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

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 NO_X 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.