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Optimization Design of the Multi-Layer Cross-Sectional Layout of An Umbilical Based on the GA-GLM 被引量:1
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作者 YANG Zhi-xun YIN Xu +5 位作者 FAN Zhi-rui YAN Jun LU Yu-cheng SU Qi MAO Yandong WANG Hua-lin 《China Ocean Engineering》 SCIE EI CSCD 2024年第2期247-254,共8页
Marine umbilical is one of the key equipment for subsea oil and gas exploitation,which is usually integrated by a great number of different functional components with multi-layers.The layout of these components direct... Marine umbilical is one of the key equipment for subsea oil and gas exploitation,which is usually integrated by a great number of different functional components with multi-layers.The layout of these components directly affects manufacturing,operation and storage performances of the umbilical.For the multi-layer cross-sectional layout design of the umbilical,a quantifiable multi-objective optimization model is established according to the operation and storage requirements.Considering the manufacturing factors,the multi-layering strategy based on contact point identification is introduced for a great number of functional components.Then,the GA-GLM global optimization algorithm is proposed combining the genetic algorithm and the generalized multiplier method,and the selection operator of the genetic algorithm is improved based on the steepest descent method.Genetic algorithm is used to find the optimal solution in the global space,which can converge from any initial layout to the feasible layout solution.The feasible layout solution is taken as the initial value of the generalized multiplier method for fast and accurate solution.Finally,taking umbilicals with a great number of components as examples,the results show that the cross-sectional performance of the umbilical obtained by optimization algorithm is better and the solution efficiency is higher.Meanwhile,the multi-layering strategy is effective and feasible.The design method proposed in this paper can quickly obtain the optimal multi-layer cross-sectional layout,which replaces the manual design,and provides useful reference and guidance for the umbilical industry. 展开更多
关键词 UMBILICAL cross-sectional layout multi-layerS GA-GLM optimization
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Multi-layer perceptron-based data-driven multiscale modelling of granular materials with a novel Frobenius norm-based internal variable 被引量:1
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作者 Mengqi Wang Y.T.Feng +1 位作者 Shaoheng Guan Tongming Qu 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2024年第6期2198-2218,共21页
One objective of developing machine learning(ML)-based material models is to integrate them with well-established numerical methods to solve boundary value problems(BVPs).In the family of ML models,recurrent neural ne... One objective of developing machine learning(ML)-based material models is to integrate them with well-established numerical methods to solve boundary value problems(BVPs).In the family of ML models,recurrent neural networks(RNNs)have been extensively applied to capture history-dependent constitutive responses of granular materials,but these multiple-step-based neural networks are neither sufficiently efficient nor aligned with the standard finite element method(FEM).Single-step-based neural networks like the multi-layer perceptron(MLP)are an alternative to bypass the above issues but have to introduce some internal variables to encode complex loading histories.In this work,one novel Frobenius norm-based internal variable,together with the Fourier layer and residual architectureenhanced MLP model,is crafted to replicate the history-dependent constitutive features of representative volume element(RVE)for granular materials.The obtained ML models are then seamlessly embedded into the FEM to solve the BVP of a biaxial compression case and a rigid strip footing case.The obtained solutions are comparable to results from the FEM-DEM multiscale modelling but achieve significantly improved efficiency.The results demonstrate the applicability of the proposed internal variable in enabling MLP to capture highly nonlinear constitutive responses of granular materials. 展开更多
关键词 Granular materials History-dependence multi-layer perceptron(MLP) Discrete element method FEM-DEM Machine learning
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Target Controllability of Multi-Layer Networks With High-Dimensional Nodes
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作者 Lifu Wang Zhaofei Li +1 位作者 Ge Guo Zhi Kong 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2024年第9期1999-2010,共12页
This paper studies the target controllability of multilayer complex networked systems,in which the nodes are highdimensional linear time invariant(LTI)dynamical systems,and the network topology is directed and weighte... This paper studies the target controllability of multilayer complex networked systems,in which the nodes are highdimensional linear time invariant(LTI)dynamical systems,and the network topology is directed and weighted.The influence of inter-layer couplings on the target controllability of multi-layer networks is discussed.It is found that even if there exists a layer which is not target controllable,the entire multi-layer network can still be target controllable due to the inter-layer couplings.For the multi-layer networks with general structure,a necessary and sufficient condition for target controllability is given by establishing the relationship between uncontrollable subspace and output matrix.By the derived condition,it can be found that the system may be target controllable even if it is not state controllable.On this basis,two corollaries are derived,which clarify the relationship between target controllability,state controllability and output controllability.For the multi-layer networks where the inter-layer couplings are directed chains and directed stars,sufficient conditions for target controllability of networked systems are given,respectively.These conditions are easier to verify than the classic criterion. 展开更多
关键词 High-dimensional nodes inter-layer couplings multi-layer networks target controllability
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A flexible ultra-broadband multi-layered absorber working at 2 GHz-40 GHz printed by resistive ink
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作者 汪涛 闫玉伦 +3 位作者 陈巩华 李迎 胡俊 毛剑波 《Chinese Physics B》 SCIE EI CAS CSCD 2024年第2期329-333,共5页
A flexible extra broadband metamaterial absorber(MMA)stacked with five layers working at 2 GHz–40 GHz is investigated.Each layer is composed of polyvinyl chloride(PVC),polyimide(PI),and a frequency selective surface(... A flexible extra broadband metamaterial absorber(MMA)stacked with five layers working at 2 GHz–40 GHz is investigated.Each layer is composed of polyvinyl chloride(PVC),polyimide(PI),and a frequency selective surface(FSS),which is printed on PI using conductive ink.To investigate this absorber,both one-dimensional analogous circuit analysis and three-dimensional full-wave simulation based on a physical model are provided.Various crucial electromagnetic properties,such as absorption,effective impedance,complex permittivity and permeability,electric current distribution and magnetic field distribution at resonant peak points,are studied in detail.Analysis shows that the working frequency of this absorber covers entire S,C,X,Ku,K and Ka bands with a minimum thickness of 0.098λ_(max)(λ_(max) is the maximum wavelength in the absorption band),and the fractional bandwidth(FBW)reaches 181.1%.Moreover,the reflection coefficient is less than-10 dB at 1.998 GHz–40.056 GHz at normal incidence,and the absorptivity of the plane wave is greater than 80%when the incident angle is smaller than 50°.Furthermore,the proposed absorber is experimentally validated,and the experimental results show good agreement with the simulation results,which demonstrates the potential applicability of this absorber at 2 GHz–40 GHz. 展开更多
关键词 extra broadband physical model flexible metamaterial absorber multi-layer frequency selective surface
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Dynamic Multi-Layer Perceptron for Fetal Health Classification Using Cardiotocography Data
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作者 Uddagiri Sirisha Parvathaneni Naga Srinivasu +4 位作者 Panguluri Padmavathi Seongki Kim Aruna Pavate Jana Shafi Muhammad Fazal Ijaz 《Computers, Materials & Continua》 SCIE EI 2024年第8期2301-2330,共30页
Fetal health care is vital in ensuring the health of pregnant women and the fetus.Regular check-ups need to be taken by the mother to determine the status of the fetus’growth and identify any potential problems.To kn... Fetal health care is vital in ensuring the health of pregnant women and the fetus.Regular check-ups need to be taken by the mother to determine the status of the fetus’growth and identify any potential problems.To know the status of the fetus,doctors monitor blood reports,Ultrasounds,cardiotocography(CTG)data,etc.Still,in this research,we have considered CTG data,which provides information on heart rate and uterine contractions during pregnancy.Several researchers have proposed various methods for classifying the status of fetus growth.Manual processing of CTG data is time-consuming and unreliable.So,automated tools should be used to classify fetal health.This study proposes a novel neural network-based architecture,the Dynamic Multi-Layer Perceptron model,evaluated from a single layer to several layers to classify fetal health.Various strategies were applied,including pre-processing data using techniques like Balancing,Scaling,Normalization hyperparameter tuning,batch normalization,early stopping,etc.,to enhance the model’s performance.A comparative analysis of the proposed method is done against the traditional machine learning models to showcase its accuracy(97%).An ablation study without any pre-processing techniques is also illustrated.This study easily provides valuable interpretations for healthcare professionals in the decision-making process. 展开更多
关键词 Fetal health cardiotocography data deep learning dynamic multi-layer perceptron feature engineering
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Multi-layer network embedding on scc-based network with motif
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作者 Lu Sun Xiaona Li +4 位作者 Mingyue Zhang Liangtian Wan Yun Lin Xianpeng Wang Gang Xu 《Digital Communications and Networks》 SCIE CSCD 2024年第3期546-556,共11页
Interconnection of all things challenges the traditional communication methods,and Semantic Communication and Computing(SCC)will become new solutions.It is a challenging task to accurately detect,extract,and represent... Interconnection of all things challenges the traditional communication methods,and Semantic Communication and Computing(SCC)will become new solutions.It is a challenging task to accurately detect,extract,and represent semantic information in the research of SCC-based networks.In previous research,researchers usually use convolution to extract the feature information of a graph and perform the corresponding task of node classification.However,the content of semantic information is quite complex.Although graph convolutional neural networks provide an effective solution for node classification tasks,due to their limitations in representing multiple relational patterns and not recognizing and analyzing higher-order local structures,the extracted feature information is subject to varying degrees of loss.Therefore,this paper extends from a single-layer topology network to a multi-layer heterogeneous topology network.The Bidirectional Encoder Representations from Transformers(BERT)training word vector is introduced to extract the semantic features in the network,and the existing graph neural network is improved by combining the higher-order local feature module of the network model representation network.A multi-layer network embedding algorithm on SCC-based networks with motifs is proposed to complete the task of end-to-end node classification.We verify the effectiveness of the algorithm on a real multi-layer heterogeneous network. 展开更多
关键词 Semantic communication and computing multi-layer network Graph neural network MOTIF
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Dynamic interwell connectivity analysis of multi-layer waterflooding reservoirs based on an improved graph neural network
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作者 Zhao-Qin Huang Zhao-Xu Wang +4 位作者 Hui-Fang Hu Shi-Ming Zhang Yong-Xing Liang Qi Guo Jun Yao 《Petroleum Science》 SCIE EI CAS CSCD 2024年第2期1062-1080,共19页
The analysis of interwell connectivity plays an important role in the formulation of oilfield development plans and the description of residual oil distribution. In fact, sandstone reservoirs in China's onshore oi... The analysis of interwell connectivity plays an important role in the formulation of oilfield development plans and the description of residual oil distribution. In fact, sandstone reservoirs in China's onshore oilfields generally have the characteristics of thin and many layers, so multi-layer joint production is usually adopted. It remains a challenge to ensure the accuracy of splitting and dynamic connectivity in each layer of the injection-production wells with limited field data. The three-dimensional well pattern of multi-layer reservoir and the relationship between injection-production wells can be equivalent to a directional heterogeneous graph. In this paper, an improved graph neural network is proposed to construct an interacting process mimics the real interwell flow regularity. In detail, this method is used to split injection and production rates by combining permeability, porosity and effective thickness, and to invert the dynamic connectivity in each layer of the injection-production wells by attention mechanism.Based on the material balance and physical information, the overall connectivity from the injection wells,through the water injection layers to the production layers and the output of final production wells is established. Meanwhile, the change of well pattern caused by perforation, plugging and switching of wells at different times is achieved by updated graph structure in spatial and temporal ways. The effectiveness of the method is verified by a combination of reservoir numerical simulation examples and field example. The method corresponds to the actual situation of the reservoir, has wide adaptability and low cost, has good practical value, and provides a reference for adjusting the injection-production relationship of the reservoir and the development of the remaining oil. 展开更多
关键词 Graph neural network Dynamic interwell connectivity Production-injection splitting Attention mechanism multi-layer reservoir
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Target layer state estimation in multi-layer complex dynamical networks considering nonlinear node dynamics
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作者 吴亚勇 王欣伟 蒋国平 《Chinese Physics B》 SCIE EI CAS CSCD 2024年第4期245-252,共8页
In many engineering networks, only a part of target state variables are required to be estimated.On the other hand,multi-layer complex network exists widely in practical situations.In this paper, the state estimation ... In many engineering networks, only a part of target state variables are required to be estimated.On the other hand,multi-layer complex network exists widely in practical situations.In this paper, the state estimation of target state variables in multi-layer complex dynamical networks with nonlinear node dynamics is studied.A suitable functional state observer is constructed with the limited measurement.The parameters of the designed functional observer are obtained from the algebraic method and the stability of the functional observer is proven by the Lyapunov theorem.Some necessary conditions that need to be satisfied for the design of the functional state observer are obtained.Different from previous studies, in the multi-layer complex dynamical network with nonlinear node dynamics, the proposed method can estimate the state of target variables on some layers directly instead of estimating all the individual states.Thus, it can greatly reduce the placement of observers and computational cost.Numerical simulations with the three-layer complex dynamical network composed of three-dimensional nonlinear dynamical nodes are developed to verify the effectiveness of the method. 展开更多
关键词 multi-layer complex dynamical network nonlinear node dynamics target state estimation functional state observer
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Multi-layer phenomena in petawatt laser-driven acceleration of heavy ions
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作者 苏琬晴 曹喜光 +2 位作者 马春旺 王玉廷 张国强 《Plasma Science and Technology》 SCIE EI CAS CSCD 2024年第2期70-76,共7页
Laser-accelerated high-flux-intensity heavy-ion beams are important for new types of accelerators.A particle-in-cell program(Smilei) is employed to simulate the entire process of Station of Extreme Light(SEL) 100 PW l... Laser-accelerated high-flux-intensity heavy-ion beams are important for new types of accelerators.A particle-in-cell program(Smilei) is employed to simulate the entire process of Station of Extreme Light(SEL) 100 PW laser-accelerated heavy particles using different nanoscale short targets with a thickness of 100 nm Cr, Fe, Ag, Ta, Au, Pb, Th and U, as well as 200 nm thick Al and Ca. An obvious stratification is observed in the simulation. The layering phenomenon is a hybrid acceleration mechanism reflecting target normal sheath acceleration and radiation pressure acceleration, and this phenomenon is understood from the simulated energy spectrum,ionization and spatial electric field distribution. According to the stratification, it is suggested that high-quality heavy-ion beams could be expected for fusion reactions to synthesize superheavy nuclei. Two plasma clusters in the stratification are observed simultaneously, which suggest new techniques for plasma experiments as well as thinner metal targets in the precision machining process. 展开更多
关键词 petawatt laser-plasma interaction laser-driven heavy-ion accelerator for synthesizing superheavy nuclei PARTICLE-IN-CELL multi-layer phenomena target fabrication
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A Well Productivity Model for Multi-Layered Marine and Continental Transitional Reservoirs with Complex Fracture Networks
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作者 Huiyan Zhao Xuezhong Chen +3 位作者 Zhijian Hu Man Chen Bo Xiong Jianying Yang 《Fluid Dynamics & Materials Processing》 EI 2024年第6期1313-1330,共18页
Using the typical characteristics of multi-layered marine and continental transitional gas reservoirs as a basis,a model is developed to predict the related well production rate.This model relies on the fractal theory... Using the typical characteristics of multi-layered marine and continental transitional gas reservoirs as a basis,a model is developed to predict the related well production rate.This model relies on the fractal theory of tortuous capillary bundles and can take into account multiple gas flow mechanisms at the micrometer and nanometer scales,as well as the flow characteristics in different types of thin layers(tight sandstone gas,shale gas,and coalbed gas).Moreover,a source-sink function concept and a pressure drop superposition principle are utilized to introduce a coupled flow model in the reservoir.A semi-analytical solution for the production rate is obtained using a matrix iteration method.A specific well is selected for fitting dynamic production data,and the calculation results show that the tight sandstone has the highest gas production per unit thickness compared with the other types of reservoirs.Moreover,desorption and diffusion of coalbed gas and shale gas can significantly contribute to gas production,and the daily production of these two gases decreases rapidly with decreasing reservoir pressure.Interestingly,the gas production from fractures exhibits an approximately U-shaped distribution,indicating the need to optimize the spacing between clusters during hydraulic fracturing to reduce the area of overlapping fracture control.The coal matrix water saturation significantly affects the coalbed gas production,with higher water saturation leading to lower production. 展开更多
关键词 Marine-continental transitional reservoir multi-layered reservoir seepage mechanisms apparent permeability hydraulic horizontal well productivity model
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Five-phase Synchronous Reluctance Machines Equipped with a Novel Type of Fractional Slot Winding
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作者 S.M.Taghavi Araghi A.Kiyoumarsi B.Mirzaeian Dehkordi 《CES Transactions on Electrical Machines and Systems》 EI CSCD 2024年第3期264-273,共10页
Multi-phase machines are so attractive for electrical machine designers because of their valuable advantages such as high reliability and fault tolerant ability.Meanwhile,fractional slot concentrated windings(FSCW)are... Multi-phase machines are so attractive for electrical machine designers because of their valuable advantages such as high reliability and fault tolerant ability.Meanwhile,fractional slot concentrated windings(FSCW)are well known because of short end winding length,simple structure,field weakening sufficiency,fault tolerant capability and higher slot fill factor.The five-phase machines equipped with FSCW,are very good candidates for the purpose of designing motors for high reliable applications,like electric cars,major transporting buses,high speed trains and massive trucks.But,in comparison to the general distributed windings,the FSCWs contain high magnetomotive force(MMF)space harmonic contents,which cause unwanted effects on the machine ability,such as localized iron saturation and core losses.This manuscript introduces several new five-phase fractional slot winding layouts,by the means of slot shifting concept in order to design the new types of synchronous reluctance motors(SynRels).In order to examine the proposed winding’s performances,three sample machines are designed as case studies,and analytical study and finite element analysis(FEA)is used for validation. 展开更多
关键词 Finite element analysis Five-phase machine Fractional slot concentrated winding(FSCW) Machine slot/pole combination MMF harmonics Synchronous reluctance machine winding factor
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Multi-Layer Feature Extraction with Deformable Convolution for Fabric Defect Detection
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作者 Jielin Jiang Chao Cui +1 位作者 Xiaolong Xu Yan Cui 《Intelligent Automation & Soft Computing》 2024年第4期725-744,共20页
In the textile industry,the presence of defects on the surface of fabric is an essential factor in determining fabric quality.Therefore,identifying fabric defects forms a crucial part of the fabric production process.... In the textile industry,the presence of defects on the surface of fabric is an essential factor in determining fabric quality.Therefore,identifying fabric defects forms a crucial part of the fabric production process.Traditional fabric defect detection algorithms can only detect specific materials and specific fabric defect types;in addition,their detection efficiency is low,and their detection results are relatively poor.Deep learning-based methods have many advantages in the field of fabric defect detection,however,such methods are less effective in identifying multiscale fabric defects and defects with complex shapes.Therefore,we propose an effective algorithm,namely multilayer feature extraction combined with deformable convolution(MFDC),for fabric defect detection.In MFDC,multi-layer feature extraction is used to fuse the underlying location features with high-level classification features through a horizontally connected top-down architecture to improve the detection of multi-scale fabric defects.On this basis,a deformable convolution is added to solve the problem of the algorithm’s weak detection ability of irregularly shaped fabric defects.In this approach,Roi Align and Cascade-RCNN are integrated to enhance the adaptability of the algorithm in materials with complex patterned backgrounds.The experimental results show that the MFDC algorithm can achieve good detection results for both multi-scale fabric defects and defects with complex shapes,at the expense of a small increase in detection time. 展开更多
关键词 Fabric defect detection multi-layer features deformable convolution
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Winding Function Model-based Performance Evaluation of a PM Transverse Flux Generator for Applications in Direct-drive Systems
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作者 Mehrage Ghods Jawad Faiz Ali A Pourmoosa 《CES Transactions on Electrical Machines and Systems》 EI CSCD 2024年第2期216-226,共11页
The magnetic flux in a permanent magnet transverse flux generator(PMTFG) is three-dimensional(3D), therefore, its efficacy is evaluated using 3D magnetic field analysis. Although the 3D finite-element method(FEM) is h... The magnetic flux in a permanent magnet transverse flux generator(PMTFG) is three-dimensional(3D), therefore, its efficacy is evaluated using 3D magnetic field analysis. Although the 3D finite-element method(FEM) is highly accurate and reliable for machine simulation, it requires a long computation time, which is crucial when it is to be used in an iterative optimization process. Therefore, an alternative to 3DFEM is required as a rapid and accurate analytical technique. This paper presents an analytical model for PMTFG analysis using winding function method. To obtain the air gap MMF distribution, the excitation magneto-motive force(MMF) and the turn function are determined based on certain assumptions. The magnetizing inductance, flux density, and back-electro-magnetomotive force of the winding are then determined. To assess the accuracy of the proposed method, the analytically calculated parameters of the generator are compared to those obtained by a 3D-FEM. The presented method requires significantly shorter computation time than the 3D-FEM with comparable accuracy. 展开更多
关键词 Index Terms—Permanent magnet transverse flux generator winding function 3D-FEM Cogging torque PROTOTYPING
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Adaptive RISE Control of Winding Tension with Active Disturbance Rejection
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作者 Junjie Mi Jianyong Yao Wenxiang Deng 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2024年第4期135-145,共11页
A winding system is a time-varying system that considers complex nonlinear characteristics,and how to control the stability of the winding tension during the winding process is the primary problem that has hindered de... A winding system is a time-varying system that considers complex nonlinear characteristics,and how to control the stability of the winding tension during the winding process is the primary problem that has hindered development in this field in recent years.Many nonlinear factors affect the tension in the winding process,such as friction,structured uncertainties,unstructured uncertainties,and external interference.These terms severely restrict the tension tracking performance.Existing tension control strategies are mainly based on the composite control of the tension and speed loops,and previous studies involve complex decoupling operations.Owing to the large number of calculations required for this method,it is inconvenient for practical engineering applications.To simplify the tension generation mechanism and the influence of the nonlinear characteristics of the winding system,a simpler nonlinear dynamic model of the winding tension was established.An adaptive method was applied to update the feedback gain of the continuous robust integral of the sign of the error(RISE).Furthermore,an extended state observer was used to estimate modeling errors and external disturbances.The model disturbance term can be compensated for in the designed RISE controller.The asymptotic stability of the system was proven according to the Lyapunov stability theory.Finally,a comparative analysis of the proposed nonlinear controller and several other controllers was performed.The results indicated that the control of the winding tension was significantly enhanced. 展开更多
关键词 winding tension Continuous robust integral of the sign of the error(RISE)control Adaptive control Disturbance compensation Extended state observer(ESO) Tension control
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Blast wave characteristics of multi-layer composite charge:Theoretical analysis,numerical simulation,and experimental validation 被引量:1
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作者 Jun-bao Li Wei-bing Li +2 位作者 Xiao-wen Hong Jia-xin Yu Jian-jun Zhu 《Defence Technology(防务技术)》 SCIE EI CAS CSCD 2023年第1期91-102,共12页
This article investigates the characteristics of shock wave overpressure generated by multi-layer composite charge under different detonation modes.Combining dimensional analysis and the explosion mechanism of the cha... This article investigates the characteristics of shock wave overpressure generated by multi-layer composite charge under different detonation modes.Combining dimensional analysis and the explosion mechanism of the charge,a peak overpressure prediction model for the composite charge under singlepoint detonation and simultaneous detonation was established.The effects of the charge structure and initiation method on the overpressure field characteristics were investigated in AUTODYN simulation.The accuracy of the prediction model and the reliability of the numerical simulation method were subsequently verified in a series of static explosion experiments.The results reveal that the mass of the inner charge was the key factor determining the peak overpressure of the composite charge under single-point detonation.The peak overpressure in the radial direction improved apparently with an increase in the aspect ratio of the charge.The overpressure curves in the axial direction exhibited a multi-peak phenomenon,and the secondary peak overpressure even exceeded the primary peak at distances of 30D and 40D(where D is the charge diameter).The difference in peak overpressure among azimuth angles of 0-90°gradually decreased with an increase in the propagation distance of the shock wave.The coupled effect of the detonation energy of the inner and outer charge under simultaneous detonation improved the overpressure in both radial and axial directions.The difference in peak overpressure obtained from model prediction and experimental measurements was less than 16.4%. 展开更多
关键词 Blast wave characteristics multi-layer composite charge Dimensional analysis AUTODYN mapping Model Explosion experiment
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Optimizing slope safety factor prediction via stacking using sparrow search algorithm for multi-layer machine learning regression models 被引量:1
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作者 SHUI Kuan HOU Ke-peng +2 位作者 HOU Wen-wen SUN Jun-long SUN Hua-fen 《Journal of Mountain Science》 SCIE CSCD 2023年第10期2852-2868,共17页
The safety factor is a crucial quantitative index for evaluating slope stability.However,the traditional calculation methods suffer from unreasonable assumptions,complex soil composition,and inadequate consideration o... The safety factor is a crucial quantitative index for evaluating slope stability.However,the traditional calculation methods suffer from unreasonable assumptions,complex soil composition,and inadequate consideration of the influencing factors,leading to large errors in their calculations.Therefore,a stacking ensemble learning model(stacking-SSAOP)based on multi-layer regression algorithm fusion and optimized by the sparrow search algorithm is proposed for predicting the slope safety factor.In this method,the density,cohesion,friction angle,slope angle,slope height,and pore pressure ratio are selected as characteristic parameters from the 210 sets of established slope sample data.Random Forest,Extra Trees,AdaBoost,Bagging,and Support Vector regression are used as the base model(inner loop)to construct the first-level regression algorithm layer,and XGBoost is used as the meta-model(outer loop)to construct the second-level regression algorithm layer and complete the construction of the stacked learning model for improving the model prediction accuracy.The sparrow search algorithm is used to optimize the hyperparameters of the above six regression models and correct the over-and underfitting problems of the single regression model to further improve the prediction accuracy.The mean square error(MSE)of the predicted and true values and the fitting of the data are compared and analyzed.The MSE of the stacking-SSAOP model was found to be smaller than that of the single regression model(MSE=0.03917).Therefore,the former has a higher prediction accuracy and better data fitting.This study innovatively applies the sparrow search algorithm to predict the slope safety factor,showcasing its advantages over traditional methods.Additionally,our proposed stacking-SSAOP model integrates multiple regression algorithms to enhance prediction accuracy.This model not only refines the prediction accuracy of the slope safety factor but also offers a fresh approach to handling the intricate soil composition and other influencing factors,making it a precise and reliable method for slope stability evaluation.This research holds importance for the modernization and digitalization of slope safety assessments. 展开更多
关键词 multi-layer regression algorithm fusion Stacking gensemblelearning Sparrow search algorithm Slope safety factor Data prediction
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Winding Function Theory Based Thrust Calculation on Nested-loop Secondary Linear Machine Adapted to Linear Metro 被引量:1
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作者 Yaping Zhang Jian Ge +5 位作者 Wei Xu Hao Tang Yang Gao Xiaoliang Chen Shihu Su Zhen Bao 《CES Transactions on Electrical Machines and Systems》 CSCD 2023年第2期153-162,共10页
With advantages of strong drive capability,nested-loop secondary linear machine(NLS-LM)has great potentiality in linear metro.For its secondary structure with multiple loops,it is difficult to calculate the electromag... With advantages of strong drive capability,nested-loop secondary linear machine(NLS-LM)has great potentiality in linear metro.For its secondary structure with multiple loops,it is difficult to calculate the electromagnetic thrust of NLS-LM reasonably.Hence,in this paper,one thrust calculation method is proposed considering variable loop inductance and transient loop current.Firstly,to establish the secondary winding function,the modeling domain is confined to a limited range,and the equivalent loop span is employed by analyzing the coupling relationship between primary and secondary.Then,in order to obtain the secondary flux density,the transient secondary current is solved based on the loop impedance and induced voltage.Finally,the electromagnetic thrust can be calculated reasonably by the given primary current sheet and the calculated secondary flux density.Comprehensive simulations and experiments have demonstrated the effectiveness of the proposed method. 展开更多
关键词 Nested-loop secondary Linear metro Electro-magnetic thrust Finite element algorithm(FEA) Transient nested-loop current winding function
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Explosive synchronization of multi-layer complex networks based on star connection between layers with delay
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作者 金彦亮 韩钱源 +2 位作者 郭润珠 高塬 沈礼权 《Chinese Physics B》 SCIE EI CAS CSCD 2023年第10期343-349,共7页
Explosive synchronization(ES)is a kind of first-order jump phenomenon that exists in physical and biological systems.In recent years,researchers have focused on ES between single-layer and multi-layer networks.Most re... Explosive synchronization(ES)is a kind of first-order jump phenomenon that exists in physical and biological systems.In recent years,researchers have focused on ES between single-layer and multi-layer networks.Most research on complex networks with delay has focused on single-layer or double-layer networks,multi-layer networks are seldom explored.In this paper,we propose a Kuramoto model of frequency weights in multi-layer complex networks with delay and star connections between layers.Through theoretical analysis and numerical verification,the factors affecting the backward critical coupling strength are analyzed.The results show that the interaction between layers and the average node degree has a direct effect on the backward critical coupling strength of each layer network.The location of the delay,the size of the delay,the number of network layers,the number of nodes,and the network topology are revealed to have no direct impact on the backward critical coupling strength of the network.Delay is introduced to explore the influence of delay and other related parameters on ES. 展开更多
关键词 multi-layer networks Kuramoto model explosive synchronization DELAY
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Solar wind ion charge state distributions and compound cross sections for solar wind charge exchange X-ray emission 被引量:1
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作者 Dimitra Koutroumpa 《Earth and Planetary Physics》 EI CSCD 2024年第1期105-118,共14页
Solar Wind Charge eXchange X-ray(SWCX) emission in the heliosphere and Ea rth’s exosphere is a hard to avoid signal in soft Xray obse rvations of astrophysical targets.On the other hand,the X-ray imaging possibilitie... Solar Wind Charge eXchange X-ray(SWCX) emission in the heliosphere and Ea rth’s exosphere is a hard to avoid signal in soft Xray obse rvations of astrophysical targets.On the other hand,the X-ray imaging possibilities offered by the SWCX process has led to an increasing number of future dedicated space missions for investigating the solar wind-terrestrial inte ractions and magnetospheric interfaces.In both cases,accurate modelling of the SWCX emission is key to correctly interpret its signal,and remove it from obse rvations,when needed.In this paper,we compile solar wind abundance measurements from ACE for different solar wind types,and atomic data from literature,including charge exchange cross-sections and emission probabilities,used fo r calculating the compound cross-section a for the SWCX X-ray emission.We calculate a values for charge-exchange with H and He,relevant to soft X-ray energy bands(0.1-2.0 keV)for various solar wind types and solar cycle conditions. 展开更多
关键词 solar wind charge exchange X-rays MAGNETOSPHERE HELIOSPHERE
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U-Net Models for Representing Wind Stress Anomalies over the Tropical Pacific and Their Integrations with an Intermediate Coupled Model for ENSO Studies 被引量:1
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作者 Shuangying Du Rong-Hua Zhang 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2024年第7期1403-1416,共14页
El Niño-Southern Oscillation(ENSO)is the strongest interannual climate mode influencing the coupled ocean-atmosphere system in the tropical Pacific,and numerous dynamical and statistical models have been develope... El Niño-Southern Oscillation(ENSO)is the strongest interannual climate mode influencing the coupled ocean-atmosphere system in the tropical Pacific,and numerous dynamical and statistical models have been developed to simulate and predict it.In some simplified coupled ocean-atmosphere models,the relationship between sea surface temperature(SST)anomalies and wind stress(τ)anomalies can be constructed by statistical methods,such as singular value decomposition(SVD).In recent years,the applications of artificial intelligence(AI)to climate modeling have shown promising prospects,and the integrations of AI-based models with dynamical models are active areas of research.This study constructs U-Net models for representing the relationship between SSTAs andτanomalies in the tropical Pacific;the UNet-derivedτmodel,denoted asτUNet,is then used to replace the original SVD-basedτmodel of an intermediate coupled model(ICM),forming a newly AI-integrated ICM,referred to as ICM-UNet.The simulation results obtained from ICM-UNet demonstrate their ability to represent the spatiotemporal variability of oceanic and atmospheric anomaly fields in the equatorial Pacific.In the ocean-only case study,theτUNet-derived wind stress anomaly fields are used to force the ocean component of the ICM,the results of which also indicate reasonable simulations of typical ENSO events.These results demonstrate the feasibility of integrating an AI-derived model with a physics-based dynamical model for ENSO modeling studies.Furthermore,the successful integration of the dynamical ocean models with the AI-based atmospheric wind model provides a novel approach to ocean-atmosphere interaction modeling studies. 展开更多
关键词 U-Net models wind stress anomalies ICM integration of AI and physical components
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