Vijay Mahadevan
Vijay Mahadevan
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MOAB
Improving climate model coupling through a complete mesh representation: a case study with E3SM (v1) and MOAB (v5.x)
Accurate climate modeling of coupled Earth systems requires mapping of solution field data between dependent components that use non-matching discrete meshes. While existing workflows provide a pathway to generate the projection weights as an offline step, severe bottlenecks impede flexible setup of high-resolution models. In this paper, we present new algorithmic approaches to simplify the E3SM computational workflow using a scalable software infrastructure to generate the remapping operators.
Vijay S. Mahadevan
,
Iulian Grindeanu
,
Robert Jacob
,
Jason Sarich
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Array-based, parallel hierarchical mesh refinement algorithms for unstructured meshes
A multi-degree, multi-dimensional and multi-level array-based hierarchical mesh refinement capability through uniform refinement of unstructured meshes for efficient solution of PDE’s using finite element methods and multigrid solvers is presented. The framework is designed to generate nested hierarchies from an initial coarse mesh that can be used for a variety of purposes such as in multigrid solvers/preconditioners, to do solution convergence and verification studies and to improve overall parallel efficiency by decreasing I/O bandwidth requirements.
Navamita Ray
,
Iulian Grindeanu
,
Xinglin Zhao
,
Vijay S. Mahadevan
,
Xiangmin Jiao
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High-resolution coupled physics solvers for analysing fine-scale nuclear reactor design problems
An integrated multi-physics simulation capability for the design and analysis of current and future nuclear reactor models is being investigated, to tightly couple neutron transport and thermal-hydraulics physics under the SHARP framework. Over several years, high-fidelity, validated mono-physics solvers with proven scalability on petascale architectures have been developed independently. Based on a unified component-based architecture, these existing codes can be coupled with a mesh-data backplane and a flexible coupling-strategy-based driver suite to produce a viable tool for analysts.
Vijay S. Mahadevan
,
Elia Merzari
,
Timothy Tautges
,
Rajeev Jain
,
Aleksandr Obabko
,
Michael Smith
,
Paul Fischer
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