Modeling almost incompressible fluid flow with CNN

Research output: Contribution to conferencesPaperContributedpeer-review

Contributors

  • F. Puffer - , University Hospital Frankfurt (Author)
  • R. Tetzlaff - , University Hospital Frankfurt (Author)
  • Dietrich Wolf - , University Hospital Frankfurt (Author)

Abstract

A novel method for transferring the Navier-Stokes-equations for two-dimensional almost incompressible, viscous flow to CNN is discussed. The problem has been treated in previous works, where the CNN layer that represents the pressure had to perform on a much faster time-scale than the layers representing the velocity components. This is a drawback, especially when hardware realizations are considered. The method presented in this contribution avoids the use of a double time-scale CNN and requires fewer connections between the cells. The treatment of boundary conditions is discussed and the accuracy of the results is determined for two known analytical solutions.

Details

Original languageEnglish
Pages78-82
Number of pages5
Publication statusPublished - 1998
Peer-reviewedYes
Externally publishedYes

Conference

TitleProceedings of the 1998 5th IEEE International Workshop on Cellular Neural Networks and Their Applications, CNNA
Duration14 - 17 April 1998
CityLondon, UK

External IDs

ORCID /0000-0001-7436-0103/work/142240254

Keywords

ASJC Scopus subject areas