Partitioned treatment of surface-coupled problems with application to the fluid-porous-media interaction

Employing a decoupled solution strategy for the numerical treatment of the set of governing equations describing a surface-coupled phenomenon is a common practice. In this regard, many partitioned solution algorithms have been developed, which usually either belong to the family of Schur-complement methods or to the group of staggered integration schemes. To select a decoupled solution strategy over another is, however, a case-dependent process that should be done with special care. In particular, the performances of the algorithms from the viewpoints of stability and accuracy of the results on the one hand, and the solution speed on the other hand should be investigated. In this contribution, two strategies for a partitioned treatment of the surface-coupled problem of fluid-porous-media interaction (FPMI) are considered. These are one parallel solution algorithm, which is based on the method of localised Lagrange multipliers (LLM), and one sequential solution method, which follows the block-Gauss-Seidel (BGS) integration strategy. In order to investigate the performances of the proposed schemes, an exemplary initial-boundary-value problem is considered and the numerical results obtained by employing the solution algorithms are compared. (© 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

MULTILEVEL AUGMENTATION METHODS FOR SOLVING OPERATOR EQUATIONS

We introduce multilevel augmentation methods for solving operator equations based on direct sum decompositions of the range space of the operator and the solution space of the operator equation and a matrix splitting scheme. We establish a general setting for the analysis of these methods, showing that the methods yield approximate solutions of the same convergence order as the best approximation from the subspace. These augmentation methods allow us to develop fast, accurate and stable nonconventional numerical algorithms for solving operator equations. In particular, for second kind equations, special splitting techniques are proposed to develop such algorithms. These algorithms are then applied to solve the linear systems resulting from matrix compression schemes using wavelet-like functions for solving Fredholm integral equations of the second kind. For this special case, a complete analysis for computational complexity and convergence order is presented. Numerical examples are included to demonstra     

含三角函数的一般形式复杂对偶积分方程组的理论解

本文基于Gopson法，进行研究，改进，推广，应用于一般形式，复杂的对偶积分方程组的求解，首先引入函数进行方程组变换，其次引入未知函数的积分变换实现退耦，应用Abel反演变换，使方程组正则化为Fredholm第二类积分方程组，并由此给出对偶积分方程组的一般性解，本文给出的解法和理论解，可供求解复杂的数学，物理，力学中的混合边值问题参考，选用．同时也提供求解复杂的对偶积分方程组另一种有效的解法。     

A modified variable neighborhood search for the discrete ordered median problem

This paper presents a modified Variable Neighborhood Search (VNS) heuristic algorithm for solving the Discrete Ordered Median Problem (DOMP). This heuristic is based on new neighborhoods’ structures that allow an efficient encoding of the solutions of the DOMP avoiding sorting in the evaluation of the objective function at each considered solution. The algorithm is based on a data structure, computed in preprocessing, that organizes the minimal necessary information to update and evaluate solutions in linear time without sorting. In order to investigate the performance, the new algorithm is compared with other heuristic algorithms previously available in the literature for solving DOMP. We report on some computational experiments based on the well-known N-median instances of the ORLIB with up to 900 nodes. The obtained results are comparable or superior to existing algorithms in the literature, both in running times and number of best solutions found.     

On globally solving the extended trust-region subproblems

With the help of the newly developed technique—second order cone (SOC) constraints to strengthen the SDP relaxation of the extended trust-region subproblem (eTRS), we modify two recent SDP relaxation based branch and bound algorithms for solving eTRS. Numerical experiments on some types of problems show that the new algorithms run faster for finding the global optimal solutions than the SDP relaxation based algorithms.     

Multigrid method for coupled semilinear elliptic equation

This paper introduces a kind of multigrid finite element method for the coupled semilinear elliptic equations. Instead of the common way of directly solving the coupled semilinear elliptic problems on some fine spaces, the presented method transforms the solution of the coupled semilinear elliptic problem into a series of solutions of the corresponding decoupled linear boundary value problems on the sequence of multilevel finite element spaces and some coupled semilinear elliptic problems on a very low dimensional space. The decoupled linearized boundary value problems can be solved by some multigrid iterations efficiently. The optimal error estimate and optimal computational work are proved theoretically and demonstrated numerically. Moreover, the requirement of bounded second‐order derivatives of the nonlinear term in the existing multigrid method is reduced to a Lipschitz continuous condition in the proposed method.     

Modified two-grid method for solving coupled Navier-Stokes/Darcy model based on Newton iteration

A new decoupled two-gird algorithm with the Newton iteration is proposed for solving the coupled Navier-Stokes/Darcy model which describes a fluid flow filtrating through porous media. Moreover the err...     

Coupled Multi-field and Multi-rate Problems – Numerical Solution and Stability Analysis

The numerical solution of coupled differential equation systems is usually done following a monolithic or a decoupled algorithm. In contrast to the holistic monolithic solvers, the decoupled solution strategies are based on breaking down the system into several subsystems. This results in different characteristics of these families of solvers, e. g., while the monolithic algorithms provide a relatively straight-forward solution framework, unlike their decoupled counterparts, they hinder software re-usability and customisation. This is a drawback for multi-field and multi-rate problems. The reason is that a multi-field problem comprises several subproblems corresponding to interacting subsystems. This suggests exploiting an individual solver for each subproblem. Moreover, for the efficient solution of a multi-rate problem, it makes sense to perform the temporal integration of each subproblem using a time-step size relative to its evolution rate. Nevertheless, decoupled solvers introduce additional errors to the solution and, thus, they must always be accompanied by a thorough stability analysis. Here, tailored solution schemes for the decoupled solution of multi-field and multi-rate problems are proposed. Moreover, the stability behaviour of the solutions obtained from these methods are studied. Numerical examples are solved and the reliability of the outcome of the stability analysis is investigated. (© 2013 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Singular integral transforms and fast numerical algorithms

Fast algorithms for the accurate evaluation of some singular integral operators that arise in the context of solving certain partial differential equations within the unit circle in the complex plane are presented. These algorithms are generalizations and extensions of a fast algorithm of Daripa [11]. They are based on some recursive relations in Fourier space and the FFT (Fast Fourier Transform), and have theoretical computational complexity of the order O(N) per point, where N² is the total number of grid points. An application of these algorithms to quasiconformal mappings of doubly connected domains onto annuli is presented in a follow-up paper.     

非匹配网格上Stokes-Darcy 问题非协调元离散的两水平和多水平方法

本文讨论了非匹配网格上Stokes-Darcy 问题的两种低阶非协调元方法, 给出了误差估计, 对耦合的非协调元离散问题, 通过粗网格求得的界面条件, 我们提出了一个解耦的两水平算法. 并且我们将两水平方法推广到多水平情形, 其只需在一个很粗的网格上解一耦合问题, 然后在逐步加细的网格上求解解耦的问题, 理论分析和数值试验都说明方法的高效性.     

Two-grid stabilized algorithms for the steady Navier–Stokes equations with damping

This paper presents and studies three two-grid stabilized quadratic equal-order finite element algorithms based on two local Gauss integrations for the steady Navier–Stokes equations with damping. In these algorithms, we first solve a stabilized nonlinear problem on a coarse grid, and then pass the coarse grid solution to a fine grid and solve a stabilized linear problem. Using some nonlinear analysis techniques, we analyze stability of the algorithms and derive optimal order error estimates of the approximate solutions. Theoretical and numerical results show that, when the algorithmic parameters are chosen appropriately, the accuracy of the approximate solutions computed by our two-grid stabilized algorithms is comparable to that of solving a fully stabilized nonlinear problem on the same fine grid; however, our two-grid algorithms save a large amount of CPU time than the one-grid stabilized algorithm.     

An E-based splitting finite element method for time-dependent eddy current equations

A new decoupled finite element method is suggested to approximate time-dependent eddy current equations in a three-dimensional polyhedral domain. This method is based on solving a vector and a scalar from the splitting of the electric field by using edge and nodal finite elements. An optimal energy-norm error estimate in finite time is obtained by introducing a projection operator.     

Robin–Robin domain decomposition methods for the steady-state Stokes–Darcy system with the Beavers–Joseph interface condition

Domain decomposition methods for solving the coupled Stokes–Darcy system with the Beavers–Joseph interface condition are proposed and analyzed. Robin boundary conditions are used to decouple the Stokes and Darcy parts of the system. Then, parallel and serial domain decomposition methods are constructed based on the two decoupled sub-problems. Convergence of the two methods is demonstrated and the results of computational experiments are presented to illustrate the convergence.     

Iterative splitting methods for solving time-dependent problems

There is increasing motivation for solving time-dependent differential equations with iterative splitting schemes. While Magnus expansion has been intensively studied and widely applied for solving explicitly time-dependent problems, the combination with iterative splitting schemes can open up new areas. The main problems with the Magnus expansion are the exponential character and the difficulty of deriving practical higher order algorithms. An alternative method is based on iterative splitting methods that take into account a temporally inhomogeneous equation. In this work, we show that the ideas derived from the iterative splitting methods can be used to solve time-dependent problems. Examples are discussed.     

使用非单调技术的不精确预条件牛顿类方法解非线性方程组

本文提供了预条件不精确牛顿型方法结合非单调技术解光滑的非线性方程组．在合理的条件下证明了算法的整体收敛性．进一步，基于预条件收敛的性质，获得了算法的局部收敛速率，并指出如何选择势序列保证预条件不精确牛顿型的算法局部超线性收敛速率．     

带有资源转移时间的RCPSP资源流模型及算法

本文在传统资源受限项目调度问题(resource-constrained project scheduling problem, RCPSP)中引入资源转移时间,为有效获得问题的最优解,采用资源流编码方式表示可行解,建立了带有资源转移时间的RCPSP资源流优化模型,目标为最小化项目工期。根据问题特征设计了改进的资源流重构邻域算子,分别设计了改进的禁忌搜索算法和贪心随机自适应禁忌搜索算法求解模型。数据实验结果表明,相较于现有文献中的方法,所提两种算法均可针对更多的项目实例求得最优解,并且得到最优解的时间更短,求解效率更高。此外,分析了算法在求解具有不同特征的项目实例时的性能,所得结果为项目经理结合项目特征评价算法适用性提供了指导。     

A Multistep Scheme for Decoupled Forward-Backward Stochastic Differential Equations

Upon a set of backward orthogonal polynomials, we propose a novel multi-step numerical scheme for solving the decoupled forward-backward stochastic differential equations (FBSDEs). Under Lipschtiz conditions on the coefficients of the FBSDEs, we first get a general error estimate result which implies zero-stability of the proposed scheme, and then we further prove that the convergence rate of the scheme can be of high order for Markovian FBSDEs. Some numerical experiments are presented to demonstrate the accuracy of the proposed multi-step scheme and to numerically verify the theoretical results.     

Benchmarking ordering techniques for nonserial dynamic programming

Five ordering algorithms for the nonserial dynamic programming algorithm for solving sparse discrete optimization problems are compared in this paper. The benchmarking reveals that the ordering of the variables has a significant impact on the run-time of these algorithms. In addition, it is shown that different orderings are most effective for different classes of problems. Finally, it is shown that, amongst the algorithms considered here, heuristics based on maximum cardinality search and minimum fill-in perform best for solving the discrete optimization problems considered in this paper.     

Duality methods with an automatic choice of parameters Application to shallow water equations in conservative form

Summary.   In [3] a duality numerical algorithm for solving variational inequalities based on certain properties of the Yosida approximation of maximal monotone operators has been introduced. The performance of this algorithm strongly depends on the choice of two constant parameters. In this paper, we consider a new class of algorithms where these constant parameters are replaced by functions. We show that convergence properties are preserved and look for optimal values of these two functions. In general these optimal values cannot be computed, as they depend on the exact solution. Therefore, we propose some strategies in order to approximate them. The resulting algorithms are applied to three variational inequalities in order to compare their performance with that of the original algorithm. Received July 20, 1998 / Revised version received November 26, 1999 / Published online February 5, 2001