Based on the fact that 3-D model discretization by artificial could not always be successfully implemented especially for large-scaled problems when high accuracy and efficiency were required, a new adaptive multigrid...Based on the fact that 3-D model discretization by artificial could not always be successfully implemented especially for large-scaled problems when high accuracy and efficiency were required, a new adaptive multigrid finite element method was proposed. In this algorithm, a-posteriori error estimator was employed to generate adaptively refined mesh on a given initial mesh. On these iterative meshes, V-cycle based multigrid method was adopted to fast solve each linear equation with each initial iterative term interpolated from last mesh. With this error estimator, the unknowns were nearly optimally distributed on the final mesh which guaranteed the accuracy. The numerical results show that the multigrid solver is faster and more stable compared with ICCG solver. Meanwhile, the numerical results obtained from the final model discretization approximate the analytical solutions with maximal relative errors less than 1%, which remarkably validates this algorithm.展开更多
In the numerical prediction of weather or climate events,the uncertainty of the initial values and/or prediction models can bring the forecast result’s uncertainty.Due to the absence of true states,studies on this pr...In the numerical prediction of weather or climate events,the uncertainty of the initial values and/or prediction models can bring the forecast result’s uncertainty.Due to the absence of true states,studies on this problem mainly focus on the three subproblems of predictability,i.e.,the lower bound of the maximum predictable time,the upper bound of the prediction error,and the lower bound of the maximum allowable initial error.Aimed at the problem of the lower bound estimation of the maximum allowable initial error,this study first illustrates the shortcoming of the existing estimation,and then presents a new estimation based on the initial observation precision and proves it theoretically.Furthermore,the new lower bound estimations of both the two-dimensional ikeda model and lorenz96 model are obtained by using the cnop(conditional nonlinear optimal perturbation)method and a pso(particle swarm optimization)algorithm,and the estimated precisions are also analyzed.Besides,the estimations yielded by the existing and new formulas are compared;the results show that the estimations produced by the existing formula are often incorrect.展开更多
With the increasing researches on geotechnical properties of the diesel contaminated soil( DCS),the water content measured is indispensable part during the early period. In this study,the relative error of water conte...With the increasing researches on geotechnical properties of the diesel contaminated soil( DCS),the water content measured is indispensable part during the early period. In this study,the relative error of water content measurement using the traditional method is as high as 20. 78%,which is no longer suitable for contaminated soil. Through a series of tests to measure the loss coefficient of diesel in the drying time,the authors finally proposed a modified calculation formula for test samples. The results show that the maximum relative error calculated by using the modified formula is 0. 96%,far lower than that of traditional formula,which can provide accurate data for further study of diesel contaminated soil.展开更多
In order to eliminate the impact of the Doppler effects caused by the motion of the spacecraft on the X-ray pulsar-based navigation, an innovative navigation method using the pulse phase and Doppler frequency measurem...In order to eliminate the impact of the Doppler effects caused by the motion of the spacecraft on the X-ray pulsar-based navigation, an innovative navigation method using the pulse phase and Doppler frequency measurements of the X-ray pulsars is proposed. Given the initial estimate of the spacecraft's state,the real-time photon arrival model is established at the spacecraft with respect to the spacecraft's position and velocity predicted by the orbit dynamic model and their estimation errors. On this basis, a maximum likelihood estimation algorithm directly using the observed photon event timestamps is developed to extract a single pair of pulse phase and Doppler frequency measurements caused by the spacecraft's state estimation error. Since the phase estimation error increases as the observation time increases, we propose a new measurement updating scheme of referring the measurements to the middle time of an observation interval. By using the ground-based simulation system of X-ray pulsar signals, a series of photon-level simulations are performed. The results testify to the feasibility and real-timeliness of the proposed navigation method, and show that the incorporation of the Doppler measurement as well as the pulse phase into the navigation filter can improve the navigation accuracy.展开更多
基金Projects(2006AA06Z105, 2007AA06Z134) supported by the National High-Tech Research and Development Program of ChinaProjects(2007, 2008) supported by China Scholarship Council (CSC)
文摘Based on the fact that 3-D model discretization by artificial could not always be successfully implemented especially for large-scaled problems when high accuracy and efficiency were required, a new adaptive multigrid finite element method was proposed. In this algorithm, a-posteriori error estimator was employed to generate adaptively refined mesh on a given initial mesh. On these iterative meshes, V-cycle based multigrid method was adopted to fast solve each linear equation with each initial iterative term interpolated from last mesh. With this error estimator, the unknowns were nearly optimally distributed on the final mesh which guaranteed the accuracy. The numerical results show that the multigrid solver is faster and more stable compared with ICCG solver. Meanwhile, the numerical results obtained from the final model discretization approximate the analytical solutions with maximal relative errors less than 1%, which remarkably validates this algorithm.
基金supported by the National Natural Science Foundation of China(Grant No.41331174)
文摘In the numerical prediction of weather or climate events,the uncertainty of the initial values and/or prediction models can bring the forecast result’s uncertainty.Due to the absence of true states,studies on this problem mainly focus on the three subproblems of predictability,i.e.,the lower bound of the maximum predictable time,the upper bound of the prediction error,and the lower bound of the maximum allowable initial error.Aimed at the problem of the lower bound estimation of the maximum allowable initial error,this study first illustrates the shortcoming of the existing estimation,and then presents a new estimation based on the initial observation precision and proves it theoretically.Furthermore,the new lower bound estimations of both the two-dimensional ikeda model and lorenz96 model are obtained by using the cnop(conditional nonlinear optimal perturbation)method and a pso(particle swarm optimization)algorithm,and the estimated precisions are also analyzed.Besides,the estimations yielded by the existing and new formulas are compared;the results show that the estimations produced by the existing formula are often incorrect.
文摘With the increasing researches on geotechnical properties of the diesel contaminated soil( DCS),the water content measured is indispensable part during the early period. In this study,the relative error of water content measurement using the traditional method is as high as 20. 78%,which is no longer suitable for contaminated soil. Through a series of tests to measure the loss coefficient of diesel in the drying time,the authors finally proposed a modified calculation formula for test samples. The results show that the maximum relative error calculated by using the modified formula is 0. 96%,far lower than that of traditional formula,which can provide accurate data for further study of diesel contaminated soil.
文摘In order to eliminate the impact of the Doppler effects caused by the motion of the spacecraft on the X-ray pulsar-based navigation, an innovative navigation method using the pulse phase and Doppler frequency measurements of the X-ray pulsars is proposed. Given the initial estimate of the spacecraft's state,the real-time photon arrival model is established at the spacecraft with respect to the spacecraft's position and velocity predicted by the orbit dynamic model and their estimation errors. On this basis, a maximum likelihood estimation algorithm directly using the observed photon event timestamps is developed to extract a single pair of pulse phase and Doppler frequency measurements caused by the spacecraft's state estimation error. Since the phase estimation error increases as the observation time increases, we propose a new measurement updating scheme of referring the measurements to the middle time of an observation interval. By using the ground-based simulation system of X-ray pulsar signals, a series of photon-level simulations are performed. The results testify to the feasibility and real-timeliness of the proposed navigation method, and show that the incorporation of the Doppler measurement as well as the pulse phase into the navigation filter can improve the navigation accuracy.
