A common issue of loose coupling of multi-physics simulations arises from the necessity to analyse the same structure relying on different meshes, each one suited for a different field of physics. Output data from a simulation must be transferred as input to another model to run a new analysis. It is strongly desirable for such information transfer to be conservative in terms of load balance. A novel method for pressure mapping between dissimilar meshes is presented. Transfer procedure consists of two steps: pressure interpolation by means of Radial Basis Functions and Fuzzy Subsets correction. The first is a pointwise interpolation using a series of basis functions. The second phase applies to the outcome of the first one to restore balance between the two models by introducing a smooth correction field. Practical test cases from the aeronautical field are presented to validate the proposed method.
Chiappa, A., Biancolini, M.e., Cella, U., Giorgetti, F., Groth, C. (2016). A conservative pressure mapping method based on Radial Basis Functions and Fuzzy Subsets. ??????? it.cilea.surplus.oa.citation.tipologie.CitationProceedings.prensentedAt ??????? International CAE Conference 2016.
A conservative pressure mapping method based on Radial Basis Functions and Fuzzy Subsets
CHIAPPA, ANDREA;BIANCOLINI, MARCO EVANGELOS;CELLA, UBALDO;GIORGETTI, FRANCESCO;GROTH, CORRADO
2016-10-01
Abstract
A common issue of loose coupling of multi-physics simulations arises from the necessity to analyse the same structure relying on different meshes, each one suited for a different field of physics. Output data from a simulation must be transferred as input to another model to run a new analysis. It is strongly desirable for such information transfer to be conservative in terms of load balance. A novel method for pressure mapping between dissimilar meshes is presented. Transfer procedure consists of two steps: pressure interpolation by means of Radial Basis Functions and Fuzzy Subsets correction. The first is a pointwise interpolation using a series of basis functions. The second phase applies to the outcome of the first one to restore balance between the two models by introducing a smooth correction field. Practical test cases from the aeronautical field are presented to validate the proposed method.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.