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7th International Conference on Information science and Control Engineering, ICISCE 2020

作者： Lin, Menglong Yi, Shuanghui Zhang, Mengmeng Shu, Zhen National University of Defense Technology Science and Technology on Information Systems Engineering Laboratory Changsha China National Key Laboratory for Complex System Simulation Beijing China

ISBN: (纸本)9781728164069

In recent years, the development and deployment of the U.S. weapon equipment systems-of-systems (SoS) have yielded rich research results. However, there are still large gaps in the SoS development, joint testing, and design and acquisition of our own equipment SoS. The barriers of these steps have not yet been opened up. This article mainly analyzes the solutions of the U.S. weapon equipment SoS from three aspects, such as capability-based requirement generation and architecture design technology, interconnected-oriented integration test technology, and weapon equipment design and acquisition technology based on complex adaptive systems. We explore key technologies involved in order to form an overall understanding and explore related research approaches. © 2020 IEEE.

关键词： System of systems

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Deep Learning-Based Prediction of Subsurface Oil Reservoir Pressure Using Spatio-Temporal Data 49

Deep Learning-Based Prediction of Subsurface Oil Reservoir P...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Cheng, Haibo He, Yunpeng Zeng, Peng Li, Shichao Vyatkin, Valeriy Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang China Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China Luleå University of Technology Department of Computer Science Electrical and Space Engineering Luleå Sweden Aalto University Department of Electrical Engineering and Automation Helsinki Finland

ISBN: (纸本)9798350331820

Prediction of subsurface oil reservoir pressure are critical to hydrocarbon production. However, the accurate pressure estimation faces great challenges due to the complexity and uncertainty of reservoir. The underground seepage flow and petrophysical parameters (permeability and porosity) are important but difficult to measure in oilfield. Deep learning methods have been successfully used in reservoir engineering and oil & gas production process. In this study, the effective but inaccessible subsurface seepage fields are not used, only the spatial coordinates and temporal information are selected as model input to predict reservoir pressure. A stacked GRU-based deep learning model is proposed to map the relationship between spatio-temporal data and reservoir pressure. The proposed deep learning method is verified by using a three-dimensional reservoir model, and compared with commonly-used methods. The results show that the stacked GRU model has a better performance and higher accuracy than other deep learning or machine learning methods in pressure prediction. © 2023 IEEE.

关键词： Forecasting

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Highly stable and wide-range flexible pressure sensors with a gradient modulus and selective foaming layer

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Chemical Engineering Journal 2025年 515卷

作者： Wang, Meng Li, Wendong Lv, Yadong Li, Guangxian Zhao, Zhijun Wang, Yaobing Zhou, Qinghua Pu, Wei Kong, Miqiu School of Aeronautics and Astronautics Key Laboratory of Advanced Spatial Mechanism and Intelligent Spacecraft Ministry of Education National Key Laboratory of Advanced Polymer Materials Sichuan University Chengdu610065 China College of Polymer Science and Engineering National Key Laboratory of Advanced Polymer Materials Sichuan University Chengdu610065 China Beijing Key Laboratory of Intelligent Space Robotic Systems Technology and Applications Beijing Institute of Spacecraft System Engineering Beijing100094 China

The service life and stability of flexible pressure sensors vary with the interfacial toughness of these multilayered structures, which are principally fabricated by adhesive bonding, hot melting, and interconnection. However, balancing the trade-off between interface toughness and sensing performance under complex stresses remains challenging. To address this issue, a foam sandwich structure with gradient modulus is constructed by integrating a thermoplastic polyurethane (TPU)/carbon nanotube electrode with a selectively foamed TPU/ionic liquid dielectric. The synthesis is fundamentally inspired by the molecular chain entanglements and hydrogen bonds formed at the electrode/dielectric interface owing to solvent diffusion due to secondary solubilization and differential foaming temperatures. The synthesized sensing structure exhibits ultra-high toughness (3000 J/m2) and dynamic impact resistance (1 J);meanwhile, the sensor shows an ultra-wide sensing range (0.02–2000 kPa), high sensitivity (1.7 nF/kPa), and excellent service stability up to 50,000 cycles under compressive stress (100 kPa), shear stress (30 kPa), bending stress (bending radius of 1.6 mm), and complex stress of 120 kPa (compression stress of 116 kPa and shear stress of 31 kPa). Additionally, on integration into robot grippers, the sensor provides accurate feedback on multi-stage object gripping and can resist shear stress while gripping high-weight objects. This study provides a new strategy for fabricating flexible pressure sensors that can be effectively used under complex stresses. © 2025 Elsevier B.V.

关键词： Shear bands

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Text2Earth: Unlocking Text-driven Remote Sensing Image Generation with a Global-Scale Dataset and a Foundation Model

arXiv

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arXiv 2025年

作者： Liu, Chenyang Chen, Keyan Zhao, Rui Zou, Zhengxia Shi, Zhenwei The Department of Aerospace Intelligent Science and Technology School of Astronautics The State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing100191 China The Key Laboratory of Spacecraft Design Optimization and Dynamic Simulation Technologies Ministry of Education China Shanghai Artificial Intelligence Laboratory Shanghai200232 China Shen Yuan Honors College of Beihang University Beijing100191 China The Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore

Recently, generative foundation models have significantly advanced large-scale text-driven natural image generation and have become a prominent research trend across various vertical domains. However, in the remote sensing field, there is still a lack of research on large-scale text-to-image (text2image) generation technology. Existing remote sensing image-text datasets are small in scale and confined to specific geographic areas and scene types. Besides, existing text2image methods have struggled to achieve global-scale, multi-resolution controllable, and unbounded image generation. To address these challenges, this paper presents two key contributions: the Git-10M dataset and the Text2Earth foundation model. Git-10M is a global-scale image-text dataset comprising 10.5 million image-text pairs, 5 times larger than the previous largest one. The dataset contains essential resolution information and covers a wide range of geographic scenes and contains essential geospatial metadata, significantly surpassing existing datasets in both size and diversity. Building on Git-10M, we propose Text2Earth, a 1.3 billion parameter generative foundation model based on the diffusion framework to model global-scale remote sensing scenes. Text2Earth integrates a resolution guidance mechanism, enabling users to specify image resolutions. A dynamic condition adaptation strategy is proposed for training and inference to improve image generation quality. Text2Earth not only excels in zero-shot text2image generation but also demonstrates robust generalization and flexibility across multiple tasks, including unbounded scene construction, image editing, and cross-modal image generation. This robust capability surpasses previous models restricted to the basic fixed size and limited scene types. On the previous text2image benchmark dataset, Text2Earth outperfoms previous models with a significant improvement of +26.23 FID and +20.95% Zero-shot Cls-OA metric. Our project page is https://chen-y

关键词： Optical remote sensing

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Effects of gaseous nitrogen rotational relaxation on its low-pressure acoustic dispersion 27

Effects of gaseous nitrogen rotational relaxation on its low...

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27th International Congress on Sound and Vibration, ICSV 2021

作者： Guanwen, Sun Hanyin, Cui Chao, Li Weijun, Lin Xiaodong, Peng Xuchen, Shen Quan, Guo University of Chinese Academy of Sciences Beijing China Key Laboratory of Electronics and Information Technology for Space Systems CAS National Space Science Center CAS Beijing China National Institute of Natural Hazards Ministry of Emergency Management Beijing China

ISBN: (纸本)9788378807995

The gases in the upper atmosphere are thinner and the air pressure is lower. Under these conditions, sound waves exhibit frequency dispersion, which is associated with molecular relaxation. This phenomenon has a strong influence on the sound propagation in the upper atmosphere. We intend to study the effects of rotational relaxation of molecules in dilute nitrogen that also satisfies the continuous medium assumption on this dispersion phenomenon. Both experimental and numerical methods are used to study acoustic dispersion at low pressures. The experiments were carried out in a space simulator and measured the speed of sound of nitrogen at pressures of 200-105 Pa. The Navier-Stokes theory and the theory with internal degrees of freedom correction to them were used for comparison with the experimental data. In both experiments and numerical calculations, it can be concluded that the speed of sound increases with decreasing air pressure. Since only translational relaxation is considered, the Navier-Stokes equation predicts a speed of sound smaller than the experimental speed. In other words, the effect of rotational relaxation on low-pressure dispersion cannot be ignored. After correction for the rotational relaxation, the theoretical sound speed is more consistent with the experimental data. © "Advances in Acoustics, Noise and Vibration - 2021" Proceedings of the 27th International Congress on Sound and Vibration, ICSV 2021. All rights reserved.

关键词： Numerical methods

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Are Electric Vehicles Greener than Hybrid Electric Vehicles in Carsharing? Insights from Large-Scale Multi-Objective simulation-Optimization

SSRN

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SSRN 2024年

作者： Li, Yan Hu, Lu Li, Haobin Chew, Ek Peng Li, Hao Zhu, Juanxiu Department of Industrial Systems Engineering and Management National University of Singapore Singapore Centre of Excellence in Modelling and Simulation for Next Generation Ports National University of Singapore Singapore School of Transportation and Logistics Southwest Jiaotong University Chengdu China School of Traffic and Transportation Engineering Changsha University of Science and Technology Changsha China Hunan Key Laboratory of Smart Roadway and Cooperative Vehicle Infrastructure Systems Changsha University of Science and Technology Changsha China School of Management Xihua University Chengdu China

Hybrid electric vehicles (HEVs) are perceived as transitional products bridging the gap between fueled vehicles and electric vehicles (EVs) because people intuitively believe that EVs are more environmentally friendly than HEVs. But is this perception true in the context of carsharing services (CSSs)? This paper pioneers a general large-scale multi-objective simulation-optimization (MOSO) method to explore the values of deploying HEVs in CSSs. We firstly develop a physically logical simulation model, emulating operations of CSSs and capturing mesoscopic dynamics of shared vehicles in a link-based traffic network. This model adopts an event-driven discrete-event mechanism, enhancing efficiency while maintaining high fidelity. Subsequently, we design a simulation-optimization framework aimed at achieving Pareto optimality by jointly optimizing station capacity, fleet size, and trip pricing. The goal is twofold: to maximize operational profits and to minimize carbon emissions, thereby quantitatively analysing the potential of shared HEVs (SHEVs). To tackle the high-dimensional MOSO problem, we propose a general algorithm that incorporates the multiple gradient descent algorithm with the simultaneous perturbation stochastic approximation algorithm. Furthermore, we derive its analytical expression for bi-objective optimization problems. We theoretically prove and practically demonstrate its strong global convergence. The efficiency of this method was validated through large-scale computational experiments conducted in Chengdu, Sichuan Province, involving 66,710 decision variables. These experiments showcased the method's superiority over existing MOSO algorithms. Several groups of sensitivity experiments focusing on vehicle types and traffic scenarios reveal some interesting findings. (1) Regardless of the increase in travel distances, SHEVs, which can be viewed as shared EVs (SEVs) without range anxiety (RA), continue to primarily rely on electricity rather than fuel fo

关键词： Stochastic systems

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Exploring the effects of phase modulation on the dynamics of the kicked rotor systems

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Physical Review E 2022年第1期105卷 014212-014212页

作者： Mengyao Li Yingying Xiao Yongchun Tao Yi Gao Peiqing Tong Center for Quantum Transport and Thermal Energy Science Jiangsu Key Lab on Opto-Electronic Technology School of Physics and Technology Nanjing Normal University Nanjing 210023 China School of Physics and Technology Jiangsu Key Laboratory for Numerical Simulation of Large Scale Complex Systems Nanjing Normal University Nanjing 210023 China

Inspired by the recent experimental progress in the time-driven phase transition in quantum chaos, we investigate comprehensively the energy diffusion of a kicked rotor in the presence of phase modulation. In the classical case, we found that there always exists anomalous diffusion as long as the phase is modulated periodically and changes by 0 or π from kick to kick. On the contrary, for quasiperiodic and random phase modulation, anomalous diffusion is suppressed. On the other hand, in the quantum case, there exist only ballistic energy diffusion and dynamical localization in the standard and periodically shifted cases, while random phase modulation destroys the quantum coherence and totally suppresses the dynamical localization. Furthermore, the quasiperiodic phase modulation is an intermediate phase between the standard case and the random one. In both the classical and quantum cases, quasiperiodic phase modulation is inequivalent to random phase modulation at large kicking times (>103), thus caution has to be taken when dealing with these two kinds of phase modulation in experiments.

关键词： Cold atoms & matter waves 1-dimensional systems

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Snapshot Compressed Sensing Computed-Tomography Imaging Spectromety

SSRN

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SSRN 2023年

作者： Li, Hu Liu, Xue-Feng Yao, Xu-Ri Wang, Xiao-Qing Zhai, Guang-Jie Key Laboratory of Electronics and Information Technology for Space Systems National Space Science Center Chinese Academy of Sciences Beijing Beijing100190 China Laboratory of Satellite Mission Operation National Space Science Center Chinese Academy of Sciences Beijing Beijing100190 China School of Physics Beijing Institute of Technology Beijing Beijing100081 China University of Chinese Academy of Sciences Beijing Beijing100149 China Beijing Academy of Quantum Information Sciences Beijing Beijing100193 China

Computed-tomography imaging spectrometry (CTIS) can achieve non-scanning and high speed imaging recording of spatial and spectral data of a rapidly changing target scene. However, it has the problem of missing cone, which means the projection data cannot be fully sampled. This limits its practicality due to the ill-posed spectral reconstruction from limited angles of projection tomography. This paper proposes a compressed sensing (CS) sampling model for the CTIS, or CSCTIS in short, with the under sampling advantage of CS to improve the problem. The simulation results validates that the CS model is more effective than the traditional computed-tomography (CT) one, and further experimental results prove that the CSCTIS performs more accurate spectral reconstruction than the traditional CTIS. © 2023, The Authors. All rights reserved.

关键词： Compressed sensing

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A Nonresonant Hybridized Electromagnetic-Triboelectric Nanogenerator for Irregular and Ultralow Frequency Blue Energy Harvesting

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Research 2021年第1期2021卷 304-315页

作者： Weibo Xie Lingxiao Gao Lingke Wu Xin Chen Fayang Wang Daqiao Tong Jian Zhang Jianyu Lan Xiaobin He Xiaojing Mu Ya Yang State Key Laboratory of Mechanical Transmissions Chongqing UniversityChongqing 400044China Key Laboratory of Optoelectronic Technology&Systems Ministry of Education International R&D Center of Micro-Nano Systems and New Materials TechnologyChongqing UniversityChongqing 400044China CAS Center for Excellence in Nanoscience Beijing Key Laboratory of Micro-Nano Energy and SensorBeijing Institute of Nanoenergy and NanosystemsChinese Academy of SciencesBeijing 100083China College of Aerospace Engineering Chongqing UniversityChongqing 400044China Shanghai Academy of Spaceflight Technology Shanghai Institute of Space Power SourceShanghai 200245China School of Nanoscience and Technology University of Chinese Academy of SciencesBeijing 100049China Center on Nanoenergy Research School of Physical Science and TechnologyGuangxi UniversityNanningGuangxi 530004China

As a promising renewable energy source,it is a challenging task to obtain blue energy,which is irregular and has an ultralow frequency,due to the limitation of ***,a nonresonant hybridized electromagnetic-triboelectric nanogenerator was presented to efficiently obtain the ultralow frequency *** instrument adopted the flexible pendulum structure with a precise design and combined the working principle of electromagnetism and triboelectricity to realize the all-directional vibration energy acquisition *** results confirmed that the triboelectric nanogenerator(TENG)had the potential to deliver the maximum power point of about 470μW while the electromagnetic nanogenerator(EMG)can provide 523 mW at *** conversion efficiency of energy of the system reached 48.48%,which exhibited a remarkable improvement by about 2.96 times,due to the elastic buffering effect of the TENG with the double helix ***,its ability to collect low frequency wave energy was successfully proven by a buoy in Jialing *** woke provides an effective candidate to harvest irregular and ultralow frequency blue energy on a large scale.

关键词： generator precise instrument

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A THz Single-Pole Four-Throw Switch Based on Microstrip Power Divider for Satellite Communication

A THz Single-Pole Four-Throw Switch Based on Microstrip Powe...

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Cross Strait Quad-Regional Radio science and Wireless technology Conference (CSRWTC)

作者： Yuanzhi He Chensheng Ma Xiaojun Li Zhongbo Zhu Caixia Wang Institute of Systems Engineering Academy of Military Sciences Beijing China National Key Laboratory of Science and Technology on Space Microwave CAST(Xi'an) Xi'an China

With the rapid development of terahertz technology, its application in satellite communication has become one of the hot topics in 6G research. Single-pole multi-throw switch is an important part of the control circuit in satellite communication load. This paper presents a terahertz single-pole four-throw switching circuit based on microstrip power divider. simulation results show that low insertion loss and high channel isolation are achieved by using the structure of serial-parallel loaded spiral inductor. The switch designed in this paper is small in size and light in weight, which is easy to be integrated into other terahertz functional components, and is conducive to the lightweight and miniaturization of satellite communication load.

关键词： Power dividers Wireless communication Spirals simulation Switches Insertion loss Microstrip

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