修正离散随机孔模型应用于两种秸秆生物质焦CO_2气化的动力学研究

Kinetics of Two Straw Biomass Chars Gasification With CO_2 Based a Modified Discrete Random Pore Model

生物质以其产量大、CO_2零排放等优点成为替代化石燃料的重要可再生能源。文中以中国2种典型生物质玉米秆焦和稻草焦为研究对象,在热重分析仪上对玉米秆焦和稻草焦CO_2气化特征进行研究。根据反应过程中生物质焦颗粒孔隙表面积与反应速率之间的关键关系,并基于其气化过程中在非常小时间微元内有效反应面积的修正,利用一种微元分析法求解随机微分方程,从而建立了在化学反应控制条件下预测生物质焦气化行为的修正离散随机孔模型(MDRPM)。通过与离散随机孔模型(DRPM)比较发现,修正离散随机孔模型的预测值比DRPM的预测值更接近实验数据,并利用该模型分析了在不同温度下玉米秆焦和稻草焦CO_2气化的特性。

Biomass is an ideal renewable energy with advantages of abundance resources and neutral in greenhouse gas circulation. In this paper, maize stalk and rice straw chars were used in this study as the representatives of biomass, and the gasification of two typical biomass chars in CO2 was studied using the thermogravimetric balance. Based on the key relationship between reaction surface and reaction rate of biomass chars gasification, the effective reaction surface area of biomass chars gasification was improved for a small increment, and differential increment analysis method for solving stochastic differential equation, modified discrete random pore model （MDRPM） was finally constructed to predict the behavior of biomass chars gasification under chemical reaction control. Compared with the result of discrete random pore model （DRPM）, it was found that MDRPM was satisfied to explain the gasification process of biomass chars. The characteristics of maize stalk and rice straw chars gasification in CO2 at different times were analyzed by this model.