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Performance Analysis and Comparison of Different Corrugated Structures and a Novel Alternative Elliptical Twisted Tube in Supercritical Co2 Tower Solar Receivers

SSRN

引用

SSRN 2022年

作者： Liu, Yun Dong, Yue Li, Tao Zhang, Chuan-Zhi Hebei Key Laboratory of Low Carbon and High Efficiency Power Generation Technology School of Energy Power and Mechanical Engineering North China Electric Power University Baoding071003 China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin300384 China

The concentrated solar power generation system with supercritical CO 2 as working medium has high cycle efficiency, which can effectively reduce the volume of heat exchange equipment and reduce the investment cost. However, there is no systematic comparative study on the effect of tube structure on the performance of supercritical CO 2 , but the structure of tubes has a significant effect on the heat transfer performance of supercritical CO 2 , so it is necessary to study it. In this contribution, we firstly analyze the effects of different structures of tubes on the performance of supercritical CO 2 . Then, we design a novel alternative elliptical twisted tube. Finally, we further analyze the effects of the novel tube on the heat transfer performance of supercritical CO 2 by using the field synergy principle. The results show that the novel alternative elliptical twisted tube is the best structure. When the mass flow is 0.08 kg·s - © 2022, The Authors. All rights reserved.

关键词： Solar energy

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PUGAN: Physical Model-Guided Underwater Image Enhancement Using GAN with Dual-Discriminators

arXiv

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arXiv 2023年

作者： Cong, Runmin Yang, Wenyu Zhang, Wei Li, Chongyi Guo, Chun-Le Huang, Qingming Kwong, Sam Institute of Information Science Beijing Jiaotong University Beijing100044 China School of Control Science and Engineering Shandong University Jinan250061 China Key Laboratory of Machine Intelligence and System Control Ministry of Education Jinan250061 China Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing100044 China College of Computer Science Nankai University Tianjin300350 China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing101408 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China Peng Cheng Laboratory Shenzhen518055 China Department of Computer Science City University of Hong Kong Hong Kong City University of Hong Kong Shenzhen Research Institute Shenzhen51800 China

Due to the light absorption and scattering induced by the water medium, underwater images usually suffer from some degradation problems, such as low contrast, color distortion, and blurring details, which aggravate the difficulty of downstream underwater understanding tasks. Therefore, how to obtain clear and visually pleasant images has become a common concern of people, and the task of underwater image enhancement (UIE) has also emerged as the times require. Among existing UIE methods, Generative Adversarial Networks (GANs) based methods perform well in visual aesthetics, while the physical model-based methods have better scene adaptability. Inheriting the advantages of the above two types of models, we propose a physical model-guided GAN model for UIE in this paper, referred to as PUGAN. The entire network is under the GAN architecture. On the one hand, we design a Parameters Estimation subnetwork (Par-subnet) to learn the parameters for physical model inversion, and use the generated color enhancement image as auxiliary information for the Two-Stream Interaction Enhancement subnetwork (TSIE-subnet). Meanwhile, we design a Degradation Quantization (DQ) module in TSIE-subnet to quantize scene degradation, thereby achieving reinforcing enhancement of key regions. On the other hand, we design the Dual-Discriminators for the style-content adversarial constraint, promoting the authenticity and visual aesthetics of the results. Extensive experiments on three benchmark datasets demonstrate that our PUGAN outperforms state-of-the-art methods in both qualitative and quantitative metrics. The code and results can be found from the link of https://***/proj_***. © 2023, CC BY-NC-SA.

关键词： Discriminators

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Attention-Guided Second-Order Pooling Convolutional Networks

Attention-Guided Second-Order Pooling Convolutional Networks

引用

IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Shannan Chen Qiule Sun Cunhua Li Jianxin Zhang Qiang Zhang Key Lab of Advanced Design and Intelligent Computing Dalian University China Faculty of Electronic Information and Electrical Engineering Dalian University of Technology China School of Computer Engineering Jiangsu Ocean University China School of Computer Science and Engineering Dalian Minzu University China

Recently, channel attention-guided convolutional networks (ConvNets) have shown great advance on visual recognition tasks. However, they mainly exploit coarse first-order statistics to characterize holistic image and rarely focus on long-range feature dependencies, which limits the representation power in a certain. To handle above limitations, this paper proposes a novel attention-guided second-order pooling convolutional network (ASP-Net). ASP-Net introduces bilinear pooling that captures pairwise feature interactions to model second-order statistics. Meanwhile, it explicitly collects long-range dependencies via non-local operations, thus providing a global view in lower layers. Then, the second-order statistics and non-local context features are fused to obtain the enhanced representation for predicting channel-wise attention map and scaling convolution features. Experiment results on three commonly used datasets illuminate that ASP-Net outperforms its counterparts and achieves competitive performance.

关键词： Convolutional codes Visualization Convolution Conferences Network architecture Acoustics Task analysis

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Diff9D: Diffusion-Based Domain-Generalized Category-Level 9-DoF Object Pose Estimation

arXiv

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arXiv 2025年

作者： Liu, Jian Sun, Wei Yang, Hui Deng, Pengchao Liu, Chongpei Sebe, Nicu Rahmani, Hossein Mian, Ajmal National Engineering Research Center for Robot Visual Perception and Control Technology College of Electrical and Information Engineering School of Robotics State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Hunan University Changsha410082 China Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Xi’an710049 China Department of Information Engineering and Computer Science University of Trento Trento38123 Italy School of Computing and Communications Lancaster University LA1 4YW United Kingdom Department of Computer Science The University of Western Australia WA6009 Australia

Nine-degrees-of-freedom (9-DoF) object pose and size estimation is crucial for enabling augmented reality and robotic manipulation. Category-level methods have received extensive research attention due to their potential for generalization to intra-class unknown objects. However, these methods require manual collection and labeling of large-scale real-world training data. To address this problem, we introduce a diffusion-based paradigm for domain-generalized category-level 9-DoF object pose estimation. Our motivation is to leverage the latent generalization ability of the diffusion model to address the domain generalization challenge in object pose estimation. This entails training the model exclusively on rendered synthetic data to achieve generalization to real-world scenes. We propose an effective diffusion model to redefine 9-DoF object pose estimation from a generative perspective. Our model does not require any 3D shape priors during training or inference. By employing the Denoising Diffusion Implicit Model, we demonstrate that the reverse diffusion process can be executed in as few as 3 steps, achieving near real-time performance. Finally, we design a robotic grasping system comprising both hardware and software components. Through comprehensive experiments on two benchmark datasets and the real-world robotic system, we show that our method achieves state-of-the-art domain generalization performance. Our code will be made public at https://***/CNJianLiu/Diff9D. Copyright © 2025, The Authors. All rights reserved.

关键词： Augmented reality

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Finite Element Analysis of Series Elastic Actuator for Exoskeleton Robot Joint 17

Finite Element Analysis of Series Elastic Actuator for Exosk...

引用

17th IEEE International Conference on Mechatronics and Automation, ICMA 2020

作者： Xi, Pengyu Ge, Weimin Zhang, Sen Zhang, Zhili Zielinska, Teresa Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin300384 China Tianjin Sino-German University of Applied Science Intelligent Manufacturing College Tianjin300384 China Institute of Aeronautics and Applied Mechanics Warsaw University of Technology Warsaw00665 Poland

ISBN: (纸本)9781728164151

The finite element simulation for the joints of an exoskeleton robot is conducted in this paper. Using software OpenSim to simulate the normal walking gait of the human body, the motion angle and moment of the human hip, knee and ankle joints are obtained. Using the obtained data as the input parameters in the finite element simulation of the simulation software Ls-dyna, the strain diagrams and contact force curves of the circular roller and cam disk were obtained. In this study, three commonly used materials are selected: alloy steel, ductile iron and hard aluminum alloy. Finally, the effects of different materials on the key components of the series elastic actuator are studied. © 2020 IEEE.

关键词： Finite element method

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Missing Data Recovery for Human Mocap Data Based on A-LSTM and LS Constraint

Missing Data Recovery for Human Mocap Data Based on A-LSTM a...

引用

IEEE International Conference on Signal and Image Processing (ICSIP)

作者： Lu Ji Rui Liu Dongsheng Zhou Qiang Zhang Xiaopeng Wei Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian University Dalian China School of Computer Science and Technology Dalian University of Technology Dalian China

ISBN: (数字)9781728168968

ISBN: (纸本)9781728168975

Human mocap (motion capture) data has been widely used in many fields. However, influenced by the occlusion and falling, missing of markers is inevitable in optical motion capture system. According to the temporal and spatial characteristics of mocap data, a missing data recovery method based on attention-based LSTM network (A-LSTM) and least-squares (LS) constraint is proposed in this paper. First, the LSTM is chosen as the basic network to estimate the position of the missing markers, in which an attention mechanism is introduced to learn the temporal continuity of human mocap data. Then, a space affine transformation based on least-squares fitting is adopted as the spatial constraint to refine the estimated positions, after which the restored error can be reduced significantly. Experiments show that the proposed A-LSTM+LS method is robust to the length of missing gap and the number of missing markers. Under the same conditions, our method achieves smaller restore error than the state of the art.

关键词： Legged locomotion Deep learning Image recognition Correlation Fitting Neural networks Image restoration

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Digital twin-driven machining process for multi-process irregular-shaped parts manufacturing

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Computers & Industrial Engineering 2024年

作者： Zhiwen Lin Zhifeng Liu Yueze Zhang Baobao Qi Jinyan Guo Chuanhai Chen Key Laboratory of Advanced Manufacturing and Intelligent Technology for High-end CNC Equipment Jilin Province Changchun 130025 China Key Laboratory of CNC Equipment Reliability Ministry of Education Jilin University Changchun 130025 China Machinery Industry Key Laboratory of Heavy Machine Tool Digital Design and Testing Technology Beijing University of Technology Beijing 100124 China

With the advancement of high-end manufacturing industries, certain critical parts exhibit peculiar shapes and characteristics of multi-process manufacturing, which intensify milling difficulties and give rise to error propagation effects during the machining process. This necessitates machining systems to be adaptive to different working conditions and capable of real-time error analysis and optimization. Digital twin technology can create virtual replicas of physical entities to observe, analyze, and optimize the machining process. Therefore, this paper proposes a framework for digital twin-driven machining of multi-process irregular-shaped parts, consisting of preparation, processing, and optimization stages. In the preparation stage, a mapping relationship between the workpiece and machine tool motion coordinates is established to create a twin simulation environment consistent with actual operational parameters. In the processing stage, the digital thread dynamically updates the digital twin workpiece and machine tool status in real-time, analyzing the machining errors for each process to assess the finished quality. In the optimization stage, a cloud-based machining knowledge graph is constructed to enhance the precision of machining optimization decisions under different error sources and causes in the digital twin system. Finally, a case study of a typical multi-process irregular-shaped part machining task validates the reliability and superiority of the digital twin-driven method. The case study demonstrates that in a total of 260 machining processes, the digital twin-driven method improves machining accuracy by 40%, saves 34.9% of machining time, and alleviates 70% of machining downtime compared to existing machining methods.

关键词： Digital Twin-driven machining Multi-process irregular-shaped parts machining Digital twin enabling technologies Digital twin machine tool Reliable manufacturing

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Ultrafast demagnetization in ferromagnetic materials: origins and progress

arXiv

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arXiv 2024年

作者： Chen, Xiaowen Adam, Roman Bürgler, Daniel E. Wang, Fangzhou Lu, Zhenyan Pan, Lining Heidtfeld, Sarah Greb, Christian Liu, Meihong Liu, Qingfang Wang, Jianbo Schneider, Claus M. Cao, Derang College of Physics Qingdao University Qingdao266071 China National Demonstration Center for Experimental Applied Physics Education Qingdao University Qingdao266071 China Spin-X Institute South China University of Technology Guangzhou511442 China Peter Grünberg Institute Forschungszentrum Jülich Jülich52425 Germany Hunan Provincial Key Laboratory of Intelligent Sensors and Advanced Sensor Materials School of Physics and Electronics Hunan University of Science and Technology Xiangtan411201 China CAS Key Laboratory of Magnetic Materials and Devices Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Ningbo315201 China Key Laboratory for Magnetism and Magnetic Materials of Ministry of Education Lanzhou University Lanzhou730000 China Key Laboratory of Special Functional Materials and Structural Design Ministry of Education Lanzhou University Lanzhou730000 China Faculty of Physics University of Duisburg-Essen Duisburg47057 Germany Department of Physics University of California Davis DavisCA95616-5270 United States

Since the discovery of ultrafast demagnetization in Ni thin films in 1996, laser-induced ultrafast spin dynamics have become a prominent research topic in the field of magnetism and spintronics. This development offers new possibilities for the advancement of spintronics and magnetic storage technology. The subject has drawn a substantial number of researchers, leading to a series of research endeavors. Various models have been proposed to elucidate the physical processes underlying laser-induced ultrafast spin dynamics in ferromagnetic materials. However, the potential origins of these processes across different material systems and the true contributions of these different origins remain challenging in the realm of ultrafast spin dynamics. This predicament also hinders the development of spintronic terahertz emitters. In this review, we initially introduce the different experimental methods used in laser-induced ultrafast spin dynamics. We then systematically explore the magnetization precession process and present seven models of ultrafast demagnetization in ferromagnetic materials. Subsequently, we discuss the physical processes and research status of four ultrafast demagnetization origins (including spin-flipping, spin transport, non-thermal electronic distribution, and laser-induced lattice strain). Since attosecond laser technique and antiferromagnetic materials exhibit promising applications in ultrahigh-frequency spintronics, we acknowledge the emerging studies used by attosecond pules and studies on ultrafast spin dynamics in antiferromagnets, noting the significant challenges that need to be addressed in these burgeoning field. © 2024, CC BY.

关键词： Spin dynamics

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A real-time one-time pad DNA-chaos image encryption algorithm based on multiple keys

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Optics & Laser Technology 2021年 143卷

作者： Shihua Zhou Key laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian University Dalian China

Image encryption is an important necessity when sharing data over public networks, and many image encryption algorithms have been proposed for the task. However, most of these algorithms are complex and slow. We propose a real-time one-time pad DNA-chaos image encryption algorithm using multiple keys. The proposed encryption algorithm uses a greatly simplified mechanism and a large, unpredictable sequence to encrypt the image. Our algorithm has three main advantages. First, its reliance on the original image for four of the keys makes it sensitive to changes in the original image. Small changes in the image produce large changes in the keys, making the algorithm resistant to differential attacks. Second, we integrate the natural DNA sequence into the process of generating the key, and the algorithm uses the massive DNA sequences stored in the DNA gene bank to solve the problem that it is difficult to store one-time pad. The keys have the property of one-time pad, and the key space is considerablely large. Finally, our algorithm encrypts quickly enough to make it suitable for real-time applications. On the premise of ensuring that the results of this paper are not worse than those of the comparison literature in other performance indicators, in terms of encryption time, even if we use a computing environment that is worse than all the comparison literature computer configurations, the algorithm of this paper can still save at least 14%–86%. As the picture size becomes larger, the advantages of the algorithm in this paper are more obvious.

关键词： Image encryption Multiple keys DNA coding Chaos 00-01 99-00

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Graph Confidence Intercalibration Network for Intracranial Aneurysm Lesion Instance Segmentation in Dsa

SSRN

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SSRN 2024年

作者： Ye, Haili Mo, Yancheng Tang, Chen Liao, Mingqian Zhang, Xiaoqing Dai, Limeng Li, Baihua Liu, Jiang Research Institute of Trustworthy Autonomous Systems Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China Department of Computer Science Loughborough University LoughboroughLE11 3TU United Kingdom School of Ophthalmology and Optometry Eye Hospital Wenzhou Medical University Wenzhou325027 China Center for High Performance Computing and Shenzhen Key Laboratory of Intelligent Bioinformatics Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Shenzhen People’s Hospital Neurosurgery Department Shenzhen518020 China China

Intracranial aneurysm (IA) lesion segmentation is significant for its treatment and prognosis. Although exiting deep network-based instance methods have good IA lesion segmentation results based on digital subtraction angiography (DSA) images, they still face great challenges with instance confidence bias and imprecise boundary segmentation, which may negatively affect IA diagnosis. To tackle these problems, this paper proposes a novel graph confidence intercalibration network (GCINet) to automatically segment IA lesions from DSA images. To be specific, we design a graph confidence intercalibration (GCI) module to mitigate instance confidence bias by dynamically adjusting their confidence distributions. At the same time, we propose an edge space perception (ESP) module to correct ambiguous segmentation boundaries. Extensive experiments on a clinical IA-DSA and a publicly available LiTS dataset demonstrate that our GCINet outperforms state-of-the-art methods. Additionally, visual analysis and ablation studies are provided to verify the effectiveness of each module in GCINet. © 2024, The Authors. All rights reserved.

关键词： Image segmentation

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