A practical method for fatigue limit prediction in ductile cast irons

Endo, Mitsuru; Matsuo, Takashi

doi:10.1111/ffe.13086

Cited by 14 publications

(4 citation statements)

References 21 publications

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“…However, only little in-depth experimental studies of the influence of the Si-segregation profile on the mechanical properties of Si-DCI were published in the literature [ 14 ]. This is probably related to the strong heterogeneity of the microstructure which leads to the interplay of multiple factors that influence the mechanical properties [ 15 , 16 ].…”

Section: Introductionmentioning

confidence: 99%

The effect of silicon microsegregation on the mechanical properties of high silicon alloyed ductile cast iron under monotonous loading

Horbach,

Gebhardt,

Zhang

et al. 2024

Heliyon

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Section: Introductionmentioning

confidence: 99%

The effect of silicon microsegregation on the mechanical properties of high silicon alloyed ductile cast iron under monotonous loading

Horbach,

Gebhardt,

Zhang

et al. 2024

Heliyon

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“…The empirical

\sqrt{\mathrm{area}}

‐parameter model developed by Murakami [34] allows for a fast estimation of the criticality of defects in AM components. It has been developed to predict the fatigue limit of steels and is successfully used for materials such as quenched and tempered steel [34] or ductile cast iron [13]. The usability of the concept for additively manufactured Ti6Al4V is investigated by Masuo et al [31] and Romano et al [39] parameterize the model for AlSi10Mg.…”

Section: Introductionmentioning

confidence: 99%

Influence of CT image processing on the predicted impact of pores on fatigue of additively manufactured Ti6Al4V and AlSi10Mg

et al. 2022

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Pores are inherent to additively manufactured components and critical especially in technical components. Since they reduce the component's fatigue life, a reliable identification and description of pores is vital to ensure the component's performance. X‐ray computed tomography (CT) is an established and non‐destructive testing method to investigate internal defects. The CT scan process can induce noise and artefacts in the resulting images which afterwards have to be reduced through image processing. To reconstruct the internal defects of a component, the images need to be segmented in defect region and bulk material by applying a threshold. The application of the threshold as well as the previous image processing alter the geometry and size of the identified defects. This contribution aims to quantify the influence of selected commercial image processing and segmentation methods on identified pores in several additively manufactured components made of AlSi10Mg and Ti6Al4V as well as in an artificial CT scan. To that aim, gray value histograms and characteristic parameters thereof are compared for different image processing tools. After the segmentation of the processed images, particle characteristics are compared. The influence of image processing and segmentation on the predicted fatigue life of the material is evaluated through the change of the largest pore in each set of data applying Murakami's empirical area$$ \sqrt{\mathrm{area}} $$‐parameter model.

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“…Against this background, the graphite morphology and the matrix microstructure in nodular cast iron become relevant if large defects can be avoided. In the absence of large casting defects, an influence of graphite morphology on the fatigue properties of ferritic cast iron is measurable [3]. It was found that in EN-GJS-400-18LT (according to DIN EN 1563 [4], ISO1083/JS/400-18-LT/S according to ISO 1083 [5]), large and smaller non-spheroidal graphite nodules reduce the fatigue strength.…”

Section: Introductionmentioning

confidence: 99%

Influence of Aluminum on Fatigue Strength of Solution-Strengthened Nodular Cast Iron

Gebhardt

Nellessen

Bührig–Polaczek

et al. 2021

Metals

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The fatigue strength of high silicon-alloyed nodular cast iron is influenced by casting defects and graphite precipitates. The literature as well as the findings of this work show that these microstructural constituents can be tailored by controlling silicon microsegregation. In addition, segregations also affect the ferritic matrix microstructure locally. In the present work, silicon segregations in high silicon-alloyed ductile iron are specifically manipulated by small additions of aluminum. It was demonstrated how the aluminum content affects a wide range of microstructural constituents across a variety of length scales. Specimens from alloys with small additions of aluminum were fabricated and tested by rotating bending. Results show that the fatigue strength can be increased compared to a reference alloy with no aluminum. Microstructure analysis as well as fractography were performed concluding that microstructural changes could be attributed to the increased aluminum content, which allows the fatigue properties to be tailored deliberately. However, according to the results of this study, the negative effect of aluminum on castability and graphite morphology limits the maximum content to approximately 0.2 wt.%.

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A practical method for fatigue limit prediction in ductile cast irons

Cited by 14 publications

References 21 publications

The effect of silicon microsegregation on the mechanical properties of high silicon alloyed ductile cast iron under monotonous loading

The effect of silicon microsegregation on the mechanical properties of high silicon alloyed ductile cast iron under monotonous loading

Influence of CT image processing on the predicted impact of pores on fatigue of additively manufactured Ti6Al4V and AlSi10Mg

Influence of Aluminum on Fatigue Strength of Solution-Strengthened Nodular Cast Iron

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