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).


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    Title :

    Reduction of Steady-State CFD HVAC Simulations into a Fully Transient Lumped Parameter Network


    Additional title:

    Sae International Journal of Passenger Cars. Mechanical Systems
    Sae Int. J. Passeng. Cars - Mech. Syst


    Contributors:


    Publication date :

    2014-05-10


    Size :

    13 pages




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English





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