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The goal of this paper is to develop energy-preserving variational integrators for time-dependent mechanical systems with forcing. We first present the Lagrange-d'Alembert principle in the extended Lagrangian mechanics framework and derive…

Numerical Analysis · Mathematics 2018-05-23 Harsh Sharma , Mayuresh Patil , Craig Woolsey

We are able to derive the equations of motion for forced mechanical systems in a purely variational setting, both in the context of Lagrangian or Hamiltonian mechanics, by duplicating the variables of the system as introduced by Galley…

Mathematical Physics · Physics 2018-08-01 D. Martín de Diego , R. Sato Martín de Almagro

Discretizing variational principles, as opposed to discretizing differential equations, leads to discrete-time analogues of mechanics, and, systematically, to geometric numerical integrators. The phase space of such variational…

Mathematical Physics · Physics 2015-05-13 Charles Cuell , George W. Patrick

Finite element methods provide accurate and efficient methods for the numerical solution of partial differential equations by means of restricting variational problems to finite-dimensional approximating spaces. However, they do not…

Numerical Analysis · Mathematics 2025-06-24 Robert C. Kirby , John D. Stephens

Since their introduction, Lie group integrators have become a method of choice in many application areas. Various formulations of these integrators exist, and in this work we focus on Runge--Kutta--Munthe--Kaas methods. First, we briefly…

Numerical Analysis · Mathematics 2021-09-28 Elena Celledoni , Ergys Çokaj , Andrea Leone , Davide Murari , Brynjulf Owren

We show that Kahan's discretization of quadratic vector fields is equivalent to a Runge--Kutta method. When the vector field is Hamiltonian on either a symplectic vector space or a Poisson vector space with constant Poisson structure, the…

Numerical Analysis · Mathematics 2015-06-11 Elena Celledoni , Robert I McLachlan , Brynjulf Owren , G R W Quispel

Optimal control problems for underactuated mechanical systems can be seen as a higher-order variational problem subject to higher-order constraints (that is, when the Lagrangian function and the constraints depend on higher-order…

Mathematical Physics · Physics 2014-10-02 Leonardo Colombo , Fernando Jiménez , David Martín de Diego

Variational integrators are derived for structure-preserving simulation of stochastic Hamiltonian systems with a certain type of multiplicative noise arising in geometric mechanics. The derivation is based on a stochastic discrete…

Numerical Analysis · Mathematics 2019-07-31 Darryl D. Holm , Tomasz M. Tyranowski

In this technical note a general procedure is described to construct internally consistent splitting methods for the numerical solution of differential equations, starting from matching pairs of explicit and diagonally implicit Runge-Kutta…

Numerical Analysis · Mathematics 2017-07-17 Willem Hundsdorfer

Nonlinear parabolic equations are central to numerous applications in science and engineering, posing significant challenges for analytical solutions and necessitating efficient numerical methods. Exponential integrators have recently…

Numerical Analysis · Mathematics 2024-12-24 Trung Hau Hoang

Multiphysics systems are driven by multiple processes acting simultaneously, and their simulation leads to partitioned systems of differential equations. This paper studies the solution of partitioned systems of differential equations using…

Numerical Analysis · Mathematics 2019-12-04 Mahesh Narayanamurthi , Adrian Sandu

We consider the efficient numerical solution of coupled dynamical systems, consisting of a small nonlinear part and a large linear time invariant part, possibly stemming from spatial discretization of an underlying partial differential…

Numerical Analysis · Mathematics 2018-11-27 Herbert Egger , Vsevolod Shashkov , Kersten Schmidt

We discuss a recently proposed variational principle for deriving the variational equations associated to any Lagrangian system. The principle gives simultaneously the Lagrange and the variational equations of the system. We define a new…

Mathematical Physics · Physics 2016-08-16 H. N Núñez-Yépez , Joaquín Delgado , A. L. Salas-Brito

In this paper we investigate a variational discretization for the class of mechanical systems in presence of symmetries described by the action of a Lie group which reduces the phase space to a (non-trivial) principal bundle. By introducing…

Dynamical Systems · Mathematics 2018-07-17 Anthony Bloch , Leonardo Colombo , Fernando Jiménez

The work deals with two major topics concerning the numerical analysis of Runge-Kutta-like (RK-like) methods, namely their stability and order of convergence. RK-like methods differ from additive RK methods in that their coefficients are…

Numerical Analysis · Mathematics 2025-06-26 Thomas Izgin

In this paper we study a Hamiltonization procedure for mechanical systems with velocity-depending (nonholonomic) constraints. We first rewrite the nonholonomic equations of motion as Euler-Lagrange equations, with a Lagrangian that follows…

Mathematical Physics · Physics 2011-05-27 T. Mestdag , A. M. Bloch , O. E. Fernandez

Multirate integration is an increasingly relevant tool that enables scientists to simulate multiphysics systems. Existing multirate methods are designed for equations whose fast and slow variables can be linearly separated using additive or…

Numerical Analysis · Mathematics 2025-04-07 Tommaso Buvoli , Brian K. Tran , Ben S. Southworth

This work introduces a new class of Runge-Kutta methods for solving nonlinearly partitioned initial value problems. These new methods, named nonlinearly partitioned Runge-Kutta (NPRK), generalize existing additive and component-partitioned…

Numerical Analysis · Mathematics 2025-04-07 Tommaso Buvoli , Ben S. Southworth

We construct several variational integrators--integrators based on a discrete variational principle--for systems with Lagrangians of the form L = L_A + epsilon L_B, with epsilon << 1, where L_A describes an integrable system. These…

Astrophysics · Physics 2009-01-25 Will M. Farr

Most physical processes posses structural properties such as constant energies, volumes, and other invariants over time. When learning models of such dynamical systems, it is critical to respect these invariants to ensure accurate…

Machine Learning · Computer Science 2022-01-11 Katharina Ensinger , Friedrich Solowjow , Sebastian Ziesche , Michael Tiemann , Sebastian Trimpe