Experimental and articial neural network based studies on thermal conductivity of lightweight building materials
Yükleniyor...
Tarih
2017-04-01
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
European Journal of Technique (EJT)
Erişim Hakkı
info:eu-repo/semantics/openAccess
Attribution-NonCommercial-ShareAlike 3.0 United States
Attribution-NonCommercial-ShareAlike 3.0 United States
Özet
The growing concern about energy consumption of heating and cooling of
buildings has led to a demand for improved thermal performances of building
materials. In this study, an experimental investigation is performed to predict
the thermal insulation properties of wall structures of which the mechanical
properties are known; by using Levenberg-Marquardt training algorithm
based artificial neural network (ANNs) method for energy efficient buildings.
The produced samples are cement based and have relatively high insulation
properties for energy efficient buildings. In this regard, 102 new concrete
samples and their compositions are produced and their mechanical and
thermal properties are tested in accordance with ASTM and EN standards.
Then, comparisons have been made between the experimental results and the
ANN predicted results. It can be concluded that thermal performance of
lightweight materials could be predicted with high accuracy using artificial
neural network approach.
Açıklama
Anahtar Kelimeler
Concrete, Thermal Properties, Mechanical Properties, ANN, Energy Efficient Building
Kaynak
WoS Q Değeri
Scopus Q Değeri
Cilt
7
Sayı
1
Künye
Oktay, H., Fidan, Ş., Sevim, D., Polat, S. (2017). Experimental and articial neural network based studies on thermal conductivity of lightweight building materials. European Journal of Technique (EJT), 7 (1), pp.33-41.
