二维土壤溶质输运方程基于POD方法的降阶CN有限元外推算法

首先给出二维土壤溶质输运方程时间二阶精度的Crank-Nicolson(CN)时间半离散化格式和时间二阶精度的全离散化CN有限元格式及其误差分析.然后利用特征投影分解(proper orthogonal decomposition,简记为POD)方法对二维土壤溶质输运方程的经典CN有限元格式做降阶处理,建立一种具有足够高精度、自由度很少的降阶CN有限元外推格式,并给出这种降阶CN有限元解的误差估计和外推算法的实现.最后用数值例子说明数值结果与理论结果是相吻合的.     

二维双曲方程基于POD方法的降阶有限差分外推迭代格式

利用特征投影分解(POD)方法建立二维双曲型方程的一种基于POD方法的含有很少自由度但具有足够高精度的降阶有限差分外推迭代格式,给出其基于POD方法的降阶有限差分解的误差估计及基于POD方法的降阶有限差分外推迭代格式的算法实现.用一个数值例子去说明数值计算结果与理论结果相吻合.进一步说明这种基于POD方法的降阶有限差分外推迭代格式对于求解二维双曲方程是可行和有效的.     

抛物型方程基于POD方法的时间二阶精度CN有限元降维格式

将特征正交分解(proper orthogonal decomposition, 简记为POD) 方法应用于抛物型方程通常的时间二阶精度Crank-Nicolson (简记为CN) 有限元格式, 简化其为一个自由度极少的时间二阶精度CN 有限元降维格式, 并给出简化的时间二阶精度CN 有限元解的误差分析. 数值例子表明在简化的时间二阶精度CN 有限元解和通常的时间二阶精度CN 有限元解之间的误差足够小的情况下, 简化的时间二阶精度CN 有限元格式能大大地节省自由度, 而且时间步长可以比时间一阶精度的格式取大10 倍, 以至能更快计算到所要时刻数值解, 减少计算机计算过程的截断误差, 提高计算速度和计算精度,从而验证降维时间二阶精度CN 有限元格式用于解类似于抛物型方程的时间依赖方程是很有效的.     

守恒高阶各向异性交通流模型基于POD方法的降阶外推差分格式

利用Godunov流方法和特征投影分解方法,对守恒高阶各向异性交通流模型建立一种自由度很少、精度足够高的降阶外推差分算法, 并给出这种降阶外推差分算法近似解的误差估计和算法实现.最后,用数值例子说明数值结果与理论结果相吻合,并阐明这种降阶外推差分算法的优越性.     

非定常Stokes方程一种基于POD方法的简化有限差分格式

特征正交分解(proper orthogonal decomposition,简记为POD)方法是一种可对偏微分方程的物理模型(如流体流动)做简化的技术．这种方法已经成功地用于对复杂系统模型降阶．推广应用POD方法,将POD方法应用于具有实际应用背景的非定常Stokes方程经典的有限差分格式,建立一种维数较低而精度足够高的简化差分格式,并给出简化差分格式解与经典差分格式解的误差估计．数值例子说明数值计算结果与理论结果相吻合．进一步表明基于POD方法的简化差分格式对求解非定常Stokes方程数值解是可行和有效的．     

地球科学中的一类耦合抛物方程组的数值模拟

地质流体的性质和动力学行为是当前地球科学研究的前沿领域.铜陵冬瓜山层控夕卡岩型铜矿床成矿作用中矿质输运-化学反应耦合过程的数学模型是一个非局部的耦合抛物方程组初边值问题.本文考虑这一数学模型的数值模拟,用降阶法对此耦合方程组建立了一个具有二阶精度的差分格式.用能量方法给出了差分方程问题解的先验估计式,并证明了差分格式的可解性、稳定性和收敛性,其收敛阶在L2范数下关于时间步长和空间步长均是二阶的.最后给出了数值例子,数值结果和理论分析结果是吻合的.     

求解奇异摄动问题的一个耦合差分格式

本文考察奇异摄动问题(1.1).在一特殊的非均匀网格上,将不稳定、二阶精度的中心差格式和稳定、一阶精度的Abrahamsson-Keller-Kreiss箱子格式相耦合,得到了一个二阶一致收敛的差分格式.最后给出了数值结果.     

Sobolev方程基于POD的降阶外推差分算法

用奇异值分解和特征投影分解(proper orthogonal decomposition,简记POD)方法建立Sobolev方程的一种降阶外推有限差分算法,并给出误差估计.最后用数值例子,验证基于POD方法降阶外推有限差分算法的可行性和有效性.     

一类偏积分微分方程一阶差分全离散格式

本文给出了数值求解一类偏积分微分方程的一阶差分全离散格式。时间方向采用了一阶向后差分格式，空间方向采用二阶差分格式，给出了稳定性的证明，误差估计及收敛性的结果，并给出了数值例子。     

抛物方程基于POD方法的降阶外推差分算法

用奇值分解和特征投影分解(Proper Orthogonal Decomposition,简记POD)方法去建立抛物方程的一种降阶外推有限差分算法,并给出误差估计.最后用数值例子验证这种基于POD方法降阶外推有限差分算法的可行性和有效性.     

交通流模型基于特征投影分解技术的外推降维有限差分格式

利用特征正交分解(proper orthogonal decomposition,简记为POD)技术研究交通流的Aw-Rascle-Zhang(ARZ)模型. 建立一种基于 POD方法维数较低的外推降维有限差分格式, 并用数值例子检验数值计算结果与理论结果相吻合, 进一步表明基于POD方法的外推降维有限差分格式对于求解交通流方程数值解是可行和有效的.     

A pod reduced-order spdmfe extrapolating algorithm for hyperbolic equations

In this article, a proper orthogonal decomposition (POD) method is used to study a classical splitting positive definite mixed finite element (SPDMFE) formulation for second-order hyperbolic equations. A POD reduced-order SPDMFE extrapolating algorithm with lower dimensions and sufficiently high accuracy is established for second-order hyperbolic equations. The error estimates between the classical SPDMFE solutions and the reduced-order SPDMFE solutions obtained from the POD reduced-order SPDMFE extrapolating algorithm are provided. The implementation for solving the POD reduced-order SPDMFE extrapolating algorithm is given. Some numerical experiments are presented illustrating that the results of numerical computation are consistent with theoretical conclusions, thus validating that the POD reduced-order SPDMFE extrapolating algorithm is feasible and efficient for solving second-order hyperbolic equations.     

A POD REDUCED-ORDER SPDMFE EXTRAPOLATING ALGORITHM FOR HYPERBOLIC EQUATIONS

In this article, a proper orthogonal decomposition （POD） method is used to study a classical splitting positive definite mixed finite element （SPDMFE） formulation for second- order hyperbolic equations. A POD reduced-order SPDMFE extrapolating algorithm with lower dimensions and sufficiently high accuracy is established for second-order hyperbolic equations. The error estimates between the classical SPDMFE solutions and the reduced-order SPDMFE solutions obtained from the POD reduced-order SPDMFE extrapolating algorithm are provided. The implementation for solving the POD reduced-order SPDMFE extrapolating algorithm is given. Some numerical experiments are presented illustrating that the results of numerical computation are consistent with theoretical conclusions, thus validating that the POD reduced-order SPDMFE extrapolating algorithm is feasible and efficient for solving second-order hyperbolic equations.     

Finite difference scheme based on proper orthogonal decomposition for the nonstationary Navier-Stokes equations

The proper orthogonal decomposition(POD)and the singular value decomposition(SVD) are used to study the finite difference scheme(FDS)for the nonstationary Navier-Stokes equations. Ensembles of data are compiled from the transient solutions computed from the discrete equation system derived from the FDS for the nonstationary Navier-Stokes equations.The optimal orthogonal bases are reconstructed by the elements of the ensemble with POD and SVD.Combining the above procedures with a Galerkin projection approach yields a new optimizing FDS model with lower dimensions and a high accuracy for the nonstationary Navier-Stokes equations.The errors between POD approximate solutions and FDS solutions are analyzed.It is shown by considering the results obtained for numerical simulations of cavity flows that the error between POD approximate solution and FDS solution is consistent with theoretical results.Moreover,it is also shown that this validates the feasibility and efficiency of POD method.     

A reduced FE formulation based on POD method for hyperbolic equations

A proper orthogonal decomposition (POD) method was successfully used in the reduced-order modeling of complex systems. In this paper, we extend the applications of POD method, namely, apply POD method to a classical finite element (FE) formulation for second-order hyperbolic equations with real practical applied background, establish a reduced FE formulation with lower dimensions and high enough accuracy, and provide the error estimates between the reduced FE solutions and the classical FE solutions and the implementation of algorithm for solving reduced FE formulation so as to provide scientific theoretic basis for service applications. Some numerical examples illustrate the fact that the results of numerical computation are consistent with theoretical conclusions. Moreover, it is shown that the reduced FE formulation based on POD method is feasible and efficient for solving FE formulation for second-order hyperbolic equations.     

A New Reduced-Order fve Algorithm Based on POD Method for Viscoelastic Equations

A proper orthogonal decomposition (POD) technique is used to reduce the finite volume element (FVE) method for two-dimensional (2D) viscoelastic equations. A reduced-order fully discrete FVE algorithm with fewer degrees of freedom and sufficiently high accuracy based on POD method is established. The error estimates of the reduced-order fully discrete FVE solutions and the implementation for solving the reduced-order fully discrete FVE algorithm are provided. Some numerical examples are used to illustrate that the results of numerical computation are consistent with theoretical conclusions. Moreover, it is shown that the reduced-order fully discrete FVE algorithm is one of the most effective numerical methods by comparing with corresponding numerical results of finite element formulation and finite difference scheme and that the reduced-order fully discrete FVE algorithm based on POD method is feasible and efficient for solving 2D viscoelastic equations.     

A reduced-order extrapolation algorithm based on CNLSMFE formulation and POD technique for two-dimensional Sobolev equations

A reduced-order extrapolation algorithm based on Crank-Nicolson least-squares mixed finite element （CNLSMFE） formulation and proper orthogonal decomposition （POD） technique for two-dimensional （2D） Sobolev equations is established. The error estimates of the reduced-order CNLSMFE solutions and the implementation for the reduced-order extrapolation algorithm are provided. A numerical example is used to show that the results of numerical computations are consistent with theoretical conclusions. Moreover, it is shown that the reduced-order extrapolation algorithm is feasible and efficient for seeking numerical solutions to 2D Sobolev equations.     

Reduced-order extrapolation spectral-finite difference scheme based on POD method and error estimation for three-dimensional parabolic equation

In this study, a classical spectral-finite difference scheme (SFDS) for the three-dimensional (3D) parabolic equation is reduced by using proper orthogonal decomposition (POD) and singular value decomposition (SVD). First, the 3D parabolic equation is discretized in spatial variables by using spectral collocation method and the discrete scheme is transformed into matrix formulation by tensor product. Second, the classical SFDS is obtained by difference discretization in time-direction. The ensemble of data are comprised with the first few transient solutions of the classical SFDS for the 3D parabolic equation and the POD bases of ensemble of data are generated by using POD technique and SVD. The unknown quantities of the classical SFDS are replaced with the linear combination of POD bases and a reducedorder extrapolation SFDS with lower dimensions and sufficiently high accuracy for the 3D parabolic equation is established. Third, the error estimates between the classical SFDS solutions and the reduced-order extrapolation SFDS solutions and the implementation for solving the reduced-order extrapolation SFDS are provided. Finally, a numerical example shows that the errors of numerical computations are consistent with the theoretical results. Moreover, it is shown that the reduced-order extrapolation SFDS is effective and feasible to find the numerical solutions for the 3D parabolic equation.     

A reduced-order finite difference extrapolation algorithm based on POD technique for the non-stationary Navier–Stokes equations

In this paper, a proper orthogonal decomposition (POD) technique is used to establish a reduced-order finite difference (FD) extrapolation algorithm with lower dimensions and sufficiently high accuracy for the non-stationary Navier–Stokes equations, and the error estimates between the reduced-order FD solutions and the classical FD solutions and the implementation for solving the reduced-order FD extrapolation algorithm are provided. Two numerical examples illustrate the fact that the results of numerical computation are consistent with theoretical conclusions. Moreover, it is shown that the reduced-order FD extrapolation algorithm based on POD method is feasible and efficient for solving the non-stationary Navier–Stokes equations.     

非饱和土壤水流问题基于POD 方法的降阶有限体积元格式及外推算法实现

利用特征投影分解(proper orthogonal decomposition, 简记为POD) 方法对非饱和土壤水流问题的经典有限体积元格式做降阶处理, 建立一种具有足够高精度维数较低的降阶有限体积元格式, 并给出这种降阶有限体积元解的误差估计和外推算法的实现, 最后用数值例子说明数值结果与理论结果是相吻合的. 进一步表明了基于POD 方法的降阶有限体积元格式对求解非饱和土壤水流问题数值解是可靠和有效的.