Modeling almost incompressible fluid flow with CNN
Research output: Contribution to conferences › Paper › Contributed › peer-review
Contributors
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 language | English |
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Pages | 78-82 |
Number of pages | 5 |
Publication status | Published - 1998 |
Peer-reviewed | Yes |
Externally published | Yes |
Conference
Title | Proceedings of the 1998 5th IEEE International Workshop on Cellular Neural Networks and Their Applications, CNNA |
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Duration | 14 - 17 April 1998 |
City | London, UK |
External IDs
ORCID | /0000-0001-7436-0103/work/142240254 |
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