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The authors proposed a general way to find particular solutions for overdetermined systems of PDEs previously, where the number of equations is greater than the number of unknown functions. In this paper, we propose an algorithm for finding…

Symbolic Computation · Computer Science 2019-12-30 Maxim Zaytsev , V'yacheslav Akkerman

We show that a wide class of geometrically defined overdetermined semilinear partial differential equations may be explicitly prolonged to obtain closed systems. As a consequence, in the case of linear equations we extract sharp bounds on…

Differential Geometry · Mathematics 2008-11-26 Thomas Branson , Andreas Cap , Michael Eastwood , Rod Gover

It is shown how a complete set of hydrodynamic equations describing an unsteady three-dimensional viscous flow nearby a solid body, can be reduced to a closed system of surface equations using the method of dimension reduction of…

Fluid Dynamics · Physics 2014-08-04 Maxim Zaytsev , Vyacheslav Akkerman

Ordinary differential equations (ODEs) are the primary means to modelling dynamical systems in many natural and engineering sciences. The number of equations required to describe a system with high heterogeneity limits our capability of…

Mathematical Software · Computer Science 2017-07-17 Andrea Vandin

We consider reduction of dimension for nonlinear dynamical systems. We demonstrate that in some cases, one can reduce a nonlinear system of equations into a single equation for one of the state variables, and this can be useful for…

Chaotic Dynamics · Physics 2015-08-25 Heather A. Harrington , Robert A. Van Gorder

It has been recently pointed out that dynamical systems depending on future values of the unknowns may be useful in different areas of knowledge. We explore in this context the extension of the concept of order reduction that has been…

Computational Physics · Physics 2007-05-23 J. M. Aguirregabiria

Existing theoretical stabilization results for linear, hyperbolic multi-dimensional problems are extended to the discretized multi-dimensional problems. In contrast to existing theoretical and numerical analysis in the spatially…

Optimization and Control · Mathematics 2024-10-30 Michael Herty , Kai Hinzmann , Siegfried Müller , Ferdinand Thein

A method is presented that reduces the number of terms of systems of linear equations (algebraic, ordinary and partial differential equations). As a byproduct these systems have a tendency to become partially decoupled and are more likely…

Symbolic Computation · Computer Science 2007-05-23 Thomas Wolf

A new approach for obtaining the transformations of solutions of nonlinear ordinary differential equations representable as the compatibility condition of the overdetermined linear systems is proposed. The corresponding transformations of…

Mathematical Physics · Physics 2009-10-31 N. V. Ustinov

Experimental life sciences like biology or chemistry have seen in the recent decades an explosion of the data available from experiments. Laboratory instruments become more and more complex and report hundreds or thousands measurements for…

Machine Learning · Statistics 2014-03-13 C. O. S. Sorzano , J. Vargas , A. Pascual Montano

Consider briefly the equations of fluid dynamics-they describe the enormous wealth of detail in all the interacting physical elements of a fluid flow-whereas in applications we want to deal with a description of just that which is…

chao-dyn · Physics 2016-08-31 A. J. Roberts

We propose a novel framework for model-order reduction of hyperbolic differential equations. The approach combines a relaxation formulation of the hyperbolic equations with a discretization using shifted base functions. Model-order…

Numerical Analysis · Mathematics 2021-05-03 Sara Grundel , Michael Herty

We present a theory of compatible differential constraints of a hydrodynamic hierarchy of infinite-dimensional systems. It provides a convenient point of view for studying and formulating integrability properties and it reveals some hidden…

Exactly Solvable and Integrable Systems · Physics 2016-08-24 L. Martínez Alonso , A. B. Shabat

The reduction of nonholonomic systems is formulated in terms of Dirac reduction. An optimal reduction method for a class of nonholonomic systems is formulated. Several examples are studied in detail.

Differential Geometry · Mathematics 2011-10-17 Madeleine Jotz , Tudor Ratiu

The phenomenon of removable singularity is studied for overedetermined systems of differential equations. We show that the dimension of the characteristic variety plays a key role in the problem.

Analysis of PDEs · Mathematics 2011-09-07 Victor Palamodov

The numerical methods for differential equation solution allow obtaining a discrete field that converges towards the solution if the method is applied to the correct problem. Nevertheless, the numerical methods have the restricted class of…

Numerical Analysis · Mathematics 2023-07-03 Alexander Hvatov , Tatiana Tikhonova

An effective method to obtain exact analytical solutions of equations describing the coherent dynamics of multilevel systems is presented. The method is based on the usage of orthogonal polynomials, integral transforms and their discrete…

Classical Analysis and ODEs · Mathematics 2007-05-23 V. A. Savva , V. I. Zelenkov , A. S. Mazurenko

We study hyperbolic systems of one-dimensional partial differential equations under general, possibly non-local boundary conditions. A large class of evolution equations, either on individual 1-dimensional intervals or on general networks,…

Analysis of PDEs · Mathematics 2021-01-19 Marjeta Kramar Fijavž , Delio Mugnolo , Serge Nicaise

We study mathematically a system of partial differential equations arising in the modelling of an aging fluid, a particular class of non Newtonian fluids. We prove well-posedness of the equations in appropriate functional spaces and…

Analysis of PDEs · Mathematics 2012-03-06 David Benoit , Lingbing He , Claude Le Bris , Tony Lelièvre

Model reduction for fluid flow simulation continues to be of great interest across a number of scientific and engineering fields. Here, we explore the use of Neural Ordinary Differential Equations, a recently introduced family of…

Machine Learning · Computer Science 2021-04-30 Sourav Dutta , Peter Rivera-Casillas , Matthew W. Farthing
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