Algorithms, Год журнала: 2025, Номер 18(5), С. 283 - 283

Опубликована: Май 13, 2025

With the growing demand for sustainable energy solutions, biomass torrefaction has emerged as a crucial technology converting agricultural waste into high-value biofuels. This work develops dual kinetic modeling using global and individual parameters combined particle swarm optimization (PSO) to predict densification based on elemental composition (CHNO) high heating values (HHVs). The are calculated from experiments conducted at 250 °C, 275 300 obtained by adjusting experimental points each temperature. A two-step model was used optimized achieve exceptional adjustment accuracy (98.073–99.999%). were carried out in an inert atmosphere of nitrogen with rate 20 °C/min 100 min residence time. results demonstrate trade-off: while provide superior (an average fit 99.516%) predicting degradation weight loss, offer better predictions composition, errors 2.129% (carbon), 1.038% (hydrogen), 9.540% (nitrogen), 3.997% (oxygen). Furthermore, it been found that determining temperature higher than maximum peak observed derivative thermogravimetric (DTG) curve (275 °C), is possible behavior process within 250–325 °C range R-squared value corresponding error lower 3%. approach significantly reduces number required twelve only four relying single isothermal condition parameter estimation.

Язык: Английский