Prediction and optimization of biodiesel production by using ANN and RSM

Ceyla ÖZGÜR

doi:https://doi.org/10.18245/ijaet.1057170

Makale detayları

Prediction and optimization of biodiesel production by using ANN and RSM

Yazarlar:

Ceyla ÖZGÜR

Yayıncı:

Murat CİNİVİZ

Ana Başlıklar:

Uygulamalı fizik

Dergi:

International Journal of Automotive Engineering and Technologies 2022 Vol.11 Issue 2, pp.53-62

Belge Tipi:

Makale

Yayın Tarihi:

6/2022

Belge Dili:

İngilizce

Document ID (Org No.):

2000476298

Sıklık:

Aylık

eISSN:

2146-9067

DOI:

https://doi.org/10.18245/ijaet.1057170

Özet:

 

This experimental work examined the prediction and optimization of biodiesel production from pomegranate seed oil using Artificial Neural Networks (ANN) and Response Surface Methodology (RSM) with central composite design and The transesterification method chosen for biodiesel production. The Central Composite Design (CCD) optimization conditions were methanol/oil molar ratio (3:1 to 11:1), catalyst rate (0.5 wt% to 1.50 wt%), temperature (50 ℃ to 70 ℃) and time (45 min to 105 min). The process factors were optimized by using CCD based on the RSM method and developed an ANN model to predict biodiesel yield. The optimum yield was found 95.68% with optimum process parameters as 8.01:1 methanol/oil molar ratio, 1.08 wt% catalyst rate, 70 ℃ temperature and 45 min time. The coefficient of determination (R2) acquired from the response surface methodology model is 0.9887 and is better when compared to the coefficient of determination (R2) of 0.9691 acquired from the Artificial neural network model. According to the results, using RSM and ANN models is beneficial for optimizing and predicting the biodiesel production process.

Makale detayları

Prediction and optimization of biodiesel production by using ANN and RSM

Yazarlar: Ceyla ÖZGÜR

Yayıncı: Murat CİNİVİZ

Ana Başlıklar: Uygulamalı fizik

Dergi: International Journal of Automotive Engineering and Technologies 2022 Vol.11 Issue 2, pp.53-62

Belge Tipi: Makale

Yayın Tarihi: 6/2022

Belge Dili: İngilizce

Document ID (Org No.): 2000476298

Sıklık: Aylık

eISSN: 2146-9067

DOI: https://doi.org/10.18245/ijaet.1057170

Sayı

Yazarlar:

Ceyla ÖZGÜR

Yayıncı:

Murat CİNİVİZ

Ana Başlıklar:

Uygulamalı fizik

Dergi:

International Journal of Automotive Engineering and Technologies 2022 Vol.11 Issue 2, pp.53-62

Belge Tipi:

Makale

Yayın Tarihi:

6/2022

Belge Dili:

İngilizce

Document ID (Org No.):

2000476298

Sıklık:

Aylık

eISSN:

2146-9067

DOI:

https://doi.org/10.18245/ijaet.1057170