Identification of rheological parameters on the basis of plane strain compression tests on specimens of various initial dimensions

Kowalski, B.I.; Sellars, C. M.; Pietrzyk, M.

doi:10.1016/j.commatsci.2005.02.024

Cited by 8 publications

(6 citation statements)

References 7 publications

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“…In this context, the key idea is to simulate the performed experiment, trying to adapt material parameters in order to numerically obtain the same results as the experimental ones [11,12]. This approach consists of an optimization problem where the objective function is to mini-mize the gap between the experimental and the numerical results.…”

Section: Introductionmentioning

confidence: 99%

Material parameters identification: Gradient-based, genetic and hybrid optimization algorithms

Chaparro¹,

Thuillier²,

Menezes³

et al. 2008

Computational Materials Science

193

102

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a b s t r a c tThis paper presents two procedures for the identification of material parameters, a genetic algorithm and a gradient-based algorithm. These algorithms enable both the yield criterion and the work hardening parameters to be identified. A hybrid algorithm is also used, which is a combination of the former two, in such a way that the result of the genetic algorithm is considered as the initial values for the gradient-based algorithm. The objective of this approach is to improve the performance of the gradient-based algorithm, which is strongly dependent on the initial set of results. The constitutive model used to compare the three different optimization schemes uses the Barlat'91 yield criterion, an isotropic Voce type law and a kinematic Lemaitre and Chaboche law, which is suitable for the case of aluminium alloys. In order to analyse the effectiveness of this optimization procedure, numerical and experimental results for an EN AW-5754 aluminium alloy are compared.

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Section: Introductionmentioning

confidence: 99%

Material parameters identification: Gradient-based, genetic and hybrid optimization algorithms

Chaparro¹,

Thuillier²,

Menezes³

et al. 2008

Computational Materials Science

193

102

View full text Add to dashboard Cite

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“…The simulation of the quasi-homogeneous compression tests on plastometer was carried out using the slab method [32], in order to account for the friction effect, while the temperature and strain rate were considered constant and uniform within the sample. This approach has been shown to be sufficiently accurate for the analysis of plastometer characterization experiments and it is regularly used [14,27]. However, for the simulation of the on-press experiments, full-field FE simulations were performed using the commercial Forge® software.…”

Section: Simulation Modelsmentioning

confidence: 99%

“…The parameters are found with the help of inverse analysis, in order to best describe a set of experiments which reveal the material's behaviour. Advanced inverse methods have been developed specifically for large strain parameter identification during the hot deformation of metals [12][13][14][15][16]. Different optimization algorithms have been used in the literature for constitutive parameter identification.…”

Section: Introductionmentioning

confidence: 99%

Parameter identification of 42CrMo4 steel hot forging plastic flow behaviour using industrial upsetting presses and finite element simulations

et al. 2021

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An experimental-numerical methodology was proposed for the parameter identification of constitutive laws, when applied to hot forging. Industrial presses were directly used to generate the reference experiments for identification. The strain and temperature heterogeneity that appears during on-press compression experiments was taken into account by an FE-based inverse method. Specific experiments were designed for the identification of the heat transfer and friction coefficients. A testing tool was designed and instrumented with displacement sensors and a force cell. This was then used on a hydraulic press and a screw press in order to cover a large range of strain rates. The identified parameter set was validated with respect to specialized plastometers, and a semiindustrial validation forging process. A reasonable accuracy was observed, particularly in realistic forging conditions.

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“…This test was commonly used there for investigation of materials and fundamental works on microstructure evolution [18] and on flow stress models [8] were a result of this research. Application of the FE model of the PSC test to aid the interpretation of results was described in [30] and further analysis of the influence of the size of the sample on the test results was performed in [31]. All these papers showed that PSC tests involve strong inhomogeneities of parameters.…”

Section: Identification Of the Flow Stress Model On The Basis Of Ucmentioning

confidence: 99%

“…Observations made in Section 5.1.2 were confirmed in Figure 18, where comparison between loads measured in the hot tests and calculated by the FE code with flow stress equations (3) and (4) with coefficients determined using conventional inverse analysis is shown. As a reference, results for the equation of [8] (published also in [30,31]) are shown in this figure. Again some discrepancies were obtained for (3) and 4, while a very good agreement between calculations and measurements was obtained for the equation of [8].…”

Section: Flow Stressmentioning

confidence: 99%

Application of Metamodels to Identification of Metallic Materials Models

Pietrzyk

Kusiak

Szeliga

et al. 2016

Advances in Materials Science and Engineering

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Improvement of the efficiency of the inverse analysis (IA) for various material tests was the objective of the paper. Flow stress models and microstructure evolution models of various complexity of mathematical formulation were considered. Different types of experiments were performed and the results were used for the identification of models. Sensitivity analysis was performed for all the models and the importance of parameters in these models was evaluated. Metamodels based on artificial neural network were proposed to simulate experiments in the inverse solution. Performed analysis has shown that significant decrease of the computing times could be achieved when metamodels substitute finite element model in the inverse analysis, which is the case in the identification of flow stress models. Application of metamodels gave good results for flow stress models based on closed form equations accounting for an influence of temperature, strain, and strain rate (4 coefficients) and additionally for softening due to recrystallization (5 coefficients) and for softening and saturation (7 coefficients). Good accuracy and high efficiency of the IA were confirmed. On the contrary, identification of microstructure evolution models, including phase transformation models, did not give noticeable reduction of the computing time.

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Identification of rheological parameters on the basis of plane strain compression tests on specimens of various initial dimensions

Cited by 8 publications

References 7 publications

Material parameters identification: Gradient-based, genetic and hybrid optimization algorithms

Material parameters identification: Gradient-based, genetic and hybrid optimization algorithms

Parameter identification of 42CrMo4 steel hot forging plastic flow behaviour using industrial upsetting presses and finite element simulations

Application of Metamodels to Identification of Metallic Materials Models

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