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Error correction iterative finite element method based on charge-conservative for the stationary inductionless magnetohydrodynamic system

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ZAMM Zeitschrift fur Angewandte Mathematik und Mechanik 2025年第5期105卷

作者： Xia, Yande Yang, Yun-Bo Department of Mathematics Yunnan Normal University Kunming China Yunnan Key Laboratory of Model Analytical Mathematics and Application Yunnan Normal University Kunming China Key Laboratory of Complex System Modeling and Application for Universities in Yunnan Yunnan Normal University Kunming China

In this paper, we propose and analyze a new error correction iterative finite element method (FEM) based on charge-conservative for solving the stationary inductionless magnetohydrodynamic (MHD). The method consists of first solving the inductionless MHD equations by the Oseen iterative scheme to obtain an approximate solution, and then an error correction strategy is applied to control the error arising from the linearization of the nonlinear inductionless MHD equations. The proposed method not only retains the advantages of the classical Oseen iterative scheme but also leads to a rapid rate of convergence. It is shown that the convergence rate of the new method is greatly improved under the uniqueness condition. Stability analysis and error estimates are provided. Numerical results are presented to verify the applicability and effectiveness of the new method. © 2025 Wiley-VCH GmbH.

关键词： Nonlinear equations

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A Projection Method With Modular Grad-Div Stabilization for Inductionless Magnetohydrodynamic Equations Based on Charge Conservation

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Mathematical Methods in the Applied Sciences 2025年

作者： Yang, Yun-Bo Xia, Yande Department of Mathematics Yunnan Normal University Kunming China Yunnan Key Laboratory of Model Analytical Mathematics and Application Yunnan Normal University Kunming China Key Laboratory of Complex System Modeling and Application for Universities in Yunnan Yunnan Normal University Kunming China

In this paper, we proposed a fully discrete projection method with modular grad-div stabilization for solving the time-dependent inductionless magnetohydrodynamic equations. The method incorporates a minimally intrusive module into the classical projection method, serving as a postprocessing step, thereby enhancing solution accuracy and improving mass conservation. Additionally, a decoupled strategy is employed to separate the magnetic and fluid field functions from the original system. Since we only need to solve several linear subsystems at each time step, the numerical solutions can be obtained efficiently. In the spatial discretization, (Formula presented.) -conforming finite element pair is used to approximate the current density and electric potential, ensuring that the discrete current density is exactly divergence-free. Therefore, the designed numerical scheme maintains the features of linearization, decoupling, unconditional energy stability, charge conservation, and improved mass conservation. The unconditional energy stability and convergence of the algorithm are rigorously analyzed and proven. Numerical results are presented to verify the robustness of the algorithm with respect to the stabilization parameters and to demonstrate the performance of the scheme, particularly in terms of its stability and accuracy. © 2025 John Wiley & Sons Ltd.

关键词： Stabilization

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Facilitating sensitivity analysis of hydrological models through knowledge-driven configuration and distributed online model services

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Journal of Hydrology 2025年 660卷

作者： Ma, Peilong Chen, Min Zhang, Shuo Zhu, Zhiyi Qian, Zhen Ma, Zaiyang Zhang, Fengyuan Li, Wenwen Yue, Songshan Wen, Yongning Nanjing Normal University Jiangsu Nanjing210023 China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Jiangsu Nanjing210023 China State Key Laboratory Cultivation Base of Geographical Environment Evolution Jiangsu Nanjing210023 China Earth System Modelling School of Engineering and Design Technical University of Munich Bavaria Munich80333 Germany Potsdam Institute for Climate Impact Research Brandenburg Postdam14473 Germany School of Geographical Sciences Nanjing University of Information Science and Technology Jiangsu Nanjing210044 China

Hydrological models (HMs) are essential for understanding the complexities of the water cycle and runoff dynamics. Sensitivity analysis (SA), an essential component of HMs, plays a key role in identifying the parameters that have the greatest impact on model outcomes. It helps to simplify the complexity of hydrological systems and provides a comprehensive understanding of the underlying physical processes. However, the complexity of HMs and the diversity of SA methods pose significant challenges for researchers, making the SA configuration process intricate and requiring substantial computational resources. To address these challenges, we propose a comprehensive strategy that integrates knowledge-driven configuration services with distributed online model services. First, we establish a rule-based knowledge repository and a case-based knowledge repository. These repositories provide general configuration guidance and similar SA case recommendations, respectively, to support decision-making in critical SA steps. This ensures that the configuration of SA is accurate and reliable. Secondly, we encapsulate HMs as web services and leverage distributed computing resources to optimize execution efficiency. Then, we integrate the HM services with the SA modules to achieve a complete SA experiment. Based on this strategy, we finally developed a prototype system that offers a user-friendly tool for conducting SA with enhanced computational performance and streamlined workflow. The watershed-scale HM, SWAT, was used to test the effectiveness of the prototype system. The results demonstrate that this strategy enables more comprehensive analysis and improves decision-making through configuration guidance, and holds promise for enhancing the reliability and efficiency of SA in hydrological modeling. © 2025 Elsevier B.V.

关键词： Platform as a Service (PaaS)

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Switching Power Supply Design Suitable for Motor Control 29

Switching Power Supply Design Suitable for Motor Control

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第29届中国控制与决策会议

作者： Zhi-Chao Zhao Li guo-hong Tianjin University of Technology Tianjin Complex System Control Theory and Application Key Laboratory

ISBN: (纸本)9781509046584

Motor control systems require multi-channel stable output low voltage DC power *** to the needs of motor control system,a switching power supply can meet the requirements of motor control is *** topology of switching power supply and the uses of PWM control chips are *** positive and negative bias generation circuit of IGBT is *** circuit components' choices and design method of a high frequency transformer of the flyback switching power supply are ***,the basic performances of switching power supply were tested;the results show that it can meet the requirements of motor control systems.

关键词： switching power supply motor drive pulse width control chip high frequency transformer

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modelling forest-atmosphere exchanges of carbon and water using an improved hydro-biogeochemical model in subtropical and temperate monsoon climates

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Ecological modelling 2025年 507卷

作者： Zhang, Wei Zheng, Xunhua Li, Siqi Han, Shenghui Liu, Chunyan Yao, Zhisheng Wang, Rui Wang, Kai Chen, Xiao Yu, Guirui Chen, Zhi Wu, Jiabing Wang, Huimin Yan, Junhua Li, Yong State Key Laboratory of Atmospheric Environment and Extreme Meteorology Institute of Atmospheric Physics Chinese Academy of Sciences Beijing100029 China College of Earth and Planetary Sciences University of Chinese Academy of Sciences Beijing100049 China Qilu Zhongke Institute of Carbon Neutrality Jinan250100 China Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China College of Resources and Environment University of Chinese Academy of Sciences Beijing100049 China Beijing Yanshan Earth Critical Zone National Research Station University of Chinese Academy of Sciences Beijing 101408 China Institute of Applied Ecology Chinese Academy of Sciences Shenyang110016 China South China Botanical Garden Chinese Academy of Sciences Guangzhou510650 China State Key Laboratory of Earth System Numerical Modelling and Application Institute of Atmospheric Physics Chinese Academy of Sciences Beijing100029 China

Forest-atmosphere carbon exchanges are crucial yet challenging to quantify accurately due to scaling uncertainties in site observations. Process-based models that mechanistically represent coupled carbon, nitrogen, and water cycling processes are theoretically capable of reducing uncertainties in forest carbon flux quantification, thereby improving predictions of multiple ecosystem variables relevant to achieving the United Nations Sustainable Development Goals (SDGs) by 2030. Thus, we enhanced the CNMM-DNDC model by developing a forest-specific growth module incorporating key processes (photosynthesis, allocation, respiration, mortality, litter decomposition) based on Biome-BGC formulations. Compared with the original model, evaluation against 8-year (2003–2010) eddy covariance data from three Asian forests showed significant improvements in the updated model. At daily and annual scales, normalized root mean square error decreased by 46% and 54% for gross primary productivity (GPP), and 65% and 37% for ecosystem respiration (ER), respectively, though net ecosystem carbon dioxide exchange (NEE) improvements were less pronounced due to error offsetting. Sensitivity analysis identified specific leaf area, fraction of leaf nitrogen in Rubisco and annual leaf and fine root turnover fraction as most influential eco-physiological parameters, with solar radiation, humidity and air temperature as dominant meteorological drivers. The model's ability to capture daily and inter-annual carbon flux variations demonstrates its potential for regional-to-global greenhouse gas assessments, while highlighting the need for component-specific validation to avoid error masking in net flux calculations. © 2025

关键词： Biotic

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Power consumption prediction modeling of cement manufacturing based on the improved multiple non-linear regression algorithm

Power consumption prediction modeling of cement manufacturin...

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2014 International Conference on Manufacturing Technology and Electronics applications, ICMTEA 2014

作者： Zhao, Hui Zhang, Ning Wang, Hong Jun Tianjin Agricultural University Tianjin university of technology Tianjin complex system control theory and application of key laboratory Tianjin China Tianjin university of technology Tianjin complex system control theory and application of key laboratory Tianjin China

ISBN: (纸本)9783038353287

The principal component analysis (PCA) is applied in this paper, since the existing power consumption prediction models of cement manufacturing influenced by many factors are quite complex and have low accuracy. In this way, four new key factors affecting the power consumption of cement manufacturing are obtained instead of the eleven original ones, with the complexity of the computing model simplified. Built upon this is the power consumption prediction model of cement manufacturing based on an improved multiple non-linear regression algorithm. Then the efficiency of the model, obviously improved the forecasting precision, is verified in Pingyi Zhonglian Cement Plant. In other words, a theoretical basis for cement plants power consumption forecasting management is provided in this paper. © (2014) Trans Tech Publications, Switzerland.

关键词： Electric power utilization

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Research of waste heat power generation main steam valve control

Research of waste heat power generation main steam valve con...

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2014 International Conference on Manufacturing Technology and Electronics applications, ICMTEA 2014

作者： Zhao, Hui Wang, Ya Fei Wang, Hong Jun Tianjin Agricultural University and Tianjin university of technology Tianjin complex system control theory and application of key laboratory Tianjin China Tianjin university of technology Tianjin complex system control theory and application of key laboratory Tianjin China

ISBN: (纸本)9783038353287

In order to improve the stability of steam turbine under large disturbance, the controller of cement waste heat power generation valve was designed by using exponential terminal sliding mode variable structure control method. In this paper, taking a single machine infinite bus power system as an example, established mathematical model of waste heat generator valve system, and designed the valve controller of synchronous generator based on the exponential terminal sliding mode variable structure control theory. Then, valve control simulation model was set up and simulation experiment was performed by MATLAB. Finally, verify the effectiveness of the scheme by comparison analysis. Simulation results show that the controller can effectively improve the transient stability of power system and the dynamic quality. © (2014) Trans Tech Publications, Switzerland.

关键词： Waste heat

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Debris flow susceptibility mapping in mountainous area based on multi-source data fusion and CNN model-taking Nujiang Prefecture,China as an example

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International Journal of Digital Earth 2022年第1期15卷 1966-1988页

作者： Fanshu Xu Baoyun Wang School of Information Science and Technology Yunnan Normal UniversityKunmingPeople’s Republic of China School of Mathematic Yunnan Normal UniversityKunmingPeople’s Republic of China Key Laboratory of Complex System Modelling and Application Yunnan Normal UniversityKunmingPeople’s Republic of China

Efforts to evaluate the susceptibility of debris flows in large areas,especially in mountainous regions,are often hampered by the alpine and canyon *** paper proposes a convolution neural network(CNN)model named dense residual shuffle net(DRSNet).It is successfully applied to Nujiang Prefecture in Yunnan Province of China,a typical alpine area with frequent debris *** uses digital elevation model,remote sensing,lithology,soil type and precipitation data as ***,dense connection and residual structure were used to extract the shallow features of various ***,channel shuffle,fuse block and fully connection were applied to strengthen the correlation between different shallow features and give inner danger ***,precipitation as the activation factor was introduced giving the valleys *** verify the feasibility of DRSNet,comparative tests were conducted on 7 CNN models and 3 other machine learning(ML)*** results show that DRSNet can achieve 78.6%accuracy in debris flow valley classification,which is at least 7.4%higher than common CNN models and 15.2%higher than other ML *** article provides new ideas for debris flow susceptibility evaluation.

关键词： Debris flow disaster prediction convolutional neural networks mountainous valleys

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Image Segmentation Method of Crop Diseases Based on Improved Segnet Neural Network 17

Image Segmentation Method of Crop Diseases Based on Improved...

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17th IEEE International Conference on Mechatronics and Automation, ICMA 2020

作者： Yue, Youjun Li, Xuesong Zhao, Hui Wang, Hongjun Tianjin University of Technology Tianjin Key Laboratory of Complex System Control Theory and Application Tianjin300384 China

ISBN: (纸本)9781728164151

In crop disease image segmentation, traditional convolutional neural networks have the problem of low image accuracy. For this reason, this paper proposes a segmentation method that combines conditional random fields with segnet networks. First, input the training set in the data set into the segnet network for training, and obtain the initial segmentation result and the network with updated parameters;secondly, the image segmented by the segnet network is sent to the conditional random field in the form of pixels and classification vectors corresponding to the pixels At the same time, construct an energy function to represent the relative relationship between pixels, and then keep training;in order to get the conditional random field in the training set, you need to adjust and optimize the image segmented by the segnet network to get it;then in the verification set, the segnet network and the weight parameters of the conditional random field model are further adjusted and optimized to obtain the final conditional random field and segnet network;finally, the final conditional random field and segnet network are applied to the crop disease image segmentation. The test results show that compared with the Otsu threshold and Grabcut segmentation methods, the segmentation accuracy P, recall rate R, and comprehensive evaluation index F of this method are all the maximum, and the average processing time of a single image is 0.86 s;compared with pspnet and deeplab methods, Under the premise that the segmentation accuracy P, the recall rate R, and the comprehensive evaluation index F are basically unchanged, the average processing time of a single image is significantly reduced. The results show that the best comprehensive effect can be achieved by segmenting crop disease images in complex environments using the method in this paper. © 2020 IEEE.

关键词： Image segmentation

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Fault Type identification in Transmission Lines based on VMD-FE and IGWO-KELM 17

Fault Type identification in Transmission Lines based on VMD...

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17th IEEE International Conference on Mechatronics and Automation, ICMA 2020

作者： Yue, Youjun Li, Lixin Wang, Hongjun Zhao, Hui Tianjin University of Technology Tianjin Key Laboratory of Complex System Control Theory and Application Tianjin300384 China

ISBN: (纸本)9781728164151

In view of the damage of transmission line short-circuit faults and low fault identification rate, A novel fault identification method based on variational mode decomposition-fuzzy entropy and improved grey wolf algorithm - kernel extreme learning machine is proposed. First, the VMD is used to decompose the three-phase current after the fault to obtain a series of three-phase stable modal components;secondly, the fuzzy entropy value of each group of components is calculated separately as the fault characteristics of the transmission line;Finally, The fault characteristics of the transmission line are input to the kernel extreme learning machine for training to obtain the diagnosis model. The experimental results show that the method is not affected by the distance of the fault, the initial phase angle of the fault and the transition resistance, and can accurately identify the fault type. © 2020 IEEE.

关键词： Variational mode decomposition

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