Open AccessVolatile State Mathematical Models for Predicting Components in Biomass Pyrolysis Products
Author(s) -
Pandit Hernowo,
Carolus Borromeus Rasrendra,
Yogi Wibisono Budhi,
Jenny Rizkiana,
Anton Irawan,
Septhian Marno,
Yana Meliana,
Oki Muraza,
Yazid Bindar
Publication year - 2022
Publication title -
journal of engineering and technological sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.202
H-Index - 14
eISSN - 2338-5502
pISSN - 2337-5779
DOI - 10.5614/j.eng.technol.sci.2022.54.1.8
Subject(s) - pyrolysis , yield (engineering) , biomass (ecology) , mass fraction , component (thermodynamics) , husk , fraction (chemistry) , chemistry , thermodynamics , organic chemistry , botany , agronomy , physics , biology
Volatile state mathematical models for quantifying the chemical components in volatile biomass pyrolysis products were developed. The component mass yield Yi rate depends linearly on its pseudo kinetic constant and the remaining mass yield. The mass fraction rate of each component was modeled from the derivation of its mass yield rate equation. A new mathematical model equation was successfully developed. The involved variables are: biomass number, temperature, heating rate, pre-exponential factor, and pseudo activation energy related to each component. The component mass fraction yi and the mass yield were predicted using this model within a temperature range. Available experimental pyrolysis data for beechwood and rice husk biomass were used to confirm the developed model. The volatile products were separated into bio-pyrolysis gas (BPG) and a bio-pyrolysis oil (BPO). Five components in the BPG and forty in the BPO were quantified. The pseudo activation energy for each pseudo chemical reaction for a specific component was modeled as a polynomial function of temperature. The component mass fraction and yield are quantifiable using this developed mathematical model equation within a temperature range. The predicted component mass fractions and yields agreed excellently with the available experimental data.