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A combined experimental and analytical method to determine the EHL friction force distribution between rollers and outer raceway in a cylindrical roller bearing

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Friction 2023年第8期11卷 1455-1469页

作者： Yu HOU Xi WANG Di YANG Zeliang XIAO School of Mechanical Electronic and Control EngineeringBeijing Jiaotong UniversityBeijing 100044China Hunan Provincial Key Laboratory of Intelligent Manufacturing Technology for High-performance Mechanical Equipment Changsha University of Science and TechnologyChangsha 410114China

Friction force is a crucial factor causing power loss and fatigue spalling of rolling element bearings.A combined experimental and analytical method is proposed to quantitatively determine the elastohydrodynamic lubrication(EHL)friction force distribution between rollers and outer raceway in a cylindrical roller bearing(CRB).An experimental system with the instrumented bearing and housing was developed for measuring radial load distribution and friction torque of bearings.A simplified model of friction force expressed by dimensionless speed,load,and material parameters was *** inequality constrained optimization problem was established and solved by using an experimental data-driven learning algorithm for determining the uncertain parameters in the *** effect of speed,load,and lubricant property on friction force and friction coefficient was discussed.

关键词： cylindrical roller bearing(CRB) elastohydrodynamic lubrication(EHL) friction force distribution friction torque combined method

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Physics-informed neural networks with residual/gradient-based adaptive sampling methods for solving partial differential equations with sharp solutions

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Applied Mathematics and Mechanics(English Edition) 2023年第7期44卷 1069-1084页

作者： Zhiping MAO Xuhui MENG School of Mathematical Sciences Fujian Provincial Key Laboratory of Mathematical Modeling and High-Performance Scientific ComputingXiamen UniversityXiamen 361005Fujian ProvinceChina Institute of Interdisciplinary Research for Mathematics and Applied Science School of Mathematics and StatisticsHuazhong University of Science and TechnologyWuhan 430074China

We consider solving the forward and inverse partial differential equations(PDEs)which have sharp solutions with physics-informed neural networks(PINNs)in this *** particular,to better capture the sharpness of the solution,we propose the adaptive sampling methods(ASMs)based on the residual and the gradient of the *** first present a residual only-based ASM denoted by ASMⅠ.In this approach,we first train the neural network using a small number of residual points and divide the computational domain into a certain number of sub-domains,then we add new residual points in the sub-domain which has the largest mean absolute value of the residual,and those points which have the largest absolute values of the residual in this sub-domain as new residual *** further develop a second type of ASM(denoted by ASMⅡ)based on both the residual and the gradient of the solution due to the fact that only the residual may not be able to efficiently capture the sharpness of the *** procedure of ASMⅡis almost the same as that of ASMⅠ,and we add new residual points which have not only large residuals but also large *** demonstrate the effectiveness of the present methods,we use both ASMⅠand ASMⅡto solve a number of PDEs,including the Burger equation,the compressible Euler equation,the Poisson equation over an Lshape domain as well as the high-dimensional Poisson *** has been shown from the numerical results that the sharp solutions can be well approximated by using either ASMⅠor ASMⅡ,and both methods deliver much more accurate solutions than the original PINNs with the same number of residual ***,the ASMⅡalgorithm has better performance in terms of accuracy,efficiency,and stability compared with the ASMⅠ*** means that the gradient of the solution improves the stability and efficiency of the adaptive sampling procedure as well as the accuracy of the ***,we also employ the similar adaptive sampling technique fo

关键词： physics-informed neural network(PINN) adaptive sampling high-dimension L-shape Poisson equation accuracy

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Simulating a Chern Insulator with C=±2 on Synthetic Floquet Lattice

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Chinese Physics Letters 2024年第9期41卷 1-8页

作者： Ling-Xiao Lei Wei-Chen Wang Guang-Yao Huang Shun Hu Xi Cao Xin-Fang Zhang Ming-Tang Deng Ping-Xing Chen Institute for Quantum Science and Technology College of ScienceNational University of Defense TechnologyChangsha 410073China Institute for Quantum Information&State Key Laboratory of High Performance Computing College of Computer Science and TechnologyNational University of Defense TechnologyChangsha 410073China Greatwall Quantum Laboratory Changsha 410006China Hefei National Laboratory Hefei 230088China

The synthetic Floquet lattice,generated by multiple strong drives with mutually incommensurate frequencies,provides a powerful platform for quantum simulation of topological *** this study,we propose a 4-band tight-binding model of the Chern insulator with a Chern number C=±2 by coupling two layers of the half Bernevig–Hughes–Zhang lattice and subsequently mapping it onto the Floquet lattice to simulate its topological *** determine the Chern number of our Floquet-version model,we extend the energy pumping method proposed by Martin et al.[2017 ***.X 7041008]and the topological oscillation method introduced by Boyers et al.[2020 ***.125160505],followed by numerical simulations for both *** simulation results demonstrate the successful extraction of the Chern number using either of these methods,providing an excellent prediction of the phase diagram that closely aligns with the theoretical one derived from the original bilayer half Bernevig–Hughes–Zhang ***,we briefly discuss a potential experimental implementation for our *** work demonstrates significant potential for simulating complex topological matter using quantum computing platforms,thereby paving the way for constructing a more universal simulator for non-interacting topological quantum states and advancing our understanding of these intriguing phenomena.

关键词： properties topological quantum

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Person Re-Identification Based on Multi-Spectrum Information Aggregation Transformers 8

Person Re-Identification Based on Multi-Spectrum Information...

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8th International Conference on Image, Vision and computing, ICIVC 2023

作者： Zhang, Yuxuan Tan, Huibin Lan, Long Ren, Jing Teng, Xiao National University of Defense Technology State Key Laboratory of High Performance Computing Changsha China

ISBN: (纸本)9798350335231

Convolutional Neural Networks (CNNs) have achieved remarkable success in various image-related tasks. However, CNNs' chunking approach of sliding windows over pixels hinders its ability to learn sequential semantic information. To address this issue, researchers have proposed models that integrate Transformers to aggregate features across different resolutions, taking advantage of the Transformer's strengths. Hierarchical Aggregation Transformer (HAT) is one such model that integrates low-level and high-level details, showing a great effect on person re-identification. Based on HAT, we propose the Multi-Spectrum Information Aggregation Transformers (MIAT), which enhances the low-level structural information captured by CNNs through a frequency channel attention module that extracts multi-spectral features. By leveraging discrete cosine transform (DCT), more detailed features can be learned to improve person re-identification, enabling better discernment of distinguishing features between different individuals. Through extensive experimentation, we validate our model's performance on two widely employed person re-identification datasets and demonstrate its superiority over existing advanced methods. © 2023 IEEE.

关键词： Discrete cosine transforms

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Boosting the dimensionality of frequency entanglement using a reconfigurable microring resonator

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Science China(Physics,Mechanics & Astronomy) 2023年第5期66卷 79-88页

作者： Chao Wu Qilin Zheng Yingwen Liu Yang Wang Jiangfang Ding Pingyu Zhu Shichuan Xue Miaomiao Yu Weihong Luo Kaikai Zhang Anqi Huang Mingtang Deng Junjie Wu Ping Xu Institute for Quantum Information State Key Laboratory of High Performance ComputingCollege of Computer Science and TechnologyNational University of Defense TechnologyChangsha 410073China National Laboratory of Solid State Microstructures School of PhysicsNanjing UniversityNanjing 210093China

Integrated quantum frequency combs(QFCs)based on microring resonators supplies as an essential resource for expanding the Hilbert-space dimensionality for high-dimensional quantum computing and information *** this work,we propose and demonstrate a reconfigurable ring resonator with tunable quality factors to efficiently increase the dimensionality of frequency entanglement,simultaneously,ensuring a high on-chip pair generation rate(PGR)and coincidence-to-accidental ratio(CAR).Our method exploits the asymmetric Mach-Zehnder interferometer instead of the traditional straight waveguide as the coupler of resonators which offer a tunable external coupling coefficient to modulate the quality factor to enlarge the QFCs’bandwidth and thus increase the dimensionality of frequency *** measured the QFCs’joint spectral intensity of 28 frequency pairs under various quality factors ranging from 16.6×10^(4) to 3.4×10^(4).Meanwhile,the measured Schmidt number increased from 11.01 to 24.77,denoting a huge expansion of the Hilbert-space dimensionality from 121 to a record number of 613 dimensions,which agrees well with our theoretical *** addition,the PGR and CAR-another two key parameters for high-quality QFCs-were all measured under different quality factors to verify that our method can significantly increase the Schmidt number and CAR while maintaining a high *** fact,bright QFCs with a total PGR of 4.3 MHz under a 0.48 mW pump power and a mean CAR of 1578 were simultaneously obtained at the highest Schmidt *** method is widely applicable to other material-based ring resonators and can act as a general solution for high-dimensional QFCs.

关键词： reconfigurable resonator quantum frequency comb Hilbert-space dimensionality

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Effect of long-period ordered stacking on twinning behavior and mechanical properties of Mg-Al-Y alloy during uniaxial hot compression

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Journal of Materials Science & technology 2023年第11期142卷 152-166页

作者： Shuai Yuan Jinhui Wang Lei Zhang Shiyu Luan Peipeng Jin Qinghai Provincial Key Laboratory of New Light Alloys Qinghai Provincial Engineering Research Center of High Performance Light Metal Alloys and FormingQinghai UniversityXining 810016China School of Material Science and Engineering Shenyang University of TechnologyShenyang 110870China

Two alloys with(T4-4h)and without(T4-8h)long-period stacking ordered(LPSO)phase were obtained by solution treatment of as-cast Mg-1Al-12Y alloy at 540℃ for 4 h and 8 h,*** compressive tests(300-450℃,ε=0.01s^(-1))showed that the strengthening effect of LPSO in T4-4h alloy gradually disappeared with temperature *** addition,the corresponding compression deformation behavior of the two alloys was also investigated by electron backscatter diffraction(EBSD).It was found that the twinning of the two alloys was dominated by{1012}extension twins,and the large amount of lamellar LPSO in T4-4 h alloy inhibited the activation and growth of ***[0001]//compression direction(CD)texture formed after deformation is mostly attributed to the activation and growth of extension *** analyzing the activated twin variants,it was found that the activation of twin variants mainly depended on Schmid factor(SF).For twin variants with smaller SF,they may be activated due to local stress *** on the analysis results of in-grain misorientation axis(IGMA)and SF,the deformation mechanism of the alloys at elevated temperature is dominated by basal slip and non-basal *** stronger mechanical properties of T4-4h alloy than those of T4-8h are attributed to the obstruction of non-basal slip movement by LPSO.

关键词： LPSO strengthening Hot deformation Twinning behavior

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Dimension by Dimension Finite Volume HWENO Method for Hyperbolic Conservation Laws

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Communications on Applied Mathematics and Computation 2024年第1期6卷 605-624页

作者： Feng Zheng Jianxian Qiu College of Mathematics and Statistics Fujian Normal UniversityFuzhou350117FujianChina School of Mathematical Sciences and Fujian Provincial Key Laboratory of Mathematical Modeling&High-Performance Scientific Computing Xiamen UniversityXiamen361005FujianChina

In this paper,we propose a finite volume Hermite weighted essentially non-oscillatory(HWENO)method based on the dimension by dimension framework to solve hyperbolic conservation *** can maintain the high accuracy in the smooth region and obtain the high resolution solution when the discontinuity appears,and it is compact which will be good for giving the numerical boundary ***,it avoids complicated least square procedure when we implement the genuine two dimensional(2D)finite volume HWENO reconstruction,and it can be regarded as a generalization of the one dimensional(1D)HWENO *** numerical tests are performed to verify the high resolution and high accuracy of the scheme.

关键词： Finite volume Dimension by dimension HWENO Hyperbolic conservation laws

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DDIRNet:robust radar emitter recognition via single domain generalization

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Journal of Systems Engineering and Electronics 2025年第2期36卷 397-404页

作者： WU Honglin LI Xueqiong HUANG Junjie JIN Ruochun TANG Yuhua Institute for Quantum Information&State Key Laboratory of High Performance Computing National University of Defense TechnologyChangsha 410073China

Automatically recognizing radar emitters from com-plex electromagnetic environments is important but ***,the changing electromagnetic environment results in inconsistent signal distribution in the real world,which makes the existing approaches perform poorly for recognition tasks in different *** this paper,we propose a domain generaliza-tion framework is proposed to improve the adaptability of radar emitter signal recognition in changing ***,we propose an end-to-end denoising based domain-invariant radar emitter recognition network(DDIRNet)consisting of a denoising model and a domain invariant representation learning model(IRLM),which mutually benefit from each *** the signal denoising model,a loss function is proposed to match the feature of the radar signals and guarantee the effectiveness of the *** the domain invariant representation learning model,contrastive learning is introduced to learn the cross-domain feature by aligning the source and unseen domain ***,we design a data augmentation method that improves the diversity of signal data for *** experiments on classification have shown that DDIRNet achieves up to 6.4%improvement compared with the state-of-the-art radar emitter recognition *** proposed method pro-vides a promising direction to solve the radar emitter signal recognition problem.

关键词： radar emitter recognition domain generalization denoising contrastive learning data augmentation.

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A high ORDER SCHEME FOR FRACTIONAL DIFFERENTIAL EQUATIONS WITH THE CAPUTO-HADAMARD DERIVATIVE

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Journal of Computational Mathematics 2025年第3期43卷 615-640页

作者： Xingyang Ye Junying Cao Chuanju Xu School of Science Jimei UniversityXiamen 361021China School of Data Science and Information Engineering Guizhou Minzu UniversityGuiyang 550025China School of Mathematical Sciences and Fujian Provincial Key Laboratory of Mathematical Modeling and High Performance Scientific Computing Xiamen UniversityXiamen 361005China

In this paper,we consider numerical solutions of the fractional diffusion equation with theαorder time fractional derivative defined in the Caputo-Hadamard sense.A high order time-stepping scheme is constructed,analyzed,and numerically *** contribution of the paper is twofold:1)regularity of the solution to the underlying equation is investigated,2)a rigorous stability and convergence analysis for the proposed scheme is performed,which shows that the proposed scheme is 3+αorder *** numerical examples are provided to verify the theoretical statement.

关键词： Caputo-Hadamard derivative Fractional differential equations high order scheme Stability and convergence analysis

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Adaptive Occlusion Face Recognition Feature Fusion Network Based on Precise Guidance Mask Extraction

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Journal of Shanghai Jiaotong University (Science) 2025年 1-12页

作者： Ye, Jihua Zhang, Lei Wang, Chao Tu, Qixuan Zheng, Rehua Huang, Huiyuan Jiang, Aiwen School of Computer and Information Engineering Jiangxi Normal University Nanchang330022 China Jiangxi Provincial Key Laboratory for High Performance Computing Jiangxi Normal University Nanchang330022 China State International Science & Technology Cooperation Base of Networked Supporting Software Jiangxi Normal University Nanchang330022 China

The uncertainty in the position and size of occluding objects greatly affects the extraction of identity features in facial recognition, which is a challenge that existing methods fail to effectively address. To tackle this issue, this paper introduces a novel feature fusion network for occluded facial recognition that adaptively handles arbitrary occlusions and accurately extracts occlusion information masks. The network effectively mitigates the impact of occlusions on facial identity features through a feature fusion module. The proposed method employs an occlusion classification module and an occlusion classification loss to precisely guide the extraction of accurate occlusion masks. Subsequently, an occlusion-aware hybrid attention module is introduced, which focuses on the relationship between facial features and occlusion masks across channel and spatial dimensions. This fusion strategy enables the extraction of facial identity features that are resilient to occlusions. Experimental results indicate that the proposed method holds a significant advantage in handling facial recognition tasks with arbitrary occlusions. On the LFW and MF1 synthetic occlusion datasets, the average accuracy rates reached 93.19% and 72.57%, respectively, showing improvements of 1.7 and 2.39 percent points over mainstream methods. © Shanghai Jiao Tong University 2025.

关键词： A feature fusion occluded facial recognition occlusion mask occlusion perception TP391.41

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