Graduate Residual of PDEs as convergence criteria of numerical solution

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SUMMARY

The discussion centers on the use of the residual of a discretized Partial Differential Equation (PDE) as a convergence criterion for numerical solutions. It establishes that while iterative solvers like Krylov subspace methods, specifically GMRES, utilize the Euclidean norm of the residual to monitor convergence, this residual does not provide a direct estimate of the error between the discretized and original PDE solutions. Instead, a mesh refinement study is necessary to assess the error accurately. The relationship between the residual and discretization error is influenced by the specific PDE and numerical method employed, as detailed in Babuska and Strouboulis' work on the finite element method.

PREREQUISITES
  • Understanding of Partial Differential Equations (PDEs)
  • Familiarity with numerical methods for PDEs, particularly finite element methods
  • Knowledge of Krylov subspace methods, specifically GMRES
  • Concept of mesh refinement studies in numerical analysis
NEXT STEPS
  • Study the principles of mesh refinement and its impact on numerical solution accuracy
  • Explore the relationship between residual norms and discretization errors in PDEs
  • Read "The Finite Element Method and its Reliability" by Babuska and Strouboulis for in-depth understanding
  • Investigate the application of different iterative solvers in numerical PDE analysis
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Researchers, numerical analysts, and engineers involved in computational fluid dynamics, finite element analysis, and anyone seeking to improve the accuracy of numerical solutions to PDEs.

feynman1
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Use a numerical method to solve a PDE f[u(x),u'(x),...]=0, where f is an operator, e.g. u'(x)+u(x)=0, and obtain a numerical solution v(x). Define f[v(x),v'(x),...] as the residual of the original PDE. Is this residual of the PDE widely used as the convergence criteria of the numerical solution v(x)?
 
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No
 
The numerical method either forces the residuals to be zero at the points where the approximate solution is obtained, or forces the residual to be orthogonal to some finite space of basis functions.

In neither case is it used to estimate the error.
 
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pasmith said:
The numerical method either forces the residuals to be zero at the points where the approximate solution is obtained, or forces the residual to be orthogonal to some finite space of basis functions.

In neither case is it used to estimate the error.
then why not a good estimate of the error?
 
feynman1 said:
Define f[v(x),v'(x),...] as the residual of the original PDE
You do not have the residual of the original PDE. What you do have is the residual of the discretized PDE.

Now, if you use iterative solvers like Krylov subspace methods (for instance GMRES https://en.wikipedia.org/wiki/Generalized_minimal_residual_method) then the Euclidian norm of the residual at iteration i can be used to monitor the convergence towards the numerical solution in this discretized subspace. These residuals are reported by numerical PDE solver software like Comsol or OpenFOAM.

However, if your residual is zero, it only means that you have found the solution of the discretized PDE to within machine precision. You still do not know how large the error is between your discretized solution and the solution of the original PDE. For this you then need to do a mesh refinement study. For example you can take your exact solution of the discretized problem on mesh N and project it onto a larger/finer mesh 2N and recompute the residual. The residual will now not be zero anymore and you have to re-iterate until convergence. The hope is that if you make your mesh larger and larger, these residual changes on the new mesh will become smaller and your discrete solution will converge to the continuous solution.

feynman1 said:
then why not a good estimate of the error?
In practice, people look at residuals of iterative methods and associate this with 'the error'. There are relationships (from functional analysis) between the norm of the residual and the discretization error, and the actual continuous solution of the original PDE. They depend on the PDE (+boundary conditions) and the numerical method used and they give you information about the order of the convergence (next to the proof that the numerical method actually converges).
You can find this kind of detailed information for instance in the book of Babuska and Strouboulis 'The Finite Element Method and its Reliability' .
 
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bigfooted said:
You do not have the residual of the original PDE. What you do have is the residual of the discretized PDE.
Thanks, but why don't we have the residual of the original PDE? Unable to take derivatives?
 
feynman1 said:
Thanks, but why don't we have the residual of the original PDE? Unable to take derivatives?
In the discretized problem you are working with a finite number of points. In your original problem ##u'(x) + u(x)## you could take a continuous solution ##f(x)## and substitute it into the ODE and determine a residual. But as soon as you construct some kind of solution vector ##x=(x_1,x_2,...,x_N)## then you are working in a discrete subspace, not in the continuous function space. For instance for first order methods, you assume that the solution is actually in a Hilbert Space ##H_1## of once locally differentiable functions. If your are solving a shock wave problem with the Euler equations, there is a discontinuity at the location of the shock. The solution of this problem is not in ##H_1##, at least not in the neighborhood of the discontinuity.

So these discrete problems have analytical solutions that are different from the continuous solution and you only ever get an approximation of the continuous solution unless your solution can be exactly represented by the discrete problem (when the solution is linear and the discretization is also linear for example).
 
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Define f[v(x),v'(x),...] as the residual of the discretized PDE. Is this residual of the PDE widely used as the convergence criteria of the numerical solution v(x)? How small should it be for an oscillatory solution?
 
feynman1 said:
Define f[v(x),v'(x),...] as the residual of the discretized PDE. Is this residual of the PDE widely used as the convergence criteria of the numerical solution v(x)? How small should it be for an oscillatory solution?
?
 
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how large is the residual of a discrete solution of a PDE from 0 in order of magnitude?
 

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