Devolatilization is always the primary process in biomass thermal conversion, and directional devolatilization has caught considerable attention in recent decades for producing certain fuels and raw chemical materials. In the present study, we report a novel sensitivity study for biomass directional devolatilization using random forest models, which shows obvious advantages in the parameter range, analysis time, and cost compared with the experimental approach. First, a biomass devolatilization product database is constructed with a detailed mechanism for various biomass types under different operation conditions. Then random forest models are developed from the constructed database to accelerate the Sobol sensitivity analysis for obtaining the full-parameter-effect phase diagram. The phase diagram shows that the cellulose fraction holds the maximum influence for the CH₄, C₂H₄, CO, and tar yields, while it has has limited effects on the H₂O, CO₂, and solid residue (SR) yields. The final temperature has the maximum effect on the H₂ yield, and the LIG-C fraction shows the dominating effect on the SR yield. The final temperature and the LIG-C fraction have comparable and considerable effects on the H₂O yield. This full-parameter phase diagram provides an efficient way to directionally choose the biomass types and alter the operation conditions to produce certain devolatilization products.

中文翻译：

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随机森林模型对生物质定向脱挥发分的敏感性研究

脱挥发分一直是生物质热转化的主要过程，并且定向脱挥发分在近几十年来已经引起了相当大的关注，用于生产某些燃料和化学原料。在本研究中，我们报告了一项使用随机森林模型进行的生物量定向脱挥发分的敏感性研究，与实验方法相比，该研究在参数范围，分析时间和成本方面显示出明显的优势。首先，利用针对不同运行条件下各种生物质类型的详细机制，构建了生物质脱挥发分产品数据库。然后从构建的数据库中开发随机森林模型，以加速Sobol灵敏度分析，以获得完整的参数效果相位图。_{如图4所示}，C ₂ H ₄，CO和焦油的收率较高，但对H ₂ O，CO ₂和固体残渣（SR）收率的影响有限。最终温度对H ₂收率影响最大，而LIG-C馏分显示对SR收率起主要作用。最终温度和LIG-C馏分对H ₂ O的产率具有相当的影响。该全参数相图提供了一种有效的方法，可以直接选择生物质类型并改变操作条件以生产某些脱挥发分产品。