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A multiscale adaptive framework based on convolutional neural network: Application to fluid catalytic cracking product yield prediction

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Petroleum Science 2024年第4期21卷 2849-2869页

作者： Nan Liu Chun-meng Zhu meng-Xuan Zhang Xing-Ying lan State Key Laboratory of Heavy Oil Processing China University of Petroleum (Beijing) College of Artificial Intelligence China University of Petroleum (Beijing)

Since chemical processes are highly non-linear and multiscale, it is vital to deeply mine the multiscale coupling relationships embedded in the massive process data for the prediction and anomaly tracing of crucial process parameters and production indicators. While the integrated method of adaptive signal decomposition combined with time series models could effectively predict process variables, it does have limitations in capturing the high-frequency detail of the operation state when applied to complex chemical processes. In light of this, a novel Multiscale Multi-radius Multi-step Convolutional Neural Network(Msrt Net) is proposed for mining spatiotemporal multiscale information. First, the industrial data from the Fluid Catalytic Cracking(FCC) process decomposition using Complete Ensemble Empirical Mode Decomposition with Adaptive Noise(CEEMDAN) extract the multi-energy scale information of the feature subset. Then, convolution kernels with varying stride and padding structures are established to decouple the long-period operation process information encapsulated within the multi-energy scale data. Finally, a reconciliation network is trained to reconstruct the multiscale prediction results and obtain the final output. Msrt Net is initially assessed for its capability to untangle the spatiotemporal multiscale relationships among variables in the Tennessee Eastman Process(TEP). Subsequently, the performance of Msrt Net is evaluated in predicting product yield for a 2.80 × 10～6 t/a FCC unit, taking diesel and gasoline yield as examples. In conclusion, Msrt Net can decouple and effectively extract spatiotemporal multiscale information from chemical process data and achieve a approximately reduction of 30% in prediction error compared to other time-series models. Furthermore, its robustness and transferability underscore its promising potential for broader applications.

关键词： Fluid catalytic cracking Product yield Data-driven modeling Multiscale prediction Data decomposition Convolution neural network

A CombustionModel for Explosive Charge Affected by a Bottom Gap in the Launch Environment

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Computer Modeling in Engineering & Sciences 2024年第2期138卷 1207-1236页

作者： ShiboWu Weidong Chen Jingxin Ma lan Liu Shengzhuo lu Honglin meng Xiquan Song College of Aerospace and Civil Engineering Harbin Engineering UniversityHarbin150001China General Department of Experimental Technology Beijing Institute of Structure and Environment EngineeringBeijing100076China Department of Economics Kunlun Energy Holding Company LimitedBeijing100101China

Launch safety of explosive charges has become an urgent problem to be solved by all countries in the world aslaunch situation of ammunition becomes ***, the existing numericalmodels have differentdefects. This paper formulates an efficient computational model of the combustion of an explosive charge affectedby a bottom gap in the launch environment in the context of the material point method. The current temperatureis computed accurately from the heat balance equation, and different physical states of the explosive charges areconsidered through various equations of state. Microcracks in the explosive charges are described with respectto the viscoelastic statistical crackmechanics (Visco–SCRAM) model. Themethod for calculating the temperatureat the bottomof the explosive charge with respect to the bottomgap is described. Based on this combustionmodel,the temperature history of a Composition B (COMB) explosive charge in the presence of a bottom gap is obtainedduring the launch process of a 155-mm artillery. The simulation results show that the bottom gap thickness shouldbe no greater than 0.039 cm to ensure the safety of the COM B explosive charge in the launch environment. Thisconclusion is consistent with previous results and verifies the correctness of the proposed model. Ultimately, thispaper derives amathematical expression for themaximumtemperature of the COMB explosive chargewith respectto the bottomgap thickness (over the range of 0.00–0.039 cm), and establishes a quantitative evaluationmethod forthe launch safety of explosive *** research results provide some guidance for the assessment and detectionof explosive charge safety in complex launch environments.

关键词： Combustion model explosive charge safety launch environment bottom gap temperature

The Completeness of Accreting Neutron Star Binary Candidates from the Chinese Space Station Telescope

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Research in Astronomy and Astrophysics 2024年第9期24卷 30-38页

作者： Hao Shen Shun-Yi lan Xiang-Cun meng Yunnan Observatories Chinese Academy of Sciences University of Chinese Academy of Sciences International Centre of Supernovae Yunnan Key Laboratory

A neutron star（NS） has many extreme physical conditions, and one may obtain some important information about an NS via accreting neutron star binary（ANSB） systems. The upcoming Chinese Space Station Telescope（CSST）provides an opportunity to search for a large sample of ANSB candidates. Our goal is to check the completeness of the potential ANSB samples from CSST data. In this paper, we generate some ANSBs and normal binaries under the CSST photometric system by binary evolution and binary population synthesis method and use a machine learning method to train a classification model. Although the Precision（94.56%） of our machine learning model is as high as before study, the Recall is only about 63.29%. The Precision/Recall is mainly determined by the mass transfer rate between the NSs and their companions. In addition, we also find that the completeness of ANSB samples from CSST photometric data by the machine learning method also depends on the companion mass and the age of the system. ANSB candidates with a low initial mass companion star（0.1 M⊙to 1 M⊙） have a relatively high Precision（94.94%） and high Recall（86.32%）, whereas ANSB candidates with a higher initial mass companion star（1.1 M⊙to 3 M⊙） have similar Precision（93.88%） and quite low Recall（42.67%）. Our results indicate that although the machine learning method may obtain a relatively pure sample of ANSBs, a completeness correction is necessary for one to obtain a complete sample.

关键词： methods: analytical stars: neutron X-rays: binaries

A Scalable Pillar Layered Metal-Organic Framework for Natural Gas Purification

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Chemical Research in Chinese Universities 2024年第4期40卷 675-681页

作者： lu Nan lan lan GAO Qiang LI Na BU Xian-He School of Materials Science and Engineering Nankai UniversityTianjin300350P.R.China State Key Laboratory of Elemento-Organic Chemistry College of ChemistryNankai UniversityTianjin300071P.R.China School of Environmental and Chemical Engineering Jiangsu University of Science and TechnologyZhenjiang212003P.R.China

One-step harvest of high-purity methane(CH_(4))from ternary propane/ethane/methane(C_(3)H_(8)/C_(2)H_(6)/CH_(4))mixtures remains a desirable yet challenging goal for natural gas ***,adsorbents either suffer from high capacity and selectivity,or are caught in a dilemma of scalable ***,we demonstrate a scalable pillar layered metal-organic framework Ni-MOF for highly efficient one-step CH_(4)***-MOF exhibits high C_(2)H_(6)and C_(3)H_(8)uptakes of 83.3 and 86.1 cm^(3)/g at 298 K and 100 kPa and remarkable C_(2)H_(6)/CH_(4)(50/50,volume ratio,21.5)and C_(3)H_(8)/CH_(4)(50/50,volume ratio,212.0)***,high C_(2)H_(6)(42.2 cm^(3)/g at 10 kPa)and C_(3)H_(8)(64.7 cm^(3)/g at 5 kPa)capacities in the low-pressure region at 298 K were realized on Ni-MOF,suggesting the strong affinities of Ni-MOF towards C_(2)H_(6)and C_(3)H_(8).Furthermore,the dynamic breakthrough experiments revealed that purifying CH_(4)from natural gas in one-step can be achieved in Ni-MOF with high-purity(>99.8%)and productivity(346.0 cm^(3)/g).Most significantly,the production of Ni-MOF can be scalably synthesized at room temperature,rendering it promising potential for industrial *** combined advantages of exceptional separation performance,scalability,and cycle stability of Ni-MOF pave the way for one-step CH_(4)purification from natural gas.

关键词： Metal-organic framework Adsorption and separation Natural gas purification Scale-up synthesis

Wind disturbance compensated path-following control for fixed-wing UAVs in arbitrarily strong winds

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Chinese Journal of Aeronautics 2024年第2期37卷 431-445页

作者： Hao lu lan GAO Yunda YAN Mingzhe HOU Chenliang WANG Hangzhou Innovation Institute Beihang UniversityHangzhou 310051China School of Information Science and Technology Hangzhou Normal UniversityHangzhou 311121China Department of Computer Science University College LondonLondon WC1E 6BTUnited Kingdom Center for Control Theory and Guidance Technology Harbin Institute of TechnologyHarbin 150001China School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China

Wind is the primary challenge for low-speed fixed-wing unmanned aerial vehicles to follow a predefined flight *** cope with various wind conditions,this paper proposes a wind disturbance compensated path following control strategy where the wind disturbance estimate is incorporated with the nominal guiding vector field to provide the desired airspeed direction for the *** the control input vector for the outer-loop kinematic subsystem needs to satisfy a magnitude constraint,a scaling mechanism is introduced to tune the proportions of the compensation and nominal ***,an optimization problem is formulated to pursue a maximum wind compensation in strong winds,which can be solved analytically to yield two scaling factors.A cascaded inner-loop tracking controller is also designed to fulfill the outer-loop wind disturbance compensated guiding vector ***-fidelity simulation results under sensor noises and realistic winds demonstrate that the proposed path following algorithm is less sensitive to sensor noises,achieves promising accuracy in normal winds,and mitigates the deviation from a desired path in wild winds.

关键词： Path following Guiding vector field Wind disturbance Disturbance rejection Fixed wings

维普期刊数据库

G protein-coupled receptors(GPCRs):advances in structures,mechanisms,and drug discovery

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Signal Transduction and Targeted Therapy 2024年第5期9卷 1938-1980页

作者： Mingyang Zhang Ting Chen Xun lu Xiaobing lan Ziqiang Chen Shaoyong lu Key Laboratory of Protection Development and Utilization of Medicinal Resources in Liupanshan AreaMinistry of EducationPeptide&Protein Drug Research CenterSchool of PharmacyNingxia Medical UniversityYinchuan 750004China Medicinal Chemistry and Bioinformatics Center Shanghai Jiao Tong University School of MedicineShanghai 200025China Department of Cardiology Changzheng HospitalAffiliated to Naval Medical UniversityShanghai 200003China Department of Orthopedics Changhai HospitalAffiliated to Naval Medical UniversityShanghai 200433China

G protein-coupled receptors(GPCRs),the largest family of human membrane proteins and an important class of drug targets,play a role in maintaining numerous physiological *** or antagonist,orthosteric effects or allosteric effects,and biased signaling or balanced signaling,characterize the complexity of GPCR dynamic *** this study,we first review the structural advancements,activation mechanisms,and functional diversity of *** then focus on GPCR drug discovery by revealing the detailed drug-target interactions and the underlying mechanisms of orthosteric drugs approved by the US Food and Drug Administration in the past five ***,an up-to-date analysis is performed on available GPCR structures complexed with synthetic small-molecule allosteric modulators to elucidate key receptor-ligand interactions and allosteric ***,we highlight how the widespread GPCR-druggable allosteric sites can guide structure-or mechanism-based drug design and propose prospects of designing bitopic ligands for the future therapeutic potential of targeting this receptor family.

关键词： steric designing mechanisms

Research on virtual coupling technology in rail transit train collision protection

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Transportation Safety and Environment 2024年第1期6卷 40-46页

作者： Gaosong Li Jinbai Zou Weijie Ma meng lan School of Railway Transportation Shanghai Institute of TechnologyShanghai 201418China Shanghai Metro First Operation Co. LtdShanghai 201418China

In the research on the new generation of intelligent rail transit system,the prevention of train collision accidents is still a *** coupling technology controls the running speed and interval distance of two or more trains cooperatively through Trainto-Train(T2T)direct communication *** aim is to form a coordinated logical system and jointly complete the train control and *** this paper,a virtual coupling train formation control method based on the model predictive control(MPC)framework is *** the establishment of the virtual coupling system,the construction of an MPC model and decoupling method,how to integrate virtual coupling technology into the rail transit train collision protection is *** safety and reliability of the system are calculated through fault tree and the method of constructing reliability *** research shows that if virtual coupling technology is used for train collision protection,the overall safety and reliability of the train control system is improved.

关键词： virtual coupling model predictive control collision protection

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Application of wastewater-based epidemiological monitoring of COVID-19 for disease surveillance in the city

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Frontiers of Environmental Science & Engineering 2024年第8期18卷 81-87页

作者： Heng Chen Zhenhua Chen Liwen Hu Fengzhu Tang Dan Kuang Jiayi Han Yao Wang Xiao Zhang Yue Cheng Jiantong meng Rong lu lan Zhang Chengdu Workstation for Emerging Infectious Disease Control and Prevention Chinese Academy of Medical SciencesChengdu 610047China Chengdu Center for Disease Control and Prevention Chengdu 610047China National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases Beijing 100050China National Institute of Environmental Health Chinese Center for Disease Control and PreventionBeijing 100050China

Wastewater-based surveillance serves as a supplementary approach to clinical surveillance of COVID-19 during the *** study aimed to track the prevalence of the disease and the viral genetic variability through wastewater-based surveillance in the post-epidemic *** January to December 2023,samples were collected from the influent lines of two wastewater treatment plants(WWTPs),concentrated using PEG8000,and subjected to detection of the target genes ORF 1ab and N of SARS-CoV-2 via reverse transcriptional quantitative PCR(RT-qPCR).For next-generation sequencing(NGS),high-quality samples from both wastewater and clinical patients were *** analysis were performed using R software to evaluate the correlation between the SARSCoV-2 RNA concentrations in wastewater and positive rate of reported cases,indicating a positive *** diversity patterns of SARS-CoV-2 in wastewater resembled those in the patient source based on Principal Coordinates Analysis(PCoA)with three clusters for different *** rise of RNA concentration in wastewater indicates the growth of cases and the emergence of new variants,serving as an early warning of potential viral mutations,disease outbreaks even possible ***,the genomic surveillance of wastewater could help identify new variants that may not be captured through population monitoring,especially when sample sizes are ***,surveillance of SARS-CoV-2 in municipal wastewater has emerged as a reliable,earlywarning monitoring system for COVID-19 in the post-epidemic era.

关键词： Wastewater-based epidemiology Monitoring COVID-19 Post-epidemic era

Combined UAMP and MF Message Passing Algorithm for Multi-Target Wideband DOA Estimation with Dirichlet Process Prior

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Tsinghua Science and Technology 2024年第4期29卷 1069-1081页

作者： Shanwen Guan Xinhua lu Ji Li Rushi lan Xiaonan luo Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin University of Electronic TechnologyGuilin 541004China Guilin Huigu Institute of AI Industrial Technology Guilin 541004China School of Information Engineering Nanyang Institute of TechnologyNanyang 473000China

When estimating the direction of arrival (DOA) of wideband signals from multiple sources, the performance of sparse Bayesian methods is influenced by the frequency bands occupied by signals in different directions. This is particularly true when multiple signal frequency bands overlap. Message passing algorithms (MPA) with Dirichlet process (DP) prior can be employed in a sparse Bayesian learning (SBL) framework with high precision. However, existing methods suffer from either high complexity or low precision. To address this, we propose a low-complexity DOA estimation algorithm based on a factor graph. This approach introduces two strong constraints via a stretching transformation of the factor graph. The first constraint separates the observation from the DP prior, enabling the application of the unitary approximate message passing (UAMP) algorithm for simplified inference and mitigation of divergence issues. The second constraint compensates for the deviation in estimation angle caused by the grid mismatch problem. Compared to state-of-the-art algorithms, our proposed method offers higher estimation accuracy and lower complexity.

关键词： wideband direction of arrival(DOA)estimation sparse Bayesian learning(SBL) unitary approximate message passing(UAMP)algorithm Dirichlet process(DP)