Sound radiation is a critical factor in the design of engineering structures to obtain good sound insulation. The analysis of sound radiation with uncertainty has received considerable research ...attention over the recent years. In this study, a novel method called symmetric matrix decomposition hybrid perturbation method is proposed to predict the global sound radiation from structural-acoustic systems with hybrid uncertainty based on the total sound power. Firstly, the acoustic radiation mode approach is used to estimate the total sound power, and the computational method is improved by using the symmetry of radiation resistance matrix. Then, a finite element model is established for the structural-acoustic system with hybrid random and interval uncertainties. Based on the perturbation technique and Taylor expansion, the lower and upper bounds of the expectation and variance of the sound power response are derived. Finally, the feasibility and effectiveness of the proposed method is validated through numerical examples. The results show that the proposed method is comparable to the Monte Carlo simulations. The method can not only deal with the influence of uncertainty of the acoustic environment on the total sound power but also can be used to address pure stochastic problems of the sound radiation. Overall, this study effectively promotes the analysis of sound radiation problem with uncertainty based on the sound power.
This paper develops an efficient reliability analysis method for composite structures with high-dimensional uncertain variables. The concept and mathematical definition of the approximate design ...point (ADP) and the approximate important direction (AID) are introduced. A fast calculation ADP/AID formula is proposed. A numerical line sampling (LS) strategy is devised, which is further combined with ADP/AID to form a novel reliability method, named AID-LS. An equivalent criterion is introduced to address the problems with the non-normal random variables. A stochastic mechanical model of composite structures with geometrical nonlinearity is established based on first-order shear deformation theory and implemented with finite element analysis (FEA). Numerical examples are given to demonstrate the validity of the proposed method. The results show that the proposed method can significantly reduce the number of FEA samples in the reliability analysis of composite structures.
Yarn hairiness affects yarn and fabric quality. The existing hairiness detection methods cannot discriminate crossover fibers or hairs. In order to accurately separate and detect crossover fibers, an ...algorithm of separating crossover hairs is proposed. By obtaining refined hair skeletons after image pretreatment, the positions of fiber intersection point were determined, and a hair information table according to the characteristics of the hair cross-point was constructed. After classifying each hair branch skeleton and screening out the hair common skeleton, the branch hair matching table by using the two end points of the true common hair skeleton adjacent to the hair branch was constructed. Through pairing the same cross-hair branch with the principle of the closest slope at the adjacent cross-end, each complete cross-hair skeleton was defined for hair count in a field of view. The detection results show that compared with the existing photoelectric hairiness detection instrument, the algorithm can realize the crossover hair separation, and calculate the length of complete crossover hairs and curved hairs with high accuracy. On average, the developed algorithm measures hair length about 11.1% longer than the manually measured results, while commercial apparatus would report hair length 62.5% shorter than the actual hair length.
Because of the operating environment and load, the main fault form of flywheel bearing is the friction fault between the cage and the rolling elements, which often lead to an increase in the friction ...torque of the bearing and even to the failure of the flywheel. However, due to the complex mechanism of the friction fault, the characteristic frequencies often used to indicate cage failure are not obvious, which makes it difficult to monitor and quantitatively judge such faults. Therefore, this paper studies the mechanism of the friction fault of the flywheel bearing cage and establishes its fault feature identification method. Firstly, the basic dynamic model of the bearing is established in this paper, and the friction between the cage and the rolling elements is simulated by the variable stiffness. The influence law of the bearing vibration response reveals the relationship between the periodic fluctuation of cage-rolling element friction failure and the bearing load. After analyzing the envelope spectrum of the vibration data, it was found that when a friction fault occurred between the cage and the rolling element, the rotation frequency component of the cage modulated the rotational frequency component of the rolling element, that is, the side frequency components appeared on both sides of the characteristic frequency of the rolling element (with the characteristic frequency of the cage as the interval). In addition, the modulation frequency components of the cage and rolling element changed with the severity of the fault. Then, a modulation sideband ratio method based on envelope spectrum was proposed to qualitatively diagnose the severity of the cage-rolling element friction faults. Finally, the effectiveness of the presented method was verified by experiments.
Yarn–yarn sliding force plays a vital role in absorbing impact energy for plain fabrics. This paper reports the methods and results of an investigation on the mechanisms that enable higher yarn ...pull-out force of woven fabrics with the incorporation of lenos and knits. The experimental results suggested that the insertion of leno lines on plain weave gives an approximately 20% increase in junction rupture force over the original plain construction. With knitted structures inserted, the structure-modified fabrics showed a junction rupture force up to about 15 times higher than simple plain weave. It was even found that the yarns failed rather than pulled out in multiple yarn pull-out tests. This is because knitted structures tend to become self-locked and consequently restrict yarn displacement when subjected to external loading. This investigation reports a method to increase the frictional force between the warp and weft yarns based on textile technologies. It is expected that the results obtained could provide some useful information for the engineering design of flexible ballistic protection systems.
Cattail is widely abounding in wetlands and marshes and is usually considered as an abundant and inexpensive biomass lignocellulose resource due to its rapid growth. In this paper, a novel cellulose ...(named as TOCF) separator for Li-ion batteries (LIBs) is successfully fabricated from cattail fibers by 2, 2, 6, 6-tetramethylpiperidine-1-oxyl (TEMPO) oxidation and vacuum filtration. The proposed TOCF membrane shows good tensile strength (75 MPa), superior thermal dimensional stability, sufficient porosity (64.8%), outstanding liquid electrolyte uptake (323%) as well as large ionic conductivity (2.83 mS cm
−1
). Moreover, the Li/LiFePO
4
cell assembled using the TOCF separator demonstrates better discharge capacity and cycling stability than the cell with a commercial Celgard separator. Thus, the TOCF separator is a promising and low-cost candidate used in high-performance LIBs.
•A new strategy for interval identification of structural parameters is proposed.•Accurate response intervals are obtained by use of MC simulation and surrogate models.•Interval overlap ratio is ...constructed based on the concept of interval length.•The proposed method has high precision in identifying intervals of input parameters.
In this paper, a new interval finite element (FE) model updating strategy is proposed for interval identification of structural parameters in the aspect of uncertainty propagation and uncertainty quantification. The accurate interval estimation of system responses can be efficiently obtained by application of Monte Carlo (MC) simulation combined with surrogate models. By means of the concept of interval length, a novel quantitative index named as interval overlap ratio (IOR) is constructed to characterize the agreement of interval distributions between analytical data and measured data. Two optimization problems are constructed and solved for estimating the nominal values and interval radii of uncertain structural parameters. Finally, the numerical and experimental case studies are given to illustrate the feasibility of the proposed method in the interval identification of structural parameters.
This paper reports an improved traditional fiber degumming method, where sisal fibers were treated by alkali oxygen and pectinase, respectively, after the solute alkali pretreatment. To explore the ...influence of various factors on its degumming, efficiency of degumming through single factor and orthogonal experiments was aasessed. The results showed that pectinase/alkali-oxygen method after the first alkali treatment had a good effect on the degumming of sisal fiber, and most of the non-cellulose components such as hemicellulose, lignin and pectin had been removed. After pectinase treatment, the cellulose content and crystallinity were 71.87% and 66.29%, respectively. After alkaline oxygen treatment, the cellulose content was 77.16%, and the crystallinity was 69.09%. In terms of degumming rate, alkali oxygen treatment worked better than pectinase treatment, the degumming rate of pectinase method was about 10%, while that of alkali-oxygen method was more than 20%. In other hand, the pectinase method was much milder and had less damage to fibers. It would provide some references for the future application and development of sisal fiber.
Finite element model updating precision depends heavily on sufficient vibration feature extraction. However, adequate amount of sample collection is generally time-consuming in frequency response ...(FR) model updating. Accurate vibration feature extraction with insufficient data has become a significant challenge in FR model updating. To update the finite element model with a small dataset, a novel approach based on transfer learning is firstly proposed in this paper. A readily available fault diagnosis dataset is selected as ancillary knowledge to train a high-precision mapping from FR data to updating parameters. The proposed transfer learning network is constructed with two branches: source and target domain feature extractor. Considering about the cross-domain feature discrepancy, a domain adaptation method is designed by embedding the extracted features into a shared feature space to train a reliable model updating framework. The proposed method is verified by a simulated satellite example. The comparison results manifest that sample amount dependency has prominently lessened this method and the updated model outperforms the method without transfer learning in accuracy with the small dataset. Furthermore, the updated model is validated through dynamic response out of the training set.
With the rapid development of flexible electronic device, yarn supercapacitors (YSCs) as one kind of flexible energy storage devices are attracting more and more attention. Carbon nanotube (CNT) and ...conductive polymers are widely investigated as potential active materials in energy storage field. Bacterial cellulose (BC) nanofiber is one of highly promising alternatives to the flexible substrates. Hence, an all-solid-state YSC is successfully fabricated via twisting CNT@BC membrane and electrochemically depositing polypyrrole. The proposed YSC demonstrates a high areal capacitance of 458 mF cm
−2
at a current density of 0.8 mA cm
−2
as well as a robust cycling stability (no significant degradation in capacitance after 2000 cycles). Moreover, the proposed YSC is comparatively flexible, confirming it as a promising power source candidate for portable and wearable electronics.
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