Skip to main content
Log in

Determination of an image point on a surface based on a \(\pi \) plane-based algorithm

  • Original Paper
  • Published:
Computational Mechanics Aims and scope Submit manuscript

Abstract

Constitutive models of particulate materials often rely on distances between the current stress state in stress space and various surfaces. Examples of these surfaces include the bounding surface and the dilatancy surface. This paper proposes a rigorous method for determination of distance to a surface in stress space. It starts by examining operations on stress variables defined in the \(\pi \) plane. Algorithms for determination of an image point on a surface are then presented as a function of the location of the current stress state with respect to the surface. For points within the surface, the bisection method is used; otherwise, the secant method is used. The paper shows that implementation of the proposed algorithm locates the image point on a surface in stress space with accuracy and rigor, providing an accurate measure of the distance to the surface that can be used in hardening or flow rules.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15

Similar content being viewed by others

References

  1. Andrianopoulos KI, Papadimitriou AG, Bouckovalas GD (2010) Explicit integration of bounding surface model for the analysis of earthquake soil liquefaction. Int J Numer Anal Methods Geomech 34:1586–1614. doi:10.1002/Nag.875

    Google Scholar 

  2. Chakraborty T, Salgado R, Loukidis D (2013) A two-surface plasticity model for clay. Comput Geotech 49:170–190. doi:10.1016/j.compgeo.2012.10.011

    Article  Google Scholar 

  3. Dafalias YF, Papadimitriou AG, Li XS (2004) Sand plasticity model accounting for inherent fabric anisotropy. J Eng Mech 130:1319

    Article  Google Scholar 

  4. Dafalias YF, Popov EP (1975) A model of nonlinearly hardening materials for complex loading. Acta Mech 21:173–192. doi:10.1007/BF01181053

    Article  MATH  Google Scholar 

  5. El-tawil S, Deierlein GG (2001) Nonlinear analysis of mixed steel-concrete frames. I: element formulation. J Struct Eng 127:647–655

    Article  Google Scholar 

  6. Loukidis D, Salgado R (2009) Modeling sand response using two-surface plasticity. Comput Geotech 36:166–186, 2008. doi:10.1016/J.Compgeo.02.009

    Google Scholar 

  7. Lubliner J (1990) Plasticity theory. Macmillan, New York

    MATH  Google Scholar 

  8. Manzari MT, Dafalias YF (1997) A critical state two-surface plasticity model for sands. Géotechnique 47:255–272

    Google Scholar 

  9. Sheng D, Augarde CE, Abbo AJ (2011) A fast algorithm for finding the first intersection with a non-convex yield surface. Comput Geotech 38:465–471. doi:10.1016/j.compgeo.2011.02.008

    Article  Google Scholar 

  10. Taiebat M, Dafalias YF (2008) SANISAND: simple anisotropic sand plasticity model. Int J Numer Anal Methods Geomech 32:915–948. doi:10.1002/Nag.651

    Google Scholar 

  11. Yang B-L, Dafalias YF, Herrmann LR (1985) A bounding surface plasticity model for concrete. J Eng Mech 111:359–380

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sang Inn Woo.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Woo, S.I., Salgado, R. Determination of an image point on a surface based on a \(\pi \) plane-based algorithm. Comput Mech 53, 1033–1046 (2014). https://doi.org/10.1007/s00466-013-0947-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00466-013-0947-3

Keywords

Navigation