This paper presents a numerical analysis of gas flow in the annular combustion chamber of a Proto X-3 Bioenergy micro gas turbine for green building applications. The computational fluids dynamics (CFD) simulation was conducted in two dimensions, turbulent flow and gas phase combustion, with the goal of comparing the effects of different models in real conditions. Two different turbulence models, standard (STD) k-ε and renormalization group (RNG) k-ε, were applied for simulations. The fuel used was biogas produced from animal waste. Fuel consumption was assumed to be 100 kJ/s for simulations. The results of the simulations were analyzed and compared for reference. The temperature and the mass fraction of CH 4 , H 2 , O 2 , and CO 2 distributions gave almost the same results for both models; therefore, both models (STD k-ε and RNG k-ε) could be used to represent the combustion process phenomenon without many significant differences.
This study uses biogas, an environmentally friendly renewable energy resource, to operate the prototype of a micro-gas turbine (MGT) system called the Proto X-3 Bioenergy Micro-gas Turbine, designed for green building application. The biogas is produced by an anaerobic digester. The aim of this research is to simulate slurry flow in an anaerobic digester as the basis for developing a biogas digester that will produce biogas to meet the requirements of the Proto X-3 Bioenergy Micro-gas Turbine. The digester is a rectangular type with 3.4 m 3 capacity. The flow calculations and simulations were done using Computational Fluid Dynamics (CFD) methods in two-dimensional, body-fitted coordinate mesh. The simulations were conducted with various baffle clearances for the digester: 50 mm, 100 mm, and 150 mm. The CFD simulations showed that the recirculation phenomena was found in all flows but that the 50-mm baffle clearance model had the largest recirculation, and it would lead to better mixing of the slurry.
As an initial analysis, numerical simulation has more advantages in saving time and costs regarding experiments. For example, variations in flow conditions and geometry can be adjusted easily to obtain results. Computational fluid dynamics (CFD) methods, such as the k-ε model, renormalization group (RNG) k-ε model and reynolds stress model (RSM), are widely used to conduct research on different objects and conditions. Choosing the appropriate model helps produce and develop constant values. Modeling studies as appropriate, i.e., in the turbulent flow simulation in the wind tunnel, is done to get a more accurate result. This study was conducted by comparing the results of the simulation k-ε model, RNG k-ε model and RSM, which is validated by the test results. The air had a density of 1,205 kg/m 3 , a viscosity of 4×10 -5 m 2 /s and a normal speed of 6 m/s. By comparing the simulation results of the k-ε model, RNG k-ε model and RSM, which is validated by the test results, the third turbulence model provided good results to predict the distribution of speed and pressure of the fluid flow in the wind tunnel. As for predicting the turbulent kinetic energy, turbulent dissipation rate and turbulent effective viscosity, the k-ε model was effectively used with comparable results to the RSM models.
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