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NUMERICAL STUDY OF CAVITATION ON THE SURFACE OF THE GUIDE VANE IN THREE GORGES HYDROPOWER UNIT

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Journal of Hydrodynamics 2010年第5期22卷 703-708页

作者： PENG Yu-cheng CHEN Xi-yang CAO yan HOU Guo-xiang School of energy and Power Engineering Huazhong University of Science and Technology Wuhan 430074 China College of Electronic information Engineering Wuhan Polytechnic Wuhan 430074 China School of Traffic science and Engineering Huazhong University of Science and Technology Wuhan 430074 China

Large-area erosions such as rust and obvious cavitation were found on the surface of the guide vane in Three Gorges hydropower units. A numerical explanation of the cavitation is given in this article. At first, based on the characteristic performance curves of the prototype hydro-turbine supplied by ALSTOM together with the actual operating conditions, an operating point is chosen for numerical analysis using the Reynolds-Averaged Navier-Stokes （RANS） equations. The flow passages from the inlet of the spiral case to the outlet of the draft tube are included in the computational domain. The results show that the static pressure on the guide vane surface is much higher than the critical pressure of cavitation. Secondly, a tiny protrusion on the guide vane surface is considered and the problem is simplified to a 2.D problem to study the local detailed flow near the guide vane surface. The protrusion is 0.5 mm in height and is 5.0 mm in width. On the basis of the results of RANS simulations, the 2.D problem is studied using the Large Eddy Simulation （LES）. It is shown that there exists a region in which the static pressure reaches a level below the vapor pressure of the water. Thirdly, a cavitation model is included for the 0.5 mm protrusion case and another tiny pit case, with a tiny pit 0.3 mm in depth and 1.0 mm in width. The results show that vapor bubble exists at the protrusion entrance and the pit exit as the low pressure regions.

关键词： cavitation guide vane numerical analysis

A Multi-objective Optimization based on Hybrid Quantum Evolutionary Algorithm in Networked Control System

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A Multi-objective Optimization based on Hybrid Quantum Evolu...

2.10 2.d International Conference on Multimedia and computational Intelligence (ICMCI 2.10)

作者： QU Zheng-geng 1 2.1.College of information science and {2. Northwest university Xi’an china ZHANG Xiao-yan 1 2.2.Deptment of Computer science Shangluo university Shangluo china

This paper proposed a new hybrid quantum clone evolutionary algorithm(HQCEA)in a two-layer networked learning control system(NLCS)*** special architecture achieves better control perform

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一类S-mKdV方程族及其扩展可积模型

物理学报 2003年第1期52卷 5-11页

作者：张玉峰闫庆友张鸿庆山东科技大学信息学院大连理工大学机械学院大连116024 大连大学先进设计技术中心大连116622

由loop代数 A1 的一个子代数出发 ,构造了一个线性等谱问题 ,再利用屠格式计算出了一类Liouvelle意义下的可积系统及其双Hamilton结构 ,作为该可积系统的约化 ,得到了著名的Schr dinger方程和mKdV方程 ,因此称该系统为S mKdV方程族 .... 详细信息

由loop代数 A1 的一个子代数出发 ,构造了一个线性等谱问题 ,再利用屠格式计算出了一类Liouvelle意义下的可积系统及其双Hamilton结构 ,作为该可积系统的约化 ,得到了著名的Schr dinger方程和mKdV方程 ,因此称该系统为S mKdV方程族 .根据已构造的 A1 的子代数 ,又构造了维数为 5的loop代数 A2.的一个新的子代数 G ,由此出发设计了一个线性等谱形式 ,再利用屠格式求得了S mKdV方程族的一类扩展可积模型 .利用这种方法还可以求BPT方程族、TB方程族等谱系的扩展可积模型 .因此本方法具有普遍应用价值 .最后作为特例 ,求得了著名的Schr dinger方程和mKdV方程的可积耦合系统 .

关键词： loop代数 Hamilton结构扩展可积模型 Schroedinger方程 mKdV方程线性等谱可积耦合系统

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一类NLS-mKdV方程族的扩展可积系统

物理学报 2003年第9期52卷 2109-2113页

作者：张玉峰闫庆友山东科技大学信息学院数学研究所山东财政学院经济统计系济南250014

利用代数变换 ,构造了与文献 [5 ]中的loop代数 A2.的子代数等价的loop代数 A1 的一个子代数 A1 .再将 A1 扩展为一个高维的loop代数 G .利用 G设计了一个等谱问题 ,结合子代数间的直和运算和同构关系 ,得到了NLS_mK dV方程族的... 详细信息

利用代数变换 ,构造了与文献 [5 ]中的loop代数 A2.的子代数等价的loop代数 A1 的一个子代数 A1 .再将 A1 扩展为一个高维的loop代数 G .利用 G设计了一个等谱问题 ,结合子代数间的直和运算和同构关系 ,得到了NLS_mK dV方程族的一类扩展可积系统 .作为约化情形 ,求得了著名的Schr

关键词： NLS-mKdV方程族扩展可积系统代数变换 loop代数等谱问题可积耦合系统孤立子

Size effect of the elastic modulus of rectangular nanobeams:Surface elasticity effect

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Chinese Physics B 2013年第10期22卷 424-428页

作者：姚海燕云国宏范文亮 College of Ordos Inner Mongolia University Inner Mongolia Key Laboratory of Nanoscience and Nanotechnology College of Physical science and technology Inner Mongolia University College of Physics and Electronic information Inner Mongolia Normal University

The size-dependent elastic property of rectangular nanobeams （nanowires or nanoplates） induced by the surface elas- ticity effect is investigated by using a developed modified core-shell model. The effect of surface elasticity on the elastic modulus of nanobeams can be characterized by two surface related parameters, i.e., inhomogeneous degree constant and surface layer thickness. The analytical results show that the elastic modulus of the rectangular nanobeam exhibits a distinct size effect when its characteristic size reduces below 1 O0 nm. It is also found that the theoretical results calculated by a mod- ified core-shell model have more obvious advantages than those by other models （core-shell model and core-surface model） by comparing them with relevant experimental measurements and computational results, especially when the dimensions of nanostructures reduce to a few tens of nanometers.

关键词： size effects elastic modulus nanobeams surface elasticity

Effect of Vacancy Defects on the Properties of CoS_(2. and FeS_(2.

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Journal of Wuhan university of technology(Materials {2.) 2024年第3期39卷 627-638页

作者：冯中营 ZHANG Jianmin WANG Xiaowei yanG Wenjin JING Yinlan yanG yan Department of science Taiyuan Institute of TechnologyTaiyuan 030008China computational Physics Research Center Taiyuan In-stitute of TechnologyTaiyuan 030008China College of Physics and information technology Shaanxi Normal UniversityXi’an 710119China Collaborative Innovation Center of Extreme Optics Shanxi UniversityTaiyuan 030006China Department of Physics College of ScienceNorth University of ChinaTaiyuan 030051China

In order to explore the effect of vacancy defects on the structural,electronic,magnetic and optical properties of CoS_(2. and FeS_(2.,first-principles calculation method was used to investigate the *** calculated results of materials without vacancy are consistent with those reported in the literatures,while the results of materials with vacancy defect were different from those of literatures due to the difference vacancy *** Co vacancy defect hardly changes the half-metallic characteristic of CoS_(2..The Fe vacancy defect changes FeS_(2. from semiconductor to half-metal,and the bottom of the spin-down conduction band changes from the p orbital state of S to the d(t_(2.))orbital state of Fe,while the top of the valence band remains the d orbital d(eg)state of *** half-metallic Co vacancy defects of CoS_(2. and Fe vacancy defects of FeS_(2. are expected to be used in spintronic devices.S vacancy defects make both CoS_(2. and FeS_(2. *** the Co and S vacancy defects lead to the decrease of the magnetic moment of CoS_(2.,while both the Fe and S vacancy defects lead to the obvious magnetic property of FeS_(2..Vacancy defects enhance the absorption coefficient of infrared band and long band of visible light obviously,and produce obvious red shift phenomenon,which is expected to be used in photoelectric devices.

关键词： cobalt disulfide iron disulfide vacancy defect fist principles

Bioinspired sensing-memory-computing integrated vision systems: biomimetic mechanisms, design principles, and applications

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science china({2. sciences) 2024年第5期67卷 5-27页

作者： Yujie HUANG Yinlong TAN yan KANG Yabo CHEN Yuhua TANG Tian JIANG Institute for Quantum information and State Key Laboratory of High Performance Computing College of Computer National University of Defense Technology College of Advanced Interdisciplinary Studies National University of Defense Technology Institute for Quantum science and technology College of ScienceNational University of Defense Technology

With the explosion of sensory data in the Internet of Things(Io T) era, conventional machine vision systems are becoming increasingly difficult to meet the requirements of high efficiency, low energy consumption, and low latency due to their inherent shortcomings of separate sensing, memory, and computing units. Inspired by the retina and neuromorphic computing, the sensing-memory-computing integrated vision system(SMCVS) that features low power consumption, low latency, and high parallelism has been considered a promising technology to surpass the von Neumann architecture and realize strong artificial ***, novel materials like two-dimensional semiconductors and quantum dots with novel optoelectronic performance provide hardware carriers for implementing integrated sensing-memory-computing architectures,attracting considerable attention. This paper reviews the recent research progress in bioinspired vision systems in terms of biomimetic mechanisms, design principles, computational architectures, and ***, the biomimetic mechanisms are illustrated to guide the design of high-performance artificial visual perception systems. Then the research progress of optoelectronic-synapse-based bioinspired vision systems in the device principles and applications including image filtering, color recognition, visual adaptation, and motion detection are summarized. Finally, the challenges and future developing directions of the SMCVS are provided regarding bionic application, architecture design, and device fabrication.

关键词： sensing-memory-computing architecture neuromorphic computing retinomorphic device image recognition visual system

DiffMat:Latent diffusion models for image-guided material generation

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Visual Informatics 2024年第1期8卷 6-14页

作者： Liang Yuan Dingkun yan Suguru Saito Issei Fujishiro Graduate School of science and technology Keio UniversityKanagawaJapan School of Computing Tokyo Institute of TechnologyTokyoJapan Department of information and Computer science Keio UniversityKanagawaJapan

Creating realistic materials is essential in the construction of immersive virtual *** existing techniques for material capture and conditional generation rely on flash-lit photos,they often produce artifacts when the illumination mismatches the training *** this study,we introduce DiffMat,a novel diffusion model that integrates the CLIP image encoder and a multi-layer,crossattention denoising backbone to generate latent materials from images under various *** a pre-trained StyleGAN-based material generator,our method converts these latent materials into high-resolution SVBRDF textures,a process that enables a seamless fit into the standard physically based rendering pipeline,reducing the requirements for vast computational resources and expansive *** surpasses existing generative methods in terms of material quality and variety,and shows adaptability to a broader spectrum of lighting conditions in reference images.

关键词： SVBRDF Diffusion model Generative model Appearance modeling

A computational model to identify fertility-related proteins using sequence information

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Frontiers of Computer science 2024年第1期18卷 229-237页

作者： yan LIN Jiashu WANG Xiaowei LIU Xueqin XIE De WU Junjie ZHANG Hui DING Key Laboratory for Animal Disease-Resistance Nutrition of the Ministry of Agriculture Animal Nutrition InstituteSichuan Agricultural UniversityChengdu 611130China School of Life science and technology and Center for {2.al Biology University of Electronic Science and Technology of ChinaChengdu 610054China

Fertility is the most crucial step in the development process,which is controlled by many fertility-related proteins,including spermatogenesis-,oogenesis-and embryogenesis-related *** identification of fertility-related proteins can provide important clues for studying the role of these proteins in ***,in this study,we constructed a two-layer classifier to identify fertility-related *** this classifier,we first used the composition of amino acids(AA)and their physical and chemical properties to code these three fertility-related ***,the feature set is optimized by analysis of variance(ANOVA)and incremental feature selection(IFS)to obtain the optimal feature *** five-fold cross-validation(CV)and independent data tests,the performance of models constructed by different machine learning(ML)methods is evaluated and ***,based on support vector machine(SVM),we obtained a two-layer model to classify three fertility-related *** the independent test data set,the accuracy(ACC)and the area under the receiver operating characteristic curve(AUC)of the first layer classifier are 81.95%and 0.89,respectively,and them of the second layer classifier are 84.74%and 0.90,*** results show that the proposed model has stable performance and satisfactory prediction accuracy,and can become a powerful model to identify more fertility related proteins.

关键词： sfertility-related proteins machine1 learning sequence information feature selection