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An Improved Time Domain Approach for Analysis of Floating Bridges Based on Dynamic Finite Element Method and State-Space Model 认领 引用 被引量：3
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作者 XIANG Sheng CHENG Bin +1 位作者 ZHANG Feng-yu TANG Miao 《China Ocean Engineering》 SCIE EI CSCD 2022年第5期682-696,共15页
The floating bridge bears the dead weight and live load with buoyancy,and has wide application prospect in deep-water transportation infrastructure.The structural analysis of floating bridge is challenging due to the ... The floating bridge bears the dead weight and live load with buoyancy,and has wide application prospect in deep-water transportation infrastructure.The structural analysis of floating bridge is challenging due to the complicated fluid-solid coupling effects of wind and wave.In this research,a novel time domain approach combining dynamic finite element method and state-space model(SSM)is established for the refined analysis of floating bridges.The dynamic coupled effects induced by wave excitation load,radiation load and buffeting load are carefully simulated.High-precision fitted SSMs for pontoons are established to enhance the calculation efficiency of hydrodynamic radiation forces in time domain.The dispersion relation is also introduced in the analysis model to appropriately consider the phase differences of wave loads on pontoons.The proposed approach is then employed to simulate the dynamic responses of a scaled floating bridge model which has been tested under real wind and wave loads in laboratory.The numerical results are found to agree well with the test data regarding the structural responses of floating bridge under the considered environmental conditions.The proposed time domain approach is considered to be accurate and effective in simulating the structural behaviors of floating bridge under typical environmental conditions. 展开更多
关键词 floating bridge time domain analysis dynamic analysis state-space model environmental load
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The Empirical Analysis on the Dynamic Effect of Rural-urban Migration on the Consumption Growth of Residents in China——Based on Varying Parameter State-space Model 认领 引用 被引量：1
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作者 邹小芳 《Agricultural Science & Technology》 CAS 2016年第2期471-475,共5页
The research constructed varying parameter state-space model and per- formed estimation on dynamic relationship between urban-rural migration and aggre- gate consumption expenditure on basis of dual economic structure... The research constructed varying parameter state-space model and per- formed estimation on dynamic relationship between urban-rural migration and aggre- gate consumption expenditure on basis of dual economic structure. The results showed that urban consumption growth made the most contribution to aggregate consumption growth, followed by urban-rural migration caused consumption. The role of rural consumption growth kept stable, but consumption caused by population growth was decreasing. Therefore, China consumption growth mainly relies on urban consumption expenditure and urban-rural migration. 展开更多
关键词 Rural-urban migration Household consumption expenditure Urbanization State-space Model
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Identification of the state-space model and payload mass parameter of a flexible space manipulator using a recursive subspace tracking method 认领 引用 被引量：9
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作者 Zhiyu NI Jinguo LIU +1 位作者 Zhigang WU Xinhui SHEN 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2019年第2期513-530,共18页
The on-orbit parameter identification of a space structure can be used for the modification of a system dynamics model and controller coefficients. This study focuses on the estimation of a system state-space model fo... The on-orbit parameter identification of a space structure can be used for the modification of a system dynamics model and controller coefficients. This study focuses on the estimation of a system state-space model for a two-link space manipulator in the procedure of capturing an unknown object, and a recursive tracking approach based on the recursive predictor-based subspace identification(RPBSID) algorithm is proposed to identify the manipulator payload mass parameter. Structural rigid motion and elastic vibration are separated, and the dynamics model of the space manipulator is linearized at an arbitrary working point(i.e., a certain manipulator configuration).The state-space model is determined by using the RPBSID algorithm and matrix transformation. In addition, utilizing the identified system state-space model, the manipulator payload mass parameter is estimated by extracting the corresponding block matrix. In numerical simulations, the presented parameter identification method is implemented and compared with the classical algebraic algorithm and the recursive least squares method for different payload masses and manipulator configurations. Numerical results illustrate that the system state-space model and payload mass parameter of the two-link flexible space manipulator are effectively identified by the recursive subspace tracking method. 展开更多
关键词 Flexible space manipulator Linearization Parameter identification State-space model Subspace methods
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PEMFC Identification Based on a Fractional-Order Hammerstein State-Space Model with ADE-BH Optimization 认领 引用 被引量：1
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作者 Qin Hao Qi Zhidong +1 位作者 Ye Weiqin Sun Chengshuo 《China Petroleum Processing & Petrochemical Technology》 SCIE CAS CSCD 2023年第2期155-164,共10页
Considering the fractional-order and nonlinear characteristics of proton exchange membrane fuel cells(PEMFC),a fractional-order subspace identification method based on the ADE-BH optimization algorithm is proposed to ... Considering the fractional-order and nonlinear characteristics of proton exchange membrane fuel cells(PEMFC),a fractional-order subspace identification method based on the ADE-BH optimization algorithm is proposed to establish a fractional-order Hammerstein state-space model of PEMFCs.Herein,a Hammerstein model is constructed by connecting a linear module and a nonlinear module in series to precisely depict the nonlinear property of the PEMFC.During the modeling process,fractional-order theory is combined with subspace identification,and a Poisson filter is adopted to enable multi-order derivability of the data.A variable memory method is introduced to reduce computation time without losing precision.Additionally,to improve the optimization accuracy and avoid obtaining locally optimum solutions,a novel ADEBH algorithm is employed to optimize the unknown parameters in the identification method.In this algorithm,the Euclidean distance serves as the theoretical basis for updating the target vector in the absorption-generation operation of the black hole(BH)algorithm.Finally,simulations demonstrate that the proposed model has small output error and high accuracy,indicating that the model can accurately describe the electrical characteristics of the PEMFC process. 展开更多
关键词 PEMFC Hammerstein model Fractional subspace identification ADE-BH optimization
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Least Squares Matrix Algorithm for State-Space Modelling of Dynamic Systems 认领 引用 被引量：1
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作者 Juuso T. Olkkonen Hannu Olkkonen 《Journal of Signal and Information Processing》 2011年第4期287-291,共5页
This work presents a novel least squares matrix algorithm (LSM) for the analysis of rapidly changing systems using state-space modelling. The LSM algorithm is based on the Hankel structured data matrix representation.... This work presents a novel least squares matrix algorithm (LSM) for the analysis of rapidly changing systems using state-space modelling. The LSM algorithm is based on the Hankel structured data matrix representation. The state transition matrix is updated without the use of any forgetting function. This yields a robust estimation of model parameters in the presence of noise. The computational complexity of the LSM algorithm is comparable to the speed of the conventional recursive least squares (RLS) algorithm. The knowledge of the state transition matrix enables feasible numerical operators such as interpolation, fractional differentiation and integration. The usefulness of the LSM algorithm was proved in the analysis of the neuroelectric signal waveforms. 展开更多
关键词 State-Space Modelling Dynamic System Analysis EEG
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Recursive State-space Model Identification of Non-uniformly Sampled Systems Using Singular Value Decomposition 认领 引用 被引量：6
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作者 王宏伟 刘涛 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2014年第Z1期1268-1273,共6页
In this paper a recursive state-space model identification method is proposed for non-uniformly sampled systems in industrial applications. Two cases for measuring all states and only output(s) of such a system are co... In this paper a recursive state-space model identification method is proposed for non-uniformly sampled systems in industrial applications. Two cases for measuring all states and only output(s) of such a system are considered for identification. In the case of state measurement, an identification algorithm based on the singular value decomposition(SVD) is developed to estimate the model parameter matrices by using the least-squares fitting. In the case of output measurement only, another identification algorithm is given by combining the SVD approach with a hierarchical identification strategy. An example is used to demonstrate the effectiveness of the proposed identification method. 展开更多
关键词 Non-uniformly sampling system State-space model identification Singular value decomposition Recursive algorithm
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Numerical method for solving dynamical equations of multibody systems with nonholonomic constraints based on state-space method 认领 引用
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作者 Jiajun Wu Xian Guo +3 位作者 Dingguo Zhang Yue Zhang Liang Li Kang Guo 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2026年第7期505-520,共16页
In this paper,a new numerical solution method is proposed for dealing with differential-algebraic equations(DAEs)for dynamics of multibody systems with nonholonomic constraints.The nonholonomic constraints directly re... In this paper,a new numerical solution method is proposed for dealing with differential-algebraic equations(DAEs)for dynamics of multibody systems with nonholonomic constraints.The nonholonomic constraints directly restrict the velocity coor-dinates,resulting in no corresponding position constraint equations.Therefore,the traditional state-space method is insufficient to solve such DAEs.In the proposed state-space method,direct integration of the ordinary differential equations obtained from the index-1 DAEs,ensures that the acceleration constraints are satisfied and provides initial values for the dependent variables.Subsequently,position and velocity constraint equations are solved to update dependent variables,strictly ensuring satisfaction of constraints at three levels.Currently,LU decomposition is the most used method to define the state-space method.However,in order to ensure the accuracy and stability of the algorithm,coordinate identification is required at every time step,which reduces the computational efficiency.Therefore,in this paper,the state-space method defined by singular value decomposition(SVD)is proposed,which does not require frequent coordinate identification and improves the computational efficiency.Numerical exam-ples show that the state-space method based on SVD outperforms the LU decomposition in terms of computational efficiency and stability. 展开更多
关键词 Multibody system dynamics Nonholonomic constraints Differential algebraic equations State-space method
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State-space modelling for infectious disease surveillance data:Dynamic regression and covariance analysis 认领 引用
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作者 Christopher D.Prashad 《Infectious Disease Modelling》 CSCD 2025年第2期591-627,共37页
We analyze COVID-19 surveillance data from Ontario,Canada,using state-space modelling techniques to address key challenges in understanding disease transmission dynamics.The study applies component linear Gaussian sta... We analyze COVID-19 surveillance data from Ontario,Canada,using state-space modelling techniques to address key challenges in understanding disease transmission dynamics.The study applies component linear Gaussian state-space models to capture periodicity,trends,and random fluctuations in case counts.We explore the relationships between COVID-19 cases,hospitalizations,workdays,and wastewater viral loads through dynamic regression models,offering insights into how these factors influence public health outcomes.Our analysis extends to multivariate covariance estimation,utilizing a novel methodology to provide time-varying correlation estimates that account for non-stationary data.Results demonstrate the significance of incorporating environmental covariates,such as wastewater data,in improving model robustness and uncovering the complex interplay between epidemiological factors.This work highlights the limitations of simpler models and emphasizes the advantages of state-space approaches for analyzing dynamic infectious disease data.By illustrating the application of advanced modelling techniques,this study contributes to a deeper understanding of disease transmission and informs public health interventions. 展开更多
关键词 State-space modelling Dynamic regression Bayesian sequential inference Online prediction Covariance estimation Infectious disease surveillance data
State-space modelling for infectious disease surveillance data:Stochastic simulation techniques and structural change detection 认领 引用
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作者 Christopher D.Prashad 《Infectious Disease Modelling》 CSCD 2025年第4期1507-1532,共26页
We present an exploration of advanced stochastic simulation techniques for state-space models,with a specific focus on their applications in infectious disease modelling.Utilizing COVID-19 surveillance data from the p... We present an exploration of advanced stochastic simulation techniques for state-space models,with a specific focus on their applications in infectious disease modelling.Utilizing COVID-19 surveillance data from the province of Ontario,Canada,we employ Markov Chain Monte Carlo(MCMC)and Sequential Monte Carlo(SMC)methods to detect structural changes and pre-dict future trends in case counts.Our approach begins with the application of a Kalman smoothing technique,integrated with MCMC for state sampling within local level and seasonal models,alongside Bayesian inference for non-linear dynamic regression models.We then assess the effectiveness of various priors,including normal,Student's t,Laplace,and horseshoe distributions,in capturing abrupt changes within the data using a Rao-Blackwellized par-ticle filter.Our findings highlight the superior performance of the horseshoe prior in identifying change points and adapting to complex data structures,offering valuable insights for real-time monitoring and forecasting in public health.This study emphasizes the efficacy of state-space models,particu-larly when enhanced with sophisticated prior distributions,in providing a nuanced understanding of infectious disease transmission. 展开更多
关键词 State-space modelling Nonlinear dynamic regression Stochastic simulation Structural change detection Rao-blackwellized particle filter Infectious disease surveillance data
A Novel Harmonic State-space Modelling Method on the Modular Multilevel Matrix Converter and Coupling Analysis 认领 引用 被引量：1
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作者 Jing Li Boyang Zhao +3 位作者 Shenquan Liu Jie Li Xiuli Wang Xifan Wang 《CSEE Journal of Power and Energy Systems》 SCIE EI CSCD 2025年第1期78-90,共13页
The fractional frequency transmission system is an emerging technology for long-distance wind power integration,and the modular multilevel matrix converter(M3C)is the keen equipment.Since the M3C directly connects two... The fractional frequency transmission system is an emerging technology for long-distance wind power integration,and the modular multilevel matrix converter(M3C)is the keen equipment.Since the M3C directly connects two ac grids with different frequencies,the external and internal harmonics have complex coupling relationships with a unique dual-fundamental-frequency spectrum,which has not been properly investigated due to a lack of an effective method.To address this issue,a novel harmonic state-space method is proposed to achieve comprehensive modelling of the harmonic dynamics of the M3C.Based on the principle of two-dimensional Fourier transform,the decomposition of the dual-fundamental-frequency harmonics is realized,and the multiplicative coupling between time-domain variables is modelled through double-layer convolution on the frequency domain.Besides,the general expression of the proposed method is provided,which highlights a modularized matrix with easy scalability to meet different truncation requirements.Then,the HSS model of M3C considering the close-loop control is established,based on which a panoramic harmonic coupling relationship between the system-and the low-frequency side is concluded.Finally,the M3C model and harmonic coupling relationship are validated by simulation tests conducted in MATLAB/Simulink environment. 展开更多
关键词 Harmonic state-space harmonic transmission modular multilevel matrix converter.Harmonic state-space harmonic transmission modular multilevel matrix converter
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Second-order Extended State-space Model of Switching Converters 认领 引用
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作者 Renji Huang Fan Ma +1 位作者 Gang Wang Runlong Xiao 《CSEE Journal of Power and Energy Systems》 SCIE EI CSCD 2025年第5期2314-2324,共11页
The state space average model of switching converters transforms time varying differential equations into time invariant differential equations by the averaging method in math.The model has merits of simple,clear phys... The state space average model of switching converters transforms time varying differential equations into time invariant differential equations by the averaging method in math.The model has merits of simple,clear physical conception and easy to design control system,but it exhibits significant steadystate error and delayed dynamic response in some special parameters or state conditions.Besides,the conventional state space average model(CSSAM)can’t reflect how much the switching period influences system performance.The averaging method based on exact time domain solution approximation for the state variable is established in this paper.Subsequently,a second-order state-space average model(SOSSAM)which extends the constant term in CSSAM to a combination of constant term and linear term of the switching period is proposed.This model inherits the advantages of CSSAM and improves accuracy of steady state performance and dynamic response of switching converters.Influence of switching period to system performance is reflected,which lays a foundation for analyzing system performance and designing a control system of switching converters. 展开更多
关键词 Dynamic response second order approximation state-space average model switching converter
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TopoEKF:From State-Space Estimation to Topological Signatures for Enhanced Multi-Object Tracking and Anomaly Detection in UAVs 认领 引用
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作者 Rabia Kıratlı Hatice Unlu Eroğlu Alperen Eroğlu 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第6期860-908,共49页
Reliable multi-object detection and tracking play a critical role in Unmanned Aerial Vehicles-based aerial surveillance applications operating under challenging real-world conditions.This study presents a mathematical... Reliable multi-object detection and tracking play a critical role in Unmanned Aerial Vehicles-based aerial surveillance applications operating under challenging real-world conditions.This study presents a mathematically grounded,model-driven tracking framework named TopoEKF,which integrates an enhanced Adaptive Extended Kalman Filter with Topological Data Analysis to improve both tracking robustness and anomaly detection performance.Unlike prior approaches that primarily focus on refining object detection architectures,this work emphasizes the predictive power of iterative Bayesian filtering,optimal state estimation,and adaptive error minimization within a unified mathematical framework.The proposed system employs a carefully optimized YOLOvl2 detector to provide accurate object location priors,followed by a formally defined discrete-time linear Gaussian tracking model.The Adaptive EKF is leveraged to handle nonlinearities arising from the projection of three-dimensional object motion onto the two-dimensional image plane through local linearization.To further enhance robustness under low resolution,large object-to-image distances,frequent occlusions,and environmental noise,TopoEKF introduces adaptive noise covariance modeling driven by measurement confidence,occlusion status,and topological feedback.Persistent homology is applied to EKF-filtered trajectories to extract topological signatures that characterize the global structure of object motion.These features are transformed into fixed-dimensional representations and processed by an unsupervised Isolation Forest classifier for trajectory-level anomaly detection.Experimental evaluations are conducted on a challenging hybrid dataset combining scenarios from COCO,VisDrone,UAVDT,Road_Anomaly_Dataset,and DoTA benchmarks.Quantitative results demonstrate that TopoEKF improves Multi-Object Tracking Accuracy from 72.8%to 76.3%and reduces identity switches by approximately 34%compared to a standard EKF baseline.The enhanced EKF achieves up to 20%higher robustness in highly noisy and indoor environments while maintaining realtime performance at 28.5 frames per second on resource-constrained embedded platforms.In the anomaly detection stage,the integration of persistent homology-based features improves the F1-score from 66%to 84%,with substantial gains in both precision and recall.Overall,the proposed approach highlights the effectiveness of interpretable,mathematically founded state estimation models as a reliable and efficient alternative to black-box deep learning systems in safety-critical UAV applications. 展开更多
关键词 Extended Kalman filter UAV tracking multi-object tracking mathematical modeling Bayesian estimation YOLOvl2 topological data analysis persistent homology
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Tracking of time-evolving sound speed profiles with an auto-regressive state-space model 认领 引用 被引量：4
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作者 JIN Liling LI Jianlong XU Wen 《Chinese Journal of Acoustics》 CSCD 2017年第3期302-312,共11页
An approach for time-evolving sound speed profiles tracking in shallow water is discussed. The inversion of time-evolving sound speed profiles is modeled as a state-space estimation problem, which includes a state equ... An approach for time-evolving sound speed profiles tracking in shallow water is discussed. The inversion of time-evolving sound speed profiles is modeled as a state-space estimation problem, which includes a state equation for predicting the time-evolving sound speed profile and a measurement equation for incorporating local acoustic measurements. In the paper, auto-regression （AR） method is introduced to obtain a high-order AR evolution model of the sound speed field time variations, and the ensemble Kalman filter is utilized to track the sound speed field. To validate the approach, the accuracy in sound speed estimation is analyzed via a numerical implementation using the ASIAEX experimental environment and the sound velocity measurement data. Compared with traditional approaches based on the state evolution represented as a random walk, simulation results show the proposed AR method can effectively reduce the tracking errors of sound speed, and still keep good tracking performance at low signal-to-noise ratios. 展开更多
关键词 time Tracking of time-evolving sound speed profiles with an auto-regressive state-space model SSP EnKF AR
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Improved State-space Modelling for Microgrids Without Virtual Resistances 认领 引用 被引量：2
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作者 Paranagamage S.A.Peiris Shaahin Filizadeh Dharshana Muthumuni 《Journal of Modern Power Systems and Clean Energy》 SCIE EI CSCD 2024年第2期584-596,共13页
Power converters and their interfacing networks are often treated as modular state-space blocks for small-signal stability studies in microgrids;they are interconnected by matching the input and output states of the n... Power converters and their interfacing networks are often treated as modular state-space blocks for small-signal stability studies in microgrids;they are interconnected by matching the input and output states of the network and converters.Virtual resistors have been widely used in existing models to generate a voltage for state-space models of the network that require voltage inputs.This paper accurately quantifies the adverse impacts of adding the virtual resistance and proposes an alternative method for network modelling that eliminates the requirement of the virtual resistor when interfacing converters with microgrids.The proposed nonlinear method allows initialization,time-domain simulations of the nonlinear model,and linearization and eigenvalue generation.A numerically linearized small-signal model is used to generate eigenvalues and is compared with the eigenvalues generated using the existing modelling method with virtual resistances.Deficiencies of the existing method and improvements offered by the proposed modelling method are clearly quantified.Electromagnetic transient(EMT)simulations using detailed switching models are used for validation of the proposed modelling method. 展开更多
关键词 Low-voltage converter state-space modelling dynamic phasor time-domain simulation eigenvalue analysis
STATE-SPACE MODELLING OF DYNAMIC SYSTEMS IN OCEAN ENGINEERING 认领 引用 被引量：2
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作者 JohannesFalnes 《Journal of Hydrodynamics》 SCIE EI 1998年第1期1-17,共17页
Pertaining to dynamic systems in general, a review is given of relations between mathematical descriptions in the frequency domain or time domain and state-space descriptions. For the analysis of hydrodynamic problems... Pertaining to dynamic systems in general, a review is given of relations between mathematical descriptions in the frequency domain or time domain and state-space descriptions. For the analysis of hydrodynamic problems in ocean engineering wave forces may be represented by convolution integrals. The paper presents a method to construct a finite-order state-space model which represents a good approximation to such a convolution integral. The method utilizes a particular algorithm to compute the partial derivative of the exponential function of a (state-space) matrix with respect to the matrix elements. The method is applied to an example of fitting a state space model of order five to the free oscillations corresponding to wave radiation in a transient experiment with an oscillating water column. 展开更多
关键词 wave forces simulation state-space model least-square method oscillating water column heave motion
An interpretable attention-guided generative adversarial network framework with dual-domain learning for multi-condition constrained sedimentary facies modeling 认领 引用 被引量：2
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作者 Lei Liu Wei Li +7 位作者 Jian Gao Da-Li Yue De-Gang Wu Wu-Rong Wang Jin Lin Zhi-Bo Li Qian Zhong Jia-Gen Hou 《Petroleum Science》 SCIE EI CAS CSCD 2026年第4期1754-1772,共19页
Sedimentary facies modeling is a critical approach for understanding geological phenomena,yet the strong heterogeneity of reservoir systems poses a serious challenge for their refined characterization.In this study,we... Sedimentary facies modeling is a critical approach for understanding geological phenomena,yet the strong heterogeneity of reservoir systems poses a serious challenge for their refined characterization.In this study,we innovatively propose an interpretable attention-guided generative adversarial network framework with dual-domain learning,which achieves precise sedimentary facies modeling under the constraints of well facies and soft probability data.Specifically,we first effectively extract and preserve prior information of sedimentary facies models from both spatial and frequency domain perspectives.Then,during simulation,to enhance the capability of the network model for finely characterizing complex heterogeneous models,cross-spatial attention mechanisms are designed to effectively capture short-range and long-range dependencies between multi-scale pattern features.Additionally,through systematic feature map visualization analysis,we elucidate the processes of conditional fitting and complex sedimentary facies model reconstruction,intuitively demonstrating the functional mechanisms of each module.Finally,systematic experiments are conducted on multiple datasets to validate the effectiveness of the proposed method.The results demonstrate that the generated sedimentary facies models exhibit high consistency with training datasets in terms of visual realism and statistical indicators.Quantitative comparisons reveal remarkable performance of the method,achieving low Wasserstein distance(0.09),Kernel Inception Distance(0.0017)and Kernel Maximum Mean Discrepancy(0.21).These findings further confirm the high realism of the generated realizations regarding pattern features.This study offers a reliable and practical method for geological reservoir modeling,thereby advancing quantitative,precise geological research with broad application prospects. 展开更多
关键词 Sedimentary facies models Attention-guided generative adversarial network Interpretable framework Sedimentary patterns Multi-condition modeling
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Ecosystem service models are indeed being validated:A response to Pereira et al.(2025) 认领 引用 被引量：1
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作者 James M.Bullock Danny A.P.Hooftman +1 位作者 John W.Redhead Simon Willcock 《Geography and Sustainability》 CSCD 2026年第1期247-248,共2页
In their recent paper Pereira et al.(2025)claim that validation is overlooked in mapping and modelling of ecosystem services(ES).They state that“many studies lack critical evaluation of the results and no validation ... In their recent paper Pereira et al.(2025)claim that validation is overlooked in mapping and modelling of ecosystem services(ES).They state that“many studies lack critical evaluation of the results and no validation is provided”and that“the validation step is largely overlooked”.This assertion may have been true several years ago,for example,when Ochoa and Urbina-Cardona(2017)made a similar observation.However,there has been much work on ES model validation over the last decade. 展开更多
关键词 evaluation mapping modeling es model ecosystem services validation
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Dynamic modeling of spatial variable stator vane mechanism using modified Lagrange multiplier method 认领 引用 被引量：1
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作者 Ke HE Kaiyi HUANG +2 位作者 Zhen LI Shuhui HU Zhinan ZHANG 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第6期251-271,共21页
The Variable Stator Vanes(VSV)system ensures the smooth operation of the highpressure compressor by adjusting the vane angles to prevent surge,and the dynamic behavior of its multistage vanes directly affects its serv... The Variable Stator Vanes(VSV)system ensures the smooth operation of the highpressure compressor by adjusting the vane angles to prevent surge,and the dynamic behavior of its multistage vanes directly affects its service performance.To investigate the dynamic behavior of the spatial VSV multi-vane mechanism,a positional constraint equation for the VSV mechanism was established,and the numerical expressions of the Jacobian matrices for different kinematic pair constraint equations were derived.The Lagrange multiplier method was modified for spatial rotation,and an ideal dynamic model of the spatial VSV multi-vane mechanism was developed.The computational results indicate that the dynamic behavior of different vanes within the same stage is similar,and the constraint moment experienced by vanes at different positions has a linear relationship with their centroid coordinates.This study expands the dynamic modeling methods for spatial mechanisms and provides a foundation for researching the frictional dynamic behavior of VSV mechanisms with clearance. 展开更多
关键词 Dynamic characteristics Dynamic models Lagrange multipliers Spatial dynamic modeling:VSV
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A peridynamics modeling approach for pre-cracked rock cracking processes under impact by integrating Drucker-Prager plasticity model and efficient contact model 认领 引用 被引量：2
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作者 Jingzhi Tu Nengxiong Xu Gang Mei 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2026年第1期179-195,共17页
In rock engineering,natural cracks in rock masses subjected to external loads tend to initiate and propagate,leading to potential safety hazards.To investigate the effect of cracking behavior on the mechanical propert... In rock engineering,natural cracks in rock masses subjected to external loads tend to initiate and propagate,leading to potential safety hazards.To investigate the effect of cracking behavior on the mechanical properties of rocks,the cracking processes of pre-cracked rocks have been extensively studied using numerical modeling methods.The peridynamics(PD)exhibits advantages over other numerical methods due to the absence of the requirements for remeshing and external crack growth criterion.However,for modeling pre-cracked rock cracking processes under impact,current PD implementations lack generally applicable rock constitutive models and impact contact models,which leads to difficulties in determining rock material parameters and efficiently calculating impact loads.This paper proposes a non-ordinary state-based peridynamics(NOSBPD)modeling method integrating the Drucker-Prager(DP)plasticity model and an efficient contact model to address the above problems.In the proposed method,the Drucker-Prager plasticity model is integrated into the NOSBPD,thereby equipping NOSBPD with the capability to accurately characterize the nonlinear stress-strain relationship inherent in rocks.An efficient contact model between particles and meshes is designed to calculate the impact loads,which is essentially a coupling method of PD with the finite element method(FEM).The effectiveness of the proposed NOSBPD modeling method is verified by comparison with other numerical methods and experiments.Experimental results indicate that the proposed method can effectively and accurately predict the 3D cracking processes of pre-cracked cracks under impact loading,and the maximum principal stress is the key driver behind wing crack formation in pre-cracked rocks. 展开更多
关键词 Pre-cracked rocks Cracking processes Non-ordinary state-based peridynamics (NOSBPD) Drucker-Prager plasticity model Efficient contact model
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AI and Deep Learning for Terahertz Ultra-Massive MIMO:From Model-Driven Approaches to Foundation Models 认领 引用 被引量：1
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作者 Wentao Yu Hengtao He +4 位作者 Shenghui Song Jun Zhang Linglong Dai Lizhong Zheng Khaled B.Letaief 《Engineering》 SCIE EI CSCD 2026年第1期14-33,共20页
This study explored the transformative potential of artificial intelligence(AI)in addressing the challenges posed by terahertz ultra-massive multiple-input multiple-output(UM-MIMO)systems.It begins by outlining the ch... This study explored the transformative potential of artificial intelligence(AI)in addressing the challenges posed by terahertz ultra-massive multiple-input multiple-output(UM-MIMO)systems.It begins by outlining the characteristics of terahertz UM-MIMO systems and identifies three primary challenges for transceiver design:computational complexity,modeling difficulty,and measurement limitations.The study posits that AI provides a promising solution to these challenges.Three systematic research roadmaps are proposed for developing AI algorithms tailored to terahertz UM-MIMO systems.The first roadmap,model-driven deep learning(DL),emphasizes the importance of leveraging available domain knowledge and advocates the adoption of AI only to enhance bottleneck modules within an established signal processing or optimization framework.Four essential steps are discussed:algorithmic frameworks,basis algorithms,loss function design,and neural architecture design.The second roadmap presents channel state information(CSI)foundation models,aimed at unifying the design of different transceiver modules by focusing on their shared foundation,that is,the wireless channel.The training of a single compact foundation model is proposed to estimate the score function of wireless channels,which serve as a versatile prior for designing a wide variety of transceiver modules.Four essential steps are outlined:general frameworks,conditioning,site-specific adaptation,and the joint design of CSI foundation models and model-driven DL.The third roadmap aims to explore potential directions for applying pretrained large language models(LLMs)to terahertz UM-MIMO systems.Several application scenarios are envisioned,including LLM-based estimation,optimization,search,network management,and protocol understanding.Finally,the study highlights open problems and future research directions. 展开更多
关键词 Terahertz communications Ultra-massive multiple-input multiple-output Model-driven deep learning Foundation models Large language models
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