Reducing the CO emissions in a laminar burner using different numerical optimization methods

Abstract

In this work, the optimization of the flame properties associated to a laminar burner is carried out using different optimization methods (genetic algorithm, Simplex) when varying the fuel/air ratio in a primary and a secondary inlet. The objective is to reduce the CO emission at a prescribed distance from the injection plane. An in-house computer package, called OPAL, controls the optimization process in a fully automatic manner. The flow involving chemical reactions is solved using the in-house computational fluid dynamics code UGC+.

Multi-objective optimization of the airfoil shape of Wells turbine used for wave energy conversion

“…We therefore employ our own optimization library, OPAL (OPtimization ALgorithms), containing many different optimization techniques. OPAL has already been coupled in the past with different CFD solvers (in-house codes, ANSYS-Fluent, ANSYS-CFX) and has been employed successfully to improve a variety of applications, for example heat exchangers [38], burners [39] or turbomachines [22,40e42]. For configurations involving concurrent objectives, Evolutionary Algorithms are particularly robust and have therefore been used in the present study.…”

Automatic Blade Shape Optimization of a Three-Bladed Modified Savonius Turbine

“…Our own optimization library is employed in this study, called OPtimization ALgorithms (OPAL), containing several optimization methodologies. OPAL had already been used with different computational fluid dynamic solvers (in-house codes, CFX, and ANSYS Fluent), and it was utilized successfully to enhance a variety of implementations, such as heat exchangers (Hilbert et al, 2006), turbomachines (Mohamed et al, 2008a;Mohamed et al, 2008b;Mohamed et al, 2010;Mohamed et al, 2011), or burners (Thévenin et al, 2005;Janiga and Thévenin, 2007).…”

“…After every generation, the optimizer takes a decision with the new generation with new input parameters after studying the stored results from the old generation. This sequence of mathematical optimization and coupling with CFD codes is very complex, and some previous studies described the procedure in detail, for example, Thévenin et al (2005), Hilbert et al (2006), Janiga and Thévenin (2007), .…”

Adjoint-based optimization in the development of low-emission industrial boilers

“…In general, similar methods have also been used extensively in the broader field of combustion optimization. For example, Janiga and Thévenin (2007) reduced the CO emissions in a laminar burner CONTACT G. Kanellis georgios.kanellis@tuni.fi using genetic algorithms and also the SIMPLEX method. Also, Liu and Bansal (2014) improved a boiler's heat transfer while at the same time decreasing the probabilities for slagging by combining the multiobjective optimization NSGA algorithm with CFD modelling.…”