Adaptive Mesh Refinement Computation of Solidification Microstructures Using Dynamic Data Structures
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abstract
We study the evolution of solidification microstructures using a phase-field
model computed on an adaptive, finite element grid. We discuss the details of
our algorithm and show that it greatly reduces the computational cost of
solving the phase-field model at low undercooling. In particular we show that
the computational complexity of solving any phase-boundary problem scales with
the interface arclength when using an adapting mesh. Moreover, the use of
dynamic data structures allows us to simulate system sizes corresponding to
experimental conditions, which would otherwise require lattices greater that
$2^{17}\times 2^{17}$ elements. We examine the convergence properties of our
algorithm. We also present two dimensional, time-dependent calculations of
dendritic evolution, with and without surface tension anisotropy. We benchmark
our results for dendritic growth with microscopic solvability theory, finding
them to be in good agreement with theory for high undercoolings. At low
undercooling, however, we obtain higher values of velocity than solvability
theory at low undercooling, where transients dominate, in accord with a
heuristic criterion which we derive.
