Skip to main content
Log in

Modeling the Response of Tensile Steel Bars by Means of Incremental Energy Minimization

  • Published:
Journal of Elasticity Aims and scope Submit manuscript

Abstract

A non-local variational model for the evolution of plastic deformation and fracture in tensile bars is proposed. The model is based on an energy functional, sum of an elastic bulk energy, a non-convex dissipative inelastic energy, and a quadratic non-local gradient term, as in (Del Piero et al. in J. Mech. Mater. Struct. 8(2–4):109–151, 2013). The non-local energy is enriched, by assuming a dependence on both the inelastic deformation and its gradient, in order to improve the description of fracture, and bars with varying cross-section are considered, to accurately reproduce the geometry of samples which are commonly used in tensile tests. The evolution of the deformation is described by a two-field incremental minimization problem, where the longitudinal displacement and the plastic part of the deformation are assumed as independent variables. The problem is discretized by finite elements, and the resulting sequence of constrained quadratic programming problems is solved numerically.

Different simulations are proposed, reproducing the results of experiments on smooth and notched bone-shaped steel samples. The numerical tests provide accurate response curves, and they capture the distinct phases of the evolution observed in experiments: from the initial yielding phase, in which inelastic deformations form, and propagate as slow plastic waves, to the final rupture, which constitutes the ending stage of a strain-localization process.

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

Similar content being viewed by others

Notes

  1. Incremental energy minimization represents a powerful tool, which was applied to fracture problems [2] and many other inelastic phenomena, as deeply discussed in [3].

  2. From here on, a subscript is used to indicate dependence on time.

  3. First-order energy minimization was used in [1] to determine the steepest descent configuration rates.

  4. The continuity of \(\dot{\gamma}'\), required to be (28) always applicable, was proved in [1].

  5. Proof. If \(\dot{\gamma}=0\) in some interval of (0,l), from (30)2, \(\dot{\sigma}\leq0\). But, integrating (30)3 over (0,l), we get \(l\dot{\sigma}\bar {\dot{\gamma}}=\int_{0}^{l} (\theta''\dot{\gamma}^{2}+\alpha\dot {\gamma }'^{2} )\,dx>0\), and thus \(\dot{\sigma}>0\), in contradiction with the above result. Thus \(\dot{\gamma}\) cannot be null in some subinterval of the bar. □

  6. Necessary and sufficient conditions for the eigenvalue non-negativeness are proposed in Sect. 3.4 of [1].

  7. It is the area of the triangle defined by θ″ in the interval 0<γ<γ 1 (see Fig. 6).

  8. In not-reported simulations, it appears in the middle, and in the left extremity.

  9. In particular, it is very similar to the Aifantis model [8], where the Laplacian of the cumulated plastic strain is introduced in the yield condition.

References

  1. Del Piero, G., Lancioni, G., March, R.: A diffuse cohesive energy approach to fracture and plasticity: the one-dimensional case. J. Mech. Mater. Struct. 8(2–4), 109–151 (2013)

    Article  Google Scholar 

  2. Del Piero, G., Truskinovsky, L.: Elastic bars with cohesive energy. Contin. Mech. Thermodyn. 21, 141–171 (2009)

    Article  MATH  MathSciNet  ADS  Google Scholar 

  3. Del Piero, G.: A variational approach to fracture and other inelastic phenomena. J. Elast. 112, 3–73 (2013)

    Article  MATH  Google Scholar 

  4. Yalcinkaya, T., Brekelmans, W.A.M., Geers, M.G.D.: Deformation patterning driven by rate dependent non-convex strain gradient plasticity. J. Mech. Phys. Solids 59, 1–17 (2011)

    Article  MATH  MathSciNet  ADS  Google Scholar 

  5. Yalcinkaya, T., Brekelmans, W.A.M., Geers, M.G.D.: Non-convex rate dependent strain gradient crystal plasticity and deformation patterning. Int. J. Solids Struct. 49, 2625–2636 (2012)

    Article  Google Scholar 

  6. Yalcinkaya, T.: Multi-scale modeling of microstructure evolution induced anysotropy in metals. Key Eng. Mater. 554–557, 2388–2399 (2013)

    Article  Google Scholar 

  7. Bažant, Z.P., Jirásek, M.: Nonlocal integral formulations of plasticity and damage: survey of progress. J. Eng. Mech. 128, 1119–1149 (2002)

    Article  Google Scholar 

  8. Aifantis, E.C.: On the microstructural origin of certain inelastic models. J. Eng. Mater. Technol. 106, 326–330 (1984)

    Article  Google Scholar 

  9. Jirásek, M., Rolshoven, S.: Localization properties of strain-softening gradient plasticity models. Part I. Strain-gradient theories. Int. J. Solids Struct. 46, 2225–2238 (2009)

    Article  MATH  Google Scholar 

  10. Jirásek, M., Rolshoven, S.: Localization properties of strain-softening gradient plasticity models. Part II. Theories with gradients of internal variables. Int. J. Solids Struct. 46, 2239–2254 (2009)

    Article  MATH  Google Scholar 

  11. de Borst, R., Pamin, J., Peerlings, R.H.J., Sluys, L.J.: On gradient-enhanced damage and plasticity models for failure in quasi-brittle and frictional materials. Comput. Mech. 17, 130–141 (1995)

    Article  MATH  Google Scholar 

  12. Bourdin, B., Francfort, G., Marigo, J.J.: The variational approach to fracture. J. Elast. 91(1–3), 1–148 (2008)

    MathSciNet  Google Scholar 

  13. Freddi, F., Royer Carfagni, G.: Regularized variational theories of fracture: a unified approach. J. Mech. Phys. Solids 58, 1154–1174 (2010)

    Article  MATH  MathSciNet  ADS  Google Scholar 

  14. Pham, K., Amor, H., Marigo, J.J., Maurini, C.: Gradient damage models and their use to approximate brittle fracture. Int. J. Damage Mech. 20, 618–652 (2011)

    Article  Google Scholar 

  15. Bourdin, B., Francfort, G., Marigo, J.J.: Numerical experiments in revisited brittle fracture. J. Mech. Phys. Solids 48, 797–826 (2000)

    Article  MATH  MathSciNet  ADS  Google Scholar 

  16. Del Piero, G., Lancioni, G., March, R.: A variational model for fracture mechanics: numerical experiments. J. Mech. Phys. Solids 55, 2513–2537 (2007)

    Article  MATH  MathSciNet  ADS  Google Scholar 

  17. Amor, H., Marigo, J.J., Maurini, C.: Regularized formulation of the variational brittle fracture with unilateral contact: numerical experiments. J. Mech. Phys. Solids 57, 1209–1229 (2009)

    Article  MATH  ADS  Google Scholar 

  18. Lancioni, G., Royer-Carfagni, G.: The variational approach to fracture mechanics: a practical application to the French Panthéon in Paris. J. Elast. 95, 1–30 (2009)

    Article  MATH  MathSciNet  Google Scholar 

  19. Nucedal, J., Wright, S.: Numerical Optimization, 2nd edn. Springer, Berlin (2006)

    Google Scholar 

  20. Rice, J.R.: The initiation and growth of shear bands. In: Palmer, A.C. (ed.) Plasticity and Soil Mechanics, pp. 263–274. Cambridge University Press, Cambridge (1973)

    Google Scholar 

  21. Sun, H.B., Yoshida, F., Ma, X., Kamei, T., Ohmori, M.: Finite element simulation on the propagation of Lüders band and effect of stress concentration. Mater. Lett. 57, 3206–3210 (2003)

    Article  Google Scholar 

  22. Froli, M., Royer-Carfagni, G.: Discontinous deformation of tensile steel bars: experimental results. J. Eng. Mech. 125, 1243–1250 (1999)

    Article  Google Scholar 

  23. Froli, M., Royer-Carfagni, G.: A mechanical model for the elastic±plastic behavior of metallic bars. Int. J. Solids Struct. 37, 3901–3918 (2000)

    Article  MATH  Google Scholar 

  24. Devillers-Guerville, L., Besson, J., Pineau, A.: Notch fracture toughness of a cast duplex stainless steel: modelling of experimental scatter and size effect. Nucl. Eng. Des. 168, 211–225 (1997)

    Article  Google Scholar 

  25. Decamp, K., Bauvineau, L., Besson, J., Pineau, A.: Size and geometry effects on ductile rupture of notched bars in a CMn steel: experiments and modelling. Int. J. Fract. 88, 1–18 (1997)

    Article  Google Scholar 

  26. Lancioni, G., Yalcinkaya, T.: Plastic slip patterns through rate-independent and rate-dependent plasticity. Key Eng. Mater. 611–612, 1777–1786 (2014)

    Article  Google Scholar 

  27. Alessi, R., Marigo, J.-J., Vidoli, S.: Gradient damage models coupled with plasticity and nucleation of cohesive cracks. Arch. Rational Mech. Anal. 214, 575–615 (2014)

    Article  MATH  MathSciNet  ADS  Google Scholar 

  28. Alessi, R., Marigo, J.-J., Vidoli, S.: Gradient damage models coupled with plasticity: variational formulation and main properties. Mech. Mater. 80, 351–367 (2015)

    Article  Google Scholar 

  29. Gill, P.E., Murray, W., Wright, M.H.: Practical Optimization. Academic Press, San Diego (1981)

    MATH  Google Scholar 

  30. Polak, E.: Computational Methods in Optimization. Academic Press, San Diego (1971)

    Google Scholar 

  31. Nadai, A.: Theory of Flow and Fracture of Solids. McGraw-Hill, New York (1950)

    Google Scholar 

  32. Miklowitz, J.: The influence of the dimensional factors on the mode of yielding and fracture in medium-carbon steel. II. The size of the round tensile bar. Proc. J. Appl. Mech 17, 159–168 (1950)

    Google Scholar 

  33. Yuan, H., Chen, J., Krompholz, K., Wittmann, F.H.: Investigations of size effects in tensile tests based on a nonlocal micro-mechanical damage model. Comput. Mater. Sci. 26, 230–243 (2003)

    Article  Google Scholar 

  34. Yuan, H., Chen, J.: Comparison of computational predictions of material failure using nonlocal damage models. Int. J. Solids Struct. 41, 1021–1037 (2004)

    Article  MATH  Google Scholar 

  35. Gurson, A.L.: Continuum theory of ductile rupture by void nucleation and growth. Part I. Yield criteria and flow rules for porous ductile media. J. Eng. Mater. Technol. 99, 2–15 (1977)

    Article  Google Scholar 

  36. Tvergaard, V., Needleman, A.: Analysis of the cup-cone fracture in a round tensile bar. Acta Metall. 32, 157–169 (1984)

    Article  Google Scholar 

  37. Chen, J., Yuan, H.: A micro-mechanical damage model based on gradient plasticity: algorithms and applications. Int. J. Numer. Methods Eng. 54, 399–420 (2002)

    Article  MATH  Google Scholar 

Download references

Acknowledgements

The author gratefully acknowledges the valuable comments and suggestions of Prof. Gianpietro Del Piero.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Giovanni Lancioni.

Additional information

This research was partially supported by the Italian Ministry of Education, Universities and Research (MIUR) by the PRIN funded Program “Dynamics, stability and control of flexible structures”, 2010/11N. 2010MBJK5B.

Appendices

Appendix A: Finite Elements Discretization

In the finite element discretization, two-points linear elements are considered for γ, and three-points quadratic elements for u. This allows to approximate both u′ and γ with linear functions, within each element. In the arbitrary e-th element (x e ,x e+1), the approximated solution is

$$\begin{aligned} u_t(x)=\boldsymbol {\varphi}^e(x)\cdot{ \mathbf{u}}^e_t,\qquad\gamma _t(x)=\boldsymbol { \psi}^e(x)\cdot{ \boldsymbol {\gamma}}^e_t, \end{aligned}$$
(56)

where \(\mathbf{u}^{e}_{t}=[u_{t}(x_{e}),u_{t}((x_{e}+x_{e+1})/2),u_{t}(x_{e+1})]^{T}\), and \(\boldsymbol {\gamma}^{e}_{t}=[\gamma_{t}(x_{e}),\gamma_{t}(x_{e+1})]^{T}\) are the nodal vectors of displacement and inelastic deformation, respectively, and \(\boldsymbol {\varphi}^{e}(x)=[\varphi^{e}_{1}(x),\varphi^{e}_{2}(x),\varphi ^{e}_{3}(x)]^{T}\) and \(\boldsymbol {\psi}^{e}(x)=[\psi^{e}_{1}(x),\psi^{e}_{2}(x)]^{T}\) are the vectors of the quadratic and linear shape functions, respectively. Substituting (56) in the functional (21), restricted to the e-th element, we obtain the discrete quadratic form

$$\begin{aligned} \mathcal{F}^e\bigl(u_t, \gamma_t; \dot{\mathbf{u}}_t^e, \dot{\boldsymbol { \gamma }}_t^e\bigr)=\frac{1}{2}\tau^2 \left [ \begin{array}{c@{\quad }c} {\mathbf{H}}^e_{11} & \mathbf{H}^e_{12} \\ \mathbf{H}_{12}^{eT} & \mathbf{H}^e_{22}(\gamma_t) \end{array} \right ]\left [ \begin{array}{c} \dot{\mathbf{u}}^e \\ \dot{\boldsymbol {\gamma}}^e \end{array} \right ]\cdot \left [ \begin{array}{c} \dot{\mathbf{u}}^e \\ \dot{\boldsymbol {\gamma}}^e \end{array} \right ]+ \tau \left [ \begin{array}{c} {\mathbf{f}}_1^e \\ \mathbf{f}_2^e(u_t,\gamma_t) \end{array} \right ]\cdot \left [ \begin{array}{c} \dot{\mathbf{u}}^e \\ \dot{\boldsymbol {\gamma}}^e \end{array} \right ], \end{aligned}$$
(57)

where \(u_{t}=\boldsymbol {\varphi}^{e}\cdot{\mathbf{u}}_{t}^{e}\) and \(\gamma =\boldsymbol {\psi}^{e}\cdot{ \boldsymbol {\gamma}}_{t}^{e}\), and

$$\begin{aligned} &\mathbf{H}^e_{11}=\int_{x_e}^{x_{e+1}}AE \boldsymbol {\varphi}'^e\otimes{ \boldsymbol {\varphi}}'^e \,dx,\qquad \mathbf{H}^e_{12}={\mathbf{H}^e_{21}}^T=- \int_{x_e}^{x_{e+1}}AE\boldsymbol {\varphi}'^e \otimes{ \boldsymbol {\psi}}^e\,dx, \\ &\begin{aligned}[b] {\mathbf{H}}^e_{22}(\gamma_t)&= \displaystyle \int_{x_e}^{x_{e+1}}A \biggl[ \biggl(E+\theta''+ \frac{1}{2}\alpha_t'' \gamma_t'^2 \biggr)\boldsymbol {\psi }^e\otimes{ \boldsymbol {\psi}}^e\\ &\quad {}+ \displaystyle \alpha_t\boldsymbol {\psi}'^e\otimes{ \boldsymbol { \psi}}'^e+ 2\alpha_t' \gamma_t'\,\mathrm{sym}\bigl(\boldsymbol {\psi}^e \otimes{ \boldsymbol {\psi }}'^e\bigr) \biggr]\,dx, \end{aligned} \\ &{\mathbf{f}}^e_1=\int _{x_e}^{x_{e+1}}EA\boldsymbol {\varphi }'^e \,dx, \\ &\mathbf{f}^e_2(u_t, \gamma_t)=\int_{x_e}^{x_{e+1}}A \biggl[ \biggl( \theta _t'-E\bigl(u_t'- \gamma_t\bigr)+\frac{1}{2}\alpha_t' \gamma_t'^2 \biggr)\boldsymbol {\psi }^e+\alpha_t\gamma_t'{\boldsymbol {\psi}}'^e \biggr]\,dx. \end{aligned}$$
(58)

Integrals are evaluated by means of two-point Gaussian quadrature. The dimension of the discretized problem is 3n e +2, with n e the number of elements.

Appendix B: Coefficients c h and c s of Formula (46)

Case θ″>0.

$$\begin{aligned} c_h(kl,hl)=\frac{(kl)^2}{(kl)^2+(hl)^2 (1-\frac{2}{kl}\tanh \frac {kl}{2} )},\qquad c_s(kl,hl)= \frac{(kl)^2}{(kl)^2+(hl)^2}. \end{aligned}$$
(59)

Case θ″=0.

$$\begin{aligned} c_h(kl,hl)=\frac{12}{12+(hl)^2},\qquad c_s(kl,hl)=0. \end{aligned}$$
(60)

Case θ″<0.

$$\begin{aligned} \begin{aligned}[c] &c_h(kl,hl)= \left \{ \begin{array}{l@{\quad }l} \frac{(kl)^2}{(kl)^2-(hl)^2 (1-\frac{2}{kl}\tan \frac {kl}{2} )}, & \mbox{if }kl\leq2\pi; \\ \frac{(kl)^2}{(kl)^2-\frac{2\pi}{kl}(hl)^2}, & \mbox{if }kl> 2\pi; \end{array} \right . \\ &c_s(kl,hl)= \left \{ \begin{array}{l@{\quad }l} \frac{(kl)^2}{(kl)^2-(hl)^2},& \mbox{if } kl\leq\pi; \\ \frac{(kl)^2}{(kl)^2-\frac{\pi}{kl}(hl)^2}, & \mbox{if }kl> \pi. \end{array} \right . \end{aligned} \end{aligned}$$
(61)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lancioni, G. Modeling the Response of Tensile Steel Bars by Means of Incremental Energy Minimization. J Elast 121, 25–54 (2015). https://doi.org/10.1007/s10659-015-9515-8

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10659-015-9515-8

Keywords

Mathematics Subject Classification (2010)

Navigation