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

Solution strategies for nonlinear conservation laws

Nonlinear conservation laws form the basis for models for a wide range of physical phenomena. Finding an optimal strategy for solving these problems can be challenging, and a good strategy for one problem may fail spectacularly for others. As different problems have different challenging features, exploiting knowledge about the problem structure is a key factor in achieving an efficient solution strategy. Most strategies found in literature for solving nonlinear problems involve a linearization step, usually using Newton's method, which replaces the original nonlinear problem by an iteration process consisting of a series of linear problems. A large effort is then spent on finding a good strategy for solving these linear problems. This involves choosing suitable preconditioners and linear solvers. This approach is in many cases a good choice and a multitude of different methods have been developed. However, the linearization step to some degree involves a loss of information about the original problem. This is not necessarily critical, but in many cases the structure of the nonlinear problem can be exploited to a larger extent than what is possible when working solely on the linearized problem. This may involve knowledge about dominating physical processes and specifically on whether a process is near equilibrium. By using nonlinear preconditioning techniques developed in recent years, certain attractive features such as automatic localization of computations to parts of the problem domain with the highest degree of nonlinearities arise. In the present work, these methods are further refined to obtain a framework for nonlinear preconditioning that also takes into account equilibrium information. This framework is developed mainly in the context of porous media, but in a general manner, allowing for application to a wide range of problems. A scalability study shows that the method is scalable for challenging two-phase flow problems. It is also demonstrated for nonlinear elasticity problems. Some models arising from nonlinear conservation laws are best solved using completely different strategies than the approach outlined above. One such example can be found in the field of surface gravity waves. For special types of nonlinear waves, such as solitary waves and undular bores, the well-known Korteweg-de Vries (KdV) equation has been shown to be a suitable model. This equation has many interesting properties not typical of nonlinear equations which may be exploited in the solver, and strategies usually reserved to linear problems may be applied. In this work includes a comparative study of two discretization methods with highly different properties for this equation

Spectral and High Order Methods for Partial Differential Equations ICOSAHOM 2018

This open access book features a selection of high-quality papers from the presentations at the International Conference on Spectral and High-Order Methods 2018, offering an overview of the depth and breadth of the activities within this important research area. The carefully reviewed papers provide a snapshot of the state of the art, while the extensive bibliography helps initiate new research directions

Solution of the 2D Navier-Stokes equations by a new FE fractional step method.

In this work, a mathematical and numerical approach for the solution of the 2D Navier-Stokes equations for incompressible fluid flow problems is investigated. A new flux conservative technique for the solution of the elliptic part of the equations is formulated. In the new model, the non linear convective terms of the momentum equations are approximated by means of characteristics and the spatial approximations, of equal order, are obtained by polynomials of degree two. The advancing in time is afforded by a fractional step method combined with a suitable stabilization technique so that the Inf-Sup condition is respected. In order to keep down the computational cost, the algebraic systems are solved by an iterative solver (Bi-CGSTAB) preconditioned by means of Schwarz additive scalable preconditioners. The properties of the new method are verified carrying out several numerical tests. At first, some elliptic, parabolic and convective-diffusive problems are solved and discussed, then the results of some time dependent and stationary 2D Navier-Stokes problems (in particular the well known benchmark problem of the natural convection in a square cavity) are discussed and compared to those found in the literature. Another, potentially very important application of the numerical tools developed, regards the solution of 1D Shallow-Water equations. In fact the use of the fractional steps scheme for advancing in time and the finite elements (of different polynomial degrees) for the spatial approximation, makes the above mentioned approach computationally profitable and convenient for real applications. The efficiency and accuracy of the numerical model have been checked by solving a theoretical test. Finally, a brief description of the software suitably developed and used in the tests conclude the thesis