The quasi-steady flow assumption (QSFA) is commonly used in the field of biomechanics of phonation. It approximates time-varying glottal flow with steady flow solutions based on frozen glottal ...shapes, ignoring unsteady flow behaviors and vocal fold motion. This study examined the limitations of QSFA in human phonation using numerical methods by considering factors of phonation frequency, air inertance in the vocal tract, and irregular glottal shapes. Two sets of irregular glottal shapes were examined through dynamic, pseudo-static, and quasi-steady simulations. The differences between dynamic and quasi-steady/pseudo-static simulations were measured for glottal flow rate, glottal wall pressure, and sound spectrum to evaluate the validity of QSFA. The results show that errors in glottal flow rate and wall pressure predicted by QSFA were small at 100 Hz but significant at 500 Hz due to growing flow unsteadiness. Air inertia in the vocal tract worsened predictions when interacting with unsteady glottal flow. Flow unsteadiness also influenced the harmonic energy ratio, which is perceptually important. The effects of glottal shape and glottal wall motion on the validity of QSFA were found to be insignificant.
This paper presents a novel method for the performance of an all-silicon accelerometer by adjusting the ratio of the Si-SiO
bonding area, and the Au-Si bonding area in the anchor zone, with the aim ...of eliminating stress in the anchor region. The study includes the development of an accelerometer model and simulation analysis which demonstrates the stress maps of the accelerometer under different anchor-area ratios, which have a strong impact on the performance of the accelerometer. In practical applications, the deformation of the comb structure fixed by the anchor zone is influenced by the stress in the anchor region, causing a distorted nonlinear response signal. The simulation results demonstrate that when the area ratio of the Si-SiO
anchor zone to the Au-Si anchor zone decreases to 0.5, the stress in the anchor zone decreases significantly. Experimental results reveal that the full-temperature stability of zero-bias is optimized from 133 μg to 46 μg when the anchor-zone ratio of the accelerometer decreases from 0.8 to 0.5. At the same time, the full-temperature stability of the scale factor is optimized from 87 ppm to 32 ppm. Furthermore, zero-bias full-temperature stability and scale factor full-temperature stability are improved by 34.6% and 36.8%, respectively.
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An optical sulfonamides sensor is fabricated based on a molecular imprinted resin templated by nanocrystalline cellulose. A chiral nematic imprinted composite film is synthesized ...which is subsequently treated with removal of templates to generate a red reflecting photonic film. The film shows a naked-eye color response to sulfanilamide, which is related to reassemble imprinted sites in the chiral nematic structure, resulting in a yellow reflecting film. Upon exposure to various antibiotics, it can be simultaneously in selectively response to three sulfonamides. This strategy facilitates enormously potential application of the resin as battery-free and portative optical monitoring sensors.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Disc buckle steel pipe brackets are widely used in building construction due to the advantages of its simple structure, large-bearing capacity, rapid assembling and disassembling, and strong ...versatility. In complex construction projects, the uncertainties affecting the stability of disc buckle steel pipe support need to be considered to ensure the safety of disc buckle steel pipe supports. A surrogate model based on a deep neural network is built and trained to predict the ultimate load-carrying capacity of a stent. The results of the finite element model calculations are used to form the sample set of the surrogate model. Then, we combined the computationally efficient DNN surrogate model with the Monte Carlo method to consider the distribution of the ultimate load capacity of the disc buckle bracket under the uncertainties of the bracket node pin wedge tightness, the wall thickness of the steel pipe, and the connection of the connecting wall member. At the same time, based on the DNN model, the SHapley Additive exPlanations (SHAP) interpretability analysis method was used to study the degree of influence of various uncertainty factors on the ultimate bearing capacity of the stent. In practical engineering, the stability analysis of a disc buckle tall formwork support has shown that a surrogate model based on a deep neural network is efficient in predicting the buckling characteristic value of the support. The error rate of the prediction is less than 2%. The buckling characteristic values of the bracket vary in the range of 17–25. Among the various factors that influence the buckling characteristic value of the bracket, the joint wedge tightness has the greatest impact, followed by the bottom and top wall-connecting parts.
•Fuzzy least squares support vector regression is developed for cryogenic void fraction measurement.•The algorithm is evaluated for tiny capacitance measurement in LN2-VN2 flow.•A set of rules for ...sample selection are established.•Regression functions show comparably good prediction and anti-noise ability.
In order to improve the measurement accuracy of void fraction in cryogenic two-phase flow using the multi-electrode capacitance sensor, an algorithm based on the fuzzy least squares support vector regression (FLSSVR) is proposed to fit the void fraction and the capacitances. Liquid nitrogen-vapor nitrogen (LN2-VN2) are taken as the working pair for numerical experiments. Finite element calculations are firstly carried out to obtain the capacitance values of each pair of electrodes, then they are casted into a symmetric matrix, of which the eigenvalues are used as the inputs of the FLSSVR. Thus the dimensions of the sample space are evidently reduced, the computational load is accordingly reduced. In the sample selection process, a set of rules is established by using the centrosymmetric characteristics of this sensor, so that the number of independent variables is significantly reduced. Moreover, the fuzzy memberships are calculated based on the distances between the sample points and the regression hyperplane in the expanded feature space, which gives the regression function a better anti-noise ability. The feasibility of the algorithm applicable to void fraction measurement is verified by the numerical experiments. The results show that the regression functions obtained by FLSSVR have satisfying accuracy and anti-noise ability in calculating the void fraction of the involved two-phase flow in the pipe.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Nanofiber membranes were successfully prepared with crown ether (CE) functionalized graphene oxide (GO), chitosan (CS), and polyvinyl alcohol (PVA) by low-temperature thermally induced liquid-liquid ...phase separation. The physical and chemical properties and adsorption performance of nanofiber membrane were studied through SEM, FT-IR, XRD, and static adsorption experiments. The results show that the specific surface area of the nanofiber membrane is as high as 101.5 m
∙g
. The results of static adsorption experiments show that the maximum adsorption capacity of the nanofiber membrane can reach 168.50 mg∙g
when the pH is 7.0. In the selective adsorption experiment, the nanofiber membrane showed high selectivity for Li
in salt lake brine. After five cycles, the material still retains 88.31% of the adsorption capacity. Therefore, it is proved that the material has good regeneration ability.
This paper presents a high-performance MEMS accelerometer with a DC/AC electrostatic stiffness tuning capability based on double-sided parallel plates (DSPPs). DC and AC electrostatic tuning enable ...the adjustment of the effective stiffness and the calibration of the geometric offset of the proof mass, respectively. A dynamical model of the proposed accelerometer was developed considering both DC/AC electrostatic tuning and the temperature effect. Based on the dynamical model, a self-centering closed loop is proposed for pulling the reference position of the force-to-rebalance (FTR) to the geometric center of DSPP. The self-centering accelerometer operates at the optimal reference position by eliminating the temperature drift of the readout circuit and nulling the net electrostatic tuning forces. The stiffness closed-loop is also incorporated to prevent the pull-in instability of the tuned low-stiffness accelerometer under a dramatic temperature variation. Real-time adjustments of the reference position and the DC tuning voltage are utilized to compensate for the residue temperature drift of the proposed accelerometer. As a result, a novel controlling approach composed of a self-centering closed loop, stiffness-closed loop, and temperature drift compensation is achieved for the accelerometer, realizing a temperature drift coefficient (TDC) of approximately 7 μg/°C and an Allan bias instability of less than 1 μg.
Matrix multiplication is a dominant but very time-consuming operation in many big data analytic applications. Thus its performance optimization is an important and fundamental research issue. The ...performance of large-scale matrix multiplication on distributed data-parallel platforms is determined by both computation and IO costs. For existing matrix multiplication execution strategies, when the execution concurrency scales up above a threshold, their execution performance deteriorates quickly because the increase of the IO cost outweighs the decrease of the computation cost. This paper presents a novel parallel execution strategy CRMM (Concurrent Replication-based Matrix Multiplication) along with a parallel algorithm, Marlin, for large-scale matrix multiplication on data-parallel platforms. The CRMM strategy exploits higher execution concurrency for sub-block matrix multiplication with the same IO cost. To further improve the performance of Marlin, we also propose a number of novel system-level optimizations, including increasing the concurrency of local data exchange by calling native library in batch, reducing the overhead of block matrix transformation, and reducing disk heavy shuffle operations by exploiting the semantics of matrix computation. We have implemented Marlin as a library along with a set of related matrix operations on Spark and also contributed Marlin to the open-source community. For large-sized matrix multiplication, Marlin outperforms existing systems including Spark MLlib, SystemML and SciDB, with about 1.29×, 3.53× and 2.21× speedup on average, respectively. The evaluation upon a real-world DNN workload also indicates that Marlin outperforms above systems by about 12.8×, 5.1× and 27.2× speedup, respectively.
This study investigated the effects of structural dimension variation arising from fabrication imperfections or active structural design on the vibration characteristics of a (100) single crystal ...silicon (SCS) ring-based Coriolis vibratory gyroscope. A mathematical model considering the geometrical irregularities and the anisotropy of Young's modulus was developed via Lagrange's equations for simulating the dynamical behavior of an imperfect ring-based gyroscope. The dynamical analyses are focused on the effects on the frequency split between two vibration modes of interest as well as the rotation of the principal axis of the 2
mode pair, leading to modal coupling and the degradation of gyroscopic sensitivity. While both anisotropic Young's modulus and nonideal deep trench verticality affect the frequency difference between two vibration modes, they have little contribution to deflecting the principal axis of the 2
mode pair. However, the 4
variations in the width of both the ring and the supporting beams cause modal coupling to occur and the degenerate 2
mode pair to split in frequency. To aid the optimal design of MEMS ring-based gyroscopic sensors that has relatively high robustness to fabrication tolerance, a geometrical compensation based on the developed model is demonstrated to identify the geometries of the ring and the suspension.
This study presents a novel method that combines a computational fluid-structure interaction model with an interpretable deep-learning model to explore the fundamental mechanisms of seal whisker ...sensing. By establishing connections between crucial signal patterns, flow characteristics, and attributes of upstream obstacles, the method has the potential to enhance our understanding of the intricate sensing mechanisms. The effectiveness of the method is demonstrated through its accurate prediction of the location and orientation of a circular plate placed in front of seal whisker arrays. The model also generates temporal and spatial importance values of the signals, enabling the identification of significant temporal-spatial signal patterns crucial for the network’s predictions. These signal patterns are further correlated with flow structures, allowing for the identification of important flow features relevant for accurate prediction. The study provides insights into seal whiskers’ perception of complex underwater environments, inspiring advancements in underwater sensing technologies.
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