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3rd International Conference on Signal Processing, Computer Networks and Communications, SPCNC 2024

作者： Liang, Yajun Yan, Su Ma, Qian Huang, Shunlun Liu, Xin China Aerodynamics Research & Development Center Sichuan Mianyang China Science and Technology on Complex Aviation Systems Simulation Laboratory Beijing China State Key Laboratory of Air Traffic Management System Beijing China Beijing Aviation Meteorological Institute Beijing China

ISBN: (纸本)9798400710834

To enhance the convergence capability of grey wolf optimizer (GWO), this research investigates an evolved GWO using weighted-leader strategy (WLS), namely WLSGWO. The key issue of WLS is realizing the adaptive adjustment of position weighting according to the control parameters, thus well overcoming the drawback of premature convergence in the basic GWO. The newly developed method’s performance is assessed through experiments conducted on a standardized test suite. Additionally, comparisons are made by utilizing GWO alongside other advanced optimization techniques. The results of non-parametric studies validate the outperformance of the WLSGWO, thus proving the efficiency of the proposed strategy. © 2024 Copyright held by the owner/author(s).

关键词： Swarm intelligence

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Prediction of New Functional Fluorooxoborates with Expected Anionic Framework:A Case of CaB_(3)O_(5)F

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Chinese Physics Letters 2025年第3期42卷 85-92页

作者： Ke-Wang Zhang Wen-Qi Jin Ke Li Abudukadi Tudi Lin-Lin Liu Cong-Wei Xie Yu Xie Research Center for Crystal Materials CAS Key Laboratory of Functional Materials and Devices for Special Environmental ConditionsXinjiang Key Laboratory of Functional Crystal MaterialsXinjiang Technical Institute of Physics&ChemistryCASUrumqi 830011China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing 100049China Key Laboratory of Materials Simulation Methods&Software of Ministry of Education International Center of Future ScienceKey Laboratory of Physics and Technology for Advanced Batteries(Ministry of Education)College of PhysicsJilin UniversityChangchun 130012China

The prediction of new fluorooxoborates as ultraviolet(UV)/deep ultraviolet(DUV)opto-electronic functional materials from a largely unexplored chemical space is a challenging *** has been suggested that the anionic frameworks formed by B–O and B–O–F units significantly determine the physical properties of ***,the rational design of anionic frameworks could facilitate the materials discovery ***,we propose that a candidate anionic framework can be efficiently derived from an existing one by slightly altering its oxygen *** this idea,we hypothesized the existence of a 1D[B_(3)O_(5)F]_(∞)chain from the wellknown 2D[B_(6)O_(9)F_(2_)]_(∞)***,seven CaB_(3)O_(5)F structures with the expected anionic framework were successfully ***-principles calculations show that all these structures have potential in the UV/DUV birefringent or nonlinear optical(NLO)material field,indicating that the 1D[B_(3)O_(5)F]_(∞)chain is indeed a promising anionic framework for achieving UV/DUV birefringent and NLO performance.

关键词： process borate anionic

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Revealing atomic strengthening mechanism in CoNiV medium-entropy alloy via machine learning-guided simulations

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Journal of Materials science and technology 2025年 238卷 66-77页

作者： Li, Wenyue Liu, Xiongjun Liu, Leqing Du, Qing Lin, Deye Chen, Xin He, Dong Wang, Shudao Wu, Yuan Wang, Hui Jiang, Suihe Zhang, Xiaobin Lu, Zhaoping Beijing Advanced Innovation Center for Materials Genome Engineering State Key Laboratory for Advanced Metals and Materials University of Science and Technology Beijing Beijing100083 China School of Intelligent Manufacturing and Mechanical Engineering Hunan Institute of Technology Hengyang421002 China School of Materials Science and Engineering Ocean University of China Qingdao266100 China CAEP Software Center for High Performance Numerical Simulation Beijing100088 China Institute of Applied Physics and Computational Mathematics Beijing100094 China School of Materials Science and Engineering Dalian University of Technology Dalian116024 China

High/medium entropy alloys (H/MEAs) have shown unique strengthening behavior and mechanical properties because of the presence of massive local chemical orderings. Nevertheless, dynamic interactions between chemical short-range orders (CSROs) and dislocations, and the underlying atomic strengthening mechanism remain elusive. In this work, we first developed a novel machine learning-embedded atom method (ML-EAM) potential of the CoNiV system, trained on a comprehensive first-principles dataset, which enables accurate and efficient modeling of CSRO formation and dislocation dynamics. Then, we investigated the strengthening mechanisms of CSROs in CoNiV MEA through machine learning-augmented molecular dynamics (MD) simulations. Hybrid MD/Monte Carlo simulations reveal that CSRO domains possess an L12 (NiCo)3 V structure, whose size increases with lowering annealing temperatures. These domains significantly enhance strength by impeding dislocation motion through complex energy pathways, increasing depinning forces, and reducing mobility. Moreover, the MD simulations combined with theoretical analysis elucidate the competition between CSRO-assisted strengthening (via antiphase boundary formation) and solid solution weakening (via reduced atomic misfit volume). Phonon-drag effects are also amplified by CSROs, further resisting dislocation glide. Our results demonstrate that L12-CSROs strengthen CoNiV MEA primarily through antiphase boundary and phonon-drag contributions, providing new insights for designing high-performance multi-principal-element alloys via tailoring CSROs. © 2025

关键词： Turing machines

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Machine learning for membrane bioreactor research:principles,methods,applications,and a tutorial

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Frontiers of Environmental science & Engineering 2025年第3期19卷 119-144页

作者： Yizhe Lai Kang Xiao Yifan He Xian Liu Jihua Tan Wenchao Xue Aiqian Zhang Xia Huang Beijing Yanshan Earth Critical Zone National Research Station College of Resources and EnvironmentUniversity of Chinese Academy of SciencesBeijing 101408China Key Laboratory of Earth System Numerical Modeling and Application University of Chinese Academy of SciencesBeijing 101408China Environmental Chemistry Faculty College of Resources and EnvironmentUniversity of Chinese Academy of SciencesBeijing 101408China State Key Laboratory of Environmental Chemistry and Ecotoxicology Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China Department of Energy Environmentand Climate ChangeSchool of EnvironmentResourcesand DevelopmentAsian Institute of TechnologyP.O.Box 4Klong LuangPathumthani 12120Thailand State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing 100084China

Membrane fouling poses a significant challenge to the sustainable development of membrane bioreactor(MBR)technologies for wastewater *** accurate prediction of the membrane filtration process is of great importance for identifying and controlling *** learning methods address the limitations of traditional statistical approaches,such as low accuracy,poor generalization ability,and slow convergence,particularly in predicting complex filtration and fouling processes within the realm of big *** article provides an in-depth exposition of machine learning *** study then reviews advances in MBRs that utilize machine learning methods,including artificial neural networks(ANN),support vector machines(SVM),decision trees,and ensemble *** on current literature,this study summarizes and compares the model input and output characteristics(including foulant characteristics,solution environments,filtration conditions,operating conditions,and time factors),as well as the selection of models and optimization *** modeling procedures of SVM,random forest(RF),back propagation neural network(BPNN),long short-term memory(LSTM),and genetic algorithm-back propagation(GA-BP)methods are elucidated through a tutorial *** simulation results demonstrated that all five methods yielded accurate predictions with R2>***,the existing challenges in the implementation of machine learning models in MBRs were *** is notable that integration of deep learning,automated machine learning(AutoML)and explainable artificial intelligence(XAI)may facilitate the deployment of models in practical engineering *** insights presented here are expected to facilitate the establishment of an intelligent control framework for MBR processes in future endeavors.

关键词： Membrane bioreactor Machine learning Pollutant removal Membrane fouling Model prediction

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Engineering design of feedstock powder and relevant thermal-mechanical performance of thermal/environmental barrier coatings

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Journal of Advanced Ceramics 2025年第2期14卷 37-56页

作者： Xinchang Feng Fangwei Guo Lirong Luo Yuzhang Wang Yun Long Xiaofeng Zhao Fei Pan Lei Guo Qingfeng Zeng Jing Feng Chunlei Wan Shanghai Key Laboratory of Advanced High-temperature Materials and Precision Forming School of Materials Science and EngineeringShanghai Jiao Tong UniversityShanghai 200240China National Engineering Research Center of Special Equipment and Power System for Ship and Marine Engineering Shanghai 200030China School of Mechanical Engineering Shanghai Jiao Tong UniversityShanghai 200240China State Key Laboratory of Advanced Nuclear Energy Technology Nuclear Power Institute of ChinaChengdu 610213China Innovative Sensor Technology IST AG Ebnat-Kappel 9642Switzerland School of Materials Science and Engineering Tianjin UniversityTianjin 300072China Tianmushan Laboratory Hangzhou 311115China School of Materials Science and Engineering Kunming University of Science and TechnologyKunming 650093China State Key Laboratory of New Ceramics and Fine Processing School of Materials Science and EngineeringTsinghua UniversityBeijing 100084China

The development of aeroengine with a high thrust-weight ratio poses great challenges for current top-coating thermal barrier coatings (TBCs) and environmental barrier coatings (EBCs) in service. Medium/high-entropy ceramics are highly promising candidate material for advanced TBCs/EBCs owing to their low thermal conductivity, high melting point, high-temperature stability, and calcium–magnesium–alumino–silicate (CMAS) resistance. Most feedstock powder used for medium/high-entropy TBCs/EBCs is prepared via traditional spray drying, which cannot fully exploit the advantages of multicomponent ceramics. The density, sphericity, inner structure, and flowability of feedstock powder affect their melting state during the thermal spraying process, which strongly affects the microstructure and properties of the deposited coatings. Therefore, the deposited coatings exhibit phase segregation, amorphous phases, and microstructure defects owing to unpredictable variations in feedstock powder with random morphologies and structures. Here, the structure and properties of feedstock powder prepared by state-of-the-art granulation technologies and their influences on the deposited coatings were systematically investigated, which can provide guidance for configuration optimization of feedstock powder and the manufacturing accuracy of the deposited coating. This review aims to bridge the gap between cutting-edge ceramics and advanced engineering technologies, thus providing concrete background knowledge and crucial guidelines for designing and developing TBCs/EBCs.

关键词： thermal/environmental barrier coatings(TBCs/EBCs) spraying ceramic powder multiscale structure control high-entropy ceramics thermal-mechanical performance

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Fabrication of a high-power pump and signal combiner with an asymmetric tapered fiber bundle utilizing un-pretreated pump fibers

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Optics Express 2025年第6期33卷 12349-12360页

作者： Ji, Mengyuan Liu, Kai Chen, Wenqi Yi, Xuezhuan Wang, Meng Tian, Lei Meng, Junqing Wangzhijiang Innovation Center for Laser Aerospace Laser Technology and System Department Shanghai Institute of Optics and Fine Mechanics Chinese Academy of Sciences Shanghai201800 China Shanghai Key Laboratory of All Solid-State Laser and Applied Techniques Shanghai Institute of Optics and Fine Mechanics Chinese Academy of Sciences Shanghai201800 China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of Sciences Beijing100049 China Advanced Laser and Optoelectronic Functional Materials Department Special Glasses and Fibers Research Center Shanghai Institute of Optics and Fine Mechanics Chinese Academy of Sciences Shanghai201800 China Beijing Institute of Tracking and Telecommunication Technology Beijing100049 China

We report a fabrication method for addressing the non-uniform arrangement issues associated with the asymmetric tapered fiber bundles (TFBs) in high-power pump and signal combiners (PSCs), which do not require pre-treatment of the pump fibers. It employs a homemade thin-walled glass tube with the coating layer, and six pump fibers surround it evenly to collectively form the TFB, while the signal fiber remains unaffected during the tapering process of the fiber bundle. The 3D simulation model of the backward (6 + 1)×1 PSC was established by the refractive index distribution method to calculate the transmission efficiency of the pump light and signal light, and then identify the optimal preparation parameters for achieving the best efficiency. In this model, a simulated quasi-uniform energy distribution light field was used as the input of the pump fiber, which can optimize the previous calculation method. Experimental results exhibited that the backward (6 + 1)×1 PSC achieved signal light and pump light transmission efficiencies of over 96% and 98%, respectively, the beam quality degradation is ∆M2 = 0.09, and the total output pump power was 4.102 kW. The experimental results are in good agreement with the simulation results. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Refractive index

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Historical inventories and future scenarios of multiple hazardous air pollutants (HAPs) emissions from the iron and steel production industry in China

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science of the Total Environment 2025年 958卷 178051页

作者： Yang, Junqi Tian, Hezhong Fu, Zhiqiang Bai, Xiaoxuan Wang, Kun Liu, Wenjun Lu, Yiping Zhou, Yu Zhao, Hongyan Cui, Jiangyu Du, Qinwei State Key Joint Laboratory of Environmental Simulation & Pollution Control School of Environment Beijing Normal University Beijing100875 China Center for Atmospheric Environmental Studies Beijing Normal University Beijing100875 China Beijing100045 China Institute of Urban Safety and Environmental Science Beijing Academy of Science and Technology Beijing100054 China

Iron and steel production (ISP) is one of significant atmospheric pollution emission sources in China. With the implementation of ultra-low emission (ULE) standards, a detailed and new updated emission inventory is urgently needed for better understanding of the temporal trends and spatial variation of emission characteristics. In this study, a unit-based comprehensive emission inventory of multiple hazardous air pollutants (HAPs) for the Chinese ISP spanned from 2012 to 2021, including the conventional pollutants, 13 kinds of Trace elements as well as 2 unconventional but toxic pollutants (PCDD/Fs, F), was dedicatedly developed by integrating dynamic localized emission factors with unit-based information of both the detailed activity level and abatement technology application. Scenario analyses were also conducted to forecast future emission trends up to 2050. The results showed that the lower emission factors owing to ULE retrofits had resulted in different spatial-temporal emission characteristics between outputs and HAPs emissions. The atmospheric emissions of SO2, NOX, PM2.5, PM10, TSP, F and PCDD/Fs from Chinese ISP in 2021 were estimated at about 414.4, 450.5, 1044.3, 2001.6, 3958.8, 9.42 kt and 9.35 kg-TEQ, respectively. And most HAPs emissions were lower than those in 2012. Regarding the spatial distribution, Hebei, Jiangsu, Shanxi, ranked as the top 3 emission provinces. Moreover, different manufacturing processes (sintering, blast furnace, steel making, etc.) contributed with different magnitude for specific species, and the future trends estimation showed a great reducing potential caused by the implementation of ULE abatement measures and structure adjustment in future. © 2024 Elsevier B.V.

关键词： Iron and steel industry

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Scattering center Modeling Using Adaptive Segmental Compressive Sampling

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Journal of beijing Institute of technology 2017年第4期26卷 484-493页

作者： Qifeng Li Kunyi Guo Jiaxin Wang Xinqing Sheng Tianshu Liu Center for Electromagnetic Simulation School of Information and ElectronicsBeijing Institute of Technology Science and Technology on Special System Simulation Laboratory Beijing Simulation Center

In order to deal with aliasing distortions of Doppler frequencies shown in time-frequency representation（ TFR） with aspect undersampling,an approach using adaptive segmental compressive sampling according to the aspect dependencies of the scattering centers is proposed. The random noise problem induced by compressive sampling is solved by employing a series of signal processing techniques of filtering,image transformation and Hough Transform. Three examples are presented to verify the effectiveness of this approach. The comparisons between the built models and the precise scattered fields computed by a well-validated full-wave numerical method are investigated,and the results showgood agreements between each other.

关键词： scattering center undersampling compressive sensing time-frequency representation parameter estimation

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The effect of external magnetic field on projectile in the stopping power of warm dense deuterium for electrons

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The European Physical Journal special Topics 2025年 1-16页

作者： Chen, Yuzhu Mo, Chongjie Xue, Quanxi Fu, Zhenguo Liu, Hao Department of Applied Physics School of Physics and Electronics Hunan University Changsha China Beijing Computational Science Research Center Beijing China State Key Laboratory of Intense Pulsed Radiation Simulation and Effect Northwest Institute of Nuclear Technology Xi’an China Institute of Applied Physics and Computational Mathematics Beijing China

The stopping power of warm dense plasmas for electrons is a critical aspect in the study of hot electron transport. An externally applied strong magnetic field can significantly influence electron transport behavior due to various factors. However, the impact of external magnetic fields on the motion of incident particles is often overlooked. Through molecular dynamics simulations using the electron force field (eFF) method, this study investigates the stopping process of individual hot electrons in warm dense deuterium plasma under an applied longitudinal magnetic field. Results show that, at typical laboratory magnetic field intensities, the magnetic field significantly alters electron trajectories without notable effects on average stopping power, trajectory length, or scattering angle. Even with increased magnetic field intensity beyond 500 kT, it doesn’t affect the total kinetic energy loss of incident electrons but reduces stopping power by compressing the scattering angle distribution width. Due to the increase in the scattering angle distribution width with intensified fluctuations in high-temperature targets, the impact of the additional magnetic field on stopping power becomes more pronounced with an increase in target temperature.

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A fast calculation method for three-impulse contingency return trajectory during the near-moon phase based on differential algebra

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Chinese Journal of Aeronautics 2025年第04期 290-308页

作者： Lin LU Haiyang LI Tianshan DONG Wanmeng ZHOU College of Aerospace Science and Technology National University of Defense Technology Hunan Key Laboratory of Intelligent Planning and Simulation for Aerospace Missions Beijing Institute of Spacecraft System Engineering China Astronaut Research and Training Center

Aimed at the demand of contingency return at any time during the near-moon phase in the manned lunar landing missions,a fast calculation method for three-impulse contingency return trajectories is ***,a three-impulse contingency return trajectory scheme is presented by combining the Lambert transfer and maneuver at the special ***,a calculation model of three-impulse contingency return trajectories is ***,fast calculation methods are proposed by adopting the high-order Taylor expansion of differential algebra in the twobody trajectory dynamics model and perturbed trajectory dynamics ***,the performance of the proposed methods is verified by numerical *** results indicate that the fast calculation method of two-body trajectory has higher calculation efficiency compared to the semi-analytical calculation method under a certain accuracy *** to its high efficiency,the characteristics of the three-impulse contingency return trajectories under different contingency scenarios are further analyzed *** findings can be used for the design of contingency return trajectories in future manned lunar landing missions.

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