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The quality of an iron melt which refers to the soundness of melting and subsequent treatments of the melt can be identified and recognized with its thermal analysis cooling curve. To compare two cooling curves, both the separating distance of the two curves and the shape similarity of the curves should be considered. A comprehensive parameter Ω ca...
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... analysis can also be confirmed from Fig. 5, where the graphite morphology of two nodular cast iron samples (the chemical compositions are listed in Table 1) with very similar cooling curves (Ω = 1.2 • C) has been shown, re- spectively. This behavior can also be found in grey cast irons (the chemical compositions are listed in Table 2). Fig. 6 shows the microstructure of two grey cast iron sam- ples with small Ω (Ω = 2.4 • C). The microstructure is very similar for the percentage of graphite type A and graphite length. It is well known that the shape of a cooling curve is mainly determined by three factors, which are the chemi- cal composition, cooling condition and melt ...
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This paper presents the results of application of artificial neural networks in determination of mechanical properties of ductile cast iron. All data were collected in a Croatian foundry for 147 melts. Error back-propagation training algorithm was applied to train the multilayer networks. The optimal size of the hidden neuron layer was determined t...
Citations
... In [22], machine learning and pattern recognition were used to investigate an important aspect of the casting process: the cooling and solidification of the metal. In general, this aspect is also relevant in the present case, but the two investigations are based on different databases (i.e., mechanical properties vs. thermal analysis cooling curves). ...
Cast iron is a very common and useful metal alloy, characterized by its high carbon content (>4%) in the allotropic state of graphite. The correct shape and distribution of graphite are essential for ensuring that the material has the right properties. The present investigation examines the metallurgical and mechanical characterization of a spheroidal (nodular) cast iron, an alloy that derives its name and its excellent properties from the presence of graphite as spheroidal nodules. Experimental data are detected and considered from a data mining perspective, with the scope to extract new and little-known information. Specifically, a machine learning toolkit (i.e., Orange Data Mining) is used as a means of permitting supervised learners/classifiers (such as neural networks, k-nearest neighbors, and many others) to understand related metallurgical and mechanical features. An accuracy rate of over 90% can be considered as representative of the method. Finally, interesting considerations emerged regarding the dimensional effect on the variation in the solidification rates, microstructure, and properties.
... An in-depth understanding of the solidification pattern may help to notice some specific points [15,16] on the cooling curve, where chemical composition and metallurgical structure of the cast irons may be determined as long as the solidifying process is monitored accurately and also to determine the microstructure and mechanical properties of castings. Any little variation in the iron melt will result in changing the shape of the cooling curve [17]. ...
In the current scenario, the energy crisis is on the continuous rise; researchers and academicians are actively working towards a common goal of energy savings by different means. Spheroidal graphite cast iron (SGI) is one of the major alloys used for automobile and structural applications. Manufacturing industries are more focused on using lightweight components to minimize the overall energy requirements. Nevertheless, the complexity of producing thin-walled SGI products is a challenge. In this study, the solidification cooling curve morphology and microstructure of SGI with varying section/wall thickness are investigated. The results obtained from the simulation of stepbar castings of varying section thickness show that thick sections have longer eutectic reaction thermal arrest due to release of latent heat by the formation of graphite. It is also observed that thin sections have a higher degree of undercooling. Microstructural investigation shows that thin sections have higher hardness and strength due to higher pearlite fraction, but the amount of graphite formed in thin sections is reduced, which could lead to aggravated carbide formation in SGI. Thus it is evident that to avoid the formation of carbides in thin-walled SGI castings more inoculation degree is required to promote graphite formation, which will ultimately suppress carbides precipitation. The results obtained from the cooling curve analysis are in agreement with the actual properties of SGI casting.
... Of the many TDA express-methods, a well-known method for recognizing cooling curves, described by Chinese authors [2,[4][5][6] (hereinafter referred to as RCC) is closest to the one we offer. The prospects of this method leave no doubt because it has several important useful features; namely: ...
... , and variance S characterizes only the accuracy of this numerical result [3]. The Chinese authors [2,[4][5][6] did not analyze the error of the RCC method at all and did not explain why some indicators of the quality of cast iron differ by almost an order of magnitude with the same Ω criterion value. Without any reasoning, the articles by the Chinese authors of the RCC method [2,[4][5][6] stated that the second term (S) in Formula (1) is supposedly necessary to take the fluctuations of the two compared cooling curves into account. ...
... The Chinese authors [2,[4][5][6] did not analyze the error of the RCC method at all and did not explain why some indicators of the quality of cast iron differ by almost an order of magnitude with the same Ω criterion value. Without any reasoning, the articles by the Chinese authors of the RCC method [2,[4][5][6] stated that the second term (S) in Formula (1) is supposedly necessary to take the fluctuations of the two compared cooling curves into account. However, any possible fluctuations (pulsations in magnitude) of the compared cooling curves are automatically taken into account by the RCC method when measuring the temperature difference between the curves in the liquidus solidus interval; no other cooling curve pulsations exist during the natural cooling and solidification of the melt in the sampler. ...
This method is based on the determination of similarity criterion Z as the average temperature difference between the reference and analyzed curves in the solidification region. The purpose of this work is to describe the thermal express-analysis (TDA) device created by us and the substantiation of the reliability and sensitivity of the results of the new method, including the definition of a two-sided confidence interval using Student's t-test. The error of the method was determined with the Student's criterion taken into account. The high sensitivity of the method to the metallurgical prehistory of the gray and white cast iron melts was confirmed. The method has been successfully tested under laboratory and experimental-industrial conditions on induction melting cast iron. The new method uses a disposable environmentally friendly submersible steel sampler with a heat-resistant coating inside and out. The method allows for the quick adaptation to the conditions of specific foundries (especially with the frequent changes of classes and types of cast iron) due to replenishing the database of the reference samples.The basic features of the new method are its universality, self-adaptability, speed, relative simplicity, and high sensitivity to the metallurgical prehistory of molten iron.
... Thermal analysis is known for the prediction of liquid metal properties such as carbon equivalent and cooling curve morphology. 6 According to Li et al. 7 the quality of an iron melt can be identified and recognized from its thermal analysis cooling curve which refers to the soundness of melting and subsequent treatments of the melt. According to Bartosova et al. 8 the number of graphite nodules in the SGI corresponds to the changes in the cooling curve specifically with the values of the eutectic temperatures. ...
The increasing demand for pre-pouring melt quality evaluation by thermal analysis has led to some important breakthroughs in understanding the solidification of spheroidal graphite cast iron (SGI). The two important parameters which characterize the solidification cooling curve of SGI are temperature of eutectic undercooling (TEU) temperature of eutectic recalescence (TER). In this study, the response of preconditioning treatment (0.1% Al,Zr,Ca–FeSi) on TEU and TER was investigated in several samples from different heats. It was found that preconditioning increases both TEU and TER. The average eutectic graphitization ability after preconditioning was found to increase from 60 to 75. The average undercooling (∆T) and recalescence (∆Tr) in preconditioned samples were 12 °C and 2 °C, whereas in samples without preconditioning average ∆T and ∆Tr are 19 °C and 7 °C, respectively. Preconditioning improves graphitization ability thereby increasing the graphite nodule count. The actual nodule count of SG iron samples obtained by image analysis was found to be in agreement with that of nodule counts predicted by thermal analysis.
... In published papers [4][5][6], it was stated that it is not possible to make solid conclusions using the results of thermal analysis of cast iron under different practical conditions. As mentioned before, one of the main reasons for this problem is; that the process stability is not sufficient in the tested foundries; therefore, a lot of influencing factors cause unreliability in the obtained results [7]. ...
The solidification of cast iron is a complex process with characterized entrance and marginal conditions. Thermal analysis is one of the processes that allows us to observe the solidification of alloys. There is a possibility of gaining information about the melted cast iron quality and predicting the final properties of the cast by evaluating the scanned cooling curves by solidification (stable and metastable system).This article deals with the study and analysis of cooling curves taken from production conditions of a foundry during ductile cast iron production. The aim is to discover the reproduction and reliability of the thermal analysis results of cast iron. The study of the progress of the cooling curves and their first derivation to follow the reactions of the curves to changing factors in the production process.
... 3) As a consequence, graphite shape monitoring is strongly recommended. Although many methods have been invented or developed, [4][5][6][7] the most widely used ones are metallographic observation and thermal analysis. As accurate they are, their measuring time is too long and their operation is too complicated. ...
A relationship between the surface tension of cast iron and the graphite shape has been proven by experimental analysis and thus the graphite shape can be forecast by the surface tension. A specific relation between the surface tension and the graphite shape has been established by experiments. When the surface tension is above 1385 mN/m, nodular graphite occurs. When the surface tension is between 1283 mN/m and 1385 mN/m, vermicular and nodular graphite occurs. When the surface tension is between 1108 mN/m and 1283 mN/m, vermicular graphite occurs. When the surface tension is between 990 mN/m and 1108 mN/m, flake and vermicular graphite occurs. When the surface tension is below 990 mN/m, flake graphite occurs.
... A modified thermal analysis technique for the identification and evaluation of liquid metal quality had been developed by the authors (Li and Hu, 1999;Li et al., 2001Li et al., , 2003Li, 2003;Li and Wang, 2005;Geng et al., 2005;Chen et al., 2006). The whole shape of a thermal analysis cooling curve reflects the solidification process of a liquid metal under a fixed solidification condition. ...
The shape of the freezing zone of a thermal analysis cooling curve not only contains the information about the modification level of compacted graphite cast iron (CGI) right after vermicularizing treatment, but also reflects the following fading process during holding. When the freezing zones of two cooling curves are approximately the same, graphite morphologies of the samples cast from the two corresponding melts right after vermicularizing treatment are similar, and those of the two corresponding samples cast after holding for the same period are similar too. Based on the pattern recognition method and database established from a large amount of experimental results, the shape of the freezing zone of a cooling curve can be used to identify the modification level of CGI melt and on-line prediction of a CGI melt quality has been realized.
The vermiculation effects of compacted graphite cast iron are seriously affected by the metallurgical and technological factors. The change of characteristic points on the cooling curve is attributed to the interaction of these factors, so it is difficult to establish the evaluation relationship between the vermicularity and the characteristic points of thermal analysis curve. Based on the idea of statistics, a method was studied to evaluate the vermicularity of molten iron by comparing with an established characteristic points representation model of hypothetical ideal metallurgical quality state under the production condition. The results showed that the method can meet the requirements of evaluating the vermicularity of molten iron by multiple characteristic points on the cooling curve. As the matching process among cooling curves was omitted, the calculation and evaluation efficiency can be improved. In addition, it is expected to achieve on-line classification and regulation of vermiculation effect in front of furnace by expanding the sample capacity for establishing the characterization model.
Fig. 1 Illustration of 10 critical characteristic points of vermicularity evaluation of CGI: 7 temperature points of the cooling curve and 3 first order differential points on corresponding cooling rate curve. Fullsize Image
In the current scenario, the energy crisis is on the continuous rise; researchers and academicians are actively working towards a common goal of energy savings by different means. Spheroidal graphite cast iron (SGI) is one of the major alloys used for automobile and structural applications. Manufacturing industries are more focused on using lightweight components to minimize the overall energy requirements. Nevertheless, the complexity of producing thin-walled SGI products is a challenge. In this study, the solidification cooling curve morphology and microstructure of SGI with varying section/wall thickness are investigated. The results obtained from the simulation of stepbar castings of varying section thickness show that thick sections have longer eutectic reaction thermal arrest due to release of latent heat by the formation of graphite. It is also observed that thin sections have a higher degree of undercooling. Microstructural investigation shows that thin sections have higher hardness and strength due to higher pearlite fraction, but the amount of graphite formed in thin sections is reduced, which could lead to aggravated carbide formation in SGI. Thus it is evident that to avoid the formation of carbides in thin-walled SGI castings more inoculation degree is required to promote graphite formation, which will ultimately suppress carbides precipitation. The results obtained from the cooling curve analysis are in agreement with the actual properties of SGI casting.
