Three-Dimensional Swirl Flow Velocity-Field Reconstruction Using A Neural Network With Radial Basis Functions  

Oleh:

Legentilhomme, P. ; Legrand, J. ; Pruvost, J.

Jenis: Article from Bulletin/Magazine
Dalam koleksi: Journal of Fluids Engineering vol. 123 no. 4 (2001), page 920-927.
Topik: NEURAL NETWORKS; three - dimensional; flow; velocity - field; neural network; radial basis functions

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: JJ89.4 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

Lihat Detail Induk

Isi artikel

For many studies, knowledge of continuous evolution of hydrodynamic characteristics is useful but generally measurement techniques provide only discrete information. In the case of complex flows, usual numerical interpolating methods appear to be not adapted, as for the free decaying swirling flow presented in this study. The three - dimensional motion involved induces a spatial dependent velocity - field. Thus, the interpolating method has to be three -dimensional and to take into account possible flow non linearity, making common methods unsuitable. A different interpolation method is thus proposed, based on a neural network algorithm with Radial Basis Functions.

Opini Anda

Klik untuk menuliskan opini Anda tentang koleksi ini!

Kembali