Weighted Sum of Gray Gases Model Optimization for Numerical Investigations of Processes inside Pulverized Coal-Fired Furnaces

The effects of the number of significant figures(NSF) in the interpolation polynomial coefficients(IPCs) of the weighted sum of gray gases model(WSGM) on results of numerical investigations and WSGM optimization were investigated. The investigation was conducted using numerical simulations of the processes inside a pulverized coal-fired furnace. The radiative properties of the gas phase were determined using the simple gray gas model(SG), two-term WSGM(W2), and three-term WSGM(W3). Ten sets of the IPCs with the same NSF were formed for every weighting coefficient in both W2 and W3. The average and maximal relative difference values of the flame temperatures, wall temperatures, and wall heat fluxes were determined. The investigation showed that the results of numerical investigations were affected by the NSF unless it exceeded certain value. The increase in the NSF did not necessarily lead to WSGM optimization. The combination of the NSF(CNSF) was the necessary requirement for WSGM optimization.

The effects of the number of significant figures （NSF） in the interpolation polynomial coefficients （IPCs） of the weighted sum of gray gases model （WSGM） on results of numerical investigations and WSGM optimization were investigated. The investigation was conducted using numerical simulations of the processes inside a pulverized coal-fired furnace. The radiative properties of the gas phase were determined using the simple gray gas model （SG）, two-term WSGM （W2）, and three-term WSGM （W3）. Ten sets of the IPCs with the same NSF were formcd for every weighting coefficient in both W2 and W3. The average and maximal relative difference values of the flame temperatures, wall temperatures, and wall heat fluxes were determined. The investigation showed that the results of numerical investigations were affected by the NSF unless it exceeded certain value. The increase in the NSF did not necessarily lead to WSGM optimization. The combination of the NSF （CNSF） was the necessary requirement for WSGM optimization.