Development of reduced and optimized reaction mechanism for potassium emissions during biomass combustion based on genetic algorithms

Kaidi Wan, Luc Vervisch, Zhenxun Gao, Pascale Domingo, Chongwen Jiang, Jun Xia and Zhihua Wang

Energy, 2020, vol. 211, issue C

Abstract: A reduced mechanism for potassium chemistry under combustion conditions is derived from a detailed chemical mechanism for alkali metal emissions (Glarborg and Marshall, 2005), which could be useful for three-dimensional (3D) numerical simulations of potassium emissions by biomass combustion furnaces. An automated chemistry reduction and optimization approach relying on canonical micro-mixing problem is applied to develop the reduced mechanism, whose performance is then evaluated in two-dimensional (2D) carrier-phase direct numerical simulation (DNS) of pulverized-biomass combustion. Good agreement is achieved between predictions of the reduced and the detailed mechanisms on the four major potassium species, i.e., K, KOH, KCl and K2SO4. The prediction capabilities of the reduced mechanism for various K/Cl/S ratios in the volatiles are further investigated by a parametric study with 14 two-dimensional DNS cases. The potassium chemistry under those various conditions are well predicted by the reduced potassium mechanism with a CPU cost reduction reaching up to 71.3% compared to the detailed reference mechanism.

Keywords: Biomass combustion; Direct numerical simulation; Potassium; Chemistry reduction; Genetic algorithm (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:211:y:2020:i:c:s036054422031673x

DOI: 10.1016/j.energy.2020.118565

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