CAREER: Multi-Level Multi-Material Problem Solver Environment with Semisolid Material Applications and Education

Worcester Polytechnic Institute, Worcester MA

Investigators

Abstract

There have been substantial developments in computational methods and capabilities for material sciences applications. These include the theory and practice of material point methods (MPM), multiple temporal and spatial scale methods, domain decomposition methods, together with increases in memory capacities, processing rates, and software capabilities for distributed computing. We will develop and combine these methods and capabilities in a Multi-Level Multi-Material Problem Solver Environment (MLMM PSE). The MLMM PSE will target applications such as crack propagation, granular materials, impact problems, fragmentation, damages among others. We will demonstrate the PSE for a novel and important engineering application in semisolid materials. The complexity inherent in this combination demands a computational framework that provides broad-based infrastructure. As a {\it computational aim} of this project we will construct this infrastructure in the MLMM PSE for material sciences applications. We will create effective computational modules and interfaces that will be necessary to build the MLMM PSE. These modules will be integrated with parallel AMR and nonlinear solvers libraries, which will facilitate code development, efficiency, load balancing and portability on a variety of parallel platforms and will support visualization capabilities. As a {\it theoretical aim}, we will design, analyze, and develop innovative numerical methods to enhance accuracy, efficiency, scalability and robustness of the MLMM PSE. We will investigate hierarchical simulation involving explicit and implicit time dependent adaptive grid and particle refinement. This important and novel area presents considerable mathematical and computational challenges. As an {\it educational aim}, we will develop with undergraduate students web-based MLMM PSE courseware that illustrates the computational solution of problems that have arisen in our research.