Abstract—Due to the limited detection range of the adiabatic equipment, it is difficult to get complete experimental curve of some materials and calculate the kinetic parameters. In this work, the conjugate direction particle swarm optimization (CDPSO) approach, as a global stochastic optimization algorithm, is proposed to estimate the kinetic parameters and complete experimental curve from part of adiabatic calorimetric data. This algorithm combines the conjugate direction algorithm (CD) which has the ability to escape from the local extremum and the global optimization ability of the particle swarm optimization (PSO) which finds the globally optimal solutions. One case was used to verify this method: 20% DTBP in toluene decompositions under adiabatic conditions. Comparing the experimental and calculated complete temperature curve, the accuracy of the fitted kinetic parameters calculated by no less than 70% temperature rise rate proportion of data is verified. The value of TD24 is well-deviated even used 10% proportion of data. The case reasonably proves the effectiveness of CDPSO algorithm in the estimation of kinetic parameters from part of adiabatic data.
Index Terms—Conjugate direction particle swarm optimization, Kinetic parameters, part of adiabatic data, 20%DTBP,
TD24.
Zhao Xiao-Qiao, Wu Wen-Qian, and Chen Wang-Hua are with Department of Safety Engineering, School of Chemical Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, China (e-mail: zhaoxq_nust@163.com, 1374981824@qq.com, chenwh_nust@sina.com).
Wang Hao is with Jiaxing Tellhow Equipment Technology Co., Ltd, Jiaxing, Zhejiang 314006, China (1269346513@qq.com).
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Cite: Xiao-Qiao Zhao, Hao Wang, Wen-Qian Wu, and Wang-Hua Chen, "Conjugate Direction Particle Swarm Optimization Based Approach to Determine Kinetic Parameters from Part of Adiabatic Data," International Journal of Chemical Engineering and Applications vol. 11, no. 4, pp. 82-88, 2020.
