English   español  
Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/51191
logo share SHARE logo core CORE   Add this article to your Mendeley library MendeleyBASE

Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL
Exportar a otros formatos:

A self-organizing-map approach to chemistry representation in combustion applications

AuthorsBlasco, J.; Fueyo, Norberto; Dopazo, C.; Chen, J.-Y.
Issue Date2000
PublisherInstitute of Physics Publishing
CitationCombustion Theory and Modelling 4: 61-76 (2000)
AbstractSeveral alternative techniques have been proposed in the literature in order to avoid the CPU-intensive numerical integration of the thermochemical equations in the simulation of combustion processes. The present paper introduces a new approach, which is based on two artificial neural-network (ANN) paradigms, namely the self-organizing map (SOM) and the multilayer perceptron (MLP). The SOM is first employed for the automatic partitioning of the thermochemical space into subdomains. Then, a specialized MLP is trained in order to fit the thermochemical points belonging to a given subdomain. The presented strategy is tested on a partially stirred reactor (PaSR) with a reduced methane-air mechanism, and encouraging results are reported. The relatively modest CPU-time and memory requirements of the method make the SOM-MLP approach a promising technique for the inclusion of large chemical mechanisms in the context of complex applications, such as the multidimensional simulation of combustion.
Identifiersdoi: 10.1088/1364-7830/4/1/304
issn: 1364-7830
Appears in Collections:(LIFTEC) Artículos
Files in This Item:
File Description SizeFormat 
accesoRestringido.pdf15,38 kBAdobe PDFThumbnail
Show full item record

Related articles:

WARNING: Items in Digital.CSIC are protected by copyright, with all rights reserved, unless otherwise indicated.