Optimization of a cyclone combustor in a flameless combustion using producer gas

Flameless combustion of producer gas offers significant environmental and efficiency advantages, but its implementation requires careful optimization of both the combustor design and operating conditions. This article is aimed to design a combustion chamber utilizing producer gas for achieving flameless combustion using SOLID-WORKS, computational fluid dynamics (CFD) ANSYS-FLUENT simulation and Design of Experiment (DOE) from Minitab software. The design varied inlet nozzle diameters from 20 to 50 mm and combustor heights from 500 to 800 mm. Computational fluid dynamics (CFD) simulations is utilized to explore the impact of altering chamber height and inlet diameter in order to achieve efficiency in flameless combustion. The producer gas composition and simulation parameters were based on prior studies. The evaluation is focused on CO, NOx emissions and the Damköhler number, and using Design of Experiment (DOE) methodology for optimization. Results showed that chamber height and inlet diameter had limited effects on combustion and CO emission. Therefore, increasing chamber height raised NOx emissions due to prolonged fuel exposure to high temperatures, while varying inlet nozzle diameter has no effect on Damköhler number, but chamber’s height does. Finally, Minitab optimization suggested a chamber with 30 mm inlet nozzle diameter and 600 mm height for desirable flameless combustion, and operating on an equivalence ratio of φ = 0 . 7 which resulted in the lowest CO and NOx emissions, with values of 71.5 ppm and 5.05 ppm, respectively. • Full-factorial optimization statistical tools used to achieve flameless combustion. • Premixed low-grade biomass producer gas is burned in pressurized cyclone combustor. • Chamber height and inlet nozzle diameter are optimized using DOE and CFD tools. • Optimum chamber geometry was achieved with 600 mm height and 30 mm nozzle diameter. • Optimum operation achieved 71 ppm CO and 5 ppm NOx emissions at lean conditions.