Error analysis for a second order approximation of a viscoelastic phase separation model

In this paper, the Gauge–Uzawa method for the time‐dependent incompressible micropolar fluid problem is proposed. Firstly, the first‐order and second‐order Euler semi‐implicit Gauge–Uzawa methods for the micropolar fluid are constructed, and the unconditionally stability analysis and error estimate of the corresponding first‐order scheme are deduced. Secondly, the fully discrete scheme with finite element approximation in space is presented, and the stability result of the corresponding first‐order scheme is derived. Finally, some numerical results are given, which test the theoretical analysis results.

Parameter identification is an important research topic with a variety of applications in industrial and environmental problems. Usually, a functional has to be minimized in conjunction with parameter identification; thus, there is a certain similarity between the parameter identification and optimization. A number of rigorous and efficient algorithms for optimization problems were developed in recent decades for the case of a convex functional. In the case of a non-convex functional, the metaheuristic algorithms dominate. This paper discusses an optimization method called modified bee colony algorithm (MBC), which is a modification of the standard bees algorithm (SBA). The SBA is inspired by a particular intelligent behavior of honeybee swarms. The algorithm is adapted for the parameter identification of reaction-dominated pore-scale transport when a non-convex functional has to be minimized. The algorithm is first checked by solving a few benchmark problems, namely finding the minima for Shekel, Rosenbrock, Himmelblau and Rastrigin functions. A statistical analysis was carried out to compare the performance of MBC with the SBA and the artificial bee colony (ABC) algorithm. Next, MBC is applied to identify the three parameters in the Langmuir isotherm, which is used to describe the considered reaction. Here, 2D periodic porous media were considered. The simulation results show that the MBC algorithm can be successfully used for identifying admissible sets for the reaction parameters in reaction-dominated transport characterized by low Pecklet and high Damkholer numbers. Finite element approximation in space and implicit time discretization are exploited to solve the direct problem.

An energy-conserving finite element method for nonlinear fourth-order wave equations

In this paper, we consider the Galerkin finite element method for solving the fractional stochastic diffusion‐wave equations driven by multiplicative noise, which can be used to describe the propagation of mechanical waves in viscoelastic media with random effects. The optimal strong convergence error estimates with respect to the semidiscrete finite element approximation in space are established. Finally, a numerical example is presented to verify the reliability of the theoretical study.

In this work, we study the thermal effects around the oil well cluster on permafrost using numerical modeling. We use the mathematical model of heat transfer with phase transitions. To take into account the arrangement of wells in a cluster, three-dimensional domains with complex geometry are employed, which leads to the use of finite element approximation in space. For time approximation we use fully implicit scheme with linearization of nonlinear coefficients. Numerical implementations are performed using open-source libraries and programs for scientific and engineering computations. To predict the temperature field and formation of thawing area around wells with different sets of input parameters we conduct large-scale computational experiments on the supercomputer of the North-Eastern Federal University.

In this article we consider the iterative solution of the linear system of equations arising from the discretisation of the poly-energetic linear Boltzmann transport equation using a high-order/hp–version discontinuous Galerkin finite element approximation in space, angle, and energy. In particular, we develop preconditioned Richardson iterations which may be understood as generalisations of source iteration in the mono-energetic setting, and derive computable a posteriori bounds for the solver error incurred due to inexact linear algebra, measured in a relevant problem-specific norm. We prove that the convergence of the resulting schemes and a posteriori solver error estimates are independent of the mesh size h and polynomial degree p. We also discuss how the poly-energetic Richardson iteration may be employed as a preconditioner for the generalised minimal residual (GMRES) method. Furthermore, we show that standard implementations of GMRES based on minimising the Euclidean norm of the residual vector can be utilized to yield computable a posteriori solver error estimates at each iteration, through judicious selections of left- and right-preconditioners for the original linear system. The effectiveness of poly-energetic source iteration and preconditioned GMRES, as well as their respective a posteriori solver error estimates, is demonstrated through numerical examples arising in the modelling of photon transport. While the convergence of poly-energetic source iteration is independent of h and p, we observe that the number of iterations required to attain convergence when employing GMRES only depends mildly on h and p. Moreover, this latter approach is highly effective in the low energy regime.

Modeling large-deforming fluid-saturated porous media using an Eulerian incremental formulation

Finite element approximations of impulsive optimal control problems for heat equations

Numerical solutions of the stochastic Stokes equations driven by white noise perturbed forcing terms using finite element methods are consid- ered. The discretization of the white noise and finite element approximation algorithms are studied. The rate of convergence of the finite element approxi- mations is proved to be almost first order (h| ln h|) in two dimensions and one half order (h 1 2 ) in three dimensions. Numerical results using the algorithms

In this paper, we present an a posteriori error analysis for finite element approximation of distributed convex optimal control problems. We derive a posteriori error estimates for the coupled state and control approximations under some assumptions which hold in many applications. Such estimates, which are apparently not available in the literature, can be used to construct reliable adaptive finite element approximation schemes for control problems. Explicit estimates are obtained for some model problems which frequently appear in real-life applications.

Direct numerical simulation (DNS) of fluid flow in porous media with many scales is often not feasible, and an effective or homogenized description is more desirable. To construct the homogenized equations, effective properties must be computed. Computation of effective properties for nonperiodic microstructures can be prohibitively expensive, as many local cell problems must be solved for different macroscopic points. In addition, the local problems may also be computationally expensive. When the microstructure varies slowly, we develop an efficient numerical method for two scales that achieves essentially the same accuracy as that for the full resolution solve of every local cell problem. In this method, we build a dense hierarchy of macroscopic grid points and a corresponding nested sequence of approximation spaces. Essentially, solutions computed in high accuracy approximation spaces at select points in the the hierarchy are used as corrections for the error of the lower accuracy approximation spaces at nearby macroscopic points. We give a brief overview of slowly varying media and formal Stokes homogenization in such domains. We present a general outline of the algorithm and list reasonable and easily verifiable assumptions on the PDEs, geometry, and approximation spaces. With these assumptions, we achieve the same accuracy as the full solve. To demonstrate the elements of the proof of the error estimate, we use a hierarchy of macro--grid points in $[0,1]^2$ and finite element (FE) approximation spaces in $[0,1]^2$. We apply this algorithm to Stokes equations in a slowly porous medium where the microstructure is obtained from a reference periodic domain by a known smooth map. Using the arbitrary Lagrange--Eulerian (ALE) formulation of the Stokes equations (cf. [G. P. Galdi and R. Rannacher, Fundamental Trends in Fluid-Structure Interaction, Contemporary Challenges in Mathematical Fluid Dynamics and Its Applications 1, World Scientific, Singapore, 2010]), we obtain modified Stokes equations with varying coefficients in the periodic domain. We show that the algorithm can be utilized in this setting. Finally, we implement the algorithm on the modified Stokes equations, using a simple stretch deformation mapping, and compute the effective permeability. We show that our efficient computation is of the same order as the full solve.

We construct a method for the parameterization of a class of planar piecewise C2‐curves over a collection of edges in an ambient triangulation. The map from the collection of edges to the curve is the closest‐point projection. A distinguishing feature of the method is that edges in the ambient triangulation need not interpolate the curve. We formulate conditions on the ambient triangulations so that the resulting parameterization over its selected edges is (i) bijective, (ii) maps simple, connected collection of edges to simple, connected components of the curve, and (iii) is C1 within each edge of the collection. These properties of the parameterization make it particularly useful in the construction of high‐order finite element approximation spaces on planar curves immersed in triangulations. We discuss this application and illustrate it with numerical examples.The parameterization method applies to a large class of planar curves, including most ones of interest in engineering and computer graphics applications, and to a large family of triangulations, including acute‐angled triangulations. Copyright © 2011 John Wiley & Sons, Ltd.

Coefficient inverse problems related to identifying the right-hand side of an equation with use of additional information is of interest among inverse problems for partial differential equations. When considering non-stationary problems, tasks of recovering the dependence of the right-hand side on time and spatial variables can be treated as independent. These tasks relate to a class of linear inverse problems, which sufficiently simplifies their study. This work is devoted to finding the dependence of right-hand side of multidimensional parabolic equation on spatial variables using additional observations of the solution at the final point of time – the final overdetermination. More general problems are associated with some integral observation of the solution in time – the integral overdetermination. The first method of numerical solution of inverse problems is based on iterative solution of boundary value problem for time derivative with non-local acceleration. The second method is based on the known approach with iterative refinement of desired dependence of the right-hand side on spatial variables. Capabilities of proposed methods are illustrated by numerical examples for a two-dimensional problem of identifying the right-hand side of a parabolic equation. The standard finite-element approximation in space is used, whilst the time discretization is based on fully implicit two-level schemes.

In this paper we develop an a posteriori error analysis for an augmented mixed-primal finite element approximation of a stationary viscous flow and transport problem. The governing system corresponds to a scalar, nonlinear convection-diffusion equation coupled with a Stokes problem with variable viscosity, and it serves as a prototype model for sedimentation-consolidation processes and other phenomena where the transport of species concentration within a viscous fluid is of interest. The solvability of the continuous mixed-primal formulation along with a priori error estimates for a finite element scheme using Raviart−Thomas spaces of order k for the stress approximation, and continuous piecewise polynomials of degree ≤ k + 1 for both velocity and concentration, have been recently established in [M. Alvarez et al., ESAIM: M2AN 49 (2015) 1399–1427]. Here we derive two efficient and reliable residual-based a posteriori error estimators for that scheme: for the first estimator, and under suitable assumptions on the domain, we apply a Helmholtz decomposition and exploit local approximation properties of the Clement interpolant and Raviart−Thomas operator to show its reliability. On the other hand, its efficiency follows from inverse inequalities and the localization arguments based on triangle-bubble and edge-bubble functions. Secondly, an alternative error estimator is proposed, whose reliability can be proved without resorting to Helmholtz decompositions. Our theoretical results are then illustrated via some numerical examples, highlighting also the performance of the scheme and properties of the proposed error indicators.

The Landau–Lifshitz–Bloch equation (LLBE) describes the evolution of the magnetic spin field in ferromagnets at high temperatures. In this paper we study the numerical approximation of the LLBE in the regime above the Curie temperature on bounded polytopal domains in $\mathbb{R}^{d}$, with $d\in \{1,2,3\}$, allowing for nonconvex domains when $d=2$. We first establish the existence and uniqueness of strong solutions to the LLBE and propose a linear, fully discrete, conforming finite element scheme for its approximation. While this scheme is shown to converge, the obtained rate is suboptimal. To address this shortcoming we introduce a viscous (pseudo-parabolic) regularization of the LLBE, which we call the $\epsilon $-LLBE. For this regularized problem we prove the unique existence of strong solutions and establish a rate of convergence of the solution $\boldsymbol{u}^\epsilon $ of the $\epsilon $-LLBE to the solution $\boldsymbol{u}$ of the LLBE as $\epsilon \to 0^{+}$. Furthermore, we propose a linear, fully discrete, conforming finite element scheme to approximate the solution of the $\epsilon $-LLBE. Given sufficiently smooth initial data error analysis is performed to show stability and uniform-in-time convergence of the scheme. Finally, several numerical simulations are presented to corroborate our theoretical results.