Predictive Defluidization Models and Operability Maps

The considerations and the experimental evidence just described suggest that the reactor design as well as the definition of process conditions need a tool, able to provide reliable predictions for the on-set of fluidization worsening and bed defluidization. Mastellone and Arena [37] proposed a predictive defluidization model valid for low-temperature pyrolysis 

THE EFFECT OF THE MAIN PROCESS VARIABLES ON THE YIELD AND COMPOSITION OF PYROLYSIS PRODUCTS 

Thermal polymer degradation is determined by the chemical structure and length of the polymer chain, by the presence of unstable structures (such as impurities or additives) and by the temperature level inside the reactor, which must be high enough to break the weakest, primary chemical bonds. Madorsky and Straus [39] found that some polymers (such as PMMA and PTFE) mainly revert to their monomers upon heating, while others (such as PE) yield a great many decomposition products. These two types of dominant thermal polymer degradation are called end-chain scission and random-chain 

The influence of the applied reaction conditions (temperatme, residence time, concentrations of reactants and products) on the product spectra obtained from pyrolysis of different plastic wastes could be estimated under the hypothesis of thermodynamic equilibrium, as shown by Westerhout et al. [43]. They evaluated the maximum achievable yield of valuable products during the pyrolysis of PE and PP, with the validation of experiments carried out under conditions of controlled temperatme and residence time. In large-scale reactors the residence time and temperature control are difficult and certainly 

Pyrolysis with steam as fluidizing gas [8] demonstrates that the olefins yield is increased due to water-gas reaction. 

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