A computational framework for G/XFEM material nonlinear analysis. (December 2017)

• Record Type: Journal Article
• Authors: Monteiro, A.B.; Wolenski, A.R.V.; Barros, F.B.; Pitangueira, R.L.S.; Penna, S.S.
• Is Part Of: Advances in engineering software. Volume 114(2017)
• Page Start: 380
• Page End: 393
• Publication Date: 2017-12
• Subjects: G/XFEM -- Nonlinear analysis -- Constitutive models; Computer-aided engineering -- Periodicals; Engineering -- Computer programs -- Periodicals; Engineering -- Software -- Periodicals; Periodicals; 620.0028553
• DOI: 10.1016/j.advengsoft.2017.08.002
• Languages: English
• ISSNs: 0965-9978

Abstract

Highlights: An expansion of G/XFEM implementation to physically nonlinear analysis is presented. Combines different elements and analysis models with G/XFEM enrichment strategies. A unified framework for constitutive models is used with G/XFEM for the first time. G/XFEM approximation provides good concordance with experimental results. The enrichment strategy allows efficient description of the equilibrium path. Abstract: The Generalized/eXtended Finite Element Method (G/XFEM) has been developed with the purpose of overcoming some limitations inherent to the Finite Element Method (FEM). Different kinds of functions can be used to enrich the original FEM approximation, building a solution specially tailored to problem. Certain obstacles related to the nonlinear analysis can be mitigated with the use of such strategy and the damage and plasticity fronts can be precisely represented. A FEM computational environment has been previously enclosed the G/XFEM formulation to linear analysis with minimum impact in the code structure and with requirements for extensibility and robustness. An expansion of the G/XFEM implementation to physically nonlinear analysis under the approach of an Unified Framework for constitutive models based on elastic degradation is firstly presented here. The flexibility of the proposed framework is illustrated by several examples with different constitutive models, enrichment functions and analysis models.