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Experimental Study on the Characteristics of Annular Fluid Film in a Locally Deformed Narrow Rectangular Channel

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SSRN 2024年

作者： Wang, Fenze Ren, Quanyao Liu, Haidong Xiao, Yi Chen, Deqi Key Laboratory of Low-grade Energy Utilization Technologies and Systems Chongqing University Ministry of Education Chongqing400044 China Department of Nuclear Engineering and Technology School of Energy and Power Engineering Chongqing University Chongqing400044 China Science and Technology on Reactor System Design Technology Laboratory Chengdu610041 China Liangjiang International College Chongqing University of Technology Chongqing401135 China Chongqing Research Institute of HIT Chongqing401151 China School of Flight Technology Civil Aviation Flight University of China Sichuan618307 China China

The study of the characteristics of the annular flow film in the narrow rectangular channel under the localized deformation can provide a research basis for the heat and mass transfer and the hydrodynamic characteristics of the locally deformed narrow flow channel. In this study, the annular flow liquid film characterization experiments are carried out in a narrow rectangular channel without local deformation, ellipsoidal deformation and pillow-shaped deformation, and different annular flow liquid film parameters liquid film thickness, disturbance wave height, and disturbance wave wavelength are obtained by high-speed camera acquisition system and intelligent image processing technology. Analyze the effects of flow conditions and local deformation on the liquid film parameters of each annular flow. Local deformation impact factor functions for liquid film thickness, disturbance wave height, and disturbance wave wavelength are obtained. The error of the impact factor function is within ±30%. © 2024, The Authors. All rights reserved.

关键词： Liquid films

Experimental Study on the Characteristics of Annular Fluid Film in a Locally Deformed Narrow Rectangular Channel

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SSRN 2024年

The local deformation of plate fuel assembly due to neutron irradiation will lead to the deterioration of heat transfer in the flow channel. Studying the characteristics of annular flow films in narrow rectangular channels under localized deformation provides a foundation for understanding the heat and mass transfer and the hydrodynamic characteristics of the locally deformed narrow flow channel. In this study, the annular flow liquid film characterization experiments were conducted in a narrow rectangular channel under three conditions: no local deformation, ellipsoidal deformation, and pillow-shaped deformation. Various parameters of the annular flow liquid films, including liquid film thickness, disturbance wave height, and disturbance wave wavelength, were obtained using a high-speed camera acquisition system and advanced image processing techniques. The effects of flow conditions and local deformation on the liquid film parameters of each annular flow were analyzed. As the radial size of the local deformation increases relative to the liquid film thickness, the viscous bottom layer of the liquid film disintegrates, resulting in a reduction of the total liquid film thickness. When the gas-phase velocity is low, the local deformation exerts a greater shear force on the disturbance wave, prolonging the action time and increasing the likelihood of wave disintegration. Under conditions of no channel deformation, the disturbance wave wavelength is negatively correlated with the gas-phase velocity;conversely, under localized channel deformation, the wavelength is positively correlated with the gas-phase velocity. Thus, the effect of localized deformation on wavelength is bidirectional. Local deformation impact factor functions for liquid film thickness, disturbance wave height, and disturbance wave wavelength have been derived, with the error of these impact factor functions maintained within ±30%. © 2024, The Authors. All rights reserved.

关键词： Neutron irradiation

Image Segmentation Algorithm of Ischemic Stroke based on Wavelet Pooling Neural Network

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Image Segmentation Algorithm of Ischemic Stroke based on Wav...

Signal, Information and Data Processing (ICSIDP), IEEE International Conference on

作者： Huiyuan Zhu Yao Zhai Jinghe Wu Chuwei Lu Xianchao Zhang Ruide Li School of Cyberspace Science and Technology Beijing Institute of Technology Beijing China Department of Nursing College of Medicine Jiaxing University &Provincial Key Laboratory of Multimodal Perceiving and Intelligent Systems Jiaxing China School of Information and Electronics Beijing Institute of Technology Beijing China Avic Xi' An Flight Automatic Control Research Institute Aviation Industry Corporation of China Xi'an China Provincial Key Laboratory of Multimodal Perceiving and Intelligent Systems Jiaxing University Jiaxing China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

Ischemic stroke is a high-risk brain disease that causes disability or death in adults worldwide. Rapid diagnosis and treatment, as well as segmentation of ischemic lesions from stroke medical images so that doctors can evaluate and develop treatment plans, are crucial to reducing brain damage. Currently, doctors’ manual segmentation of lesions is time-consuming and labor-intensive and prone to missed or misdiagnosed diagnoses, delaying the best time for treatment. A well-trained neural network is considered as an effective aid for image segmentation tasks. However, in the traditional neural network down-sampling process, the pooling layer loses feature information, and the lost information significantly impacts the edge regions. While for medical images, edge regions are crucial features in the segmentation process. Therefore, to address the above issues, in this paper we improve upon the existing stroke lesion segmentation algorithm U-net, we design a segmentation network based on wavelet pooling and attention mechanisms. The network was tested on ISLES 2018 and ISLES 2022 datasets, and the Dice coefficient improved by 2.13% and 1.93% compared to baseline network, respectively.

关键词： Image segmentation Image edge detection Medical services Manuals Stroke (medical condition) Discrete wavelet transforms Lesions Medical diagnostic imaging Biological neural networks Diseases

Bioinspired Moth-Eye Multi-Mechanism Composite Ultra-Wideband Microwave Absorber Based on the Graphite Powder

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SSRN 2022年

作者： Chen, Ziming Zhang, Ying Wang, Zhide Wu, Yue Zhao, Yue Liu, Lie Ji, Guangbin College of Materials Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing210016 China General Test Systems Shenzhen518102 China Aviation Key Laboratory of Science and Technology on Stealth Materials AECC Beijing Institute of Aeronautical Materials Beijing100095 China

Broadband electromagnetic wave absorbers are of great significance in military and civil fields. Absorbent coatings, although highly conformal, suffer from a narrow absorption band and a single absorption mechanism. In this work, inspired by the idea of bionics, we extracted the structural model of the moth-eye and designed the structure size by using electromagnetic simulation. Conductive graphite powder was selected as the wave absorbing agent due to its good dielectric and conductivity losses, and the final products were prepared according to the structural parameters obtained from the simulation. The result shows that the frequency bandwidth with absorption rate above 90% (reflection loss © 2022, The Authors. All rights reserved.

关键词： Graphite

Layered Fe-Doped Srlaino 4 Perovskite Electron Transport Layer for Dye-Sensitized Solar Cell with High Open-Circuit Voltage

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SSRN 2023年

作者： Xie, Yuan Gu, Mengmeng Chen, Minghan Cao, Li Zhang, Shaoqing Wang, Yanping Niu, Feier Yan, Haoran Civil Aircraft Fire Science and Safety Engineering Key Laboratory of Sichuan Province Civil Aviation Flight University of China Guanghan618307 China College of Chemistry and Materials Engineering Anhui Science and Technology University Bengbu233030 China Anhui Quartz Sand Purification and Photovoltaic Glass Engineering Research Center Anhui Science and Technology University Bengbu233030 China

This study presents the synthesis of SrLaInO4 perovskite oxides using a high-temperature solid-phase method under atmospheric pressure, with varying Fe-doping concentrations incorporated during fabrication. The synthesized particles underwent characterization using X-ray diffraction and electron microscopy, revealing a layered crystal structure. X-ray photoelectron spectroscopy and energy dispersive X-ray spectroscopy were employed to confirm the successful incorporation of Fe into the SrLaInO4 crystal structure. Significantly, Fe-doping was observed to broaden the light absorption range of the perovskite oxide whilst simultaneously reducing the bandgap. When employed as the electron transport layer in dye-sensitized solar cells, Fe-doped SrLaInO4 perovskite exhibited a maximum efficiency of 4.64%, alongside an open-circuit voltage (VOC) of 0.801 V, which was noticeably higher than that observed in identically-prepared cells employing TiO2 as the electron transport layer. © 2023, The Authors. All rights reserved.

关键词： Open circuit voltage

Learning Adaptive Feature for Object Detection in Low-Light Conditions

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SSRN 2023年

作者： Fu, Gui Chu, Hongyu Tu, Xiaoguang Huang, Yi Liu, Liwen He, Zhi Zhang, Chao Zhang, Chengfang Zhang, Xiaoqiang School of Information Engineering Southwest University of Science and Technology Mianyang621010 China Institute of Electronic and Electrical Engineering Civil Aviation Flight University of China Guanghan618307 China Intelligent Policing Key Laboratory of Sichuan Province Sichuan Police College Luzhou646099 China

In low-light conditions, object detection algorithms suffer from reduced accuracy due to factors like noise and insufficient information. Current solutions often involve a two-stage process: first, improving image illumination, and then performing object detection. However, this method has limitations, as these networks work independently. To address this, we propose a parallel object detection algorithm for low-light environments. Our approach simultaneously encodes image features using both an illumination enhancement network and an object detection network. This innovative design allows these networks to adapt to each other, improving feature adaptability for object detection. We enhance adaptive learning efficiency by introducing a novel mutual feedback mechanism, dynamically adjusts the learning weights of the two networks, thereby enhancing the network's capacity to encode object-related information in low-light conditions. We conducted experiments on both the real-world and synthetic datasets, the results demonstrate that the proposed method outperforms the other state-of-the-art approaches in low-light environments. © 2023, The Authors. All rights reserved.

关键词： Object detection

Flexible Antenna Arrays for Wireless Communications: Modeling and Performance Evaluation

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arXiv

arXiv 2024年

作者： Yang, Songjie An, Jiancheng Xiu, Yue Lyu, Wanting Ning, Boyu Zhang, Zhongpei Debbah, Mérouane Yuen, Chau The National Key Laboratory of Wireless Communications University of Electronic Science and Technology of China Chengdu611731 China College of Air Traffic Management Civil Aviation Flight University of China Sichuan 618311 China KU 6G Research Center Khalifa University of Science and Technology P O Box 127788 Abu Dhabi United Arab Emirates The School of Electrical and Electronics Engineering Nanyang Technological University 639798 Singapore

Flexible antenna arrays (FAAs), distinguished by their rotatable, bendable, and foldable properties, are extensively employed in flexible radio systems to achieve customized radiation patterns. This paper aims to illustrate that FAAs, capable of dynamically adjusting surface shapes, can enhance communication performances with both omni-directional and directional antenna patterns, in terms of multi-path channel power and channel angle Cramér-Rao bounds. To this end, we develop a mathematical model that elucidates the impacts of the variations in antenna positions and orientations as the array transitions from a flat to a rotated, bent, and folded state, all contingent on the flexible degree-of-freedom. Moreover, since the array shape adjustment operates across the entire beamspace, especially with directional patterns, we discuss the sum-rate in the multi-sector base station that covers the 360◦ communication area. Particularly, to thoroughly explore the multi-sector sum-rate, we propose separate flexible precoding (SFP), joint flexible precoding (JFP), and semi-joint flexible precoding (SJFP), respectively. In our numerical analysis comparing the optimized FAA to the fixed uniform planar array, we find that the bendable FAA achieves a remarkable 156% sum-rate improvement compared to the fixed planar array in the case of JFP with the directional pattern. Furthermore, the rotatable FAA exhibits notably superior performance in SFP and SJFP cases with omni-directional patterns, with respective 35% and 281%. Copyright © 2024, The Authors. All rights reserved.

关键词： Base stations

Research on Cart Decision Tree Fire Image Recognition Algorithm Considering Optimal Combination of Color Features

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SSRN 2022年

作者： Li, Hai Sun, Peng Xiong, Sheng-Hua Civil Aircraft Fire Science and Safety Engineering Key Laboratory of Sichuan Province Civil Aviation Flight University of China Guanghan Sichuan 618307 China College of Civil Aviation Safety Engineering Civil Aviation Flight University of China Guanghan Sichuan 618307 China School of Information Science and Engineering Shenyang University of Technology Shenyang110870 China Department of Criminal Science and Technique Criminal Investigation Police University of China Shenyang110854 China

Aiming at the problem of multi-dimensional feature fusion and color feature combination optimization in the process of fire image recognition, a fire image recognition method based on CART decision tree considering the optimal combination of color features was proposed. First, in Lab, RGB and HSV color modes, eigenvalues of fire images are extracted based on image color features. Secondly, the optimal combination of color features is extracted based on fine decision tree. Finally, the extracted optimal feature combination eigenvalues of fire images are used as input of CART decision tree to classify the sample data. Experimental results show that this method has high accuracy in fire image recognition. Its classification effect is obviously better than other decision tree and ensemble tree methods. © 2022, The Authors. All rights reserved.

关键词： Decision trees

Research on Cart Decision Tree Fire Image Recognition Algorithm Considering Optimal Combination of Color Features

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SSRN 2022年

关键词： Decision trees