Prediction of Graphite Nodule Count and Shrinkage Tendency in Ductile Cast Iron, with 1 Cup Thermal Analysis

Kanno, Toshitake; Iwami, Yuki; Kang, Ilgoo

doi:10.1007/s40962-016-0111-x

Cited by 22 publications

(21 citation statements)

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“…As discussed, the equilibrium T st and T met calculated from equilibrium thermodynamics ignore the effect of processing variables such as pouring temperature and inoculation. Kanno et al [33,34] developed the corresponding equations from experiments:…”

Section: Prediction Of Graphitization Potentialmentioning

confidence: 99%

“…6 and Eq. 7, Kano et al [34] developed a one cup method that uses the T Emin (TSC) from the cooling curve. As the sulfur combines with Mg, it is ignored in the calculation of T st and T met .…”

Section: Special Reviewmentioning

confidence: 99%

“…of SG iron [7] Fig. 21: Relationship between EGA and the graphite nodule count for irons inoculated with various alloys [34] Fig. 19: Correlation between parameters of cooling curve and % ferrite measured on metallographic samples [41] is a significant part of process control.…”

Section: Fig 20: Effect Of Inoculation Fading On the Cooling Curvesmentioning

confidence: 99%

“…Kanno et al [34] used a conical-shape test piece to measure the correlation of shrinkage volume and the θ angle on the 1-cup TA (Fig. 33a).…”

Section: Prediction Of Shrinkage Propensitymentioning

confidence: 99%

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90 years of thermal analysis as a control tool in the melting of cast iron

2020

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Since its first literature mention in conjunction with cast iron in 1931 by Esser and Lautenbusch, thermal analysis (TA) has journeyed a long way. Today it is an accepted and widely used tool for process control for all types of cast irons. This paper reviews the latest progress in the development of equipment and analysis methods that make TA successful in applications such as the estimation of chemical composition, graphitization potential, and the shape and number of graphite aggregates. The potential and limitations of the prediction of shrinkage defects propensity are analyzed in some details. Examples of attempts at prediction of mechanical properties and shrinkage propensity are also discussed. Several graphs showing the data scattering are presented to convey the reader a better sense of the accuracy of various predictions.

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Section: Prediction Of Graphitization Potentialmentioning

confidence: 99%

Section: Special Reviewmentioning

confidence: 99%

Section: Fig 20: Effect Of Inoculation Fading On the Cooling Curvesmentioning

confidence: 99%

“…Kanno et al [34] used a conical-shape test piece to measure the correlation of shrinkage volume and the θ angle on the 1-cup TA (Fig. 33a).…”

Section: Prediction Of Shrinkage Propensitymentioning

confidence: 99%

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90 years of thermal analysis as a control tool in the melting of cast iron

2020

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“…The simplest approach of a commercial cast iron is in a ternary system, as in the Fe-C-Si alloy, with silicon as an important influencing factor for T st and T mst evaluation, according to Equations (4) and ( 5) [17]. However, as the more realistic approach of a commercial cast iron is in the Fe-C-Si-Xi system, more complex equations, including the most important influencing elements in the chemical composition of commercial ductile cast irons are necessary, such as expressed by Equations ( 6) and ( 7) [18,19].…”

Section: Thermal (Cooling Curve) Analysismentioning

confidence: 99%

Solidification Pattern of Si-Alloyed, Inoculated Ductile Cast Irons, Evaluated by Thermal Analysis

Stan

Anca

Stan

et al. 2021

Metals

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The solidification cooling curve itself as well as its first derivative, and related temperatures, reported to the calculated equilibrium temperatures in stable and metastable solidification systems, are used to predict the solidification characteristics of the cast iron. Silicon, as the most representative cast iron element, and inoculation, as graphitizing metallurgical treatment, have a major influence on the transition from the liquid to the solid state. Six experimental programs are performed, with Si content typically for non-alloyed (<3.0% Si), low (3.0–3.5% Si) and medium alloyed (4.5–5.5% Si) ductile cast irons, as Si-content increasing, and inoculation simultaneous effects. Silicon is an important influencing factor, but the base and minor elements also affect the equilibrium eutectic temperatures, much more in the Fe-C-Si-Xi stable system (15–20 °C) than in the metastable system (5–10 °C), comparing with their calculation based only on a Si effect (Fe-C-Si system). The highest positive effect of inoculation is visible in non-Si alloyed cast irons (2.5% Si): 9–15 °C for the eutectic reaction and 3 to 4 times increased at the end of solidification (37–47 °C). Increased Si content decreases inoculation power to 7–9 °C for low alloying grade (up to 3.5% Si), with the lowest contribution at more than 4.5% Si (0.3–2.0 °C). 2.5–3.5% Si ductile cast irons are more sensitive to high solidification undercooling, especially at the end of solidification (but with a higher efficiency of inoculation), compared to 4.5–5.5% Si ductile cast irons, at a lower undercooling level, and at lower inoculation contribution, as well.

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