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Physiological effects caused by power ultrasound radiation are of therapeutic benefits for fracture healing. However, these effects are hard to detect with current instrumentations. The aim of this paper is to analyze the behavior of bone subject to therapeutic ultrasound and provide data reference for an intelligent bone ultrasonic system. In this paper, we adopted a 3-D finite element method as a virtual measurement tool to study the acoustic-radiation-induced stress fields inside and on the surface of bone. The equivalent long bone model was built and the soft tissue was involved by establishing coupling connections with bone surface points. The ultrasound radiation was generated by a 2-MHz excitation and was applied on the surface of soft tissue. In this paper, we first defined six paths in different bone layers to quantitatively study the longitudinal stress distribution and examined the concentration center positions and width with sliding windows. Then, the circumferential stress evolution from relaxation fields to concentration fields was investigated by computing the stress fields on cross sections. Analytical dispersion curves were measured to characterize the guided wave modes. The results show that the middle bone tissue has a higher mean stress (2027.7 Pa) than the surface (763.3 Pa) and the outer bone layer (1898.1 Pa), and the stress distribution of the middle layer is less disturbed (coefficient of variation $= 39.8$ %). Also, on cross section of the concentration zones, periodical fields with a distance of half-wavelength are obtained. From 0.2 to 2 MHz, the acoustic intensity grows proportionally with excitation amplitude. [ABSTRACT FROM PUBLISHER]

The solar photovoltaic (PV) industry has seen rapid expansion in the past decade with an ever-increasing share of the electricity-generating capacity for the world. Continuous efforts have been made by the involved industry in order to increase the efficiency of the PV devices and, at the same time, to reduce costs. Third-generation solutions such as dye-sensitized solar cells (DSSCs) represent a very promising technology for PV energy production. Such cells offer a new and less-expensive technology compared with the silicon-based solar cells, the latter still with relatively high production costs. To expand their use in energy generation, an assessment of DSSC long-term stability is necessary. In particular, this paper aims to analyze Aging effects on DSSCs under different operating conditions. The proposed test activity is divided into three phases. In the first phase, we use accelerated optical stress to understand the mechanisms' degradation of DSSC parameters such as efficiency, open circuit voltage, and short circuit current. Then the DSSCs are studied in natural sunlight conditions. Finally, a combined optical and thermal stress is analyzed. The experimental data are intended to better determine the strengths and weaknesses of DSSCs in order to optimize their functional configuration. [ABSTRACT FROM PUBLISHER]

This paper presents an innovative and automated measurement setup for the characterization of variability effects in CMOS transistors using array-based integrated circuits (ICs), through which a better understanding of CMOS reliability could be attained. This setup addresses the issues that come with the need for a trustworthy statistical characterization of these effects: testing a very large number of devices accurately but, also, in a timely manner. The setup consists of software and hardware components that provide a user-friendly interface to perform the statistical characterization of CMOS transistors. Five different electrical tests, comprehending time-zero and time-dependent variability effects, can be carried out. Test preparation is, with the described setup, reduced to a few seconds. Moreover, smart parallelization techniques allow reducing the typically time-consuming aging characterization from months to days or even hours. The scope of this paper thus encompasses the methodology and practice of measurement of CMOS time-dependent variability, as well as the development of appropriate measurement systems and components used in efficiently generating and acquiring the necessary electrical signals. [ABSTRACT FROM AUTHOR]

Estimating the aging-related degradation and failure of nanoscale integrated circuits (ICs), before they actually occur, is crucial for developing aging prevention/mitigation actions and in turn avoiding unexpected in-field circuit failures. Real-time monitoring of IC operating conditions can be efficiently used for predicting aging degradation and in turn timing failures caused by device aging. The existing approaches only take some specific operating conditions (e.g., workload or temperature) into account. In this paper, we propose a novel method for real-time IC aging prediction by extending the prediction schemes to a comprehensive model which takes into account any time-variant dynamic operating conditions relevant to aging prediction. Using a machine learning prediction model and the notion of equivalent aging time, we show that our approach outperforms the existing methods in terms of aging-prediction accuracy under different scenarios of time-variant operating conditions. [ABSTRACT FROM AUTHOR]

This paper proposes a wearable device-based system to monitor the abnormal conditions of a driver, including stress, fatigue, and drowsiness. The system measures the motional and physiological information of the driver using the developed wearable device on the wrist. Preprocessing is used to distinguish the valid signal parts of the measured signals, because various noises can occur in wearable sensors. Features are extracted from the signal parts, and an optimal feature set is determined by an analysis of variance and a sequential floating forward selection algorithm. To classify the driver’s state, a support vector machine-based classification method is used to obtain high generalization performance considering interdriver variance. Experiments were conducted on an indoor driving simulator, with 28 subjects, to gather data for each state. The classification accuracy was 98.43% for fivefold cross validation on the data. In a subject-independent test, the accuracy was 68.31% for the four states and 84.46% for the three states consisting of normal, stressed, and fatigued or drowsy states. Using the proposed system, the abnormal conditions of the driver can be detected and distinguished. This advantage contributes to safer and more comfortable driving. Furthermore, the utilization of the wearable device makes the system easy to use. [ABSTRACT FROM PUBLISHER]

In the coming years, biomedical instrument manufacturers will have to inform the Notified Body of RoHS conformity assessment of the new medical instruments. In particular, in the case of lead-free solders, the Notified Body will require evidence that such solders are equally reliable as tin–lead, for the proposed use and lifetime of the product. So, biomedical instrument manufacturers are strongly interested in evaluating the performance of new soldering lead-free material used for the implementation of electronic parts. In order to support them and fill the technology knowledge gap, this paper presents a novel 128-channel phased-array probe for echocardiograph applications realized by new soldering technique where isotropic silver electrically conductive adhesive is used. In particular, the new soldering material is taken into consideration in the design phase of ultrasound array transducer, which is the core of a linear phased-array probe that is able to monitor the cardiac muscle. Being such material innovative in the application, a detailed study of the failure condition regarding the phased-array probe by means of accelerated qualification testing is proposed in order to assure its performances under stress and over time. A comparison of the electroacoustic measurement results with respect to the conventional probe, soldered with Sn–Pb, is also presented in this paper. [ABSTRACT FROM PUBLISHER]

This paper addresses an innovative solution to develop a circuit to perform accelerated stress tests of capacitive microelectromechanical-system (MEMS) switches and shows the use of instruments and equipment to monitor physical aging phenomena. A dedicated test circuit was designed and fabricated in order to meet the need for accelerated techniques for those structures. It integrated an in-house miniaturized circuit connected to additional test equipment (e.g., oscilloscopes and capacitance meters) that enabled the reliability characterization of capacitive switches. The accelerated stress test (AST) circuit generated an electrostatic-discharge-like impulse that stressed the device. This setup allowed the simultaneous measurement of the current and voltage waveforms, and the capacitance variation of the device under test after each stress. The results obtained using the miniature AST circuit were discussed and were correlated with results obtained using a commercial human-body-model tester as well as data from a cycling benchmark. The scope of this paper encompasses the theory, methodology, and practice of measurement; the development of a testing miniaturized board; and the analysis and representation of the information obtained from a set of measurements. As a result, it may contribute to the scientific and technical standards in the field of instrumentation and measurement of electrostactically actuated devices having insulating layers. [ABSTRACT FROM PUBLISHER]

The gallium nitride transistors suffer from current collapse effect in operation regions, which leads the dynamic ON-resistance to increase when high voltage is applied to the transistor. Dynamic ON-resistance under practical application conditions is also an important factor for the reliability and conduction efficiency of transistors. To measure the dynamic ON-resistance and evaluate the current collapse effect, a softswitching circuit based on synchronous buck topology is proposed in this paper. To apply high-voltage and high-current stresses to the device without additional spikes and oscillation, resonance technique has been employed. As a result, the proposed circuit could produce sufficient power stresses to the devices with general equipment. To achieve accurate measurement of ON-resistance under switching operations and eliminate the saturation of oscilloscope probes, an active voltage clamp circuit is developed. Operation principles and design analysis of the circuit are described in this paper. The dynamic ON-resistance measurement method is illustrated in detail. Furthermore, a prototype circuit has been built. A simulation and experiments were carried out to verify the performance of the system. A comparison of the active clamp circuit with common voltage probes is presented through the measurement results. The experimental results confirm that dynamic ON-resistance can be accurately measured using the proposed circuit and the current collapse effect can be evaluated under practical operation conditions with high precision. [ABSTRACT FROM PUBLISHER]

Built-in tests (BITs) are widely used in mechanical systems to detect and diagnose a fault, whereas the BIT false alarms bring much trouble for precise fault diagnosis and logistics/maintenance arrangement. The false alarm phenomenon is related to the degradation over time, and the false alarm evolution process can be typically divided into three stages. This paper proposes a condition-based multistage false alarm detection and reduction method for mechanical systems. The stages are clarified according to the degradation level and the false alarm severity. The dividing boundaries of the stages are optimized using soft margin one-versus-rest support vector machine (SVM) classifiers. The associated intermediate stage is the intense period of false alarms, and the dynamic Bayesian network inference model is developed to satisfy the requirements of accurate false alarm diagnosis. To achieve the goal of false alarm suppression, the top-level BIT outputs are updated with the original BIT alarms and the identified probable states. Finally, the proposed approach is demonstrated in the application study of a milling machine and the well-round experimental results are analyzed. [ABSTRACT FROM PUBLISHER]

Structural Health Monitoring represents one of the primary field applications for new sensor technologies. Different kinds of sensors to monitor stability anomalies of civil structures are deployed on different kinds of building materials. Observation of stability must be durable and reliable for the lifetime of a structure. This paper is part of a research to investigate the possibility of application of thick-film (TF) piezoresistive sensors on building materials for the scope of monitoring structure's stability and conditions of load. As a first approach toward this objective, TF piezoresistive sensors will be used like metal-foil strain gauges on two different building materials, namely brick (clay) and concrete. A boosted Wheatstone bridge interface circuitry will be proposed and simulated with a Saber simulator. Thick film ceramic sensors (TFCS) will be applied on red brick and concrete to investigate TF response proportionality and linearity when applied on these two kinds of building materials. [ABSTRACT FROM AUTHOR]

The use of a built-in test equipment (BITE) that is able to provide a real-time diagnostic of a monitored device allows increasing reliability and decreasing costs. The BITE operation can be based on a suitable life model of the device that must relate the time to failure to the “stress history” of the component. The life model is developed by exploiting the results of a proper measurement campaign. This paper investigates a life model for capacitors subjected to both constant and time-varying temperatures by illustrating the test system and discussing the achieved results. [ABSTRACT FROM AUTHOR]

The physical distance between adjacent memory cells is rapidly decreasing as memory density increases and technology geometry shrinks. As a result of the narrower distance, the capacitance between adjacent cells, which are referred to as the cell coupling capacitor (CCCP), increases and behaves as the source of crosstalk. The crosstalk is further aggravated by increasing operational speeds. When the sizes of the CCCP are marginal, they may not be detected by normal test patterns but can appear when various stresses accumulate. When they are not detected in an early manufacturing stage, they become the source of intermittent failures. Creating a complex test environment is sometimes rejected at the expense of higher parts per million of a device. In this paper, a negative voltage stress is applied to bit lines to test and diagnose the issues from the marginal CCCP. The negative voltage level is closely correlated to the CCCP size, which implies that the proposed method can be used as a vehicle to diagnose the potential issues due to cell coupling capacitors. The simulation results demonstrated that the negative stress voltage can screen the cell coupling capacitors from a few femtofarads to tens of femtofarads in an experimental circuit. The proposed technique has been validated by test chip using 130-nm technology. [ABSTRACT FROM PUBLISHER]

The European Union Restriction of Hazardous Substances Directive of 2006 has revolutionized the use of materials for electronic packaging: tin–lead solder has had to be replaced with lead-free solder. While years of experience and data acquired in the field are available for tin–lead solder, the same cannot be said for lead-free solder. The lack of data on these new alloys hinders the use of modeling for predicting the reliability of lead-free solder. This paper describes a new testing machine that can assess the properties of solder joints in a copper–solder–copper structure. Finite-element analysis models using the newly acquired data will improve lifetime predictions. During a typical test, a model solder joint is expanded and contracted in shear. This actuation is achieved from the thermal expansion of a steel tube, which provides a smooth movement at a rate that is equivalent to that encountered on printed circuit boards when thermally stressed. The applied force is measured using a load cell; the sample displacement is determined from laser displacement sensors. Hysteresis load–displacement loops are obtained and can be used for evaluating the material plastic response and loading history. A camera/microscope system captures time-lapse photography images, which digital image correlation software can analyze to obtain strain profiles and study crack propagation. The instrument is capable of investigating creep, stress relaxation, and isothermal and thermal–mechanical fatigue behavior of solder interconnects. Results from this new instrument are presented here for isothermal and thermal cycling fatigue tests. [ABSTRACT FROM PUBLISHER]

This paper presents a novel approach in assessing material damage resulted from micro- and mesostructural variations. We measured acoustic signals of randomly generated microscopic events (RGMEs) due to these variations and extracted the acoustic signals that represent the most physical essence of the RGME. To integrate the components of the measurements, we defined a variate \BBD such that it establishes the spectrum of the RGME amplitude. We then employed Gibbs probabilistic entropy s to quantify the spectrum. When correlated with the applied stress, we proposed a novel s– \sigma relationship. This relationship depicts the evolving state of RGME as the stress field varies. We evidenced that entropy s can be used to assess the material's damage states such that if the current stress level does not exceed the previous maximum, damage is in the states of “not-yet-the-maximum” by being either in “equientropy” or “vertical increment s” processes using a sample polymer material. We also evidenced that the essence of the well-known Kaiser effect is its “memory” of damage. The significance of this variate or s is that it takes into account the effects of the RGME on the material macroscopic behavior. A broader merit of our proposed approach lies within its great practical potential that connects the micro- and macrobehaviors of the materials through a set of simple mechanical tests. [ABSTRACT FROM AUTHOR]

Friction, generated in the contact patch between tires and runway, has long been recognized as a key issue to a safe landing. Moreover, soft sensing technology is also considered to be one of the effective means to improve measurement accuracy and reduce measurement cost of friction coefficient. This article presents a study on the prediction methods of runway friction coefficient based on multivariable coupling. Firstly, the relationships between friction coefficient and tread frictional stress under different working conditions are investigated using finite element analysis; meanwhile, the modeling dataset and test datasets for multivariate coupling are established. Secondly, regression analysis and BP neural network (BPNN) are used to develop prediction models between independent variables (inflation pressure, load, velocity, slip, and frictional stress) and dependent variable (friction coefficient). Finally, the prediction models are evaluated based on internal and external verification. The results demonstrate the superior performance of both prediction models. After further comparison, it is concluded that the performance of BPNN is even better combining the error range and model evaluation indicators including MAE, RMSE, and ${R}^{2}$. [ABSTRACT FROM AUTHOR]

Measurements on soft magnetic materials were made to determine the measurement capabilities available to the partners of a government-funded collaborative research project, with 16 partners from industry and academia. One of the objectives of this project was the development of advanced magnetic materials for novel electrical machines for use in harsh environments such as gas turbines. To establish the measurement confidence necessary to deliver this project objective, an equivalence study was undertaken. A reference core of soft magnetic material that has been measured over a period of many years at the National Physical Laboratory (NPL) was distributed and the dc and ac properties were measured. The measurement systems of the three laboratories are independent and this ensured that no correlations that could skew the results existed. In the analyses, the measurements at NPL were used as the baseline. With the core capabilities established, it was possible to develop the new measurements required to deliver the overall project objectives. At NPL, a standard permeameter method was modified for the measurement of strips. This was incorporated into a stress machine to measure the dc properties of the soft magnetic materials used by the partners, at stress levels of up to 700 MPa. The results for seven materials are presented and the changes in the properties with applied stress compared to establish which materials exhibit favorable properties. [ABSTRACT FROM AUTHOR]

In the recent decade, high-throughput plant phenotyping techniques, which combine noninvasive image analysis and machine learning, have been successfully applied to identify and quantify plant health and diseases. However, these techniques usually do not consider the progressive nature of plant stress and often require images showing severe signs of stress to ensure high confidence detection, thereby reducing the feasibility for early detection and recovery of plants under stress. To overcome the problem mentioned above, we propose a deep learning pipeline for the temporal analysis of the visual changes induced in the plant due to stress and apply it to the specific water stress identification case in Chickpea plant shoot images. For this, we have considered an image dataset of two chickpea varieties JG-62 and Pusa-372, under three water stress conditions: control, young seedling, and before flowering, captured over five months. We have employed a variant of convolutional neural network-long short-term memory (CNN-LSTM) network to learn spatiotemporal patterns from the chickpea plant dataset and use them for water stress classification. Our model has achieved ceiling level classification performance of 98.52% on JG-62 and 97.78% on Pusa-372 chickpea plant data and has outperformed the best reported time-invariant technique by at least 14% for both JG-62 and Pusa-372 species to the best of our knowledge. Furthermore, our CNN-LSTM model has demonstrated robustness to noisy input, with a less than 2.5% dip in average model accuracy and a small standard deviation about the mean for both species. Finally, we have performed an ablation study to analyze the performance of the CNN-LSTM model by decreasing the number of temporal session data used for training. [ABSTRACT FROM AUTHOR]

Studies show that the demagnetization effect of the pipeline wall affects the detection accuracy and detection range of the pipelines’ weak magnetic stress internal detection (WMSID). This study deals with mathematical modeling of the WMSID under the demagnetization effect. Moreover, the interference characteristics of the demagnetization effect on the weak magnetic signal (WMS) are analytically calculated, and the transfer features of WMSs are studied. Obtained results show that, in the transmission medium, the demagnetization effect produces an interfering magnetic field. It is found that performing the demagnetization effect calculation can reduce the calculation error of the mathematical model by 27.6%. Moreover, the demagnetization impact on the pipeline wall material complicates detecting the stress concentration zone (SCZ) on the pipeline’s outer wall. Normal component WMS has high stability in the pipeline wall material so that it is an appropriate choice for detecting the SCZ on the pipeline’s outer wall. Finally, the BiHill function is introduced to fit the excitation curve of the WMS. [ABSTRACT FROM AUTHOR]

Errors induced by pillar taper and eccentric load in micropillar compression experiments have seldom been investigated, although they significantly affect the measurement accuracy, especially in the testing of specimens in a micrometer and nanometer size. A novel calibration method related to stress–strain responses in micropillar compression testing was proposed in this study to eliminate this kind of errors. Axial load and eccentric load were applied to high-entropy alloy (HEA) pillars with taper angles of 1°, 2°, and 3°, respectively, and the measured stress–strain curves were corrected by the proposed calibration method. The results revealed that the difference of the corrected curves with different tapers or eccentricities was smaller than the measured curves. The errors induced by the taper and eccentric load increased with the taper angle and eccentricity. In addition, the difference between measured and corrected flow stresses increased with the taper angle, which was essentially consistent with the results from the calibration method. [ABSTRACT FROM AUTHOR]

The metal magnetic memory (MMM) inspection technology is an effective method to detect the stress damage of ferromagnetic materials, and it especially possesses great application potential in the field of long-distance oil and gas pipeline weld crack detection. In order to study the MMM generation mechanism and the signal feature of weld cracks, a model to quantitatively calculate the MMM signal of nonuniform magnetic charge of internal inspection is proposed. The effect of changes to the crack depth, the crack width, and the pipeline internal pressure on the MMM signal is studied, and the theoretical results have been proved by extensive experimental studies. The results indicate that the axial component has only one peak value, while the radial component has two pairs of independent and zero-crossing peak-to-peak values, of which the outside pair corresponds to the weld and the inside pair corresponds to the crack. The feature values change nonlinearly with the crack depth, and the growth rate decreases gradually. The feature values increase linearly with the crack width, and the radial component is more sensitive to width than the axial component. The internal pressure will increase the stress concentration around the weld and the crack, but the stress around the crack responds more sensitively. Therefore, the MMM signal is positively correlated with the internal pressure, and the feature value will increase linearly. [ABSTRACT FROM AUTHOR]

This article presents a mass sensor based on a low-frequency MEMS resonator. Its mechanical structure grants a linear relationship between the measured mass and resonance frequency. The presence of an embedded AlN layer allows for exploiting piezoelectric actuation and sensing and for using a simple and low-cost read-out electronics. In this article, the linear behavior of the sensor is demonstrated by finite-element method (FEM) modal analysis, by developing a simple lumped parameter model and by experimental campaigns. Moreover, in this article, the device performance in terms of piezoelectric transduction is theoretically analyzed and demonstrated using both FEM analysis and experiments, showing that the proposed MEMS device is suitable also for applications in the low-power electronics scenario. [ABSTRACT FROM AUTHOR]

A novel direct measurement strategy of wave near-bed velocity and bottom shear stress based on the use of ferrofluids is presented. The proposed methodology is aimed at overcoming some of the limits of state-of-the-art instruments, for use in presence of both surface waves and sediments. An inductive readout strategy is proposed to sense displacements of the ferrofluid spike over the inductive circuit due to the flow. Experimental tests have been performed in a wave tank both in hydrostatic conditions and in the presence of regular linear waves corresponding to deep and intermediate water depth cases. Obtained results indicate the applicability of the proposed strategy also in the presence of suspended load (either moderate or intense) and of a moderate bed load transport. [ABSTRACT FROM PUBLISHER]

The design and performance of a technique for determining 2-D cross-sectional stress distributions in optical fibers and fiber-based devices is described. The Brace-Köhler phase compensation method is implemented on a commercial polarization microscope to perform full-field measurements of the transverse retardations induced by the low levels of birefringence in optical fibers. Analysis of the region surrounding the fiber enables removal of the background retardation induced by the imaging optics. A custom microscope stage plate, fiber rotation apparatus, and compensator rotation apparatus allow for semi-automated measurements at various angular orientations of the fiber. Image analysis techniques are described that reduce the number of angular increments over which the compensator must be rotated, thus providing a more workable total data acquisition time. Computed tomography principles and the filtered backprojection algorithm are implemented to determine full cross-sectional axial stress distributions. The lateral spatial resolution of the technique is 0.46 \mu\m . The axial stress distribution in Corning SMF-28 fiber is presented. The resolution of the axial stress determined with the technique is estimated to be 0.24 MPa. The accuracy of the axial stress is estimated to be \pm0.18 MPa. [ABSTRACT FROM AUTHOR]