Eigenvalue and Near Eigenvalue Problems Solved by Brandt's Multigrid Method.

Flow fields in a centrifugal fan for an indoor unit of an air-conditioner were calculated with finite element method-based large eddy simulation (LES) with the aim of predicting fan performance and aerodynamic noise in this study. The numerical simulation code employed throughout the LES was called FrontFlow/blue (FFB). We compared 10M grid [coarse grid] and 60M grid [fine grid] calculation results for investigation of influence of grid resolution. In the fine grid, the number of grid elements in blade-to-blade direction, and of region between the shroud and the bell mouth increased in particular. By calculating with the fine grid, calculated distributions of absolute velocities at blade exit reasonably agreed with experimental results. Because of this, maximum absolute velocity by fine grid near hub decreased as compared to those by coarse grid. Calculated sound pressure level by fine grid was therefore smaller than that by coarse grid, and the overestimation of sound pressure was suppressed by calculating with fine grid. This decrease of the absolute velocity was a first factor for the improvement of calculation accuracy. Moreover, number of captured streaks on the blade, hub, and shroud surfaces by fine grid increased as compared to those by coarse grid. As a result, size of streak by fine grid became smaller than that by coarse grid. Static pressure fluctuations by fine grid on the blade, hub, and shroud surfaces therefore reduced as compared to those by coarse grid. Aerodynamic noise was related to static pressure fluctuations according to Curle’s equation. This reduction of static pressure fluctuations was therefore a second factor for improvement of calculation accuracy.

Running a fine grid model with 107 - 109 of cells is possible using a supercomputer with 103 - 106 of CPUs but may not be always cost-effective. The most cost-effective way is to use a coarse grid model that is much smaller but with static/dynamic profiles very close to the fine grid model. This paper proposes a new layer optimization and upscaling method with the aim for creating a consistent coarse grid model. Unlike the industry's existing layer optimization and upscaling methods, the proposed method performs layer optimization and upscaling fully integrated with the Lorenz coefficient and curves (LCC). Coarse grid layers and their permeabilities are created by minimizing the difference between fine and coarse grid LCCs. The process consists of static and dynamic optimizations. The former is measured by LCC while the latter by pressure, GOR, and water-cut. A new LCC-based permeability upscaling method is developed to preserve the fine grid multiphase flow behaviors. A satisfactory coarse grid model is achieved when both static and dynamic criteria are met. The proposed method has been successfully applied to a giant carbonate oil field in the Caspian Sea that consists of a matrix dominated platform and a fracture/karst dominated rim. Due to the field's complex geology and high H2S content (15%), a dual porosity, dual permeability compositional model has been created to model compositional sour crude flow within and between the matrix and fracture/karst features. The reservoir drive mechanisms are fluid expansion, miscible gas injection and aquifer drive. The reservoir is undersaturated and has an abnormally high initial reservoir pressure. The fine-grid static model contains 104 million cells (370×225×625×2) and the optimized upscaled coarse-grid dynamic model has 8.3 million cells (370×225×50×2). The upscaled model can be run efficiently on the company's existing HPC infrastructure with a maximum of 64 CPUs. Excellent matches of the Lorenz coefficient maps for reservoir total/zones and Lorenz curves at all wells between the fine and coarse grid models have been achieved. Matches on the dynamic variables, e.g., pressure, gas breakthrough time, and GOR growth, in all producers are within the defined acceptable tolerances. The high quality of the static and dynamic matches between the coarse- and fine-grid models confirms that the reservoir properties of the coarse-grid model is very close to the fine-grid model and can be used a base model for history matching and uncertainty analysis.

Seismic data are routinely used to infer in situ properties of earth materials on many scales, ranging from global studies to investigations of surficial geological formations. While inversion and imaging algorithms utilizing these data have improved steadily, there are remaining challenges that make detailed measurements of the properties of some geologic materials very difficult. For example, the determination of the concentration and orientation of fracture systems is prohibitively expensive to simulate on the fine grid and, thus, some type of coarse-grid simulations are needed. In this paper, we describe a new multiscale finite element algorithm for simulating seismic wave propagation in heterogeneous media. This method solves the wave equation on a coarse grid using multiscale basis functions and a global coupling mechanism to relate information between fine and coarse grids. Using a mixed formulation of the wave equation and staggered discontinuous basis functions, the proposed multiscale methods have the following properties. • The total wave energy is conserved. • Mass matrix is diagonal on a coarse grid and explicit energy-preserving time discretization does not require solving a linear system at each time step. • Multiscale basis functions can accurately capture the subgrid variations of the solution and the time stepping is performed on a coarse grid. We discuss various subgrid capturing mechanisms and present some preliminary numerical results.

This paper presents a multidomain (MD) computational approach to multiscale (MS) compositional reservoir simulation amenable to parallel processing. The main objective is to minimize the upscaling process and preserve the pertinent flow characteristics of the fine-scale geological features of the reservoir. The preservation of the fine-scale reservoir characteristics yields higher-accuracy solution compared to an upscaled model. The computing algorithm involves breaking down the fine-grid (FG) computing mesh into an underlying coarse-grid (CG) subdomain. Unlike other MS techniques, the CG subdomain only serves as an assemblage of the FG cells and not as a computational CG overlaying the FG cells. The flow equations are then restructured into a global pressure equation which is solved on the FG using a large time step without solving for the compositions, saturations, etc. The convergence tolerance for the global pressure solution is soft (no iterations) to reduce computing time. The pressure solution is then used to calculate the molar flux of components only at the FG boundaries of the CG subdomain cells. Finally, each CG subdomain subject to its boundary conditions is solved independently using a smaller time step to compute cell pressures, compositions, and phase saturations. This procedure is amenable to parallel processing. This MS scheme was applied to time domain, in which the global pressure solution is obtained with a larger time step than in the local FG solution. This means that the molar flux boundary condition at the CG subdomain boundaries is not updated every time step, thus, buying additional computational advantage. This new technique was tested on several volatile oil and gas-condensate systems and excellent agreement was obtained with FG simulation with about 60% reduction in computing time using a single processor. Much greater time reduction is expected in a multi processing environment.

Higher-order compact finite difference scheme with multigrid algorithm is applied in this paper for solving one-dimensional and two-dimensional inhomogeneous Helmholtz equations. In two-dimensional case, the suggested scheme has the stencil of twenty one points. An efficient solver multigrid method yields eighth-order accurate approximation on both fine and coarse grids. For the Neumann boundary condition, an eighth-order accurate representation is also developed. The accuracy and efficiency of eighth-order compact difference scheme are exhibited through graphical illustrations and computed results are drafted in tabular form to validate the numerical experiments.

We propose to enhance the stability of IMEX schemes applied to the numerical solution of nonlinear parabolic equations by using proper smoothing procedures on bands of frequency components of the solution. The separation of those different components is realized by considering a multigrid (MG) approach. The time scheme on the coarsest grid is implicit and energy diminishing, while time marching is done by a weighted damped IMEX scheme on the finer grids. This approach allows to concentrate most computational efforts on a small set of components (the coarsest grid) and to fine-tune the damping parameters so that there is limited consistency perturbation while enhancing stability. We provide stability results and numerical illustrations on pattern dynamics, Swift-Hohenberg, and crystal-phase fields equations, in both 2D and 3D cases. The results obtained with MG are comparable with those given by a one-grid simulation.

Fast and robust sixth-order multigrid computation for the three-dimensional convection–diffusion equation

On the basis of Yang and Bi’s work (SIAM J Numer Anal 49, p.1602-1624), this paper discusses a discretization scheme for a sort of Steklov eigenvalue problem and proves the high effiency of the scheme. With the scheme, the solution of an eigenvalue problem on a fine grid is reduced to the solution of an eigenvalue problem on a much coarser grid and the solution of a linear algebraic system on the fine grid. And the resulting solution can maintain an asymptotically optimal accuracy. Finally, the numerical results are provided to support the theoretical analysis..

This paper provides a new two-grid discretization method for solving partial differential equation or integral equation eigenvalue problems. In 2001, Xu and Zhou introduced a scheme that reduces the solution of an eigenvalue problem on a finite element grid to that of one single linear problem on the same grid together with a similar eigenvalue problem on a much coarser grid. By solving a slightly different linear problem on the fine grid, the new algorithm in this paper significantly improves the theoretical error estimate which allows a much coarser mesh to achieve the same asymptotic convergence rate. Numerical examples are also provided to demonstrate the efficiency of the new method.

Convergence analysis of two-grid fixed stress split iterative scheme for coupled flow and deformation in heterogeneous poroelastic media

The starved lubrication is common in engine. However, there are only few studies on starved lubrication problem for textured surfaces. In particular, for the textured surface, a two-dimensional solution is required to study their performances clearly, by considering the pattern and distribution of textured cells. This article presents a new analysis method for the two-dimensional starved lubrication problems with the textured surfaces. In the starved model, the inlet boundary condition of oil film is required and needs to be updated over the process of calculation. In order to obtain the inlet boundary condition, the flow conservation equations at the inlet region are built to determine the position of the attaching point. Meanwhile, as the two-dimensional code is expensive in the computational cost, the multigrid method is employed to accelerate the convergence of pressure. The inlet boundary condition should be transferred between the coarse grids and the fine grids. In this way, solutions for the starved lubrication are offered for an efficient implementation. The starved lubrication model is successfully applied in the ring–liner system. The effects of the surface features on the inlet boundary, wear and friction loss are discussed. It is found that the surface texturing can improve the performance of the ring–liner system under the staved lubrication.

Based on the photoacoustic effect, photoacoustic tomography (PAT) illuminates biological tissue with modulated light to obtain high-contrast images non-invasively, making it increasingly popular in biomedical and life sciences. In practical applications, the varying speed of sound (SOS) in biological tissue is a critical factor influencing the quality of reconstructed images. Among various reconstruction methods addressing this heterogeneity, joint reconstruction (JR) has emerged as a promising approach since it can recover both the initial pressure (IP) and SOS simultaneously, based solely on detected signals, without requiring prior knowledge of the SOS or additional ultrasound equipment. However, traditional JR suffers from two key limitations: 1) the SOS inversion problem is ill-posed, and 2) the alternating iterative solution for IP and SOS incurs very high computational costs. In this study, we introduce a multi-grid iterative strategy into the JR framework, addressing the inverse problem across multi-scale grids and coupling the results from different scales of grids. Specifically, computation begins on the coarse grids, with the reconstruction results serving as high-quality initial estimates for subsequent iterations on the fine grids. This process ultimately reconstructs the distributions of IP and SOS on the target grid successfully. Through numerical simulations, the proposed method is compared with traditional methods in terms of imaging quality and speed. The results demonstrate that the multi-grid iterative strategy significantly accelerates the speed of JR while preserving accuracy. The proposed multi-grid JR method is highly cost-effective in providing high-quality reconstructions and has the potential to offer valuable guidance for the practical applications of JR.

The paper deals with certain adaptive multilevel methods at the confluence of nested multigrid methods and iterative methods based on the cascade principle of [10]. From the multigrid point of view, no correction cycles are needed; from the cascade principle view, a basic iteration method without any preconditioner is used at successive refinement levels. For a prescribed error tolerance on the final level, more iterations must be spent on coarser grids in order to allow for less iterations on finer grids. A first candidate of such a cascadic multigrid method was the recently suggested cascadic conjugate gradient method of [9], in short CCG method, whichused the CG method as basic iteration method on each level. In [18] it has been proven, that the CCG method is accurate with optimal complexity for elliptic problems in 2D and quasi-uniform triangulations. The present paper simplifies that theory and extends it to more general basic iteration methods like the traditional multigrid smoothers. Moreover, an adaptive control strategy for the number of iterations on successive refinement levels for possibly highly non-uniform grids is worked out on the basis of a posteriori estimates. Numerical tests confirm the efficiency and robustness of the cascadic multigrid method.

A novel technique for upscaling of detailed geological reservoir descriptions is presented. The technique aims at reducing both numerical dispersion and homogenization error, generated due to incorporating a coarse computational grid and assigning effective permeability to coarse grid blocks respectively. In particular we consider implicit-pressure explicit-saturation (IMPES) scheme where homogenization error impacts the accuracy of the coarse grid solution of the pressure equation. To reduce the homogenization error, we employ the new vorticity-based gridding that generates a nonuniform coarse grid with high resolution at high vorticity zones. In addition, to control numerical dispersion, we use Dual Mesh Method (DMM), which uses different grids to solve pressure and saturation equations. The coarse grid generated from vorticity is used for computation of pressure and the reference fine grid is used for updating saturation explicitly. The most strong point of the method is that dual mesh method has been incorporated onto non-uniform grid structure. This combination removes the need to solve the full fine grid for two-phase flow modeling, resulting in a less computationally demanding and more accurate upscaling technique. To evaluate the method, we run two-phase simulation using different 2D test cases. Our results indicate that the non-uniform DMM is more accurate than the uniform DMM due to using vorticity-based grids. The speed-up achieved in the computation is significant depending on the complexity of model and degree of upscaling.

A method for performing nested grid calculations with a large-eddy simulation code is described. A common numerical method is used for all meshes, and the grid architecture consists of a single outer or coarse grid, and nested or fine grids, which overlap in some common region. Inter-grid communication matches the velocity, pressure and potential temperature fields in the overlap region. Resolved and sub-grid scale (SGS) turbulent fluxes and kinetic energy on the fine grid are averaged to the coarse grid using a conservation rule equivalent to Germano's identity used to develop dynamic SGS models. Simulations of a slightly convective, strong shear planetary boundary layer were carried out with varying surface-layer resolutions. Grid refinements in the (x, y, z) directions of up to (5, 5, 2) times were employed. Two-way interaction solutions on the coarse and fine meshes are successfully matched in the overlap region on an instantaneous basis, and the turbulent motions on the fine grid blend smoothly into the coarse grid across the grid interface. With surface-layer grid nesting, significant increases in resolved eddy fluxes and variances are found. The energy-scale content of the vertical velocity, and hence vertical turbulent fluxes, appear to be most influenced by increased grid resolution. Vertical velocity spectra show that the dominant scale shifts towards higher wavenumbers (smaller scales) and the magnitude of the peak energy is increased by more than a factor of 3 with finer resolution. Outside of the nested region the average heat and momentum fluxes and spectra are slightly influenced by the fine resolution in the surface layer. From these results we conclude that fine resolution is required to resolve the details of the turbulent motions in the surface layer. At the same time, however, increased resolution in the surface layer does not appreciably alter the ensemble statistics of the resolved and SGS motions outside of the nested region.