The Growth and Evolution of Biomass Soot in Partial Oxidation-Assisted Hot Gas Filtration

Lin Tian (), Zixuan Jin and Wenran Gao
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Lin Tian: New Energy Science and Engineering, Nanjing Forestry University, Nanjing 210037, China
Zixuan Jin: New Energy Science and Engineering, Nanjing Forestry University, Nanjing 210037, China
Wenran Gao: New Energy Science and Engineering, Nanjing Forestry University, Nanjing 210037, China

Energies, 2023, vol. 16, issue 10, 1-14

Abstract: At present, partial oxidation is applied in the filtration processes of biomass hot gas to aid in solving the blockage problems caused by tar and dust condensates. However, in the resulting high-temperature and oxygen-limited environment, the risk of tar polymerization forming soot is created during the purification processes. Thus, this work established a hardware-in-the-loop simulation model using the Lagrangian method coupled with the chemical reactions on the particle surface. The model was then used to simulate the entire evolution process of soot, including its formation, growth, and interception. The simulation results confirmed that under partial oxidation conditions, the increase in tar’s conversion rate promotes the formation of soot. Further analysis indicated that the high-temperature field formed as a result of oxidation and the increase in the naphthalene/oxygen ratio are the main reasons for the soot formation. On the other hand, the growth process of soot was inhibited by partial oxidation, which is mainly reflected in the relatively smaller increasing magnitude of soot particle mass and the decrease in the soot formation rate. Although the formation and growth of biomass soot cannot be completely avoided, the growth process is beneficial to interception and the soot escape rate can be minimized by varying the premixed oxygen content. On this basis, the potential of the partial oxidation-assisted hot gas filtration method can be further investigated and analyzed.

Keywords: soot; partial oxidation; hot-gas filtration; discrete phase model (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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