Structural assessment of lumped reaction networks with correlating parameters. (1st April 2020)

• Record Type: Journal Article
• Authors: Till, Zoltán; Varga, Tamás; Sója, János; Miskolczi, Norbert; Chován, Tibor
• Is Part Of: Energy conversion and management. Volume 209(2020)
• Publication Date: 2020-04-01
• Subjects: Energy from waste -- Fuel production -- Kinetic identification -- Kinetic model reduction -- Plastic waste pyrolysis -- Process development; Direct energy conversion -- Periodicals; Energy storage -- Periodicals; Energy transfer -- Periodicals; Énergie -- Conversion directe -- Périodiques; Direct energy conversion; Periodicals; 621.3105
• DOI: 10.1016/j.enconman.2020.112632
• Languages: English
• ISSNs: 0196-8904

Abstract

Graphical abstract: Highlights: Two-stage batch pyrolysis was studied with discrete lumping method. High correlation between the concentrations of volatile products was observed. Reaction kinetics were combined with the explicit expression of correlations. The suggested model is reasonably accurate and highly flexible. The methods described here are well suited for components with low residence times. Abstract: In this paper, we consider a lumped reaction network developed for studying the pyrolysis of real plastic waste carried out in a laboratory-scale two-stage batch reactor, with the primary intention of recovering valuable fuel components. Generally, the kinetic parameters of the reaction network, whether it is a lumped or detailed one, might correlate to some extent directly through the amounts of products to be formed. If the formation of two or more products has a strong correlation, we might even combine the corresponding reactions to reduce the size of the reaction network. This modeling step instinctively occurs when we have thousands of reactions, but it is usually not carried out in the case of a lumped model because of its elementary nature. Yet, in this work, we would like to show that taking the correlations between the formations of the pseudocomponents into consideration very much has its advantages. We show that these correlations can be utilized to increase the number of lumps included in the model, increasing its accuracy by applying some not so complicated structural modifications to the original model. This way, we can optimize the structure of the lumped reaction network so that we can capture the characteristics of the measurement rather efficiently without using an overcomplicated reaction model full of uncertain parameters.