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We present a new adaptive collocation scheme for solving partial differential equations based on Local Coupled Multiquadrics (LCMQs) within a covers-and-nodes framework. The method, referred to as the Adaptive Ch Method, automatically…

Numerical Analysis · Mathematics 2025-11-20 Ahmed E. Seleit

A space-time adaptive scheme is presented for solving advection equations in two space dimensions. The gradient-augmented level set method using a semi-Lagrangian formulation with backward time integration is coupled with a point value…

Computational Physics · Physics 2015-04-20 Dmitry Kolomenskiy , Jean-Christophe Nave , Kai Schneider

Polytopal methods provide a flexible framework for the numerical approximation of partial differential equations on general meshes. Their convergence analysis raises specific challenges due to their inherently non-conforming nature and, in…

Numerical Analysis · Mathematics 2026-05-25 Lourenço Beirão da Veiga , Daniele Antonio Di Pietro , Jérôme Droniou

This paper interprets the stabilized finite element method via residual minimization as a variational multiscale method. We approximate the solution to the partial differential equations using two discrete spaces that we build on a…

Computational Engineering, Finance, and Science · Computer Science 2023-05-23 Juan F. Giraldo , Victor M. Calo

We present a velocity-based moving mesh virtual element method for the numerical solution of PDEs involving moving boundaries. The virtual element method is used for computing both the mesh velocity and a conservative Arbitrary…

Numerical Analysis · Mathematics 2023-12-19 H. Wells , M. E. Hubbard , A. Cangiani

The difference variational bicomplex, which is the natural setting for systems of difference equations, is constructed and used to examine the geometric and algebraic properties of various systems. Exactness of the bicomplex gives a…

Mathematical Physics · Physics 2026-04-21 Linyu Peng , Peter E. Hydon

The theme of the present paper is numerical integration of $C^r$ functions using randomized methods. We consider variance reduction methods that consist in two steps. First the initial interval is partitioned into subintervals and the…

Numerical Analysis · Mathematics 2023-06-21 Leszek Plaskota , Paweł Przybyłowicz , Łukasz Stępień

Variational integrators are a special kind of geometric discretisation methods applicable to any system of differential equations that obeys a Lagrangian formulation. In this thesis, variational integrators are developed for several…

Numerical Analysis · Mathematics 2014-12-08 Michael Kraus

Although the isogeometric analysis has shown its great potential in achieving highly accurate numerical solutions of partial differential equations, its efficiency is the main factor making the method more competitive in practical…

Numerical Analysis · Mathematics 2025-01-10 Tao Wang , Xucheng Meng , Ran Zhang , Guanghui Hu

We introduce two hybridizable discontinuous Galerkin (HDG) methods for numerically solving the Monge-Ampere equation. The first HDG method is devised to solve the nonlinear elliptic Monge-Ampere equation by using Newton's method. The second…

Numerical Analysis · Mathematics 2023-06-09 Ngoc Cuong Nguyen , Jaime Peraire

A new approach is developed to integrate numerically the equations of motion for systems of interacting rigid polyatomic molecules. With the aid of a leapfrog framework, we directly involve principal angular velocities into the integration,…

Computational Physics · Physics 2007-05-23 Igor P. Omelyan

In many applications of practical interest, solutions of partial differential equation models arise as critical points of an underlying (energy) functional. If such solutions are saddle points, rather than being maxima or minima, then the…

Numerical Analysis · Mathematics 2020-09-07 Pascal Heid , Thomas P. Wihler

Stochastic partial differential equations can be used to model second order thermodynamical phase transitions, as well as a number of critical out-of-equilibrium phenomena. In (2+1) dimensions, many of these systems are conjectured (and…

Statistical Mechanics · Physics 2013-05-29 L. Moriconi , M. Moriconi

High-order meshes are crucial for achieving optimal convergence rates in curvilinear domains, preserving symmetry, and aligning with key flow features in moving mesh simulations, but their quality is challenging to control. In prior work,…

Numerical Analysis · Mathematics 2026-01-27 Ketan Mittal , Veselin Dobrev , Tzanio Kolev , Vladimir Tomov

An important ingredient of any moving-mesh method for fluid-structure interaction (FSI) problems is the mesh deformation technique (MDT) used to adapt the computational mesh in the moving fluid domain. An ideal technique is computationally…

Computational Engineering, Finance, and Science · Computer Science 2020-06-26 Alexander Shamanskiy , Bernd Simeon

We present a structure preserving discretization of the fundamental spacetime geometric structures of fluid mechanics in the Lagrangian description in 2D and 3D. Based on this, multisymplectic variational integrators are developed for…

Numerical Analysis · Mathematics 2021-02-23 François Demoures , François Gay-Balmaz

Astrophysical relativistic flow problems require high resolution three-dimensional numerical simulations. In this paper, we describe a new parallel three-dimensional code for simulations of special relativistic hydrodynamics (SRHD) using…

Astrophysics · Physics 2009-11-13 Peng Wang , Tom Abel , Weiqun Zhang

Formation control of autonomous agents can be seen as a physical system of individuals interacting with local potentials, and whose evolution can be described by a Lagrangian function. In this paper, we construct and implement forced…

Systems and Control · Electrical Eng. & Systems 2020-10-02 Leonardo Colombo , Hector Garcia de Marina

Time integration of ODEs or time-dependent PDEs with required resolution of the fastest time scales of the system, can be very costly if the system exhibits multiple time scales of different magnitudes. If the different time scales are…

Numerical Analysis · Mathematics 2012-05-15 Anders Logg

In recent years, Riemannian stochastic gradient descent (R-SGD), Riemannian stochastic variance reduction (R-SVRG) and Riemannian stochastic recursive gradient (R-SRG) have attracted considerable attention on Riemannian optimization. Under…

Optimization and Control · Mathematics 2021-10-18 Jiabao Yang