A common issue in multiphysics analysis regards a reliable way for loose couplings, because the same object is modeled using different mesh refinements, each one suited for a proper field of physics. Output data originating from a simulation environment are transferred as input data to a different model to run a new analysis. It is strongly desirable that such information transfers in a conservative way in terms of general balance. This paper faces the problem of pressure mapping between widely dissimilar meshes. The proposed procedure yields two steps: pressure interpolation by means of radial basis functions and fuzzy subset correction. The first step is pointwise interpolation that exploits a series of basis functions. The second step applies to the outcome of the first one to reestablish load balance between the two models through the introduction of a smooth correction field. Practical tests from the aeronautical field allow validating the method.
Biancolini, M.e., Chiappa, A., Giorgetti, F., Groth, C., Cella, U., Salvini, P. (2018). A balanced load mapping method based on radial basis functions and fuzzy sets. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, 115(12), 1411-1429 [10.1002/nme.5850].
A balanced load mapping method based on radial basis functions and fuzzy sets
Biancolini, M. E.;Chiappa, A.;Giorgetti, F.;Groth, C.;Cella, U.;Salvini, P.
2018-01-01
Abstract
A common issue in multiphysics analysis regards a reliable way for loose couplings, because the same object is modeled using different mesh refinements, each one suited for a proper field of physics. Output data originating from a simulation environment are transferred as input data to a different model to run a new analysis. It is strongly desirable that such information transfers in a conservative way in terms of general balance. This paper faces the problem of pressure mapping between widely dissimilar meshes. The proposed procedure yields two steps: pressure interpolation by means of radial basis functions and fuzzy subset correction. The first step is pointwise interpolation that exploits a series of basis functions. The second step applies to the outcome of the first one to reestablish load balance between the two models through the introduction of a smooth correction field. Practical tests from the aeronautical field allow validating the method.File | Dimensione | Formato | |
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