¿&lt;i&gt;Adiaphora&lt;/i&gt; en San Agustín?

Svensson, Manfred

doi:10.1353/trd.2010.0003

Cited by 2 publications

(2 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The correct functionality of the diffusion solver is of great importance, since the shape of the microsegregation pattern is determined by diffusion. 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.…”

mentioning

confidence: 99%

See 1 more Smart Citation

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

et al. 2010

View full text Add to dashboard Cite

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.

show abstract

Section: Validation and Database Selectionmentioning

confidence: 99%

mentioning

confidence: 99%