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Development and validation of a gridded emissions inventory for HFC-134a in China

Environment International 2025年 200卷 109535页

作者： Wu, Jing Wang, Tong An, Minde Ding, Shan Yao, Bo Western, Luke M. Purohit, Pallav Liu, Zehua Zhang, Zechen Peng, Lin School of Environment Beijing Jiaotong University Beijing100044 China Institute of Transport Energy and Environment Beijing Jiaotong University Beijing100044 China Center for Sustainability Science and Strategy Massachusetts Institute of Technology CambridgeMA United States School of Chemistry University of Bristol BristolBS8 1TS United Kingdom The MOE Key Laboratory of Resource and Environmental System Optimization College of Environmental Science and Engineering North China Electric Power University Beijing102206 China Beijing100081 China Department of Atmospheric and Oceanic Sciences & Institute of Atmospheric Sciences Fudan University Shanghai China Schlossplatz 1 LaxenburgA-2361 Australia Beijing Jingcheng Machinery & Electricity Company Beijing100027 China Chinese Acad Environm Planning State Environm Protect Key Lab Environm Pollut & G Beijing100041 China

1,1,1,2-Tetrafluoroethane (HFC-134a), a potent greenhouse gas, breaks down to form trifluoroacetic acid (TFA). Lack of its gridded emissions inventories makes it difficult to analyze the spatial distribution of emissions. This study developed a framework for national and gridded HFC-134a bank and emission calculations, validation and environmental impact assessments. Within this framework, we used production and consumption data along with emission factors to compile a gridded inventory for China. The results reveal an increase in national HFC-134a emissions, from 0.1 kt yr−1 in 1995 to 48 kt yr−1 in 2020, with banks also increasing from 0.9 to 301 kt. Guangdong, Jiangsu, and Shandong provinces showed the largest cumulative emissions, totaling 98 kt between 1995 and 2020, representing 28% of HFC-134a national emissions. A Lagrangian dispersion model, in conjunction with atmospheric observations, was used to validate the gridded inventory, where the simulations based on the gridded inventory were in reasonable agreement with the observations. A carbon–neutral (CN) scenario was developed to project future emissions. The adoption of HFO-1234yf and R-513A as substitutes for HFC-134a is projected to cause an additional 701 kt of cumulative TFA formation potential between 1995 and 2060, on top of the 3825 kt projected under the Kigali Amendment scenario. © 2025

关键词： Global warming

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A POSTERIORI ERROR ESTIMATE OF THE DSD METHOD FOR FIRST-ORDER HYPERBOLIC EQUATIONS

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Applied Mathematics and Mechanics(English Edition) 2002年第6期23卷 732-740页

作者： KANG Tong(康彤) YU De-hao(余德浩) State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and System Science Chinese Academy of Sciences Beijing 100080 P R China State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and System Science Chinese Academy of Sciences Beijing 100080 P R China

A posteriori error estimate of the discontinuous-streamline diffusion method for first-order hyperbolic equations was presented, which can be used to adjust space mesh reasonably. A numerical example is given to illus... 详细信息

关键词： posteriori error estimate discontinuous-streamline diffusion method first-order hyperbolic equation

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Slab morphology and associated seismic and volcanic activities beneath Sulawesi Island, Indonesia

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Journal of Volcanology and Geothermal Research 2025年 465卷

作者： Wibowo, Bagus Adi Bai, Ling Rohadi, Supriyanto Sahara, David Prambudi Chen, Zhiwen Karyono, Karyono Setiawan, Yosi Widyadharma, Putu Hendra Arimuko, Abraham Rahayu, Anisa Nurbaeti Adi, Suko Prayitno Karnawati, Dwikorita State Key Laboratory of Tibetan Plateau Earth System Environment and Resources Institute of Tibetan Plateau Research Chinese Academy of Sciences No. 16 Lincui Road Chaoyang District Beijing100101 China University of Chinese Academy of Sciences No.80 Zhongguancun East Road Haidian District Beijing100049 China Center of Earthquake and Tsunami's Early Warning System Deputy of Geophysics Agency of Meteorology Climatology and Geophysics Angkasa I Street No.2 PO Box 3540 Jakarta Indonesia Center of Research and Development Geophysics Section Agency of Meteorology Climatology and Geophysics Angkasa I Street No.2 PO Box 3540 Jakarta Indonesia Agency of Meteorology Climatology and Geophysics Angkasa I Street No.2 PO Box 3540 Jakarta Indonesia Faculty of Mining and Petroleum Engineering Bandung Institute of Technology Ganesa Street No. 10 Coblong Bandung Indonesia

The Sulawesi Island, Indonesia, represents a complex deformation with multiple subducting slabs and produces frequent earthquake, volcano, and tsunami hazards. Here, we investigate lithospheric velocity structures beneath Sulawesi Island to study the subducting slabs and their associated seismicity and volcanism. P- and S-wave arrival time data are acquired from the dense seismic network of the Indonesia Tsunami Early Warning system. We collected 192,301 P-wave and 40,345 S-wave phases arrival time data from 10,421 earthquakes with 2.5 ≤ Mw ≤ 7.5 that occurred between 2017 and 2022. Earthquake data are recorded by 137 InaTEWS seismic stations which provide sufficient ray path density for the entire Sulawesi Island. There are high velocity anomalies for subducting slabs and low velocity anomalies beneath active volcanoes. These observations revealed southward subduction of the Celebes slab, northward subduction of the Banggai-Sula slab, southwest subduction of the Sangihe slab, and double subduction of the Sangihe and Halmahera arcs northeast of the Sulawesi Island. The 2018 Mw7.5 Palu earthquake occurred on the left-lateral strike-slip Palu-Koro fault, which was formed by the northward subduction of the Banggai-Sula slab with respect to the Makassar Strait. The 2018 Mw7.5 Palu earthquake sequence and the 2018 Mamasa earthquake swarm are located with low Vp and Vs anomalies, probably due to the combination of active fault activity and fluid migration. © 2025 Elsevier B.V.

关键词： Earthquake effects

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PLANE SURFACE SUDDENLY SET IN MOTION IN A VISCOELASTIC FLUID WITH FRACTIONAL MAXWELL MODEL

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Acta Mechanica Sinica 2002年第4期18卷 342-349页

作者：谭文长徐明瑜 Department of Mechanics and Engineering Science & State Key Laboratory for Turbulence Research Peking UniversityBeijing 100871China Institute of Mathematics and System Science Shandong UniversityJinan 250100China

The fractional calculus approach in the constitutive relationship model of viscoelastic fluid is *** flow near a wall suddenly set in mo- tion is studied for a non-Newtonian viscoelastic fluid with the fractional Maxwell *** solutions of velocity and stress are obtained by using the discrete in- verse Laplace transform of the sequential fractional *** is found that the effect of the fractional orders in the constitutive relationship on the flow field is signif- *** results show that for small times there are appreciable viscoelastic effects on the shear stress at the plate,for large times the viscoelastic effects become weak.

关键词： viscoelastic fluid fractional calculus Stokes problem fractional Maxwell model

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A Natural Deep Ritz Method for Essential Boundary Value Problems

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Journal of Computational Physics 2025年

作者： Haijun Yu Shuo Zhang Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and System Sciences State Key Laboratory of Mathematical Sciences (SKLMS) and State Key Laboratory of Scientific and Engineering Computing (LSEC) Chinese Academy of Sciences Beijing 100190 China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing 100049 China

Deep neural network approaches show promise in solving partial differential equations. However, unlike traditional numerical methods, they face challenges in enforcing essential boundary conditions. The widely adopted penalty-type methods, for example, offer a straightforward implementation but introduces additional complexity due to the need for hyper-parameter tuning; moreover, the use of a large penalty parameter can lead to artificial extra stiffness, complicating the optimization process. In this paper, we propose a novel, intrinsic approach to impose essential boundary conditions through a framework inspired by intrinsic structures. We demonstrate the effectiveness of this approach using the deep Ritz method applied to Poisson problems, with the potential for extension to more general equations and other deep learning techniques. Numerical results are provided to substantiate the efficiency and robustness of the proposed method.

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Integrated Active Suspension and Anti-Lock Braking Control for Four-Wheel-Independent-Drive Electric Vehicles

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Chinese Journal of Mechanical engineering 2024年第1期37卷 87-98页

作者： Ze Zhao Lei Zhang Xiaoling Ding Zhiqiang Zhang Shaohua Li Liang Gu National Engineering Research Center for Electric Vehicles Beijing Institute of TechnologyBeijing 100081China State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures Shijiazhuang Tiedao UniversityShijiazhuang 050043China

This paper presents an integrated control scheme for enhancing the ride comfort and handling performance of a four-wheel-independent-drive electric vehicle through the coordination of active suspension system(ASS)and anti-lock braking system(ABS).First,a longitudinal-vertical coupled vehicle dynamics model is established by integrating a road input *** the coupling mechanisms between longitudinal and vertical vehicle dynamics are *** ASS-ABS integrated control system is proposed,utilizing an H∞controller for ASS to optimize load transfer effect and a neural network sliding mode control for ABS ***,the effectiveness of the proposed control scheme is evaluated through comprehensive tests conducted on a hardware-in-loop(HIL)test *** HIL test results demonstrate that the proposed control scheme can significantly improve the braking performance and ride comfort compared to conventional ABS control methods.

关键词： Four-wheel-independent-drive electric vehicles Active suspension system(ASS) Anti-lock braking system(ABS) Vertical-longitudinal vehicle dynamics

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Analytical Representation of Data-driven Transient Stability Constraint and Its Application in Preventive Control

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Journal of Modern Power systems and Clean Energy 2022年第5期10卷 1085-1097页

作者： Yiwei Fu Xiaohua Zhang Lei Chen Zengyao Tian Kaiyuan Hou Haikuan Wang State Key Laboratory of Control and Simulation of Power System and Generation Equipment Department of Electrical EngineeringTsinghua UniversityBeijing 100084China State Grid Jibei Electric Power Company Beijing 100053China Northeast China Branch of State Grid Corporation of China Shenyang 110180China

Accurate transient stability assessment(TSA) and effective preventive control are important for the stable operation of power systems. With the superiorities in precision and efficiency, data-driven methods are widely used in TSA nowadays. Data-driven TSA model can be adopted in the stability constraints of preventive control optimization, but existing methods are mostly iteration-based ones, which may result in low efficiency, sometimes even non-convergence. In this paper,an analytical representation method of data-driven transient stability constraint is proposed based on a non-parametric regression model built for TSA. key feature extraction and dominant sample selection are proposed to reduce the scale of the TSA model, and bi-level linearization is applied to further modify *** preventive control model is then formulated as a mixed-integer linear program(MILP) problem with the linearized analytical data-driven transient stability constraint, which can be solved without iterations. An overall procedure of datadriven TSA and preventive control is finally developed. Case studies show that the proposed method has high accuracy in TSA and can achieve effective preventive control of power system with high efficiency.

关键词： Data-driven critical clearing time transient stability constraint non-parametric regression optimal preventive control

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DeePMD-kit v3: A Multiple-Backend Framework for Machine Learning Potentials

arXiv

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arXiv 2025年

作者： Zeng, Jinzhe Zhang, Duo Peng, Anyang Zhang, Xiangyu He, Sensen Wang, Yan Liu, Xinzijian Bi, Hangrui Li, Yifan Cai, Chun Zhang, Chengqian Du, Yiming Zhu, Jia-Xin Mo, Pinghui Huang, Zhengtao Zeng, Qiyu Shi, Shaochen Qin, Xuejian Yu, Zhaoxi Luo, Chenxing Ding, Ye Liu, Yun-Pei Shi, Ruosong Wang, Zhenyu Bore, Sigbjørn Løland Chang, Junhan Deng, Zhe Ding, Zhaohan Han, Siyuan Jiang, Wanrun Ke, Guolin Liu, Zhaoqing Lu, Denghui Muraoka, Koki Oliaei, Hananeh Singh, Anurag Kumar Que, Haohui Xu, Weihong Xu, Zhangmancang Zhuang, Yong-Bin Dai, Jiayu Giese, Timothy J. Jia, Weile Xu, Ben York, Darrin M. Zhang, Linfeng Wang, Han School of Artificial Intelligence and Data Science Unversity of Science and Technology of China Hefei China AI for Science Institute Beijing100080 China DP Technology Beijing100080 China Academy for Advanced Interdisciplinary Studies Peking University Beijing100871 China State Key Lab of Processors Institute of Computing Technology Chinese Academy of Sciences Beijing100871 China University of Chinese Academy of Sciences Beijing China Baidu Inc. Beijing China Department of Computer Science University of Toronto TorontoON Canada Department of Chemistry Princeton University PrincetonNJ08540 United States University of Chinese Academy of Sciences Beijing100871 China State Key Laboratory of Physical Chemistry of Solid Surfaces iChEM College of Chemistry and Chemical Engineering Xiamen University Xiamen361005 China College of Integrated Circuits Hunan University Changsha410082 China State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Center for Smart Materials and Device Integration School of Material Science and Engineering Wuhan University of Technology Wuhan430070 China College of Science National University of Defense Technology Changsha410073 China Hunan Key Laboratory of Extreme Matter and Applications National University of Defense Technology Changsha410073 China ByteDance Research Beijing100098 China Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Ningbo315201 China College of Materials Science and Opto-Electronic Technology University of Chinese Academy of Sciences Beijing100049 China Key Laboratory of Theoretical and Computational Photochemistry of Ministry of Education College of Chemistry Beijing Normal University Beijing100875 China Department of Geosciences Princeton University PrincetonNJ08544 United States Department of Applied Physics and Applied Mathematics Columbia University New YorkNY10027 United States IKKEM Fujian Xiamen361005 China Graduate

In recent years, machine learning potentials (MLPs) have become indispensable tools in physics, chemistry, and materials science, driving the development of software packages for molecular dynamics (MD) simulations and related applications. These packages, typically built on specific machine learning frameworks such as TensorFlow, PyTorch, or JAX, face integration challenges when advanced applications demand communication across different frameworks. The previous TensorFlow-based implementation of DeePMD-kit exemplified these limitations. In this work, we introduce DeePMD-kit version 3, a significant update featuring a multi-backend framework that supports TensorFlow, PyTorch, JAX, and PaddlePaddle backends, and demonstrate the versatility of this architecture through the integration of other MLPs packages and of Differentiable Molecular Force Field. This architecture allows seamless backend switching with minimal modifications, enabling users and developers to integrate DeePMD-kit with other packages using different machine learning frameworks. This innovation facilitates the development of more complex and interoperable workflows, paving the way for broader applications of MLPs in scientific research. Copyright © 2025, The Authors. All rights reserved.

关键词： Molecular dynamics

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Hohmann transfer via constrained optimization

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Frontiers of Information Technology & Electronic engineering 2018年第11期19卷 1444-1458页

作者： Li XIE Yi-qun ZHANG Jun-yan XU State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer EngineeringNorth China Electric Power UniversityBeijing 102206China Beijing Institute of Electronic Systems Engineering Beijing 100854China

Inspired by the geometric method proposed by Jean-Pierre MAREC, we first consider the Hohmann transfer problem between two coplanar circular orbits as a static nonlinear programming problem with an inequality constraint. By the Kuhn-Tucker theorem and a second-order sufficient condition for minima, we analytically prove the global minimum of the Hohmann transfer. Two sets of feasible solutions are found: one corresponding to the Hohmann transfer is the global minimum and the other is a local minimum. We next formulate the Hohmann transfer problem as boundary value problems, which are solved by the calculus of variations. The two sets of feasible solutions are also found by numerical examples. Via static and dynamic constrained optimizations, the solution to the Hohmann transfer problem is re-discovered, and its global minimum is analytically verified using nonlinear programming.

关键词： Hohmann transfer Nonlinear programming Constrained optimization Calculus of variations

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Enhancing heat dissipation and temperature uniformity of microchannel heat sinks using fractal gradient honeycomb-reverse Tesla valve configuration

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Case Studies in Thermal engineering 2025年 72卷

作者： Chun-Yu Chen Min Yang Yuanyuan Li Gui Lu School of Energy Power and Mechanical Engineering North China Electric Power University Beijing 102206 China State Key Laboratory of Space Thermal Control Technology Beijing Institute of Spacecraft System Engineering China Academy of Space Technology Beijing 100094 China

This study introduces a fractal gradient honeycomb-reverse Tesla valve configuration (HC-RTV-GD) to enhance heat transfer and temperature uniformity in high-flux thermal management systems. Through comparative analysis with conventional Tesla valves and honeycomb structures, the HC-RTV-GD leverages hierarchical bifurcation and controlled turbulence generation to achieve superior heat transfer performance. At high Reynolds numbers, the design significantly reduces thermal resistance and suppresses maximum wall temperatures while flattening longitudinal temperature gradients, mitigating thermal stress risks. The improved temperature uniformity stems from gradient-driven flow redistribution, which minimizes stagnant zones and sustains coolant velocity in secondary channels. Thermal improvements come with hydraulic trade-offs: the gradient geometry amplifies flow resistance through localized vortices, elevating pressure drop and friction coefficients compared to conventional designs. Performance evaluation confirms the HC-RTV-GD’s viability exclusively in high-flux scenarios, where heat transfer gains outweigh pumping penalties. A neural network-enhanced optimization framework further identifies optimal coolant parameters, balancing thermal and hydraulic efficiency. The HC-RTV-GD advances cooling system design by strategically combining geometric complexity with turbulence control, prioritizing thermal uniformity in extreme heat flux environments.

关键词： Temperature uniformity Fractal gradient Honeycomb-reverse Tesla valve NSGA-II

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