A virtual element method-based positivity-preserving conservative scheme for convection–diffusion problems on polygonal meshes

In this paper, we propose a positivity-preserving conservative scheme based on the virtual element method (VEM) to solve convection–diffusion problems on general meshes. As an extension of finite element methods to general polygonal elements, the VEM has many advantages such as substantial mathematical foundations, simplicity in implementation. However, it is neither positivity-preserving nor locally conservative. The purpose of this article is to develop a new scheme, which has the same accuracy as the VEM and preserves the positivity of the numerical solution and local conservation on primary grids. The first step is to calculate the cell-vertex values by the lowest-order VEM. Then, the nonlinear two-point flux approximations are utilized to obtain the nonnegativity of cell-centered values and the local conservation property. The new scheme inherits both advantages of the VEM and the nonlinear two-point flux approximations. Numerical results show that the new scheme can reach the optimal convergence order of the virtual element theory, that is, the second-order accuracy for the solution and the first-order accuracy for its gradient. Moreover, the obtained cell-centered values are nonnegative, which demonstrates the positivity-preserving property of our new scheme.     

Virtual element methods for parabolic problems on polygonal meshes

The virtual element method (VEM) is a recent technology that can make use of very general polygonal/polyhedral meshes without the need to integrate complex nonpolynomial functions on the elements and preserving an optimal order of convergence. In this article, we develop for the first time, the VEM for parabolic problems on polygonal meshes, considering time‐dependent diffusion as our model problem. After presenting the scheme, we develop a theoretical analysis and show the practical behavior of the proposed method through a large array of numerical tests. © 2015 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 31: 2110–2134, 2015     

Veamy: an extensible object-oriented C++ library for the virtual element method

Numerical Algorithms - This paper summarizes the development of Veamy, an object-oriented C++ library for the virtual element method (VEM) on general polygonal meshes, whose modular design is...     

The dynamic random subgraph model for the clustering of evolving networks

In recent years, many clustering methods have been proposed to extract information from networks. The principle is to look for groups of vertices with homogenous connection profiles. Most of these techniques are suitable for static networks, that is to say, not taking into account the temporal dimension. This work is motivated by the need of analyzing evolving networks where a decomposition of the networks into subgraphs is given. Therefore, in this paper, we consider the random subgraph model (RSM) which was proposed recently to model networks through latent clusters built within known partitions. Using a state space model to characterize the cluster proportions, RSM is then extended in order to deal with dynamic networks. We call the latter the dynamic random subgraph model (dRSM). A variational expectation maximization (VEM) algorithm is proposed to perform inference. We show that the variational approximations lead to an update step which involves a new state space model from which the parameters along with the hidden states can be estimated using the standard Kalman filter and Rauch–Tung–Striebel smoother. Simulated data sets are considered to assess the proposed methodology. Finally, dRSM along with the corresponding VEM algorithm are applied to an original maritime network built from printed Lloyd’s voyage records.     

A priori and a posteriori error analysis for virtual element discretization of elliptic optimal control problem

Numerical Algorithms - In this paper, a virtual element method (VEM) discretization of elliptic optimal control problem with pointwise control constraint is investigated. Virtual element discrete...     

Gradient recovery type a posteriori error estimates of virtual element method for an elliptic variational inequality of the second kind

In this paper, gradient recovery type a posteriori error estimators of virtual element discretization are derived for a simplified friction problem, which is a typical elliptic variational inequality of the second kind. Both the reliability and the efficiency of the error estimators are proved. In addition, one numerical example is presented to show the efficiency of the adaptive VEM based on the derived error estimators.     

The Virtual Element Method for large scale Discrete Fracture Network simulations: fracture-independent mesh generation

We consider the problem of underground flow simulations in fractured media. This is a large scale, heterogeneous multi-scale phenomenon involving very complex geological configurations. Within the Discrete Fracture Network (DFN) model, we focus on the resolution of the steady-state flow in large fracture networks. Exploiting the peculiarity of the Virtual Element Method (VEM), which allows the use of rather general polygonal mesh elements, we propose an approach for building a suitable mesh for representing the solution on DFNs. (© 2015 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Virtual Elements for the Reissner‐Mindlin plate problem

In this work, we present a virtual element method for the approximation of the plate bending problem in the Reissner‐Mindlin formulation. The proposed method follows the MITC approach of the FEM context. We construct a family of VEM spaces with arbitrary degree of accuracy that satisfies the conditions of the MITC philosophy. We perform some numerical tests which allow us to assess the convergence and the robustness of the method.     

A MIXED VIRTUAL ELEMENT METHOD FOR THE BOUSSINESQ PROBLEM ON POLYGONAL MESHES

In this work we introduce and analyze a mixed virtual element method(mixed-VEM)for the two-dimensional stationary Boussinesq problem.The continuous formulation is based on the introduction of a pseudostress tensor depending nonlinearly on the velocity,which allows to obtain an equivalent model in which the main unknowns are given by the aforementioned pseudostress tensor,the velocity and the temperature,whereas the pressure is computed via a postprocessing formula.In addition,an augmented approach together with a fixed point strategy is used to analyze the well-posedness of the resulting continuous formulation.Regarding the discrete problem,we follow the approach employed in a previous work dealing with the Navier-Stokes equations,and couple it with a VEM for the convection-diffusion equation modelling the temperature.More precisely,we use a mixed-VEM for the scheme associated with the fluid equations in such a way that the pseudostress and the velocity are approximated on virtual element subspaces of H(div)and H¹,respectively,whereas a VEM is proposed to approximate the temperature on a virtual element subspace of H¹.In this way,we make use of the L²-orthogonal projectors onto suitable polynomial spaces,which allows the explicit integration of the terms that appear in the bilinear and trilinear forms involved in the scheme for the fluid equations.On the other hand,in order to manipulate the bilinear form associated to the heat equations,we define a suitable projector onto a space of polynomials to deal with the fact that the diffusion tensor,which represents the thermal conductivity,is variable.Next,the corresponding solvability analysis is performed using again appropriate fixed-point arguments.Further,Strang-type estimates are applied to derive the a priori error estimates for the components of the virtual element solution as well as for the fully computable projections of them and the postprocessed pressure.The corresponding rates of convergence are also established.Finally,several numerical examples illustrating the performance of the mixed-VEM scheme and confirming these theoretical rates are presented.     

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??Dynamic complex network has become a popular topic in the many fields, such as population ecology, social ecology, biology and Internet. Meanwhile cluster analysis is a common tool to extract network structure. Previous articles on network clustering mostly supposed that observations are conditionally independent. However, we construct novel model which combines the stochastic block model, the hidden structure in Markov process and the autoregressive model to relax this assumption. We also propose relative statistical inference and VEM algorithm. Finally, the Monte Carlo simulations are performed well, which shows the consistency and robustness of the work.     

Dynamic Cluster Analysis of Dependent Networks

Dynamic complex network has become a popular topic in the many fields, such as population ecology, social ecology, biology and Internet. Meanwhile cluster analysis is a common tool to extract network structure. Previous articles on network clustering mostly supposed that observations are conditionally independent. However, we construct novel model which combines the stochastic block model, the hidden structure in Markov process and the autoregressive model to relax this assumption. We also propose relative statistical inference and VEM algorithm. Finally, the Monte Carlo simulations are performed well, which shows the consistency and robustness of the work.     

Error propagation of general linear methods for ordinary differential equations

We discuss error propagation for general linear methods for ordinary differential equations up to terms of order p+2, where p is the order of the method. These results are then applied to the estimation of local discretization errors for methods of order p and for the adjacent order p+1. The results of numerical experiments confirm the reliability of these estimates. This research has applications in the design of robust stepsize and order changing strategies for algorithms based on general linear methods.     

Finite volume transport schemes

We analyze arbitrary order linear finite volume transport schemes and show asymptotic stability in L ¹ and L ^∞ for odd order schemes in dimension one. It gives sharp fractional order estimates of convergence for BV solutions. It shows odd order finite volume advection schemes are better than even order finite volume schemes. Therefore the Gibbs phenomena is controlled for odd order finite volume schemes. Numerical experiments sustain the theoretical analysis. In particular the oscillations of the Lax–Wendroff scheme for small Courant numbers are correlated with its non stability in L ¹. A scheme of order three is proved to be stable in L ¹ and L ^∞.     

On the notion of stability of order convergence in vector lattices

In the theory of Banach lattices the following criterion for a norm to be order continuous is established: a norm is order continuous if and only if every order bounded sequence of positive pairwise disjoint elements in a lattice converges to zero in norm. In this paper we give a criterion for order convergence to be stable in a rather wide class of vector lattices which includes all Köthe spaces. The formulation of the criterion is analogous to that of the above-mentioned criterion for a norm to be order continuous. Namely, under certain conditions imposed on a vector lattice, stability of order convergence is equivalent to the condition that every order bounded sequence of positive pairwise disjoint elements converges relatively uniformly to zero. Furthermore, we study some types of order ideals in vector lattices. In terms of these ideals we give clarified versions of the above-stated criterions. As for notation and terminology, see for example [1,2].Translated fromSibirskiî Matematicheskiî Zhurnal, Vol. 35, No. 5, pp. 1026–1031, September–October, 1994.     

Comparison of multigrid algorithms for high‐order continuous finite element discretizations

We present a comparison of different multigrid approaches for the solution of systems arising from high‐order continuous finite element discretizations of elliptic partial differential equations on complex geometries. We consider the pointwise Jacobi, the Chebyshev‐accelerated Jacobi, and the symmetric successive over‐relaxation smoothers, as well as elementwise block Jacobi smoothing. Three approaches for the multigrid hierarchy are compared: (1) high‐order h‐multigrid, which uses high‐order interpolation and restriction between geometrically coarsened meshes; (2) p‐multigrid, in which the polynomial order is reduced while the mesh remains unchanged, and the interpolation and restriction incorporate the different‐order basis functions; and (3) a first‐order approximation multigrid preconditioner constructed using the nodes of the high‐order discretization. This latter approach is often combined with algebraic multigrid for the low‐order operator and is attractive for high‐order discretizations on unstructured meshes, where geometric coarsening is difficult. Based on a simple performance model, we compare the computational cost of the different approaches. Using scalar test problems in two and three dimensions with constant and varying coefficients, we compare the performance of the different multigrid approaches for polynomial orders up to 16. Overall, both h‐multigrid and p‐multigrid work well; the first‐order approximation is less efficient. For constant coefficients, all smoothers work well. For variable coefficients, Chebyshev and symmetric successive over‐relaxation smoothing outperform Jacobi smoothing. While all of the tested methods converge in a mesh‐independent number of iterations, none of them behaves completely independent of the polynomial order. When multigrid is used as a preconditioner in a Krylov method, the iteration number decreases significantly compared with using multigrid as a solver. Copyright © 2015 John Wiley & Sons, Ltd.     

Higher order optimality conditions with an arbitrary non-differentiable function

In this paper, we introduce a higher order directional derivative and higher order subdifferential of Hadamard type of a given proper extended real function. We obtain necessary and sufficient optimality conditions of order n (n is a positive integer) for unconstrained problems in terms of them. We do not require any restrictions on the function in our results. In contrast to the most known directional derivatives, our derivative is harmonized with the classical higher order Fréchet directional derivative of the same order in the sense that both of them coincide, provided that the last one exists. A notion of a higher order critical direction is introduced. It is applied in the characterizations of the isolated local minimum of order n. Higher order invex functions are defined. They are the largest class such that the necessary conditions for a local minimum are sufficient for global one. We compare our results with some previous ones. As an application, we improve a result due to V. F. Demyanov, showing that the condition introduced by this author is a complete characterization of isolated local minimizers of order n.     

A note on phase synchronization in coupled chaotic fractional order systems

The dynamic behaviors of fractional order systems have received increasing attention in recent years. This paper addresses the reliable phase synchronization problem between two coupled chaotic fractional order systems. An active nonlinear feedback control scheme is constructed to achieve phase synchronization between two coupled chaotic fractional order systems. We investigated the necessary conditions for fractional order Lorenz, Lü and Rössler systems to exhibit chaotic attractor similar to their integer order counterpart. Then, based on the stability results of fractional order systems, sufficient conditions for phase synchronization of the fractional models of Lorenz, Lü and Rössler systems are derived. The synchronization scheme that is simple and global enables synchronization of fractional order chaotic systems to be achieved without the computation of the conditional Lyapunov exponents. Numerical simulations are performed to assess the performance of the presented analysis.     

Intelligent variable orderings and re-orderings in DAC-based solvers for WCSP

Weighted constraint satisfaction problems (WCSPs) is a well-known framework for combinatorial optimization problems with several domains of application. In the last few years, several local consistencies for WCSPs have been proposed. Their main use is to embed them into a systematic search, in order to detect and prune unfeasible values as well as to anticipate the detection of deadends. Some of these consistencies rely on an order among variables but nothing is known about which orders are best. Therefore, current implementations use the lexicographic order by default. In this paper we analyze the effect of heuristic orders at three levels of increasing overhead: i) compute the order prior to search and keep it fixed during the whole solving process (we call this a static order), ii) compute the order at every search node using current subproblem information (we call this a dynamic order) and iii) compute a sequence of different orders at every search node and sequentially enforce the local consistency for each one (we call this dynamic re-ordering). We performed experiments in three different problems: Max-SAT, Max-CSP and warehouse location problems. We did not find an alternative better than the rest for all the instances. However, we found that inverse degree (static order), sum of unary weights (dynamic order) and re-ordering with the sum of unary weights are good heuristics which are always better than a random order. This research is supported by the MEC through project TIC-2002-04470-C03.     

On the order of summability of the Fourier inversion formula

In this article we show that the order of the point value, in the sense of Łojasiewicz, of a tempered distribution and the order of summability of the pointwise Fourier inversion formula are closely related. Assuming that the order of the point values and certain order of growth at infinity are given for a tempered distribution, we estimate the order of summability of the Fourier inversion formula. For Fourier series, and in other cases, it is shown that if the distribution has a distributional point value of order k, then its Fourier series is e.v. Cesàro summable to the distributional point value of order k+1. Conversely, we also show that if the pointwise Fourier inversion formula is e.v. Cesàro summable of order k, then the distribution is the (k+1)-th derivative of a locally integrable function, and the distribution has a distributional point value of order k+2. We also establish connections between orders of summability and local behavior for other Fourier inversion problems.     

Finite Order Rank-One Convex Envelopes and Computation of Microstructures with Laminates in Laminates

Finite order rank-one convex envelopes are introduced and it is shown that the i-th order laminated microstructures, or laminates in laminates, can be solved by any of the k-th order rank-one convex envelopes with k i. It is also shown that in finite element approximations of microstructures, replacing the non-quasiconvex potential energy density by its k-th order rank-one convex envelope, one can generally obtain sharper numerical results. Especially, for crystalline microstructures with laminates in laminates of order no greater than k + 1, numerical results with up to the computer precision can be obtained. Numerical examples on the first and second order rank-one convex envelopes for the Ericksen-James two-dimensional model for elastic crystals are given. A numerical example on finite element approximations of a crystalline microstructure by using the first order rank-one convex envelope and the periodic relaxation method is also presented. The methods turn out to be very successful for microstructures with laminates in laminates.