CANLI
Yükleniyor Veriler getiriliyor…
/ Makaleler / Scopus Detay
Scopus YÖKSİS Eşleşti

Neural network-based correlations for the thermal conductivity of propane

Fluid Phase Equilibria · Ağustos 2007

YÖKSİS DOI Eşleşmesi Bulundu

Bu Scopus makalesi YÖKSİS veritabanında da kayıtlı. Aşağıda YÖKSİS verilerini görebilirsiniz.

YÖKSİS Kayıtları
Neural network based correlations for the thermal conductivity of propane
Fluid Phase Equilibria · 2007 SCI 1 atıf
PROFESÖR MUSTAFA KOYUNCU →
Neural network based correlations for the thermal conductivity of propane
Fluid Phase Equilibria · 2007 SCI 1 atıf
PROFESÖR ELİFE ÖZNUR KARABULUT →
Neural network based correlations for the thermal conductivity of propane
Fluid Phase Equilibria · 2007 SCI 1 atıf
PROFESÖR ELİFE ÖZNUR KARABULUT →

Makale Bilgileri

DergiFluid Phase Equilibria
Yayın TarihiAğustos 2007
Cilt / Sayfa257 · 6-17
DOI10.1016/j.fluid.2007.04.024
Scopus ID2-s2.0-34250714771
Özet An alternative approach, exploiting neural networks, is proposed to develop thermal conductivity correlation of propane for the first time. In order to test the accuracy of the proposed technique and demonstrate its utility in fitting the thermal conductivity surface of propane, we have established a thermal conductivity correlation in terms of temperature and density, and then compared its predictions with those obtained by the conventional method. The results obtained are so impressive that the neural network correlation has lower overall average absolute deviations (AADs) in each data set. The requirement of using a high accuracy equation of state (EoS) for the correlations which include density as a variable has been avoided by developing thermal conductivity equations as a function of temperature and pressure. For this purpose, three neural network models have been constructed for the liquid, vapour, and supercritical phases. It is found that neural network approach produces a much better correlation for the liquid region while the predictions of the other two models are in substantial agreement with the traditional results. Consequently, neural networks offer a powerful tool for the development of thermal conductivity correlations of fluids, no matter whether an EoS is used or not. © 2007 Elsevier B.V. All rights reserved.

Yazarlar (2)

1
Elife Ö Karabulut
2
Mustafa Koyuncu

Anahtar Kelimeler

Neural networks Propane Thermal conductivity Transport properties correlation techniques

Kurumlar

Selçuk Üniversitesi
Selçuklu Turkey

Metrikler

3
Atıf
2
Yazar
4
Anahtar Kelime

Sistemimizdeki Yazarlar

EK
ELİFE ÖZNUR KARABULUT
PROFESÖR

Hızlı Erişim

DOI ile aç Scopus'ta aç Makaleler listesi