Since transient vehicle HVAC computational fluids (CFD) simulations take too long to solve in a production environment, the goal of this project is to automatically create a lumped-parameter flow network from a steady-state CFD that solves nearly instantaneously. The data mining algorithm k-means is implemented to automatically discover flow features and form the network (a reduced order model). The lumped-parameter network is implemented in the commercial thermal solver MuSES to then run as a fully transient simulation. Using this network a “localized heat transfer coefficient” is shown to be an improvement over existing techniques. Also, it was found that the use of the clustering created a new flow visualization technique. Finally, fixing clusters near equipment newly demonstrates a capability to track localized temperatures near specific objects (such as equipment in vehicles).
Reduction of Steady-State CFD HVAC Simulations into a Fully Transient Lumped Parameter Network
Sae International Journal of Passenger Cars. Mechanical Systems
Sae Int. J. Passeng. Cars - Mech. Syst
Sae International Journal of Passenger Cars - Mechanical Systems ; 7 , 1 ; 382-394
2014-05-10
13 pages
Conference paper
English
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