Analytical springback model for lightweight hexagonal close-packed sheet metal

Lee, M.G.; Kim, J.H.; Chung, Kwansoo; Kim, S.J.; Wagoner, R. H.; Kim, H.Y.

doi:10.1016/j.ijplas.2008.04.005

Cited by 46 publications

(14 citation statements)

References 16 publications

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“…As a result, the material exhibits significant flow asymmetries under tension and compression. Under tension, the macroyielding at the tensile stress of 192 MPa may be attributed to the activation of non-basal slip with hai type Burgers vectors and/or the formation of f10 12g tension twins (Gharghouri et al, 1999;Agnew and Duygulu, 2005;Agnew et al, 2006;Koike, 2005;Muránsky et al, 2009;Lee et al, 2009b). f10…”

Section: Resultsmentioning

confidence: 99%

An experimental study of cyclic deformation of extruded AZ61A magnesium alloy

Zhang

Jiang

et al. 2011

International Journal of Plasticity

133

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Section: Resultsmentioning

confidence: 99%

An experimental study of cyclic deformation of extruded AZ61A magnesium alloy

Zhang

Jiang

et al. 2011

International Journal of Plasticity

133

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“…But their computation efficiency is low and often trapping in local [3][4] . Being a probability search algorithm, neighborhood cultivation genetic algorithm (NCGA) is good at optimization process parameters globally and quickly.…”

Section: Finally Valid Of Optimized Parameters Set As Well As the Fmentioning

confidence: 99%

Prediction and optimization on springback and process parameters of S-Rail forming

Cheng

Zhang

et al. 2010

2010 International Conference on Mechanic Automation and Control Engineering

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In stamping process, springback is always determined by process parameters, such as blank-holder force, mould parameters, material parameters, and so on. Prediction of springback and parameters is a multi-objective optimization problem. Firstly, based on the same quantity of orthogonal experimental samples, prediction accuracy and efficiency of back propagation neural network (BPNN) prediction model and the response surface prediction model (RSPM) for springback of SRail forming were compared. As a result, RSPM was adopted benefit to less influence by sample scale and higher accuracy. Furthermore, a self-adaptive global optimizing of probability search algorithm, neighborhood cultivation genetic algorithm (NCGA) was proposed to optimize the prediction of process parameters. Then optimized parameters can be obtained quickly. Finally, valid of optimized parameters set, as well as the feasible of the prediction model based on both RSPM and NCGA were confirmed by the finite element analysis (FEA) test of S-Rail springback.Both the weighting method and objective programming approach are often used to solve multi-objective optimization problems. But their computation efficiency is low and often trapping in local [3][4] . Being a probability search algorithm, neighborhood cultivation genetic algorithm (NCGA) is good at optimization process parameters globally and quickly.So, in this paper, firstly, based on the same quantity of orthogonal experimental samples, results of BPNN prediction model and RSPM for springback were compared. Furthermore, NCGA was used to optimize process parameters. Finally, the feasible of prediction model based on both RSPM and NCGA was confirmed by the finite element analysis (FEA) test of SRail stamping.

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“…Generally, the cyclic plasticity models are constitutive models that are modelled by numerical tools. They can be divided in six major groups, four groups based in yield surface [7][8][9][10], one based in overlapping models [11] and other one based in endochroic models [12]. Models with one yield surface tend to be more robust than others that have two or more yield surfaces.…”

Section: Introductionmentioning

confidence: 99%

“…One example is the non-proportional hardening, which is the result of nonproportional loadings. In this type of loading all slip plans are activated however, the hardening effect it may be not equal in all directions [10,13]. Also within the non-proportional loadings there exist several non-proportionality levels, which also contribute to different anisotropy types.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the AZ31 cyclic elastic-plastic behaviour under multiaxial loading conditions

Anes¹,

Reis

Freitas

2014

Frattura Ed Integrità Strutturale

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ABSTRACT. Components and structures are designed based in their material's mechanical properties such as Young's modulus or yield stress among others. Often those properties are obtained under monotonic mechanical tests but rarely under cyclic ones. It is assumed that those properties are maintained during the material fatigue life. However, under cyclic loadings, materials tend to change their mechanical properties, which can improve their strength (material hardening) or degrade their mechanical capabilities (material softening) or even a mix of both. This type of material behaviour is the so-called cyclic plasticity that is dependent of several factors such as the load type, load level, and microstructure. This subject is of most importance in design of structures and components against fatigue failures in particular in the case of magnesium alloys. Magnesium alloys due to their hexagonal compact microstructure have only 3 slip planes plus 1 twining plane which results in a peculiar mechanical behaviour under cyclic loading conditions especially under multiaxial loadings. Therefore, it is necessary to have a cyclic elastic-plastic model that allows estimating the material mechanical properties for a certain stress level and loading type. In this paper it is discussed several aspects of the magnesium alloys cyclic properties under uniaxial and multiaxial loading conditions at several stress levels taking into account experimental data. A series of fatigue tests under strain control were performed in hour glass specimens test made of a magnesium alloy, AZ31BF. The strain/stress relation for uniaxial loadings, axial and shear was experimentally obtained and compared with the estimations obtained from the theoretical elastic-plastic models found in the state-of-the-art. Results show that the AZ31BF magnesium alloy has a peculiar mechanical behaviour, which is quite different from the steel one. Moreover, the state of the art cyclic models do not capture in full this peculiar behaviour, especially the cyclic magnesium alloys anisotropy. Further, an analysis is performed to identify the shortcomings inherent to the actual cyclic models in the capture of the magnesium alloys cyclic behaviour. Several conclusions are drawn.

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Analytical springback model for lightweight hexagonal close-packed sheet metal

Cited by 46 publications

References 16 publications

An experimental study of cyclic deformation of extruded AZ61A magnesium alloy

An experimental study of cyclic deformation of extruded AZ61A magnesium alloy

Prediction and optimization on springback and process parameters of S-Rail forming

Evaluation of the AZ31 cyclic elastic-plastic behaviour under multiaxial loading conditions

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