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Prediction of the thermal conductivity of lightweight building materials utilizing backpropagation neural network method ; Geri yayılım sinir ağı yöntemi kullanılarak hafif yapı malzemelerinin ısıl iletkenliğinin tahmini
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.
Prediction of the thermal conductivity of lightweight building materials utilizing backpropagation neural network method ; Geri yayılım sinir ağı yöntemi kullanılarak hafif yapı malzemelerinin ısıl iletkenliğinin tahmini
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.
Prediction of the thermal conductivity of lightweight building materials utilizing backpropagation neural network method ; Geri yayılım sinir ağı yöntemi kullanılarak hafif yapı malzemelerinin ısıl iletkenliğinin tahmini
Oktay, Hasan (author) / Polat, Süleyman (author) / Fidan, Şehmus (author) / Batman Üniversitesi Mühendislik - Mimarlık Fakültesi Makine Mühendisliği Bölümü / orcid:0000-0002-0917-7844
2015-01-01
Conference paper
Electronic Resource
English
DDC:
690
Strength and thermal conductivity in lightweight building materials
| Online Contents | 2008
Strength and thermal conductivity in lightweight building materials
| Online Contents | 2008