Artificial neural networks for pyrolysis, thermal analysis, and thermokinetic studies: the status quo

NV Muravyev, G Luciano, HL Ornaghi Jr, R Svoboda… - Molecules, 2021 - mdpi.com
Artificial neural networks (ANNs) are a method of machine learning (ML) that is now widely
used in physics, chemistry, and material science. ANN can learn from data to identify …

[KİTAP][B] Biomass gasification and pyrolysis: practical design and theory

P Basu - 2010 - books.google.com
This book offers comprehensive coverage of the design, analysis, and operational aspects
of biomass gasification, the key technology enabling the production of biofuels from all …

Equilibrium modeling of gasification: a free energy minimization approach and its application to a circulating fluidized bed coal gasifier

X Li, JR Grace, AP Watkinson, CJ Lim, A Ergüdenler - Fuel, 2001 - Elsevier
A non-stoichiometric equilibrium model based on free energy minimization is developed to
predict the performance of gasifiers. The model considers five elements and 44 species in …

Artificial neural network based modelling approach for municipal solid waste gasification in a fluidized bed reactor

DS Pandey, S Das, I Pan, JJ Leahy, W Kwapinski - Waste management, 2016 - Elsevier
In this paper, multi-layer feed forward neural networks are used to predict the lower heating
value of gas (LHV), lower heating value of gasification products including tars and entrained …

Modeling and optimization of the NOx emission characteristics of a tangentially fired boiler with artificial neural networks

H Zhou, K Cen, J Fan - Energy, 2004 - Elsevier
The present work introduces an approach to predict the nitrogen oxides (NOx) emission
characteristics of a large capacity pulverized coal fired boiler with artificial neural networks …

Assessment of producer gas composition in air gasification of biomass using artificial neural network model

J George, P Arun, C Muraleedharan - International Journal of Hydrogen …, 2018 - Elsevier
Energy generation from renewable and carbon-neutral biomass is significant in the context
of a sustainable energy framework. Hydrogen can be conveniently extracted from biomass …

Tar prediction in bubbling fluidized bed gasification through artificial neural networks

D Serrano, D Castelló - Chemical Engineering Journal, 2020 - Elsevier
Tars are one of the main barriers for the implementation of biomass gasification at industrial
scale. Among the considerable number of models to predict gas composition, there is a lack …

Simulation of biomass gasification with a hybrid neural network model

B Guo, D Li, C Cheng, Z Lü, Y Shen - Bioresource Technology, 2001 - Elsevier
Gasification of several types of biomass has been conducted in a fluidized bed gasifier at
atmospheric pressure with steam as the fluidizing medium. In order to obtain the gasification …

Machine learning-based modeling approaches for estimating pyrolysis products of varied biomass and operating conditions

J Shen, M Yan, M Fang, X Gao - Bioresource Technology Reports, 2022 - Elsevier
The pyrolysis products of different biomass are difficult to predict due to the complex
biomass properties and wide range of operating conditions. In this study, machine learning …

Multi-input multi-output (MIMO) ANN and Nelder-Mead's simplex based modeling of engine performance and combustion emission characteristics of biodiesel-diesel …

C Esonye, OD Onukwuli, AU Ofoefule… - Applied Thermal …, 2019 - Elsevier
Engine performance, combustion and emission characteristics of African pear (Dyacrodes
edulis) seed oil biodiesel-petrodiesel blends (B25, B50, B75 and B100) tested on four …