The chemistry of pyrolysis, together with heat transfer, drives ignition and flame spread of biomass materials under many fire conditions, but it is poorly understood. Cellulose is the main component of
biomass and is often taken as its surrogate. Its chemistry of pyrolysis
is simpler and dominates the pyrolysis of biomass. Many reaction schemes with corresponding kinetic parameters can be found in the literature for the pyrolysis of cellulose, but their appropriateness
for fire is unknown. This study investigated inverse modelling and
the blind prediction of six reaction schemes of different complexities
for isothermal and non-isothermal thermogravimetric experiments. We used multi-objective optimisation to simultaneously and separately
inverse model the kinetic parameters of each reaction scheme
to several experiments. Afterwards we tested these parameters
with blind predictions. For the first time, we reveal a set of equally
good solutions for the modelling of pyrolysis chemistry of different experiments. This set of solutions is called a Pareto front, and represents a trade-off between predictions of different experiments. It stems from the uncertainty in the experiments and in the modelling.
Parameters derived from non-isothermal experiments compared well with the literature, and performed well in blind predictions of both isothermal and non-isothermal experiments. Complexity beyond
the Broido-Shafizadeh scheme with seven parameters proved to be
unnecessary to predict the mass loss of cellulose; hence, simple
reaction schemes are most appropriate for macroscale fire models.
Our results show that modellers should use simple reaction
schemes to model pyrolysis in macroscale fire models.