Modelling of volumes in cast iron solidification to predict shrinkage and expansion defects

Svensson, Ingvar L; Dugic, Izudin

doi:10.1080/13640461.1999.11819322

Cited by 10 publications

(8 citation statements)

References 7 publications

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“…In Figure 7, the cooling curves and the calculated sample volume variation based on the measured displacements are plotted as a function of the fraction solid calculated by FTA. [38], ρ according to [39]. The parameter T 1 denotes the cooling curve registered from the geometrical centrum of the spherical sample, T 2 denotes the average of the temperatures measured on the surface of the sample.…”

Section: Resultsmentioning

confidence: 99%

Extended Method of Volume Change Measurements during Solidification of Lamellar Graphite Iron

Svidró

Diószegi

Jönsson

2018

MSF

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Abstract. Lamellar graphite iron (LGI) is an important technical alloy used to produce cast components for the automotive and the marine industry. The performance of the component is defined by the solidification sequence. Therefore, a lot of research work has been done in the field of solidification. The present work introduces a new measurement approach that combines advanced dilatation measurements with thermal analysis to investigate the solidification of LGI. The method involves a thermally balanced spherical sample. The temperature values are measured in the geometrical center and on the surface of the sample. The released heat of solidification is calculated by using the Fourier Thermal Analysis (FTA) method. The displacement values are measured on the surface of the sample. The volume change is calculated from the displacement data. The dilatation results clearly shows the advantage of the multidirectional measurement.

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Section: Resultsmentioning

confidence: 99%

Extended Method of Volume Change Measurements during Solidification of Lamellar Graphite Iron

Svidró

Diószegi

Jönsson

2018

MSF

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“…Furthermore, this defines the species gradient and therefore the diffusive flux at the solid-liquid interface, which is in turn defines the change in solid fraction according to Equation (7). Therefore, the diffusion solver is tested by application to a simple diffusion problem for which an analytical solution exists.…”

Section: Validation and Database Selectionmentioning

confidence: 99%

“…Lacaze found that pronounced microsegregations build up on solidification. Svensson and Dugic [7] demonstrated that it is possible to calculate an average density of the phase mixture (liquid and solid phases) by using molar volumes of each phase and molar masses of the elements in order to predict the shrinkage behavior of cast iron. Celentano et al [8] coupled a macroscopic finite element method (FEM) temperature solver with a microsegregation model for ductile iron by considering nucleation and diffusion-controlled growth, which is determined by the carbon and silicon diffusion.…”

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confidence: 99%

Modeling the Porosity Formation in Austenitic SGI Castings by Using a Physics‐Based Material Model

et al. 2010

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On solidification, microsegregations build up in solid phases due to changes in solid concentrations with temperature. Diffusion, which is a kinetic process, usually reduces the occurrence of microsegregations. This work is aimed at modeling such kinetic effects on the solidification of austenitic cast iron, using a holistic approach. For this purpose, a microsegregation model is developed and validated. Moreover, this model is directly coupled to a commercial process‐simulation tool and thermodynamic software. A series of GJSA‐XNiCr 20‐2 clamp‐rings is cast by varying the inoculation state and the number of feeders. The composition of this cast alloy is analyzed and the microstructure characterized to provide input data for the microsegregation model. In order to validate the software, cooling curves are recorded; differential thermal analysis, electron dispersive X‐ray analysis and electron probe micro analysis are carried out. Furthermore, the porosity within the casting is analyzed by X‐ray. By performing coupled simulations, the different cooling characteristics within the casting lead to pronounced differences in phase fractions and solidification temperatures which are due to dendrite arm coarsening. The hot spot effect below the feeders is assisted by a shift towards lower solidification temperatures over the solidification time. This shift is a result of the local cooling characteristics, which can only be predicted when process simulation is directly coupled with material simulation. The porosity predictions and the porosity analysis exhibit good agreement. A comparison between experimental and virtual cooling curves closes, implying that the novel coupling concept and its implementation are valid.

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“…[1][2][3] However, these methods should be improved and verified with real castings further. In the authors' former research, a method to predict macro porosity of the casting considering microstructure formation was forwarded, and was applied to two practical castings.…”

Section: Introductionmentioning

confidence: 99%

Simulation of feeding flow and prediction of macro porosity of SGI casting based on microstructure formation

Zhao¹,

Liu²

2007

International Journal of Cast Metals Research

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Based on the model of microstructure formation of spheroidal graphite iron (SGI) casting which includes continuous nucleation and growth of graphite nodules, carbides and austenite, a method was proposed to calculate the feeding flow during solidification processes by considering mass conservation and using Darcy's laws. The method takes into account liquid shrinkage as well as shrinkage and expansion caused by different phase formation, and can calculate the flow in liquid and mushy regions. According to calculation of the flow, macro porosity formation could be described through treating free surfaces and boundary of the regions. The proposed method has been applied to an automotive wheel hub SGI casting with two different processing cases. The feeding flow during the casting solidification with two cases, especially in isolated regions, was investigated and discussed. With the flow calculation, expansion or shrinkage of liquid or mushy regions might be judged, which could offer important information for evaluating formation of macro porosity. The results of macro porosity prediction were compared with results of practical castings. It is indicated that two results were in quite good agreement, and the method could predict macro porosity formation more accurately.

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Modelling of volumes in cast iron solidification to predict shrinkage and expansion defects

Cited by 10 publications

References 7 publications

Extended Method of Volume Change Measurements during Solidification of Lamellar Graphite Iron

Extended Method of Volume Change Measurements during Solidification of Lamellar Graphite Iron

Modeling the Porosity Formation in Austenitic SGI Castings by Using a Physics‐Based Material Model

Simulation of feeding flow and prediction of macro porosity of SGI casting based on microstructure formation

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