Investigation into the Evolution of Microstructure and Mechanical Properties of Compacted Graphite Iron under Elevated Temperature

Shi, Guo Qing; Yang, Zhong; Li, J. P.; Sun, Shuhui; Guo, Min; Dong, Tao; J., Z.

doi:10.1007/s11665-021-06068-6

Cited by 10 publications

(2 citation statements)

References 23 publications

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“…The tensile strength and hardness of vermicular graphite cast iron are between that of nodular graphite cast iron and gray cast iron, but the heat fatigue resistance and machinability are better than those of nodular graphite cast iron [1][2][3]. Moreover, the good casting performance, wear resistance, and compactness make it widely used in working environments of high mechanical thermal stress, such as in large diesel engines with high power density [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Influence of FeS2 and FeSi75 in Double-Chamber Sample Cup on Thermal Analysis Curve and Graphite Morphology of Molten Iron

An-li

Tian

Shi

et al. 2023

Metals

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In the production of vermicular graphite cast iron, the allowable range of residual magnesium content in molten iron after treatment is very narrow, amounting to only 0.008%. Therefore, thermal analysis technology was used to quickly evaluate the vermiculation and inoculation level of molten iron at the furnace itself, thus allowing the molten iron to be adjusted in time. The additives in the sample cups play a crucial role in obtaining cooling curves with remarkable characteristics. In this study, either FeS2 or FeSi75 additives were added to one chamber of a double-chamber sample cup made of resin sand, in which the cavities of the double chambers were spherical with diameters of 30 mm. The thermal analysis curves of molten iron in the double-chamber sample cup were acquired using a double channel temperature recorder, and the solidified spherical samples were analyzed quantitatively. The influence of FeS2 or FeSi75 additives on both the cooling curves of molten iron and the graphite morphology were investigated. The experiment’s results indicated that when 0.05% FeS2 is added to one chamber of the sample cup, the cooling curve changes to the solidification pattern of gray cast iron. The continuous increase in the FeS2 additive has little influence on the shape of cooling curves, and the graphite changes form from vermicular to flaked. When the amount of FeS2 is increased from 0.05% to 0.10%, the resulting graphite changes from D-type and E-type to A-type and B-type. When the amount of FeS2 reaches 0.20%, the morphology of graphite is short and thick. With the increase in the amount of FeSi75 additive, the amount of spherical graphite in the sample cup increases gradually, and the vermicularity decreases gradually from 89% to 46%. With the increase in FeSi75 additive from 0 to 0.45%, we observed that the average diameter of graphite decreases from 23 μm to 19 μm and then increases to 22 μm. The eutectic recalescence temperature shows a decreasing trend, and the cooling curve gradually changes from a hypoeutectic to a eutectic pattern. The addition of 0.05% FeS2 or 0.45% FeSi75 to one chamber is more appropriate for a double-chamber sample cup with two spherical cavities with diameters of 30 mm. This lays a foundation for the optimization of additives when using the double-chamber sample cup for thermal analysis of vermicular graphite cast iron.

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Section: Introductionmentioning

confidence: 99%

Influence of FeS2 and FeSi75 in Double-Chamber Sample Cup on Thermal Analysis Curve and Graphite Morphology of Molten Iron

An-li

Tian

Shi

et al. 2023

Metals

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“…To obtain pearlite, copper, nickel, or tin are used. Due to the unique properties of CGI, the technology is still being developed, which is reflected in many publications [2][3][4][5][6][7][8][9][10][11]. There is a lot of information on the effect of alloy additions on the microstructure and the properties of CGI, e.g., [12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Data-Driven Model Selection for Compacted Graphite Iron Microstructure Prediction

et al. 2022

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Compacted graphite iron (CGI), having a specific graphite form with a large matrix contact surface, is a unique casting material. This type of cast iron tends to favor direct ferritization and is characterized by a complex of very interesting properties. Intelligent computing tools such as artificial neural networks (ANNs) are used as predictive modeling tools, allowing their users to forecast the microstructure of the tested cast iron at the level of computer simulation. This paper presents the process of the development of a metamodel for the selection of a neural network appropriate for a specific chemical composition. Predefined models for the specific composition have better precision, and the initial selection provides the user with automation of reasoning and prediction. Automation of the prediction is based on the rules obtained from the decision tree, which classifies the type of microstructure. In turn, the type of microstructure was obtained by clustering objects of different chemical composition. The authors propose modeling the prediction of the volume fraction of phases in the CGI microstructure in a three-step procedure. In the first phase, k-means, unsupervised segmentation techniques were used to determine the metamodel (DT), which in the second phase enables the selection of the appropriate ANN submodel (third phase).

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Investigation on the Thermal Fatigue and Microstructure Evolution Mechanism of Compacted Graphite Iron under Elevated Temperature

Shi

Yang

Guo³

et al. 2022

J. of Materi Eng and Perform

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Investigation into the Evolution of Microstructure and Mechanical Properties of Compacted Graphite Iron under Elevated Temperature

Cited by 10 publications

References 23 publications

Influence of FeS2 and FeSi75 in Double-Chamber Sample Cup on Thermal Analysis Curve and Graphite Morphology of Molten Iron

Influence of FeS2 and FeSi75 in Double-Chamber Sample Cup on Thermal Analysis Curve and Graphite Morphology of Molten Iron

Data-Driven Model Selection for Compacted Graphite Iron Microstructure Prediction

Investigation on the Thermal Fatigue and Microstructure Evolution Mechanism of Compacted Graphite Iron under Elevated Temperature

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