Development of the subroutine library ‘UMMDp’ for anisotropic yield functions commonly applicable to commercial FEM codes

Takizawa, Hideo; Kuwabara, Toshihiko; Oide, Kai

doi:10.1088/1742-6596/734/3/032028

Cited by 10 publications

(5 citation statements)

References 6 publications

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“…Moreover, the four-node plane stress element (CPS4R) is used and the mesh is defined as regular, with a total of 858 elements. A user-defined material subroutine, Unified Material Model Driver for Plasticity (UMMDp) [21], is used to model the material behaviour. The boundary conditions were imposed as displacements along the y-direction on the top boundary of the specimen and fixed as 0 on the bottom boundary.…”

Section: Methodsmentioning

confidence: 99%

Identification of Swift Law Parameters Using FEMU by a Synthetic Image DIC-Based Approach

Henriques

Coppieters

Andrade‐Campos

et al. 2022

KEM

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Computer-aided engineering systems rely on constitutive models and their parameters to describe the material behaviour. The calibration of more elaborated material models with a larger number of parameters becomes very time and cost consuming. The development of image-based technology has enhanced the interest in inverse identification methods, which, when coupled with full-field measurements, have the potential to reduce the number of experimental tests required to accurately identify material properties. This work aims to identify the Swift hardening law parameters of a dual-phase steel using a tensile test on a heterogeneous dogbone specimen under uniaxial and quasi-static loading conditions using the finite element model updating (FEMU) technique. The numerical results were used to generate synthetic images, which were then processed by digital image correlation (DIC) and used as the reference in the identification procedure. Two different approaches were tested: (i) directly comparing the numerical results to the reference; (ii) using DIC-levelled numerical data by iteratively generating synthetic images and using the DIC filter with the same settings as were used on the reference (virtual experiment). The identification results obtained from both approaches are compared and discussed.

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Section: Methodsmentioning

confidence: 99%

Identification of Swift Law Parameters Using FEMU by a Synthetic Image DIC-Based Approach

Henriques

Coppieters

Andrade‐Campos

et al. 2022

KEM

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“…Material and Constitutive Models Under Analysis. The materials used in the simulations were the DP600 dual-phase steel and the AA3104 aluminum alloy, which behaviors were modelled using the UMMDp (Unified Material Model Driver for Plasticity) from Jancae (Japan Association of Nonlinear CAE) [24]. Concerning the constitutive models under analysis, the Swift hardening law [5], the Voce law [25], the Yld2000-2D for the yield criterion [6] and the Armstrong-Frederick 1966 model (denoted as A-F model) [26] for the kinematic hardening were implemented.…”

Section: Fig 2 Hole Expansion Test Configuration (Dimensions In Mm)mentioning

confidence: 99%

Process-informed material model selection

Conde

2023

Materials Research Proceedings

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Abstract. The efficient development of metal products with high quality usually requires realistic numerical simulations before the manufacturing procedure. The choice of the constitutive model has a considerable influence on the predicted material behavior’s description. Several material constitutive models have been proposed to describe different mechanical phenomena. However, its selection is a labored task that requires expertise. This lack of knowledge can lead to errors in the numerical predictions and, consequently, large costs and delays in the manufacturing procedure. To overcome this problem, an automatic material model selection tool is necessary. This work aims to compare the impact of different constitutive models and their features on the simulation of a forming process and develop a rational and systematic strategy for model selection. The approach focuses on the study of a hole expansion test using Abaqus and a statistical analysis of variance (ANOVA). It was possible to establish a ranking for the importance of the types of models that can help with model selection decision-making and efficient parameter calibration for accurate predictions.

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“…The type of numerical element used was the CPS4R. The material behavior was implemented using the UMMDp developed by JANCAE (Japan Association of Nonlinear CAE) [23]. Both specimens were subjected to uniaxial loading conditions by imposing a displacement up to rupture.…”

Section: Mechanical Testsmentioning

confidence: 99%

Parameter Identification of Swift Law Using a FEMU-Based Approach and an Innovative Heterogeneous Mechanical Test

Coppieters

Henriques

Andrade‐Campos

2022

KEM

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The reliability and predictive accuracy of forming simulation depend on both the material constitutive model and its inherent parameters. As opposed to conventional sheet metal material testing, heterogeneous mechanical tests provide more complex strain and stress states. Heterogeneous mechanical tests can be used to efficiently predict the material behavior in forming processes due to an improvement in the time required and accuracy in the identification of the parameters. The present work aims at identifying the Swift hardening law parameters of a dual-phase steel by means of an optimum-designed interior notched specimen that presents several strain and stress states simultaneously. The finite element model updating (FEMU) technique was used for the identification of parameters, by comparing a DIC-measured virtual material with numerical results iteratively DIC-filtered.

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Development of the subroutine library ‘UMMDp’ for anisotropic yield functions commonly applicable to commercial FEM codes

Cited by 10 publications

References 6 publications

Identification of Swift Law Parameters Using FEMU by a Synthetic Image DIC-Based Approach

Identification of Swift Law Parameters Using FEMU by a Synthetic Image DIC-Based Approach

Process-informed material model selection

Parameter Identification of Swift Law Using a FEMU-Based Approach and an Innovative Heterogeneous Mechanical Test

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