Architecture / Mimarlık

Permanent URI for this collectionhttps://hdl.handle.net/11147/24

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  • Article
    Citation - WoS: 7
    Citation - Scopus: 8
    Performance Indices of Soft Computing Models To Predict the Heat Load of Buildings in Terms of Architectural Indicators
    (Yıldız Teknik Üniversitesi, 2017) Turhan, Cihan; Kazanasmaz, Zehra Tuğçe; Gökçen Akkurt, Gülden
    This study estimates the heat load of buildings in Izmir/Turkey by three soft computing (SC) methods; Artificial Neural Networks (ANNs), Fuzzy Logic (FL) and Adaptive Neuro-based Fuzzy Inference System (ANFIS) and compares their prediction indices. Obtaining knowledge about what the heat load of buildings would be in architectural design stage is necessary to forecast the building performance and take precautions against any possible failure. The best accuracy and prediction power of novel soft computing techniques would assist the practical way of this process. For this purpose, four inputs, namely, wall overall heat transfer coefficient, building area/ volume ratio, total external surface area and total window area/total external surface area ratio were employed in each model of this study. The predicted heat load is evaluated comparatively using simulation outputs. The ANN model estimated the heat load of the case apartments with a rate of 97.7% and the MAPE of 5.06%; while these ratios are 98.6% and 3.56% in Mamdani fuzzy inference systems (FL); 99.0% and 2.43% in ANFIS. When these values were compared, it was found that the ANFIS model has become the best learning technique among the others and can be applicable in building energy performance studies.
  • Article
    Citation - WoS: 7
    Citation - Scopus: 7
    The Importance of Internal Heat Gains for Building Cooling Design
    (Yıldız Teknik Üniversitesi, 2017) Coşkun, Turgay; Turhan, Cihan; Durmuş Arsan, Zeynep; Gökçen Akkurt, Gülden
    This paper aims to investigate the effect of internal heat gains on the cooling load of a building. The house occupied by three adult men is selected as the case study for paper. The house is in the third floor of the apartment. The apartment has four flats and it has no insulation around the external walls. The heat dissipation from lighting devices, electrical equipment and the occupants are calculated by using the DesignBuilder v4 Beta release simulation program. The temperature of the house is observed during three weeks by using hobo data loggers and calibration of the measurements is made with respect to weather data file of the flat. Detailed schedule based on time of operation and occupancy is prepared to get more accurate results. Annual energy consumption and cooling load of the house is determined by using the dynamic simulation program.