Journal
JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES
Volume 64, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.jlp.2020.104094
Keywords
Reaction order model; Kinetic triplet; Global one-step heterogeneous reaction; Decelerating reaction; Nonlinear ordinary differential equation
Categories
Funding
- National Natural Science Foundation of China [51804168, 21436006, 21576136]
- China Postdoctoral Science Foundation [2018T110492, 2017M620209]
- Natural Science Foundation of Jiangsu Province [BK20171005, 17KJB620003]
- Jiangsu Project Plan for Outstanding Talents in Six Research Fields [2015-XCL-019]
Ask authors/readers for more resources
Computing kinetic triplet is of importance for the process safety of combustion/gasification industries to establish the chemical reaction scheme and to assess the hazardous risk. Few approaches have been capable of calculating lumped kinetic triplet at one time efficiently, which might be attributed to the fact that the analytical solution for the nonlinear ordinary differential equation (NNODE) for the nth order reaction model has not been found yet. This paper presents an analytical solution of NNODE to compute kinetic triplet. Results showed that the proposed method (mass fraction curve-fitting error phi = 1.49%-2.07%) is more efficient to compute kinetic triplet of the nth order reaction model, comparing to genetic algorithm (GA) optimization (phi = 1.43%-1.81%), Coats-Redfern (phi = 2.36%-3.16%), peak-shape, and isoconversional methods. A compensation effect between lnA and E-a is observed due to heating rates. Effects of exported data quality and smooth processing on computation of kinetic triplet are discussed. It is the first time that an analytical solution of NNODE (nth order model) for global one-step heterogeneous reaction is derived for computing kinetic triplet. This work may help to search for analytical solutions of power-law and Avrami-Erofeev models in the future to efficiently calculate kinetic triplet for accelerating and sigmoidal reaction systems.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available