In this work,a frame work for time-varying channel modeling and simulation is proposed by using neural network(NN)to overcome the shortcomings in geometry based stochastic model(GBSM)and simulation approach.Two NN mod...In this work,a frame work for time-varying channel modeling and simulation is proposed by using neural network(NN)to overcome the shortcomings in geometry based stochastic model(GBSM)and simulation approach.Two NN models are developed for modeling of path loss together with shadow fading(SF)and joint small scale channel parameters.The NN models can predict path loss plus SF and small scale channel parameters accurately compared with measurement at 26 GHz performed in an outdoor microcell.The time-varying path loss and small scale channel parameters generated by the NN models are proposed to replace the empirical path loss and channel parameter random numbers in GBSM-based framework to playback the measured channel and match with its environment.Moreover,the sparse feature of clusters,delay and angular spread,channel capacity are investigated by a virtual array measurement at 28 GHz in a large waiting hall.展开更多
The auto-regressive moving-average (ARMA) model with time-varying parameters is analyzed. The time-varying parameters are assumed to be a linear combination of a set of basis time-varying functions, and the feedbac...The auto-regressive moving-average (ARMA) model with time-varying parameters is analyzed. The time-varying parameters are assumed to be a linear combination of a set of basis time-varying functions, and the feedback linear estimation algorithm is used to estimate the time-varying parameters of the ARMA model. This algorithm includes 2 linear least squares estimations and a linear filter. The influence of the order of basis time-(varying) functions on parameters estimation is analyzed. The method has the advantage of simple, saving computation time and storage space. Theoretical analysis and experimental results show the validity of this method.展开更多
This article discusses regression analysis of failure time under the additive hazards model, when the regression coefficients are time-varying. The regression coefficients are estimated locally based on the pseudo-sco...This article discusses regression analysis of failure time under the additive hazards model, when the regression coefficients are time-varying. The regression coefficients are estimated locally based on the pseudo-score function [12] in a window around each time point. The proposed method can be easily implemented, and the resulting estimators are shown to be consistent and asymptotically normal with easily estimated variances. The simulation studies show that our estimation procedure is reliable and useful.展开更多
We investigate a two-fluid anisotropic plane symmetric cosmological model with variable gravitational constant G（t） and cosmological term A（t）. In the two-fluid model, one fluid is chosen to be that of the radiati...We investigate a two-fluid anisotropic plane symmetric cosmological model with variable gravitational constant G（t） and cosmological term A（t）. In the two-fluid model, one fluid is chosen to be that of the radiation field modeling the cosmic microwave background and the other one a perfect fluid modeling the material content of the universe. Exact solutions of the field equations are obtained by using a special form for the average scale factor which corresponds to a specific time-varying deceleration parameter. The model obtained presents a cosmological scenario which describes an early acceleration and late-time deceleration. The gravitation constant increases with the cosmic time whereas the cosmological term decreases and asymptotically tends to zero. The physical and kinematical behaviors of the associated fluid parameters are discussed.展开更多
We propose a high-order conservative method for the nonlinear Sehodinger/Gross-Pitaevskii equation with time- varying coefficients in modeling Bose Einstein condensation （BEC）. This scheme combined with the sixth-or...We propose a high-order conservative method for the nonlinear Sehodinger/Gross-Pitaevskii equation with time- varying coefficients in modeling Bose Einstein condensation （BEC）. This scheme combined with the sixth-order compact finite difference method and the fourth-order average vector field method, finely describes the condensate wave function and physical characteristics in some small potential wells. Numerical experiments are presented to demonstrate that our numerical scheme is efficient by the comparison with the Fourier pseudo-spectral method. Moreover, it preserves several conservation laws well and even exactly under some specific conditions.展开更多
The present study develops a data-based compact model for the prediction of the fluid temperature evolution in district heating-and-cooling pipeline networks.This model is based on an existing“reduced-order model”by...The present study develops a data-based compact model for the prediction of the fluid temperature evolution in district heating-and-cooling pipeline networks.This model is based on an existing“reduced-order model”by the authors obtained from reduction of the“full-order model”describing the spatio-temporal energy balance for each pipe segment to a semi-analytical input-output relation between the pipe outlet temperature and the pipe inlet and ground temperatures.The proposed model(denoted XROM)expands on the original reduced-order model by incorporating variable mass flux as an additional input and thus greatly increases its practical relevance.The XROM represents variable mass flux by step-wise switching between mass-flux levels and thereby induces a prediction error relative to the true full-order model evolution after each switching.Theoretical analysis rigorously demonstrates that this error always decays and the XROM invariably converges on the full-order model evolution and,consequently,affords the same prediction accuracy.Performance analyses reveal that prediction errors are restricted to short“convergence intervals”after each mass-flux switching and the XROM therefore can handle substantially faster operating schemes than the current ones based on hourly monitoring and control.Convergence intervals of O(minutes)are namely typically sufficient-and thus switching frequencies up to O(minutes 1)permissible during dynamic operation and control actions-for reliable predictions.Quantification of these convergence intervals by an easy-to-use empirical relation furthermore enables a priori determination of the conditions for reliable predictions.Moreover,the XROM can capture the full 3D system dynamics(provided incompressible flow and heat-transfer mechanisms depending linearly on temperature)versus the essentially 1D approximation of current compact pipe models yet at similar computational cost.These attributes advance(parts of)district heating and cooling networks demanding prediction accuracies beyond 1D as its primary application area.This makes the XROM complementary to said pipe models and thereby expands the modelling capabilities for handling the growing complexity of(next-generation)networks.展开更多
This paper aims to investigate the nonlinear dynamic behaviors of an NGW planetary gear train with multi-clearances and manufacturing/assembling errors. For this purpose, an analytical translational- torsional coupled...This paper aims to investigate the nonlinear dynamic behaviors of an NGW planetary gear train with multi-clearances and manufacturing/assembling errors. For this purpose, an analytical translational- torsional coupled dynamic model is developed considering the effects of time-varying stiffness, gear backlashes and component errors. Based on the proposed model, the nonlinear differential equations of motion are derived and solved iteratively by the Runge-Kutta method. An NGW planetary gear reducer with three planets is taken as an example to analyze the effects of nonlinear factors. The results indicate that the backlashes induce complicated nonlinear dynamic behaviors in the gear train. With the increment of the backlashes, the gear system has experienced periodic responses, quasi-periodic response and chaos responses in sequence. When the planetary gear system is in a chaotic motion state, the vibration amplitude increases sharply, causing severe vibration and noise. The present study provides a fundamental basis for design and parameter optimization of NGW planetary gear trains.展开更多
The control of highly contagious disease spreading in campuses is a critical challenge.In residential universities,students attend classes according to a curriculum schedule,and mainly pack into classrooms,dining hall...The control of highly contagious disease spreading in campuses is a critical challenge.In residential universities,students attend classes according to a curriculum schedule,and mainly pack into classrooms,dining halls and dorms.They move from one place to another.To simulate such environments,we propose an agent-based susceptible–infected–recovered model with time-varying heterogeneous contact networks.In close environments,maintaining physical distancing is the most widely recommended and encouraged non-pharmaceutical intervention.It can be easily realized by using larger classrooms,adopting staggered dining hours,decreasing the number of students per dorm and so on.Their real-world influence remains uncertain.With numerical simulations,we obtain epidemic thresholds.The effect of such countermeasures on reducing the number of disease cases is also quantitatively evaluated.展开更多
Based on the tectonic genesis and seismic data of fault-controlled fractured-vuggy reservoirs,the typical fractured-vuggy structure features were analyzed.A 3D large-scale visual physical model of“tree-like”fracture...Based on the tectonic genesis and seismic data of fault-controlled fractured-vuggy reservoirs,the typical fractured-vuggy structure features were analyzed.A 3D large-scale visual physical model of“tree-like”fractured-vuggy structure was designed and made.The experiments of bottom-water flooding and multi-media synergistic oil displacement after bottom-water flooding were conducted with different production rates and different well-reservoir configuration relationships.The formation mechanisms and distribution rules of residual oil during bottom-water flooding under such fractured-vuggy structure were revealed.The producing characteristics of residual oil under different production methods after bottom-water flooding were discovered.The results show that the remaining oil in"tree-like"fractured-vuggy structure after bottom-water flooding mainly include the remaining oil of non-well controlled fault zones and the attic remaining oil at the top of well controlled fault zones.There exists obvious water channeling of bottom-water along the fault at high production rate,but intermittent drainage can effectively weaken the interference effect between fault zones to inhibit water channeling.Compared with the vertical well,horizontal well can reduce the difference in flow conductivity between fault zones and show better resistance to water channeling.The closer the horizontal well locates to the upper part of the“canopy”,the higher the oil recovery is at the bottom-water flooding stage.However,comprehensive consideration of the bottom-water flooding and subsequent gas injection development,the total recovery is higher when the horizontal well locates in the middle part of the“canopy”and drills through a large number of fault zones.After bottom water flooding,the effect of gas huff and puff is better than that of gas flooding,and the effect of gas huff and puff with large slug is better than that of small slug.Because such development method can effectively develop the remaining oil of non-well controlled fault zones and the attic remaining oil at the top of well controlled fault zones transversely connected with oil wells,thus greatly improving the oil recovery.展开更多
Time-varying channel modeling plays an important role for many applications in time-variant scenarios,while most clustering algorithms focus on static channels and cannot accurately model the channel time-evolution pr...Time-varying channel modeling plays an important role for many applications in time-variant scenarios,while most clustering algorithms focus on static channels and cannot accurately model the channel time-evolution properties.In this paper,a fuzzy clustering algorithm based on multipath component(MPC)trajectory is proposed.Firstly,both the distance and velocity similarities of the MPCs in different snapshots are taken into account to track the MPC trajectory,in which the fuzzy scheme and a kernel function are used to calculate the distance and velocity similarities,respectively.Secondly,a fuzzy MPC trajectory clustering algorithm is proposed to cluster the MPCs in multiple snapshots.The MPCs in a snapshot are clustered according to the membership,which is defined as the probability that a MPC belongs to different clusters.Finally,time-varying channels at 28 GHz are simulated to validate the performance of our proposed algorithm.The results show that our proposed algorithm is able to accurately identify the clusters in time-varying channels compared with the existing clustering algorithms.展开更多
基金supported by the National Nature Science Foundation of China(NSFC)under grant No.61771194supported by Key Program of Beijing Municipal Natural Science Foundation with No.17L20052
文摘In this work,a frame work for time-varying channel modeling and simulation is proposed by using neural network(NN)to overcome the shortcomings in geometry based stochastic model(GBSM)and simulation approach.Two NN models are developed for modeling of path loss together with shadow fading(SF)and joint small scale channel parameters.The NN models can predict path loss plus SF and small scale channel parameters accurately compared with measurement at 26 GHz performed in an outdoor microcell.The time-varying path loss and small scale channel parameters generated by the NN models are proposed to replace the empirical path loss and channel parameter random numbers in GBSM-based framework to playback the measured channel and match with its environment.Moreover,the sparse feature of clusters,delay and angular spread,channel capacity are investigated by a virtual array measurement at 28 GHz in a large waiting hall.
文摘The auto-regressive moving-average (ARMA) model with time-varying parameters is analyzed. The time-varying parameters are assumed to be a linear combination of a set of basis time-varying functions, and the feedback linear estimation algorithm is used to estimate the time-varying parameters of the ARMA model. This algorithm includes 2 linear least squares estimations and a linear filter. The influence of the order of basis time-(varying) functions on parameters estimation is analyzed. The method has the advantage of simple, saving computation time and storage space. Theoretical analysis and experimental results show the validity of this method.
基金supported by the Fundamental Research Funds for the Central Universities (QN0914)
文摘This article discusses regression analysis of failure time under the additive hazards model, when the regression coefficients are time-varying. The regression coefficients are estimated locally based on the pseudo-score function [12] in a window around each time point. The proposed method can be easily implemented, and the resulting estimators are shown to be consistent and asymptotically normal with easily estimated variances. The simulation studies show that our estimation procedure is reliable and useful.
文摘We investigate a two-fluid anisotropic plane symmetric cosmological model with variable gravitational constant G（t） and cosmological term A（t）. In the two-fluid model, one fluid is chosen to be that of the radiation field modeling the cosmic microwave background and the other one a perfect fluid modeling the material content of the universe. Exact solutions of the field equations are obtained by using a special form for the average scale factor which corresponds to a specific time-varying deceleration parameter. The model obtained presents a cosmological scenario which describes an early acceleration and late-time deceleration. The gravitation constant increases with the cosmic time whereas the cosmological term decreases and asymptotically tends to zero. The physical and kinematical behaviors of the associated fluid parameters are discussed.
基金Supported by the National Natural Science Foundation of China under Grant Nos 11571366 and 11501570the Open Foundation of State Key Laboratory of High Performance Computing of China+1 种基金the Research Fund of National University of Defense Technology under Grant No JC15-02-02the Fund from HPCL
文摘We propose a high-order conservative method for the nonlinear Sehodinger/Gross-Pitaevskii equation with time- varying coefficients in modeling Bose Einstein condensation （BEC）. This scheme combined with the sixth-order compact finite difference method and the fourth-order average vector field method, finely describes the condensate wave function and physical characteristics in some small potential wells. Numerical experiments are presented to demonstrate that our numerical scheme is efficient by the comparison with the Fourier pseudo-spectral method. Moreover, it preserves several conservation laws well and even exactly under some specific conditions.
文摘The present study develops a data-based compact model for the prediction of the fluid temperature evolution in district heating-and-cooling pipeline networks.This model is based on an existing“reduced-order model”by the authors obtained from reduction of the“full-order model”describing the spatio-temporal energy balance for each pipe segment to a semi-analytical input-output relation between the pipe outlet temperature and the pipe inlet and ground temperatures.The proposed model(denoted XROM)expands on the original reduced-order model by incorporating variable mass flux as an additional input and thus greatly increases its practical relevance.The XROM represents variable mass flux by step-wise switching between mass-flux levels and thereby induces a prediction error relative to the true full-order model evolution after each switching.Theoretical analysis rigorously demonstrates that this error always decays and the XROM invariably converges on the full-order model evolution and,consequently,affords the same prediction accuracy.Performance analyses reveal that prediction errors are restricted to short“convergence intervals”after each mass-flux switching and the XROM therefore can handle substantially faster operating schemes than the current ones based on hourly monitoring and control.Convergence intervals of O(minutes)are namely typically sufficient-and thus switching frequencies up to O(minutes 1)permissible during dynamic operation and control actions-for reliable predictions.Quantification of these convergence intervals by an easy-to-use empirical relation furthermore enables a priori determination of the conditions for reliable predictions.Moreover,the XROM can capture the full 3D system dynamics(provided incompressible flow and heat-transfer mechanisms depending linearly on temperature)versus the essentially 1D approximation of current compact pipe models yet at similar computational cost.These attributes advance(parts of)district heating and cooling networks demanding prediction accuracies beyond 1D as its primary application area.This makes the XROM complementary to said pipe models and thereby expands the modelling capabilities for handling the growing complexity of(next-generation)networks.
基金Funded by the National Natural Science Foundation of China(Grant No.51375013)the Anhui Provincial Natural Science Foundation(Grant No.1208085ME64)
文摘This paper aims to investigate the nonlinear dynamic behaviors of an NGW planetary gear train with multi-clearances and manufacturing/assembling errors. For this purpose, an analytical translational- torsional coupled dynamic model is developed considering the effects of time-varying stiffness, gear backlashes and component errors. Based on the proposed model, the nonlinear differential equations of motion are derived and solved iteratively by the Runge-Kutta method. An NGW planetary gear reducer with three planets is taken as an example to analyze the effects of nonlinear factors. The results indicate that the backlashes induce complicated nonlinear dynamic behaviors in the gear train. With the increment of the backlashes, the gear system has experienced periodic responses, quasi-periodic response and chaos responses in sequence. When the planetary gear system is in a chaotic motion state, the vibration amplitude increases sharply, causing severe vibration and noise. The present study provides a fundamental basis for design and parameter optimization of NGW planetary gear trains.
基金Project supported by the National Natural Science Foundation of China(Grant No.61871234).
文摘The control of highly contagious disease spreading in campuses is a critical challenge.In residential universities,students attend classes according to a curriculum schedule,and mainly pack into classrooms,dining halls and dorms.They move from one place to another.To simulate such environments,we propose an agent-based susceptible–infected–recovered model with time-varying heterogeneous contact networks.In close environments,maintaining physical distancing is the most widely recommended and encouraged non-pharmaceutical intervention.It can be easily realized by using larger classrooms,adopting staggered dining hours,decreasing the number of students per dorm and so on.Their real-world influence remains uncertain.With numerical simulations,we obtain epidemic thresholds.The effect of such countermeasures on reducing the number of disease cases is also quantitatively evaluated.
基金Supported by the National Natural Science Foundation of China(52074344)。
文摘Based on the tectonic genesis and seismic data of fault-controlled fractured-vuggy reservoirs,the typical fractured-vuggy structure features were analyzed.A 3D large-scale visual physical model of“tree-like”fractured-vuggy structure was designed and made.The experiments of bottom-water flooding and multi-media synergistic oil displacement after bottom-water flooding were conducted with different production rates and different well-reservoir configuration relationships.The formation mechanisms and distribution rules of residual oil during bottom-water flooding under such fractured-vuggy structure were revealed.The producing characteristics of residual oil under different production methods after bottom-water flooding were discovered.The results show that the remaining oil in"tree-like"fractured-vuggy structure after bottom-water flooding mainly include the remaining oil of non-well controlled fault zones and the attic remaining oil at the top of well controlled fault zones.There exists obvious water channeling of bottom-water along the fault at high production rate,but intermittent drainage can effectively weaken the interference effect between fault zones to inhibit water channeling.Compared with the vertical well,horizontal well can reduce the difference in flow conductivity between fault zones and show better resistance to water channeling.The closer the horizontal well locates to the upper part of the“canopy”,the higher the oil recovery is at the bottom-water flooding stage.However,comprehensive consideration of the bottom-water flooding and subsequent gas injection development,the total recovery is higher when the horizontal well locates in the middle part of the“canopy”and drills through a large number of fault zones.After bottom water flooding,the effect of gas huff and puff is better than that of gas flooding,and the effect of gas huff and puff with large slug is better than that of small slug.Because such development method can effectively develop the remaining oil of non-well controlled fault zones and the attic remaining oil at the top of well controlled fault zones transversely connected with oil wells,thus greatly improving the oil recovery.
基金supported by the National Key Laboratory of Electromagnetic Environment(No.202101004)the National Nature Science of China(NSFC)(No.61931001),respectively。
文摘Time-varying channel modeling plays an important role for many applications in time-variant scenarios,while most clustering algorithms focus on static channels and cannot accurately model the channel time-evolution properties.In this paper,a fuzzy clustering algorithm based on multipath component(MPC)trajectory is proposed.Firstly,both the distance and velocity similarities of the MPCs in different snapshots are taken into account to track the MPC trajectory,in which the fuzzy scheme and a kernel function are used to calculate the distance and velocity similarities,respectively.Secondly,a fuzzy MPC trajectory clustering algorithm is proposed to cluster the MPCs in multiple snapshots.The MPCs in a snapshot are clustered according to the membership,which is defined as the probability that a MPC belongs to different clusters.Finally,time-varying channels at 28 GHz are simulated to validate the performance of our proposed algorithm.The results show that our proposed algorithm is able to accurately identify the clusters in time-varying channels compared with the existing clustering algorithms.
