Investigation of the slow pyrolysis kinetics of olive oil pomace using thermo-gravimetric analysis coupled with mass spectrometry U Özveren, ZS Özdoğan Biomass and bioenergy 58, 168-179, 2013 | 74 | 2013 |
A deep learning approach for prediction of syngas lower heating value from CFB gasifier in Aspen plus® F Kartal, U Özveren Energy 209, 118457, 2020 | 72 | 2020 |
Investigation of syngas exergy value and hydrogen concentration in syngas from biomass gasification in a bubbling fluidized bed gasifier by using machine learning S Sezer, U Özveren International Journal of Hydrogen Energy 46 (39), 20377-20396, 2021 | 49 | 2021 |
An artificial intelligence approach to predict gross heating value of lignocellulosic fuels U Ozveren Journal of the Energy Institute 90 (3), 397-407, 2017 | 40 | 2017 |
A comparative study for biomass gasification in bubbling bed gasifier using Aspen HYSYS F Kartal, U Özveren Bioresource Technology Reports 13, 100615, 2021 | 29 | 2021 |
Prediction of torrefied biomass properties from raw biomass F Kartal, U Özveren Renewable Energy 182, 578-591, 2022 | 27 | 2022 |
Prediction of chemical exergy of syngas from downdraft gasifier by means of machine learning S Sezer, F Kartal, U Özveren Thermal Science and Engineering Progress 26, 101031, 2021 | 23 | 2021 |
Investigation of steam gasification in thermogravimetric analysis by means of evolved gas analysis and machine learning U Özveren, F Kartal, S Sezer, ZS Özdoğan Energy 239, 122232, 2022 | 22 | 2022 |
Energy and exergy analysis of entrained bed gasifier/GT/Kalina cycle model for CO2 co-gasification of waste tyre and biochar F Kartal, U Özveren Fuel, 125943, 2023 | 21 | 2023 |
Artificial intelligence approach in gasification integrated solid oxide fuel cell cycle S Sezer, F Kartal, U Özveren Fuel 311, 122591, 2022 | 21 | 2022 |
An improved machine learning approach to estimate hemicellulose, cellulose, and lignin in biomass F Kartal, U Özveren Carbohydrate Polymer Technologies and Applications 2, 100148, 2021 | 21 | 2021 |
Prediction of activation energy for combustion and pyrolysis by means of machine learning F Kartal, U Özveren Thermal Science and Engineering Progress 33, 101346, 2022 | 20 | 2022 |
The investigation of co-combustion process for synergistic effects using thermogravimetric and kinetic analysis with combustion index S Sezer, F Kartal, U Özveren Thermal Science and Engineering Progress 23, 100889, 2021 | 20 | 2021 |
Investigation of the chemical exergy of torrefied biomass from raw biomass by means of machine learning F Kartal, U Özveren Biomass and Bioenergy 159, 106383, 2022 | 19 | 2022 |
Investigation of an integrated circulating fluidized bed gasifier/steam turbine/proton exchange membrane (PEM) fuel cell system for torrefied biomass and modeling with … F Kartal, U Özveren Energy Conversion and Management 263, 115718, 2022 | 17 | 2022 |
An artificial intelligence approach to predict a lower heating value of municipal solid waste U Ozveren Energy sources, part a: recovery, utilization, and environmental effects 38 …, 2016 | 13 | 2016 |
Investigation of steam and CO2 gasification for biochar using a circulating fluidized bed gasifier model in Aspen HYSYS F Kartal, S Sezer, U Özveren Journal of CO2 Utilization 62, 102078, 2022 | 12 | 2022 |
Theoretical and experimental investigation of biomass and coal gasification U Özveren PQDT-Global, 2013 | 11 | 2013 |
Pem yakıt hücrelerinin yapay sinir ağları ile modellenmesi U ÖZVEREN | 11 | 2006 |
Novel multistage kinetic models for biomass pyrolysis and CO2 gasification by means of reaction pathways F Kartal, U Özveren Bioresource Technology Reports 15, 100804, 2021 | 7 | 2021 |