Petrov–Galerkin_method

Petrov–Galerkin method

Petrov–Galerkin method

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The Petrov–Galerkin method is a mathematical method used to approximate solutions of partial differential equations which contain terms with odd order and where the test function and solution function belong to different function spaces.[1] It can be viewed as an extension of Bubnov-Galerkin method where the bases of test functions and solution functions are the same. In an operator formulation of the differential equation, Petrov–Galerkin method can be viewed as applying a projection that is not necessarily orthogonal, in contrast to Bubnov-Galerkin method.

It is named after the Soviet scientists Georgy I. Petrov and Boris G. Galerkin.[2]

Introduction with an abstract problem

Petrov-Galerkin's method is a natural extension of Galerkin method and can be similarly introduced as follows.

A problem in weak formulation

Let us consider an abstract problem posed as a weak formulation on a pair of Hilbert spaces and , namely,

find such that for all .

Here, is a bilinear form and is a bounded linear functional on .

Petrov-Galerkin dimension reduction

Choose subspaces of dimension n and of dimension m and solve the projected problem:

Find such that for all .

We notice that the equation has remained unchanged and only the spaces have changed. Reducing the problem to a finite-dimensional vector subspace allows us to numerically compute as a finite linear combination of the basis vectors in .

Petrov-Galerkin generalized orthogonality

The key property of the Petrov-Galerkin approach is that the error is in some sense "orthogonal" to the chosen subspaces. Since , we can use as a test vector in the original equation. Subtracting the two, we get the relation for the error, which is the error between the solution of the original problem, , and the solution of the Galerkin equation, , as follows

for all .

Matrix form

Since the aim of the approximation is producing a linear system of equations, we build its matrix form, which can be used to compute the solution algorithmically.

Let be a basis for and be a basis for . Then, it is sufficient to use these in turn for testing the Galerkin equation, i.e.: find such that

We expand with respect to the solution basis, and insert it into the equation above, to obtain

This previous equation is actually a linear system of equations , where

Symmetry of the matrix

Due to the definition of the matrix entries, the matrix is symmetric if , the bilinear form is symmetric, , , and for all In contrast to the case of Bubnov-Galerkin method, the system matrix is not even square, if

See also


Notes

  1. J. N. Reddy: An introduction to the finite element method, 2006, Mcgraw–Hill
  2. "Georgii Ivanovich Petrov (on his 100th birthday)", Fluid Dynamics, May 2012, Volume 47, Issue 3, pp 289-291, DOI 10.1134/S0015462812030015



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