Numerical Methods for Stiff Index-3 DAEs

Space semidiscretization of PDAEs, i.e. coupled systems of PDEs and algebraic equations, give raise to stiff DAEs and thus the standard theory of numerical methods for DAEs is not valid. As the study of numerical methods for stiff ODEs is done in terms of logarithmic norms, it seems natural to use also logarithmic norms for stiff DAEs. In this paper we show how the standard conditions imposed on the PDAE and the semidiscretized problem are formally the same if they are expressed in terms of logarithmic norms. To study the mathematical problem and their numerical approximations, this link between the standard conditions and logarithmic norms allow us to use for stiff DAEs techniques similar to the ones used for stiff ODEs. The analysis is done for problems which appear in the context of elastic multibody systems, but once the tools, i.e., logarithmic norms, are developed, they can also be used for the analysis of other PDAEs/DAEs.     

指数—2非线性广义系统的解及其稳定性

本文主要给出指数－2的非线性广义系统的可解性和零解的稳定性分析．     

Linear Index-1 DAEs: Regular and Singular Problems

Several features and interrelations of projector methods and reduction techniques for the analysis of linear time-varying differential-algebraic equations (DAEs) are addressed in this work. The application of both procedures to regular index-1 problems is reviewed, leading to some new results which extend the scope of reduction techniques through a projector approach. Certain singular points are well accommodated by reduction methods; the projector framework is adapted in this paper to handle (not necessarily isolated) singularities in an index-1 context. The inherent problem can be described in terms of a scalarly implicit ODE with continuous operators, in which the leading coefficient function does not depend on the choice of projectors. The nice properties of projectors concerning smoothness assumptions are carried over to the singular setting. In analytic problems, the kind of singularity arising in the scalarly implicit inherent ODE is also proved independent of the choice of projectors. The discussion is driven by a simple example coming from electrical circuit theory. Higher index cases and index transitions are the scope of future research.     

Stabilized multistep methods for index 2 Euler-Lagrange DAEs

We consider multistep discretizations, stabilized by -blocking, for Euler-Lagrange DAEs of index 2. Thus we may use nonstiff multistep methods with an appropriate stabilizing difference correction applied to the Lagrangian multiplier term. We show that orderp =k + 1 can be achieved for the differential variables with orderp =k for the Lagrangian multiplier fork-step difference corrected BDF methods as well as for low orderk-step Adams-Moulton methods. This approach is related to the recently proposed half-explicit Runge-Kutta methods.     

Partitioning strategies in Runge-Kutta type methods

The numerical solution of ode's suffers from stability constraints,if there are solution components with different time constants.Two recommended approaches in software packages to handle thesedifficulties (i) automatic switching between stiff and nonstiffmethods and (ii) the use of partitioned methods for a givensplitting into stiff and nonstiff subsystems, are presentedand investigated for Runge-Kutta type methods. A strategy fora dynamic partitioning in these methods is discussed. Numericalresults illustrate the efficiency of partitioning.     

Multiple invariants conserving Runge-Kutta type methods for Hamiltonian problems

In a recent series of papers, the class of energy-conserving Runge-Kutta methods named Hamiltonian BVMs (HBVMs) has been defined and studied. Such methods have been further generalized for the efficient solution of general conservative problems, thus providing the class of Line Integral Methods (LIMs). In this paper we derive a further extension, which we name Enhanced Line Integral Methods (ELIMs), more tailored for Hamiltonian problems, allowing for the conservation of multiple invariants of the continuous dynamical system. The analysis of the methods is fully carried out and some numerical tests are reported, in order to confirm the theoretical achievements.     

Enumeration results for Runge–Kutta methods for index 2 DAEs

Recursive formulas are presented that give the number of order conditions for single-step Runge–Kutta methods for index 2 DAEs.     

An efficient time-step-based self-adaptive algorithm for predictor-corrector methods of Runge-Kutta type

Finding an efficient implementation variant for the numerical solution of problems from computational science and engineering involves many implementation decisions that are strongly influenced by the specific hardware architecture. The complexity of these architectures makes it difficult to find the best implementation variant by manual tuning. For numerical solution methods from linear algebra, auto-tuning techniques based on a global search engine as they are used for ATLAS or FFTW can be used successfully. These techniques generate different implementation variants at installation time and select one of these implementation variants either at installation time or at runtime, before the computation starts. For some numerical methods, auto-tuning at installation time cannot be applied directly, since the best implementation variant may strongly depend on the specific numerical problem to be solved. An example is solution methods for initial value problems (IVPs) of ordinary differential equations (ODEs), where the coupling structure of the ODE system to be solved has a large influence on the efficient use of the memory hierarchy of the hardware architecture. In this context, it is important to use auto-tuning techniques at runtime, which is possible because of the time-stepping nature of ODE solvers.In this article, we present a sequential self-adaptive ODE solver that selects the best implementation variant from a candidate pool at runtime during the first time steps, i.e., the auto-tuning phase already contributes to the progress of the computation. The implementation variants differ in the loop structure and the data structures used to realize the numerical algorithm, a predictor-corrector (PC) iteration scheme with Runge-Kutta (RK) corrector considered here as an example. For those implementation variants in the candidate pool that use loop tiling to exploit the memory hierarchy of a given hardware platform we investigate the selection of tile sizes. The self-adaptive ODE solver combines empirical search with a model-based approach in order to reduce the search space of possible tile sizes. Runtime experiments demonstrate the efficiency of the self-adaptive solver for different IVPs across a range of problem sizes and on different hardware architectures.     

Parallel iterated methods based on multistep Runge-Kutta methods of Radau type

This paper investigates iterated Multistep Runge-Kutta methods of Radau type as a class of explicit methods suitable for parallel implementation. Using the idea of van der Houwen and Sommeijer [18], the method is designed in such a way that the right-hand side evaluations can be computed in parallel. We use stepsize control and variable order based on iterated approximation of the solution. A code is developed and its performance is compared with codes based on iterated Runge-Kutta methods of Gauss type and various Dormand and Prince pairs [15]. The accuracy of some of our methods are comparable with the PIRK10 methods of van der Houwen and Sommeijer [18], but require fewer processors. In addition at very stringent tolerances these new methods are competitive with RK78 pairs in a sequential implementation.     

Lie-Butcher theory for Runge-Kutta methods

Runge-Kutta methods are formulated via coordinate independent operations on manifolds. It is shown that there is an intimate connection between Lie series and Lie groups on one hand and Butcher's celebrated theory of order conditions on the other. In Butcher's theory the elementary differentials are represented as trees. In the present formulation they appear as commutators between vector fields. This leads to a theory for the order conditions, which can be developed in a completely coordinate free manner. Although this theory is developed in a language that is not widely used in applied mathematics, it is structurally simple. The recursion for the order conditions rests mainly on three lemmas, each with very short proofs. The techniques used in the analysis are prepared for studying RK-like methods on general Lie groups and homogeneous manifolds, but these themes are not studied in detail within the present paper.     

Pseudo-symplectic Runge-Kutta methods

Apart from specific methods amenable to specific problems, symplectic Runge-Kutta methods are necessarily implicit. The aim of this paper is to construct explicit Runge-Kutta methods which mimic symplectic ones as far as the linear growth of the global error is concerned. Such method of orderp have to bepseudo-symplectic of pseudosymplecticness order2p, i.e. to preserve the symplectic form to within ⊗(h ^2p )-terms. Pseudo-symplecticness conditions are then derived and the effective construction of methods discussed. Finally, the performances of the new methods are illustrated on several test problems.     

Reducible Runge-Kutta methods

Reducible Runge-Kutta methods are characterized by means of special matrices. Previous definitions of reducibility are incorporated. This characterization may be useful in the study of algebraic stability and in studies of existence and uniqueness.     

Canonical Runge-Kutta methods

Summary In the present note we provide a complete characterization of all Runge-Kutta methods which generate a canonical transformation if applied to a Hamiltonian system of ordinary differential equations.     

S-Stability properties for generalized Runge-Kutta methods

Summary A class of generalized Runge-Kutta methods is considered for the numerical integration of stiff systems of ordinary differential equations. These methods are characterized by the fact that the coefficients of the integration formulas are matrices depending on the Jacobian, or on an approximation to the Jacobian. Special attention is paid to stability aspects. In particular, theS-stability properties of the method are investigated. The concept of internal stability is discussed. Internal stability imposes conditions on intermediate results in the Runge-Kutta scheme. Some numerical examples are discussed.     

Equilibria of Runge-Kutta methods

Summary It is known that certain Runge-Kutta methods share the property that, in a constant-step implementation, if a solution trajectory converges to a bounded limit then it must be a fixed point of the underlying differential system. Such methods are calledregular. In the present paper we provide a recursive test to check whether given method is regular. Moreover, by examining solution trajectories of linear equations, we prove that the order of ans-stage regular method may not exceed 2[(s+2)/2] and that the maximal order of regular Runge-Kutta method with an irreducible stability function is 4.     

Order conditions for partitioned Runge-Kutta methods

We illustrate the use of the recent approach by P. Albrecht to the derivation of order conditions for partitioned Runge-Kutta methods for ordinary differential equations.     

Contractivity of Runge-Kutta methods

In this paper we present necessary and sufficient conditions for Runge-Kutta methods to be contractive. We consider not only unconditional contractivity for arbitrary dissipative initial value problems, but also conditional contractivity for initial value problems where the right hand side function satisfies a circle condition. Our results are relevant for arbitrary norms, in particular for the maximum norm.For contractive methods, we also focus on the question whether there exists a unique solution to the algebraic equations in each step. Further we show that contractive methods have a limited order of accuracy. Various optimal methods are presented, mainly of explicit type. We provide a numerical illustration to our theoretical results by applying the method of lines to a parabolic and a hyperbolic partial differential equation.Research supported by the Netherlands Organization for Scientific Research (N.W.O.) and the Royal Netherlands Academy of Arts and Sciences (K.N.A.W.)     

Runge-Kutta collocation methods for differential-algebraic equations of indices 2 and 3

Stiffly accurate Runge-Kutta collocation methods with explicit first stage are examined. The parameters of these methods are chosen so as to minimize the errors in the solutions to differential-algebraic equations of indices 2 and 3. This construction results in methods for solving such equations that are superior to the available Runge-Kutta methods.     

Convergence results for multistep Runge-Kutta methods

Summary. Recently Ch. Lubich proved convergence results for Runge-Kutta methods applied to stiff mechanical systems. The present paper discusses the new ideas necessary to extend these results to general linear methods, in particular BDF and multistep Runge-Kutta methods. Received August 9, 1993 / Revised version received May 3, 1994     

Runge-Kutta methods for jump-diffusion differential equations

In this paper we consider Runge-Kutta methods for jump-diffusion differential equations. We present a study of their mean-square convergence properties for problems with multiplicative noise. We are concerned with two classes of Runge-Kutta methods. First, we analyse schemes where the drift is approximated by a Runge-Kutta ansatz and the diffusion and jump part by a Maruyama term and second we discuss improved methods where mixed stochastic integrals are incorporated in the approximation of the next time step as well as the stage values of the Runge-Kutta ansatz for the drift. The second class of methods are specifically developed to improve the accuracy behaviour of problems with small noise. We present results showing when the implicit stochastic equations defining the stage values of the Runge-Kutta methods are uniquely solvable. Finally, simulation results illustrate the theoretical findings.