Kyoto University · Engineering
Professor Jiangkuan Xing's research lab specializes in computational combustion and energy conversion, focusing on the fundamental mechanisms of coal and biomass devolatilization, ammonia-based combustion, and turbulent mixing in energy systems. The lab employs advanced numerical modeling techniques—such as chemical percolation devolatilization (CPD), direct numerical simulation (DNS), and machine learning (e.g., random forest) to predict combustion behavior, volatile release, and NOx formation under complex conditions. Key research directions include multi-fuel co-firing (e.g., coal-ammonia, biomass-hydrogen), flame structure analysis, and turbulence-chemistry interactions in practical combustion environments.
Figures are computed from collected data and may differ slightly.
Currently, volatile matter is generally treated as a postulate substance or a mixture of light gases and tar with given proportion in pulverized coal combustion (PCC) simulation. Whether those treatments can well characterize the PCC or not remains unknown. Here, current different coal devolatilization treatments are numerically evaluated under the configuration of laminar stagnation PCC (Xia, M.; et al. Proc. Combust. Inst. 2017, 36, 2123–2130). The results show that the one-step model fitted f
Open papers in the app to read, cite, and organize with AI.
