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An artificial intelligence approach for particle transport velocity prediction in horizontal flows

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Particuology 2024年第9期92卷 234-250页

作者： Haoyu chen Zhiguo {1. Hai Huang Jun Zhang College of Petroleum Engineering Xi'an Shiyou UniversityXi'an710065China Shaanxi Key Laboratory of Carbon Dioxide Sequestration and Enhanced Oil Recovery Xi'an710065China College of New Energy Xi'an Shiyou UniversityXi'an710065China Engineering Research Center of Smart Energy and Carbon Neutral in Oil&Gas Field Universities of Shaanxi ProvinceChina The Erosion/Corrosion Research Center The University of TulsaOK74104United States

Particle entrainment is an inevitable phenomenon in pipeline systems,especially during the development and extraction phases of oil and gas *** predicting the critical velocity for particle transport is a key focus for implementing effective sand control *** work presents a semi-supervised learning–deep hybrid kernel extreme learning machine(SSL-DHKELM)model for predicting the critical velocity,which integrates multiple machine learning theories including the deep learning approach,which is adept at advanced feature ***,the SSL framework enhances the model's capabilities when data availability is *** improved slime mould algorithm is also employed to optimize the model's *** proposed model has high accuracy on both the sample dataset and out-of-sample *** trained with only 1.%of the data,the model's error still did not increase ***,this model achieves superior predictive accuracy compared to existing mechanistic models,demonstrating its impressive performance and robustness.

关键词： Particle transport Critical velocity Deep learning Semi-supervised learning Extreme learning machine

Classification of aviation incident causes using LGBM with improved cross-validation

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Journal of Systems Engineering and Electronics 2024年第2期35卷 396-405页

作者： NI Xiaomei wang Huawei {1. Lingzi LIN Ruiguan School of Civil Aviation Nanjing University of Aeronautics and AstronauticsNanjing 211106China School of Aeronautical Engineering Nanjing Vocational University of Industry TechnologyNanjing 210023China

Aviation accidents are currently one of the leading causes of significant injuries and deaths worldwide. This entices researchers to investigate aircraft safety using data analysis approaches based on an advanced machine learning *** assess aviation safety and identify the causes of incidents, a classification model with light gradient boosting machine (LGBM)based on the aviation safety reporting system (ASRS) has been developed. It is improved by k-fold cross-validation with hybrid sampling model (HSCV), which may boost classification performance and maintain data balance. The results show that employing the LGBM-HSCV model can significantly improve accuracy while alleviating data imbalance. Vertical comparison with other cross-validation (CV) methods and lateral comparison with different fold times comprise the comparative approach. Aside from the comparison, two further CV approaches based on the improved method in this study are discussed:one with a different sampling and folding order, and the other with more CV. According to the assessment indices with different methods, the LGBMHSCV model proposed here is effective at detecting incident causes. The improved model for imbalanced data categorization proposed may serve as a point of reference for similar data processing, and the model’s accurate identification of civil aviation incident causes can assist to improve civil aviation safety.

关键词： aviation safety imbalance data light gradient boosting machine(LGBM) cross-validation(CV)

Study on the force chain characteristics with coal dust layer and the three-body contact stiffness

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Particuology 2024年第9期92卷 288-304页

作者： Xinwei Yang Dongxuan Wu Hongyue chen Dong {1. School of Mechanical Engineering Liaoning Technical UniversityFuxin123000China Ordos Institute of Liaoning Technical University Ordos017000China School of Mining Liaoning Technical UniversityFuxin123000China China National Coal Association Dynamic Research for High-end Complete Integrated Coal Mining Equipment and Big Data Analysis CentreFuxin123000China

To explore the influence of the meso-mechanical behaviors of the wet coal dust layers on the contact stiffness of mechanical bonding surfaces,a three-body contact model incorporating an interface with wet coal dust was constructed based on breakage *** model considered the mechanical surface morphology and contact characteristics of the wet coal *** force chain evolution laws of the wet coal dust layer were elucidated under the effects of gap filling and the cover layer,and the bearing characteristics of the three-body contact bonding surfaces were revealed by quantitative analyses of the number,length,collimation coefficient,and coordination number of the force chains within the wet coal dust ***,the three-body normal contact stiffness under various preload forces was computed and experimentally *** results demonstrate that the external load transfer path of the three-body contact bonding surfaces was from mechanical surface(macroscopic stress)to wet coal dust layer(mesoscopic force chains)and then to mechanical surface(peaks and valleys).The interactions among these three elements contributed to transforming the distributions of the macroscopic stresses and mesoscopic force chains to the locations at the peaks and valleys of the mechanical *** them,the proportion of short force chains in the wet coal dust layer increased from approximately 0.8%–91.,while the proportion of long force chains exhibited an opposite changing *** force chain collimation coefficient initially increased and subsequently stabilized,reaching a maximum value of 0.93.A large number of broken,small particles in the wet coal dust layer mainly served to fill the gaps among large *** maximum relative error between the experimental and simulated values on the three-body contact stiffness is 7.26%,indicating that the simulation results can be an approximate substitute for the experimental results with a certain degree of accuracy and practic

关键词： Wet coal dust Force chain Three-body contact stiffness Gap flling effect Cover layer effect

Uncertainty quantification of mechanism motion based on coupled mechanism—motor dynamic model for ammunition delivery system

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Defence Technology（防务技术） 2024年第3期33卷 125-133页

作者： Jinsong Tang Linfang Qian Longmiao chen Guangsong chen Mingming wang Guangzu Zhou Nanjing University of Science and Technology Nanjing 210094China Northwest Institute of Mechanical and Electrical Engineering Xianyang 712099China

In this paper,a dynamic modeling method of motor driven electromechanical system is presented,and the uncertainty quantification of mechanism motion is investigated based on this *** main contribution is to propose a novel mechanism-motor coupling dynamic modeling method,in which the relationship between mechanism motion and motor rotation is established according to the geometric coordination of the *** advantages of this include establishing intuitive coupling between the mechanism and motor,facilitating the discussion for the influence of both mechanical and electrical parameters on the mechanism,and enabling dynamic simulation with controller to take the randomness of the electric load into *** simulation considering feedback control of ammunition delivery system is carried out,and the feasibility of the model is verified *** on probability density evolution theory,we comprehensively discuss the effects of system parameters on mechanism motion from the perspective of uncertainty *** work can not only provide guidance for engineering design of ammunition delivery mechanism,but also provide theoretical support for modeling and uncertainty quantification research of mechatronics system.

关键词： Ammunition delivery system Electromechanical coupling dynamics Uncertainty quantification Generalized probability density evolution

Application Analysis of Multiple Neurons Connected with Fast Inhibitory Synapses

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Journal of Bionic Engineering 2024年第4期21卷 1905-1918页

作者： Wen Duan Weihai chen Jianhua {1. Zhongcai Pei Jingmeng Liu Jianer chen School of Automation Science and Electrical Engineering Beihang UniversityXueyuan RoadBeijing100191China Hangzhou Innovation Institute Beihang UniversityChuanghui StreetHangzhou310051ZhejiangChina School of Electrical Engineering and Automation Anhui UniversityAnhui230601ZhejiangChina Zhejiang Rehabilitation Medical Center Binsheng RoadHangzhou310052ZhejiangChina

Almost all living organisms exhibit autonomic oscillatory activities,which are primarily generated by the rhythmic activities of their neural *** nonlinear oscillator models have been proposed to elucidate these neural behaviors and subsequently applied to the domain of robot ***,the oscillation patterns generated by these models are often unpredictable and need to be obtained through parameter *** study introduces a mathematical model that can be used to analyze multiple neurons connected through fast inhibitory *** characteristic of this oscillator is that its stationary point is stable,but the location of the stationary point changes with the system *** through reasonable topology and threshold parameter selection can the oscillation be *** study analyzed the conditions for stable oscillation in two-neuron networks and three-neuron networks,and obtained the basic rules of the phase relationship of the oscillator network established by this *** addition,this study also introduces synchronization mechanisms into the model to enable it to be synchronized with the sensing ***,this study used these theories to establish a robot single leg joint angle generation *** experimental results showed that the simulated robot could achieve synchronization with human motion,and had better control effects compared to traditional oscillators.

关键词： Oscillator Phase trajectory Synaptic threshold Synchronization Motion generation

Impact Force Localization and Reconstruction via ADMM-based Sparse Regularization Method

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Chinese Journal of Mechanical Engineering 2024年第3期37卷 170-188页

作者： Yanan wang Lin {1. Junjiang Liu Baijie Qiao Weifeng He Xuefeng {1. National Key Lab of Aerospace Power System and Plasma Technology Xi’an Jiaotong UniversityXi’an 710049China School of Mechanical Engineering Xi’an Jiaotong UniversityXi’an 710049China

In practice,simultaneous impact localization and time history reconstruction can hardly be achieved,due to the illposed and under-determined problems induced by the constrained and harsh measuring *** l_(1. regularization can be used to obtain sparse solutions,it tends to underestimate solution amplitudes as a biased *** address this issue,a novel impact force identification method with l_(p) regularization is proposed in this paper,using the alternating direction method of multipliers(ADMM).By decomposing the complex primal problem into sub-problems solvable in parallel via proximal operators,ADMM can address the challenge *** mitigate the sensitivity to regularization parameters,an adaptive regularization parameter is derived based on the K-sparsity ***,an ADMM-based sparse regularization method is developed,which is capable of handling l_(p) regularization with arbitrary p values using adaptively-updated *** effectiveness and performance of the proposed method are validated on an aircraft skin-like composite ***,an investigation into the optimal p value for achieving high-accuracy solutions via l_(p) regularization is *** turns out that l_(0.6)regularization consistently yields sparser and more accurate solutions for impact force identification compared to the classic l_(1. regularization *** impact force identification method proposed in this paper can simultaneously reconstruct impact time history with high accuracy and accurately localize the impact using an under-determined sensor configuration.

关键词： Impact force identification Non-convex sparse regularization Alternating direction method of multipliers Proximal operators

A data-driven approach for predicting the fatigue life and failure mode of self-piercing rivet joints

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Advances in Manufacturing 2024年第3期12卷 538-555页

作者： Jian wang Qiu-Ren {1. Li Huang {1.-Di Wei Chao Tong Xian-Hui wang Qing Liu Nanjing University of Science and Technology Nanjing210094People’s Republic of China Material Academy JitriSuzhou215100JiangsuPeople’s Republic of China Key Laboratory for Light-weight Materials Nanjing Tech UniversityNanjing210009People’s Republic of China Xi’an Jiaotong-Liverpool University Suzhou215123JiangsuPeople’s Republic of China

In lightweight automotive vehicles,the application of self-piercing rivet(SPR)joints is becoming increasingly *** the importance of automotive service performance,the fatigue performance of SPR joints has received considerable ***,this study proposes a data-driven approach to predict the fatigue life and failure modes of SPR *** dataset comprises three specimen types:cross-tensile,cross-peel,and *** ensure data consistency,a finite element analysis was employed to convert the external loads of the different *** selection was implemented using various machine-learning algorithms to determine the model *** Gaussian process regression algorithm was used to predict fatigue life,and its performance was compared with different kernel functions commonly used in the *** results revealed that the Matern kernel exhibited an exceptional predictive capability for fatigue *** the data points,95.9%fell within the 3-fold error band,and the remaining 4.1.exceeded the 3-fold error band owing to inherent dispersion in the fatigue *** predict the failure location,various tree and artificial neural network(ANN)models were *** findings indicated that the ANN models slightly outperformed the tree *** ANN model accurately predicts the failure of joints with varying dimensions and ***,minor deviations were observed for the joints with the same ***,this data-driven approach provided a reliable predictive model for estimating the fatigue life and failure location of SPR joints.

关键词： Self-piercing rivet(SPR)joints Fatigue life prediction Failure mode prediction Machine learning

Molecular Mechanism of Polysaccharides Extracted from Chinese Medicine Targeting Gut Microbiota for Promoting Health

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Chinese Journal of Integrative Medicine 2024年第2期30卷 171-180页

作者： ZHAO Wen-xiao wang Tong ZHANG Ya-nan {1. Qian wang Yuan XING Yan-qing ZHENG Jun DUAN {1.-{1. {1. Lijun ZHAO Hai-jun wang Shijun School of Nursing Shandong University of Traditional Chinese MedicineShandong University of Traditional Chinese MedicineJi'nan(250355)China Shandong Co-innovation Center of Classic Traditional Chinese Medicine Formula Shandong University of Traditional Chinese MedicineJi'nan(250355)China College of Traditional Chinese Medicine Shandong University of Traditional Chinese MedicineJinan(250355)China

The accumulating evidence revealed that gut microbiota plays an important role in pathological process of disease including obesity,type 2 diabetes mellitus,heart failure,and non-alcoholic fatty liver *** extracted from Chinese medicine(CM)can not only alleviate pathological status but also promote health by anti-inflammatory,regulating immunity,lowering blood glucose and lipids,anti-cancer,and *** alterations of gut microbiota composition and metabolism pathways are the potential mechanisms of CM polysaccharides *** addition,they exert functions through gut-organ axis or play an indirect role by synergistic actions with other drugs or components mediated by gut *** review summarizes the molecular mechanisms of CM polysaccharides interacted with intestinal microbial inhabitants as potential prebiotics forpromoting health.

关键词： Chinese medicine polysaccharides gut microbiota short-chain fatty acids lipopolysaccharides gut-organaxis synergistic actions

Global characterization of OsPIP aquaporins reveals that the H_(2)O_(2)transporter OsPIP2;6 increases resistance to rice blast

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The Crop Journal 2024年第1期12卷 102-109页

作者： Gousi Li Jingluan Han chen Yi Hao Luo Yuzhu {1. Fengpin {1. Xiaoyu {1. Letian chen Yaling Zhang State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources College of Life SciencesSouth China Agricultural UniversityGuangzhou 510642GuangdongChina Guangdong Laboratory for Lingnan Modern Agriculture Guangzhou 510642GuangdongChina National Key Laboratory of Plant Molecular Genetics Shanghai Center for Plant Stress BiologyCAS Center for Excellence in Molecular Plant SciencesShanghai Institute of Plant Physiology and EcologyChinese Academy of SciencesShanghai 200032China

Plasma membrane intrinsic proteins(PIPs)are conserved plant aquaporins that transport small molecules across the plasma membrane to trigger instant stress responses and maintain cellular homeostasis under biotic and abiotic *** elucidate their roles in plant immunity to pathogen attack,we characterized the expression patterns,subcellular localizations,and H_(2)O_(2)-transport ability of 1. OsPIPs in rice(Oryza sativa),and identified OsPIP2;6 as necessary for rice disease ***2;6 resides on the plasma membrane and facilitates cytoplasmic import of the immune signaling molecule H_(2)O_(2).Knockout of OsPIP2;6 increases rice susceptibility to Magnaporthe oryzae,indicating a positive function in plant ***2;6 interacts with OsPIP2;2,which has been reported to increase rice resistance to pathogens via H_(2)O_(2)*** findings suggest that OsPIP2;6 cooperates with OsPIP2;2 as a defense signal transporter complex during plant–pathogen interaction.

关键词： Aquaporin Plant immunity Rice blast H_(2)O_(2)transport