Bioenergy and bioexergy analyses with artificial intelligence application on combustion of recycled hardwood and softwood wastes

Novel biomass bioenergy-bioexergy analyses via thermogravimetry analysis and 18 artificial intelligence are employed to evaluate the three biofuels from wood wastes (softwood-19 SW, hardwood-HW, and woods blend-WB). The chemical characterization of SW has the 20 highest bioenergy (higher heating value – HHV: 18.84 MJ·kg-1) and bioexergy (specific 21 chemical bioexergy – SCB: 19.65 MJ·kg-1) with the SCB/HHV ratio of wood waste as about 22 1.043-1.046. The high C-element has a significant influence on the HHV-SCB. The SCB/HHV 23 ratio of wood waste is recognized as about 1.043-1.046. The three distinct zones of wood waste 24 combustion are identified: moisture evaporation (Zone I, up to 110 °C), combustion reaction – 25 degradation of three major lignocellulosic components (hemicelluloses, cellulose, and lignin) 26 at Zone II, 110-600 °C, and ash remains (Zone III, 600-800 °C). The ignition (Dig=0.01-0.04) 27 and fuel reactivity (Rfuel=3.82-6.97 %·min-1·°C-1) indexes are evaluated. The comprehensive 28 combustion index (Sn:>5×10-7%2·min-2·°C-3) suggests that wood waste has a better combustion 29 performance than bituminous coal. The statistical evaluation presents that the highest HHV-30 SCB values are obtained by performing combustion for SW-250 µm at 15 °C·min-1. The S/N 31 Journal Pre-proof 32 33 34 35 36 37 ratio and ANOVA results agree that the wood waste type and particle size denote the most influential parameters. The artificial neural network prediction shows an excellent result (R2=1) with 1 hidden layer and 5 neuron configurations.