relation: https://khub.utp.edu.my/scholars/12523/
title: Air catalytic biomass (PKS) gasification in a fixed-bed downdraft gasifier using waste bottom ash as catalyst with NARX neural network modelling
creator: Shahbaz, M.
creator: Taqvi, S.A.A.
creator: Inayat, M.
creator: Inayat, A.
creator: Sulaiman, S.A.
creator: McKay, G.
creator: Al-Ansari, T.
description: The air gasification of Palm Kernel Shells (PKS) using coal bottom ash (CBA) as a catalyst has been performed in a fixed-bed gasifier. The impact of three process parameters, namely, temperature (575�775 °C), air flowrate (1.5�45 litter/min) and catalyst loading (0�30 wt.) has been investigated on the product gas yield. The composition of the H2 product is computed to be a maximum of 28 vol. at 875 °C. The air flowrate has a direct relation with H2 production. The catalysts used have demonstrated a positive impact on the carbon conversion efficiency, showing the increase in carbon-containing gases in the product gas due to the increases in gas yield. A Non-linear Autoregressive Network with exogenous inputs (NARX) neural network has been used to predict the gaseous flowrate dynamically in order to improve gasification performance. The predicted results from the NARX network demonstrate good agreement with the experimental study with R2 � 0.99. © 2020
publisher: Elsevier Ltd
date: 2020
type: Article
type: PeerReviewed
identifier:   Shahbaz, M. and Taqvi, S.A.A. and Inayat, M. and Inayat, A. and Sulaiman, S.A. and McKay, G. and Al-Ansari, T.  (2020) Air catalytic biomass (PKS) gasification in a fixed-bed downdraft gasifier using waste bottom ash as catalyst with NARX neural network modelling.  Computers and Chemical Engineering, 142.   ISSN 00981354     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089153631&doi=10.1016%2fj.compchemeng.2020.107048&partnerID=40&md5=7b1f48bcdb982d378165f9492a1c4ba9
relation: 10.1016/j.compchemeng.2020.107048
identifier: 10.1016/j.compchemeng.2020.107048