In recent years,Fourier spectral methods have emerged as competitive numerical methods for large-scale phase field simulations of microstructures in computational materials sciences.To further improve their effectiven...In recent years,Fourier spectral methods have emerged as competitive numerical methods for large-scale phase field simulations of microstructures in computational materials sciences.To further improve their effectiveness,we recently developed a new adaptive Fourier-spectral semi-implicit method(AFSIM)for solving the phase field equation by combining an adaptive moving mesh method and the semi-implicit Fourier spectral algorithm.In this paper,we present the application of AFSIM to the Cahn-Hilliard equation with inhomogeneous,anisotropic elasticity.Numerical implementations and test examples in both two and three dimensions are considered with a particular illustration using the well-studied example of mis-fitting particles in a solid as they approach to their equilibrium shapes.It is shown that significant savings in memory and computational time is achieved while accurate solutions are preserved.展开更多
基金This work has been supported by the National Science Foundation Information Technol-ogy Research Project(NSF-ITR)through Grant DMR-0205232The work of Qiang Du is also supported by NSF-DMS 0712744.
文摘In recent years,Fourier spectral methods have emerged as competitive numerical methods for large-scale phase field simulations of microstructures in computational materials sciences.To further improve their effectiveness,we recently developed a new adaptive Fourier-spectral semi-implicit method(AFSIM)for solving the phase field equation by combining an adaptive moving mesh method and the semi-implicit Fourier spectral algorithm.In this paper,we present the application of AFSIM to the Cahn-Hilliard equation with inhomogeneous,anisotropic elasticity.Numerical implementations and test examples in both two and three dimensions are considered with a particular illustration using the well-studied example of mis-fitting particles in a solid as they approach to their equilibrium shapes.It is shown that significant savings in memory and computational time is achieved while accurate solutions are preserved.
