Quantifying uncertainty in the process-structure relationship for Al-Cu solidification

Anh Tran, Dehao Liu, Hoang Tran, Yan Wang

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

Phase field method (PFM) is a simulation tool to predict microstructural evolution during solidification and is helpful to establish the process-structure relationship for alloys. The robustness of the relationship however is affected by model-form and parameter uncertainties in PFM. In this paper, the uncertainty associated with the thermodynamic and process parameters of PFM is studied and quantified. Surrogate modeling is used to interpolate four quantities of interests (QoIs), including dendritic perimeter, area, primary arm length, and solute segregation, as functions of thermodynamic and process parameters. A sparse grid approach is applied to mitigate the curse-of-dimensionality computational burden in uncertainty quantification. Polynomial chaos expansion is employed to obtain the probability density functions of the QoIs. The effect of parameter uncertainty on the Al-Cu dendritic growth during solidification simulation are investigated. The results show that the dendritic morphology varies significantly with respect to the interface mobility and the initial temperature.

Original languageEnglish
Article number064005
JournalModelling and Simulation in Materials Science and Engineering
Volume27
Issue number6
DOIs
StatePublished - Jun 19 2019

Keywords

  • phase field method
  • polynomial chaos expansion
  • solidification
  • sparse grid
  • uncertainty quantification

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