Adaptive Mesh Refinement for Multiphysics Applications
Mesh generation is a crucial first step for the solution of multi-dimensional problems in field simulation. The accuracy and convergence of computational solutions of mesh-based methods is strongly dependent on the quality of the mesh used. Mesh generation lies at the core of many areas in advanced computational sciences and engineering and has emerged as an enabling technology and a major pacing item in computational modeling and simulation. In particular, adaptive mesh optimization and refinement plays an important role in complex high-fidelity simulation fields. Generation of a quality mesh to support these calculations is a challenging, multi-disciplinary problem.
Oak Ridge National Laboratory (ORNL) has developed methods for generating and optimizing meshes that are comprised of elements of arbitrary polygonal and polyhedral type. In addition, ongoing research within the Computational Mathematics Group at ORNL includes the development of adaptive meshing technology tailored to application areas relevant to other simulation fields. The adaptive meshing approach and its underlying methods can be attractive to many application areas when solving three-dimensional, multi-physics, multi-scale, and time-dependent problems. ORNL has successfully introduced its hybrid meshing and adaptivity to climate modeling, astrophysics simulation, neutronics, modern reactor modeling and simulation.
ORNL’s capability is also geared for generating high-quality adaptive meshes for petascale applications. The advent of petascale computing creates new opportunities for representation of realistic geometries via meshing at an unprecedented fidelity. ORNL’s efforts focus is on developing advanced scalable interoperable software associated with geometry, mesh, adaptivity, and field transformation. It also provides the necessary meshing tools to reach new levels of understanding through the use of high-fidelity calculations based on multiple coupled physical processes and multiple interacting physical scales.
Hybrid meshing and adaptivity for multi-material multi-physics simulations
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