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The acoustoelastic technique shows considerable potential for in situ stress measurement in concrete. However, the current technology is not fully developed, and challenges primarily arise from the intricate nature of concrete, along with various factors affecting its acoustoelastic properties, such as material strength, aggregate size, porosity, temperature, and humidity. A comprehensive understanding of how these factors influence the acoustoelastic characteristics of concrete is essential for advancing acoustoelastic technology in engineering applications. This study specifically focuses on the material strength, a pivotal factor influencing the quality of concrete, and explores its correlation with the acoustoelastic coefficient (AEC). An initial theoretical investigation was conducted to establish a theoretical model between the two factors, involving two steps: (1) integrating the empirical formula correlating material strength and Young's modulus into the acoustoelastic equations for bulk waves to derive the formula connecting AECs and concrete strengths; (2) applying qualitative analysis and statistical methods to assess the monotonic properties of the formula within its defined domain. To validate the accuracy of the theoretical model, acoustoelastic tests were conducted on prismatic concrete specimens with five different strength levels under axial compressive stress. The findings revealed a consistent pattern, demonstrating that the AECs of concrete decrease with an increase in material strength under axial compressive stress. The outcomes of this study make a substantial contribution to establishing a theoretical foundation for the development of concrete stress monitoring technology based on the ultrasonic method. Practical Applications: The safety of concrete structures is paramount. Currently, structural performance assessment relies primarily on on-site inspections and evaluations by professionals to detect visible cracks and deformations. Typically, cracks become apparent only once the damage has reached a critical level. Failure to identify deterioration processes before reaching this critical stage necessitates significant repairs to prevent premature failure of concrete structural components. If the in situ stress information of structures can be nondestructively obtained would be highly beneficial for warning the early deterioration, tracking the evolution of crack or damage, and forecasting the remaining service life of structures. Acoustoelastic techniques have demonstrated significant potential in achieving this objective. Nonetheless, concrete acoustoelastic effects are influenced by various factors, such as material strength, aggregate size, porosity, and environmental conditions, which impede further advancement of this technology. Therefore, this study investigated the dependence of concrete acoustoelastic effects on material strength. Correlation equations between concrete strength and acoustoelastic coefficients have been formulated. The application of these equations in practice can mitigate the impact of material strength on acoustoelastic measurements. This research contributes to advancing the engineering applications of acoustoelastic techniques in concrete stress assessment. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Donghua University (Natural Science Edition) is the property of Journal of Donghua University (Natural Science) Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

(1) Background: At present, physiological stress detection technology is a critical means for precisely evaluating the comprehensive health status of live fish. However, the commonly used biochemical tests are invasive and time-consuming and cannot simultaneously monitor and dynamically evaluate multiple stress levels in fish and accurately classify their health levels. The purpose of this study is to deploy wearable bioelectrical impedance analysis (WBIA) sensors on fish skin to construct a deep learning-based stress dynamic evaluation model for precisely estimating their accurate health status. (2) Methods: The correlation of fish (turbot) muscle nutrients and their stress indicators are calculated using grey relation analysis (GRA) for allocating the weight of the stress factors. Next, WBIA features are sieved using the maximum information coefficient (MIC) in stress trend evaluation modeling, which is closely related to the key stress factors. Afterward, a convolutional neural network (CNN) is utilized to obtain the features of the WBIA signals. Then, the long short-term memory (LSTM) method learns the stress trends with residual rectification using bidirectional gated recurrent units (BiGRUs). Furthermore, the Z-shaped fuzzy function can accurately classify the fish health status by the total evaluated stress values. (3) Results: The proposed CNN-LSTM-BiGRU-based stress evaluation model shows superior accuracy compared to the other machine learning models (CNN-LSTM, CNN-GRU, LSTM, GRU, SVR, and BP) based on the MAPE, MAE, and RMSE. Moreover, the fish health classification under waterless and low-temperature conditions is thoroughly verified. High accuracy is proven by the classification validation criterion (accuracy, F1 score, precision, and recall). (4) Conclusions: the proposed health evaluation technology can precisely monitor and track the health status of live fish and provides an effective technical reference for the field of live fish vital sign detection. [ABSTRACT FROM AUTHOR]

Stress state evaluation in axially loaded structural members is significant for sustaining and preserving the service life of buildings. While successful monitoring furnishes staunch information on the health, integrity, safety and serviceability of structures, maintaining the structural performance of a building with time significantly depends on assessing the occurrence. Variations in the stress in axially loaded members may occur in masonry buildings or space structures caused by different conditions and human-induced factors. In the last decades, numerous nondestructive methods have been generated to furnish practical means for identifying axial load in the tie-rods of masonry buildings and in the structural members of space structures. Significant effort has been put into dynamic-based approaches, which make use of the vibrational response of the monitored member to investigate its condition and evaluate the axial load. In particular, wide laboratory and field tests have been executed worldwide, resulting in several findings. Meanwhile, with flourishing sensing technology and computing power, Artificial Intelligence (AI) applications, such as hybrid methods, optimization techniques and deep learning algorithms, have become more practicable and widely used in vibration-based axial stress prediction, with efficiency and, frequently, with strict precision. While there have been various manuscripts published on dynamic-based axial stress evaluation, there are no works in which the passage from traditional methods to combinations with AI approaches have been illustrated. This article aims to address this gap by introducing the highlights of the traditional methods, and furnish a review of the applications of AI techniques used for nondestructive-based axial stress prediction in tie-rods and structural members. Conclusions, including further studies and field developments, have also been mentioned at the end of the article. [ABSTRACT FROM AUTHOR]

Simple Summary: It is well recognized that companionship is important to animals and that they need to be provided with an environment accompanied by materials for enrichment, such as toys. However, few studies have evaluated whether specific environments actually benefit animals. Therefore, we designed various environments for laboratory animals and scientifically evaluated which environments reduced these animals' stress. We found that an environment with freer air circulation and the provision of enrichment materials reduced animal stress, and no risk or benefit could be determined for the presence or absence of a companion. We do not consider that our results necessarily indicate the lack of a need for a companion, but, rather, the importance of having a good companion. Our results can serve as a meaningful guideline for the creation of suitable environments for laboratory animals. Animal welfare is recognized as essential for the coexistence of humans and animals. Considering the increased demand and interest in animal welfare, many methods for improving animal welfare are being devised, but which method reduces animal stress has not been scientifically verified. Therefore, reducing animal stress by providing a proper breeding environment and environmental enrichment can be the basis for animal study. In this study, stress levels were assessed based on the mouse-breeding environment. We considered that the higher the body weight and the lower the corticosterone concentration, the lower the stress. According to the results, animals in the individual ventilation cages were determined to have lower serum cortisol concentrations, while the body weight of the animals was increased when in individual ventilation cages compared with individual isolated cages and when providing environmental enrichment compared with group breeding or not providing environmental enrichment. The results provide appropriate guidelines for improving laboratory animal welfare. [ABSTRACT FROM AUTHOR]

Tensile deformation in situ neutron diffraction of an extruded AZ31 alloy was performed to validate conventional procedures and to develop new procedures for stress evaluation from lattice strains by diffraction measurements of HCP-structured magnesium alloys. Increases in the lattice strains with respect to the applied true stress after yielding largely vary among [hk.l] grains. Some [hk.l] grains have little or no increase in lattice strain, making it difficult to use the conventional procedures to determine the average phase strain by using lattice constants or by averaging several lattice strains. The newly proposed procedure of stress evaluation from the lattice strains shows very high accuracy and reliability by weighting the volume fraction of [hk.l] grains and evaluating them in many [hk.l] orientations in addition to multiplication by the diffraction elastic constant. When multiple hk.l peaks cannot be obtained simultaneously, we recommend to use the 12.1 peak for stress evaluation. The lattice strain value evaluated from the 12.1 peak shows a good linear relationship with the applied true stress for the whole deformation region.

(1) Background: At present, physiological stress detection technology is a critical means for precisely evaluating the comprehensive health status of live fish. However, the commonly used biochemical tests are invasive and time-consuming and cannot simultaneously monitor and dynamically evaluate multiple stress levels in fish and accurately classify their health levels. The purpose of this study is to deploy wearable bioelectrical impedance analysis (WBIA) sensors on fish skin to construct a deep learning-based stress dynamic evaluation model for precisely estimating their accurate health status. (2) Methods: The correlation of fish (turbot) muscle nutrients and their stress indicators are calculated using grey relation analysis (GRA) for allocating the weight of the stress factors. Next, WBIA features are sieved using the maximum information coefficient (MIC) in stress trend evaluation modeling, which is closely related to the key stress factors. Afterward, a convolutional neural network (CNN) is utilized to obtain the features of the WBIA signals. Then, the long short-term memory (LSTM) method learns the stress trends with residual rectification using bidirectional gated recurrent units (BiGRUs). Furthermore, the Z-shaped fuzzy function can accurately classify the fish health status by the total evaluated stress values. (3) Results: The proposed CNN-LSTM-BiGRU-based stress evaluation model shows superior accuracy compared to the other machine learning models (CNN-LSTM, CNN-GRU, LSTM, GRU, SVR, and BP) based on the MAPE, MAE, and RMSE. Moreover, the fish health classification under waterless and low-temperature conditions is thoroughly verified. High accuracy is proven by the classification validation criterion (accuracy, F1 score, precision, and recall). (4) Conclusions: the proposed health evaluation technology can precisely monitor and track the health status of live fish and provides an effective technical reference for the field of live fish vital sign detection.

The alarming presence of COVID-19 challenged the United Nations' (UN) Sustainable Development Goal 2 and made the World Health Organization (WHO) declare a public health emergency of international concern. Imposed lockdowns disrupted the supply and demand chain of the food systems, hence affecting food security. This research would like to know and assess the early effect (two months after the lockdown) of the enhanced community quarantine on food security in the Philippines. An online survey was employed participated by 331 household representatives using a survey instrument containing food security assessment, household sociodemographic characteristics, behavioral responses covering food purchase and consumption behavior, and emergency measure adoption. Statistical tests were applied: Mann-Whitney U test to know the behavioral response of the food secure vs. food insecure households, as well as the phi coefficient and Cramer's V test to determine and assess the parameters that plays important role in food security during this period. Results showed that 73% of the respondents were food insecure. The early effect of the lockdown was seen in the behavioral responses, significant differences between food secure and insecure households were found in age, income, and food purchase behavior. Parameters associated with food security are age, income, food allocation, expectations on the livelihood impact and change in expenditure, and the adoption motivations in practicing backyard gardening. The stress evaluation revealed that while Filipinos tried to cope, an increased level of anxiety was experienced. The need for clear measures in terms of preparedness in any pandemic situation was heightened. These findings are significant in providing benchmark information on food security during a pandemic. [ABSTRACT FROM AUTHOR]

In the era of Industry 4.0, the study of Human–Robot Collaboration (HRC) in advancing modern manufacturing and automation is paramount. An operator approaching a collaborative robot (cobot) may have feelings of distrust, and experience discomfort and stress, especially during the early stages of training. Human factors cannot be neglected: for efficient implementation, the complex psycho-physiological state and responses of the operator must be taken into consideration. In this study, volunteers were asked to carry out a set of cobot programming tasks, while several physiological signals, such as electroencephalogram (EEG), electrocardiogram (ECG), Galvanic skin response (GSR), and facial expressions were recorded. In addition, a subjective questionnaire (NASA-TLX) was administered at the end, to assess if the derived physiological parameters are related to the subjective perception of stress. Parameters exhibiting a higher degree of alignment with subjective perception are mean Theta (76.67%), Alpha (70.53%) and Beta (67.65%) power extracted from EEG, recovery time (72.86%) and rise time (71.43%) extracted from GSR and heart rate variability (HRV) metrics PNN25 (71.58%), SDNN (70.53%), PNN50 (68.95%) and RMSSD (66.84%). Parameters extracted from raw RR Intervals appear to be more variable and less accurate (42.11%) so as recorded emotions (51.43%). • Real-time monitoring of operator stress in Industry 4.0 is essential. • Different psychophysiological signals recorded in real-time with modern biosensors. • The subjective stress response is very variable and dependent on various factors. • Record if variations in physiological parameters agree with individual perceptions. • Select metrics best in accordance with subjective stress perception. [ABSTRACT FROM AUTHOR]

• New advances of metal magnetic memory technology in civil engineering during past 10 years are reviewed. • The problems with the existing studies are pointed out. • The challenges and directions for the future are presented. As a new non-destructive testing technology, the metal magnetic memory (MMM) method is considered to have potential application prospects in civil engineering due to its unique advantage of diagnosis of early damage in ferromagnetic materials. This paper reviewed the theoretical basis of MMM technology, summarized the new research advances for MMM technology in civil engineering during the past 10 years, discussed the current problems, and presented the challenges for the future. This paper can provide references and advice for the application of MMM technology in civil engineering. [ABSTRACT FROM AUTHOR]

Metal magnetic memory testing (MMMT) is an effective nondestructive technique for fatigue damage monitoring of weldments because of its capacity for stress evaluation. An experimental investigation of the effect of the applied fatigue stress on MMMT signals, including the tangential component Bx and the normal component Bz, during tension–compression fatigue tests in welded joints was carried out systematically. The Bx and Bz signals at different fatigue cycles and fatigue stresses were collected and analyzed, and the results showed that there was a peak of Bx and abnormal peaks of Bz that existed at the welded joint before loading. After loading, the peak of Bx and the abnormal peaks of Bz reversed, and the Bx signals moved upward and the Bz signals rotated anticlockwise dramatically in the first few fatigue cycles. After the fatigue cycle number was larger than 1000, Bx and Bz were stable, with very little fluctuation. In addition, the characteristics of Bx signals, the mean value, and the peak value of the average of Bx had an extremely significant linear relationship with the applied fatigue stress during the stable stage of the fatigue test, which indicates that MMMT is a feasible method for fatigue stress evaluation and even residual fatigue life estimation for weldments in service. [ABSTRACT FROM AUTHOR]

Recent work has shown that deep convolutional neural network is capable of solving inverse problems in computational imaging, and recovering the stress field of the loaded object from the photoelastic fringe pattern can also be regarded as an inverse problem solving process. However, the formation of the fringe pattern is affected by the geometry of the specimen and experimental configuration. When the loaded object produces complex fringe distribution, the traditional stress analysis methods still face difficulty in unwrapping. In this study, a deep convolutional neural network based on the encoder–decoder structure is proposed, which can accurately decode stress distribution information from complex photoelastic fringe images generated under different experimental configurations. The proposed method is validated on a synthetic dataset, and the quality of stress distribution images generated by the network model is evaluated using mean squared error (MSE), structural similarity index measure (SSIM), peak signal-to-noise ratio (PSNR), and other evaluation indexes. The results show that the proposed stress recovery network can achieve an average performance of more than 0.99 on the SSIM.

Animal welfare is recognized as essential for the coexistence of humans and animals. Considering the increased demand and interest in animal welfare, many methods for improving animal welfare are being devised, but which method reduces animal stress has not been scientifically verified. Therefore, reducing animal stress by providing a proper breeding environment and environmental enrichment can be the basis for animal study. In this study, stress levels were assessed based on the mouse-breeding environment. We considered that the higher the body weight and the lower the corticosterone concentration, the lower the stress. According to the results, animals in the individual ventilation cages were determined to have lower serum cortisol concentrations, while the body weight of the animals was increased when in individual ventilation cages compared with individual isolated cages and when providing environmental enrichment compared with group breeding or not providing environmental enrichment. The results provide appropriate guidelines for improving laboratory animal welfare.

Background: Menopause is a natural phase of a woman's life when menstrual periods stop permanently and cause psychological symptoms such as anxiety. anxiety can be reduced when women get social support. Objective: The purpose of this study is to develop a social support model to reduce anxiety in menopausal women. Method: This study applied explanatory research design with a Cross-sectional approach. The study population was selected 197 menopausal women who were in 11 clusters in Diwek - Jombang Regency. The participants were selected using Cluster Random sampling. The data analyzed by using the Partial Least Square test. The inclusion criteria of this research are 1) Women Menopause Age 45-55 years old experiencing anxiety, 2) Registered in couples of childbearing age records 2017 of Diwek District Health Center, while the exclusion criteria of this research are 1) Menopausal women single/ virgin, 2) Using tranquilizers, 3) Using hormone replacement therapy (TSH). Results: The results showed that (1) individual factors significantly influenced the evaluation of stress (path coefficient of -0.056, t = 3.74); (2) social networking significantly influences stress evaluation (path coefficient -0.147, t = 2.13); (3) social support significantly influences stress evaluation (path coefficient -0.117, t = 2.02); (4) social support significantly influences anxiety (path coefficient -0.326, t = 5.25); and (5) stress evaluation significantly influences anxiety (path coefficient 0.196, t = 9.07). Conclusion: The development of social support models to reduce postmenopausal anxiety has a significant direct effect. The development of the model consists of stress assessment consisting of experience, trust, coping resources, informative support and award support. The development of social support is highly recommended to reduce anxiety among menopausal women by promoting stress evaluation and social support from close relationships. [ABSTRACT FROM AUTHOR]

• The loading history can be considered through the improved force-magnetic coupling model. • It can reflect the stress state accurately concerning the specimen position in geomagnetic field. • The stress state can be effectively demonstrated with proposed magnetic characteristic parameters. • The normalized magnetic characteristic parameter is less affected by the specimen position. • The variation of normalized magnetization calculated can reflect the stress state during loading. It's of great significance to conduct the nondestructive evaluation of steel bridges to extend their service life. The metal magnetic memory testing (MMMT) method can effectively evaluate the stress states of ferromagnetic components. To improve the accuracy and reliability of the stress evaluation on bridge steel structures based on MMMT technology, an improved force-magnetic coupling model considering loading history is proposed, which can reflect the impact of material mechanical properties on magnetization behavior. The MMMT is carried out on the Q345qD bridge steel plates under load-unload tensile stress considering the relative location between the specimen and the geomagnetic field, according to the rotation angle θ r. It comprehensively analyzes the variation laws of representative tangential and normal components of the magnetic signal, i.e. H m (y) and H m (z), corresponding to different inspection parameters during the loading process. The mean value A y of the H m (y) curves and the linear fitting slope K z of H m (z) curves are applied to characterize the variation laws of magnetic signal with respect to the applied load F a. According to the fitting curves of A y and K z with F a , it quantitatively demonstrates the applied loads. It further puts forward the normalized magnetic characteristic parameters A yn and K zn to characterize the force-magnetic relationship of the specimen, which are less affected by the position of the specimen in geomagnetic field. Finally, the proposed force-magnetic coupling model is applied to calculate the variation of normalized magnetization Δ M n. The theoretical results are compared with the synthetic magnetic characteristic parameter AK n obtained by experiment. It shows an average error of 8.53% between Δ M n and AK n , which proves the feasibility and effectiveness of the force-magnetic coupling model proposed in this paper. [ABSTRACT FROM AUTHOR]

In the design process of offshore steel structures, it is typical to employ commercial calculation codes in which simulation and evaluation of results are performed on the basis of the available standards (e.g. API, DNV, Lloyds). The modeling and solution rely on finite element methods and cover the simulation of the structure’s properties along with the influence of the marine environment – sea currents, wave and wind loading, as well as the influence of vibrations, buoyancy and accompanying mass of water. Both commercial and open source mathematical modeling software which is available nowadays allows for cost effective and flexible implementation of advanced models for offshore industrial structures with high level of credibility and safety. The models can be built to suit task-specific requirements and evaluated on the basis of the selected criterial system best suited to the needs of the customer. Examples of methodology for environmental and structural model development are presented, along with simulation results covering a wide scope of data, ranging from stress and deformation to resonant characteristics and issues of technological feasibility.

Temperature field and thermal-structure coupling stress field calculation were conducted to a main steam safety valve prototype for nuclear power stations using finite element software Ansys,and the stress of the valve subjected to operating pressure load and thermal stress was in compliance with the stress evaluation criteria. In addition,alternating stress of the pressure components for the specified cyclic operation application of loads and thermal stresses were calculated,and fatigue analysis was evaluated according to RCC-M code. Results indicate that the valve prototype is able to meet the requirements of fatigue failure criteria for the specified cycles and would have good prospects in engineering applications.

A sensitive and precise experimental system able to time-track the static and dynamic response of steel sheets to intense loads is hereby described. This methodological article is based on a specific investigation carried out in order to verify the correct functioning and safety conditions of a large sheet metal structure. Several suggestions and practical tricks are presented in ample details describing in what ways they allow to improve the results of the experiment.

Relevant examples of the application of innovative measuring devices of NNT Company in the area of non-destructive assessment of the stress state of steel components using the Barkhausen effect are presented here. We have developed two innovative devices in which the Barkhausen effect signal detected at a given point is converted into real-time information about the stress level at that point. The research was focused on the objects and technological processes where the high stress state causes specific problems both at the stage of construction and later exploitation. Such processes include steel section manufacturing process, welding, rolling or tensile loading.

Copyright of Nuclear Safety is the property of Nuclear & Radiation Safety Center and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Stress affects the microstructure of the material to influence the durability and service life of the components. However, the previous work of stress measurement lacks quantification of the different variations in time and spatial features of micromagnetic properties affected by stress in elastic and plastic ranges, as well as the evolution of microstructure. In this paper, microstructure evolution under stress in elastic and plastic ranges is evaluated by magnetic Barkhausen noise (MBN) transient analysis. Based on a J-A model, the duration and the intensity are the eigenvalues for MBN transient analysis to quantify transient size and number of Barkhausen events under stress. With the observation of domain wall (DW) distribution and microstructure, the correlation between material microstructure and MBN transient eigenvalues is investigated to verify the ability of material status evaluation on the microscopic scale of the method. The results show that the duration and the intensity have different change trends in elastic and plastic ranges. The eigenvalue fusion of the duration and intensity distinguishes the change in microstructure under the stress in elastic and plastic deformation. The appearance of grain boundary (GB) migration and dislocation under the stress in the plastic range makes the duration and the intensity higher on the GB than those inside the grain. Besides, the reproducibility of the proposed method is investigated by evaluating microstructure evolution for silicon steel sheet and Q235 steel sheet. The proposed method investigates the correlation between the microstructure and transient micromagnetic properties, which has the potential for stress evaluation in elastic and plastic ranges for industrial materials.

Geometrical discontinues such as notches play a significant rule in structural integrity of the components, especially when the component is subjected to very severe conditions, such as the high temperature fatigue or creep. In this paper, a generalized form of the existing notch tip creep stressstrain analysis method developed by Nuñez and Glinka, is developed and extended to a wide variety of blunt V-notches. Assuming the generalized Lazzarin-Tovo solution that allows a unified approach to the evaluation of linear elastic stress fields in the vicinity of both cracks and notches is the key in getting the extension to blunt V-notches. Numerous cases have been analysed and the stress fields obtained according to the proposed method were compared with proper finite element data, showing a very good agreement.

Strain and stress monitoring is an important approach for evaluating the stress state of concrete dams. Since the hydration rate of cement increases with increasing temperature, the parameters of the thermal and mechanical properties of concrete are related to its temperature and temperature history. However, the influence of temperature history has not been taken into account in theories of transformation from measured strains to stresses used for analysis of concrete dams. Hence, significant errors can occur in stress evaluations of concrete dams. In this paper, based on the equivalent age theory and deformation method, we investigate a transformation equation from measured strains to viscoelastic stresses that considers the temperature history and describe the calculation steps in detail. The new algorithm is implemented by a comparative analysis of the viscoelastic stresses transformed from measured strains with and without considering the temperature history for a typical concrete dam located in northwestern China. The analysis results show that the trends of the transformed stresses with and without considering the temperature history are essentially the same, while the maximum normal stress difference is 0.49 MPa in the early stage. [ABSTRACT FROM AUTHOR]

Teacher burnout is a growing phenomenon that may dramatically reduce the quality of life of both teachers and students. Many studies have conceptualized teaching as a high-contact profession and, focusing on the emotional exhaustion dimension of burnout, they have highlighted the relation with students as a key dimension of teachers' stress. This paper presents an original instrument (TSS-Sr) to measure teachers' stress related to the interaction with their pupils. It provides the psychometric characteristic of this scale. Results support a model of measurement of teacher social stress based on four dimensions: verbal aggression, dislike students, awkward reactions, demanding requests. Implications about the use and the applications of this instrument are discussed. [ABSTRACT FROM AUTHOR]

Stress is the crucial factor of ferromagnetic material failure origin. However, the nondestructive test methods to analyze the ferromagnetic material properties’ inhomogeneity on the microscopic scale with stress have not been obtained so far. In this study, magnetic Barkhausen noise (MBN) signals on different silicon steel sheet locations under in situ tensile tests were detected by a high-spatial-resolution magnetic probe. The domain-wall (DW) motion, grain, and grain boundary were detected using a magneto-optical Kerr (MOKE) image. The time characteristic of DW motion and MBN signals on different locations was varied during elastic deformation. Therefore, a time-response histogram is proposed in this work to show different DW motions inside the grain and around the grain boundary under low tensile stress. In order to separate the variation of magnetic properties affected by the grain and grain boundary under low tensile stress corresponding to MBN excitation, time-division was carried out to extract the root-mean-square (RMS), mean, and peak in the optimized time interval. The time-response histogram of MBN evaluated the silicon steel sheet’s inhomogeneous material properties, and provided a theoretical and experimental reference for ferromagnetic material properties under stress.

The paper presents the results of application of a novel Barkhausen effect (BE) probe with adjustable magnetizing field direction for the stress level evaluation in ferromagnetic materials. The investigated sample was in a form of a pipe, made of P91 steel that was anisotropic due to the production process. The measurements were performed before and after welding, revealing the influence of welding process on the residual stress distribution. As was observed, the process introduced high tensile stresses in the normal to the weld direction (which can be interpreted as a decrease of strongly compressive residual stresses present in martensitic steels). In addition to that, the paper presents investigations of the measurement set performance corroborating its applicability for Barkhausen effect signal measurements in the magnetically anisotropic materials. The signals obtained during manual rotation of the probe (typical method of BE measurements) are very similar to those recorded during automatic field axis rotation. [ABSTRACT FROM AUTHOR]

This paper presents the study of applying the nonlinear ultrasonic wave to evaluate the stress state of metallic materials under steady state. The pre-stress loading method is applied to guarantee components with steady stress. Three kinds of nonlinear ultrasonic experiments based on critically refracted longitudinal wave are conducted on components which the critically refracted longitudinal wave propagates along x , x 1 and x 2 direction. Experimental results indicate the second and third order relative nonlinear coefficients monotonically increase with stress, and the normalized relationship is consistent with simplified dislocation models, which indicates the experimental result is logical. The combined ultrasonic nonlinear parameter is proposed, and three stress evaluation models at x direction are established based on three ultrasonic nonlinear parameters, which the estimation error is below 5%. Then two stress detection models at x 1 and x 2 direction are built based on combined ultrasonic nonlinear parameter, the stress synthesis method is applied to calculate the magnitude and direction of principal stress. The results show the prediction error is within 5% and the angle deviation is within 1.5°. Therefore the nonlinear ultrasonic technique based on L CR wave could be applied to nondestructively evaluate the stress of metallic materials under steady state which the magnitude and direction are included. [ABSTRACT FROM AUTHOR]

A systematic dynamic and structural integrity analysis of an elevator system, under real dynamic load conditions, is presented in this work. The proposed method constitutes an important innovation for the field “analysis and design optimization of elevator systems”. Current elevator design requirements lead to development of lightweight structures which often are of higher complexity. In order to achieve design optimization of these systems, it is important to develop an accurate Finite Element Analysis methodology, to support their precise numerical modeling, also in the worst loading case for their operation. One of the worst loading cases for an elevator system is when the elevator falls free and the safety gear is activated until the elevator stops. Each elevator, when installed in a building, is tested in this loading scenario. This means, that should be designed to withstand in these loads and not to have any damage after this test. One of the special features of this paper is that the study was performed on a complete industrial elevator system, including all details/complexities of a commercial system. Comparison of the numerical and experimental data verifies that the proposed “mixed computational-experimental” analysis method is quite reliable, concluding application/verification of the method on a complete industrial elevator system. [ABSTRACT FROM AUTHOR]

Body acceleration due to heartbeat-induced reaction forces can be measured as mobile phone accelerometer (m-ACC) signals. Our aim was to test the feasibility of using m-ACC to detect changes induced by stress by ultra-short heart rate variability (USV) indices (standard deviation of normal-to-normal interval—SDNN and root mean square of successive differences—RMSSD). Sixteen healthy volunteers were recruited; m-ACC was recorded while in supine position, during spontaneous breathing at rest conditions (REST) and during one minute of mental stress (MS) induced by arithmetic serial subtraction task, simultaneous with conventional electrocardiogram (ECG). Beat occurrences were extracted from both ECG and m-ACC and used to compute USV indices using 60, 30 and 10 s durations, both for REST and MS. A feasibility of 93.8% in the beat-to-beat m-ACC heart rate series extraction was reached. In both ECG and m-ACC series, compared to REST, in MS the mean beat duration was reduced by 15% and RMSSD decreased by 38%. These results show that short term recordings (up to 10 s) of cardiac activity using smartphone’s accelerometers are able to capture the decrease in parasympathetic tone, in agreement with the induced stimulus.

Due to the existing relationship between microstructural properties and magnetic ones of the ferromagnetic materials, the application potential of the magnetic Barkhausen noise (BN) method to non-destructive testing is constantly growing. However, the stochastic nature of the Barkhausen effect requires the use of advanced signal processing methods. Recently, the need to apply time-frequency (TF) transformations to the processing of BN signals arose. However, various TF methods have been used in the majority of cases for qualitative signal conditioning and no extensive analysis of TF-based information has been conducted so far. Therefore, in this paper, the wide analysis of BN TF representation was carried out. Considering the properties of TF transformations, the Short-Time Fourier Transform (STFT) was used. A procedure for definition of the envelopes of the TF characteristic was proposed. To verify the quality of extracted features, an analysis was performed on the basis of BN signals acquired during stress loading experiments of steel elements. First, the preliminary experiments were processed for various parameters of the measuring system and calculation procedures. The feature extraction procedure was performed for different modes of TF representations. Finally, the distributions of TF features over the loading stages are presented and their information content was validated using commonly used features derived from time T and frequency F domains.

In this paper, we present an analytical method for evaluating the stress field within a casing-cement-formation system of oil/gas wells under anisotropic in-situ stresses in the rock formation and uniform pressure within the casing. The present method treats the in-situ stresses in the formation as initial stresses since the in-situ stresses have already developed in the formation before placement of cement and casing into the well. It is demonstrated that, via this treatment, the present method excludes additional displacements within the formation predicted by the existing method, and gives more reasonable stress results. An actual tight-oil well is analyzed using the present and existing analytical methods, as well as the finite element method. Good agreement between the analytical results and the finite element analysis (FEA) results is obtained, validating the present method. It is also evident that, compared with the present method, the existing method overestimates the compressive stress level within the casing and the cement. Finally, the effects of elastic properties of the formation, cement, and inner pressure of casing on stresses within the casing and cement are illustrated with a series of sensitivity analyses. [ABSTRACT FROM AUTHOR]

Geometrical discontinues such as notches play a significant rule in structural integrity of the components, especially when the component is subjected to very severe conditions, such as the high temperature fatigue or creep. In this paper, a generalized form of the existing notch tip creep stressstrain analysis method developed by Nuñez and Glinka, is developed and extended to a wide variety of blunt V-notches. Assuming the generalized Lazzarin-Tovo solution that allows a unified approach to the evaluation of linear elastic stress fields in the vicinity of both cracks and notches is the key in getting the extension to blunt V-notches. Numerous cases have been analysed and the stress fields obtained according to the proposed method were compared with proper finite element data, showing a very good agreement. [ABSTRACT FROM AUTHOR]