Applicability and performance analysis of the phase-field modelling based on the Cahn-Hilliard method for the binary alloy

Applicability and performance analysis of the phase-field modelling based on the Cahn-Hilliard method for the binary alloys

Kamil Dudek, Danuta Szeliga

AGH University of Science and Technology, Faculty of Metals Engineering and Industrial Computer Science, Mickiewicza 30, 30-059 Krakow, Poland.

DOI:

https://doi.org/10.7494/cmms.2016.1.0558

Abstract:

The Cahn-Hilliard method descries the driving force of the process of phase separation. Considering a binary (two-phase) alloy of conserved composition variable, the C-H model makes it possible to trace the process at which the domain creates pure subdomains of each component. Gururajan et al. have offered a simplified reference implementation of the aforementioned model, using the C language and FFTW libraries. It allows to perform a reverse Fourier transform to acquire a domain composition profile at a given time. Being a proof-of-concept, this approach does not stress on performance and the dedicated tools, like OpenPhase might not provide the flexibility necessary for new implementations. The following work aims on analyzing the C-H algorithm with regards of optimization, taking the Gururajan, among others, as a reference problem. Utilizing the models accompanied by replicable results facilitates the analysis of FFTW and GSL libraries, answering whether to search the replacement implementations and where (if necessary) work on code performance and parallelization. Finally, the improved model is intended to be used on external (non-random) initial composition, taken from ongoing simulations, in hope of preparation of the pearlitic steel model in the future.

Cite as:

Dudek, K., Szeliga, D. (2016). Applicability and performance analysis of the phase-field modelling based on the Cahn-Hilliard method for the binary alloys. Computer Methods in Materials Science, 16(1), 37 – 46. https://doi.org/10.7494/cmms.2016.1.0558

Article (PDF):

Keywords:

Imaging, Visualization, Iipsrv, Modelling

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