Numerical simulation of combustion of sulfide- biomass concentrate ingredients and contaminants in copper furnace smelting

  • Zahedi R
  • Shaghaghi A
  • et al.
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Abstract

Co-firing biomass and fossil fuels in industrial furnaces is a suitable way to reduce the environmental impact of human activities with acceptable investment. In this paper, the results of numerical simulation co-firing of sulfide concentrate and three auxiliary fuels, including gasoil, kerosene, and sawdust biomass, are compared in the flash furnace copper smelting. For modeling of turbulent flow and combustion, RNG, k-ε model, and probability density function model (pdf) have been used, respectively. This study has been carried out to investigate the furnace temperature and combustion pollutants distribution. The numerical simulation results show that the flame temperature resulting from the combustion of diesel fuel and sawdust as auxiliary fuel is the highest and lowest, respectively. In biomass combustion, despite that the flame temperature is low, but the NOx mass fraction increases because there is nitrogen in the sawdust chemical composition. Also in sawdust combustion, the oxygen content is high, the SO2 and SO3 sulfur pollutants increase in the high temperatures regions of the furnace and the lower temperature of the auxiliary fuel burner, respectively. Because SO2 is formed at high temperatures (> 1273K), oxygen-rich and SO3 species are produced at relatively low temperatures with excess oxygen. The amount of CO emissions in sawdust combustion is much lower than the amount of combustion of diesel and oil. In the peak of the flash furnace for sawdust and diesel auxiliary fuels, the temperature is 2.29E+03 K, and the distribution of NOx, CO2, O2, SO2, and SO3 are 1.51E-04, 9.72E-02, 2.33E-03, 1.71E-01 and 2.45E-02 respectively.

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Zahedi, R., Shaghaghi, A., Tahooneh, M. T., & Ahmadi, A. (2022). Numerical simulation of combustion of sulfide- biomass concentrate ingredients and contaminants in copper furnace smelting. Future Energy, 2(1), 1–8. https://doi.org/10.55670/fpll.fuen.2.1.1

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