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Variable stiffness design optimization of fiber-reinforced composite laminates with regular and irregular holes considering fiber continuity for additive manufacturing

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Chinese Journal of Aeronautics 2025年第3期38卷 334-354页

作者： Yi LIU Zunyi DUAN Chunping ZHOU Yuan SI Chenxi GUAN Yi XIONG Bin XU Jun YAN Jihong ZHU School of Mechanics Civil Engineering&ArchitectureNorthwestern Polytechnical UniversityXi’an 710072China Research&Development Institute of Northwestern Polytechnical University in Shenzhen Shenzhen 518063China Key Lab for Airborne Hi-performance Electro-magnetic Window RISACJinan 130012China School of System Design and Intelligent Manufacturing Southern University of Science and TechnologyShenzhen 518055China State Key Laboratory of Structural Analysis for Industrial Equipment Department of Engineering MechanicsInternational Research Center for Computational MechanicsDalian University of TechnologyDalian 116024China State IJR Center of Aerospace Design and Additive Manufacturing MIIT Lab of Metal Additive Manufacturing and Innovative DesignNorthwestern Polytechnical UniversityXi’an 710072China

Fiber-reinforced composites are an ideal material for the lightweight design of aerospace structures. Especially in recent years, with the rapid development of composite additive manufacturing technology, the design optimization of variable stiffness of fiber-reinforced composite laminates has attracted widespread attention from scholars and industry. In these aerospace composite structures, numerous cutout panels and shells serve as access points for maintaining electrical, fuel, and hydraulic systems. The traditional fiber-reinforced composite laminate subtractive drilling manufacturing inevitably faces the problems of interlayer delamination, fiber fracture, and burr of the laminate. Continuous fiber additive manufacturing technology offers the potential for integrated design optimization and manufacturing with high structural performance. Considering the integration of design and manufacturability in continuous fiber additive manufacturing, the paper proposes linear and nonlinear filtering strategies based on the Normal Distribution Fiber Optimization (NDFO) material interpolation scheme to overcome the challenge of discrete fiber optimization results, which are difficult to apply directly to continuous fiber additive manufacturing. With minimizing structural compliance as the objective function, the proposed approach provides a strategy to achieve continuity of discrete fiber paths in the variable stiffness design optimization of composite laminates with regular and irregular holes. In the variable stiffness design optimization model, the number of candidate fiber laying angles in the NDFO material interpolation scheme is considered as design variable. The sensitivity information of structural compliance with respect to the number of candidate fiber laying angles is obtained using the analytical sensitivity analysis method. Based on the proposed variable stiffness design optimization method for complex perforated composite laminates, the numerical examples cons

关键词： Variable stiffness composite laminates Discrete material interpolation scheme Normal distribution fiber optimization Discrete fiber continuous filtering strategy Additive manufacturing of composite laminates

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Unsupervised Semantic Segmentation with Contrastive Translation Coding 6th

Unsupervised Semantic Segmentation with Contrastive Translat...

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6th International Conference on Cognitive systems and Signal Processing, ICCSIP 2021

作者： Chen, Runfa Sun, Hanbing Wang, Ling State Key Lab on Intelligent Technology and Systems Department of Computer Science and Technology Tsinghua University Beijing China Department of Air Defense Early Warning Command System Air Force Early Warning Academy Wuhang China

ISBN: (纸本)9789811692468

The proposed new method constructs a contrastive learning task through unsupervised image-to-image translation and indirectly extracts domain-invariant features by maximizing mutual information. Specifically, by reusing the semantic segmentation network for image-to-image translation, the probability space of the segmentation output is projected into the RGB space, thereby constructing positive and negative samples to maximize the mutual information between the input image and the semantic segmentation RGB projection map. Meanwhile, the output space of the target domain is transferred to the source domain, and then the robust domain-invariant semantic features are extracted. We develop two adversarial transfer methods and a three-stage training paradigm of pre-training, cross-domain transfer, and self-supervised training. Experiments on benchmarks demonstrate that this method is reasonable and feasible. Comprehensive ablation studies and analyses are also carried out to reveal the advantages and disadvantages of the two designed transfer schemes and the effect and significance of color-invariant semantic information for unsupervised semantic segmentation tasks. The contrastive learning task, which is constructed through unsupervised cross-domain image-to-image translation, provides a new insight for cross-domain transfer learning to overcome the problem of domain shift. © 2022, Springer Nature Singapore Pte Ltd.

关键词： Semantic Segmentation

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Theoretical study of the electroactive bistable actuator and regulation methods

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International Journal of Smart and Nano Materials 2023年第1期14卷 36-56页

作者： Wenjie Sun Huwei Liang Fei Zhang Bo Li School of Mechanical and Precision Instrument Engineering Xi’an University of Technology710048Xi’anChina State Key Laboratory for Strength and Vibration of Mechanical Structures and School of Aerospace Xi’an Jiaotong University710049Xi’anChina CAS Center for Excellence in Nanoscience Beijing Key Laboratory of Micro-nano Energy and SensorBeijing Institute of Nano Energy and Nano SystemsChinese Academy of Sciences101400BeijingChina State Key Laboratory for Manufacturing System Engineering Shaanxi Key Lab for the Intelligent RobotsSchool of Mechanical EngineeringXi’an Jiaotong University710049Xi’anChina

Dielectric elastomer actuators have attracted growing interest for soft robot due to their large deformation and fast ***,continuous high-voltage loading tends to cause the electric breakdown of the actuator due to heat accumulation,and viscoelasticity complicates precise *** snap-through bistability of the Venus flytrap is one of the essential inspirations for bionic structure,which can be adopted to improve the shortcoming of dielectric elastomer actuators and develop a new actuation structure with low energy consumption,variable configuration,and multi-mode ***,in this paper,the structural design principles of electroactive bistable actuators are first presented based on the total potential energy of the *** that,a feasible design parameter region is provided,the influence of crucial parameters on the actuation stroke,trigger voltage,and actuation charge are ***,according to the coupling relationship between the bending stiffness and the bistable property of the actuator,the adjusting methods of bistable actuation are explored.A qualitative experiment was performed to verify the feasibility and correctness of the bistable design methodology and the actuation regulation *** study provides significant theoretical guidance and technical support for developing and applying dielectric elastomer actuators with multi-mode,high-performance,and long-life characteristics.

关键词： Dielectric elastomer bistable structure snap-through electromechanical actuation minimum energy structure

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A fast calculation method for three-impulse contingency return trajectory during the near-moon phase based on differential algebra

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Chinese Journal of Aeronautics 2025年第4期 290-308页

作者： Lin LU Haiyang LI Tianshan DONG Wanmeng ZHOU College of Aerospace Science and Technology National University of Defense Technology Hunan Key Laboratory of Intelligent Planning and Simulation for Aerospace Missions Beijing Institute of Spacecraft System Engineering China Astronaut Research and Training Center

Aimed at the demand of contingency return at any time during the near-moon phase in the manned lunar landing missions,a fast calculation method for three-impulse contingency return trajectories is ***,a three-impulse contingency return trajectory scheme is presented by combining the Lambert transfer and maneuver at the special ***,a calculation model of three-impulse contingency return trajectories is ***,fast calculation methods are proposed by adopting the high-order Taylor expansion of differential algebra in the twobody trajectory dynamics model and perturbed trajectory dynamics ***,the performance of the proposed methods is verified by numerical *** results indicate that the fast calculation method of two-body trajectory has higher calculation efficiency compared to the semi-analytical calculation method under a certain accuracy *** to its high efficiency,the characteristics of the three-impulse contingency return trajectories under different contingency scenarios are further analyzed *** findings can be used for the design of contingency return trajectories in future manned lunar landing missions.

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AWNet: Negative obstacle semantic segmentation Network based on adaptive weight loss 22

AWNet: Negative obstacle semantic segmentation Network based...

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22nd IEEE International Conference on Industrial Informatics, INDIN 2024

作者： Zhao, Jiarui Yu, Guizhen Wang, Jie Wang, Zhangyu Zhang, Junjie Feng, Yunsong School of Transportation Science and Engineering Beihang University Beijing China State Key Lab of Intelligent Transportation System Beihang University Beijing China The Key Laboratory of Autonomous Transportation Technology for Special Vehicles Beihang University Beijing China Ministry of Industry and Information Technology Beihang University Beijing China Research Institute for Frontier Science Beihang University Hefei China Hefei innovation research institute of Beihang university Beihang University Hefei China State Key Laboratory of Pulsed Power Laser Technology National University of Defense Technology Heufei China

ISBN: (纸本)9798331527471

On roads, both vehicles and pedestrians will leave traces after passing by. Slight traces will not cause any trouble to the passing vehicles and pedestrians subsequently. However, there are certain potholes in the road that have been formed by repeated crushing of vehicles. It may cause mechanical damage to following vehicles and lead to accidents as vehicles get stuck in the potholes. Thus, the segmentation of negative obstacles is crucial for the safe driving of self-driving vehicles. This paper proposed an AWNet neural network to this end, and quantitative analyses were conducted based on the publicly available dataset DRNO. Specifically, a random cut-and-joint module (RCJ) was proposed to augment the dataset. The cross-entropy loss function was modified by adding an adaptive weight module, i.e., the adaptive weight cross-entropy loss function. It allows the model to focus on negative obstacles during implementation. Furthermore, this paper proposed a post-processing module for adaptive viewpoint conversion based on depth maps, which is capable of fusing depth maps and RGB images to convert the front view into a BEV viewpoint. The mAcc for Negative obstacle semantic segmentation can reach 78.39%, the mIoU can reach 73.21%, the mF1 can reach 79.23%. The experimental results reveal that the AWNet is able to state-of-the-art performance compared with other networks. © 2024 IEEE.

关键词： Semantic Segmentation

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AWNet: Negative Obstacle Semantic Segmentation Network Based on Adaptive Weight Loss

AWNet: Negative Obstacle Semantic Segmentation Network Based...

引用

IEEE International Conference on Industrial Informatics (INDIN)

作者： Jiarui Zhao Guizhen Yu Jie Wang Zhangyu Wang Junjie Zhang Yunsong Feng State Key Lab of Intelligent Transportation System School of Transportation Science and Engineering The Key Laboratory of Autonomous Transportation Technology for Special Vehicles Ministry of Industry and Information Technology Beihang University Beijing China State Key Lab of Intelligent Transportation System Research Institute for Frontier Science Hefei innovation research institute of Beihang university Beihang University Hefei China State Key Laboratory of Pulsed Power Laser Technology National University of Defense Technology Heufei China

ISBN: (数字)9798331527471

ISBN: (纸本)9798331527488

On roads, both vehicles and pedestrians will leave traces after passing by. Slight traces will not cause any trouble to the passing vehicles and pedestrians subsequently. However, there are certain potholes in the road that have been formed by repeated crushing of vehicles. It may cause mechanical damage to following vehicles and lead to accidents as vehicles get stuck in the potholes. Thus, the segmentation of negative obstacles is crucial for the safe driving of self-driving vehicles. This paper proposed an AWNet neural network to this end, and quantitative analyses were conducted based on the publicly available dataset DRNO. Specifically, a random cut-and-joint module (RCJ) was proposed to augment the dataset. The crossentropy loss function was modified by adding an adaptive weight module, i.e., the adaptive weight cross-entropy loss function. It allows the model to focus on negative obstacles during implementation. Furthermore, this paper proposed a post-processing module for adaptive viewpoint conversion based on depth maps, which is capable of fusing depth maps and RGB images to convert the front view into a BEV viewpoint. The mAcc for Negative obstacle semantic segmentation can reach $78.39\%$ , the mIoU can reach $73.21{{\% }}$ , the mF 1 can reach $79.23{{\% }}$ . The experimental results reveal that the AWNet is able to state-of-the-art performance compared with other networks.

关键词： Adaptation models Pedestrians Statistical analysis Roads Semantic segmentation Semantics Neural networks Data augmentation Data models Informatics

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Study on the thinning characteristics of aviation tubes during bending forming under boundary lubrication friction

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Journal of Manufacturing Processes 2025年 149卷 443-455页

作者： Wu, Yu Wang, Zhineng Tian, Jing Chen, Renzhen Lin, Weiming Lin, Yaochen Health Maintenance for Mechanical Equipment Key Lab Hunan University of Science and Technology Xiangtan411201 China Liaoning Key Laboratory of Advanced Measurement and Test Technology for Aviation Propulsion System Shenyang Aerospace University Shenyang110136 China Zhejiang King-Mazon Intelligent Manufacturing Corp. Ltd Lijiang321400 China

The reduction of wall thickness during the bending forming process of aviation tubes is a common issue, particularly for large-diameter, thick-walled tubes. Under heavy load conditions, the lubrication state deteriorates, leading to a boundary lubrication state that complicates the prediction of wall thickness reduction. Current research on tube bending forming relies on Coulomb friction, which does not accurately reflect real-world conditions. Therefore, we propose a method for analysing tube thinning during bending forming that considers the friction characteristics of boundary lubrication. ABAQUS/VFRIC was employed to develop a dynamic friction model that considers contact pressure. Additionally, material hardness and RMS roughness were incorporated into the finite element simulation. Results show that as the tubing advances, the contact area between the pressure die and the tube changes and the friction between them generates a certain amount of compressive stress. An increase in contact pressure results in a higher friction coefficient, leading to a substantial rise in the tensile stress on the tube's exterior, further aggravating the thinning of the outer wall. In particular, stress concentrations and elevated strains resulting from boundary lubrication friction are especially pronounced at the 40° and 60° bending positions. In addition, increased RMS roughness and decreased material hardness contribute to more significant thinning effects. Experimental verification indicates that this dynamic friction model offers greater accuracy than the traditional Coulomb friction model in predicting wall thickness thinning, achieving a maximum error reduction to 3% and an accuracy enhancement of 7%. The findings provide theoretical support for process optimisation in aerospace manufacturing and establish a foundation for designing and implementing high-precision forming processes. © 2025 The Society of Manufacturing Engineers

关键词： Bending (forming)

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Adaptive Optimization Tracking Control for an Unmanned Aerial Vehicle with Disturbance Suppression

Adaptive Optimization Tracking Control for an Unmanned Aeria...

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IEEE International Conference on systems, Man and Cybernetics

作者： Meiying Yang Hai Zhu Xingyu Xia Zhe Liu Wen Yao MoE Key Lab of Artificial Intelligence AI Institute Shanghai Jiao Tong University Shanghai China Defense Innovation Institute Chinese Academy of Military Science Beijing China Intelligent Game and Decision Laboratory Beijing China College of Aerospace Science and Engineering National University of Defense Technology Changsha China

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

Aiming at the tracking control for an unmanned aerial vehicle (UAV) with uncertainty and external disturbances, an adaptive optimization control method is proposed based on the backstepping method. The model uncertainty in the UAV is estimated using neural networks. Moreover, a disturbance observer is designed to estimate and counteract the disturbance in real-time. In addition, reinforcement learning (RL) is used to solve optimal problems and overcome the difficult issues of the Hamilton-Jacobi-Bellman (HJB) equation. In the controller design, dynamic surfaces are employed to avoid complex derivation issues in the virtual controller and improve operating efficiency. Furthermore, the stability of the UAV system is proved by the Lyapunov theory. Finally, the effectiveness and superiority of the proposed method are verified through numerical simulations and real-world experiments.

关键词： Uncertainty Backstepping Neural networks Autonomous aerial vehicles Numerical simulation Mathematical models Stability analysis Disturbance observers Optimization Numerical stability

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TS-ENAS:Two-Stage Evolution for Cell-based Network Architecture Search

arXiv

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arXiv 2023年

作者： Zou, Juan Wu, Shenghong Xia, Yizhang Jiang, Weiwei Wu, Zeping Zheng, Jinhua Engineering Research Center of Hunan Province for Optimization and Security of Intelligent System Key Laboratory of Intelligent Computing and Information Processing Ministry of Education of China Key Laboratory of Hunan Province for Internet of Things and Information Security Xiangtan University Hunan Province Xiangtan411105 China The College of Aerospace Science and Engineering National University of Defense Technology Hunan Changsha410073 China

Neural network architecture search provides a solution to the automatic design of network structures. However, it is difficult to search the whole network architecture directly. Although using stacked cells to search neural network architectures is an effective way to reduce the complexity of searching, these methods do not able find the global optimal neural network structure since the number of layers, cells and connection methods is fixed. In this paper, we propose a Two-Stage Evolution for cell-based Network Architecture Search(TS-ENAS), including one-stage searching based on stacked cells and second-stage adjusting these cells. In our algorithm, a new cell-based search space and an effective two-stage encoding method are designed to represent cells and neural network structures. In addition, a cell-based weight inheritance strategy is designed to initialize the weight of the network, which significantly reduces the running time of the algorithm. The proposed methods are extensively tested and compared on four image classification dataset, Fashion-MNIST, CIFAR10, CIFAR100 and ImageNet and compared with 22 state-of-the-art algorithms including hand-designed networks and NAS networks. The experimental results show that TS-ENAS can more effectively find the neural network architecture with comparative performance. Copyright © 2023, The Authors. All rights reserved.

关键词： Image classification

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A 4-Channel Ultrafast Wavelength-Swept REC-DFB Laser Array for Fiber Bragg Grating Interrogation

A 4-Channel Ultrafast Wavelength-Swept REC-DFB Laser Array f...

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2023 Asia Communications and Photonics Conference/2023 International Photonics and Optoelectronics Meetings, ACP/POEM 2023

作者： Meng, Lingxin Dai, Pan Ban, Qilu Xu, Kaichuan Wang, Jiacheng Li, Zhen Wang, Feng Zeng, Jie Li, Shaobo Ma, Xiang Chen, Xiangfei Res. Center of Precision Photonics Integration and System Application of the Ministry of Education College of Engineering and Applied Sciences Nanjing University Key Lab. of Intelligent Optical Sensing and Manipulation of the Ministry of Education Engineering National Laboratory of Solid State Microstructures Nanjing210023 China Nanjing University of Aeronautics and Astronautics State Key Laboratory of Mechanics and Control for Aerospace Structures Nanjing210016 China The 54th Research Institute of China Electronics Technology Group Corporation Optical Communication Research and Development Center Shijiazhuang050081 China

ISBN: (纸本)9798350312614

We present a four-channel ultrafast wavelength-swept distributed feedback (DFB) semiconductor laser array based on the reconstruction-equivalent-chirp (REC) technique using instantaneous injection current modulation. With the aid of our designed laser driving circuit system consists of the microcontroller unit (MCU), field-programmable gate array (FPGA) and negative metal-oxide-semiconductor field effect transistors (n-MOSFETs), the precise pulse driving current for the 4-channel wavelength-swept REC-DFB laser array can be generated and a fast tuning of 16.424 nm within 10 μs is achieved. To further investigate the tuning performance of the proposed wavelength-swept laser source, we then applied it to the fiber Bragg grating (FBG) interrogation system and four FBG temperature sensor arrays were successfully demodulated. The development of high-efficient optical sensing systems heavily relies on the significance of the ultrafast wavelength-swept laser source, which has the potential to greatly enhance FBG interrogator performance in the future. © 2023 IEEE.

关键词： DFB laser array fast wavelength-swept fiber Bragg grating interrogation REC technique

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