DocumentCode
2415826
Title
Two-dimensional compressible flow simulation on emulated digital CNN-UM
Author
Kocsárdi, Sándor ; Nagy, Zoltán ; Csík, Á Rpád ; Szolgay, Péter
Author_Institution
Dept. of Image Process. & Neurocomputing, Univ. of Pannonia, Veszprem
fYear
2008
fDate
14-16 July 2008
Firstpage
169
Lastpage
174
Abstract
In the area of mechanical, aerospace, chemical and civil engineering the solution of partial differential equations (PDEs) has been one of the most important problems of mathematics for a long time. In this field, one of the most exciting areas is the simulation of fluid flow, which involves for example problems of air, sea and land vehicle motion. In this paper a CNN-UM based solver of 2D inviscid, adiabatic, compressible fluids will be presented. The governing equations are solved by using first- and second-order numerical methods. Unfortunately the necessity the coupled multi-layered computational structure with non-linear, space-variant templates does not make it possible to utilize the huge computing power of the analog CNN-UM chips. To improve the performance of our solution emulated digital CNN-UM implemented on FPGA has been used. Properties of the implemented specialized architecture is examined in terms of area, speed and accuracy.
Keywords
cellular neural nets; compressible flow; computational fluid dynamics; field programmable gate arrays; flow simulation; partial differential equations; FPGA; PDE; emulated digital CNN-UM; numerical method; partial differential equation; two-dimensional compressible fluid flow simulation; Aerospace engineering; Analog computers; Chemical engineering; Civil engineering; Computational modeling; Fluid flow; Land vehicles; Mathematics; Nonlinear equations; Partial differential equations;
fLanguage
English
Publisher
ieee
Conference_Titel
Cellular Neural Networks and Their Applications, 2008. CNNA 2008. 11th International Workshop on
Conference_Location
Santiago de Compostela
Print_ISBN
978-1-4244-2089-6
Electronic_ISBN
978-1-4244-2090-2
Type
conf
DOI
10.1109/CNNA.2008.4588672
Filename
4588672
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