Effect and optimization of process conditions during solvolysis and torrefaction of pine sawdust using the desirability function and genetic algorithm
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Date
Authors
Ikegwu, Ugochukwu M.
Ozonoh, Maxwell
Okoro, Nnanna-Jnr M.
Daramola, Michael Olawale
Journal Title
Journal ISSN
Volume Title
Publisher
American Chemical Society
Abstract
Understanding optimal process conditions is an
essential step in providing high-quality fuel for energy production,
efficient energy generation, and plant development. Thus, the effect
of process conditions such as the temperature, time, nitrogen-tosolid
ratio (NSR), and liquid-to-solid ratio (LSR) on pretreated
waste pine sawdust (PSD) via torrefaction and solvolysis is
presented. The desirability function approach and genetic algorithm
(GA) were used to optimize the processes. The response surface
methodology (RSM) based on Box−Behnken design (BBD) was
used to determine the effect of the process conditions mentioned
above on the higher heating value (HHV), mass yield (MY), and
energy enhancement factor (EEF) of biochar/hydrochar obtained
from waste PSD. Seventeen experiments were designed each for
torrefaction and solvolysis processes. The benchmarked process
conditions were as follows: temperature, 200−300 °C; time, 30−120 min; NSR/LSR, 4−5. In this study, the operating temperature
was the most influential variable that affected the pretreated fuel’s properties, with the NSR and LSR having the least effect. The
oxygen-to-carbon content ratio and the HHV of the pretreated fuel sample were compared between the two pretreatment methods
investigated. Solvolysis pretreatment showed a higher reduction in the oxygen-to-carbon content ratio of 47%, while 44% reduction
was accounted for the torrefaction process. A higher mass loss and energy content were also obtained from solvolysis than the
torrefaction process. From the optimization process results, the accuracy of the optimal process conditions was higher for GA (299
°C, 30.07 min, and 4.12 NSR for torrefaction and 295.10 °C, 50.85 min, and 4.55 LSR for solvolysis) than that of the desirability
function based on RSM. The models developed were reliable for evaluating the operating process conditions of the methods studied.
Description
Keywords
Fuel, Solvolysis, Energy production, Temperature
Sustainable Development Goals
Citation
Ikegwu, U.M., Ozonoh, M., Okoro, N.-J.M. et al. Effect and optimization of process conditions during solvolysis and torrefaction of pine sawdust using the desirability function and genetic algorithm. ACS Omega 2021, 6, 20112−20129.