In this study, we present adaptive moving boundary computation technique with parallel implementation on a distributed memory multi-processor system for large scale thermo-fluid and interfacial flow computations. The ...In this study, we present adaptive moving boundary computation technique with parallel implementation on a distributed memory multi-processor system for large scale thermo-fluid and interfacial flow computations. The solver utilizes Eulerian-Lagrangian method to track moving （Lagrangian） interfaces explicitly on the stationary （Eulerian） Cartesian grid where the flow fields are computed. We address the domain decomposition strategies of Eulerian- Lagrangian method by illustrating its intricate complexity of the computation involved on two different spaces inter- actively and consequently, and then propose a trade-off ap- proach aiming for parallel scalability. Spatial domain decomposition is adopted for both Eulerian and Lagrangian do- main due to easy load balancing and data locality for mini- mum communication between processors. In addition, parallel cell-based unstructured adaptive mesh refinement （AMR） technique is implemented for the flexible local refinement and even-distributed computational workload among processors. Selected cases are presented to highlight the computa- tional capabilities, including Faraday type interfacial waves with capillary and gravitational forcing, flows around varied geometric configurations and induced by boundary conditions and/or body forces, and thermo-fluid dynamics with phase change. With the aid of the present techniques, large scale challenging moving boundary problems can be effectively addressed.展开更多
基金supported by NASA Constellation University Institutes Program (CUIP), Claudia Meyer program manager
文摘In this study, we present adaptive moving boundary computation technique with parallel implementation on a distributed memory multi-processor system for large scale thermo-fluid and interfacial flow computations. The solver utilizes Eulerian-Lagrangian method to track moving （Lagrangian） interfaces explicitly on the stationary （Eulerian） Cartesian grid where the flow fields are computed. We address the domain decomposition strategies of Eulerian- Lagrangian method by illustrating its intricate complexity of the computation involved on two different spaces inter- actively and consequently, and then propose a trade-off ap- proach aiming for parallel scalability. Spatial domain decomposition is adopted for both Eulerian and Lagrangian do- main due to easy load balancing and data locality for mini- mum communication between processors. In addition, parallel cell-based unstructured adaptive mesh refinement （AMR） technique is implemented for the flexible local refinement and even-distributed computational workload among processors. Selected cases are presented to highlight the computa- tional capabilities, including Faraday type interfacial waves with capillary and gravitational forcing, flows around varied geometric configurations and induced by boundary conditions and/or body forces, and thermo-fluid dynamics with phase change. With the aid of the present techniques, large scale challenging moving boundary problems can be effectively addressed.
