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Deep reinforcement learning based active surge control for aeroengine compressors

Chinese Journal of Aeronautics 2024年第7期37卷 418-438页

作者： Xinglong ZHANG Zhonglin LIN Runmin ji Tianhong ZHANG College of Energy and Power Engineering Nanjing University of Aeronautics and AstronauticsNanjing 210016China School of Mechanical Engineering and Automation Fuzhou UniversityFuzhou 350108China

This study proposes an active surge control method based on deep reinforcement learning to ensure the stability of compressors when adhering to the pressure rise command across the wide operating range of an ***,the study establishes the compressor dynamic model with uncertainties,disturbances,and Close-Coupled Valve(CCV)actuator *** upon this foundation,a Partially Observable Markov Decision Process(POMDP)is defined to facilitate active surge *** address the issue of unobservability,a nonlinear state observer is designed using a finite-time high-order sliding ***,an Improved Soft Actor-Critic(ISAC)algorithm is developed,incorporating prioritized experience replay and adaptive temperature parameter techniques,to strike a balance between exploration and convergence during *** addition,reasonable observation variables,error-segmented reward functions,and random initialization of model parameters are employed to enhance the robustness and generalization ***,to assess the effectiveness of the proposed method,numerical simulations are conducted,and it is compared with the fuzzy adaptive backstepping method and Second-Order Sliding Mode Control(SOSMC)*** simulation results demonstrate that the deep reinforcement learning based controller outperforms other methods in both tracking accuracy and ***,the proposed active surge controller can effectively ensure stable operation of compressors in the high-pressure-ratio and high-efficiency region.

关键词： Aeroengine surge Active surge control Moore-Greitzer model Deep reinforcement learning Soft actor-critic Nonlinear observer

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Role of catalyst surface-active sites in the hydrogenation ofα,β-unsaturated aldehyde

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Frontiers of Chemical Science and Engineering 2024年第6期18卷 41-69页

作者： Haixiang Shi Tongming Su Zuzeng Qin Hongbing ji School of Chemistry and Chemical Engineering Guangxi Key Laboratory of Petrochemical Resource Processing and Process Intensification TechnologyGuangxi UniversityNanning 530004China Zhejiang Green Petrochemical and Light Hydrocarbon Transformation Research Institute Zhejiang University of TechnologyHangzhou 310014China

As an important technology in fine chemical production,the selective hydrogenation ofα,β-unsaturated aldehydes has attracted much attention in recent *** the process ofα,β-unsaturated aldehyde hydrogenation,a conjugated system is formed between>C=CC=O,leading to hydrogenation at both ends of the conjugated system,which competes with each other and results in more complex ***,improving the reaction selectivity is also difficult in industrial ***,many researchers have reported that surface-active sites on catalysts play a crucial role inα,β-unsaturated aldehyde *** review attempts to summarize recent advances in understanding the effects of surface-active sites(SASs)over metal catalysts for enhancing the process of *** construction strategies and roles of SASs for hydrogenation catalysts are *** attention has been given to the adsorption configuration and transformation mechanism ofα,β-unsaturated aldehydes on catalysts,which contributes to understanding the relationship between SASs and hydrogenation *** addition,recent advances in metal-supported catalysts for the selective hydrogenation ofα,β-unsaturated aldehydes to understand the role of SASs in hydrogenation are briefly ***,the opportunities and challenges will be highlighted for the future development of the precise construction of SASs.

关键词： α,β-unsaturatedd aldehydes hydrogenation active site cinnamaldehyde

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Novel data-driven sparse polynomial chaos and analysis of covariance for aerodynamics of compressor cascades with dependent geometric uncertainties

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Chinese Journal of Aeronautics 2024年第6期37卷 89-108页

作者： Zhengtao GUO Wuli CHU Haoguang ZHANG Tianyuan ji School of Power and Energy Northwestern Polytechnical UniversityXi’an 710072China

Polynomial Chaos Expansion(PCE)has gained significant popularity among engineers across various engineering disciplines for uncertainty ***,traditional PCE suffers from two major ***,the orthogonality of polynomial basis functions holds only for independent input variables,limiting the model’s ability to propagate uncertainty in dependent ***,PCE encounters the"curse of dimensionality"due to the high computational cost of training the model with numerous polynomial *** practical manufacturing,compressor blades are subject to machining precision limitations,leading to deviations from their ideal geometric *** deviations require a large number of geometric parameters to describe,and exhibit significant *** efficiently quantify the impact of high-dimensional dependent geometric deviations on the aerodynamic performance of compressor blades,this paper firstly introduces a novel approach called Data-driven Sparse PCE(DSPCE).The proposed method addresses the aforementioned challenges by employing a decorrelation algorithm to directly create multivariate basis functions,accommodating both independent and dependent random ***,the method utilizes an iterative Diffeomorphic Modulation under Observable Response Preserving Homotopy regression algorithm to solve the unknown coefficients,achieving model sparsity while maintaining fitting ***,the study investigates the simultaneous effects of seven dependent geometric deviations on the aerodynamics of a high subsonic compressor cascade by using the DSPCE method proposed and sensitivity analysis of *** joint distribution of the dependent geometric deviations is determined using Quantile-Quantile plots and normal copula functions based on finite measurement *** results demonstrate that the correlations between geometric deviations significantly impact the variance of aerodynamic performance and the flow ***,

关键词： Data-driven sparse polyno-mial chaos Analysis of covariance Dependent uncertainty Aerodynamic performance Compressor cascade

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Data-Driven Design for Targeted Regulation of Heat Transfer in Carbon/Carbon Composite Structure

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Journal of Thermal Science 2024年第2期33卷 648-657页

作者： XIAO Heye WANG Zelin WANG Hui ji Ritian Unmanned System Research Institute Northwestern Polytechnical UniversityXi’an710072China School of Aeronautics Northwestern Polytechnical UniversityXi’an710072China Research&Development Institute of Northwestern Polytechnical University in Shenzhen Shenzhen518063China MOE Key Laboratory of Thermo-Fluid Science and Engineering School of Energy and Power EngineeringXi’an Jiaotong UniversityXi’an710049China

Targeted regulation of heat transfer in carbon/carbon composite structure is built for cooling electronic device.A three-dimensional data-driven design model coupling genetic algorithm(GA) with self-adaption deep learning for targeted regulation of heat transfer in built structure is *** self-adaption deep learning model predicts the temperature of built structure closer to optimal value in GA *** distributions of pore and carbon fiber bundles in built structure are optimized by the proposed *** surface temperature of electronic device in the optimized structures is 19.1%-27.5% lower than that in the initial configurations when the porosity of built structure varies from 3% to 11%.The surface temperature of electronic device increases with an increase in *** built structure with carbon fiber bundles near the surface of electronic device and pore distribution in the middle of structure has a higher heat dissipation capacity compared with that in the initial ***,the computation time of the proposed model is less than one tenth compared with that of the traditional genetic algorithm.

关键词： targeted regulation of heat transfer self-adaption deep learning genetic algorithm carbon/carbon composite structure

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Performance evaluation for multi-target tracking with temporal dimension specifics

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Chinese Journal of Aeronautics 2024年第2期37卷 446-458页

作者： Zhenzhen SU Hongbing ji Cong TIAN Yongquan ZHANG School of Computer Science and Technology Xidian UniversityXi’an 710071China School of Electronic Engineering Xidian UniversityXi’an 710071China

With the great development of Multi-Target Tracking(MTT)technologies,many MTT algorithms have been proposed with their own advantages and *** to the fact that requirements to MTT algorithms vary from the application scenarios,performance evaluation is significant to select an appropriate MTT algorithm for the specific application *** this paper,we propose a performance evaluation method on the sets of trajectories with temporal dimension specifics to compare the estimated trajectories with the true *** proposed method evaluates the estimate results of an MTT algorithm in terms of tracking accuracy,continuity and ***,its computation is based on a multi-dimensional assignment problem,which is formulated as a computable form using linear *** enhance the influence of recent estimated states of the trajectories in the evaluation,an attention function is used to reweight the trajectory errors at different time ***,simulation results show that the proposed performance evaluation method is able to evaluate many aspects of the MTT *** evaluations are worthy for selecting suitable MTT algorithms in different application scenarios.

关键词： Multi-target tracking Temporal dimension specifics Performance evaluation Random finite sets Linear programming

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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

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Compound Product of Hypermatrices

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Journal of Systems Science & Complexity 2024年第1期37卷 169-183页

作者： CHENG Daizhan MENG Min ZHANG Xiao ji Zhengping Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China Department of Control Science and Engineering School of Electronics and Information EngineeringTongji UniversityShanghai 201210China National Center for Mathematics and Interdisciplinary Sciences Chinese Academy of SciencesBeijing 100190China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100149China.

The semi-tensor product(STP)of matrices is generalized to multidimensional arrays,called the compound product of *** product is first defined for three-dimensional hypermatrices with compatible orders and then extended to general *** different types of hyperdeterminants are introduced and certain properties are *** Lie groups and Lie algebras corresponding to the hypermatrix products are ***,these results are applied to dynamical systems.

关键词： Compound semi-tensor product hyperdeterminants hypereigenvalues and hypereigenvectors hypergeneral linear groups hypermatrices.

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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

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Scalar dark energy models and scalar–tensor gravity:theoretical explanations for the accelerated expansion of the present Universe

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Communications in Theoretical Physics 2024年第10期76卷 160-189页

作者： Peixiang ji Lijing Shao Department of Astronomy School of Physics Peking University Kavli Institute for Astronomy and Astrophysics Peking University National Astronomical Observatories Chinese Academy of Sciences

The reason for the present accelerated expansion of the Universe stands as one of the most profound questions in the realm of science, with deep connections to both cosmology and fundamental physics. From a cosmological point of view, physical models aimed at elucidating the observed expansion can be categorized into two major classes: dark energy and modified gravity. We review various major approaches that employ a single scalar field to account for the accelerating phase of our present Universe. Dynamic system analysis was employed in several important models to find cosmological solutions that exhibit an accelerating phase as an *** scalar field models of dark energy, we consistently focused on addressing challenges related to the fine-tuning and coincidence problems in cosmology, as well as exploring potential solutions to them. For scalar–tensor theories and their generalizations, we emphasize the importance of constraints on theoretical parameters to ensure overall consistency with experimental tests. Models or theories that could potentially explain the Hubble tension are also emphasized throughout this review.

关键词： cosmology dark energy dynamic system modified gravity quintessence

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Forced boiling of nonazeotropic immiscible mixture in a supercapillary microchannel array for ultra-high heat flux removal with chip junction temperature below 85℃

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Science China(Technological Sciences) 2024年第5期67卷 1364-1380页

作者： SUN Bo BAO YuChen TIAN Tong LI ji School of Engineering Science University of Chinese Academy of SciencesBeijing100049China Laboratory of Advanced Thermal Management Technologies School of Engineering ScienceUniversity of Chinese Academy of SciencesBeijing100049China

In this study,a structure-optimized two-phase microchannel heat sink with sintered submicron nucleation sites was developed and *** copper-based microchannels had a rectangular cross-section with an equivalent hydraulic diameter of 222μ*** subcooled flow boiling characteristics were comprehensively compared between pure HFE-7100 and a non-azeotropic,immiscible binary mixture of HFE-7100 and water,considering heating areas of 1 and 5 cm^(2).The total heating power input to the test section were 100–1500 and 250–3000 W for a 1 and 5 cm^(2)heat source,respectively,with a flow rate ranging from 50 to150 L/*** to pure HFE-7100,the non-azeotropic immiscible binary mixture of HFE-7100/water in the sintered porous microchannels exhibited a much higher overall heat transfer coefficient and lower power *** maintain the junction temperature of a high power electronic chip below 85℃,the proposed supercapillary microchannel heat sink could effectively dissipate the heat flux of 1275 W/cm^(2)over 1 cm^(2)heat source and 500 W/cm^(2)over 5 cm^(2)heat *** addition,the volume ratio of the binary mixture strongly influence the two-phase flow heat transfer *** optimal volume ratio exist in terms of the thermal resistance–pumping power minimization(HFE-7100:water=2:8 is recommended in this study).The findings of this investigation on the flow boiling properties of non-azeotropic immiscible mixtures help fill a gap in the related field.

关键词： microchannel sintered powder coating submicron nucleation cavities nonazeotropic immiscible ultra-high heat flux

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