Journal Articles

Journal Publications

  1. 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, https://doi.org/10.1016/j.tsep.2021.100889
  2. Kartal, F., & Özveren, U. (2021). A comparative study for biomass gasification in bubbling bed gasifier using Aspen HYSYS. Bioresource Technology Reports, 100615.  https://doi.org/10.1016/j.biteb.2020.100615
  3. 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, 8(1):291–304. https://doi.org/10.18596/jotcsa.635073.
  4. Kartal,F., Cingisiz, Ş.,Özveren, U. (2021). Çan Kömürü Gazlaştırılmasının Sürüklemeli Akış Gazlaştırıcıda Aspen PLUS® Kullanılarak İncelenmesi. DEUFMD, 23(67), 309-318. https://doi.org/10.21205/deufmd.2021236727
  5. Sezer, S., Yakışık, H., Kartal, F., Fucucu, 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, 7(4) 265270. https://doi.org/10.17350/HJSE19030000195
  6. Kartal, F., & Özveren, U. (2020). A deep learning approach for prediction of syngas lower heating value from CFB gasifier in Aspen plus®. Energy, 209, 118457. https://doi.org/10.1016/j.energy.2020.118457
  7. 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 Engineering3(2), 55-64. https://dergipark.org.tr/tr/pub/jotcsb/issue/54720/659729
  8. 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
  9. Özveren, U. (2017). An artificial intelligence approach to predict gross heating value of lignocellulosic fuels. Journal of the Energy Institute, 90(3), 397-407.  https://doi.org/10.1016/j.joei.2016.04.003
  10. Özveren, U., Dilmac, O. 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, 1(Sp. is. 1), 69-76. https://dergipark.org.tr/tr/pub/jotcsb/issue/31518/345327
  11. 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
  12. 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, 58, 168-179. https://doi.org/10.1016/j.biombioe.2013.08.011