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Comprehensive investigation of almond shells pyrolysis using advance predictive models

Khan, Arslan (författare)
National University of Sciences & Technology, Pakistan
Saeed, Saad (författare)
NFC Institute of Engineering & Technology, Pakistan
Pervaiz, Erum (författare)
National University of Sciences & Technology, Pakistan
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Khoja, Asif Hussain (författare)
National University of Sciences & Technology, Pakistan
Naqvi, Salman Raza (författare)
Karlstads universitet,Institutionen för ingenjörs- och kemivetenskaper (from 2013),National University of Sciences & Technology, Pakistan
Saeed, Sana (författare)
NFC Institute of Engineering & Technology, Pakistan
Ali, Imtiaz (författare)
King Abdulaziz University, Saudi Arabia
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 (creator_code:org_t)
Elsevier, 2024
2024
Engelska.
Ingår i: Renewable energy. - : Elsevier. - 0960-1481 .- 1879-0682. ; 227
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
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  • This research focused on comprehensive characterization and assessment of almond shells pyrolysis for bioenergy potential through thermogravimetric analysis from ambient temperature to 900 °C at different heating rates of 10, 15, and 20 °C/min in inert environment. Iso-conversional model-free methods like Friedman, Ozawa-Flynn-Wall (OFW), and Kissinger-Akahira-Sunose (KAS) were used for kinetic analysis. Average activation energies (Ea) evaluated using Friedman, OFW, and KAS methods were 198.45 kJ mol−1, 204.43 kJ mol−1, and 204.97 kJ mol−1, respectively. The evaluation of thermodynamic parameters, including ΔH‡, ΔG‡, and ΔS‡, was also assessed. The average values of ΔH‡, ΔG‡, and ΔS‡, were found to be 199.4 kJ mol−1, 172.17 kJ mol−1 and 42.60 kJ mol−1 respectively. The reaction mechanism was obtained from combined kinetics. A high R2 value of 0.9933 demonstrates strong agreement between the combined kinetic analysis results and the experimental data. The distribution activation energy model was assessed employing four pseudo elements identified as PC1, PC2, PC3, and PC4. Artificial Neural Network (ANN) and Boosting regression trees (BRT) were used for the prediction of Ea of almond shells pyrolysis. The detailed understanding of thermokinetics and creating customized predictive and innovative modelling techniques like ANN and BRT sets a new benchmark for developing customized models for thermochemical conversion of varieties of almond shells. 

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Maskinteknik -- Energiteknik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Mechanical Engineering -- Energy Engineering (hsv//eng)

Nyckelord

Almond shells
Pyrokinetics
DAEM
ANN
BRT
Chemical Engineering
Kemiteknik

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