Grid Adaptive Computational Engine (GrACE). An adaptive computational engine infrastructure forms an effective basis for the development of adaptive methods for the solution of systems of partial differential equations for varied complex scientific application domains, including Grand Challenge problems. Parallel/distributed implementations of these adaptive methods offer the potential for the accurate solution of realistic models of important physical systems. This assumes greater importance as scientific simulations play an increasingly critical role in all areas of science and engineering. The simulations of expensive scientific problems are necessary to validate and justify the investment to be made.
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References in zbMATH (referenced in 5 articles )
Showing results 1 to 5 of 5.
- Jiang, Chaowei; Cui, Shuxin; Feng, Xueshang: Solving the Euler and Navier-Stokes equations by the AMR-CESE method (2012)
- Ray, J.; Armstrong, R.; Safta, C.; Debusschere, B. J.; Allan, B. A.; Najm, H. N.: Computational frameworks for advanced combustion simulations (2011)
- Henshaw, William D.; Schwendeman, Donald W.: Parallel computation of three-dimensional flows using overlapping grids with adaptive mesh refinement (2008)
- Chandra, Sumir; Parashar, Manish: Addressing spatiotemporal and computational heterogeneity in structured adaptive mesh refinement (2006) ioport
- Hornung, Richard D.; Kohn, Scott R.: Managing application complexity in the SAMRAI object-oriented framework (2002)
Further publications can be found at: http://nsfcac.rutgers.edu/TASSL/Projects/GrACE/pubs.html