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浙江大学学报(工学版)
浙江大学学报(工学版)  2019, Vol. 53 Issue (3): 605-612    DOI: 10.3785/j.issn.1008-973X.2019.03.023
化学工程、能源工程     
预测生物质热解动力学参数的随机森林模型
邢江宽(),王海鸥,罗坤*(),白云,樊建人
浙江大学 能源清洁利用国家重点实验室，浙江 杭州 310027
Random forest model for predicting kinetic parameters of biomass devolatilization
Jiang-kuan XING(),Hai-ou WANG,Kun LUO*(),Yun BAI,Jian-ren FAN
State Key Laboratory of Clean Energy Utilization, Zhejiang University, Hangzhou 310027, China
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摘要：

基于大量已发表的生物质热解实验数据，采用数值方法拟合全局反应热解模型的动力学参数，建立生物质热解的训练和验证数据库，并利用随机森林算法研究生物质热解动力学参数与生物质种类和加热条件之间的非线性关系，发展预测生物质热解动力学参数的随机森林模型. 训练和验证的结果显示：随机森林模型能够较好地预测训练数据库中的生物质热解的动力学参数(R2>0.92)，并能够准确预测验证数据库中的多种生物质的热解过程(R2>0.93). 此外，变量重要性分析结果显示：纤维素质量分数对于反应级数和活化能影响较大，木质素对于反应级数的影响最大. 加热条件对于活化能的影响可以忽略，但是对指前因子和反应级数的影响显著.
关键词： 生物质热解;  随机森林(RF);  动力学参数;  化学组成;  升温速率    
Abstract:

Two biomass devolatilization databases, including the training and validation databases, were constructed from diverse available experiments in literature. The kinetic parameters were fitted under the framework of order-based global biomass devolatilization model. The random forest (RF) method was employed to investigate the complex nonlinear correlations between the kinetic parameters with chemical compositions and heating condition, in order to develop the RF model to accurately predict the kinetic parameters of biomass devolatilization based on its chemical compositions and heating condition. The training and validation results show that the RF model can well predict the kinetic parameters of different biomass types under different heating rates (determination coefficient R2>0.92), also with an accurate prediction of the biomass devolatilization process (R2>0.93). The variable importance measurement (VIM) results show that the fraction of cellulose (CL) has significant effect on the reaction order and activation energy, and the fraction of lignin (LIG) has the maximum effect on the reaction order. The effect of heating rate is negligible for activation energy, but considerable for the frequency factor and reaction order.
Key words: biomass devolatilization    random forest (RF)    kinetic parameters    chemical composition    heating rate
收稿日期: 2018-08-16 出版日期: 2019-03-04
CLC:  TK 6  
通讯作者: 罗坤     E-mail: zjuxjk@zju.edu.cn;zjulk@zju.edu.cn
作者简介: 邢江宽(1993—)，男，博士生，从事气固两相燃烧的热物理模型及数值模拟研究. orcid.org/0000-0002-2423-5627. E-mail： zjuxjk@zju.edu.cn
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邢江宽
王海鸥
罗坤
白云
樊建人

引用本文:

邢江宽,王海鸥,罗坤,白云,樊建人. 预测生物质热解动力学参数的随机森林模型[J]. 浙江大学学报(工学版), 2019, 53(3): 605-612.

Jiang-kuan XING,Hai-ou WANG,Kun LUO,Yun BAI,Jian-ren FAN. Random forest model for predicting kinetic parameters of biomass devolatilization. Journal of ZheJiang University (Engineering Science), 2019, 53(3): 605-612.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2019.03.023    或    http://www.zjujournals.com/eng/CN/Y2019/V53/I3/605

β/（K·min?1） K/s?1 E/（J·mol-1） n
10 1.606×107 9.794×104 2.089
40 5.329×108 1.111×105 2.294
表 1  桉树叶生物质在不同升温速率条件下拟合出的动力学参数
图 1  采用拟合出的动力学参数预测的桉树叶生物质热解过程与实验值的比较
图 2  随机森林(RF)算法的流程示意图
图 3  训练和验证数据库中样本的分布
图 4  不同棵树的随机森林模型的测试结果
图 5  RF模型对于所有动力学参数的训练结果（实线代表最佳的预测效果）
图 6  RF模型对于所有动力学参数的验证结果（实线代表最佳的预测效果）
图 7  不同加热速率条件下采用RF模型计算的动力学参数所预测的桉树皮和桉树木屑的热解过程与实验值的比较
图 8  不同输入参数对于热解动力学参数的相对影响大小
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