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Effects of Operation Parameters on Heat Transfer in Tubular Moving Bed Heat Exchangers:A CFD-DEM Study

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Journal of Thermal Science 2025年第02期 542-554页

作者： LU Weiqin LI Zhihan TANG Xueyu LIU Dinghe KE Xiwei ZHOU Tuo key laboratory for Thermal Science and power engineering of Ministry of Education Department of Energy and Power EngineeringTsinghua University School of Transportation and Vehicle engineering Shandong University of Technology College of electrical and power engineering Taiyuan University of Technology

Tubular moving bed heat exchangers（MBHEs） present inherent advantages for efficiently and stably recovering sensible heat from high-temperature granular *** this study,we introduce a viable and practical approach based on the combined approach of Computational Fluid Dynamics with Discrete Element Method（CFD-DEM） and employ it to conduct a comprehensive investigation into the effects of operation parameters on tubular *** parameters include inlet particle temperature（ranging from 500℃ to 700℃）,tube wall temperature（ranging from 50℃ to 250℃）,and particle descent velocity（ranging from 0.5 mm/s to 12 mm/s）.Our analysis reveals that the heat radiation and gas film heat conduction predominantly govern the heat transfer process in the particle-fluid-wall system,collectively contributing to approximately 90% of the total heat flux of tube wall(Qwsimu).The results indicate that increasing the inlet particle temperature and reducing the tube wall temperature intensify heat transfer by enlarging the temperature *** interestingly,Qwsimuexhibits three distinct stages as particle descent velocity increases,including an ascent stage,a descent stage,and a stable ***,the simulation attempts suggest that the optimal descent velocity for maximizing Qwsimufalls within the range of 1.3-2.0 mm/*** findings not only uncover the precise influence mechanisms of operation parameters on heat transfer outcomes but also offer valuable insights for heat transfer enhancement efficiency in MBHE system.

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Two-Stage Scheduling Model for Flexible Resources in Active Distribution Networks Based on Probabilistic Risk Perception

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Energy engineering 2025年第2期122卷 681-707页

作者： Yukai Li Ruixue Zhang Yongfeng Ni Hongkai Qiu Yuning Zhang Chunming Liu Beijing Kedong power Control system Co. Ltd.State Grid Electric Power Research InstituteBeijing100192China School of electrical and Electronic engineering North China Electric Power UniversityBeijing102206China

Aiming at the problems of increasing uncertainty of low-carbon generation energy in active distribution network(ADN)and the difficulty of security assessment of distribution network,this paper proposes a two-phase scheduling model for flexible resources in ADN based on probabilistic risk ***,a full-cycle probabilistic trend sequence is constructed based on the source-load historical data,and in the day-ahead scheduling phase,the response interval of the flexibility resources on the load and storage side is optimized based on the probabilistic trend,with the probability of the security boundary as the security constraint,and with the economy as the *** in the intraday phase,the core security and economic operation boundary of theADNis screened in real ***,it quantitatively senses the degree of threat to the core security and economic operation boundary under the current source-load prediction information,and identifies the strictly secure and low/high-risk time *** resources within the response interval are dynamically adjusted in real-time by focusing on high-risk periods to cope with future core risks of the distribution ***,the improved IEEE 33-node distribution system is simulated to obtain the flexibility resource scheduling scheme on the load and storage *** results are evaluated from the perspectives of risk probability and flexible resource utilization efficiency,and the analysis shows that the scheduling model in this paper can promote the consumption of low-carbon energy from wind and photovoltaic sourceswhile reducing the operational risk of the distribution network.

关键词： Core operation boundary probabilistic power flow risk perception optimize scheduling flexible resource

Achieving an Accurate Random Process Model for PV power Using Cheap Data:Leveraging the SDE and Public Weather Reports

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CSEE Journal of power and Energy systems 2025年第1期11卷 124-135页

作者： Yiwei Qiu Jin Lin Zhipeng Zhou Ningyi Dai Feng Liu Yonghua Song College of electrical engineering Sichuan UniversityChengdu610065China state key laboratory of the Control and Simulation of power systems and Generation Equipment Tsinghua UniversityBeijing 100087China state key laboratory of Internet of Things for Smart City University of MacaoMacao999078China department of electrical engineering Tsinghua UniversityBeijing100087China

Stochastic differential equation (SDE)-based random process models of renewable energy sources (RESs) jointly capture evolving probability distribution and temporal correlation in continuous time. It enabled recent studies to remarkably improve performance of power system dynamic uncertainty quantification and optimization. However, considering the non-homogeneous random process nature of PV, there still remains a challenging question: how can a realistic and accurate daily SDE model for PV power be obtained that reflects its weather-dependent and non-Gaussian uncertainty in operation, especially when high-resolution numerical weather prediction (NWP) or sky imager is unavailable for many distributed plants? To fill this gap, this article finds that an accurate SDE model for PV power can be constructed only using the data from low-resolution public weather reports. Specifically, for each day, an hourly parameterized Jacobi diffusion process recreates temporal patterns of PV volatility. Its parameters are mapped from the day's public weather reports to reflect varying weather conditions using a simple learning model. The SDE model jointly captures intraday and intrahour volatility. Statistical examination shows that the proposed approach outperforms a selection of the latest deep learning-based time series models on real-world data collected in Macao.

关键词： Photovoltaic(PV)power random process stochastic differential equation(SDE) stochastic optimization time series modeling uncertainty quantification weather report.

Automatic and Rapid Throughflow-Based Optimal Design Method for Multi-Stage Axial-Flow Compressors

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Journal of Thermal Science 2025年第1期34卷 77-91页

作者： LEI Fan ZHANG Xiawen JU Yaping ZHANG Chuhua department of Fluid Machinery and engineering School of Energy and Power EngineeringXi'an Jiaotong UniversityXi'an 710049China state key laboratory for Strength and Vibration of Mechanical Structures Xi'an Jiaotong UniversityXi'an 710049China Production and Environmental department China Huaneng Group.Co.Ltd.Beijing 100031China

Throughflow design has the advantages of less time consumption and large optimization space,and thus is the corner stone of advanced design system of multi-stage axial-flow *** majority of relevant studies were limited to the throughflow inverse designs,and quite few works have been till now devoted to the throughflow optimal *** this work,an automatic and rapid throughflow-based optimal design method is proposed for axial-flow compressors in which a throughflow inverse design solver is embedded in optimal genetic algorithm to improve the design efficiency of axial-flow *** types of design parameters in the throughflow inverse design of axial-flow compressors,i.e.,swirl and shroud curve,are simultaneously used to optimize both the blade shape and flow *** proposed method is validated by the redesign optimization of the benchmark axial-flow compressor NASA Stage 35,and the CFD predictions show that the throughflow-based optimization leads to 1.18% efficiency benefit at design *** proposed method is then utilized to the two-dimensional throughflow optimal design of a large-scale 6.5-stage axial-flow industrial *** optimal design results are confirmed by CFD predictions,indicating that the proposed method can effectively improve the design adiabatic efficiency of the compressors by 1.09% within a few minutes on desk-top *** throughflow design implications are also obtained for advanced axial-flow industrial *** work could enhance the capability of throughflow design method and has engineering application value to explore the throughflow optimization space of multi-stage axial-flow compressors.

关键词： multi-stage axial-flow compressor throughflow design empirical correlations genetic algorithm aerodynamic optimization

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Interference Suppression and Jitter Elimination Ability-Based Adaption Tracking Guidance for Robotic Fishes

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 126-137页

作者： Dongfang Li Jie Huang Rob Law Xin Xu Limin Zhu Edmond Q.Wu IEEE the School of electrical engineering and Automation Fuzhou University the key laboratory of system Control and Information Processing Ministry of Education the School of electrical engineering and Automation Fuzhou University 5G+Industrial Internet Institute Fuzhou University the University of Macau the College of Mechatronics and Automation National University of Defense Technology the School of Mechanical engineering Shanghai Jiao Tong University the department of Computer Science and engineering Shanghai Jiao Tong University

This work presents an adaptive tracking guidance method for robotic fishes. The scheme enables robots to suppress external interference and eliminate motion jitter. An adaptive integral surge line-of-sight guidance rule is designed to eliminate dynamics interference and sideslip issues. Limited-time yaw and surge speed observers are reported to fit disturbance variables in the model. The approximation values can compensate for the system's control input and improve the robots' tracking ***, this work develops a terminal sliding mode controller and third-order differential processor to determine the rotational torque and reduce the robots' run jitter. Then, Lyapunov's theory proves the uniform ultimate boundedness of the proposed method. Simulation and physical experiments confirm that the technology improves the tracking error convergence speed and stability of robotic fishes.

关键词： Adaptive integral surge line-of-sight approximation robotic fish speed observer

Tailoring BaCe0.7Zr0.1(Dy0.1|Yb0.1)0.2O3-δ electrolyte through strategic Cu doping for low temperature proton conducting fuel cells:Envisioned theoretically and experimentally

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Journal of Energy Chemistry 2025年第2期101卷 692-701页

作者： Zaheer Ud Din Babar Muhammad Bilal Hanif Yan'an Li Wan-Ting Wang Hanchen Tian Cheng-Xin Li state key laboratory for Mechanical Behavior of Materials School of Materials Science and Engineering Xi'an Jiaotong University department of Inorganic Chemistry Faculty of Natural Sciences Comenius University Bratislava

This study addresses the challenge of high sintering temperatures in proton-conducting fuel cells（PCFCs）with BaCeO3-doped *** demonstrate that 1 mol% copper（Cu） doping at the B-site of BaCe0.7Zr0.1(Dy0.1|Yb0.1)0.2O3-δ（BCZDYb） improves sintering behavior,enabling densification at1400℃.However,Cu doping disrupts stoichiometry,creating barium vacancies and reducing protonaccepting cations,affecting overall *** mechanism is confirmed through density functional theory（DFT） calculations and various experimental techniques,including crystal structure analysis using X-ray diffraction（XRD） and morphology and elemental analysis via field emission scanning electron microscopy（FESEM） and energy-dispersive X-ray spectroscopy（EDS）.Electrochemical measurements are performed using the electrochemical impedance spectroscopy（EIS）.The ionic conductivity of1 mol% Cu-doped BCZDYb（BCZDYb-1） is 1.49×10-2S cm-1at 650℃,which is～3.58 times higher than that of BCZDYb sintered at 1200℃.The BCZDYb-1 exhibits ～16 times higher grain boundary conductivity when sintered at 1400℃,compared to undoped *** single cell employing BCZDYb-1 as the electrolyte achieved a power density of ～606 mW cm-2at 550℃.These results indicate that a controlled amount of Cu doping can enhance densification while maintaining high ionic co nductivity,making it suitable for practical applications in PCFCs operating at lower temperatures.

关键词： BaCe0.7Zr0.1(Dy0.1|Yb0.1)0.2O3−δ (BCZDYb) Cu-doping Densification electrical conductivity Proton conducting fuel cells (PCFCs) Sintering

Physics-informed battery degradation prediction:Forecasting charging curves using one-cycle data

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Journal of Energy Chemistry 2025年第2期101卷 825-836页

作者： Aihua Tang Yuchen Xu Jinpeng Tian Xing Shu Quanqing Yu key laboratory of Advanced Manufacturing Technology for Automobile Parts Ministry of Education Chongqing University of Technology department of electrical and Electronic engineering and Research Centre for Grid Modernization The Hong Kong Polytechnic University School of Automotive engineering Harbin Institute of Technology

Accurately predicting battery degradation is crucial for battery system ***,due to the complexities of aging mechanisms and limitations of historical data,comprehensively indicating battery degradation solely through maximum capacity loss assessment is *** machine learning offers promising solutions,it often overlooks domain knowledge,resulting in reduced accu racy,increased computational burden and decreased ***,this study proposes a method to predict the voltage-capacity（V-Q） curve during battery degradation with limited historical *** process is achieved through two physically interpretable components:a lightweight interpretable physical model and a physics-informed neural *** components incorporate domain knowledge into machine learning to improve V-Q curve prediction performance and enhance *** validation was conducted on 52 batteries of different types under different testing *** proposed method can accurately predict future *** for hundreds of cycles using only one-present-cycle V-Q curve,with root mean square error and mean absolute error basically less than 0.035 Ah and R2basically less than 98.5%.This means that incremental capacity curves can be extracted from the predicted results for a more comprehensive and accurate battery degradation ***,the method can flexibly adjust prediction length and density to cater to the practical needs of long-cycle prediction and data *** study provides a viable method for rapid degradation prediction and is expected to be generalized to in-vehicle implementations.

关键词： Degradation prediction Lightweight interpretable physical model Lithium-ion battery Physics-informed neural network Voltage-capacity curve

Controllability of heterogeneous networked sampled-data systems

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Science China(Information Sciences) 2025年第03期68卷 302-318页

作者： Zixuan YANG Lin WANG Xiaofan WANG Guanrong CHEN department of Automation Shanghai Jiao Tong University key laboratory of system Control and Information Processing Ministry of Education of China School of Mechatronic engineering and Automation Shanghai University School of electrical and Electronic engineering Shanghai Institute of Technology department of electrical engineering City University of Hong Kong

This study investigates the controllability of a general heterogeneous networked sampled-data system(HNSS) consisting of nonidentical node systems, where the inner coupling between any pair of nodes can be described by a unique *** signals on control and transmission channels are sampled and held by zero-order holders, and the control sampling period of each node can be different. Necessary and sufficient controllability conditions are developed for the general HNSS, using the Smith normal form and matrix equations, respectively. The HNSS in specific topology or dynamic settings is discussed subsequently with easier-to-verify conditions derived. These heterogeneous factors have been determined to independently or jointly affect the controllability of networked sampled-data systems. Notably, heterogeneous sampling periods have the potential to enhance the overall controllability, but not for systems with some special dynamics. When the node dynamics are heterogeneous,the overall system can be controllable even if it is topologically uncontrollable. In addition, in several typical heterogeneous sampled-data multi-agent systems, pathological sampling of single-node systems will necessarily cause overall uncontrollability.

关键词： network controllability sampled-data system heterogeneous system inner coupling multi-agent system

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Achievable Rate Analysis and Optimization of Double-RIS Assisted Spatially Correlated MIMO with Statistical CSI

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China Communications 2025年第1期22卷 139-157页

作者： Xu Kaizhe Guo Jiajia Zhang Jun Jin Shi Ma Shaodan department of Communications and Networking Xi’an Jiaotong-Liverpool UniversitySuzhou 215123China state key laboratory of Internet of Things for Smart City University of MacaoMacao SARChina Jiangsu key laboratory of Wireless Communications Nanjing University of Posts and TelecommunicationsNanjing 210003China National Mobile Communications Research laboratory Southeast UniversityNanjing 210096China state key laboratory of Internet of Things for Smart City and the department of electrical and Computer engineering University of MacaoMacao SARChina

Reconfigurable intelligent surface(RIS)is a novel meta-material which can form a smart radio environment by dynamically altering reflection directions of the impinging electromagnetic *** the prior literature,the inter-RIS links which also contribute to the performance of the whole system are usually neglected when multiple RISs are *** this paper we investigate a general double-RIS assisted multiple-input multiple-output(MIMO)wireless communication system under spatially correlated non line-of-sight propagation channels,where the cooperation of the double RISs is also *** design objective is to maximize the achievable ergodic rate based on full statistical channel state information(CSI).Specifically,we firstly present a closedform asymptotic expression for the achievable ergodic rate by utilizing replica method from statistical *** a full statistical CSI-enabled optimal design is proposed which avoids high pilot training overhead compared to instantaneous CSI-enabled *** further reduce the signal processing overhead and lower the complexity for practical realization,a common-phase scheme is proposed to design the double *** results show that the derived asymptotic ergodic rate is quite accurate even for small-sized antenna *** the proposed optimization algorithm can achieve substantial gain at the expense of a low overhead and ***,the cooperative double-RIS assisted MIMO framework is proven to achieve superior ergodic rate performance and high communication reliability under harsh propagation environment.

关键词： common reflection pattern double RISs large system analysis MIMO replica method

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