Mixed Multiscale Finite Element Method Research Articles

A mixed multiscale FEM for the eddy current problem with T,Φ-Φ and vector hysteresis

PurposeThis work introduces an efficient and accurate technique to solve the eddy current problem in laminated iron cores considering vector hysteresis.Design/methodology/approachThe mixed multiscale finite element method based on the based on the T,Φ-Φ formulation, with the current vector potential T and the magnetic scalar potential Φ allows the laminated core to be modelled as a single homogeneous block. This means that the individual sheets do not have to be resolved, which saves a lot of computing time and reduces the demands on the computer system enormously.FindingsAs a representative numerical example, a single-phase transformer with 4, 20 and 184 sheets is simulated with great success. The eddy current losses of the simulation using the standard finite element method and the simulation using the mixed multiscale finite element method agree very well and the required simulation time is tremendously reduced.Originality/valueThe vector Preisach model is used to account for vector hysteresis and is integrated into the mixed multiscale finite element method for the first time.

Bayesian Uncertainty Quantification for Channelized Reservoirs via Reduced Dimensional Parameterization

In this article, we study uncertainty quantification for flows in heterogeneous porous media. We use a Bayesian approach where the solution to the inverse problem is given by the posterior distribution of the permeability field given the flow and transport data. Permeability fields within facies are assumed to be described by two-point correlation functions, while interfaces that separate facies are represented via smooth pseudo-velocity fields in a level set formulation to get reduced dimensional parameterization. The permeability fields within facies and pseudo-velocity fields representing interfaces can be described using Karhunen–Loève (K-L) expansion, where one can select dominant modes. We study the error of posterior distributions introduced in such truncations by estimating the difference in the expectation of a function with respect to full and truncated posteriors. The theoretical result shows that this error can be bounded by the tail of K-L eigenvalues with constants independent of the dimension of discretization. This result guarantees the feasibility of such truncations with respect to posterior distributions. To speed up Bayesian computations, we use an efficient two-stage Markov chain Monte Carlo (MCMC) method that utilizes mixed multiscale finite element method (MsFEM) to screen the proposals. The numerical results show the validity of the proposed parameterization to channel geometry and error estimations.

A Comparison of Mixed Multiscale Finite Element Methods for Multiphase Transport in Highly Heterogeneous Media

AbstractIn this study, we systemically review and compare two mixed multiscale finite element methods (MMsFEM) for multiphase transport in highly heterogeneous media. In particular, we will consider the mixed multiscale finite element method using limited global information, simply denoted by MMsFEM, and the mixed generalized multiscale finite element method (MGMsFEM) with residual driven online multiscale basis functions. Both methods are within the framework of MMsFEM, where the pressure equation is solved in the coarse grids with carefully constructed multiscale basis functions for the velocity. The multiscale basis functions in both methods include local and global media information. In terms of MsFEM using limited global information, only one multiscale basis function is utilized in each local neighborhood, while multiple bases are used in MGMsFEM. We will test and compare these two methods using the benchmark three‐dimensional SPE10 model. A range of coarse grid sizes and different combinations of basis functions (offline and online) will be considered with CPU time reported for each case. In our numerical experiments, we observe good accuracy by the two above methods. Finally, we will discuss and compare the advantages and disadvantages of the two methods in terms of accuracy and computational costs.

The Discontinuous Petrov–Galerkin methodology for the mixed Multiscale Finite Element Method

We present the application of the Discontinuous Petrov–Galerkin (DPG) methodology for the mixed Multiscale Finite Element Method (MsFEM). The MsFEM upscaling technique relies on incorporating fine-scale features through special, in a sense optimized for approximability, trial functions while the DPG methodology allows for the selection of the optimal test functions to provide stability of the FEM approximation. The special trial functions are computed online by the solution of local boundary value problems. We improved this process using the static condensation that restricted the construction of the functions to the coarse mesh skeleton (element interfaces) only. We have verified by numerical tests that the proposed improvement of MsFEM reduced both the approximation error and computational cost. Moreover, it simplified the algorithm significantly. The key component of this prolongation construction is our novel method for prolongation of both traction and displacement vectors on element edges of arbitrary shape. The proposed prolongation operator may be also used in the multigrid solver for direct analysis of composites with varying material parameters, using an arbitrary well-posed functional setting with or without the DPG methodology.

Online Mixed Multiscale Finite Element Method with Oversampling and Its Applications

In this paper, we consider an online basis enrichment mixed generalized multiscale method with oversampling, for solving flow problems in highly heterogeneous porous media. This is an exten- sion of the online mixed generalized multiscale method [6]. The multiscale online basis functions are computed by solving a Neumann problem in an over-sampled domain, instead of a standard neighborhood of a coarse face. We are motivated by the restricted domain decomposition method. Extensive numerical experiments are presented to demonstrate the performance of our methods for both steady-state flow, and two-phase flow and transport problems.

Application of the mixed multiscale finite element method to parallel simulations of two-phase flows in porous media

The Mixed Multiscale Finite Element method (MMsFE) is a promising alternative to traditional upscaling techniques in order to accelerate the simulation of flows in large heterogeneous porous media. Indeed, in this method, the calculation of the basis functions which encompass the fine-scale variations of the permeability field, can be performed in parallel and the size of the global linear system is reduced. However, we show in this work that a two-level MPI strategy should be used to adapt the calculation resources at these two steps of the algorithm and thus obtain a better scalability of the method. This strategy has been implemented for the resolution of the pressure equation which arises in two-phase flow models. Results of simulations performed on complex reservoir models show the benefits of this approach.

Least-squares mixed generalized multiscale finite element method

In this paper, we present an approximation of elliptic problems with multiscale and high-contrast diffusion coefficients. A mixed formulation is considered such that both pressure and velocity are approximated simultaneously. This formulation arises naturally in many applications such as flows in porous media. Due to the multiscale nature of the solutions, using model reduction is required to efficiently obtain approximate solutions. There are many multiscale approaches for elliptic problems in mixed formulation. These approaches include numerical homogenization and mixed multiscale finite element method, which aim to obtain a coarse accurate representation of the velocity without using an accurate representation for pressure. It has been a challenging task to construct a method giving accurate representation for both pressure and velocity. The goal in this paper is to construct multiscale basis functions for both pressure and velocity. We will apply the framework of Generalized Multiscale Finite Element Method (GMsFEM), and design systematic strategies for the construction of basis. The construction involves snapshot spaces and dimension reduction via local spectral problems. The mixed formulation is minimized in the sense of least-squares. The compatibility condition for multiscale finite element spaces of the pressure and velocity is not required in the least-squares mixed form. This gives more flexibility for the construction of multiscale basis functions for velocity and pressure. Convergence analysis is carried out for the least-squares mixed GMsFEM. Several numerical examples for various permeability fields are presented to show the performance of the presented method. The numerical results show that the least-squares mixed GMsFEM can give accurate approximation for both pressure and velocity using only a few basis functions per coarse element.

A mixed multiscale finite element method for convex optimal control problems with oscillating coefficients

We study numerical approximation of convex optimal control problems governed by elliptic partial differential equations with oscillating coefficients. Since the objective functional contains flux, we approximate the problems using the mixed finite element methods. We first analyze the standard mixed finite element approximation schemes. Then, motivated by the numerical simulation of the primal variable and the flux in highly heterogeneous porous media, we use a multiscale mixed finite element method to solve the state equations. The multiscale finite element bases are constructed by locally solving Neumann boundary value problems. The analysis of the approximate control problems is carried out under the assumption that the oscillating coefficients are locally periodic, which allows us to use homogenization theory to obtain the asymptotic structure of the solutions, although the numerical schemes are designed for the general case.

A Hybrid HDMR for Mixed Multiscale Finite Element Methods with Application to Flows in Random Porous Media

Stochastic modeling has become a popular approach to quantifying uncertainty in flows through heterogeneous porous media. In this approach the uncertainty in the heterogeneous structure of material properties is often parametrized by a high-dimensional random variable, leading to a family of deterministic models. The numerical treatment of this stochastic model becomes very challenging as the dimension of the parameter space increases. To efficiently tackle the high-dimensionality, we propose a hybrid high-dimensional model representation (HDMR) technique, through which the high-dimensional stochastic model is decomposed into a moderate-dimensional stochastic model, in the most active random subspace, and a few one-dimensional stochastic models. The derived low-dimensional stochastic models are solved by incorporating the sparse-grid stochastic collocation method with the proposed hybrid HDMR. In addition, the properties of porous media, such as permeability, often display heterogeneous structure across multiple spatial scales. To treat this heterogeneity we use a mixed multiscale finite element method (MMsFEM). To capture the nonlocal spatial features (i.e., channelized structures) of the porous media and the important effects of random variables, we can hierarchically incorporate the global information individually from each of the random parameters. This significantly enhances the accuracy of the multiscale simulation. Thus, the synergy of the hybrid HDMR and the MMsFEM reduces the dimension of the flow model in both the stochastic and physical spaces, and hence significantly decreases the computational complexity. We analyze the proposed hybrid HDMR technique and the derived stochastic MMsFEM. Numerical experiments are carried out for two-phase flows in random porous media to demonstrate the efficiency and accuracy of the proposed hybrid HDMR with MMsFEM.

ANALYSIS OF VARIANCE-BASED MIXED MULTISCALE FINITE ELEMENT METHOD AND APPLICATIONS IN STOCHASTIC TWO-PHASE FLOWS

The stochastic partial differential systems have been widely used to model physical processes, where the inputs involve large uncertainties. Flows in random and heterogeneous porous media is one of the cases where the random inputs (e.g., permeability) are often modeled as a stochastic field with high-dimensional random parameters. To treat the high dimensionality and heterogeneity efficiently, model reduction is employed in both stochastic space and physical space. An analysis of variance (ANOVA)-based mixed multiscale finite element method (MsFEM) is developed to decompose the high-dimensional stochastic problem into a set of lower-dimensional stochastic subproblems, which require much less computational complexity and significantly reduce the computational cost in stochastic space, and the mixed MsFEM can capture the heterogeneities on a coarse grid to greatly reduce the computational cost in the spatial domain. In addition, to enhance the efficiency of the traditional ANOVA method, an adaptive ANOVA method based on a new adaptive criterion is developed, where the most active dimensions can be selected to greatly reduce the computational cost before conducting ANOVA decomposition. This novel adaptive criterion is based on variance-decomposition method coupled with sparse-grid probabilistic collocation method or multilevel Monte Carlo method. The advantage of this adaptive criterion lies in its much lower computational overhead for identifying the active dimensions and interactions. A number of numerical examples in two-phase stochastic flows are presented and demonstrate the accuracy and performance of the adaptive ANOVA-based mixed MsFEM.

A Hybrid Laplace Transform Mixed Multiscale Finite-Element Method for Flow Model in Porous Media

This paper presents a hybrid Laplace transform Mixed Multiscale Finite-element Method (MMsFEM) to solve partial differential equations of flow in porous media. First, the time term of parabolic equation with unknown pressure term is removed by the Laplace transform. Then, to obtain the numerical approximation of pressure and velocity directly, the transformed equations on coarse mesh are solved by mixed multiscale FEM, which utilizes the effects of fine-scale heterogeneities through basis function formulations computed from local flow problems. Finally, the associated pressure and velocity transform are inverted by the method of numerical inversion of the Laplace transform to obtain the numerical solution.

Multilevel Monte Carlo methods using ensemble level mixed MsFEM for two-phase flow and transport simulations

In this paper, we propose multilevel Monte Carlo (MLMC) methods that use ensemble level mixed multiscale methods in the simulations of multiphase flow and transport. The contribution of this paper is twofold: (1) a design of ensemble level mixed multiscale finite element methods and (2) a novel use of mixed multiscale finite element methods within multilevel Monte Carlo techniques to speed up the computations. The main idea of ensemble level multiscale methods is to construct local multiscale basis functions that can be used for any member of the ensemble. In this paper, we consider two ensemble level mixed multiscale finite element methods: (1) the no-local-solve-online ensemble level method (NLSO); and (2) the local-solve-online ensemble level method (LSO). The first approach was proposed in Aarnes and Efendiev (SIAM J. Sci. Comput. 30(5):2319-2339, 2008) while the second approach is new. Both mixed multiscale methods use a number of snapshots of the permeability media in generating multiscale basis functions. As a result, in the off-line stage, we construct multiple basis functions for each coarse region where basis functions correspond to different realizations. In the no-local-solve-online ensemble level method, one uses the whole set of precomputed basis functions to approximate the solution for an arbitrary realization. In the local-solve-online ensemble level method, one uses the precomputed functions to construct a multiscale basis for a particular realization. With this basis, the solution corresponding to this particular realization is approximated in LSO mixed multiscale finite element method (MsFEM). In both approaches, the accuracy of the method is related to the number of snapshots computed based on different realizations that one uses to precompute a multiscale basis. In this paper, ensemble level multiscale methods are used in multilevel Monte Carlo methods (Giles 2008a, Oper.Res. 56(3):607-617, b). In multilevel Monte Carlo methods, more accurate (and expensive) forward simulations are run with fewer samples, while less accurate (and inexpensive) forward simulations are run with a larger number of samples. Selecting the number of expensive and inexpensive simulations based on the number of coarse degrees of freedom, one can show that MLMC methods can provide better accuracy at the same cost as Monte Carlo (MC) methods. The main objective of the paper is twofold. First, we would like to compare NLSO and LSO mixed MsFEMs. Further, we use both approaches in the context of MLMC to speedup MC calculations.

Multiscale Parameter Identification Method for Three Dimension Steady Heat Transfer Model of Composite Materials

In this paper, for heat conductivity identification of three dimension steady heat transfer model of composite materials, a new hybrid Tikhonov regularization mixed multiscale finite-element method is present. First the mathematical models of the forward and the coefficient inverse problems are discussed. Then the forward model is solved by mixed multiscale FEM which utilizes the effects of fine-scale heterogeneities through basis functions formulation computed from local heat transfer problems. At last the numerical approximation of inverse coefficient problem is obtained by Tikhonov regularization method.

A Combination Method of Mixed Multiscale Finite-Element and Laplace Transform for Flow in a Dual-Permeability System

An efficient combination method of Laplace transform and mixed multiscale finite-element method for coupling partial differential equations of flow in a dual-permeability system is present. First, the time terms of parabolic equation with unknown pressure term are removed by the Laplace transform. Then the transformed equations are solved by mixed FEMs which can provide the numerical approximation formulas for pressure and velocity at the same time. With some assumptions, the multiscale basis functions are constructed by utilizing the effects of fine-scale heterogeneities through basis functions formulation computed from local flow problems. Without time step in discrete process, the present method is efficient when solving spatial discrete problems. At last, the associated pressure transform is inverted by the method of numerical inversion of the Laplace transform.

Expanded Mixed Multiscale Finite Element Methods and Their Applications for Flows in Porous Media

We develop a family of expanded mixed Multiscale Finite Element Methods (MsFEMs) and their hybridizations for second-order elliptic equations. This formulation expands the standard mixed Multiscale Finite Element formulation in the sense that four unknowns (hybrid formulation) are solved simultaneously: pressure, gradient of pressure, velocity and Lagrange multipliers. We use multiscale basis functions for the both velocity and gradient of pressure. In the expanded mixed MsFEM framework, we consider both cases of separable-scale and non-separable spatial scales. We specifically analyze the methods in three categories: periodic separable scales, $G$- convergence separable scales, and continuum scales. When there is no scale separation, using some global information can improve accuracy for the expanded mixed MsFEMs. We present rigorous convergence analysis for expanded mixed MsFEMs. The analysis includes both conforming and nonconforming expanded mixed MsFEM. Numerical results are presented for various multiscale models and flows in porous media with shales to illustrate the efficiency of the expanded mixed MsFEMs.

A priori estimates for two multiscale finite element methods using multiple global fields to wave equations

AbstractWe consider a scalar wave equation with nonseparable spatial scales. If the solution of the wave equation smoothly depends on some global fields, then we can utilize the global fields to construct multiscale finite element basis functions. We present two finite element approaches using the global fields: partition of unity method and mixed multiscale finite element method. We derive a priori error estimates for the two approaches and theoretically investigate the relation between the smoothness of the global fields and convergence rates of the approximations for the wave equation. © 2011 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 2011

A stochastic mixed finite element heterogeneous multiscale method for flow in porous media

A computational methodology is developed to efficiently perform uncertainty quantification for fluid transport in porous media in the presence of both stochastic permeability and multiple scales. In order to capture the small scale heterogeneity, a new mixed multiscale finite element method is developed within the framework of the heterogeneous multiscale method (HMM) in the spatial domain. This new method ensures both local and global mass conservation. Starting from a specified covariance function, the stochastic log-permeability is discretized in the stochastic space using a truncated Karhunen–Loève expansion with several random variables. Due to the small correlation length of the covariance function, this often results in a high stochastic dimensionality. Therefore, a newly developed adaptive high dimensional stochastic model representation technique (HDMR) is used in the stochastic space. This results in a set of low stochastic dimensional subproblems which are efficiently solved using the adaptive sparse grid collocation method (ASGC). Numerical examples are presented for both deterministic and stochastic permeability to show the accuracy and efficiency of the developed stochastic multiscale method.

Stochastic mixed multiscale finite element methods and their applications in random porous media

We present a framework for stochastic mixed multiscale finite element methods (mixed MsFEMs) for elliptic equations with heterogeneous random coefficients. The use of some global information is necessary in multiscale simulations when there is no scale separation for the heterogeneity. The methods in the proposed framework for the stochastic mixed MsFEMs use some global information. The media properties in a stochastic environment drastically vary among realizations and, thus, many global fields are needed for multiscale simulation. The computations of these global fields on a fine grid can be very expensive. One can utilize upscaling methods to compute the global information on an intermediate coarse grid that reduces the computational cost. We investigate two approaches of stochastic mixed MsFEMs in the framework. First approach entails no stochastic interpolation and the second approach uses stochastic interpolation. If the random media have deterministic features that play significant roles in the flow, we can use the deterministic features of the random media as the global information. This reduces the computational cost of the simulations. We make convergence analysis of the stochastic mixed MsFEMs and investigate their applications to incompressible two-phase flows in random porous media. The numerical results demonstrate the effectiveness of the proposed methods and confirm the convergence.

Mixed multiscale finite element methods using approximate global information based on partial upscaling

The use of limited global information in multiscale simulations is needed when there is no scale separation. Previous approaches entail fine-scale simulations in the computation of the global information. The computation of the global information is expensive. In this paper, we propose the use of approximate global information based on partial upscaling. A requirement for partial homogenization is to capture long-range (non-local) effects present in the fine-scale solution, while homogenizing some of the smallest scales. The local information at these smallest scales is captured in the computation of basis functions. Thus, the proposed approach allows us to avoid the computations at the scales that can be homogenized. This results in coarser problems for the computation of global fields. We analyze the convergence of the proposed method. Mathematical formalism is introduced, which allows estimating the errors due to small scales that are homogenized. The proposed method is applied to simulate two-phase flows in heterogeneous porous media. Numerical results are presented for various permeability fields, including those generated using two-point correlation functions and channelized permeability fields from the SPE Comparative Project (Christie and Blunt, SPE Reserv Evalu Eng 4:308–317, 2001). We consider simple cases where one can identify the scales that can be homogenized. For more general cases, we suggest the use of upscaling on the coarse grid with the size smaller than the target coarse grid where multiscale basis functions are constructed. This intermediate coarse grid renders a partially upscaled solution that contains essential non-local information. Numerical examples demonstrate that the use of approximate global information provides better accuracy than purely local multiscale methods.

Mixed Multiscale Finite Element Methods Using Limited Global Information

In this paper, we present a mixed multiscale finite element method using limited global information. We consider a general case where multiple global information is given such that the solution depends smoothly on these global fields. The global fields typically contain small-scale (local or global) information required for achieving a convergence with respect to the coarse mesh size. We present a rigorous analysis and show that the proposed mixed multiscale finite element methods converge. Some preliminary numerical results are shown. We study a parameter dependent permeability field (a simplified case for general stochastic permeability fields). As for spatial heterogeneities, channelized permeability fields with strong nonlocal effects are considered. Using a few global fields corresponding to realizations of permeability fields, we show that one can achieve high accuracy in numerical simulations.