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Efficient and robust numerical treatment of a gradient-enhanced damage model at large deformations
- Source :
- International Journal for Numerical Methods in Engineering 123 (2022), Nr. 3, International Journal for Numerical Methods in Engineering
- Publication Year :
- 2022
- Publisher :
- Chichester [u.a.] : Wiley, 2022.
-
Abstract
- The modeling of damage processes in materials constitutes an ill-posed mathematical problem which manifests in mesh-dependent finite element results. The loss of ellipticity of the discrete system of equations is counteracted by regularization schemes of which the gradient enhancement of the strain energy density is often used. In this contribution, we present an extension of the efficient numerical treatment, which has been proposed by Junker et al. in 2019, to materials that are subjected to large deformations. Along with the model derivation, we present a technique for element erosion in the case of severely damaged materials. Efficiency and robustness of our approach is demonstrated by two numerical examples including snapback and springback phenomena. © 2021 The Authors. International Journal for Numerical Methods in Engineering published by John Wiley & Sons Ltd.
- Subjects :
- FOS: Computer and information sciences
Finite element method
Snapback
Element erosion technique
Numerical treatments
Finite difference method
Finite-difference methods
Dewey Decimal Classification::500 | Naturwissenschaften::510 | Mathematik
Deformation
Computational Engineering, Finance, and Science (cs.CE)
Element erosion
Erosion
International journals
Spring-back
Damage modelling
Larger deformations
Numerical methods
ddc:510
Computer Science - Computational Engineering, Finance, and Science
Gradient-enhanced damage
Strain energy
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- International Journal for Numerical Methods in Engineering 123 (2022), Nr. 3, International Journal for Numerical Methods in Engineering
- Accession number :
- edsair.doi.dedup.....2546951a08e04466c720dcd5a7289b7f