生物质气化过程的混合神经网络模拟

用几种生物质的料进行了水蒸汽流化条件下的常压气化实验。为得到各种生物质的气化特性，用混合神经网络模型于气化过程进行了模拟。模型得到的气化产率与实验数据吻合得较好。神经网络给出的气化特性能正确地反映实际的生物质气化过程。模拟结果还显示，草本生物质和木本生物质在气化过程中，各种煤气成分的释放有不同的规律。

SIMULATION OF BIOMASSGASIFICATION WITH A HYBRID NEURAL NETWORK MODEL

Gasification experiments of several types of biomass were conducted in an atmospheric steam fluidized bed gasifier,which biomass samples were fed into continuously and without residue discharge.In order to obtain the gasification profiles for each type of biomass,an artificial neural network model has been developed to simulate the gasification process.Model-predicted gas production rates for the biomass gasification processes are in good agreement with the experimental data,thereby the gasification profiles given by the neural network model are considered to properly reflect the real gasification process of a biomass.Gasification profiles identified by neural network model suggest that gasification behavior of arboreal types of biomass is significantly different from that of herbaceous ones.