Journal Articles

Journal Publications and Preprints

  1. Kartal, F., & Özveren, U. (2022). Energy and Exergy Analysis of Entrained Bed Gasifier/GT/Kalina Cycle Model for CO2 Co-gasification of Waste Tyre and Biochar. Fuel (Q1 Journal), 331, Part 1, 125943. https://doi.org/10.1016/j.fuel.2022.125943.
  2. Kartal, F., & Özveren, U. (2022). The dimensional design of a laboratory-scale fluidized bed gasifier using machine learning based on a kinetic method. Energy Conversion and Management (Q1 Journal), 269, 116183. https://doi.org/10.1016/j.enconman.2022.116183
  3. Kekik, B., Yakışık, H., & Özveren, U. (2022). Investigation of light crude oil removal using biocoal from torrefaction of biomass waste. Bioresource Technology Reports (Q1 Journal)19, 101139https://doi.org/10.1016/j.biteb.2022.101139
  4. Kartal, F., Sezer, S., & Özveren, U. (2022). Investigation of steam and CO2 gasification for biochar using a circulating fluidized bed gasifier model in Aspen HYSYS. Journal of CO2 Utilization (Q1 Journal), 62, 102078. https://doi.org/10.1016/j.jcou.2022.102078
  5. Kekik, B., & Özveren U. (2022). Investigation of Microalgae Gasification Under Steam Atmosphere in Downdraft Gasifier by using Aspen Plus®. Eskişehir Technical University Journal of Science and Technology A – Applied Sciences and Engineering (TR-Index Journal), 23(2), 149-160. https://doi.org/10.18038/estubtda.873981
  6. Kartal, F., & Özveren, U. (2022). Prediction of activation energy for combustion and pyrolysis by means of machine learning. Thermal Science and Engineering Progress (Q1 Journal), 101346. https://doi.org/10.1016/j.tsep.2022.101346
  7. Kartal, F., & Özveren, U. (2022). Investigation of an integrated circulating fluidized bed gasifier/steam turbine/proton exchange membrane (PEM) fuel cell system for torrefied biomass and modeling with artificial intelligence approach. Energy Conversion and Management  (Q1 Journal), 263, 115718. https://doi.org/10.1016/j.enconman.2022.115718
  8. Yakışık, H., & Özveren U. (2022). The impact of the COVID-19 pandemic on the air quality (PM10) in Şile district of İstanbul, Turkey. International Journal of Advances in Engineering and Pure Sciences (TR-Index Journal), 34(2),198-205. https://doi.org/10.7240/jeps.877396
  9. Kartal, F., & Özveren, U. (2022). Investigation of The Chemical Exergy of Torrefied Biomass from Raw Biomass by Means of Machine Learning. Biomass and Bioenergy  (Q1 Journal), 159, 106383. https://doi.org/10.1016/j.biombioe.2022.106383
  10. Sezer, S., Kartal, F., & Özveren, U. (2022). Prediction of combustion reactivity for lignocellulosic fuels by means of machine learning. Journal of Thermal Analysis and Calorimetry  (Q2 Journal),147, 9793–9809. https://doi.org/10.1007/s10973-022-11208-8
  11. Sezer, S., Kartal, F., & Özveren, U. (2022). Artificial Intelligence Approach in Gasification Integrated Solid Oxide Fuel Cell Cycle. Fuel  (Q1 Journal), 311, 122591.  https://doi.org/10.1016/j.fuel.2021.122591
  12. Kartal, F., & Özveren, U. (2022). Prediction of Torrefied Biomass Properties from Raw Biomass. Renewable Energy   (Q1 Journal), 182, 578-591. https://doi.org/10.1016/j.renene.2021.10.042
  13. Özveren, U., Sezer, S., Kartal, F., Özdoğan, Z. S. (2022). Investigation of steam gasification in thermogravimetric analysis by means of evolved gas analysis and machine learning. Energy  (Q1 Journal), 239, Part C, 122232. https://doi.org/10.1016/j.energy.2021.122232
  14. Sezer, S., Fucucu, N. N., Özveren, U. (2021). Investigation of Oak Wood Biochar Gasification in Downdraft
    Gasifier Using Aspen Plus Simulation. Bioenergy Studies, 1(1), 15-23. http://doi.org/10.51606/bes.2021.3
  15. Kartal, F., & Özveren, U. (2021). An Improved Machine Learning Approach to Estimate Hemicellulose, Cellulose, and Lignin in Biomass. Carbohydrate Polymer Technologies and Applications, 2, 100148. https://doi.org/10.1016/j.carpta.2021.100148
  16. Kartal, F., & Özveren, U. (2021). Novel multistage kinetic models for biomass pyrolysis and CO2 gasification by means of reaction pathways. Bioresource Technology Reports  (Q1 Journal), 25, 100804. https://doi.org/10.1016/j.biteb.2021.100804  
  17. Sezer, S., Kartal, F., & Özveren, U. (2021). Prediction of Chemical Exergy of Syngas From Downdraft Gasifier by Means of Machine Learning. Thermal Science and Engineering Progress (Q1 Journal), 25, 101031. https://doi.org/10.1016/j.tsep.2021.101031
  18. Sezer, S., & Özveren, U. (2021). Investigation of syngas exergy value and hydrogen concentration in syngas from biomass gasification in a bubbling fluidized bed gasifier by using machine learning. International Journal of Hydrogen Energy (Q1 Journal), 46(39), 20377-20396. https://doi.org/10.1016/j.ijhydene.2021.03.184
  19. Sezer, S., & Özveren, U. (2021). Investigation of Hazelnut Husk Combustion by using A Novel Non-linear Kinetic Model through Thermogravimetric Analysis. Sakarya University Journal of Science (TR-Index Journal), 25(2), 42-54. https://doi.org/10.16984/saufenbilder.811684
  20. Sezer, S., Kartal, F., & Özveren, U. (2021). The Investigation of Co-Combustion Process for Synergistic Effects Using Thermogravimetric and Kinetic Analysis with Combustion Index.Thermal Science and Engineering Progress (Q1 Journal), 23, 100889. https://doi.org/10.1016/j.tsep.2021.100889
  21. Kartal, F., & Özveren, U. (2021). A comparative study for biomass gasification in bubbling bed gasifier using Aspen HYSYS. Bioresource Technology Reports (Q1 Journal), 13, 100615.  https://doi.org/10.1016/j.biteb.2020.100615
  22. Yakışık H, Özveren U. (2021). Synthesis of Polyaniline/Biochar Composite Material and Modeling with Nonlinear Model for Removal of Copper (II) Heavy Metal Ions. JOTCSA (TR-Index Journal), 8(1), 291–304. https://doi.org/10.18596/jotcsa.635073.
  23. Kartal, F., Cingisiz, Ş., Özveren, U. (2021). Çan Kömürü Gazlaştırılmasının Sürüklemeli Akış Gazlaştırıcıda Aspen PLUS® Kullanılarak İncelenmesi. DEUFMD (TR-Index Journal), 23(67), 309-318. https://doi.org/10.21205/deufmd.2021236727
  24. Sezer, S., Yakışık, H., Kartal, F., Fuçucu, N. N., Dalbudak, Y., Yaşar, S., Özveren, U. (2020). Prediction of NOx Emissions with A Novel ANN Model in Adana. Hittite Journal of Science and Engineering (TR-Index Journal), 7(4), 265–270. https://doi.org/10.17350/HJSE19030000195
  25. Kartal, F., & Özveren, U. (2020). A deep learning approach for prediction of syngas lower heating value from CFB gasifier in Aspen plus®. Energy (Q1 Journal), 209, 118457. https://doi.org/10.1016/j.energy.2020.118457
  26. Sezer, S., & Özveren, U. (2020). Energy and Exergy Analysis on Bubbling Fluidized Bed Gasifier Using Aspen Plus Simulation. Journal of the Turkish Chemical Society Section B: Chemical Engineering (TR-Index Journal), 3(2), 55-64. https://dergipark.org.tr/tr/pub/jotcsb/issue/54720/659729
  27. Sezer, S., & Özveren, U. (2019). Simulation of rice straw gasification in bubbling bed reactor using ASPEN PLUS.  Gedik University International Journal Of Engineering And Natural Sciences (IJENS), 3(2), 7-14. https://www.gedik.edu.tr/wp-content/uploads/IJENS-Vol.2-No.2.pdf
  28. Özveren, U. (2017). An artificial intelligence approach to predict gross heating value of lignocellulosic fuels. Journal of the Energy Institute (Q1 Journal), 90(3), 397-407https://doi.org/10.1016/j.joei.2016.04.003
  29. Özveren, U., Dilmaç, Ö. F., Mert, M. S., & Albayrak, F. K. (2017). Investigation of the Chemical Exergy of Torrefied Lignocellulosic Fuels using Artificial Neural Networks. Journal of the Turkish Chemical Society Section B: Chemical Engineering (TR-Index Journal), 1(Sp. is. 1), 69-76. https://dergipark.org.tr/tr/pub/jotcsb/issue/31518/345327
  30. Özveren, U. (2016). An artificial intelligence approach to predict a lower heating value of municipal solid waste. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 38(19), 2906-2913. https://doi.org/10.1080/15567036.2015.1107864
  31. Özveren, U., & Özdoğan, Z. S. (2013). Investigation of the slow pyrolysis kinetics of olive oil pomace using thermo-gravimetric analysis coupled with mass spectrometry. Biomass and Bioenergy (Q1 Journal), 58, 168-179. https://doi.org/10.1016/j.biombioe.2013.08.011