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Journal of Systems Science & Complexity 2024年第2期37卷 511-544页

作者： zhou Huijuan School of Science Shanghai Maritime UniversityShanghai 201306China

This paper mainly introduces the parallel physics-informed neural networks(PPINNs)method with regularization strategies to solve the data-driven forward-inverse problems of the variable coefficient modified Korteweg-de Vries(VC-MKdV)*** the forward problem of the VC-MKdV equation,the authors use the traditional PINN method to obtain satisfactory data-driven soliton solutions and provide a detailed analysis of the impact of network width and depth on solving accuracy and ***,the author finds that the traditional PINN method outperforms the one with locally adaptive activation functions in solving the data-driven forward problems of the VC-MKdV *** for the data-driven inverse problem of the VC-MKdV equation,the author introduces a parallel neural networks to separately train the solution function and coefficient function,successfully addressing the function discovery problem of the VC-MKdV *** further enhance the network’s generalization ability and noise robustness,the author incorporates two regularization strategies into the *** amount of numerical experimental data in this paper demonstrates that the PPINNs method can effectively address the function discovery problem of the VC-MKdV equation,and the inclusion of appropriate regularization strategies in the PPINNs can improves its performance.

关键词： Data-driven forward-inverse problems parallel physics-informed neural networks regularization strategies variable coefficient modified KdV equation

Influence of stearic acid surface modification on flowability and agglomeration of battery grade Li_(2)CO_(3)powder

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Particuology 2024年第9期92卷 263-277页

作者： Ming zhou Lithium Industry Center Zhejiang New Era Zhongneng Technology Co.Ltd.Shaoxing312000China

This work investigates the flow and agglomeration behaviors of battery grade Li_(2)CO_(3)powder and the influence of stearic acid surface *** degree of agglomeration is directly related to the uniformity of Li_(2)CO_(3)and its powder *** to the Chinese National Nonferrous Metal Industry Standard,battery grade Li_(2)CO_(3)powder has D50 equal to 3–8μm which belongs to a micron-sized superfine ***,with the extension of storage time,the serious agglomeration phenomenon occurs due to the large specific surface area and rough and irregular powder *** Hausner ratio(HR)of the unmodified sample increases from 1.14 to 1.41,and the corresponding flowability is classified as good to ***,among samples with doping stearic acid,the optimum amount of it is 0.10 wt%which exhibits an extremely stable HR value from 1.14 to ***,after 156 days,the repose angle(AR)obtained for samples without surface modification and using 0.10 wt%stearic acid are calculated to be 49°and 28°,*** on the values of HR and AR,the flowability of the unmodified sample is poor while the sample modified with 0.10 wt%of stearic acid still maintain excellent powder flow ***,The LiMn_(2)O_(4)cathode material synthesized from modified Li_(2)CO_(3)powder with a stearic acid content of 0.10 wt%exhibits good crystallinity and comparable electrochemical performance to that prepared by commercial Li_(2)CO_(3).These results indicate that stearic acid has the potential to be an ideal modifier for battery grade Li_(2)CO_(3)powder that needs to be kept for a long time.

关键词： Battery grade Li_(2)CO_(3)powder Flowability Surface modification Stearic acid

Phase field modeling of ferroelastic variant switching in yttria-stabilized t'zirconia with strain gradient elasticity and interface tension

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Science China(Technological Sciences) 2024年第5期67卷 1443-1457页

作者： zhou QianQian WEI YueGuang zhou YiChun YANG Li College of Engineering BIC-ESATPeking UniversityBeijing100871China School of Advanced Materials and Nanotechnology Xidian UniversityXi’an710126China Frontier Research Center of Thin Films and Coatings for Device Applications Academy of Advanced Interdisciplinary ResearchXidian UniversityXi’an710126China

The 6–8 wt%yttria-stabilized zirconia with a tetragonal structure(t’-YSZ)is extensively employed in thermal barrier *** exceptional fracture toughness of t’-YSZ can be attributed to its distinctive ferroelastic toughening *** and interface tension play a critical role in ferroelastic variant switching at the micro-and *** paper presents an original thermodynamically consistent phase field(PF)theory for analyzing ferroelastic variant switching at the micro-and nano-scale of t’-*** theory incorporates strain gradient elasticity using higher-order elastic energy and interface tension tensor via geometric nonlinearity to represent biaxial tension resulting from interface ***,a mixed-type formulation is employed to implement the higher-order theory through the finite element *** an interface in equilibrium,the effects of strain gradient elasticity result in a more uniform distribution of stresses,whereas the presence of interface tension tensor significantly amplifies the stress magnitude at the *** introduction of an interface tension tensor increases the maximum value of stress at the interface by a factor of 4 to *** nucleation and evolution of variants at a pre-existing crack tip in a mono-phase t’-YSZ have also been *** strain gradient elasticity is capable of capturing the size effect of ferroelastic variant switching associated with microstructures in ***,when the grain size approaches that of the specimen,the critical load required for variant switching at the crack tip increases,resulting in greater dissipation of elastic energy during ferroelastic variant ***,the interface tension accelerates the evolution of *** presented framework exhibits significant potential in modeling ferroelastic variant switching at the micro-and nano-scale.

关键词： thermodynamics strain gradient elasticity interface tension phase field method ferroelastic variant switching

Oxidation of emerging organic contaminants by in-situ H_(2)O_(2) fenton system

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Green Energy & Environment 2024年第3期9卷 417-434页

作者： Yuqin Ni Chuxiang zhou Mingyang Xing Yi zhou State Environmental Protection Key Lab of Environmental Risk Assessment and Control on Chemical Processes School of Resources&Environmental EngineeringEast China University of Science and TechnologyShanghai200237China Key Laboratory for Advanced Materials and Institute of Fine Chemicals National Engineering Laboratory for Industrial Wastewater TreatmentSchool of Chemistry and Molecular EngineeringEast China University of Science and Technology130 Meilong RoadShanghai200237China Department of Applied Natural Sciences Technische Hochschule LubeckMonkhofer Weg 23923562 LubeckGermany

The existence and risk of emerging organic contaminants(EOCs)have been under consideration and paid much effort to degrade these *** system is one of the most widely used technologies to solve this *** original Fenton system relies on the hydroxyl radicals produced by Fe(Ⅱ)/H_(2)O_(2) to oxidize the organic ***,the application of the Fenton system is limited by its low iron cycling efficiency and the high risks of hydrogen peroxide transportation and *** introduction of external energy(including light and electricity etc.)can effectively promote the Fe(Ⅲ)/Fe(Ⅱ)cycle and the reduction of oxygen to produce hydrogen peroxide in *** review introduces three in-situ Fenton systems,which are electro-Fenton,Photo-Fenton,and chemical *** mechanism,influencing factors,and catalysts of these three in-situ Fenton systems in degrading EOCs are discussed *** review strengthens the understanding of Fenton and in-situ Fenton systems in degradation,offering further insight into the real application of the in-situ Fenton system in the removal of EOCs.

关键词： In-situ H_(2)O_(2)production Fenton Emerging organic contaminants Photocatalysis Electrocatalysis

Inverse aerodynamic design for distributed propulsion wing with expected circulation distribution

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Chinese Journal of Aeronautics 2024年第9期37卷 206-223页

作者： Pengbo SUN zhou zhou Xu LI Kelei WANG School of Aeronautics Northwestern Polytechnical UniversityXi'an 710072China

Distributed Propulsion Wing(DPW)technology offers significant advantages in terms of flight energy savings,but the strong aerodynamic coupling between the propulsive internal flow and aerodynamic external flow brings significant design *** the primary DPW profile design is of great significance,this paper proposes a hybrid method to solve the inverse problem mainly based on the formula relationship between the required aerodynamic loads and the profile shape,which is more direct and instructive compared with traditional parametric iterative *** aerodynamic characteristics are described by the circulation distribution in the Fourier series form,then the mean camber line of the profile is solved through the re-derived airfoil theory considering disk's *** CFD correction methods are also *** validate the effectiveness and feasibility of the proposed hybrid inverse method,several DPW profile design tests are then ***,the relationship between 2D and realistic 3D unit shape is also *** results show that the proposed inverse design method has great accuracy and convergence speed in the design tests,and shows good robustness against changes of the design *** 2D profile shape and the actual 3D shape of DPW unit can establish an aerodynamic-propulsion equivalent relationship based on the same internal mass fluxes.

关键词： Propulsion Inverse problem Aerodynamic load Fourier series Flux

Deep-reinforcement-learning-based UAV autonomous navigation and collision avoidance in unknown environments

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Chinese Journal of Aeronautics 2024年第3期37卷 237-257页

作者： Fei WANG Xiaoping ZHU zhou zhou Yang TANG School of Astronautics Northwestern Polytechnical UniversityXi’an 710072China School of Aeronautics Northwestern Polytechnical UniversityXi’an 710072China

In some military application scenarios,Unmanned Aerial Vehicles(UAVs)need to perform missions with the assistance of on-board cameras when radar is not available and communication is interrupted,which brings challenges for UAV autonomous navigation and collision *** this paper,an improved deep-reinforcement-learning algorithm,Deep Q-Network with a Faster R-CNN model and a Data Deposit Mechanism(FRDDM-DQN),is proposed.A Faster R-CNN model(FR)is introduced and optimized to obtain the ability to extract obstacle information from images,and a new replay memory Data Deposit Mechanism(DDM)is designed to train an agent with a better *** training,a two-part training approach is used to reduce the time spent on training as well as retraining when the scenario *** order to verify the performance of the proposed method,a series of experiments,including training experiments,test experiments,and typical episodes experiments,is conducted in a 3D simulation *** results show that the agent trained by the proposed FRDDM-DQN has the ability to navigate autonomously and avoid collisions,and performs better compared to the FRDQN,FR-DDQN,FR-Dueling DQN,YOLO-based YDDM-DQN,and original FR outputbased FR-ODQN.

关键词： Faster R-CNN model Replay memory Data Deposit Mechanism(DDM) Two-part training approach Image-based Autonomous Navigation and Collision Avoidance(ANCA) Unmanned Aerial Vehicle(UAV)

SPARSE RECOVERY BASED ON THE GENERALIZED ERROR FUNCTION

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Journal of Computational Mathematics 2024年第3期42卷 679-704页

作者： Zhiyong zhou Department of Statistics and Data Science and Institute of Digital FinanceHangzhou City UniversityHangzhou 310015China

In this paper,we offer a new sparse recovery strategy based on the generalized error *** introduced penalty function involves both the shape and the scale parameters,making it extremely *** both constrained and unconstrained models,the theoretical analysis results in terms of the null space property,the spherical section property and the restricted invertibility factor are *** practical algorithms via both the iteratively reweighted■_(1)and the difference of convex functions algorithms are *** experiments are carried out to demonstrate the benefits of the suggested approach in a variety of *** practical application in magnetic resonance imaging(MRI)reconstruction is also investigated.

关键词： Sparse recovery Generalized error function Nonconvex regularization Itera-tive reweighted Li Difference of convex functions algorithms

Emergent Geometry of KP Hierarchy

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Acta Mathematica Sinica,English Series 2024年第1期40卷 3-25页

作者： Jian zhou Department of Mathematical Sciences Tsinghua UniversityBeijng 100084P.R.China

We explain how to construct a quantum deformation of a spectral curve associated to a tau-function of the KP *** construction is applied to Witten-Kontsevich tau-function to give a natural explanation of some earlier ... 详细信息

关键词： KP hierarchy tau-functions spectral curves

The dry-hot feedback between soil moisture and atmosphere and the accelerated global warming

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Science China Earth Sciences 2024年第3期67卷 890-891页

作者： Tianjun zhou State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics(LASG) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China

Greenhouse gas (GHG) emissions have been increasing due to human activities since the Industrial Revolution, resulting in continuous warming of the global climate system and significant drought over a large parts of global land, both have shown a non-linear growth trend in recent decades(Berg et al., 2017;zhou et al., 2019;IPCC, 2021).

关键词： warming moisture drought

Surface wave inversion with unknown number of soil layers based on a hybrid learning procedure of deep learning and genetic algorithm

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Earthquake Engineering and Engineering Vibration 2024年第2期23卷 345-358页

作者： Zan zhou Thomas Man-Hoi Lok Wan-Huan zhou Department of Civil and Environmental Engineering Faculty of Science and TechnologyUniversity of MacaoMacaoChina

Surface wave inversion is a key step in the application of surface waves to soil velocity ***,a common practice for the process of inversion is that the number of soil layers is assumed to be known before using heuristic search algorithms to compute the shear wave velocity profile or the number of soil layers is considered as an optimization ***,an improper selection of the number of layers may lead to an incorrect shear wave velocity *** this study,a deep learning and genetic algorithm hybrid learning procedure is proposed to perform the surface wave inversion without the need to assume the number of soil ***,a deep neural network is adapted to learn from a large number of synthetic dispersion curves for inferring the layer ***,the shear-wave velocity profile is determined by a genetic algorithm with the known layer *** applying this procedure to both simulated and real-world cases,the results indicate that the proposed method is reliable and efficient for surface wave inversion.

关键词： surface wave inversion analysis shear-wave velocity profile deep neural network genetic algorithm