摘要
在流化床内用若干种生物质材料进行了氮气流化条件下的常压热解实验 .为研究生物质的热解规律 ,建立了混沌神经网络模型对其进行模拟 .分别按照 3种方案进行了神经网络的模拟 ,经过比较确定了对于流化床内生物质热解过程最为有效的网络输入方案 ,该方案充分考虑了实验运行参数、生物质料的工业分析数据以及化学成分分析数据 ,可以对热解产物给出较好的预测 .
Pyrolysis of several kinds of biomass was carried out in a fluidized bed at atmospheric pressure using nitrogen as fluidizing gas. A chaotic neural network model was set up to study biomass pyrolysis. Three schemes of network input were applied and compared in the simulation, and the most effective one which could make sound prediction about the pyrolysis products was determined. This scheme involved experimental operation parameters, biomass proximate analysis data and chemical component analyses data. A rational explanation for the three schemes was given based on the difference of the evolution and chemical structures between biomass and coal.
出处
《化工学报》
EI
CAS
CSCD
北大核心
2003年第6期783-789,共7页
CIESC Journal
基金
国家自然科学基金资助项目 (No 5 97760 3 6)~~
