The 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, car ried 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.

A multi-objective design optimization strategy as applied to pre-mixedpre-vaporized injection systems for low emission combustors

MANNA, MARCELLO
;
2010

Abstract

The 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, car ried 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.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/371986
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