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ACS ES&T Air 2024年第7期1卷 734-742页

作者： Helan Wang Bo Zheng Hui Li Qiang Zhang Kebin He Shenzhen Key Laboratory of Ecological Remediation and Carbon Sequestration Institute of Environment and Ecology Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen 518055 China State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Beijing 100084 China Department of Earth System Science Ministry of Education Key Laboratory for Earth System Modeling Institute for Global Change Studies Tsinghua University Beijing 100084 China State Key Joint Laboratory of Environment Simulation and Pollution Control School of Environment Tsinghua University Beijing 100084 China

The energy system fuels climate change as the largest emitter of global greenhouse gases, while a lack of transparent, infrastructure-level information undermines efforts to cut emissions. Coal mining has been the largest emitter of methane (CH4) in China over the past 10 years, which is not tracked at the mine level, and effective mitigation pathways have yet to be established. Herein, we develop a state-of-the-art CH4emission database, comprising 3343 active coal mines in China, by harmonizing multisource information. The results suggest that China’s coal mines emitted 15.8 ± 5.1 million metric tons CH4yr–1in 2019. Those with CH4emission intensities >2 standard deviations above the national mean accounted for 4% of China’s coal production, yet they generated 23% of China’s coal CH4emissions. We project a steady decline in China’s coal CH4emissions by >75% in 2100 compared to 2019 levels under three different scenarios, due to reduced coal demand during energy transition. Targeting ultra-emitters for mine closure will accelerate emission reductions in the midterm and achieve deep CH4emission cuts by >92% in 2100, which buys us time to control global warming. Our idealized mine closure strategy serves as a cost-effective CH4mitigation strategy to enable swift climate action.

关键词： Biological databases Climate Coal Energy Hydrocarbons

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Autonomous migration of virtual machine based on OpenStack

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International Journal of Hybrid Information Technology 2016年第8期9卷 65-84页

作者： Zhou, Li Yu, Zhuoer Zhang, Jilin Wan, Jian Wu, Yusen School of Computer and Technology Hangzhou Dianzi University Hangzhou310018 China Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education Hangzhou China College of Electrical Engineering Zhejiang University Hangzhou310058 China School of Information and Electronic engineering Zhejiang University of Science & Technology Hangzhou310023 China Zhejiang Provincial Engineering Center on Media Data Cloud Processing and Analysis HangzhouZhejiang China

For the problem of compute nodes load unbalance leads to the overload node impact VM performance and the underload node waste electrical energy. Dynamic VM consolidation is an efficient approach for improving the utilization of servers and reducing energy costs. In this paper, we introduce dynamic consolidation into OpenStack and implement AMVM based on OpenStack. AMVM collect and analyze all performance data of VM and compute node in OpenStack. Then AMVM automatically schedules VM live migrate to the most appropriate node according to the real-time load of all compute nodes. Then we use hybrid-copy instead of pre-copy in AMVM to improve the efficiency of VM live migration. Finally, we analyze the performance of hybrid-copy, hybrid-copy can reduce page faults compared with post-copy and reduce total data transferred compared with pre-copy. © 2016 SERSC.

关键词： Virtual machine

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Thermodynamically Consistent Hybrid Computational Models for Fluid-Particle Interactions

SSRN

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SSRN 2023年

作者： Hong, Qi Wang, Qi School of Mathematics Nanjing University of Aeronautics and Astronautics Nanjing211106 China MIIT Nanjing211106 China Key Laboratory of Numerical Simulation for Large Scale Complex Systems Nanjing Normal University Ministry of Education Nanjing210023 China Department of Mathematics University of South Carolina ColumbiaSC29208 United States

We introduce a novel computational framework designed to explore the dynamic interactions between fluid and solid particles or structures immersed in a viscous fluid medium. This innovative framework harnesses the power of the phase-field-embedding method, in which each solid component, whether rigid or elastic, is characterized by a volume-preserving phase field. The unified velocity within the fluid-solid ensemble governs the movement of both solid particles and the surrounding fluid, specifically for passive particles. Active particles, however, are not only influenced by this unified velocity but are also driven by their self-propelling velocities. To capture exclusive volume interactions among particles and between particles and boundaries, we employ repulsive potential forces at a coarser scale. These forces effectively model repulsion and collision effects. Rigid particles maintain structural integrity by enforcing a zero velocity gradient tensor within their spatial domains, necessitating the introduction of a constraining stress tensor. In contrast, elastic particles are governed by a quasi-linear constitutive equation describing the elastic stress within their domains, allowing for accurate modeling of their deformations. The motion of solid particles is tracked by monitoring the dynamics of their centers of mass. This approach facilitates the development of a hybrid, thermodynamically consistent hydrodynamic model applicable to both rigid and elastic particles. Adhering to the generalized Onsager principle, this model spans the entire computational domain. To numerically solve this thermodynamically consistent model for elastic particles, we present a structure-preserving numerical algorithm. Notably, in the limit of an infinite elastic modulus, this algorithm converges to the one employed for modeling rigid particles. Finally, we substantiate the effectiveness, accuracy, and stability of our proposed scheme through a series of numerical experiments. Thes

关键词： Hydrodynamics

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An Auto-Parallel Method for Deep Learning Models Based on Genetic Algorithm

An Auto-Parallel Method for Deep Learning Models Based on Ge...

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International Conference on Parallel and Distributed systems (ICPADS)

作者： Yan Zeng ChengChuang Huang YiJie Ni ChunBao Zhou JiLin Zhang Jue Wang MingYao Zhou MeiTing Xue YunQuan Zhang School of Computer Science and Technology Hangzhou Dianzi University Hangzhou China Key Laboratory for Modeling and Simulation of Complex Systems Ministry of Education Hangzhou China Data Security Governance Zhejiang Engineering Research Center Hangzhou China School of ITMO Joint Institute Hangzhou Dianzi University Hangzhou China Institute of Computer Network Information Center of the Chinese Academy of Sciences Beijing China HuaWei State Key Laboratory of Computer Architecture Institute of Computing Technology of the Chinese Academy of Sciences Beijing China

As the size of datasets and neural network models increases, automatic parallelization methods for models have become a research hotspot in recent years. The existing auto-parallel methods based on machine learning or graph algorithms still have issues with search efficiency and applicability. This paper proposes an automatic parallel method based on a dual-population genetic algorithm, TGA, which transforms model partitioning and placement into an integer linear programming problem and constructs a cost model to evaluate the solution. The solution space is built using the neural network’s dataflow graph and device cluster’s topology, and the dual-population genetic algorithm is used to search for the optimal model parallel strategy. Experiments with various models show that the proposed method can improve single-step execution time by up to 42% compared to the Baechi method and up to 37.7% compared to the Hierarchical method.

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Constructing IGA-suitable planar parameterization from complex CAD boundary by domain partition and global/local optimization

arXiv

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arXiv 2017年

作者： Xu, Gang Li, Ming Mourrain, Bernard Rabczuk, Timon Xu, Jinlan Bordas, Stéphane P.A. School of Computer Science and Technology Hangzhou Dianzi University Hangzhou310018 China Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education Hangzhou310018 China State Key Laboratory of CAD &CG Zhejiang University Hangzhou310058 China INRIA Sophia-Antipolis 2004 Route des Lucioles Cedex06902 France Institute of Structural Mechanics Bauhaus-University Weimar Marienstr. 15 WeimarD-99423 Germany Research Unit in Engineering University of Luxembourg Luxembourg

In this paper, we propose a general framework for constructing IGA-suitable planar B-spline parameterizations from given complex CAD boundaries consisting of a set of B-spline curves. Instead of forming the computational domain by a simple boundary, planar domains with high genus and more complex boundary curves are considered. Firstly, some pre-processing operations including Bézier extraction and subdivision are performed on each boundary curve in order to generate a high-quality planar parameterization;then a robust planar domain partition framework is proposed to construct high-quality patch-meshing results with few singularities from the discrete boundary formed by connecting the end points of the resulting boundary segments. After the topology information generation of quadrilateral decomposition, the optimal placement of interior Bézier curves corresponding to the interior edges of the quadrangulation is constructed by a global optimization method to achieve a patch-partition with high quality. Finally, after the imposition of C1/G1-continuity constraints on the interface of neighboring Bézier patches with respect to each quad in the quadrangulation, the high-quality Bézier patch parameterization is obtained by a C1constrained local optimization method to achieve uniform and orthogonal iso-parametric structures while keeping the continuity conditions between patches. The efficiency and robustness of the proposed method are demonstrated by several examples which are compared to results obtained by the skeleton-based parameterization approach. Copyright © 2017, The Authors. All rights reserved.

关键词： Parameterization

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A Distributed Approximation Algorithm for the Total Dominating Set Problem 1

引用

18th International Conference on Algorithmic Aspects in Information and Management, AAIM 2024

作者： Wang, Limin Zhang, Zhao Du, Donglei Mao, Yaping Zhang, Xiaoyan School of Mathematical Sciences Henan Institute of Science and Technology Xinxiang453003 China College of Mathematics and Computer Sciences Zhejiang Normal University Zhejiang321004 China Faculty of Management University of New Brunswick Fredericton E3B 5A3 New Brunswick Canada School of Mathematics and Statistics Qinghai Normal University Qinghai810008 China Academy of Plateau Science and Sustainability Xining Qinghai810008 China School of Mathematical Science and Institute of Mathematics Key Laboratory of Ministry of Education Numerical Simulation of Large Scale Complex Systems Nanjing Normal University Jiangsu210023 China

ISBN: (数字)9789819777983

ISBN: (纸本)9789819777976

Given a network graph G=(V,E), a subset T⊆V is said to be a total dominating set (TDS) if every v∈V is adjacent to at least one node in T. In this paper, we present a distributed algorithm for the TDS problem via the LP relaxation techniques. For a positive integer k and maximum degree Δ, the proposed algorithm outputs a fractional total dominating set of expected size O(kΔ2k)|TDSOPT|. The distributed algorithm runs in O(k2) communication rounds, and the algorithm use messages of size O(logΔ). The fractional solution is then rounded to obtain an integer total dominating set for the original problem. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Consensus algorithm

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Spring festival points the way to cleaner air in China

arXiv

引用

arXiv 2020年

作者： Wang, Siwen Su, Hang Streets, David G. Zhang, Qiang Lu, Zifeng He, Kebin Andreae, Meinrat O. Pöschl, Ulrich Cheng, Yafang Max Planck Institute for Chemistry Mainz55128 Germany Energy Systems Division Argonne National Laboratory LemontIL60439 United States Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System Science Tsinghua University Beijing100084 China State Key Joint Laboratory of Environment Simulation and Pollution Control School of Environment Tsinghua University Beijing100084 China Scripps Institution of Oceanography University of California San Diego San DiegoCA92093 United States

Human migration during the Chinese Spring Festival (SF) is the largest collective human activity of its kind in the modern era-involving about one-tenth of the world population and over six percent of the earth's land surface area. The festival results in a drop of air pollutant emissions that causes dramatic changes of atmospheric composition over China's most polluted regions. Based on satellite and in-situ measurements for the years 2005-2019 over 50 cities in eastern China, we find that the atmospheric NO2 pollution dropped by ~40% during the SF week, and fine particulate matter (PM2.5) decreased by ~30% in the following week, reflecting the effectiveness of precursor emission controls on the mitigation of secondary PM2.5 formation. However, although human activity and emissions are at the lowest level, air pollution over eastern China during the SF still far exceeds that over other worldwide pollution hotspots. Our analyses suggest that measures based solely on end-of-pipe controls and industry upgrades may not suffice to meet air quality goals. Further cleaning of the air in China depends fundamentally on sustainable advances in both heavy industry upgrades and clean energy transition. Copyright © 2020, The Authors. All rights reserved.

关键词： Air cleaners

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Superexponential diffusion in nonlinear non-Hermitian systems

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Physical Review A 2020年第6期102卷 062213-062213页

作者： Wen-Lei Zhao Longwen Zhou Jie Liu Peiqing Tong Kaiqian Huang School of Science Jiangxi University of Science and Technology Ganzhou 341000 China Department of Physics College of Information Science and Engineering Ocean University of China Qingdao 266100 China Graduate School of China Academy of Engineering Physics Beijing 100193 China CAPT HEDPS and IFSA Collaborative Innovation Center of the Ministry of Education Peking University Beijing 100871 China Department of Physics and Institute of Theoretical Physics Nanjing Normal University Nanjing 210023 China Jiangsu Provincial Key Laboratory for Numerical Simulation of Large Scale Complex Systems Nanjing Normal University Nanjing Jiangsu 210023 China Guangdong Provincial Key Laboratory of Quantum Engineering and Quantum Materials SPTE South China Normal University Guangzhou 510006 China

We investigate the quantum diffusion of a periodically kicked particle subjected to both nonlinearity-induced self-interactions and PT-symmetric potentials. We find that, due to the interplay between the nonlinearity and non-Hermiticity, the expectation value of the mean square of momentum scales with time in a superexponential form 〈p2(t)〉∝exp[βexp(αt)], which is faster than any known rates of quantum diffusion. In the PT-symmetry-breaking phase, the intensity of a state increases exponentially with time, leading to the exponential growth of the interaction strength. The feedback of the intensity-dependent nonlinearity further turns the interaction energy into the kinetic energy, resulting in a superexponential growth of the mean energy. These theoretical predictions are in good agreement with numerical simulations in a PT-symmetric nonlinear kicked particle. Our discovery establishes a mechanism of diffusion in interacting and dissipative quantum systems. Important implications and possible experimental observations are discussed.

关键词： Anderson localization Atomic, optical & lattice clocks Diffusion Nonlinear optics Quantum transport Spatiotemporal chaos Wave chaos

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Streaming Algorithms for the k-Submodular Cover Problem

arXiv

引用

arXiv 2023年

作者： Wang, Wenqi Gutin, Gregory Mao, Yaping Du, Donglei Zhang, Xiaoyan School of Mathematical Science Institute of Mathematics Nanjing Normal University Key Laboratory of Ministry of Education Numerical Simulation of Large Scale Complex Systems Nanjing210023 China Royal Holloway University of London Egham SurreyTW20 0EX United Kingdom School of Mathematics and Statistics Academy of Plateau Science and Sustainability Qinghai Normal University Qinghai Xining810008 China Faculty of Management University of New Brunswick FrederictonNBE3B9Y2 Canada

Given a natural number k ≥ 2, we consider the k-submodular cover problem (k-SC). The objective is to find a minimum cost subset of a ground set X subject to the value of a k-submodular utility function being at least a certain predetermined value τ. For this problem, we design a bicriteria algorithm with a cost at most O(1/ǫ) times the optimal value, while the utility is at least (1 − ǫ)τ/r, where r depends on the monotonicity of g. © 2023, CC BY.

关键词： Approximation algorithms

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Generation of orthogonal curvilinear grids on the sphere surface based on Laplace-Beltrami equations

引用

IOP Conference Series: Earth and Environmental Science 2014年第1期19卷

作者： Fuqiang Lu Zhiyao Song Xin Fang Key Laboratory of Virtual Geographic Environment (Ministry of Education) Nanjing Normal UniversityNanjing Jiangsu Province 210046 China AA(Jiangsu Provincial Key Laboratory for Numerical Simulation of Large Scale Complex Systems School of Mathematical Sciences Nanjing Normal University Nanjing 210046 China

In this paper, Laplace-Beltrami equations are used to generate orthogonal curvilinear grids on the sphere for ocean models. In addition to overcoming the pole-problem, the grid configuration has quasi-uniform cell-size on the whole sphere. Some quantities such as the grid length along two directions, the angle deviation from orthogonality, the area of the cell to evaluate the quality of the grid, which demonstrate the grid produced is fit to be a model grid on which the finite difference method or finite volume method can be implemented for numerical simulating of global atmosphere and ocean dynamics on large scale.

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