Determination of combined hardening material parameters under strain controlled cyclic loading by using the genetic algorithm method

Badnava, H.; Pezeshki, Mahmoud; Nejad, Kh. Fallah; Farhoudi, Hamidreza

doi:10.1007/s12206-012-0837-1

Cited by 31 publications

(17 citation statements)

References 19 publications

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“…and Equation (3) still illustrates the relationship between the stress and elastic strain during the plastic loading. For yield surface F 2 , the kinematic hardening evolution of the back-stress α ′ is composed of three nonlinear terms as follows [46,47]:…”

Section: Constitutive Modelling Based On Thementioning

confidence: 99%

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Analysis of Springback Behaviour in Micro Flexible Rolling of Crystalline Materials

Jiang

Wang

et al. 2018

Advances in Materials Science and Engineering

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This paper presents a constitutive modelling of the polycrystalline thin metal strip under a state of combined loading in microflexible rolling. The concept of grained inhomogeneity is incorporated into the classic Chaboche hardening model that accounts for the Bauschinger effect, in order to provide more precise description and analysis of the springback mechanism in the particular forming operation. The model is first implemented in the finite element program ABAQUS to numerically predict the stress-strain relationship of 304 stainless steel specimens over a range of average grain sizes. After validation of the developed model by comparison of predicted curves and actual stress-strain data points, it is further applied to predict the thickness directional springback in microflexible rolling of 304 stainless steel strips with initial thickness of 250 µm and reduction changing from 5 to 10%. The model predictions show a reasonable agreement with the experimental measurements and have proven to be more accurate than those obtained from the conventional multilinear isotropic hardening model in combination with the Voronoi tessellation technique. In addition, the variation of thickness directional springback along with the scatter effect is compared and analysed in regard to the average grain size utilising both qualitative and quantitative approaches in respect of distinct types of data at different reductions.

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Section: Constitutive Modelling Based On Thementioning

confidence: 99%

“…where a 1 , a 2 , a 3 , C 1 , C 2 , C 3 are material parameters, ε p and ε p are the plastic strain and effective plastic strain, respectively. e evolution of isotropic hardening takes the following form [46]:…”

Section: Constitutive Modelling Based On Thementioning

confidence: 99%

Analysis of Springback Behaviour in Micro Flexible Rolling of Crystalline Materials

Jiang

Wang

et al. 2018

Advances in Materials Science and Engineering

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“…As the experimental understanding of materials increases, so has the level of sophistication and complexity of elastoplastic models, leading to increased parameter calculation requirements, as recognised by Grama et al (2015). In order to improve the calculation process of elastoplastic constitutive model parameters, various optimisation techniques have been investigated, with two main optimisation strategies identified, the gradient-based (Mahnken and Stein, 1996, Saleeb et al, 2002, Desai and Chen, 2006 and the genetic algorithm (GA) methodologies (Rahman et al, 2005, Krishna et al, 2009, Badnava et al, 2012, Agius et al, 2017a, Mahmoudi et al, 2011, Farrahi et al, 2014, Rokonuzzaman and Sakai, 2010, Khademi et al, 2015, Cermak et al, 2015, Zhao and Lee, 2002, Khutia and Dey, 2014, Franulović et al, 2009. As highlighted by Furukawa et al (2002), the disadvantage of the gradient-based approach in constitutive model parameter determination lies in the solution divergence, an issue not typically associated with GA methodologies, which are instead associated with poor solution efficiency.…”

Section: Introductionmentioning

confidence: 99%

Optimising the multiplicative AF model parameters for AA7075 cyclic plasticity and fatigue simulation

Agius

Kajtaz

Kourousis

et al. 2018

AEAT

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Purpose -This study presents the improvements of the Multicomponent Armstrong-Frederick model with Multiplier performance through a numerical optimisation methodology available in a commercial software. Moreover, it explores the application of a multi-objective optimisation technique for the determination of the parameters of the constitutive models using uniaxial experimental data gathered from Aluminium Alloy 7075-T6 specimens. This approach aims to improve the overall accuracy of stress-strain response, not only for symmetric strain controlled loading but also for asymmetrically strain-and stress-controlled loading.Design/methodology/approach -Experimental data from stress and strain controlled symmetric and asymmetric cyclic loadings have been utilised for this purpose. The analysis of the influence of the parameters on simulation accuracy has led to an adjustment scheme that can be used for focused optimisation of the MAFM model performance. The method was successfully employed to provide a better understanding of the influence of each model parameter on the overall simulation accuracy. Findings -The optimisation identified an important issue associated with competing ratcheting and mean stress relaxation objectives; highlighting the issues with arriving at a parameter set that can simulate ratcheting and mean stress relaxation for load cases not reaching at complete relaxation.Post-print: "Optimising the multiplicative AF model parameters for AA7075 cyclic plasticity and fatigue simulation", Aircraft Engineering and Aerospace Technology, Vol. 90 Issue: 2, pp.251-260, https://doi.org/10.1108/AEAT-05-2017-0119 2 Practical implications -The study uses a strain-life fatigue application to demonstrate the importance of incorporating a technique such as the presented multi-objective optimisation method to arrive at robust parameters capable of accurately simulating a variety of transient cyclic phenomena.Originality/value -The proposed methodology improves the accuracy of cyclic plasticity phenomena and strain-life fatigue simulations for engineering applications. This study is considered a valuable contribution for the engineering community, as it can act as starting point for further exploration of the benefits that can be obtained through material parameter optimisation methodologies for models of the Multicomponent Armstrong-Frederick class.

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“…As the models increase their level of sophistication and complexity, the number of material parameters has increased as well. This has led to the introduction of various material parameter optimisation techniques, in order to ease/streamline the identification process and improve the accuracy of the model predictions [16][17][18][19][20][21][22][23][24][25][26][27]. However, the sensitivity of the strain life fatigue predictions to the model parameters requires a thorough assessment, owing to the complexity of many real-life load spectra.…”

Section: Introductionmentioning

confidence: 99%

Sensitivity and optimisation of the Chaboche plasticity model parameters in strain-life fatigue predictions

et al. 2017

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The aerospace industry is widely employing strain-life methodologies for structural fatigue predictions. Under spectrum loading, overloads significantly affect the fatigue, therefore it is very important to accurately account for the cyclic transient deformation phenomena. Describing these phenomena requires advanced plasticity models that involve a set of material parameters. Even for the well-known Chaboche model, there is lack of understanding of each parameter's sensitivity

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Determination of combined hardening material parameters under strain controlled cyclic loading by using the genetic algorithm method

Cited by 31 publications

References 19 publications

Analysis of Springback Behaviour in Micro Flexible Rolling of Crystalline Materials

Analysis of Springback Behaviour in Micro Flexible Rolling of Crystalline Materials

Optimising the multiplicative AF model parameters for AA7075 cyclic plasticity and fatigue simulation

Sensitivity and optimisation of the Chaboche plasticity model parameters in strain-life fatigue predictions

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