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PurposeCurrent measurement methods for fabric comfort attributes generally suffer from either complicated testing processes and intricate measuring equipment or partial evaluation objectives and thus are difficult for effectively evaluating multidimensional human perceptions towards the comprehensive comfort of fabrics. The purpose of this paper is to develop a facile test device, namely fabric comfort tester, to achieve a comprehensive evaluation of human sensations in terms of sensorial, thermal and acoustic comfort in clothing.Design/methodology/approachThe prototype of the designed device was introduced, which enables a simultaneous test for multiple physical and mechanical properties of fabrics based on a force sensor and a set of infrared sensors via constructing multi-deformation states of the measured fabrics. Eleven measurement indices extracted from the measurement curves are defined and interpreted based on correlation analysis. A series of regression models are developed by relating the measurement indices with subjective evaluation results and validated by a set of independent samples.FindingsHuman perceptions of sensorial, thermal and acoustic comfort in clothing can be predicted by the measured physical indices and the designed test device with the developed regression models provides an alternative method to characterize the fabric comfort attributes effectively.Originality/valueThe work develops a novel device for objective evaluation of fabric comfort properties by a simultaneous test, integrating the mechanical measurement with thermal test and thereby filling the gap between the existing evaluation methods and practical requirements for the digitalization of fabric comfort in present textile and garment trade.

This study aimed to analyse the relationship between perceived social support and marital quality in balanced translocation patients and their spouses undergoing a preimplantation genetic testing (PGT) treatment cycle in China. The authors assessed the actor and partner effects of perceived social support on marital quality in patient-spouse dyads using a dyadic analysis approach. In total, 59 couples were assessed using self-report questionnaires for marital quality and perceived social support. There were significant differences in marital quality between patients and their spouses (

Carbon nanotubes (CNTs) produced by catalytic reforming of the waste plastic syngas is a high value-added by-product of hydrogen production. Catalysts play an important role in the growth of carbon nanotubes. The influences of Ni/ZSM-5 catalyst, Ni–Mn/ZSM-5 catalyst and temperature were performed in a lab-scale tubular reactor. The catalysts and product carbon were analyzed by different characterization methods, including temperature-programed reduction/oxidation, X-ray diffractometer, scanning electron microscope, transmission electron microscope, X-ray energy spectrometer. The results showed that in the presence of Ni–Mn/ZSM-5 catalyst with the addition of catalytic promoter Mn, 650 °C was the optimum temperature during the operating temperature range of 600 °C~800 °C for the rate of carbon production and hydrogen production, and the carbon production was the highest, which was 2.95gCNTs/gCatalyst (wherein the Multi-walled carbon nanotubes (MWCNTs) were main product), and compared with the monometallic Ni/ZSM-5 catalyst, the Ni–Mn/ZSM-5 catalyst with Mn addition increased the H2 content in the syngas from 14 Vol.% to 39 Vol.%. The highest carbon nanotubes proportion of 95.81% to total carbon deposition was obtained under the conditions of 750 °C. The introduction of catalytic promoter Mn transforms the growth mode of carbon nanotubes from top growth mode to bottom growth mode, and obtains carbon nanotubes with more regular structure. It suggested that Ni–Mn/ZSM-5 catalyst had the potential for high quality carbon nanotubes and H2-riched gas production from waste plastic syngas.

Aiming at the laborious process in motor structure modeling for acoustic noise calculation, an improved stator structure modeling scheme is proposed, which includes stator structure simplification and equivalent material parameters identification. The stator assembly is modeled as a homogeneous solid with the same size as the stator core, and the influence of model simplification is compensated by orthotropic equivalent material parameters. The equivalent material parameters are acquired through an optimization algorithm by minimizing the error between FEM calculated modal frequencies and the modal tested results. With the stator assembly model, the motor assembly model is built, and the constrained modal characteristics of the motor assembly are verified by comparing the modal frequencies to the resonance bands in the vibration acceleration spectrum. Finally, the motor structure model is used to calculate the electromagnetic noise of an induction motor. As the calculated result matches well with the tested data, the applicability of the proposed motor structure modeling scheme for electromagnetic noise calculation is validated. The proposed method can greatly reduce the workload in motor structure modeling without sacrificing the accuracy and applicability of the model.

The accurate prediction and analysis of electromagnetic excitation source is the pre-condition for the investigation of electromagnetic vibration and noise. In this work, an analytical model for electromagnetic (EM) force calculation of interior permanent magnet synchronous motors (IPMSMs) is proposed by coupling the 2-D model in polar coordinates and the Maxwell stress tensor method (MSTM). In the modeling, the boundary conditions for solving the air-gap magnetic field are firstly simplified based on the equivalent conversion of permanent magnets (PMs). Then, the magnetic field is acquired by solving the governing equation based on the simplified boundary conditions. Finally, the EM force is obtained according to the MSTM. The effectiveness is fully verified by finite element (FE) analysis that the analytical model can be applied not only for the calculation of radial EM force of IPMSMs with/without load but also for the calculation of tangential EM force. Besides, the tangential EM force is further analyzed by 2-D Fourier decomposition, and the relationship between tangential EM force and torque fluctuation is also clarified. The results show that the radial EM force harmonics and the tangential EM force harmonics have the same spatiotemporal characteristics no matter under no-load or load. Moreover, the high-frequency components of tangential EM force harmonics with low spatial orders, which have the highest contribution to vibration and noise, are comparable to those of radial EM force harmonics. Meanwhile, the torque fluctuation of IPMSMs with/without load only comes from the zero-order tangential EM force harmonics in space.

Different resonance constraints enrich the behavior of soliton solutions. The soliton molecules, which are the bound states of solitons, can be set off by the velocity resonance. The lump waves, which are localized in all directions in space, are theoretically regarded as a limit form of soliton in some ways. In this paper, a (2+1)-dimensional Sharma–Tasso–Olver–Burgers (STOB) equation is investigated. Soliton (kink) molecule, half periodic kink(HPK) and HPK molecule are studied. Then the lump solution is obtained and the interactions between lump and kink molecule are discussed. The kink molecule-lump solutions exhibit a fusion phenomenon and a rogue (instanton) phenomenon, respectively.

Interior permanent magnet synchronous motors (IPMSMs) have been widely used as drive machines in electric vehicles (EVs) due to their high torque density. However, the torque ripple of IPMSMs will result in severe noise and vibration. This paper proposes a new analytical method for electromagnetic torque prediction and harmonic reduction of IPMSM. On the basis of dq theory, an analytical model of electromagnetic torque is firstly established by taking the permanent magnet flux harmonics and the cross-coupling effect into consideration. And the specific sources and orders of torque harmonics are also determined. Then, the torque-angle characteristics are further studied. In particular, the permanent magnet (PM) torque and the reluctance torque are separated and quantitatively analyzed via the proposed analytical model. Finally, a theoretical method of reducing the specific order torque harmonic by PM shifting is derived and proposed from the perspective of avoiding resonance. The accuracy and effectiveness of the proposed analytical method are verified by finite-element analysis. The results show that the proposed analytical model is accurate enough to predict the electromagnetic torque performance of IPMSM. Moreover, the electromagnetic torque harmonics with specific orders can be effectively reduced by shifting the PM to an appropriate angle.

Electric wheel system (EWS) has become a research hotspot of the electric vehicle. As motor torque is directly exerted on wheels, torque ripples could induce longitudinal vibration that is more noticeable than traditional vehicles. In this article, the influence of rotor position error on the longitudinal vibration of the EWS is analyzed and suppressed. First, a bench test of EWS is conducted to observe the characteristics of the longitudinal vibration and harmonic components in the phase current. Then, by constructing an analytical model, the influence of rotor position error on the phase current and torque ripple is discussed. Moreover, with a dynamic model of the EWS, the longitudinal vibration considering the rotor position error is deduced. As the analytical and experimental results are consistent, the accuracy of the models is proven, and the relationship between rotor position error and longitudinal vibration of the EWS is clarified. Finally, to attenuate the longitudinal vibration related to rotor position error, an observer based on the extended Kalman filter is designed to replace the variable reluctance resolver for rotor positioning. The simulation result verifies the feasibility of the observer as well as its effectiveness in longitudinal vibration control.

Oxygen-steam gasification of biomass catalyzed by modified iron-rich red mud extract is firstly performed in our work. During the impregnation of the modified red mud extract (MRME), the pore structure characteristics and thermal behavior of the maize straw changed significantly. The influence of MRME on syngas quality, gas yield, and thermal efficiency were performed in a lab-scale gasification reactor. The results showed that higher temperature, sufficient MRME addition, appropriate equivalent ratio (ER) and a small amount of steam all promoted syngas quality and energy conversion. For maximum economic efficiency, the optimal rate of MRME addition is 30% weight ratio to maize straw. The optimal level of ER was found to be 0.23, and the maximum energy conversion ratio was 82.4% at 800 °C with optimal levels of MRME addition and ER. Compared with the raw maize straw gasification at the same operating condition, the content of H2 increased from 17.32% to 33.77%, and CO raised from 22.89% to 35.11%. It seems that the red mud extract catalyst has the potential for using as an economic efficiency industrially catalyst for high quality and H2-riched syngas production from biomass gasification.

Liver cirrhosis is a clinical chronic developmental liver disease, which is caused by long-term or repeated effects of liver dysfunction, and there are more and more cases of epileptic seizures in patients with liver cirrhosis and HEV infection. This article aims to study how to analyze epileptic seizures in patients with liver cirrhosis and overlapping HEV infection based on deep multimodal fusion technology. This article proposes a deep learning neural network algorithm based on deep multimodal fusion technology, and how to use this algorithm to automatically detect and classify epileptic seizures. The data in the experiment in this article show that the prevalence of epilepsy accounts for 1% of the world's population, about 56.7 million people, and 1 in 25 people may have an epileptic seizure at some time in their lives, and in each person’s life, the probability of seizures due to various reasons is 10%. In 2016, the proportion of males with cirrhosis reached 16%, females reached 8%, and males were 8% higher than females, which is a full double. The test results show that with the increase in patients with cirrhosis and overlapping HEV infection, the frequency of epileptic seizures is also getting higher and higher, indicating that the frequency of epileptic seizures has been increased in patients with cirrhosis and overlapping HEV infection. Therefore, it is imperative to analyze the epileptic seizures of patients with liver cirrhosis and overlapping HEV infection based on deep multimodal fusion technology.

Calculating accurately iron bridge saturation effects of the magnetic field, for Permanent Magnet Assisted Synchronous Reluctance Motors (PMASynRMs), remains to be a knotty problem. This paper presents an analytical modeling method to predict open-circuit magnetic field distributions and electromagnetic performances of PMASynRMs, considering iron bridge saturation effects. This analytical modeling method combines the magnetic equivalent circuit method, superposition principle, the solution of the governing Maxwell’s field equations and a complex relative permeance function. A quadruple-layer PMASynRM are remodeled into four surface-inserted permanent magnet synchronous motors (SPMSMs) which have different surface-inserted permanent magnets. Each layer of the interior permanent magnets of the PMASynRM is transformed into a new equivalent surface-inserted permanent magnet whose equivalent thickness needs to be defined by the magnetic equivalent circuit method due to iron bridge saturation effects. Based on superposition principle and the solution of the Laplace’s or Poisson’s field equation, the distribution characteristics of the radial and tangential magnetic flux density are obtained for PMASynRMs. The slotting effect is considered by a complex relative permeance function. To confirm the accuracy of the proposed analytical modeling method, the analytical solutions of magnetic flux density and cogging torque have been compared with Finite Element Method (FEM) simulation results. The root mean square errors of radial and tangential magnetic flux density between analytical and FEM results are 0.000553 and 0.0000916 respectively. The results indicate that the proposed analytical modeling method can consider iron bridge saturation effects effectively, which is suitable for performance predictions and parametric studies of PMASynRMs.

A testing apparatus, namely, touch sensation tester for fabrics (TST-F), was introduced to evaluate the touch properties of fabrics. This novel apparatus enables a simultaneous measurement of different mechanical properties of the sample with a combination of temporal and spatial resolution, enhancing the measuring accuracy and reliability of the time-dependent physical behavior of textile materials. The prototype of the TST-F and details of the measurement principle were exhibited, and nine indices relating to fabric’s deformation performance during wearing were extracted from measured force–displacement curve to characterize the mechanical properties relating to fabric’s touch sensory attributes. Stepwise regression was used to develop a series of prediction models for assessing human sensations toward bending stiffness, compression softness, and stretching tightness of fabrics by linking the measured indices to subjective assessments. Moreover, the prediction models were validated using a set of independent fabric samples. Results show that prediction values have good agreements with subjective grades as indicated by the coefficients of determination R2 higher than 0.887 and reasonably low mean square errors (MSEs). Also, the repeatability of the measured curves was confirmed by statistical analysis. Therefore, the TST-F provides an alternative to evaluate the touch properties of fabrics objectively.