Parameter determination of Chaboche kinematic hardening model using a multi objective Genetic Algorithm

Mahmoudi, A.H.; Pezeshki, Mahmoud; Badnava, H.

doi:10.1016/j.commatsci.2010.11.010

Cited by 92 publications

(55 citation statements)

References 17 publications

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“…This model is based on a decomposition of the non-linear kinematic hardening rule proposed by Armstrong and Frederik (1966). Chaboche decomposed a stable hysteresis curve in several parts, and it was observed that increasing the material parameters of the hardening rule by the superposition of backstresses, a more accurate model was obtained [49,50]. However, in this work only one backstress has been considered in the model definition because of many FE codes have only implemented the model with one backstress.…”

Section: Parameter Identification Of Mixed Chaboche and Lemaitre Hardmentioning

confidence: 89%

Comparison of the hardening behaviour of different steel families: From mild and stainless steel to advanced high strength steels

Silvestre

Mendiguren

Galdos

et al. 2015

International Journal of Mechanical Sciences

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Section: Parameter Identification Of Mixed Chaboche and Lemaitre Hardmentioning

confidence: 89%

Comparison of the hardening behaviour of different steel families: From mild and stainless steel to advanced high strength steels

Silvestre

Mendiguren

Galdos

et al. 2015

International Journal of Mechanical Sciences

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“…The possibility of generating global optimisation techniques, such as implemented in [24,25], will also be investigated. However, to ensure that the strain-rate effect is captured accurately, it is imperative that any optimisation technique does not remove the physical basis of the current set of material parameters.…”

Section: Discussionmentioning

confidence: 99%

A Unified Viscoplastic Model for High Temperature Low Cycle Fatigue of Service-Aged P91 Steel

Barrett

Farragher

Hyde

et al. 2014

Journal of Pressure Vessel Technology

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The finite element (FE) implementation of a hyperbolic sine unified cyclic viscoplasticity model is presented. The hyperbolic sine flow rule facilitates the identification of strain-rate independent material parameters for high temperature applications. This is important for the thermo-mechanical fatigue of power plant where a significant stress range is experienced during operational cycles and at stress concentration features, such as welds and branch connections. The material model is successfully applied to the characterisation of the high temperature low cycle fatigue behaviour of a service-aged P91 material, including isotropic (cyclic) softening and non-linear kinematic hardening effects, across a range of temperatures and strain-rates.KEYWORDS: service-aged P91, strain-rate independence, unified viscoplasticity, high temperature low cycle fatigue, material Jacobian. INTRODUCTIONGrade P91 steel, a 9Cr martensitic steel developed at Oakridge National Laboratory (ORNL) [1], is used extensively in fossil-fuel based power plant due to its high creep strength and low coefficient of thermal expansion. However, modern and next generation power plants are subjected to thermomechanical fatigue (TMF) due to a rapid rise in the number of start-up cycles to accommodate renewable sources of energy. This results in premature failure of plant components, including plant header and piping systems. Thus, there is a greater requirement to be able to characterise the advanced materials of modern and next generation plants under realistic loading conditions and accurately predict failure at the component level.The high strength of such 9Cr steels may be attributed to its complex microstructure, consisting of prior austenite grains, packets and blocks in a hierarchical format [2]. The blocks contain long martensitic laths and more equi-axed subgrains [2,3]. The martensitic laths contain MX type precipitates which resist motion of mobile dislocations and M 23 C 6 carbonitrides are dispersed along boundaries to increase the resistance of the material to creep deformation [4]. Although 9Cr steels have a high creep strength, fatigue loading results in a coarsening of this microstructure, leading to the cyclic softening phenomenon observed in such materials [2,3,5] and to a reduction in creep strength.

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“…A multi-set of nonlinear equations was established and then, the obtained equations were solved to determine the required parameters using an iterative technique such as Newton-Raphson approach. In other studies (Chaparro et al, 2008;Mahmoudi et al, 2011), genetic algorithm (GA) was used to minimize the difference between the numerical predictions and the experimental results when calibrating the NLKH models. However, FEMU has a drawback that it is time-consuming due to the iterative nature of the FE model updating process.…”

Section: Introductionmentioning

confidence: 99%

Identification of nonlinear kinematic hardening constitutive model parameters using the virtual fields method for advanced high strength steels

Barlat

Kim

et al. 2016

International Journal of Solids and Structures

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In this work, the nonlinear kinematic hardening combined with Voce isotropic hardening was selected to characterize the material behavior of advanced high strength steel sheet samples subjected to a few reverse loading cycles. Multi-components of backstress were considered for the combined nonlinear kinematical hardening model, namely, one, two, and three backstress components. To calibrate the model, an inverse problem solution tool, so-called virtual fields method, which takes full advantage of full-field deformation measurement, was applied to identify the material constitutive parameters. First, finite element simulations of forward-reverse simple shear were performed to validate the proposed identification method. The influence of strain noise on the identification accuracy was also evaluated. Then, the proposed method was applied to three kinds of sheet metals (DP600, TRIP780 and TWIP980) tested under two cycles of forward-reverse simple shear for parameter identification. The identification results obtained with different number of backstress components were critically discussed.

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Parameter determination of Chaboche kinematic hardening model using a multi objective Genetic Algorithm

Cited by 92 publications

References 17 publications

Comparison of the hardening behaviour of different steel families: From mild and stainless steel to advanced high strength steels

Comparison of the hardening behaviour of different steel families: From mild and stainless steel to advanced high strength steels

A Unified Viscoplastic Model for High Temperature Low Cycle Fatigue of Service-Aged P91 Steel

Identification of nonlinear kinematic hardening constitutive model parameters using the virtual fields method for advanced high strength steels

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