Enhancement of the Mixing Efficiency for a Steam Boiler Premix Channel with a Surrogate Based Optimization

Abstract

Global warming and the ever-increasing pollutants in the atmosphere force many governments to limit emissions. The use of methane as a fuel is widespread in the boiler industry, due to the low pollutant levels in its exhaust gas products. Nevertheless, in the combustion process, nitrogen and oxygen bind giving rise to a series of molecular compounds called NO x, which are considered pollutants because they react in the atmosphere causing the production of acid rain and reducing the level of ozone [1]. The aim of this work is to improve the mixture quality between fresh air, methane and recirculated exhaust gases introduced within Ecovapor Boiler's Mixing-Channel and, as consequence, to increase the combustion quality and limit the pollution production. The geometry is parameterized within Ansys Space Claim CAD software [2], and gas mixture flow is computed with Ansys Fluent solver [3]. To achieve these goals an automated shape optimization is adopted, which couples the Ansys Workbench environment to Dakota software [4]. In particular, a multi-objective genetic algorithm (MOGA) [5] combined with the Kriging response surface method is used, while the geometries are evaluated by solving for a compressible mixture of non-reacting gases the steady-state Reynolds Average NavierStokes (RANS) equations coupled with the kRealizable turbulence model [6].

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