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An approach for providing quasi‐convexity to yield functions and a generalized implicit integration scheme for isotropic constitutive models based on 2 unknowns
Author(s) -
Panteghini Andrea,
Lagioia Rocco
Publication year - 2018
Publication title -
international journal for numerical and analytical methods in geomechanics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.419
H-Index - 91
eISSN - 1096-9853
pISSN - 0363-9061
DOI - 10.1002/nag.2767
Subject(s) - convexity , yield surface , constitutive equation , mathematics , isotropy , mathematical analysis , boundary value problem , boundary (topology) , yield (engineering) , finite element method , structural engineering , materials science , engineering , physics , quantum mechanics , financial economics , economics , metallurgy
Summary Yield and plastic potential surfaces are often affected by problems related to convexity. One such problem is encountered when the yield surface that bounds the elastic domain is itself convex; however, convexity is lost when the surface expands to pass through stress points outside the current elastic domain. In this paper, a technique is proposed, which effectively corrects this problem by providing linear homothetic expansion with respect to the centre of the yield surface. A very compact implicit integration scheme is also presented, which is of general applicability for isotropic constitutive models, provided that their yield and plastic potential functions are based on a separate mathematical definition of the meridional and deviatoric sections and that stress invariants are adopted as mechanical quantities. The elastic predictor‐plastic corrector algorithm is based on the solution of a system of 2 equations in 2 unknowns only. This further reduces to a single equation and unknown in the case of yield and plastic potential surfaces with a linear meridional section. The effectiveness of the proposed convexification technique and the efficiency and stability of the integration scheme are investigated by running numerical analyses of a notoriously demanding boundary value problem.