Suppr超能文献

交错复杂演化法估算山毛榉热解动力学参数

Estimation of beech pyrolysis kinetic parameters by Shuffled Complex Evolution.

机构信息

State Key Laboratory of Fire Science, University of Science and Technology of China, Heifei 230027, China.

School of Civil Engineering, Hefei University of Technology, Hefei 230009, China.

出版信息

Bioresour Technol. 2016 Jan;200:658-65. doi: 10.1016/j.biortech.2015.10.082. Epub 2015 Nov 10.

Abstract

The pyrolysis kinetics of a typical biomass energy feedstock, beech, was investigated based on thermogravimetric analysis over a wide heating rate range from 5K/min to 80K/min. A three-component (corresponding to hemicellulose, cellulose and lignin) parallel decomposition reaction scheme was applied to describe the experimental data. The resulting kinetic reaction model was coupled to an evolutionary optimization algorithm (Shuffled Complex Evolution, SCE) to obtain model parameters. To the authors' knowledge, this is the first study in which SCE has been used in the context of thermogravimetry. The kinetic parameters were simultaneously optimized against data for 10, 20 and 60K/min heating rates, providing excellent fits to experimental data. Furthermore, it was shown that the optimized parameters were applicable to heating rates (5 and 80K/min) beyond those used to generate them. Finally, the predicted results based on optimized parameters were contrasted with those based on the literature.

摘要

基于热重分析,在 5K/min 到 80K/min 的较宽加热速率范围内,研究了一种典型生物质能源原料——山毛榉的热解动力学。采用三组分(对应半纤维素、纤维素和木质素)平行分解反应方案来描述实验数据。所得到的动力学反应模型与进化优化算法(Shuffled Complex Evolution,SCE)相结合,以获得模型参数。据作者所知,这是首次在热重分析中使用 SCE 的研究。针对 10、20 和 60K/min 的加热速率,对动力学参数进行了同时优化,对实验数据的拟合效果非常好。此外,结果表明,优化后的参数适用于除生成它们之外的加热速率(5 和 80K/min)。最后,对比了基于优化参数的预测结果和基于文献的预测结果。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验