Filtreler

2015 - 20173
Filtreleri Sıfırla

Ayarlar

Yazar: Polat, Süleyman × Konu: Energy Efficient Building ×

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Listeleniyor 1 - 3 / 3
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    Prediction of the thermal conductivity of lightweight building materials utilizing backpropagation neural network method
    (Fırat Üniversitesi, 2015) Oktay, Hasan; Polat, Süleyman; Fidan, Şehmus
    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.
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    Experimental and articial neural network based studies on thermal conductivity of lightweight building materials
    (European Journal of Technique (EJT), 2017-04-01) Oktay, Hasan; Fidan, Şehmus; Sevim, Davut; Polat, Süleyman
    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.