Application of artificial neural networks to co-combustion of hazelnut husk–lignite coal blends
Yazarlar (4)
Doç. Dr. Zeynep YILDIZ UZUN Ondokuz Mayis Üniversitesi, Türkiye
Harun Uzun Ondokuz Mayis Üniversitesi, Türkiye
Selim Ceylan Ondokuz Mayis Üniversitesi, Türkiye
Prof. Dr. Yildiray Topcu Ondokuz Mayis Üniversitesi, Türkiye
| Makale Türü | Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | Bioresource Technology (Q1) | ||
| Dergi ISSN | 0960-8524 Dergi Bilgileri (2016) | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | İngilizce | Basım Tarihi | 01-2016 |
| Kabul Tarihi | – | Yayınlanma Tarihi | 01-01-2016 |
| Cilt / Sayı / Sayfa | 200 / 1 / 42–47 | DOI | 10.1016/j.biortech.2015.09.114 |
| Makale Linki | https://linkinghub.elsevier.com/retrieve/pii/S0960852415013978 | ||
| UAK Araştırma Alanları |
Adsorpsiyonlu Süreçler
Yakıtlar ve Yanma
Modelleme ve Optimizasyon
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| Özet |
| The artificial neural network (ANN) theory is applied to thermal data obtained by non-isothermal thermogravimetric analysis (TGA) from room temperature to 1000. °C at different heating rates in air to study co-combustion of hazelnut husk (HH)-lignite coal (LC) blends of various composition. The heating rate, blend ratio and temperature were used in the ANN analysis to predict the TG curves of the blends as parameters that affect the thermal behavior during combustion. The ANN model provides a good prediction of the TG curves for co-combustion with a coefficient of determination for the developed model of 0.9995. The agreement between the experimental data and the predicted values substantiated the accuracy of the ANN calculation. |
| Anahtar Kelimeler |
| Artificial neural network | Co-combustion | Hazelnut husk | Lignite coal | TGA |
Science Direct
Application of artificial neural networks to co-combustion of hazelnut husk–lignite coal blends
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Web of Science | 96 |
| Scopus | 101 |