Benchmarks for Accelerated Cyclic Plasticity Models with Finite Elements

Novak, Jelena Srnec; Bona, Francesco De; Benasciutti, Denis

doi:10.3390/met10060781

Cited by 6 publications

(5 citation statements)

References 33 publications

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“…where: 𝜎𝜎 𝑦𝑦,0 is the initial yield stress, 𝑄𝑄 is a multiplicative Voce's equation parameter, 𝑏𝑏 is an exponential Voce's equation one, 𝑄𝑄parameter determines the saturation of the isotropic hardening and its variation might be positive for cyclic hardening or negative for cyclic softening [43], 𝑏𝑏parameter describes the saturation rate [44].…”

Section: Constitutive Equations Of the Cikh Modelmentioning

confidence: 99%

Computational Methods of the Identification of Chaboche Isotropic-Kinematic Hardening Model Parameters Derived from the Cyclic Loading Tests

Wójcik,

Gontarz,

Skrzat

et al. 2024

Adv. Sci. Technol. Res. J.

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The Chaboche-Lemaitre combined isotropic-kinematic hardening model (CKIH) gives an overall information about the material behaviour under cyclic loading. The identification of hardening parameters is a difficult and time-consuming problem. The procedure of the parameters identification using the experimental hysteresis curve obtained in a cyclic loading test under strain control is presented in details here for a S235JR construction steel. The last stabilized cycle extracted from the hysteresis curve is required for the identification of hardening parameters. The model with three backstresses is tested here. The optimization algorithm is also used for the improvement of the agreement between experimental and numerical data. In order to include some uncertainty of experiment and the identification procedure, the authorial algorithm written on the basis of the fuzzy logic soft-computing method is applied here. The results obtained show that the identification procedure presented in this paper ensures the good agreement between the experimental tests and numerical calculations. The correct selection of parameters associated with the hardening is essential for the right description of material behaviour subject to loading in different engineering problems, including in metal forming processes.

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Section: Constitutive Equations Of the Cikh Modelmentioning

confidence: 99%

Computational Methods of the Identification of Chaboche Isotropic-Kinematic Hardening Model Parameters Derived from the Cyclic Loading Tests

Wójcik,

Gontarz,

Skrzat

et al. 2024

Adv. Sci. Technol. Res. J.

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show abstract

“…Numerous approaches for incorporating material cyclic properties have been developed. Comparison between currently leading methods and the aforementioned challenges in their application are comprehensively provided in [8][9][10][11][12][13]. Most high-end modern commercial FEA (finite element analysis) software fatigue packages eliminate the need for tedious cyclic solutions and the fatigue assessment is performed solely at the post processing level, as extensively described in [14][15][16][17].…”

Section: Fig 2 -Materials Response Under Fatigue Regimementioning

confidence: 99%

Force Controlled Low Cycle Fatigue (LCF) Life Evaluation Methodology Based on Unstabilized Material Properties

Men

2021

AEF

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Low Cycle Fatigue (LCF) is a prominent failure mechanism in many design components; therefore, an evaluation of cycles to failure in this regime is of high importance. Most international standards recommend a closed loop strain-controlled mode specimen testing in this regime. However, the ꜪN data obtained from this test is not suitable for life evaluation of parts enduring force-controlled history during actual service without correction for control mode. Many existing procedures, which accounts for cyclic strain stabilization during force-controlled loading may significantly complicate the finite elements analysis (FEA) at solving or post processing stages and are often an inherent source of uncertainty. A heuristic, cost effective and sufficiently accurate approach for LCF life estimation is advocated. The method involves only two force loading FEA simulations, one of the actual parts and the other of the test specimen, using initial unstabilized stress strain curve, followed by a limited number of force-controlled specimens testing. Actual part and specimen life correlation performed using first loading unstabilized equivalent plastic strain value Ꜫp1 under locality and similitude assumptions. Unstabilized strain vs. number of cycles to failure curve Ꜫp1N is constructed and discussion regarding specimen geometry considerations for providing sufficient accuracy is included. Method validation and crack propagation study are provided.

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“…It is thus essential to rely on a cyclic plasticity model capable of describing the material behaviour up number of cycles of interest. At that point, the computed strain amplitude, appropriately evaluated through a failure criterion (for example as done by several authors [11,12]), can be employed to estimate the cycles to failure using the Manson-Coffin strain-life curve [13].…”

Section: Introductionmentioning

confidence: 99%

Cyclic Plasticity and Low Cycle Fatigue of an AISI 316L Stainless Steel: Experimental Evaluation of Material Parameters for Durability Design

et al. 2021

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AISI 316L stainless steels are widely employed in applications where durability is crucial. For this reason, an accurate prediction of its behaviour is of paramount importance. In this work, the spotlight is on the cyclic response and low-cycle fatigue performance of this material, at room temperature. Particularly, the first aim of this work is to experimentally test this material and use the results as input to calibrate the parameters involved in a kinematic and isotropic nonlinear plasticity model (Chaboche and Voce). This procedure is conducted through a newly developed calibration procedure to minimise the parameter estimates errors. Experimental data are eventually used also to estimate the strain–life curve, namely the Manson–Coffin curve representing the 50% failure probability and, afterwards, the design strain–life curves (at 5% failure probability) obtained by four statistical methods (i.e., deterministic, “Equivalent Prediction Interval”, univariate tolerance interval, Owen’s tolerance interval for regression). Besides the characterisation of the AISI 316L stainless steel, the statistical methodology presented in this work appears to be an efficient tool for engineers dealing with durability problems as it allows one to select fatigue strength curves at various failure probabilities depending on the sought safety level.

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Benchmarks for Accelerated Cyclic Plasticity Models with Finite Elements

Cited by 6 publications

References 33 publications

Computational Methods of the Identification of Chaboche Isotropic-Kinematic Hardening Model Parameters Derived from the Cyclic Loading Tests

Computational Methods of the Identification of Chaboche Isotropic-Kinematic Hardening Model Parameters Derived from the Cyclic Loading Tests

Force Controlled Low Cycle Fatigue (LCF) Life Evaluation Methodology Based on Unstabilized Material Properties

Cyclic Plasticity and Low Cycle Fatigue of an AISI 316L Stainless Steel: Experimental Evaluation of Material Parameters for Durability Design

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