A posteriori error control for discontinuous Galerkin methods for parabolic problems

We derive energy-norm a posteriori error bounds for an Euler time-stepping method combined with various spatial discontinuous Galerkin schemes for linear parabolic problems. For accessibility, we address first the spatially semidiscrete case, and then move to the fully discrete scheme by introducing the implicit Euler time-stepping. All results are presented in an abstract setting and then illustrated with particular applications. This enables the error bounds to hold for a variety of discontinuous Galerkin methods, provided that energy-norm a posteriori error bounds for the corresponding elliptic problem are available. To illustrate the method, we apply it to the interior penalty discontinuous Galerkin method, which requires the derivation of novel a posteriori error bounds. For the analysis of the time-dependent problems we use the elliptic reconstruction technique and we deal with the nonconforming part of the error by deriving appropriate computable a posteriori bounds for it.Comment: 6 figure

Reaction-diffusion systems on evolving domains with applications to the theory of biological pattern formation

In this thesis we investigate a model for biological pattern formation during growth development. The pattern formation phenomenon is described by a reaction-diffusion system on a time-dependent domain. We prove the global existence of solutions to reaction-diffusion systems on time-dependent domains.We extend global existence results for a class of reaction-diffusion systems on fixed domains to the same systems posed on spatially linear isotropically evolving domains. We demonstrate that the analysis is applicable to many systems that commonly arise in the theory of pattern formation. Our results give a mathematical justification to the widespread use of computer simulations of reaction-diffusion systems on evolving domains. We propose a finite element method to approximate the solutions to reaction-diffusion systems on time-dependent domains. We prove optimal convergence rates for the error in the method and we derive a computable error estimator that provides an upper bound for the error in the semidiscrete (space) scheme. We have implemented the method in the C programming language and we verify our theoretical results with benchmark computations. The method is a robust tool for the study of biological pattern formation, as it is applicable to domains with irregular geometries and nonuniform evolution. This versatility is illustrated with extensive computer simulations of reaction-diffusion systems on evolving domains. We observe varied pattern transitions induced by domain evolution, such as stripe to spot transitions, spotsplitting, spot-merging and spot-annihilation. We also illustrate the striking effects of spatially nonuniform domain evolution on the position, orientation and symmetry of patterns generated by reaction-diffusion systems. To improve the efficiency of the method, we have implemented a space-time adaptive algorithm where spatial adaptivity is driven by an error estimator and temporal adaptivity is driven by an error indicator.We illustrate with numerical simulations the dramatic improvements in accuracy and efficiency that are achieved via adaptivity. To demonstrate the applicability and generality of our methodology, we examine the process of parr mark pattern formation during the early development of the Amago trout. By assuming the existence of chemical concentrations residing on the surface of the Amago fish which react and diffuse during surface evolution, we model the pattern formation process with reactiondiffusion systems posed on evolving surfaces. An important generalisation of our study is the experimentally driven modelling of the fish’s developing body surface. Our results add weight to the feasibility of reaction-diffusion system models of fish skin patterning, by illustrating that a reaction-diffusion system posed on an evolving surface generates transient patterns consistent with those experimentally observed on the developing Amago trout. Furthermore, we conclude that the surface evolution profile, the surface geometry and the curvature are key factors which play a pivotal role in pattern formation via reaction-diffusion systems

Space-time Methods for Time-dependent Partial Differential Equations

Modern discretizations of time-dependent PDEs consider the full problem in the space-time cylinder and aim to overcome limitations of classical approaches such as the method of lines (first discretize in space and then solve the resulting ODE) and the Rothe method (first discretize in time and then solve the PDE). A main advantage of a holistic space-time method is the direct access to space-time adaptivity and to the backward problem (required for the dual problem in optimization or error control). Moreover, this allows for parallel solution strategies simultaneously in time and space. Several space-time concepts where proposed (different conforming and nonconforming space-time finite elements, the parareal method, wavefront relaxation etc.) but this topic has become a rapidly growing field in numerical analysis and scientific computing. In this workshop the focus is the development of adaptive and flexible space-time discretization methods for solving parabolic and hyperbolic space-time partial differential equations

Computational modelling of iron-ore mineralisation with stratigraphic permeability anisotropy

This study develops a computational framework to model fluid transport in sedimentary basins, targeting iron ore deposit formation. It offers a simplified flow model, accounting for geological features and permeability anisotropy as driving factors. A new finite element method lessens computational effort, facilitating robust predictions and cost-effective exploration. This methodology, applicable to other mineral commodities, enhances understanding of genetic models, supporting the search for new mineral deposits amid the global energy transition

Multiscale Methods for Stochastic Collocation of Mixed Finite Elements for Flow in Porous Media

This thesis contains methods for uncertainty quantification of flow in porous media through stochastic modeling. New parallel algorithms are described for both deterministic and stochastic model problems, and are shown to be computationally more efficient than existing approaches in many cases.First, we present a method that combines a mixed finite element spatial discretization with collocation in stochastic dimensions on a tensor product grid. The governing equations are based on Darcy's Law with stochastic permeability. A known covariance function is used to approximate the log permeability as a truncated Karhunen-Loeve expansion. A priori error analysis is performed and numerically verified.Second, we present a new implementation of a multiscale mortar mixed finite element method. The original algorithm uses non-overlapping domain decomposition to reformulate a fine scale problem as a coarse scale mortar interface problem. This system is then solved in parallel with an iterative method, requiring the solution to local subdomain problems on every interface iteration. Our modified implementation instead forms a Multiscale Flux Basis consisting of mortar functions that represent individual flux responses for each mortar degree of freedom, on each subdomain independently. We show this approach yields the same solution as the original method, and compare the computational workload with a balancing preconditioner.Third, we extend and combine the previous works as follows. Multiple rock types are modeled as nonstationary media with a sum of Karhunen-Loeve expansions. Very heterogeneous noise is handled via collocation on a sparse grid in high dimensions. Uncertainty quantification is parallelized by coupling a multiscale mortar mixed finite element discretization with stochastic collocation. We give three new algorithms to solve the resulting system. They use the original implementation, a deterministic Multiscale Flux Basis, and a stochastic Multiscale Flux Basis. Multiscale a priori error analysis is performed and numerically verified for single-phase flow. Fourth, we present a concurrent approach that uses the Multiscale Flux Basis as an interface preconditioner. We show the preconditioner significantly reduces the number of interface iterations, and describe how it can be used for stochastic collocation as well as two-phase flow simulations in both fully-implicit and IMPES models

Nonstandard Finite Element Methods

[no abstract available

The Investigation of Efficiency of Physical Phenomena Modelling Using Differential Equations on Distributed Systems

This work is dedicated to development of mathematical modelling software. In this dissertation numerical methods and algorithms are investigated in software making context. While applying a numerical method it is important to take into account the limited computer resources, the architecture of these resources and how do methods affect software robustness. Three main aspects of this investigation are that software implementation must be efficient, robust and be able to utilize specific hardware resources. The hardware specificity in this work is related to distributed computations of different types: single CPU with multiple cores, multiple CPUs with multiple cores and highly parallel multithreaded GPU device. The investigation is done in three directions: GPU usage for 3D FDTD calculations, FVM method usage to implement efficient calculations of a very specific heat transferring problem, and development of special techniques for software for specific bacteria self organization problem when the results are sensitive to numerical methods, initial data and even computer round-off errors. All these directions are dedicated to create correct technological components that make a software implementation robust and efficient. The time prediction model for 3D FDTD calculations is proposed, which lets to evaluate the efficiency of different GPUs. A reasonable speedup with GPU comparing to CPU is obtained. For FVM implementation the OpenFOAM open source software is selected as a basis for implementation of calculations and a few algorithms and their modifications to solve efficiency issues are proposed. The FVM parallel solver is implemented and analyzed, it is adapted to heterogeneous cluster Vilkas. To create robust software for simulation of bacteria self organization mathematically robust methods are applied and results are analyzed, the algorithm is modified for parallel computations

Reactive Flows in Deformable, Complex Media

Many processes of highest actuality in the real life are described through systems of equations posed in complex domains. Of particular interest is the situation when the domain is changing in time, undergoing deformations that depend on the unknown quantities of the model. Such kind of problems are encountered as mathematical models in the subsurface, material science, or biological systems.The emerging mathematical models account for various processes at different scales, and the key issue is to integrate the domain deformation in the multi-scale context. The focus in this workshop was on novel techniques and ideas in the mathematical modelling, analysis, the numerical discretization and the upscaling of problems as described above