Effects analysis on the gasification kinetic characteristics of food waste in supercritical water
Effects analysis on the gasification kinetic characteristics of food waste in supercritical water
复制标题
餐厨垃圾在超临界水中气化动力学特性的影响分析
DOI：
10.1016/j.fuel.2018.12.012
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发表时间：
2019-04
期刊：
影响因子：
7.4
通讯作者：
Wenwen Xu
中科院分区：
文献类型：
--
作者：
Jingwei Chen;Yi Fan;Jiaqiang E;Wen Cao;Feng Zhang;Jinke Gong;Guanlin Liu;Wenwen Xu
在石英管反应器中对餐厨垃圾（FW）的超临界水气化（SCWG）过程进行了研究，并利用一系列动力学模型对实验结果进行了分析。实验结果表明，在相同停留时间下，碳的气化效率随反应温度的升高而增加，反应活性在气化初期急剧增加，然后随反应时间的延长而降低。模拟结果表明，所有经典的动力学模型低估了实验结果，类似的模型在以前的工作中使用的超临界水煤气化。碱土金属（AAEM）的催化作用可显著增加气化反应的活性位，但不改变气化反应的动力学机制，从而导致模型的低估。为了解决上述问题，本文在RPM模型的基础上，考虑了催化作用对FW超临界水凝胶动力学行为的影响，建立了半经验修正的无规孔模型（MRPM）。MRP模型的模拟结果与实验结果吻合较好，表明MRP模型可以在不将气化过程划分为不同反应阶段的情况下，对不同条件下的SCWG全过程进行预测。MRP模型还可用于预测煤、生物质和有机废物的SCWG，并且对反应器优化和放大至关重要。
The gasification kinetic characteristics of food waste (FW) gasification by supercritical water (SCW) were investigated by examining the SCW gasification (SCWG) of FW in a quartz tube reactor, and the experimental results were investigated by using a series of kinetic models. The experimental results show that the carbon gasification efficiency increases with reaction temperature at the same residence time, and reactivity increases sharply at the early stage of gasification and then decreases with reaction time. The simulation results show that all the classical kinetic models underestimate the experimental results, similar to the models used in previous work on coal gasification by SCW. The underestimation of the models results from the catalytic effect of alkaline earth metals (AAEMs), which can notably increase the active sites of gasification reaction without changing the gasification kinetic mechanism. To solve the above problem, the catalytical effect to describe the kinetic behavior of the SCWG of FW is considered and a semiempirical modified random pore model (MRPM) is developed based on the RPM model. The simulation results of the MRP models are close to experimental findings, indicating that MRP model can be used to predict the entire process of SCWG under different conditions without dividing gasification into different stages of reaction. The MRP model can also be used for the prediction of SCWG of coal, biomass, and organic wastes and is crucial to reactor optimization and scaling up.
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