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总压和对涡旋流组合畸变发生器流场S-PIV测试

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航空动力学报 2021年第4期36卷 874-884页

作者：陈峰宗有海马护生时培杰李学臣中国空气动力研究与发展中心高超声速冲压发动机技术重点实验室四川绵阳621000

为研究组合畸变对推进系统性能和稳定性的影响,设计了一种总压和对涡旋流组合畸变发生器。该组合畸变发生器利用畸变网生成总压畸变,利用攻角平板产生对涡旋流畸变,并可通过前后畸变网作用进一步增强对涡旋流强度。利用立体粒子图像测速... 详细信息

为研究组合畸变对推进系统性能和稳定性的影响,设计了一种总压和对涡旋流组合畸变发生器。该组合畸变发生器利用畸变网生成总压畸变,利用攻角平板产生对涡旋流畸变,并可通过前后畸变网作用进一步增强对涡旋流强度。利用立体粒子图像测速(S-PIV)技术对3种畸变发生器构型的流场特征和畸变指标进行了测试分析,获取了测试截面流场高空间分辨率的时均值和脉动值特征。结果表明:畸变发生器可产生与S弯进气道出口相似的组合畸变形态;在马赫数为0.2,平板攻角为10°条件下,由攻角平板和前后畸变网共同作用产生的最大旋流角为23°;平板攻角减小时,对涡旋流强度降低,旋流稳定性和对称性降低;进气速度对旋流角的时均值和脉动量的影响较小。在畸变指标方面,提出表示最大和最小旋流角的旋流幅度指标以及周向角度位置指标,以弥补国际自动机工程师学会(SAE)旋流评估方法对小范围强旋流状态评估的不足。

关键词：总压畸变对涡旋流组合畸变翼尖涡立体粒子图像测速(S-PIV)

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亚声速压气机平面叶栅雷诺数影响试验

航空动力学报 2022年第5期37卷 1020-1029页

作者：魏巍任思源马护生李学臣宗有海中国空气动力研究与发展中心空天技术研究所四川绵阳621000

采用降低试验压力减小试验叶栅弦长雷诺数的方法,研究了UKG030.3压气机叶型叶片表面和尾迹区域气流随雷诺数、马赫数及攻角变化的流动特性,获得了表面等熵马赫数、总压损失系数等参数随雷诺数的变化规律。试验结果表明:弦长雷诺数减小... 详细信息

采用降低试验压力减小试验叶栅弦长雷诺数的方法,研究了UKG030.3压气机叶型叶片表面和尾迹区域气流随雷诺数、马赫数及攻角变化的流动特性,获得了表面等熵马赫数、总压损失系数等参数随雷诺数的变化规律。试验结果表明:弦长雷诺数减小到一定程度时,叶片吸力面峰值马赫数位置之后会逐渐呈现流动分离气泡产生、分离气泡扩大至分离气泡破碎的过程;长分离气泡出现以后尾迹宽度和叶型总压损失突然急剧增大,但损失突增所对应的临界雷诺数并不一致;叶型总压损失和弦长雷诺数经地面状态参数比值处理以后可以发现,总压损失比突增位置处于0.4倍弦长雷诺数比附近。

关键词：压气机平面叶栅雷诺数分离气泡总压损失

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渐扩后倾肩臂孔平板气膜冷却特性实验研究

实验流体力学 2018年第4期32卷 47-52,71页

作者：黄康王红彪黄辉马护生宗有海中国空气动力研究与发展中心高速空气动力研究所四川绵阳621000

提出一种新型气膜冷却孔型——渐扩后倾肩臂孔,运用压力敏感漆(PSP)实验技术,研究其与圆孔、肩臂孔的气膜冷却性能差异,并采用N2和CO2气体作为冷却气,对比分析了密度比1.0和1.5情况下吹风比(Br=0.5～2.0)对渐扩后倾肩臂孔平板气膜冷却... 详细信息

提出一种新型气膜冷却孔型——渐扩后倾肩臂孔,运用压力敏感漆(PSP)实验技术,研究其与圆孔、肩臂孔的气膜冷却性能差异,并采用N2和CO2气体作为冷却气,对比分析了密度比1.0和1.5情况下吹风比(Br=0.5～2.0)对渐扩后倾肩臂孔平板气膜冷却性能的影响。结果表明:在相同密度比、吹风比条件下,渐扩后倾肩臂孔方案冷却效率优于圆孔和肩臂孔(肩臂孔略高于圆孔)。在密度比为1.0的情况下,当测量点离孔的距离与孔入口直径的比值x/D15时,冷却效率在Br=1.0时最大。在密度比为1.5的情况下,渐扩后倾肩臂孔方案的展向平均气膜冷却效率随着吹风比的增大呈先增大后减小的趋势,在Br=1.0时冷却效率最大。分析认为:不同密度比情况下,吹风比对渐扩后倾肩臂孔冷却性能的影响差异,主要是由于密度比较小时,冷却气出口速度更大,使冷却气更易吹离冷却壁面。

关键词：航空涡轮发动机气膜冷却渐扩后倾肩臂孔孔型压力敏感漆

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基于探针管路动态修正的压气机动态总压测试

实验流体力学 2018年第5期32卷 82-88页

作者：陈峰宗有海刘东健马护生杜炜中国空气动力研究与发展中心高速空气动力研究所四川绵阳621000 中国空气动力研究与发展中心计算空气动力研究所四川绵阳621000

为方便安全地获取压气机内部多点动态总压信号,采用气动探针将测点压力引出,并通过动态修正还原测点处的压力信号。利用爆破气球装置产生的向下阶跃输入信号和探针响应输出信号,辨识得到探针管路的离散传递函数模型,以此来修正测量信号... 详细信息

为方便安全地获取压气机内部多点动态总压信号,采用气动探针将测点压力引出,并通过动态修正还原测点处的压力信号。利用爆破气球装置产生的向下阶跃输入信号和探针响应输出信号,辨识得到探针管路的离散传递函数模型,以此来修正测量信号,获得测点真实压力。所用标定方法能够实现1000Hz以内信号的动态修正,探针信号经过修正后能够消除相位延迟,且管路谐振效应对信号的放大作用显著减小。压气机动态总压测试结果表明:随着进气流量的减小,转子进口叶片通过频率信号幅值逐渐增大,静子出口宽频扰动增强,在近失速点宽频扰动最大;压气机突尖型旋转失速先兆首先出现在转子叶片前缘叶顶附近,而后向叶根方向迅速扩展,并形成全叶高范围的旋转失速团,完全发展的失速团传播速度约为30%转子转速。

关键词：压气机气动探针传递函数动态修正旋转失速突尖

Smart Gas Sensors:Recent Developments and Future Prospective

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Nano-Micro Letters 2025年第3期17卷 55-86页

作者： Boyang zong Shufang Wu Yuehong Yang Qiuju Li Tian Tao Shun Mao College of Environmental Science and Engineering Biomedical Multidisciplinary Innovation Research InstituteShanghai East HospitalState Key Laboratory of Pollution Control and Resource ReuseTongji University1239 Siping RoadShanghai 200092People’s Republic of China Shanghai Institute of Pollution Control and Ecological Security Shanghai 200092People’s Republic of China Microbiome Medicine Center Department of Laboratory MedicineZhujiang HospitalSouthern Medical UniversityGuangzhou 510280People’s Republic of China

Gas sensor is an indispensable part of modern society withwide applications in environmental monitoring,healthcare,food industry,public safety,*** the development of sensor technology,wireless communication,smart monitoring terminal,cloud storage/computing technology,and artificial intelligence,smart gas sensors represent the future of gassensing due to their merits of real-time multifunctional monitoring,earlywarning function,and intelligent and automated *** electronicand optoelectronic gas sensors have been developed for high-performancesmart gas *** the development of smart terminals and the maturityof integrated technology,flexible and wearable gas sensors play an increasingrole in gas *** review highlights recent advances of smart gassensors in diverse *** structural components and fundamentalprinciples of electronic and optoelectronic gas sensors are described,andflexible and wearable gas sensor devices are ***,sensorarray with artificial intelligence algorithms and smart gas sensors in“Internet of Things”paradigm are ***,the challengesand perspectives of smart gas sensors are discussed regarding the future need of gas sensors for smart city and healthy living.

关键词： Smart gas sensor Electronic sensor Optoelectronic sensor Flexible and wearable sensor Artificial intelligence

First observation results of Macao Science Satellite-1 on lightning-induced electron precipitation

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Science China Earth Sciences 2025年第1期68卷 1-10页

作者： Yongping WANG Yixin SUN Qiugang zong Gaopeng LU Xudong GU Ze-Jun HU Bin LI Key Laboratory for Polar Science Ministry of Natural Resources Polar Research Institute of China Institute of Space Physics and Applied Technology Peking University State Key Laboratory of Lunar and Planetary Science Macau University of Science and Technology School of Earth and Space Sciences University of Science and Technology of China School of Electronic Information Wuhan University

The Medium-energy Electron Spectrometers(MES) is a space-borne instrument onboard Macao Science Satellite-1(MSS-1) dedicated to monitoring the typical charged particle radiation characteristics in the satellite orbit and the process of their occurrence and development, including short bursts of lightning-induced electron precipitation(LEP).This paper presents the first results of the LEP measurements by the MSS-1.47 LEP events are identified with the routine operation for 3 months since satellite launch, all within the range of 1.5

关键词： Lightning-induced electron precipitation Inner radiation belts Energetic electrons Macao Science Satellite-1

Simulations of electron zebra stripes in the inner radiation belt using a composite empirical electric field model

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Science China Earth Sciences 2025年第1期68卷 27-38页

作者： Ziyang WANG Ying LIU Qiugang zong Hong ZOU Yuguang YE Xuzhi ZHOU Chao YUE Shan WANG Institute of Space Physics and Applied Technology Peking University State Key Laboratory of Lunar and Planetary Science Macau University of Science and Technology

The phenomenon termed “zebra stripes” manifests as regular patterns in the energy-space(L shell) spectrum of energetic electrons(ranging from tens to hundreds ke V) within the inner radiation belt. These structures exhibit drift-periodic behavior and commonly arise from large-scale electric field perturbations near the substorm onsets. In this study, we introduce a composite electric field model and replicate the formation, structure, and evolution of zebra stripes using a bounce-averaged test particle code under this electric field model. High-resolution measurements of energetic electrons obtained from the Van Allen Probes and the recently launched Macao Science Satellites-1 are used as initial conditions and served to validate our test particle simulations. Comparative analyses between observed data and simulations demonstrate our test particle method's efficacy in capturing zebra stripes' general behavior. Moreover, the composite model proves capable of reproducing realistic variations in the electric field within the inner radiation belt to a certain extent. Nevertheless, subtle differences emerge in the flux strength and the positions of stripes. These disparities primarily stem from limitations inherent in the electric field model and the initial conditions of the simulation. Acknowledging that the model represents an average case, it is conceivable that real-world scenarios may deviate from the average, thereby introducing variations in the observed phenomena.

关键词： Zebra stripes Inner radiation belt Large-scale electric fields Van Allen Probes Macao Science Satellite

Observation of acoustic hybrid topological phases induced by the p-d orbital interactions

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 132-139页

作者： Xiao Xiang Feng Gao Yu-Gui Peng Peng Wu zong-Lin Li Xue-Feng Zhu School of Physics and Innovation Institute Huazhong University of Science and Technology

In spinless systems,growing attention has recently been attracted to synthetic gauge fields,which redefine the fundamental crystal symmetries by utilizing the projective algebraic ***,synthetic gauge fields have been commonly investigated in single orbital systems,and explorations on hybrid orbitals remain elusive in ***,we report the experimental observation of hybrid topological phases induced by hybrid synthetic gauge flux,which is formed by the interaction between p and d orbitals embedded in acoustic *** breaking the translation symmetries of Lxand/or Ly,we unambiguously demonstrate the first-order M?bius edge states and higher-order corner *** work establishes a platform for seeking exotic topological phases induced by hybrid-orbitals interactions and initializing the framework of hybrid-orbitalsrelated topological *** applications can be anticipated in scenarios such as high-quality sensing and robust wave trapping due to the stepwise energy distribution of the hybrid topological phase.

关键词： topological insulator synthetic gauge field projective symmetry corner states

Application of the improved dung beetle optimizer,muti-head attention and hybrid deep learning algorithms to groundwater depth prediction in the Ningxia area,China

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Atmospheric and Oceanic Science Letters 2025年第1期18卷 18-23页

作者： Jiarui Cai Bo Sun Huijun Wang Yi Zheng Siyu Zhou Huixin Li Yanyan Huang Peishu zong Collaborative Innovation Center on forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster Ministry of Education/Joint International Research Laboratory of Climate and Environment ChangeNanjing University of Information Science and TechnologyNanjingChina Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) ZhuhaiChina China Meteorological Administration Key Laboratory of Transportation MeteorologyNanjingChina Jiangsu Meteorological Observatory NanjingChina

Due to the lack of accurate data and complex parameterization,the prediction of groundwater depth is a chal-lenge for numerical *** learning can effectively solve this issue and has been proven useful in the prediction of groundwater depth in many *** this study,two new models are applied to the prediction of groundwater depth in the Ningxia area,*** two models combine the improved dung beetle optimizer(DBO)algorithm with two deep learning models:The Multi-head Attention-Convolution Neural Network-Long Short Term Memory networks(MH-CNN-LSTM)and the Multi-head Attention-Convolution Neural Network-Gated Recurrent Unit(MH-CNN-GRU).The models with DBO show better prediction performance,with larger R(correlation coefficient),RPD(residual prediction deviation),and lower RMSE(root-mean-square error).Com-pared with the models with the original DBO,the R and RPD of models with the improved DBO increase by over 1.5%,and the RMSE decreases by over 1.8%,indicating better prediction *** addition,compared with the multiple linear regression model,a traditional statistical model,deep learning models have better prediction performance.

关键词： Groundwater depth Multi-head attention Improved dung beetle optimizer CNN-LSTM CNN-GRU Ningxia