2014
DOI: 10.1177/0309324714524398
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Characterization of electrolytic tinplate materials via combined finite element and regression models

Abstract: In this article, a new method that combines finite element method with data mining techniques is proposed to obtain the mechanical properties of electrolytic tinplate. Using information provided by two simple and economic tests (hardness and spring-back), already used in industries to classify tinplate, yield stress and tensile parameters of a generic electrolytic tinplate can be estimated. Initially, a group of finite element models based on these simple tests were built and validated against experimental dat… Show more

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Cited by 14 publications
(6 citation statements)
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“…The particular geometrical dimensions of the studied TRB are: Then, like the work performed by Illera et al (2014) to set FE models in contact problems, the FE models based on the TRB are considered to be valid when the computational costs of each simulation are not excessive, and when:…”
Section: Adjustment Of Trb Based On the Mesh Size Of Raceways And Rolmentioning
confidence: 99%
“…The particular geometrical dimensions of the studied TRB are: Then, like the work performed by Illera et al (2014) to set FE models in contact problems, the FE models based on the TRB are considered to be valid when the computational costs of each simulation are not excessive, and when:…”
Section: Adjustment Of Trb Based On the Mesh Size Of Raceways And Rolmentioning
confidence: 99%
“…When combined with a relatively limited number of experimental data, FEM can be used to evaluate material models and adjust their constants that are most appropriate for modeling the material behavior [33][34][35] and to vary the specimen parameters and loading modes to research the failure mode of material conveniently [36]. This provides a quick, simpler, and more economical alternative method to study material characterization.…”
Section: Simulation Analysis For the Tension Testsmentioning
confidence: 99%
“…There are only a few publications focusing on characterization methods of packaging steel. Illera et al [17] proposed an approach to determine material parameters via a combination of finite element methods and data mining techniques in 2014. Therein, simulated data of hardness and springback tests were used to predict yield strength and plastic hardening with regression models.…”
Section: State Of the Artmentioning
confidence: 99%