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Estimation of convergence of spectral element method in CAE Fidesys based on exact solution of the Lame problem for elastoplastic materials using an automated regression testing system

https://doi.org/10.22405/2226-8383-2022-23-4-272-284

Abstract

This paper considers convergence estimation of the spectral element method implemented in CAE Fidesys. It was based on exact analytical solutions of the Lame problems in small deformations in the elastic and elastic-perfectly plastic obeying Huber-von Mises yield criterion
formulations. Due to the symmetry, we consider quarters of the models. Numerical results were obtained in the CAE Fidesys strength analysis system using the finite element method for the first and second orders and the spectral element method for the third to ninth orders. Based on the results obtained, an analysis was carried out to determine the nature of the decrease in the errors of the CAE Fidesys spectral element method with an increase in the order of the
elements. The study was conducted using a specialized automated testing system. The results of the work can be useful in making a decision on the use of the spectral element method in industrial calculations.

About the Authors

Vladimir Anatol’evich Levin
Lomonosov Moscow State University
Russian Federation

doctor of physical and mathematical sciences, professor



Viktor Vyacheslavovich Kozlov
Tula State University (Tula); Lomonosov Moscow State University
Russian Federation

candidate of physical and mathematical sciences



Elena Dmitrievna Komolova
Lomonosov Moscow State University; Fidesys LLC
Russian Federation

candidate of physical and mathematical sciences



Alexandra Vyacheslavovna Filatova
Fidesis LLC
Russian Federation


Mikhail Aleksandrovich Kartsev
Tula State University
Russian Federation

postgraduate student



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Review

For citations:


Levin V.A., Kozlov V.V., Komolova E.D., Filatova A.V., Kartsev M.A. Estimation of convergence of spectral element method in CAE Fidesys based on exact solution of the Lame problem for elastoplastic materials using an automated regression testing system. Chebyshevskii Sbornik. 2022;23(4):272-284. (In Russ.) https://doi.org/10.22405/2226-8383-2022-23-4-272-284

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