In part I of this paper, we presented two efficient front‐tracking methods to simulate the growth of a spherulite within an imposed temperature field. In this second part we present a method that predicts the final microstructure in a macroscopic part by coupling these front‐tracking techniques with (a) a stochastic model for the nucleation of individual spherulites, (b) a cellular model for spherulite impingement and solid fraction evolution and (c) a Finite Difference Method (FDM) for latent heat release and heat diffusion. The method tracks the physical phenomena on several length scales: a course grid for the heat diffusion, a fine grid for solid fraction evolution and a very fine grid for the shape of the individual spherulites and the lamellae within them. To our knowledge this is the first time that fully coupled multiscale model has been applied to the solidification of polymers which gives realistic microstructure evolution, orientation of the different lamellae within spherulites and maps of the solid fraction and temperature fields during solidification. The model provides us with a quantitative predictive tool that can be used to optimize industrial processes.
In this two‐part paper, we present a model for the solidification of semicrystalline thermoplastic polymers that links the microscopic and macroscopic length scales. The model accounts for the important physical phenomena occurring during spherulitic cyrstallization and predicts microstructural evolution. In this first part, we concentrate on the growth of individual spherulites. We present a fast and accurate model that predicts the shape of a spherulite as well as the path of its constitutive lamellae in any thermal situation. In part II of this paper we shall couple this new model for spherulite growth with a nucleation law and a macroscopic heat flow computation, thus enabling us to model realistic crystallization conditions.
SUMMARYWe describe the implementation of a short-range parallel molecular dynamics (MD) code, SPaSM, on the heterogeneous general-purpose Roadrunner supercomputer. Each Roadrunner 'TriBlade' compute node consists of two AMD Opteron dual-core microprocessors and four IBM PowerXCell 8i enhanced Cell microprocessors (each consisting of one PPU and eight SPU cores), so that there are four MPI ranks per node, each with one Opteron and one Cell. We will briefly describe the Roadrunner architecture and some of the initial hybrid programming approaches that have been taken, focusing on the SPaSM application as a case study. An initial 'evolutionary' port, in which the existing legacy code runs with minor modifications on the Opterons and the Cells are only used to compute interatomic forces, achieves roughly a 2× speedup over the unaccelerated code. On the other hand, our 'revolutionary' implementation adopts a Cell-centric view, with data structures optimized for, and living on, the Cells. The Opterons are mainly used to direct inter-rank communication and perform I/O-heavy periodic analysis, visualization, and checkpointing tasks. The performance measured for our initial implementation of a standard LennardJones pair potential benchmark reached a peak of 369 Tflop/s double-precision floating-point performance on the full Roadrunner system (27.7% of peak), nearly 10× faster than the unaccelerated (Opteron-only) version.
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