检索结果-南通市图书馆

Control Policy Learning Design for Vehicle Urban Positioning via BeiDou Navigation

在线全文

学校读者我要写书评

暂无评论

Journal of Systems Science & Complexity 2024年第1期37卷 114-135页

作者： QIN Yahang ZHANG chengye chen Ci XIE Shengli LEWIS frank L School of Automation Guangdong University of TechnologyGuangzhou 510006China Guangdong Key Laboratory of IoT Information Technology Guangzhou 510006China. Center for Intelligent Batch Manufacturing Based on IoT Technology Key Laboratory of Intelligent Detection and The Internet of Things in Manufacturing Ministry of EducationGuangzhou 510006China Guangdong-HongKong-Macao Joint Laboratory for Smart Discrete Manufacturing Guangzhou 510006China Key Laboratory of Intelligent Information Processing and System Integration of IoT Ministry of EducationGuangzhou 510006China. UTA Research Institute The University of Texas at ArlingtonFort WorthTX 76019USA

This paper presents a learning-based control policy design for point-to-point vehicle positioning in the urban environment via BeiDou *** navigating in urban canyons,the multipath effect is a kind of interference that causes the navigation signal to drift and thus imposes severe impacts on vehicle localization due to the reflection and diffraction of the BeiDou ***,the authors formulated the navigation control system with unknown vehicle dynamics into an optimal control-seeking problem through a linear discrete-time system,and the point-to-point localization control is modeled and handled by leveraging off-policy reinforcement learning for feedback *** proposed learning-based design guarantees optimality with prescribed performance and also stabilizes the closed-loop navigation system,without the full knowledge of the vehicle *** is seen that the proposed method can withstand the impact of the multipath effect while satisfying the prescribed convergence rate.A case study demonstrates that the proposed algorithms effectively drive the vehicle to a desired setpoint under the multipath effect introduced by actual experiments of BeiDou navigation in the urban environment.

关键词： BeiDou navigation multipath effect prescribed convergence rate reinforcement learning urban localization.

Multi-population particle swarm optimization algorithm for automatic design of steel frames

在线全文

学校读者我要写书评

暂无评论

Frontiers of Structural and Civil Engineering 2024年第1期18卷 89-103页

作者： Wenchen SHAN Jiepeng LIU Yao DING Y.frank chen Junwen ZHOU Institute of Smart City and Intelligent Transportation Southwest Jiaotong UniversityChengdu 610000China School of Civil Engineering Chongqing UniversityChongqing 400045China Department of Civil Engineering the Pennsylvania State UniversityMiddletownPA 17057USA

Steel structures are widely used;however,their traditional design method is a trial-and-error procedure which is neither efficient nor cost ***,a multi-population particle swarm optimization(MPPSO)algorithm is developed to optimize the weight of steel frames according to standard design *** are made to improve the algorithm performances including the constraint-based strategy,piecewise mean learning strategy and multi-population cooperative *** proposed method is tested against the representative frame taken from American standards and against other steel frames matching Chinese design *** related parameter influences on optimization results are *** the representative frame,MPPSO can achieve greater efficiency through reduction of the number of analyses by more than 65% and can obtain frame with the weight for at least 2.4%lighter.A similar trend can also be observed in cases subjected to Chinese design *** addition,a migration interval of 1 and the number of populations as 5 are recommended to obtain better MPPSO *** purpose of the study is to propose a method with high efficiency and robustness that is not confined to structural scales and design *** aims to provide a reference for automatic structural optimization design problems even with dimensional *** proposed method can be easily generalized to the optimization problem of other structural systems.

关键词： steel frame multi-population particle swarm optimization automatic structural optimization design

Application of machine learning in perovskite materials and devices:A review

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Energy Chemistry 2024年第7期94卷 254-272页

作者： Ming chen Zhenhua Yin Zhicheng Shan Xiaokai Zheng Lei Liu Zhonghua Dai Jun Zhang Shengzhong(frank)Liu Zhuo Xu School of Electric Power Civil Engineering and ArchitectureCollege of Physics and Electronics EngineeringState Key Laboratory of Quantum Optics and Quantum Optics DevicesShanxiUniversityTaiyuan030006ShanxiChina Key Laboratory of Applied Surface and Colloid Chemistry National Ministry of EducationShanxi Engineering Lab for Advanced Energy TechnologySchool of Materials Science and EngineeringShaanxi Normal UniversityXi'an 710119ShaanxiChina State Key Laboratory of Catalysis Dalian National Laboratory for Clean EnergyDalian Institute of Chemical PhysicsChinese Academy of SciencesDalian 116023LiaoningChina

Metal-halide hybrid perovskite materials are excellent candidates for solar cells and photoelectric *** recent years,machine learning(ML)techniques have developed rapidly in many fields and provided ideas for material discovery and *** can be applied to discover new materials quickly and effectively,with significant savings in resources and time compared with traditional experiments and density functional theory(DFT)*** this review,we present the application of ML in per-ovskites and briefly review the recent works in the field of ML-assisted perovskite ***,the advantages of perovskites in solar cells and the merits of ML applied to perovskites are ***,the workflow of ML in perovskite design and some basic ML algorithms are ***,the applications of ML in predicting various properties of perovskite materials and devices are ***,we propose some prospects for the future development of this *** rapid devel-opment of ML technology will largely promote the process of materials science,and ML will become an increasingly popular method for predicting the target properties of materials and devices.

关键词： Machine learning Perovskite Materials design Bandgap engineering Stability Crystal structure

A PI+R Control Scheme Based on Multi-Agent Systems for Economic Dispatch in Isolated BESSs

在线全文

学校读者我要写书评

暂无评论

IEEE/CAA Journal of Automatica Sinica 2024年第10期11卷 2154-2165页

作者： Yalin Zhang Zhongxin Liu Zengqiang chen College of Artificial Intelligence Nankai UniversityTianjin 300350 Tianjin Key Laboratory of Interventional Brain-Computer Interface and Intelligent Rehabilitation Nankai UniversityTianjin 300350China IEEE

Battery energy storage systems(BESSs)are widely used in smart ***,power consumed by inner impedance and the capacity degradation of each battery unit become particularly severe,which has resulted in an increase in operating *** general economic dispatch(ED)algorithm based on marginal cost(MC)consensus is usually a proportional(P)controller,which encounters the defects of slow convergence speed and low control *** order to solve the distributed ED problem of the isolated BESS network with excellent dynamic and steady-state performance,we attempt to design a proportional integral(PI)controller with a reset mechanism(PI+R)to asymptotically promote MC consensus and total power mismatch towards 0 in this *** be frank,the integral term in the PI controller is reset to 0 at an appropriate time when the proportional term undergoes a zero crossing,which accelerates convergence,improves control accuracy,and avoids *** eigenvalues of the system under a PI+R controller is well analyzed,ensuring the regularity of the system and enabling the reset *** ensure supply and demand balance within the isolated BESSs,a centralized reset mechanism is introduced,so that the controller is distributed in a flow set and centralized in a jump *** cope with Zeno behavior and input delay,a dwell time that the system resides in a flow set is *** on this,the system with input delays can be reduced to a time-delay free *** the capacity limitation of the battery,a modified MC scheme with PI+R controller is *** correctness of the designed scheme is verified through relevant simulations.

关键词： Battery energy storage system(BESS) distributed control economic dispatch multi-agent system reset control

Learning the continuous-time optimal decision law from discrete-time rewards

在线全文

学校读者我要写书评

暂无评论

National Science Open 2024年第5期3卷 130-147页

作者： Ci chen Lihua Xie Kan Xie frank Leroy Lewis Yilu Liu Shengli Xie School of Automation Guangdong University of TechnologyGuangdong Key Laboratory of IoT Information Technology Key Laboratory of Intelligent Information Processing and System Integration of IoT Ministry of Education School of Electrical and Electronic Engineering Nanyang Technological University 111 Center for Intelligent Batch Manufacturing Based on IoT Technology UTA Research Institute the University of Texas at Arlington Department of Electrical Engineering and Computer Science University of Tennessee Oak Ridge National Laboratory Guangdong-HongKong-Macao Joint Laboratory for Smart Discrete Manufacturing

The concept of reward is fundamental in reinforcement learning with a wide range of applications in natural and social sciences. Seeking an interpretable reward for decision-making that largely shapes the system's behavior has always been a challenge in reinforcement learning. In this work, we explore a discrete-time reward for reinforcement learning in continuous time and action spaces that represent many phenomena captured by applying physical laws. We find that the discrete-time reward leads to the extraction of the unique continuous-time decision law and improved computational efficiency by dropping the integrator operator that appears in classical results with integral rewards. We apply this finding to solve output-feedback design problems in power systems. The results reveal that our approach removes an intermediate stage of identifying dynamical models. Our work suggests that the discrete-time reward is efficient in search of the desired decision law, which provides a computational tool to understand and modify the behavior of large-scale engineering systems using the optimal learned decision.

关键词： continuous-time state and action decision law learning discrete-time reward dynamical systems reinforcement learning

Study on thermal decomposition kinetics of azobenzene-4,4′-dicarboxylic acid by using compensation parameter method and nonlinear fitting evaluation

在线全文

学校读者我要写书评

暂无评论

Chinese Journal of Chemical Engineering 2024年第6期70卷 269-279页

作者： Shuyi Shen Song Guo Sining chen Jinhua Zhao Nanjing University of Science&Technology Nanjing 210094China China Academy of Safety Science and Technology Beijing 100012China

Recently,azobenzene-4,4'-dicarboxylic acid(ADCA)has been produced gradually for use as an organic synthesis or pharmaceutical intermediate due to its eminent *** large quantities put into application in the future,the thermal stability of this substance during storage,transportation,and use will become quite ***,in this work,the thermal decomposition behavior,thermal decomposition kinetics,and thermal hazard of ADCA were *** were conducted by using a SENSYS evo DSC device.A combination of differential iso-conversion method,compensation parameter method,and nonlinear fitting evaluation were also used to analyze thermal kinetics and mechanism of ADCA *** results show that when conversion rate α increases,the activation energies of ADCA's first and main decomposition peaks *** amount of heat released during decomposition varies between 182.46 and 231.16 J·g^(-1).The proposed kinetic equation is based on the Avrami-Erofeev model,which is consistent with the decomposition *** the frank-Kamenetskii model,a calculated self-accelerating decomposition temperature of 287.0℃is obtained.

关键词： Azobenzene-4,4′-dicarboxylic acid Thermal decomposition behavior Kinetic mechanism Thermal hazard evaluation Compensation parameter effect

Molecular insights into oil detachment from hydrophobic quartz surfaces in clay-hosted nanopores during steam-surfactant co-injection

在线全文

学校读者我要写书评

暂无评论

Petroleum Science 2024年第4期21卷 2457-2468页

作者： Ben-Jie-Ming Liu Xuan-Tong Lei Mohammadali Ahmadi Zhangxin chen Department of Chemical and Petroleum Engineering University of Calgary Eastern Institute of Technology

Thermal recovery techniques for producing oil sands have substantial environmental impacts. Surfactants can efficiently improve thermal bitumen recovery and reduce the required amount of steam. Such a technique requires solid knowledge about the interaction mechanism between surfactants, bitumen,water, and rock at the nanoscale level. In particular, oil sands ores have extremely complex mineralogy as they contain many clay minerals(montmorillonite, illite, kaolinite). In this study, molecular dynamics simulation is carried out to elucidate the unclear mechanisms of clay minerals contributing to the bitumen recovery under a steam-anionic surfactant co-injection process. We found that the clay content significantly influenced an oil detachment process from hydrophobic quartz surfaces. Results reveal that the presence of montmorillonite, illite, and the siloxane surface of kaolinite in nanopores can enhance the oil detachment process from the hydrophobic surfaces because surfactant molecules have a stronger tendency to interact with bitumen and quartz. Conversely, the gibbsite surfaces of kaolinite curb the oil detachment process. Through interaction energy analysis, the siloxane surfaces of kaolinite result in the most straightforward oil detachment process. In addition, we found that the clay type presented in nanopores affected the wettability of the quartz surfaces. The quartz surfaces associated with the gibbsite surfaces of kaolinite show the strongest hydrophilicity. By comparing previous experimental findings with the results of molecular dynamics(MD) simulations, we observed consistent wetting characteristics. This alignment serves to validate the reliability of the simulation outcomes. The outcome of this paper makes up for the lack of knowledge of a surfactant-assisted bitumen recovery process and provides insights for further in-situ bitumen production engineering designs.

关键词： Clay minerals Bitumen Contact angle Interaction energy Surfactant Molecular dynamics

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

含双腐蚀缺陷管道的氢浓度分布模拟

中国腐蚀与防护学报 2024年第2期44卷 335-344页

作者：郭诗雯吴浩志董绍华陈林程玉峰中国石油大学(北京)安全与海洋工程学院北京102249 中国石油大学(北京)应急管理部油气生产安全与应急技术重点实验室北京102249 Schulich School of Engineering University of CalgaryCalgary T2N 1N4

为了研究含双腐蚀缺陷管道上的氢浓度分布规律,本文建立了应力场和氢扩散场耦合的有限元模型,针对双腐蚀缺陷间的应力耦合行为,探究了腐蚀缺陷长度、缺陷间距以及管道所受拉伸应变对管材中氢扩散富集行为的影响机制。结果表明,腐蚀缺陷... 详细信息

为了研究含双腐蚀缺陷管道上的氢浓度分布规律,本文建立了应力场和氢扩散场耦合的有限元模型,针对双腐蚀缺陷间的应力耦合行为,探究了腐蚀缺陷长度、缺陷间距以及管道所受拉伸应变对管材中氢扩散富集行为的影响机制。结果表明,腐蚀缺陷的存在导致氢原子在管道内发生局部富集,富集区最大氢浓度数值随拉伸应变的增大和缺陷长度的减小而升高,同时,最大氢浓度位置发生改变。而双缺陷在间距足够大时不再对氢扩散和富集产生叠加影响,可看作两个独立的缺陷。研究成果为含双腐蚀缺陷管道在输氢环境中的安全评价提供了理论支撑。

关键词：双腐蚀缺陷氢分布有限元模拟 X52 管线钢

Modulating the alloying mode in the doping-induced synthesis of Au-Pd nanowires

在线全文

学校读者我要写书评

暂无评论

Nano Research 2024年第4期17卷 3334-3343页

作者： Hui Jin Xiaoliang Wei Lecheng Zhao Jialong Yu Qiao Pan Shumin Li Qian Wang Zhaotong Yuan Dan Yang Donghui Zhao Hongyu chen Yawen Wang Institute of Advanced Synthesis School of Chemistry and Molecular EngineeringJiangsu National Synergistic Innovation Center for Advanced MaterialsNanjing Tech UniversityNanjing 211816China School of Science Westlake UniversityHangzhou 310064China Institute of Natural Sciences Westlake Institute for Advanced StudyHangzhou 310064China

Heterogeneous doping is one effective strategy for synthesizing metal alloy ***,the heterogeneous doping processes of Pd on the ultrathin Au nanowires were systematically modulated and ***-Pd alloy nanowires with various morphologies and lattice structures can be obtained by adjusting the morphology of the precursor Au nanowires and the kinetics of the heterogeneous doping *** effects of the rate of Pd reduction and the concentration of the ligand oleylamine(OAm)on the Pd deposition and alloying mode were ***,as the Pd deposition rate decreases,the Pd deposition and alloying mode switches from the island-forming Stransky–Krastanov(SK)mode to the epitaxial frank-van der Merwe(FM)mode,and eventually to an unconventional twisting alloying mode,where the interdiffusion of Pd and Au causes drastic rearrangement of the lattice structure and formation of helical *** kinetics-related variation of alloying mode could also be observed in the Au-Ag nanowires,demonstrating a general design principle for the synthesis of alloy *** addition,the electrocatalytic performance of various Au-Pd nanowires was evaluated,and the alloy nanowire formed via the SK mode was found to be an excellent electrocatalyst for oxygen reduction and ethanol oxidation.

关键词： gold nanowires Au-Pd alloy oleylamine post-synthetic modification