The self-assembled nanoparticles(SAN)formed during the decoction process of traditional Chinese medicine(TCM)exhibit non-uniform particle sizes and a tendency for aggregation.Our group found that the p H-driven method...The self-assembled nanoparticles(SAN)formed during the decoction process of traditional Chinese medicine(TCM)exhibit non-uniform particle sizes and a tendency for aggregation.Our group found that the p H-driven method can improve the self-assembly phenomenon of Herpetospermum caudigerum Wall.,and the SAN exhibited uniform particle size and demonstrated good stability.In this paper,we analyzed the interactions between the main active compound,herpetrione(Her),and its main carrier,Herpetospermum caudigerum Wall.polysaccharide(HCWP),along with their self-assembly mechanisms under different p H values.The binding constants of Her and HCWP increase with rising p H,leading to the formation of Her-HCWP SAN with a smaller particle size,higher zeta potential,and improved thermal stability.While the contributions of hydrogen bonding and electrostatic attraction to the formation of Her-HCWP SAN increase with rising p H,the hydrophobic force consistently plays a dominant role.This study enhances our scientific understanding of the self-assembly phenomenon of TCM improved by p H driven method.展开更多
Orthogonal conditional nonlinear optimal perturbations(O-CNOPs)have been used to generate ensemble forecasting members for achieving high forecasting skill of high-impact weather and climate events.However,highly effi...Orthogonal conditional nonlinear optimal perturbations(O-CNOPs)have been used to generate ensemble forecasting members for achieving high forecasting skill of high-impact weather and climate events.However,highly efficient calculations for O-CNOPs are still challenging in the field of ensemble forecasting.In this study,we combine a gradient-based iterative idea with the Gram‒Schmidt orthogonalization,and propose an iterative optimization method to compute O-CNOPs.This method is different from the original sequential optimization method,and allows parallel computations of O-CNOPs,thus saving a large amount of computational time.We evaluate this method by using the Lorenz-96 model on the basis of the ensemble forecasting ability achieved and on the time consumed for computing O-CNOPs.The results demonstrate that the parallel iterative method causes O-CNOPs to yield reliable ensemble members and to achieve ensemble forecasting skills similar to or even slightly higher than those produced by the sequential method.Moreover,the parallel method significantly reduces the computational time for O-CNOPs.Therefore,the parallel iterative method provides a highly effective and efficient approach for calculating O-CNOPs for ensemble forecasts.Expectedly,it can play an important role in the application of the O-CNOPs to realistic ensemble forecasts for high-impact weather and climate events.展开更多
Clock difference between the ensemble pulsar timescale(PT)and the International Atomic Time(TAI)PT-TAI derived from the International Pulsar Timing Array(IPTA)data set indicates a very similar variation trend with the...Clock difference between the ensemble pulsar timescale(PT)and the International Atomic Time(TAI)PT-TAI derived from the International Pulsar Timing Array(IPTA)data set indicates a very similar variation trend with the Terrestrial Time TT(BIPMXXXX)-TAI but PT has larger measurement error.In this paper,we discuss the smoothing method of PT using a combined smoothing filter and compare the results with that from other filters.The clock difference sequence between PT-TAI and the first time derivative series of the TT(BIPMXXXX)-TAI can be combined by a combined smoothing filter to yield two smooth curves tied by the constraints assuring that the latter is the derivative of the former.The ensemble pulsar time IPTA2016 with respect to TAI published by G.Hobbs et al.and first time derivative series of the TT(BIPM2017)-TAI with quadratic polynomial terms removed are processed by combined smoothing filter in order to demonstrate the properties of the smoothed results.How to correctly estimate two smoothing coefficients is described and the output results of the combined smoothing filter are analyzed.The results show that the combined smoothing method efficiently removes high frequency noises of two input data series and the smoothed data of the PT-TAI combine long term fractional frequency stability of the pulsar time and frequency accuracy of the terrestrial time.Fractional frequency stability analysis indicates that both short and medium time interval stability of the smoothed PT-TAI is improved while keeping its original long term frequency stability level.The combined smoothing filter is more suitable for smoothing observational pulsar timescale data than any filter that only performs smoothing of a single pulsar time series.The smoothed pulsar time by combined smoothing filter is a pulsar atomic time combined timescale.This kind of combined timescale can also be used as terrestrial time.展开更多
The electromagnetic(EM)telemetry systems,employed for real-time data transmission from the borehole and the earth surface during drilling,are widely used in measurement-while-drilling(MWD)and logging-while-drilling(LW...The electromagnetic(EM)telemetry systems,employed for real-time data transmission from the borehole and the earth surface during drilling,are widely used in measurement-while-drilling(MWD)and logging-while-drilling(LWD).Several numerical methods,including the method of moments(MoM),the electric field integral equation(EFIE)method,and the finite-element(FE)method have been developed for the simulation of EM telemetry systems.The computational process of these methods is complicated and time-consuming.To solve this problem,we introduce an axisymmetric semi-analytical FE method(SAFEM)in the cylindrical coordinate system with the virtual layering technique for rapid simulation of EM telemetry in a layered earth.The proposed method divides the computational domain into a series of homogeneous layers.For each layer,only its cross-section is discretized,and a high-precision integration method based on Riccati equations is employed for the calculation of longitudinally homogeneous sections.The block-tridiagonal structure of the global coefficient matrix enables the use of the block Thomas algorithm,facilitating the efficient simulation of EM telemetry problems in layered media.After the theoretical development,we validate the accuracy and efficiency of our algorithm through a series of numerical experiments and comparisons with the Multiphysics modeling software COMSOL.We also discussed the impact of system parameters on EM telemetry signal and demonstrated the applicability of our method by testing it on a field dataset acquired from Dezhou,Shandong Province,China.展开更多
This paper aims to investigate the tamed Euler method for the random periodic solution of semilinear SDEs with one-sided Lipschitz coefficient.We introduce a novel approach to analyze mean-square error bounds of the n...This paper aims to investigate the tamed Euler method for the random periodic solution of semilinear SDEs with one-sided Lipschitz coefficient.We introduce a novel approach to analyze mean-square error bounds of the novel schemes,without relying on a priori high-order moment bound of the numerical approximation.The expected order-one mean square convergence is attained for the proposed scheme.Moreover,a numerical example is presented to verify our theoretical analysis.展开更多
Non-technical losses(NTL)of electric power are a serious problem for electric distribution companies.The solution determines the cost,stability,reliability,and quality of the supplied electricity.The widespread use of...Non-technical losses(NTL)of electric power are a serious problem for electric distribution companies.The solution determines the cost,stability,reliability,and quality of the supplied electricity.The widespread use of advanced metering infrastructure(AMI)and Smart Grid allows all participants in the distribution grid to store and track electricity consumption.During the research,a machine learning model is developed that allows analyzing and predicting the probability of NTL for each consumer of the distribution grid based on daily electricity consumption readings.This model is an ensemble meta-algorithm(stacking)that generalizes the algorithms of random forest,LightGBM,and a homogeneous ensemble of artificial neural networks.The best accuracy of the proposed meta-algorithm in comparison to basic classifiers is experimentally confirmed on the test sample.Such a model,due to good accuracy indicators(ROC-AUC-0.88),can be used as a methodological basis for a decision support system,the purpose of which is to form a sample of suspected NTL sources.The use of such a sample will allow the top management of electric distribution companies to increase the efficiency of raids by performers,making them targeted and accurate,which should contribute to the fight against NTL and the sustainable development of the electric power industry.展开更多
In this paper,a composite numerical scheme is proposed to solve the threedimensional Darcy-Forchheimer miscible displacement problem with positive semi-definite assumptions.A mixed finite element is used for the fow e...In this paper,a composite numerical scheme is proposed to solve the threedimensional Darcy-Forchheimer miscible displacement problem with positive semi-definite assumptions.A mixed finite element is used for the fow equation.The velocity and pressure are computed simultaneously.The accuracy of velocity is improved one order.The concentration equation is solved by using mixed finite element,multi-step difference and upwind approximation.A multi-step method is used to approximate time derivative for improving the accuracy.The upwind approximation and an expanded mixed finite element are adopted to solve the convection and diffusion,respectively.The composite method could compute the diffusion flux and its gradient.It possibly becomes an eficient tool for solving convection-dominated diffusion problems.Firstly,the conservation of mass holds.Secondly,the multi-step method has high accuracy.Thirdly,the upwind approximation could avoid numerical dispersion.Using numerical analysis of a priori estimates and special techniques of differential equations,we give an error estimates for a positive definite problem.Numerical experiments illustrate its computational efficiency and feasibility of application.展开更多
The quasi-rectangular tunnel represents a novel cross-section design,intended to supersede the traditional circular and rectangular tunnel formats.Due to the limited capacity of the tunnel vault to withstand vertical ...The quasi-rectangular tunnel represents a novel cross-section design,intended to supersede the traditional circular and rectangular tunnel formats.Due to the limited capacity of the tunnel vault to withstand vertical loads,an interior column is often installed at the center to enhance its load-bearing capacity.This study aims to develop a hyperstatic reaction method(HRM)for the analysis of deformation and structural integrity in this specific tunnel type.The computational model is validated through comparison with the corresponding finite element method(FEM)analysis.Following comprehensive validation,an ensemble machine learning(ML)model is proposed,using numerical benchmark data,to facilitate real-time design and optimization.Subsequently,three widely used ensemble models,i.e.random forest(RF),gradient boosting decision tree(GBDT),and extreme gradient boosting(XGBoost)are compared to identify the most efficient ML model for replacing the HRM model in the design optimization process.The performance metrics,such as the coefficient of determination R2 of about 0.999 and the mean absolute percentage error(MAPE)of about 1%,indicate that XGBoost outperforms the others,exhibiting excellent agreement with the HRM analysis.Additionally,the model demonstrates high computational efficiency,with prediction times measured in seconds.Finally,the HRM-XGBoost model is integrated with the well-known particle swarm optimization(PSO)for the real-time design optimization of quasi-rectangular tunnels,both with and without the interior column.A feature importance assessment is conducted to evaluate the sensitivity of design input features,enabling the selection of the most critical features for the optimization task.展开更多
基金supported by the National Natural Science Foundation of China(Nos.81873092,82174074)。
文摘The self-assembled nanoparticles(SAN)formed during the decoction process of traditional Chinese medicine(TCM)exhibit non-uniform particle sizes and a tendency for aggregation.Our group found that the p H-driven method can improve the self-assembly phenomenon of Herpetospermum caudigerum Wall.,and the SAN exhibited uniform particle size and demonstrated good stability.In this paper,we analyzed the interactions between the main active compound,herpetrione(Her),and its main carrier,Herpetospermum caudigerum Wall.polysaccharide(HCWP),along with their self-assembly mechanisms under different p H values.The binding constants of Her and HCWP increase with rising p H,leading to the formation of Her-HCWP SAN with a smaller particle size,higher zeta potential,and improved thermal stability.While the contributions of hydrogen bonding and electrostatic attraction to the formation of Her-HCWP SAN increase with rising p H,the hydrophobic force consistently plays a dominant role.This study enhances our scientific understanding of the self-assembly phenomenon of TCM improved by p H driven method.
基金sponsored by the National Natural Science Foundation of China(Grant Nos.41930971,42330111,and 42405061)the National Key Scientific and Technological Infrastructure project“Earth System Numerical Simulation Facility”(Earth Lab).
文摘Orthogonal conditional nonlinear optimal perturbations(O-CNOPs)have been used to generate ensemble forecasting members for achieving high forecasting skill of high-impact weather and climate events.However,highly efficient calculations for O-CNOPs are still challenging in the field of ensemble forecasting.In this study,we combine a gradient-based iterative idea with the Gram‒Schmidt orthogonalization,and propose an iterative optimization method to compute O-CNOPs.This method is different from the original sequential optimization method,and allows parallel computations of O-CNOPs,thus saving a large amount of computational time.We evaluate this method by using the Lorenz-96 model on the basis of the ensemble forecasting ability achieved and on the time consumed for computing O-CNOPs.The results demonstrate that the parallel iterative method causes O-CNOPs to yield reliable ensemble members and to achieve ensemble forecasting skills similar to or even slightly higher than those produced by the sequential method.Moreover,the parallel method significantly reduces the computational time for O-CNOPs.Therefore,the parallel iterative method provides a highly effective and efficient approach for calculating O-CNOPs for ensemble forecasts.Expectedly,it can play an important role in the application of the O-CNOPs to realistic ensemble forecasts for high-impact weather and climate events.
基金supported by the Strategic Priority Research Program of Chinese Academy of Sciences(grant No.XDA0350502)the National SKA Program of China(grant No.2020SKA0120103)the National Natural Science Foundation of China(NSFC,Grant Nos.U1831130 and 11973046)。
文摘Clock difference between the ensemble pulsar timescale(PT)and the International Atomic Time(TAI)PT-TAI derived from the International Pulsar Timing Array(IPTA)data set indicates a very similar variation trend with the Terrestrial Time TT(BIPMXXXX)-TAI but PT has larger measurement error.In this paper,we discuss the smoothing method of PT using a combined smoothing filter and compare the results with that from other filters.The clock difference sequence between PT-TAI and the first time derivative series of the TT(BIPMXXXX)-TAI can be combined by a combined smoothing filter to yield two smooth curves tied by the constraints assuring that the latter is the derivative of the former.The ensemble pulsar time IPTA2016 with respect to TAI published by G.Hobbs et al.and first time derivative series of the TT(BIPM2017)-TAI with quadratic polynomial terms removed are processed by combined smoothing filter in order to demonstrate the properties of the smoothed results.How to correctly estimate two smoothing coefficients is described and the output results of the combined smoothing filter are analyzed.The results show that the combined smoothing method efficiently removes high frequency noises of two input data series and the smoothed data of the PT-TAI combine long term fractional frequency stability of the pulsar time and frequency accuracy of the terrestrial time.Fractional frequency stability analysis indicates that both short and medium time interval stability of the smoothed PT-TAI is improved while keeping its original long term frequency stability level.The combined smoothing filter is more suitable for smoothing observational pulsar timescale data than any filter that only performs smoothing of a single pulsar time series.The smoothed pulsar time by combined smoothing filter is a pulsar atomic time combined timescale.This kind of combined timescale can also be used as terrestrial time.
基金supported by the Major Research Project on Scientific Instrument Development of the National Natural Science Foundation of China(42327901)National Natural Science Foundation of China(42030806,42074120,41904104,423B2405).
文摘The electromagnetic(EM)telemetry systems,employed for real-time data transmission from the borehole and the earth surface during drilling,are widely used in measurement-while-drilling(MWD)and logging-while-drilling(LWD).Several numerical methods,including the method of moments(MoM),the electric field integral equation(EFIE)method,and the finite-element(FE)method have been developed for the simulation of EM telemetry systems.The computational process of these methods is complicated and time-consuming.To solve this problem,we introduce an axisymmetric semi-analytical FE method(SAFEM)in the cylindrical coordinate system with the virtual layering technique for rapid simulation of EM telemetry in a layered earth.The proposed method divides the computational domain into a series of homogeneous layers.For each layer,only its cross-section is discretized,and a high-precision integration method based on Riccati equations is employed for the calculation of longitudinally homogeneous sections.The block-tridiagonal structure of the global coefficient matrix enables the use of the block Thomas algorithm,facilitating the efficient simulation of EM telemetry problems in layered media.After the theoretical development,we validate the accuracy and efficiency of our algorithm through a series of numerical experiments and comparisons with the Multiphysics modeling software COMSOL.We also discussed the impact of system parameters on EM telemetry signal and demonstrated the applicability of our method by testing it on a field dataset acquired from Dezhou,Shandong Province,China.
基金supported by the National Natural Science Foundation of China(Nos.12471394,12371417)Natural Science Foundation of Changsha(No.kq2502101)。
文摘This paper aims to investigate the tamed Euler method for the random periodic solution of semilinear SDEs with one-sided Lipschitz coefficient.We introduce a novel approach to analyze mean-square error bounds of the novel schemes,without relying on a priori high-order moment bound of the numerical approximation.The expected order-one mean square convergence is attained for the proposed scheme.Moreover,a numerical example is presented to verify our theoretical analysis.
文摘Non-technical losses(NTL)of electric power are a serious problem for electric distribution companies.The solution determines the cost,stability,reliability,and quality of the supplied electricity.The widespread use of advanced metering infrastructure(AMI)and Smart Grid allows all participants in the distribution grid to store and track electricity consumption.During the research,a machine learning model is developed that allows analyzing and predicting the probability of NTL for each consumer of the distribution grid based on daily electricity consumption readings.This model is an ensemble meta-algorithm(stacking)that generalizes the algorithms of random forest,LightGBM,and a homogeneous ensemble of artificial neural networks.The best accuracy of the proposed meta-algorithm in comparison to basic classifiers is experimentally confirmed on the test sample.Such a model,due to good accuracy indicators(ROC-AUC-0.88),can be used as a methodological basis for a decision support system,the purpose of which is to form a sample of suspected NTL sources.The use of such a sample will allow the top management of electric distribution companies to increase the efficiency of raids by performers,making them targeted and accurate,which should contribute to the fight against NTL and the sustainable development of the electric power industry.
基金supported by the Natural Science Foundation of Shandong Province(ZR2021MA019)the National Natural Science Foundation of China(11871312)。
文摘In this paper,a composite numerical scheme is proposed to solve the threedimensional Darcy-Forchheimer miscible displacement problem with positive semi-definite assumptions.A mixed finite element is used for the fow equation.The velocity and pressure are computed simultaneously.The accuracy of velocity is improved one order.The concentration equation is solved by using mixed finite element,multi-step difference and upwind approximation.A multi-step method is used to approximate time derivative for improving the accuracy.The upwind approximation and an expanded mixed finite element are adopted to solve the convection and diffusion,respectively.The composite method could compute the diffusion flux and its gradient.It possibly becomes an eficient tool for solving convection-dominated diffusion problems.Firstly,the conservation of mass holds.Secondly,the multi-step method has high accuracy.Thirdly,the upwind approximation could avoid numerical dispersion.Using numerical analysis of a priori estimates and special techniques of differential equations,we give an error estimates for a positive definite problem.Numerical experiments illustrate its computational efficiency and feasibility of application.
基金funded by the Hanoi University of Mining and Geology(Grant No.T23-44)The research is also funded by the German Research Foundation(DFG e Project number 518862444)in collaboration with the Vietnam National Foundation for Science and Technology Development(NAFOSTED)under grant number DFG.105e2022.03The third author was funded by the Postdoctoral Scholarship Program of the Vingroup Innovation Foundation(VINIF)(VINIF.2023.STS.15).
文摘The quasi-rectangular tunnel represents a novel cross-section design,intended to supersede the traditional circular and rectangular tunnel formats.Due to the limited capacity of the tunnel vault to withstand vertical loads,an interior column is often installed at the center to enhance its load-bearing capacity.This study aims to develop a hyperstatic reaction method(HRM)for the analysis of deformation and structural integrity in this specific tunnel type.The computational model is validated through comparison with the corresponding finite element method(FEM)analysis.Following comprehensive validation,an ensemble machine learning(ML)model is proposed,using numerical benchmark data,to facilitate real-time design and optimization.Subsequently,three widely used ensemble models,i.e.random forest(RF),gradient boosting decision tree(GBDT),and extreme gradient boosting(XGBoost)are compared to identify the most efficient ML model for replacing the HRM model in the design optimization process.The performance metrics,such as the coefficient of determination R2 of about 0.999 and the mean absolute percentage error(MAPE)of about 1%,indicate that XGBoost outperforms the others,exhibiting excellent agreement with the HRM analysis.Additionally,the model demonstrates high computational efficiency,with prediction times measured in seconds.Finally,the HRM-XGBoost model is integrated with the well-known particle swarm optimization(PSO)for the real-time design optimization of quasi-rectangular tunnels,both with and without the interior column.A feature importance assessment is conducted to evaluate the sensitivity of design input features,enabling the selection of the most critical features for the optimization task.
