Microstructural strain distribution in ductile iron; comparison between finite element simulation and digital image correlation measurements

Kasvayee, Keivan Amiri; Salomonsson, Kent; Ghassemali, Ehsan; Jarfors, Anders E. W.

doi:10.1016/j.msea.2015.12.056

Cited by 40 publications

(51 citation statements)

References 42 publications

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“…They used models where the microstructure was considered as biphasic, and models with the nodules that were considered as holes, and demonstrated that it is not possible to consider graphite nodules as holes, because in addition to being unrealistic, such considerations decrease the intensification of the stress near of the graphite nodules. In the same sense, there is the work of Kasvayee et al [14] which studied the distribution of strains produced in a tensile test of a DCI; in their work, as Di Cocco does, demonstrated that the assumption of graphite nodules as holes in the microstructure is not valid, since taking into account this consideration occurred high deformations around all of the graphite nodules, unlike when the nodules are considered as solids, where the deformations were only located on some specific nodules. Therefore, the models that consider graphite nodules as holes, despise the effects on the mechanical properties of graphite in the microstructure of DCIs.…”

Section: Introductionmentioning

confidence: 87%

“…Table 1 shows the models obtained from four nodules (A, B, C and D) using the three different methods mentioned, besides the CSF est and E r values for each graphite nodule are shown, where the maximum errors are highlighted in bold. Regarding the models that are generated using a fixed Bézier degree for all the nodules, three different models were created with the following degrees: 4, 10, and 18. high CSFest values and high Er values, therefore do not approximate adequately to the geometry of the digital contours; on the other hand, as the curve degree increases (degree 10), the curves approximate to the contours obtained digitally preserving the smoothness that characterizes them, unlike the models that are obtained with commercial img2CAD software and the models that are obtained by another methodologies [11,14,16], where no smooth algorithms has been applied. Table 1.…”

Section: Geometric Comparison Of the Obtained Modelsmentioning

confidence: 94%

“…This effect can be explained as the system represented in Equation (2) becomes indeterminate as the curve degree used is greater than the number of points that the contour has, generating spurious Table 1 shows the generated models, where geometric evolution it can be seen as the Bézier curve degree increases. In relation to the models obtained using a fixed Bézier curve degree for all of the nodules, it can be seen that the curves that are obtained with Bézier degrees of 4 are curves with high CSF est values and high E r values, therefore do not approximate adequately to the geometry of the digital contours; on the other hand, as the curve degree increases (degree 10), the curves approximate to the contours obtained digitally preserving the smoothness that characterizes them, unlike the models that are obtained with commercial img2CAD software and the models that are obtained by another methodologies [11,14,16], where no smooth algorithms has been applied.…”

Section: Geometric Comparison Of the Obtained Modelsmentioning

confidence: 94%

“…They considered a node within each pixel of the contour and then joined each node using straight lines. In this context, there is the work of Kasvayee et al [14], which studied the distribution of strains that were produced in a tensile test of a DCI, when comparing finite element simulation and measurements by digital image correlation, in their work they used real micrographs to produce their models. Another work is that of Fernandino et al [16], in which it was developed a methodology for predicting the elastic behavior of a DCI using multi-scale analysis.…”

Section: Introductionmentioning

confidence: 99%

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Genetic Algorithm-Based Optimization Methodology of Bézier Curves to Generate a DCI Microscale-Model

et al. 2017

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Abstract:The aim of this article is to develop a methodology that is capable of generating micro-scale models of Ductile Cast Irons, which have the particular characteristic to preserve the smoothness of the graphite nodules contours that are lost by discretization errors when the contours are extracted using image processing. The proposed methodology uses image processing to extract the graphite nodule contours and a genetic algorithm-based optimization strategy to select the optimal degree of the Bézier curve that best approximate each graphite nodule contour. To validate the proposed methodology, a Finite Element Analysis (FEA) was carried out using models that were obtained through three methods: (a) using a fixed Bézier degree for all of the graphite nodule contours, (b) the present methodology, and (c) using a commercial software. The results were compared using the relative error of the equivalent stresses computed by the FEA, where the proposed methodology results were used as a reference. The present paper does not have the aim to define which models are the correct and which are not. However, in this paper, it has been shown that the errors generated in the discretization process should not be ignored when developing geometric models since they can produce relative errors of up to 35.9% when an estimation of the mechanical behavior is carried out.

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Section: Introductionmentioning

confidence: 87%

Section: Geometric Comparison Of the Obtained Modelsmentioning

confidence: 94%

Section: Geometric Comparison Of the Obtained Modelsmentioning

confidence: 94%

Section: Introductionmentioning

confidence: 99%

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Genetic Algorithm-Based Optimization Methodology of Bézier Curves to Generate a DCI Microscale-Model

et al. 2017

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“…Once the matrix-nodule debonding is completed, the localized plastic strain is the driving mechanism for the development of ductile damage [17]. Fig.…”

Section: Micro-scale Damage Evolutionmentioning

confidence: 99%

Mechanism of Damage of Ferritic Ductile Iron, Influence of Matrix Heterogeneity

Fernandino

Boeri

Massone

2018

MSF

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Abstract. Ferritic ductile cast iron (FDI) microstructure is composed by graphite nodules embedded in a ferritic matrix. It is usual to assume that the ferritic matrix is homogeneous. However, the experimental analysis shows impurities and in some cases a high degree of heterogeneity. It is necessary to investigate the influence of these heterogeneities on the mechanical properties of FDI. This work focusses on the characterization of the elastoplastic properties of different zones of the ferritic matrix of FDI and the identification of the sequence and extent of the damage mechanisms at the micro-scale under uniaxial tensile loading.The methodologies for the characterization of the material micro constituents and microsegregated zones involve nano-indentation and atomic force microscopy techniques in combination with computational modelling. The analysis is performed by applying inverse analysis algorithms proposed in the literature. The microsegregated zones are identified by using color etching. The assessment of the micro-scale damage mechanisms was performed by in-situ optical microscopy observation of tensile tests of very small specimens.The results led to the quantification of the differences in mechanical properties along the metallic matrix as a result of the existing heterogeneities and allow for a better understanding of the ductile iron damage mechanism.

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Recent trends in X‐ray‐based characterization of nodular cast iron

Andriollo

Zhang

et al. 2020

Mat Design & Process Comms

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Through various examples, this short review presents the main X‐ray‐based techniques that are available to characterize nodular cast iron at the microstructural level. Emphasis is placed on the enormous potential offered by the recent developments in X‐ray tomography, X‐ray diffraction, and digital volume correlation, which allow collecting microstructural and micromechanical information in 4D (3D plus time) during both casting and subsequent mechanical loading. The goal is to demonstrate that for nodular cast iron, which has an inherently three‐dimensional, composite microstructure, X‐ray‐based techniques provide some significant advantages over conventional microscopy. For this reason, these techniques can be instrumental in unveiling the mechanisms controlling both the formation of the microstructure as well as its micromechanical behavior during in‐service loading, thus paving the way to the development of improved process–structure–property relations.

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Microstructural strain distribution in ductile iron; comparison between finite element simulation and digital image correlation measurements

Cited by 40 publications

References 42 publications

Genetic Algorithm-Based Optimization Methodology of Bézier Curves to Generate a DCI Microscale-Model

Genetic Algorithm-Based Optimization Methodology of Bézier Curves to Generate a DCI Microscale-Model

Mechanism of Damage of Ferritic Ductile Iron, Influence of Matrix Heterogeneity

Recent trends in X‐ray‐based characterization of nodular cast iron

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