摘要
文章选取松针作为典型的生物质,对其热解动力学展开研究。在惰性气体中分别在升温速率为10、30、50 K/min下开展松针热重实验,质量损失速率曲线中出现2个特征峰,分别对应半纤维素和纤维素的热解。采用Flynn-Wall-Ozawa(FWO)法和Kissinger-Akahira-Sunose(KAS)法计算松针热解的活化能,分别为63.90~205.23 kJ/mol和59.56~203.85 kJ/mol。采用分布活化能模型(distributed activation energy model,DAEM)计算指前因子的值。利用shuffled complex evolution(SCE)方法优化热解动力学参数,优化热解动力学参数预测的热重曲线与实验数据高度吻合。利用开发的多组分生物质热解求解器biopyrolysisFOAM进一步模拟松针热解,并将优化后的热解动力学参数作为初始参数。模拟结果显示,在不同的升温速率下,模拟结果与实验数据吻合度较高。
Pine needles were selected as typical biomass to investigate their pyrolysis kinetics.The thermogravimetric experiments were carried out on pine needles under an inert atmosphere with heating rates of 10,30 and 50 K/min.There were two characteristic peaks in the mass loss rate curve,corresponding to the pyrolysis of hemicellulose and cellulose.Flynn-Wall-Ozawa(FWO)and Kissinger-Akahira-Sunose(KAS)methods were used to calculate the values of activation energy,which were 63.90-205.23 kJ/mol and 59.56-203.85 kJ/mol,respectively.The distributed activation energy model(DAEM)was used to calculate the value of the pre-exponential factor.The shuffled complex evolution(SCE)optimization algorithm was applied to optimizing the calculated parameters.The predicted values using the optimized pyrolysis kinetic parameters match the experimental data well.The developed multi-component biomass pyrolysis solver,which is named biopyrolysisFOAM,was used to further simulate the pyrolysis of pine needles.The optimized pyrolysis kinetic parameters were used as the initial parameters.The simulation results fit well with the experimental data at different heating rates.
作者
刘浩然
李阳
王昌建
LIU Haoran;LI Yang;WANG Changjian(School of Civil and Hydraulic Engineering,Hefei University of Technology,Hefei 230009,China)
出处
《合肥工业大学学报(自然科学版)》
CAS
北大核心
2023年第4期494-499,共6页
Journal of Hefei University of Technology:Natural Science
基金
安徽省自然科学基金安徽能源互联网联合基金资助项目(2008085UD13)。
关键词
松针
热解动力学
SCE全局优化算法
OpenFOAM平台
数值模拟
pine needle
pyrolysis kinetics
shuffled complex evolution(SCE)global optimization algorithm
OpenFOAM platform
numerical simulation