Master Degree / Yüksek Lisans Tezleri
Permanent URI for this collectionhttps://hdl.handle.net/11147/3008
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Master Thesis Thermal Comfort Analysis of Historical Mosques, Case Study: the Ulu Mosque, Manisa, Turkey(Izmir Institute of Technology, 2019) Diler, Yusuf; Gökçen Akkurt, Gülden; Turhan, CihanMosques are sanctuary places for Muslims where they can communicate with each other and perform their religious activities. Mosques differ from other building types in terms of occupancy period during a day with their unique function and intermittent operating schedule. Historical mosques with cultural heritage value, contain lots of artworks and represent Turkish culture for centuries. These mosques are originally built and serve without heating, cooling and mechanical ventilation systems. In this thesis, a systematic approach on monitoring and evaluating the microclimate and thermal comfort of historical mosques has been developed. This approach consists of two phases: detailed data collection and developing a dynamic building energy model. As a case study, The Ulu Mosque was monitored between 2015 and 2018. Thermal comfort evaluation of the mosque during worship periods were conducted based on the method provided by EN ISO 7730 standard. A dynamic Building Energy Performance Software, is used to model the mosque, and the model was calibrated by hourly indoor temperature data. The calibrated model, which meets ASHRAE 14 requirements, is used to develop retrofitting proposals. Thirteen different scenarios were proposed to improve thermal comfort during worship periods. The results were then evaluated according to EN 16883 standard in terms of the conservation of cultural heritage. Electric radiator heating with intermittent operating schedules was obtained as the best options to protect cultural heritage, while decreasing dissatisfaction level from 45% to 10% in winter months. Additionally, comparing with continuous operating schedule, intermittent operation saves 46.9% energy.Master Thesis Prediction of Energy Consumption of Residential Buildings by Artificial Neural Networks and Fuzzy Logic(Izmir Institute of Technology, 2012) Turhan, Cihan; Gökçen Akkurt, GüldenThere are several ways to attempt to forecast building energy consumption. Different techniques, varying from simple regression to dynamic models that are based on physical principles, can be used for simulation. A frequent hypothesis for all these models is that the input variables should be based on realistic data when they are available, otherwise the evaluation of energy consumption might be under or over estimated. The aim of this thesis is to create simple models based on artificial intelligence methods (artificial neural networks and fuzzy logic) as predicting tools and to compare these methods with a building energy performance software (KEP-IYTE ESS). Architectural projects and heat load calculation reports of 148 apartment buildings (5-13 storey) from three municipalities in Ġzmir provide the input data for the models and software. Building energy consumption is modeled as a function of zoning status, heating system type, number of floors, wall overall heat transfer coefficient, glass type, area/volume ratio, existence of insulation, total external surface area, orientation, number of flats, total external surface area/total useful area, total windows area/total external surface area, width/length, total wall area/total useful floor area, total lighting requirement/total useful floor area and total wall area. Four different artificial neural network models and one fuzzy logic model were constructed, trained, tested and the results were compared with the software outcomes. The lowest mean absolute percentage error (MAPE) and mean absolute deviation (MAD) of ANN models appeared to be 4.1% and 6.57, respectively, which shows that ANN can make accurate predictions. On the other hand, fuzzy model gave an 4.86% and 7.59 of MAPE and MAD, respectively, which can be considered as sufficient accuracy.