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

Kaidi Wan (1, 2) , Luc Vervisch (3) , Chongwen Jiang (1, 2) , Pascale Domingo (3) , Zhenxun Gao (1, 2) , Jun Xia (4) , Zhihua Wang (5)

1 NIT - Ningbo Institute of Technology
2 School of Aeronautic Science and Engineering, Beihang University, Beijing, China
3 CORIA - Complexe de recherche interprofessionnel en aérothermochimie
4 Department of Mechanical and Aerospace Engineering & Institute of Energy Futures, Brunel University London
5 State Key Laboratory of Clean Energy Utilization, Zhejiang University, Hangzhou

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 agreements are achieved between predictions of the reduced and the detailed mechanisms on the four major potassium species, i.e., K, KOH, KCl and K 2 SO 4. 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 predicted well by the reduced potassium mechanism with a CPU cost reduction reaching up to 71.3% compared to the detailed reference mechanism.

Mots clés: Pulverized-biomass combustion; Direct numerical simulation; Potassium; Chemistry reduction; Genetic algorithm

Domaines: Sciences de l'ingénieur [physics]

Kaidi Wan, Luc Vervisch, Chongwen Jiang, Pascale Domingo, Zhenxun Gao, et al.. Development of reduced and optimized reaction mechanism for potassium emissions during pulverized-biomass combustion based on genetic algorithms. Energy, 2020, 211, pp.118565. ⟨10.1016/j.energy.2020.118565⟩. ⟨hal-03041419⟩