Dynamic Modeling with Experimental Calibration for the Syngas Production
from Biomass Fixed-bed Gasification
Abstract
In this paper, a dynamic biomass gasification model was developed based
on the hybrid peripheral fragmentation and shrinking-core (HPFS) model.
To improve the accuracy of syngas generation transient prediction, the
chemical kinetic model was trained using global surrogate optimization
techniques. The pre-exponential factors of kinetic reactions are
calibrated under non-catalytic conditions, employing experimental
transient data of syngas generation rate and compositions under
different temperatures and gasifying agents. The DYCORS and GOMORS were
employed as the numerical solvers for finding the global optimum
solution of the pre-exponential factors. The calibrated kinetic models
based on both single-objective and multi-objective approaches have been
validated by experimental data in four different biomass gasification
scenarios. The calibrated kinetic model shows an over 95% decrease in
terms of integrated squared error (ISE)-based model mismatch when
compared to the original kinetic model.