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Chinese Journal of Aeronautics 2024年第3期37卷 404-416页

作者： Huibin SUN Meng LIU Yingzhi zhang Chenle wei Key Laboratory of High Performance Manufacturing for Aero Engine Ministry of Industry and Information TechnologyNorthwestern Polytechnical UniversityXi’an 710072China AECC South Industry Company Limited Zhuzhou 412002China

Due to the excellent self-centering and load-carrying capability,curvic couplings have been widely used in advanced aero-engine ***,curvic tooth surface errors lead to poor assembly *** physical-master-gauge-based indirect tooth surface error measurement and circumferential assembly angle optimization methods have the disadvantages of high cost and weak *** unknown tooth surface fitting mechanism is a big barrier to assembly precision prediction and ***,this work puts forward a data-driven assembly simulation and optimization approach for aero-engine rotors connected by curvic *** origin of curvic tooth surface error is deeply *** 5-axis sweep scan method,a large amount of high-precision curvic tooth surface data are acquired *** on geometric models of parts,the fitting mechanism of curvic couplings is uncovered for assembly precision simulation and prediction.A circumferential assembly angle optimization model is developed to decrease axial and radial assembly *** results show that the assembly precision can be predicted accurately and improved *** uncovering the essential principle of the assembly precision formation and proposing circumferential assembly angle optimization model,this work is meaningful for assembly quality,efficiency and economy improvement of multistage aero-engine rotors connected by curvic couplings.

关键词： Curvic couplings Tooth surface error Assembly precision Axial and radial runouts Circumferential assembly angle

Counteracting effects on ENSO induced by ocean chlorophyll interannual variability and tropical instability wave-scale perturbations in the tropical Pacific

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Science China Earth Sciences 2024年第2期67卷 387-404页

作者： Rong-Hua zhang Feng tian Qidong SHI Xiujun WANG Tongwen WU School of Marine Sciences Nanjing University of Information Science and TechnologyNanjing210044China Laoshan Laboratory Qingdao266237China Key Laboratory of Ocean Circulation and Waves Institute of OceanologyChinese Academy of SciencesQingdao266071China University of Chinese Academy of Sciences Beijing101408China Faculty of Geographical Sciences Beijing Normal UniversityBeijing100875China Earth System Modeling and Prediction Centre China Meteorological AdministrationBeijing100081China

Large perturbations in chlorophyll(Chl)are observed to coexist at interannual and tropical instability wave(TIW)scales in the tropical Pacific;at present,their combined effects on El Ni?o-Southern Oscillation(ENSO)through ocean biologyinduced heating(OBH)feedbacks are not understood ***,a hybrid coupled model(HCM)for the atmosphere and ocean physics-biogeochemistry(AOPB)in the tropical Pacific is adopted to quantify how ENSO can be modulated by Chl perturbations at interannual and TIW scales,individually or collectively,*** HCM-based sensitivity experiments demonstrate a counteracting effect on ENSO:the bio-climate feedback due to large-scale Chl interannual variability acts to damp ENSO through its impact on upper-ocean stratification and vertical mixing,whereas that due to TIW-scale Chl perturbations tends to amplify *** ENSO simulations are sensitively dependent on the ways Chl effects are represented at these different scales,it is necessary to adequately take into account these related differential Chl effects in climate modeling.A bias source for ENSO simulations is illustrated that is related with the Chl effects in the tropical Pacific,adding in a new insight into interactions between the climate system and ocean ecosystem on different scales in the *** results reveal a level of complexity of ENSO modulations resulting from Chl effects at interannual and TIW scales,which are associated with ocean biogeochemical processes and their interactions with physical processes in the tropical Pacific.

关键词： Ocean chlorophyll Bio-climate feedbacks Interannual variability Tropical instability waves Counteracting effects A hybrid coupled model

3D coarse-grained DPM simulation of the MIP reaction-regeneration loop

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Particuology 2024年第6期89卷 57-66页

作者： Yanhao Ye Shuai zhang Ji Xu wei Ge State Key Laboratory of Mesoscience and Engineering(formerly State Key Laboratory of Multiphase Complex Systems) Institute of Process EngineeringChinese Academy of SciencesBeijing100190China School of Chemical Engineering University of Chinese Academy of SciencesBeijing100049China

The reactor-regenerator loop is the core facility of the maximizing iso-paraffin(MIP)*** the discrete particle method(DPM)simulation can provide detailed information at the particle scale,it has been unable to simulate such a complex loop system due to limitations of coarse-grained(CG)models,computing software,and *** this study,a newly proposed soft-shell CG-DPM model with a CG ratio of up to 800 is used to simulate a 3.5 Mt/a industrial-scale MIP reactor-regenerator *** solid fraction distribution obtained is found to agree well with in-situ *** properties including the distribution of solid fraction,gas and solid velocity,standard derivation of solid fraction with time,temporal distribution of the flow field,and particle residence time distribution are measured in the simulation,which are meaningful to better design and operate such systems in the future.

关键词： Discrete particle method Coarse-grain Maximizing iso-paraffins Full-loop Reaction-regeneration system

Robust Interval State Estimation for Distribution Systems Considering Pseudo-measurement Interval Prediction

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Journal of Modern Power Systems and Clean Energy 2024年第1期12卷 179-188页

作者： Xu zhang wei Yan Meiqing Huo Hui Li the School of Electrical Engineering Chongqing UniversityChongqing 400044China

Interval state estimation(ISE)can estimate state intervals of power systems according to confidence intervals of predicted pseudo-measurements,thereby analyzing the impact of uncertain pseudo-measurements on ***,predicted pseudo-measurements have prediction errors,and their confidence intervals do not necessarily contain the truth values,leading to estimation biases of the *** solve this problem,this paper proposes a pseudo-measurement interval prediction framework based on the Gaussian process regression(GPR)model,thereby improving the prediction accuracy of pseudo-measurement confidence ***,a weight assignment strategy for improving the robustness of weighted least squares(WLS)ISE is *** strategy quantifies the deviation between the pseudo-measurement intervals and their estimated intervals and assigns smaller weights to the pseudo-measurement intervals with larger deviations,thereby improving the estimation accuracy and robustness of the *** paper adopts the data from the supervisory control and data acquisition(SCADA)system of the New York Independent System Operator(NYISO).It verifies the advantages of the GPR method for pseudo-measurement interval prediction by comparing it with the quantile regression and neural network *** addition,this paper demonstrates the effectiveness of the proposed weight assignment strategy through the IEEE 14-bus ***,the differences in the estimation accuracy and the bad data identification between the robust interval state estimation and deterministic state estimation are discussed.

关键词： Interval state estimation interval analysis pseudo-measurement Gaussian process regression(GPR)

Gas–solid reactor optimization based on EMMS-DPM simulation and machine learning

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Particuology 2024年第6期89卷 131-143页

作者： Haolei zhang Aiqi Zhu Ji Xu wei Ge State Key Laboratory of Mesoscience and Engineering Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China State Key Laboratory of Multiphase Complex Systems Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China School of Chemical Engineering University of Chinese Academy of SciencesBeijing 100049China Innovation Academy for Green Manufacture Chinese Academy of SciencesBeijing 100190China

Design,scaling-up,and optimization of industrial reactors mainly depend on step-by-step experiments and engineering experience,which is usually time-consuming,high cost,and high *** numerical simulation can reproduce high resolution details of hydrodynamics,thermal transfer,and reaction process in reactors,it is still challenging for industrial reactors due to huge computational *** this study,by combining the numerical simulation and artificial intelligence(AI)technology of machine learning(ML),a method is proposed to efficiently predict and optimize the performance of industrial reactors.A gas–solid fluidization reactor for the methanol to olefins process is taken as an example.1500 cases under different conditions are simulated by the coarse-grain discrete particle method based on the Energy-Minimization Multi-Scale model,and thus,the reactor performance data set is *** develop an efficient reactor performance prediction model influenced by multiple factors,the ML method is established including the ensemble learning strategy and automatic hyperparameter optimization technique,which has better performance than the methods based on the artificial neural ***,the operating conditions for highest yield of ethylene and propylene or lowest pressure drop are searched with the particle swarm optimization algorithm due to its strength to solve non-linear optimization *** show that decreasing the methanol inflow rate and increasing the catalyst inventory can maximize the yield,while decreasing methanol the inflow rate and reducing the catalyst inventory can minimize the pressure *** two objectives are thus conflicting,and the practical operations need to be compromised under different circumstance.

关键词： Discrete particle method Artificial intelligence Machine learning Particle swarm optimization Industrial reactor optimization

Modulated-ISRJ rejection using online dictionary learning for synthetic aperture radar imagery

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Journal of Systems Engineering and Electronics 2024年第2期35卷 316-329页

作者： wei Shaopeng zhang Lei LU Jingyue LIU Hongwei College of Oceanography and Space Informatics China University of Petroleum(East China)Qingdao 266580China School of Electronics Engineering Xidian UniversityXi’an 710071China School of Electronics and Communication Engineering Shenzhen Campus of Sun Yat-sen UniversityGuangzhou 518107China School of Computer Science and Technology Xidian UniversityXi’an 710071China

In electromagnetic countermeasures circumstances,synthetic aperture radar(SAR)imagery usually suffers from severe quality degradation from modulated interrupt sampling repeater jamming(MISRJ),which usually owes considerable coherence with the SAR transmission waveform together with periodical modulation *** paper develops an MISRJ suppression algorithm for SAR imagery with online dictionary *** the algorithm,the jamming modulation temporal properties are exploited with extracting and sorting MISRJ slices using fast-time *** dictionary learning is followed to separate real signals from jamming *** the learned representation,time-varying MISRJs are suppressed *** simulated and real-measured SAR data are also used to confirm advantages in suppressing time-varying MISRJs over traditional methods.

关键词： synthetic aperture radar(SAR) modulated interrupt sampling jamming(MISRJ) online dictionary learning

Neural network based adaptive nonsingular practical predefined-time fault-tolerant control for hypersonic morphing aircraft

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Chinese Journal of Aeronautics 2024年第4期37卷 421-435页

作者： Shihao XU Changzhu wei Litao zhang Rongjun MU School of Astronautics Harbin Institute of TechnologyHarbin 150001China Beijing Institute of Control&Electronics Technology Beijing 100038China

This paper develops a novel Neural Network(NN)-based adaptive nonsingular practical predefined-time controller for the hypersonic morphing aircraft subject to actuator faults. Firstly, a novel Lyapunov criterion of practical predefined-time stability is established. Following the proposed criterion, a tangent function based nonsingular predefined-time sliding manifold and the control strategy are developed. Secondly, the radial basis function NN with a low-complexity adaptation mechanism is incorporated into the controller to tackle the actuator faults and uncertainties. Thirdly, rigorous theoretical proof reveals that the attitude tracking errors can converge to a small region around the origin within a predefined time, while all signals in the closed-loop system remain bounded. Finally, numerical simulation results are presented to verify the effectiveness and improved performance of the proposed control scheme.

关键词： Hypersonic morphing aircraft(HMA) Neural network(NN) Adaptive control Practical predefined-time control Fault-tolerant control

Targeted multi-agent communication algorithm based on state control

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Defence Technology（防务技术） 2024年第1期31卷 544-556页

作者： Li-yang Zhao tian-qing Chang Lei zhang Jie zhang Kai-xuan Chu De-peng Kong Department of Weaponry and Control Army Academy of Armored ForcesBeijing100072China Unit 92942 Beijing100161China

As an important mechanism in multi-agent interaction,communication can make agents form complex team relationships rather than constitute a simple set of multiple independent ***,the existing communication schemes can bring much timing redundancy and irrelevant messages,which seriously affects their practical *** solve this problem,this paper proposes a targeted multiagent communication algorithm based on state control(SCTC).The SCTC uses a gating mechanism based on state control to reduce the timing redundancy of communication between agents and determines the interaction relationship between agents and the importance weight of a communication message through a series connection of hard-and self-attention mechanisms,realizing targeted communication message *** addition,by minimizing the difference between the fusion message generated from a real communication message of each agent and a fusion message generated from the buffered message,the correctness of the final action choice of the agent is *** evaluation using a challenging set of Star Craft II benchmarks indicates that the SCTC can significantly improve the learning performance and reduce the communication overhead between agents,thus ensuring better cooperation between agents.

关键词： Multi-agent deep reinforcement learning State control Targeted interaction Communication mechanism

Electronic-scale assessment of high-temperature oxidation mechanisms in a novel Fe-based alloy

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Journal of Iron and Steel Research International 2024年第4期31卷 982-997页

作者： wei-di Luo Ting-ping Hou Xuan Liang Dong zhang Heng-fu Lin Yu Li tian-liang Zhao Cheng-yang Hu Serhii Yershov Kai-ming Wu The State Key Laboratory of Refractories and Metallurgy.Wuhan University of Science and Technology.Wuhan 430081 HubeiChina Hubei Province Key Laboratory of Systems Science in Meallurgial Process Wuhan University of Science and Technology.Wuhan 430081.Hubei.China International Research Institute for Steel Technology Wuhan University of Science and Technology.Wuhan 430081.HubeiChina Collaborative Innovation Center for Advanced Steels w uhan University of Science and Technology.Wuhan 430081.HuleiChina

The development of alloys with high antioxidation performance is limited by the ambiguous details of the oxidation ***,based on the structures of internal oxides detected by high-resolution transmission electron microscopy,a hybrid method combining first-principles calculation,climb image nudged elastic band method and quasi-harmonic Debye model has been implemented to explain the oxidation mechanism with an emphasis on the origin of delamination and *** results showed that the delamination of oxides corresponds to the acceleration of diffusion of Cr element caused by lamellar *** reduction in the cracking occurrence at high temperature mainly results from the smaller bulk modulus of ***,the stronger chemical bonds promoted by lamellar structures also correspond to the higher crackingresistance.

关键词： Oxidation Crystal structure Diffusion Cracking-First-principles calculation

Orientational growth behavior and mechanism of delta(δ)phase precipitation in cold-rolled Inconel 718 alloy during heat treatment

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Journal of Iron and Steel Research International 2024年第1期31卷 264-274页

作者： Neng-yong Ye Guang-liang zhang tian-yue Huang Ming Cheng Shi-hong zhang Lei Wang School of Materials Science&Engineering Taizhou UniversityTaizhou318000ZhejiangChina Institute of Metal Research Chinese Academy of SciencesShenyang110016LiaoningChina

Due to the important role ofδphase's quantity and morphology in the mechanical and fatigue properties of Inconel 718 alloy and its components,it is necessary to renew insights into the effect of cold deformation on theδphase precipitation,especially on the morphology ***,the nucleation and growth behavior ofδphase in cold-rolled Inconel 718 alloy during aging were *** results show that the precipitation rate and volume fraction ofδphase increase with increasing the cold rolling reduction from 10%to 50%.The volume fraction ofδphase reaches equilibrium after 5 h,remaining at 5.98%,6.52%,and 6.79%under different rolling reductions(10%,30%,and 50%),*** nucleation ofδphase mainly occurs on different sites(grain boundaries,new twin boundaries and old twin boundaries)under 10%rolling reduction,whileδphase mainly nucleates on the new grain boundaries of static recrystallization due to 50%rolling *** the growth ofδphase undergoes a process of alternate orientation growth from spherical(nucleation)→short rod(longitudinal orientation growth)→short rod(radial orientation growth)→dynamic *** 10%rolling reduction,δphase tends to grow into the matrix,while under 50%rolling reduction,the orientation grows faster and is easily affected by the grain boundary curvature.

关键词： Inconel 718 alloy Cold rolling δphase Orientation growth Morphology evolution