The prediction of vibration and noise for the high-speed train based on neural network and boundary element method

The vibration acceleration of the high-speed train is an important parameter reflecting the state of track irregularities and the quality of contact between wheel and rail. A model for predicting vibration acceleration of the high-speed train based on nonlinear auto-associative neural network (NARX NN) and multi-body dynamics model is built. In order to improve the prediction precision, the parameters such as the order of time-delay and hidden nodes are determined by traversal method. The vibration acceleration computed by the NN model is then compared with that computed by SIMPACK model. The corresponding results show that the output of NARX NN is highly consistent with those of the multi-body dynamics model. Then, the vibration acceleration computed by NN model is used to compute the low frequency noise of the high-speed train. The computational results are also compared with those of the experimental values, and they are consistent with each other. It shows that the computational noises are reliable, and it also indirectly indicates that the vibration acceleration predicted by NN model is credible. Otherwise, the computational results will deviate far away from the experimental value

Synthesis of ultrathin platinum nanoplates for enhanced oxygen reduction activity.

Ultrathin Pt nanostructures exposing controlled crystal facets are highly desirable for their superior activity and cost-effectiveness in the electrocatalytic oxygen reduction reaction (ORR), and they are conventionally synthesized by epitaxial growth of Pt on a limited range of templates, such as Pd nanocrystals, resulting in a high cost and less structural diversity of the ultrathin Pt nanostructures. To solve this problem, we demonstrate that ultrathin Pt nanostructures can be synthesized by templating conveniently available Ag nanocrystals without involving galvanic replacement, which enables a much-reduced cost and controllable new morphologies, such as ultrathin Pt nanoplates that expose the {111} facets. The resulting ultrathin Pt nanoplates are ∼1-2 nm in thickness, which show an ∼22-fold increase in specific activity (5.3 mA cm-2), an ∼9.5-fold increase in mass activity (1.62 A mg-1) and significantly enhanced catalytic stability in the ORR, compared with the commercial Pt/C catalyst. We believe this strategy opens a door to a highly extendable family of ultrathin noble metal nanostructures, thus promising excellent activity and stability in a broad range of catalytic applications

A Superdirective Beamforming Approach with Impedance Coupling and Field Coupling for Compact Antenna Arrays

In most multiple-input multiple-output (MIMO) communication systems, the antenna spacing is generally no less than half a wavelength. It helps to reduce the mutual coupling and therefore facilitate the system design. The maximum array gain equals the number of antennas in this settings. However, when the antenna spacing is made very small, the array gain of a compact array can be proportional to the square of the number of antennas - a value much larger than the traditional array. To achieve this so-called ``superdirectivity" however, the calculation of the excitation coefficients (beamforming vector) is known to be a challenging problem. In this paper, we address this problem with a novel double coupling-based superdirective beamforming method. In particular, we categorize the antenna coupling effects to impedance coupling and field coupling. By characterizing these two coupling in model, we derive the beamforming vector for superdirective arrays. In order to obtain the field coupling matrix, we propose a spherical wave expansion approach, which is effective in both simulations and realistic scenarios. Moreover, a prototype of the independently controlled superdirective antenna array is developed. Full-wave electromagnetic simulations and real-world experiments validate the effectiveness of our proposed approaches, and superdirectivity is achieved in reality by a compact array with 4 and 5 dipole antennas.Comment: arXiv admin note: text overlap with arXiv:2204.1154

Interior sound quality evaluation model of heavy commercial vehicles

Based on back-propagation (BP) artificial neural network (ANN) technique, interior sound quality evaluation model of heavy commercial vehicles(HCV) was designed in this paper. According to the standard named GB/T18697-2002, firstly, the interior noises of five different types of HCV under different working conditions were measured and collected. Secondly, the subjective evaluation of sound quality was estimated by jury tests following the magnitude estimation. Meanwhile, seven objective psycho-acoustical parameters of these samples were calculated. Using the objective and subjective evaluation results, furthermore, the sound quality prediction model of HCV was developed based on BP ANN. Thirdly, this model was proved by some verification tests. The results suggest that the proposed model has ability of high precision and good generalization. And lastly, the sound quality prediction model of HCV could be used to determine the impact weight of measuring objective evaluation parameters contributing to the results of subjective evaluation. The results played a significant guiding role in both HCV and other areas for sound quality evaluation and analysis

Chemical composition and anti-cholesterol activity of tea (Camellia sinensis) flowers from albino cultivars

Albino tea cultivars are mutant tea plants with altered metabolisms. Current studies focus on the leaves while little is known about the flowers. To evaluate tea flowers from different albino cultivars, the chemical composition and anti-cholesterol activity of tea flowers from three albino cultivars (i.e., Baiye No.1, Huangjinya, and Yujinxiang) were compared. According to the results, tea flowers from Yujinxiang had more amino acids but less polyphenols than tea flowers from the other two albino cultivars. A reduced content of procyanidins and a high chakasaponins/floratheasaponins ratio were characteristics of tea flowers from Yujinxiang. In vitro anti-cholesterol activity assays revealed that tea flowers from Yujinxiang exhibited stronger activity in decreasing the micellar cholesterol solubility, but not in cholesterol esterase inhibition and bile salt binding. It was noteworthy that there were no specific differences on the chemical composition and anti-cholesterol activity between tea flowers from albino cultivars and from Jiukeng (a non-albino cultivar). These results increase our knowledges on tea flowers from different albino cultivars and help food manufacturers in the cultivar selection of tea flowers for use

Interior sound quality evaluation model of heavy commercial vehicles

Based on back-propagation (BP) artificial neural network (ANN) technique, interior sound quality evaluation model of heavy commercial vehicles(HCV) was designed in this paper. According to the standard named GB/T18697-2002, firstly, the interior noises of five different types of HCV under different working conditions were measured and collected. Secondly, the subjective evaluation of sound quality was estimated by jury tests following the magnitude estimation. Meanwhile, seven objective psycho-acoustical parameters of these samples were calculated. Using the objective and subjective evaluation results, furthermore, the sound quality prediction model of HCV was developed based on BP ANN. Thirdly, this model was proved by some verification tests. The results suggest that the proposed model has ability of high precision and good generalization. And lastly, the sound quality prediction model of HCV could be used to determine the impact weight of measuring objective evaluation parameters contributing to the results of subjective evaluation. The results played a significant guiding role in both HCV and other areas for sound quality evaluation and analysis

Interior sound quality evaluation model of heavy commercial vehicles

Based on back-propagation (BP) artificial neural network (ANN) technique, interior sound quality evaluation model of heavy commercial vehicles(HCV) was designed in this paper. According to the standard named GB/T18697-2002, firstly, the interior noises of five different types of HCV under different working conditions were measured and collected. Secondly, the subjective evaluation of sound quality was estimated by jury tests following the magnitude estimation. Meanwhile, seven objective psycho-acoustical parameters of these samples were calculated. Using the objective and subjective evaluation results, furthermore, the sound quality prediction model of HCV was developed based on BP ANN. Thirdly, this model was proved by some verification tests. The results suggest that the proposed model has ability of high precision and good generalization. And lastly, the sound quality prediction model of HCV could be used to determine the impact weight of measuring objective evaluation parameters contributing to the results of subjective evaluation. The results played a significant guiding role in both HCV and other areas for sound quality evaluation and analysis