Abstract

Low and medium solar heating systems used for domestic and industrial applications, such as water and space heating, usually utilize solar flat plate collectors in order to absorb solar thermal energy converting it into heat and then transferring the heat to a fluid (usually water or air) that flows through it. The aim of this study is to evaluate the solar flat plate collector’s efficiency and the fluid behavior inside the pipeline with three different cross sections, whose hydraulic diameters are 10, 5.12 and 6.16 mm, by using ANSYS Fluent. The results obtained from the Computational Fluid Dynamics (CFD) tool showed that the collector with the Type I cross section reached temperatures up to 330 K at the pipe outlet obtaining an efficiency of 68 %, higher than those of Types II and III, whose efficiencies were 51 % and 60 %, respectively. Type I cross section also presented the lowest values in both speed and pressure drop, these being 0.266 m/s and 108.3 Pa, respectively.

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].