SIMULATION OF BIOMASS PYROLYSIS WITH CHAOTIC NEURAL NETWORK MODEL

TANG Songtao; LI Dingkai; Lü Zi’an; SHEN Youting

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SIMULATION OF BIOMASS PYROLYSIS WITH CHAOTIC NEURAL NETWORK MODEL

更新时间：2025-12-10

- SIMULATION OF BIOMASS PYROLYSIS WITH CHAOTIC NEURAL NETWORK MODEL
- CIESC Journal Issue 6, Pages: 783-789(2003)
- 作者机构：
  
  清华大学煤的清洁燃烧技术国家重点实验室
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Online First：25 June 2003，
  
  Published：25 June 2003
- 稿件说明：
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TANG Songtao, LI Dingkai, Lü Zi’an, et al. SIMULATION OF BIOMASS PYROLYSIS WITH CHAOTIC NEURAL NETWORK MODEL[J]. CIESC Journal, 2003, (6): 783-789.
DOI：

TANG Songtao, LI Dingkai, Lü Zi’an, et al. SIMULATION OF BIOMASS PYROLYSIS WITH CHAOTIC NEURAL NETWORK MODEL[J]. CIESC Journal, 2003, (6): 783-789. DOI：

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.最后基于生物质与煤在形成过程与化学结构等方面的不同之处对上述方案间的差异给出了合理的解释.

Abstract

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.

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