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On Energy Stable Runge-Kutta Methods for the Water Wave Equation and its Simplified Non-Local Hyperbolic Model

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Communications in Computational Physics 2022年第6期32卷 222-258页

作者： Lei Li jian-guo liu Zibu liu Yi Yang Zhennan Zhou School of Mathematical Sciences Institute of Natural SciencesMOE-LSCShanghai Jiao Tong UniversityShanghai200240P.R.China Department of Mathematics and Department of Physics Duke UniversityDurhamNC 27708USA Department of Mathematics Duke UniversityDurhamNC 27708USA Nanjing Research Institute of Electronics Technology NanjingP.R.China Beijing International Center for Mathematical Research Peking UniversityP.R.China

Although interest in numerical approximations of the water wave equationgrows in recent years, the lack of rigorous analysis of its time discretization inhibits thedesign of more efficient algorithms. In practice of water wave simulations, the tradeoff between efficiency and stability has been a challenging problem. Thus to shed lighton the stability condition for simulations of water waves, we focus on a model simpli-fied from the water wave equation of infinite depth. This model preserves two mainproperties of the water wave equation: non-locality and hyperbolicity. For the constantcoefficient case, we conduct systematic stability studies of the fully discrete approximation of such systems with the Fourier spectral approximation in space and generalRunge-Kutta methods in time. As a result, an optimal time discretization strategy isprovided in the form of a modified CFL condition, i.e. ∆t = O(√∆x). Meanwhile,the energy stable property is established for certain explicit Runge-Kutta *** CFL condition solves the problem of efficiency and stability: it allows numericalschemes to stay stable while resolves oscillations at the lowest requirement, which onlyproduces acceptable computational load. In the variable coefficient case, the convergence of the semi-discrete approximation of it is presented, which naturally connectsto the water wave equation. Analogue of these results for the water wave equationof finite depth is also discussed. To validate these theoretic observation, extensive numerical tests have been performed to verify the stability conditions. Simulations of thesimplified hyperbolic model in the high frequency regime and the water wave equation are also provided.

关键词： Runge-Kutta methods non-locality hyperbolicity

Random Walk Approximation for Irreversible Drift-Diffusion Process on Manifold:Ergodicity,Unconditional Stability and Convergence

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Communications in Computational Physics 2023年第6期33卷 132-172页

作者： Yuan Gao jian-guo liu Department of Mathematics Purdue UniversityWest LafayetteINUSA Departments of Mathematics and Physics Duke UniversityDurhamNCUSA

Irreversible drift-diffusion processes are very common in biochemical *** have a non-equilibrium stationary state(invariant measure)which does not satisfy detailed *** the corresponding Fokker-Planck equation on a closed manifold,using Voronoi tessellation,we propose two upwind finite volume schemes with or without the information of the invariant *** schemes possess stochastic Q-matrix structures and can be decomposed as a gradient flow part and a Hamiltonian flow part,enabling us to prove unconditional stability,ergodicity and error *** on the two upwind schemes,several numerical examples–including sampling accelerated by a mixture flow,image transformations and simulations for stochastic model of chaotic system–are *** two structurepreserving schemes also give a natural random walk approximation for a generic irreversible drift-diffusion process on a *** makes them suitable for adapting to manifold-related computations that arise from high-dimensional molecular dynamics simulations.

关键词： Symmetric decomposition non-equilibrium thermodynamics enhancement by mixture exponential ergodicity structure-preserving numerical scheme

Environmental benefits and farmers' adoption of winter cover crops in the North China Plain

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Pedosphere 2024年第1期34卷 159-169页

作者： Shufang guo Yitao ZHANG Limei ZHAI jian liu Hongyuan WANG Hongbin liu State Key Laboratory of Efficient Utilization of Arid and Semi-arid Arable Land in Northern China Key Laboratory of Nonpoint Source Pollution ControlMinistry of Agriculture and Rural AffairsInstitute of Agricultural Resources and Regional PlanningChinese Academy of Agricultural SciencesBeijing 100081China Institute of Agricultural Environment and Resources Yunnan Academy of Agricultural SciencesKunming 650205China Shandong Yucheng Agro-ecosystem National Observation Research Station Key Laboratory of Ecosystem Network Observation and ModelingInstitute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China The Norwegian Institute of Bioeconomy Research(NIBIO) Akershus 1431Norway

The introduction of cover crops into monoculture systems to improve soil health has been widely adopted worldwide. However, little is known about the environmental risks and application prospects of different cover crops in spring maize(Zea mays L.) monocultures proposed in the North China Plain. A pot experiment was conducted to evaluate the effects of different winter cover crops on subsequent maize yield, soil fertility, and environmental risks of nitrogen(N) loss, and a questionnaire survey was conducted to examine factors influencing farmers' willingness to adopt cover crops in the North China Plain. Based on the same fertilization regime during the maize growing period, four winter cover crop treatments were set up, including bare fallow, hairy vetch(Vicia villosa Roth.), February orchid(Orychophragmus violaceus), and winter oilseed rape(Brassica campestris L.). The results indicated that winter cover crops significantly increased subsequent maize yield and soil organic carbon, total N, and microbial biomass carbon and N compared with the bare fallow *** incorporation of cover crops led to a negligible increase in nitrous oxide(N_(2)O) emissions and had a very limited effect on ammonia(NH_(3)) *** incorporation of February orchid and winter oilseed rape decreased nitrate leaching compared with the hairy vetch treatment in the maize growing *** N losses via N_(2)O and NH_(3) emissions and N leaching accounted for 71%–84% of the N surplus. However, yield increase and environmental benefits were not the main positive factors for farmers to accept cover crops. Financial incentive was rated by 83.9% of farmers as an “extremely important” factor, followed by other costs, when considering winter cover cropping. These results indicate that the environmental benefits depend on the type of cover crop. Maintaining high levels of soil fertility and maize yield, providing sufficient subsidies, and encouraging large-area cultivation of cover crops

关键词： cover crop N leaching NH_(3)emission N_(2)O emission spring maize willingness to accept

Improving mathematical model of burden distribution and correcting chute angle to cope with fluctuation of stock line

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Journal of Iron and Steel Research(International) 2024年第2期31卷 342-356页

作者： jian-sheng Chen Wen-guo liu Hao guo Wang Ding Qing-guo Xue Jing-song Wang Hai-bin Zuo State Key Laboratory of Advanced Metallurgy University of Science and Technology BeijingBeijing100083China MCC Capital Engineering&Research Incorporation Limited Beijing100176China Hunan Valin Xiangtan Iron and Steel Co. Ltd.Xiangtan411101HunanChina

Accurate evaluations of the burden distribution are of critical importance to stabilize the operation of blast *** mathematical model and discrete element method(DEM)are two attractive methods for predicting burden *** on DEM,the initial velocities of the pellet,sinter,and coke were calculated,and the velocity attenuations of the above three particles between the burden and the chute were *** initial velocity and velocity attenuation were applied to a mathematical model for improving the ***,based on the improved model,a scheme for rectifying the chute angles was proposed to address the fluctuation of the stock line and maintain a stable burden *** validity of the scheme was confirmed via a stable burden distribution under different stock *** mathematical model has been successfully applied to evaluate the online burden distribution and cope with the fluctuation of the stock line.

关键词： Burden distribution Mathematical model Discrete element method Velocity attenuation Stock line fluctuation

Attaining synergetic equilibrium of electrical conductivity and tensile strength in GQDs@GN/Cu composites through multi-scale intragranular and intergranular reinforcements

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Rare Metals 2024年第1期43卷 366-379页

作者： Shuang-Yin Zhang Liang liu Rui Bao jian-Hong Yi Sheng-Da guo Faculty of Materials Science and Engineering Kunming University of Science and TechnologyKunming 650093China Key Laboratory of Advanced Materials of Yunnan Province Kunming University of Science and TechnologyKunming 650093China Faculty of Materials Metallurgy and Chemistry Jiangxi University of Science and TechnologyGanzhou 341000China

The configuration and quality of reinforcements, as well as the robustness of interfacial bonding,holding a critical significance in determining the concurrence between electrical conductivity and mechanical strength in metal matrix composites. In this study, citric acid was employed as the precursor for synthesizing multiscale carbon nanomaterials(graphene quantum dots and graphene, abbreviated as GQDs and GN). The GQDs@GN/Cu composites were fabricated through a segmented ball milling process in conjunction with subsequent spark plasma sintering(SPS). The intragranular GQDs and intergranular GQDs@GN had synergistically reinforced Cu composites through Orowan strengthening, load transfer strengthening and refinement strengthening. Furthermore,the robust interface bonding between GQDs@GN and Cu effectively mitigated interfacial impedance stemming from electron-boundary scattering. The yield strength and ultimate tensile strength of the GQDs@GN/Cu composites were recorded as 270 and 314 MPa, respectively, representing an improvement of 92 and 28% over pure Cu, while maintaining electrical conductivity at a level comparable to that of pure Cu. This study advances the understanding of the possibility of realizing a synergistic compatibility between electrical conductivity and mechanical strength in Cu composites.

关键词： Cu matrix composites Interface bonding Mechanical property Graphene quantum dots(GQDs) Electrical conductivity

Hybrid Model of Power Transformer Fault Classification Using C-set and MFCM – MCSVM

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CSEE Journal of Power and Energy Systems 2024年第2期10卷 672-685页

作者： Ali Abdo Hongshun liu Yousif Mahmoud Hongru Zhang Ying Sun Qingquan Li jian guo Shandong Provincial Key Laboratory of UHV Transmission Technology and Equipment School of Electrical EngineeringShandong UniversityJinan 250061China

This paper aims to increase the diagnosis accuracy of the fault classification of power transformers by introducing a new off-line hybrid model based on a combination subset of the et method(C-set)&modified fuzzy C-mean algorithm(MFCM)and the optimizable multiclass-SVM(MCSVM).The innovation in this paper is shown in terms of solving the predicaments of outliers,boundary proportion,and unequal data existing in both traditional and intelligence *** into consideration the closeness of dissolved gas analysis(DGA)data,the C-set method is implemented to subset the DGA data samples based on their type of faults within unrepeated ***,the MFCM is used for removing outliers from DGA samples by combining highly similar data for every subset within the same cluster to obtain the optimized training data(OTD)*** is also used to minimize dimensionality of DGA samples and the uncertainty of transformer condition *** that,the optimized MCSVM is trained by using the(OTD).The proposed model diagnosis accuracy is 93.3%.The obtained results indicate that our model significantly improves the fault identification accuracy in power transformers when compared with other conventional and intelligence models.

关键词： Combination subset of set(C-set)method modified fuzzy C-means(MFCM) optimizable multiclass-SVM(MCSVM) optimized training data(OTD)

Neoantigen cancer vaccines:a new star on the horizon

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Cancer Biology & Medicine 2024年第4期21卷 274-311页

作者： Xiaoling Li jian You Liping Hong Weijiang liu Peng guo Xishan Hao Cell Biotechnology Laboratory Tianjin Cancer Hospital Airport HospitalTianjin 300308China National Clinical Research Center for Cancer Tianjin 300060China Haihe Laboratory of Synthetic Biology Tianjin 300090China Department of Thoracic Oncology Tianjin Cancer Hospital Airport HospitalTianjin 300308China Department of Thoracic Oncology Surgery Tianjin Medical University Cancer Institute&HospitalTianjin 300060China Tianjin Medical University Cancer Institute&Hospital Tianjin 300060China

Immunotherapy represents a promising strategy for cancer treatment that utilizes immune cells or drugs to activate the patient's own immune system and eliminate cancer *** of the most exciting advances within this field is the targeting of neoantigens,which are peptides derived from non-synonymous somatic mutations that are found exclusively within cancer cells and absent in normal *** neoantigen-based therapeutic vaccines have not received approval for standard cancer treatment,early clinical trials have yielded encouraging outcomes as standalone monotherapy or when combined with checkpoint *** made in high-throughput sequencing and bioinformatics have greatly facilitated the precise and efficient identification of ***,personalized neoantigen-based vaccines tailored to each patient have been developed that are capable of eliciting a robust and long-lasting immune response which effectively eliminates tumors and prevents *** review provides a concise overview consolidating the latest clinical advances in neoantigen-based therapeutic vaccines,and also discusses challenges and future perspectives for this innovative approach,particularly emphasizing the potential of neoantigen-based therapeutic vaccines to enhance clinical efficacy against advanced solid tumors.

关键词： Immunotherapy neoantigen cancer vaccine solid tumors high-throughput sequencing bioinformatics PDOs AI HLA TCR

Harnessing data using symbolic regression methods for discovering novel paradigms in physics

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Science China(Physics,Mechanics & Astronomy) 2024年第6期67卷 1-11页

作者： jianyang guo Wan-jian Yin College of Energy Soochow Institute for Energy and Materials Innovations(SIEMIS)Jiangsu Provincial Key Laboratory for Advanced Carbon Materials and Wearable Energy TechnologiesSoochow UniversitySuzhou 215006China Shanghai Qi Zhi Institute Shanghai 200232China Light Industry Institute of Electrochemical Power Sources Soochow UniversitySuzhou 215006China

In recent years,machine-learning methods have profoundly impacted research in the interdisciplinary fields of ***,most machine-learning models lack interpretability,and physicists doubt the credibility of their conclusions because they cannot be combined with prior physical ***,this review focuses on symbolic regression,which is an interpretable machine-learning ***,the relevant concepts of machine learning are introduced in conjunction with ***,we provide an overview of symbolic regression ***,the recent directions for the application of symbolic regression methods in different subfields of physics are outlined,and an overview of the ways in which the applications of symbolic regression have evolved in the realm of physics is *** major aim of this review is to introduce the basic principles of symbolic regression and explain its applications in the field of physics.

关键词： machine learning genetic programming symbolic regression

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MADRL-based UAV swarm non-cooperative game under incomplete information

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Chinese Journal of Aeronautics 2024年第6期37卷 293-306页

作者： Ershen WANG Fan liu Chen HONG Jing guo Lin ZHAO jian XUE Ning HE School of Electronic and Information Engineering Shenyang Aerospace UniversityShenyang 110136China College of Robotics Beijing Union UniversityBeijing 100101China School of Engineering Science University of Chinese Academy of SciencesBeijing 100049China College of Smart City Beijing Union UniversityBeijing 100101China

Unmanned Aerial Vehicles(UAVs)play increasing important role in modern *** this paper,considering the incomplete observation information of individual UAV in complex combat environment,we put forward an UAV swarm non-cooperative game model based on Multi-Agent Deep Reinforcement Learning(MADRL),where the state space and action space are constructed to adapt the real features of UAV swarm air-to-air *** multi-agent particle environment is employed to generate an UAV combat scene with continuous observation *** recently popular MADRL methods are compared extensively in the UAV swarm noncooperative game model,the results indicate that the performance of Multi-Agent Soft Actor-Critic(MASAC)is better than that of other MADRL methods by a large *** swarm employing MASAC can learn more effective policies,and obtain much higher hit rate and win *** under different swarm sizes and UAV physical parameters are also performed,which implies that MASAC owns a well generalization ***,the practicability and convergence of MASAC are addressed by investigating the loss value of Q-value networks with respect to individual UAV,the results demonstrate that MASAC is of good practicability and the Nash equilibrium of the UAV swarm non-cooperative game under incomplete information can be reached.

关键词： UAV swarm Reinforcement learning Deep learning Multi-agent Non-cooperative game Nash equilibrium