In:
Physics of Fluids, AIP Publishing, Vol. 34, No. 4 ( 2022-04-01)
Kurzfassung:
Thermal radiation is the dominant mode of heat transfer in many combustion systems, and in typical flameless furnaces, it can represent up to 80% of the total heat transfer. Accurate modeling of radiative heat transfer is, thus, crucial in the design of these large-scale combustion systems. Thermal radiation impacts the thermochemistry, thereby the energy efficiency and the temperature sensitive species prediction, such as NOx and soot. The requirement to accurately describe the spectral dependence of gaseous radiative properties of combustion products interacts with the modeling of finite rate chemistry effects and conjugates heat transfer and turbulence. Additionally, because of the multiple injection of fuels and/or oxidizers of various compositions, case-specific radiative properties' expressions are required. Along these lines, a comprehensive modeling to couple radiation and combustion in reacting flows is attempted and applied to the simulation of flameless combustion. Radiation is modeled using the spectral line-based weighted-sum-of-gray-gases approach to calculate gaseous radiative properties of combustion products using the correlation of the line-by-line spectra of H2O and CO2. The emissivity weights and absorption coefficients were optimized for a range of optical thicknesses and temperatures encountered in the considered furnace. Efforts were also made on the development of a reliable and detailed experimental dataset for validation. Measurements are performed in a low calorific value syngas furnace operating under flameless combustion. This test rig features a thermal charge which can extract about 60% of combustion heat release via 80% of radiative heat transfer, making it of special interest for modeling validation. The comparison between the simulation and the experiment demonstrated a fair prediction of heat transfer, energy balance, temperature, and chemical species fields.
Materialart:
Online-Ressource
ISSN:
1070-6631
,
1089-7666
Sprache:
Englisch
Verlag:
AIP Publishing
Publikationsdatum:
2022
ZDB Id:
1472743-2
ZDB Id:
241528-8
