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EXPERIMENTAL AND ARTICIAL NEURAL NETWORK BASED STUDIES ON THERMAL CONDUCTIVITY OF LIGHTWEIGHT BUILDING MATERIALS

Yıl 2017, Cilt: 7 Sayı: 1, 33 - 41, 01.04.2017

Öz

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

Yıl 2017, Cilt: 7 Sayı: 1, 33 - 41, 01.04.2017

Öz

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Ayrıntılar

Diğer ID JA56NR36BB
Bölüm Araştırma Makalesi
Yazarlar

Davut Sevim Bu kişi benim

Şehmus Fidan Bu kişi benim

Süleyman Polat Bu kişi benim

Hasan Oktay Bu kişi benim

Yayımlanma Tarihi 1 Nisan 2017
Yayımlandığı Sayı Yıl 2017 Cilt: 7 Sayı: 1

Kaynak Göster

APA Sevim, D., Fidan, Ş., Polat, S., Oktay, H. (2017). EXPERIMENTAL AND ARTICIAL NEURAL NETWORK BASED STUDIES ON THERMAL CONDUCTIVITY OF LIGHTWEIGHT BUILDING MATERIALS. European Journal of Technique (EJT), 7(1), 33-41.

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