Kinetic parameters estimation of pinus sylvestris pyrolysis by Kissinger-Kai method coupled with Particle Swarm Optimization and global sensitivity analysis

• Published in: Bioresource technology Vol. 293; p. 122079
• Main Authors: Ding, Yanming, Zhang, Yu, Zhang, Jiaqing, Zhou, Ru, Ren, Zeyu, Guo, Hailin
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.12.2019
• Subjects: Kinetics; Particle Swarm Optimization; Pinewood; Pyrolysis; Sensitivity analysis; Pyrolysis; Sensitivity analysis; Kinetics; Pinewood; Particle Swarm Optimization
• ISSN: 0960-8524; 1873-2976
• DOI: 10.1016/j.biortech.2019.122079

•Kissinger-Kai method is coupled with Particle Swarm Optimization.•Global sensitivity analysis of kinetic parameters is conducted.•Latin Hypercube Sampling and rank transformation are applied. Pyrolysis of pinewood (pinus sylvestris) was investigated based on thermogravimetric analysis. A new method was put forward to estimate its kinetic parameters by coupling model-free and model-fitting models. Kissinger-Kai method updated from Kissinger method was used as the representative of model-free method. Particle Swarm Optimization heuristic algorithm, as the typical model-fitting method, was coupled with three-component parallel reaction mechanism to search the optimized values, wherein its search ranges of kinetic parameters were referred to the original calculated values by Kissinger-Kai method. Furthermore, to explore the influence of separate kinetic parameter on the final predicted thermogravimetric results, global sensitivity analysis about these parameters was conducted by comparison of Spearman rank correlation coefficient based on Latin Hypercube Sampling and rank transformation. It was found that the top three parameters affecting the predicted results were activation energy of lignin, reaction order of cellulose and pre-exponential factor of lignin.