with 349 and 547 strands. [ABSTRACT FROM AUTHOR]

In this study, a novel setup for a nanoscale finishing process - magnetic abrasive finishing (MAF) - was investigated together with in-process monitoring using acoustic emissions (AE). A specially fabricated direction control piece with a neodymium magnet was attached to an MAF setup to perform surface finishing of thin-film (IZO) coated Pyrex glass workpieces within a selective area. For the selective finishing experiments, design of experiment (DOE) was applied to optimize the surface roughness of the workpieces. In addition, an acoustic emission (AE) sensor, which can effectively monitor surface roughness and process states during ultraprecision machining/polishing of nanoscale workpieces, was adopted to detect the depth of the polished surface during MAF. The experimental results show that the proposed MAF setup produces uniform surfaces with nano-level surface roughness in a confined (target) area. Moreover, AE monitoring appears to have strong correlations with process states and sufficient sensitivity to detect the critical thickness (the end point of the coating layer). The processed AE signals were utilized as input parameters for an artificial neural network (ANN) to determine whether the polishing was reached to the coating-substrate (Pyrex) boundary. With the proposed polishing and monitoring scheme, controlled nano-finishing of a thin film coated material are feasible in a selective area within specific thickness/layer.

Based on the actual monitoring data of the acoustic emission (AE) ground pressure monitoring and positioning system, this paper introduces fractal theory and the multifractal detrended fluctuation analysis (MF-DFA) method to estimate the waveform multifractal spectrum of goaf rock acoustic emission signals and investigate multifractal time-varying response characteristics. The research results show that the wavelet hard thresholding method has the best noise reduction effect on the original signal, and the box counting dimension has a strong waveform identification effect. Before deformation damage occurs, fractal spectral width Δα shows an increase and then decrease and the fluctuation scale factor Δf(α) decreases and then increases. When damage occurs, fractal spectral width Δα decreases and then stabilizes and concentrates. Simultaneously, the fluctuation scale factor Δf(α) keeps decreasing until the lowest point, and then shows an increasing trend until it reaches a stable state. This study is of great significance to the stability evaluation and disaster early warning of mine goaf.

However, the value of crack closure stress ( I i SB cc sb ) and crack initiation stress ( I i SB ci sb ) will be clearly changed by small fluctuations of Poisson's ratio. If the stress level is higher than the crack damage stress ( I i SB cd sb ) but lower than peak strength ( I i SB f sb ), cracks will propagate continuously and coalescence to reach macroscopic failure. 6 Curves of lateral strain difference for a siliceous siltstone and b limestone Moving Point Regression Method (MPR) Eberhardt et al. ([4]) proposed a new method to obtain the crack closure stress ( I i SB cc sb ) and the crack initiation stress ( I i SB ci sb ). If the stress level is higher than crack initiation stress ( I i SB ci sb ) but lower than crack damage stress ( I i SB cd sb ), cracks randomly initiated but they will cease at a certain length without coalescence. [Extracted from the article]

Featured Application: Damage assessment of a reinforced concrete (RC) by means of different nondestructive testing (NDT) techniques. Joined application of a PZT sensor network for AE-based local damage detection and a FOS setup for global strain mapping. Coupling of local and global methods through DIC-based strain localization to reduce the uncertainty on the strain field description. Potential for AE- and strain-based damage detection in large structures of interest to civil engineering. This paper presents the structural and damage assessment of a reinforced concrete (RC) beam subjected to a four-point bending test until yielding of reinforcing steel. The deterioration progress was monitored using different nondestructive testing (NDT) techniques. The strain was measured by distributed fiber optic sensors (FOSs), embedded prior to concrete pouring. The initiation and propagation of cracks were monitored by acoustic emission (AE) sensors attached to the surface of the material. The recorded AE activity results in good agreement with FOS strain measurements. The results of the integrated monitoring system are confirmed by visual observation of the actual crack pattern. At different loading steps, digital image correlation (DIC) analysis was also conducted. [ABSTRACT FROM AUTHOR]

Based on a 10-year climate survey for Oklahoma City, OK, three exposure regimens were devised: cyclic high temperature exposure, cyclic freezing-and-thawing exposure, and cyclic wetting-and-drying exposure. A total of four different test methods were compared to determine the extent of damage induced by the exposure mechanisms. Two standard nondestructive methods--ultrasonic pulse velocity and resonant frequency--were compared along with compression load testing. It was found that resonant frequency testing was more sensitive to microcrack formation. All methods discerned a change in properties after 30 cycles of freezing-and-thawing exposure. Interestingly, all three exposure regimens demonstrated a similar extent in degradation after 90 exposure cycles; however, high temperature and wet-dry cyclic exposure induced further damage than freezing-and-thawing-induced damage. Moreover, acoustic emission (AE) monitoring was performed during mechanical loading. A simple AE parameterbased evaluation confirmed the presence of material distress as that found for the destructive and nondestructive evaluation. [ABSTRACT FROM AUTHOR]

Acoustic emission (AE) monitoring has become an optional technology to quantify slope deformation. However, there are still challenges in developing generic AE interpretation strategies. Dynamics and kinematics models are two physical methods for analysing slope stability, which appear to improve the interpretability of AE monitoring data. The aim of this study is to explore the change patterns and interrelations of dynamics, kinematics, and AE measurements using a model test and physical analysis, to further understand the development process of a progressive landslide. A model test is designed based on the kinematics model of landslide three-stage deformation. An equation between factor of safety (FoS) and thrust is proposed based on the mechanical model of a landslide test. There is a clear correspondence between the displacement and inverse velocity during the deformation-controlled process. Relationships are uncovered between the thrust and FoS as well as the thrust and acceleration. As a characteristic parameter of AE, ring down count (RDC) is able to quantify the deformation process of the soil slope. Moreover, acceleration and RDC can reflect the sudden change of the slope state and, hence, can be effective indicators for the early warning in a progressive landslide.

An experimental investigation has been conducted to monitor the cracking process in self-consolidating rubberized concrete (SCRC) beam-column connections with the aid of acoustic emission (AE). Reinforced concrete beam-column connections were cast using various SCRC mixtures containing six different crumb rubber (CR) percentages (0 to 25%) as a replacement of fine aggregates. The investigated connections were tested under reversed cyclic loading conditions and simultaneously monitored via three attached AE sensors per specimen. The AE data from each loading test were analyzed to detect the crack initiation and quantify the crack propagation in all specimens throughout the tests. This analysis involved studying the variations in the signal amplitudes, number of hits, and cumulative signal strength. In addition, b-value and intensity analyses on the signals’ amplitude and strength were completed to generate three additional AE parameters: b-value, historic index (H(t)), and severity (Sr). The influences of both CR content and sensor location on these AE parameters were highlighted. The results of the AE analysis performed herein allowed an early detection of the first cracks before they could be visually observed, regardless of CR percentage. The development of additional cracks due to further loading cycles was found to be associated with an overall increase in AE activities until failure of all tested specimens. Meanwhile, the increase in the CR content resulted in a noticeable reduction in the AE signal amplitudes. Finally, the results of intensity analysis parameters (H(t) and Sr) were used to develop a damage classification chart. This chart can successfully be used to identify the stages of first crack initiation and ultimate load in the SCRC beam-column connections. [ABSTRACT FROM AUTHOR]

This research examined the application of acoustic emission analysis to monitor the crack growth in various concrete mixtures reinforced with synthetic fibers of variable types and lengths under monotonic loading four-point flexural tests. The signals attained from these tests were correlated to the crack development until failure. The study also investigated the impact of varying the synthetic fiber types (flexible and semi-rigid) and lengths on the flexural performance and their corresponding acoustic emission signal parameters. Furthermore, this investigation involved performing b-value and intensity analyses on the signals' amplitude and strength to develop additional acoustic emission parameters. The results of these different acoustic emission analyses enabled an early identification of two stages of damage (microcracking and macrocracking) prior to failure in all mixtures. Both the experimental results and studied acoustic emission parameters indicated that the semi-rigid synthetic fibers exhibited slightly higher average flexural strength than that of the flexible type. Also, the increase in length of synthetic fibers showed an evident improvement in the average flexural strength according to both experimental and acoustic emission signal results. The results also presented a developed damage classification chart that can be used to identify the stages of microcracking and macrocracking in synthetic fiber-reinforced mixtures based on the intensity analysis parameters. [ABSTRACT FROM AUTHOR]

• AE analysis was used to assess the crack growth of ECC beam-column connections under reversed cyclic loading tests. • The effect of fibers type on the performance of the specimens was examined. • AE b-value and intensity analyses were completed to analyze the AE data. • Damage classification chart was developed in terms of intensity analysis parameters. This paper presents the results from an experimental program conducted to assess the cracking behavior of reinforced concrete beam-column connections cast with engineered cementitious composites (ECC). Reversed cyclic loading tests in conjunction with acoustic emission (AE) monitoring were completed on all specimens till failure. Four ECC mixtures containing four different types of fibers along with a control conventional concrete (CC) mixture were tested. The AE data obtained from all tests were filtered and analyzed to identify and evaluate the crack growth in all beam-column connections. First, the changes in the AE parameters such as signal amplitudes, number of hits, and cumulative signal strength were considered. Then, additional b-value and intensity analyses on both signal amplitude and strength were performed to develop three further AE parameters including b-value, historic index (H (t)), and severity (S r). The impact of fibers type and sensor location on the aforementioned AE parameters was examined. The AE analysis completed in this study led to the identification of the first cracks prior to their visual observation, regardless of fibers type and/or sensor location. The studied AE parameters were highly correlated to the process of crack propagation in all specimens until failure. The results also showed that varying the types of fibers in ECC yielded non-significant effect on the AE signal characteristics (in terms of signal amplitudes) throughout the tests. The intensity analysis parameters (H (t) and S r) were eventually used to generate a damage classification chart to classify the stages of first crack and maximum load in the tested specimens. [ABSTRACT FROM AUTHOR]

This study was conducted to examine the influence of vugs on hydraulic fracture propagation, which is very significant for hydraulic fracturing design in fractured-vuggy carbonate reservoirs. In this paper, a series of hydraulic fracturing physical simulation experiments were performed under true triaxial stress states and acoustic emission devices were used to monitor real-time hydraulic fracture propagation. Moreover, the key influencing factors and the typical fracturing curve characteristics of vug-hydraulic fracture interaction were studied and analyzed. The experimental results demonstrated that vugs exert an important effect on hydraulic fracture propagation. Three main vug-hydraulic fracture interaction modes were observed in our experiments: a) the hydraulic fractures directly crossed the vugs, which usually happened for small vugs. b) the vugs arrested the hydraulic fractures for further propagation when the hydraulic fractures tip reached the vugs that are in large size. c) the hydraulic fractures bypassed the vugs by propagating around it, which usually happened under low horizontal stress difference states. Furthermore, the fracturing curve response was obvious when the interaction between vugs and hydraulic fractures occurs. Our research findings provide a reliable basis for optimizing hydraulic fracturing design in fractured-vuggy carbonate reservoirs. • A series of hydraulic fracturing experiments were conducted to examine the effect of vugs on hydraulic fracture propagation. • Three main interaction modes between hydraulic fractures and vugs were observed: crossing, arrest and bypassing. • The vug size and horizontal stress difference play an important role in vug-hydraulic fracture interaction. • The response of fracturing curve characteristics is obvious when vug-hydraulic fracture interaction occurs. [ABSTRACT FROM AUTHOR]

• Damage performance states for CES columns were calibrated using the AE technique. • Sectional strain criteria of damage performance levels for CES columns were proposed. • Statistical damage limit values of CES columns were calculated. Concrete encased steel (CES) columns under low-cyclic lateral loading and high axial compressive ratios were tested using the acoustic emission (AE) monitoring technique to determine their damage performance states. These damage performance states include cover concrete cracking, compressive longitudinal reinforcement yielding, cover concrete crushing or steel flange local buckling, cover concrete spalling, longitudinal reinforcement buckling, and core concrete crushing. Using the test results, a fiber finite element method was calibrated and used to numerically simulate 486 CES columns under lateral loading and determine an empirical expression for the material parameter of the Park-Ang damage model. Use of this modified Park-Ang model in conjunction with the response databank coming from the numerical analysis of the 486 CES columns, finally leads to limit damage values for the damage states of no-damage, minor-damage, medium-damage, serious-damage, and collapse. [ABSTRACT FROM AUTHOR]

• Each studied wood species presents a specific acoustic activity in terms of emissivity and energy. • The acoustic activity is related to the degree of heterogeneity of the species. • The more the species is heterogeneous, the more the acoustic signatures are specific. • The more the species is heterogeneous, the more the signals statistical classification is effective. The use of wood in civil engineering structures, such as timber bridges, has been increasing in recent years. Unfortunately, our knowledge of their behaviour towards sustainability problems is far from complete and it is necessary to develop monitoring techniques like acoustic Emission (AE) that allow early identification of pathologies. This study focuses on the analysis of the influence of wood species on the acoustic response under bending loading. The results of this experimental study show a correlation between AE signal features and certain failure mechanisms but also that these acoustic signatures are different for each timber species. [ABSTRACT FROM AUTHOR]

The purpose of this ISRM Suggested Method is to describe a methodology for in situ acoustic emission monitoring of the rock mass fracturing processes occurring as a result of excavations for tunnels, large caverns in the fields of civil, rock slopes and mining engineering, etc. In this Suggested Method, the equipment that is required for an acoustic emission monitoring system is described; the procedures are outlined and illustrated, together with the methods for data acquisition and processing for improving the monitoring results. There is an explanation of the methods for presenting and interpreting the results, and recommendations are supported by several examples. [ABSTRACT FROM AUTHOR]

Fiber-reinforced polymer composites yield a range of microscopic damage mechanisms even under apparently "simple" load cases, e.g. quasi-static uniaxial tensile tests to failure. Even reducing the fiber-reinforced polymer composite to a single fiber embedded in a matrix will produce several different damage types under quasi-static tensile loading. These are fiber breaks and simultaneous fiber–matrix debonding as well as friction between fiber and debonded matrix, and sometimes, additional matrix cracks. Acoustic emission monitoring of mechanical load tests on material specimens or components is often used to identify the occurrence of damage and attempts at locating the source and identifying the damage mechanism or type in a wide range of materials. The complex damage behavior of fiber-reinforced polymer composites poses a challenge in that respect. Therefore, various approaches (e.g. pattern recognition or neural networks) have been developed to identify the different microscopic damage mechanisms from acoustic emission signals obtained from various load tests. For improved understanding of the damage mechanisms in fiber-reinforced polymer composites as well as for validating the procedures for identifying the types of mechanisms, fiber-reinforced polymer specimens showing a "single dominant damage mechanism", i.e. occurring in significantly larger number than all others, at least in certain stages of damage accumulation or in localized volume elements, can be designed. The contribution discusses and classifies selected examples of single dominant damage mechanism for fiber-reinforced polymer composites and their application. [ABSTRACT FROM AUTHOR]