A multi-objective design optimization strategy as applied to pre-mixed pre-vaporized injection systems for low emission combustors
| Autor: | P. Di Martino, Marcello Manna, S. Colantuoni, M. Laraia |
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| Přispěvatelé: | M., Laraia, Manna, Marcello, S., Colantuoni, P., Di Martino |
| Rok vydání: | 2010 |
| Předmět: |
Artificial neural network
Computer science business.industry General Chemical Engineering General Physics and Astronomy Energy Engineering and Power Technology design optimization General Chemistry Computational fluid dynamics computer.software_genre pollutant emission Expert system gas turbine combustor Fuel Technology Modeling and Simulation Low emission Viscous flow State space Combustion chamber Process engineering business computer NOx |
| Zdroj: | Combustion Theory and Modelling. 14:203-233 |
| ISSN: | 1741-3559 1364-7830 |
| Popis: | This paper presents a multi-objective optimization procedure as applied to the design of the injection system of a Lean Pre-mixed Pre-vaporized combustion chamber. The optimizer drives an Artificial Neural Network in a repeated analysis scheme in order to simultaneously reduce NOX and CO pollutant emissions. The ANN is trained with a few three-dimensional high resolution reactive viscous flow simulations, carried out with a reliable and robust CFD code. Results, obtained in a four-dimensional state space, demonstrate the validity of the overall procedure with truly moderate computational costs. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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