Prediction of the thermal conductivity of lightweight building materials utilizing backpropagation neural network method
Yükleniyor...
Dosyalar
Tarih
2015
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Fırat Üniversitesi
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 and roof structures of
which the mechanical properties are known, by using backpropagation artificial neural network (ANNs) method. The
produced samples are cement based and have relatively high
insulation properties for energy efficient buildings. In this
regard, 102 new 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 determined thermal conductivity
of the newly produced structures, which are obtained from
experimental method and ANN method that uses mechanical
properties as input parameters. From the test results, since the
percentage errors in the thermal conductivity values between
experimental data and neural network prediction vary from -
1.09% to 6.4%, It can be concluded that the prediction of the
artificial neural network has proceed in the correct manner.
Açıklama
Anahtar Kelimeler
Concrete, Thermal Conductivity, Mechanical Properties, Back-Propagation, Energy Efficient Building
Kaynak
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Scopus Q Değeri
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Künye
Oktay, H., Polat, S., Fidan, Ş. (2015). Prediction of the thermal conductivity of lightweight building materials utilizing backpropagation neural network method. International Conference on Advances and Innovations in Engineering (ICAIE), 10-12 May 2015, Elazığ, Turkey
