Adaptive and Parallel Computational Techniques in Materials Science
Abstract
This Augmentation Award for Science and Engineering Research Training (AASERT) supported research students to work 0 adaptive and parallel computational techniques associated with crystal growth processing. This grant accompanied the AFOSR Multidisciplinary University Research Initiative (MURI) in crystal growth which is centered at the State University of New York at Stony Brook. Students conducted research on the following topics. Systems integration tools to enable the various software components to interact and, thus, address the simulation of the entire crystal-growth manufacturing process. Software for parallel adaptive computation that may be used by the crystal growth consortium to solve finite element and finite volume problems. The tools will be capable of solving transient and steady problems on serial and parallel computers using adaptive h-, p-, and r-refinement. Unstructured-grid flow analysis software that may be used to address problems in complex geometrical configuration, e.g., in the vicinity of the radiative heater of a Czochralski process.
Document Details
- Document Type
- Technical Report
- Publication Date
- May 31, 1998
- Accession Number
- ADA380813
Entities
People
- J. E. Flaherty
Organizations
- Rensselaer Polytechnic Institute