Abstract
This paper describes a coupling framework for parallel execution of different solvers for multi-physics and multi-domain simulations with an arbitrary number of adjacent zones connected by different physical or overlapping interfaces. The coupling architecture is based on the execution of several instances of the same coupling code and relies on the use of smart edges (i.e., separate processes) dedicated to managing the exchange of information between two adjacent regions. The collection of solvers and coupling sessions forms a flexible and modular system, where the data exchange is handled by independent servers that are dedicated to a single interface connecting two solvers’ sessions. Accuracy and performance of the strategy is considered for turbomachinery applications involving Conjugate Heat Transfer (CHT) analysis and Sliding Plane (SP) interfaces.
Highlights
Framework for Multi-DomainFuture simulation technologies will increasingly rely on the capability to perform flexible coupling between existing solvers
The amount of coolant introduced in Stator Well 2 is relatively smaller, and the jet with cold air appears to be all sucked into the labyrinth seal
We have presented a high-performance inter-code coupling framework for distributed execution of coupled multi-physics solvers using the suite of CFD Hydra codes as an example
Summary
Future simulation technologies will increasingly rely on the capability to perform flexible coupling between existing solvers. The growing importance of similar requirements, combined with the modularity available in a modern simulation environment, naturally suggest the need for some capability allowing for coupling of these individual physical modules, discretisation techniques, or mixed fidelity methods Good examples of this approach are the CEDRE software package [8] developed at ONERA and the zonal flow solver of Schröder and his group [9,10]. One has to consider the case where the mutual interaction between two distinct solvers involves a significant amount of computational work Operations such as searching algorithms, interpolating, filtering, or reading from an external database may all be required by the coupling. The scalability characteristics of JMxx are examined for a model problem, and the parallel performance is discussed for a test case involving a sliding plane interface
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