From a Geometrical Interpretation of Bramble-Hilbert Lemma to a Probability Distribution for Finite Element Accuracy

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Finite Difference Methods. Theory and Applications (FDM 2018)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11386))

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Abstract

The aim of this paper is to provide new perspectives on relative finite element accuracy which is usually based on the asymptotic speed of convergence comparison when the mesh size h goes to zero. Starting from a geometrical reading of the error estimate due to Bramble-Hilbert lemma, we derive two probability distributions that estimate the relative accuracy, considered as a random variable, between two Lagrange finite elements \(P_k\) and \(P_m\), (\(k < m\)). We establish mathematical properties of these probabilistic distributions and we get new insights which, among others, show that \(P_k\) or \(P_m\) is more likely accurate than the other, depending on the value of the mesh size h.

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References

  1. Assous, F., Chaskalovic, J.: Data mining techniques for scientific computing: Application to asymptotic paraxial approximations to model ultra-relativistic particles. J. Comput. Phys. 230, 4811–4827 (2011)

    Article  MathSciNet  Google Scholar 

  2. Assous, F., Chaskalovic, J.: Error estimate evaluation in numerical approximations of partial differential equations: a pilot study using data mining methods. C. R. Mec. 341, 304–313 (2013)

    Article  Google Scholar 

  3. Assous, F., Chaskalovic, J.: Indeterminate constants in numerical approximations of PDE’s: a pilot study using data mining techniques. J. Comput. Appl. Math. 270, 462–470 (2014)

    Article  MathSciNet  Google Scholar 

  4. Chaskalovic, J.: Mathematical and Numerical Methods for Partial Differential Equations. ME. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-03563-5

    Book  MATH  Google Scholar 

  5. Ciarlet, P.G.: Basic error estimates for elliptic problems. In: Ciarlet, P.G., Lions, J.L. (eds.) Handbook of Numerical Analysis, North Holland, vol. 2 (1991)

    Google Scholar 

  6. Raviart P.A., Thomas, J.M.: Introduction à l’analyse numérique des équations aux dérivées partielles, Masson (1982)

    Google Scholar 

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Correspondence to Joel Chaskalovic .

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Chaskalovic, J., Assous, F. (2019). From a Geometrical Interpretation of Bramble-Hilbert Lemma to a Probability Distribution for Finite Element Accuracy. In: Dimov, I., Faragó, I., Vulkov, L. (eds) Finite Difference Methods. Theory and Applications. FDM 2018. Lecture Notes in Computer Science(), vol 11386. Springer, Cham. https://doi.org/10.1007/978-3-030-11539-5_1

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  • DOI: https://doi.org/10.1007/978-3-030-11539-5_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-11538-8

  • Online ISBN: 978-3-030-11539-5

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