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Title: In-memory integration of existing software components for parallel adaptive unstructured mesh workflows

Unstructured mesh methods, like finite elements and finite volumes, support the effective analysis of complex physical behaviors modeled by partial differential equations over general threedimensional domains. The most reliable and efficient methods apply adaptive procedures with a-posteriori error estimators that indicate where and how the mesh is to be modified. Although adaptive meshes can have two to three orders of magnitude fewer elements than a more uniform mesh for the same level of accuracy, there are many complex simulations where the meshes required are so large that they can only be solved on massively parallel systems.
 [1] ;  [1] ;  [1] ;  [2] ;  [1] ;  [3] ;  [1]
  1. Rensselaer Polytechnic Inst., Troy, NY (United States). Scientific Computation Research Center (SCOREC)
  2. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
  3. Univ. of Colorado, Boulder, CO (United States)
Publication Date:
Grant/Contract Number:
SC0013919; SC0006117; SC0014609; AC02-06CH11357
Accepted Manuscript
Journal Name:
Currency and Computation (Online)
Additional Journal Information:
Journal Name: Currency and Computation (Online); Conference: Proceedings of the XSEDE16 Conference, Miami, FL (United States), 19 Jul 2016
Research Org:
Simmetrix Inc., Clifton Park, NY (United States)
Sponsoring Org:
USDOE Office of Science (SC), Fusion Energy Sciences (FES) (SC-24); USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)
Country of Publication:
United States
97 MATHEMATICS AND COMPUTING; in-memory; parallel; unstructured mesh; workflow
OSTI Identifier: