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PHYSIC: 作品数：230被引量：335H指数：10; 导出分析报告; 相关领域：电子电信更多>>; 相关作者：翟清伟谢晓晖马坚伟马佼佼肖红勤更多>>; 相关机构：兖州煤业股份有限公司《现代音响技术》编辑部哈尔滨工业大学宝钢特钢有限公司更多>>; 相关期刊：更多>>; 相关基金：国家自然科学基金中国博士后科学基金瑞士科学基金国家重点基础研究发展计划更多>>

Wake field prediction of a wind farm based on a physics-informed neural network with different spatiotemporal prediction performance improvement strategies: 《Theoretical & Applied Mechanics Letters》2025年第2期141-153,共13页Junyong Song Lei Wang Zhiqiang Xin Hao Wang; supported by the National Natural Science Foundation of China(Grant Nos.12072105,11932006,and 52308498);the Natural Science Foundation of Jiangsu Province,China(Grant No.BK20220976).; Dynamic wake field information is vital for the optimized design and control of wind farms.Combined with sparse measurement data from light detection and ranging(LiDAR),the physics-informed neural network(PINN)framewo...; 关键词：Dynamic wake prediction LiDAR measurements Physics-informed neural network Accuracy improvement strategy Step-by-step time saving strategy

Simultaneous imposition of initial and boundary conditions via decoupled physics-informed neural networks for solving initialboundary value problems: 《Applied Mathematics and Mechanics(English Edition)》2025年第4期763-780,共18页K.A.LUONG M.A.WAHAB J.H.LEE; Project supported by the Basic Science Research Program through the National Research Foundation(NRF)of Korea funded by the Ministry of Science and ICT(No.RS-2024-00337001)。; Enforcing initial and boundary conditions(I/BCs)poses challenges in physics-informed neural networks(PINNs).Several PINN studies have gained significant achievements in developing techniques for imposing BCs in static...; 关键词：decoupled physics-informed neural network(dPINN) decoupled formulation Galerkin method initial-boundary value problem(IBVP) machine learning

Simulation of lubrication on rough surfaces with multiscale lubrication neural networks: 《Science China(Technological Sciences)》2025年第3期192-203,共12页Yihu TANG Li HUANG Limin WU Xianghui MENG; supported by the National Natural Science Foundation of China(Grant No.52130502);the National Key Laboratory of Marine Engine Science and Technology(Grant No.LAB2023-06-WD)。; The simulation of lubrication on rough surfaces is essential for the design and optimization of tribological performance.Although the application of physics-informed neural networks(PINNs)in analyzing hydrodynamic lub...; 关键词：physics-informed neural network Fourier feature embedding multiscale lubrication rough surface

Underground laboratories·Deep underground observation·Scientific questions——Insights from observations of multi-physic fields in deep underground labs: 《Science China Earth Sciences》2025年第2期343-362,共20页Huiqi REN Yun WANG Chang CHEN Guangyu FU Longqing QIU Lianghui GUO Chengliang XIE Yongsheng HE Heping SUN Jiwen TENG; supported by the National Science and Technology Major Project (Grant No. 2024ZD1002700);the National Natural Science Foundation of China (Grant Nos. 62127815, 42150201, U1839208)。; This paper presents a comprehensive review on recent development and research conducted in domestic and international underground laboratories. We first introduce the differences in three environments—surface, mounta...; 关键词：Deep underground Multi-physic fields Super-high precision Slow earthquake Schumann Resonance Quantum measurement

Prediction of velocity and pressure of gas-liquid flow using spectrum-based physics-informed neural networks: 《Applied Mathematics and Mechanics(English Edition)》2025年第2期341-356,共16页Nanxi DING Hengzhen FENG H.Z.LOU Shenghua FU Chenglong LI Zihao ZHANG Wenlong MA Zhengqian ZHANG; Supported by the National Natural Science Foundation of China(No.62304022)。; This research introduces a spectrum-based physics-informed neural network(SP-PINN)model to significantly improve the accuracy of calculation of two-phase flow parameters,surpassing existing methods that have limitatio...; 关键词：physics-informed neural network(PINN) spectral method two-phase flow parameter prediction

Physics-informed battery degradation prediction:Forecasting charging curves using one-cycle data: 《Journal of Energy Chemistry》2025年第2期825-836,I0018,共13页Aihua Tang Yuchen Xu Jinpeng Tian Xing Shu Quanqing Yu; jointly supported by the National Natural Science Foundation of China(Grant No.52277213,52177210,and 52207229);key project of science and technology research program of Chongqing Education Commission of China (Grant No. KJZD-K202201103,KJZD-K202301108);Chongqing Graduate Research Innovation Project (Grant No.CYS240657).; Accurately predicting battery degradation is crucial for battery system management.However,due to the complexities of aging mechanisms and limitations of historical data,comprehensively indicating battery degradation ...; 关键词：BATTERY PREDICTION CURVES

Globally optimized dynamic mode decomposition:A first study in particulate systems modelling: 《Theoretical & Applied Mechanics Letters》2025年第1期98-106,共9页Abhishek Gupta Barada Kanta Mishra; supported by the Ramanujan Fellowship from the Science and Engineering Research Board,Government of India(Grant No.RJF/2022/000115).; This paper introduces dynamic mode decomposition(DMD)as a novel approach to model the breakage kinetics of particulate systems.DMD provides a data-driven framework to identify a best-fit linear dynamics model from a s...; 关键词：Physics-informed dynamic mode DECOMPOSITION Population balance equation Particle breakage Zeroth-order optimization

Traffic oscillation mitigation with physics-enhanced residual learning (PERL)-based predictive control: 《Communications in Transportation Research》2024年第1期491-502,共12页Keke Long Zhaohui Liang Haotian Shi Lei Shi Sikai Chen Xiaopeng Li; National Science Foundation Cyber-Physical Systems(CPS)program(No.2343167).; Real-time vehicle prediction is crucial in autonomous driving technology,as it allows adjustments to be made in advance to the driver or the vehicle,enabling them to take smoother driving actions to avoid potential co...; 关键词：Traffic oscillations Traffic safety Connected and autonomous vehicle Mix traffic Vehicle-in-the-loop

Gas prediction in tight sandstones based on the rock-physics-derived seismic amplitude variation versus offset method: 《Petroleum Science》2024年第6期3951-3964,共14页Han Jin Cai Liu Zhi-Qi Guo; supported by the National Natural Science Foundation of China(Grant Nos.42074153 and 42274160)。; Estimating gas enrichments is a key objective in exploring sweet spots within tight sandstone gas reservoirs.However,the low sensitivity of elastic parameters to gas saturations in such formations makes it a significa...; 关键词：Gas content indicator POROSITY AVO Rock physics Tight sandstones

Data-driven friction modeling and compensation for rotary servo actuators: 《Frontiers of Mechanical Engineering》2024年第6期69-85,共17页Baoyu LI Xin XIE Bin YU Yuwen LIAO Dapeng FAN; supported by the National Natural Science Foundation of China(Grant Nos.52305079 and U19A2072).; This study proposes a data-driven friction modeling and compensation method aimed at solving the problem of servo performance degradation caused by friction in rotary servo actuators.First,a data-driven friction model...; 关键词：rotary servo actuator physics-informed neural network LuGre model data-driven friction model friction compensation

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