Sürdürülebilir Yeşil Kampüs Koleksiyonu / Sustainable Green Campus Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7755
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Master Thesis Simultaneous Improvement in Visual and Acoustic Performance by Modifying Common Design Components in Lecture Halls(Izmir Institute of Technology, 2017) Öztürk, Yasemin; Kazanasmaz, Zehra TuğçeProviding indoor comfort conditions at optimum level in educational buildings increases the concentration, the desire for learning and occupants’ performance. The learning environment’s appeal for students and teachers are mostly derived from their visual and aural sensations. So, properly-designed lighting and acoustic conditions have become an important concern. Daylighting is a component of energy saving strategy. It provides visual performance and comfort to support executing tasks, additionally to achieve aesthetic and occupants’ appraisal of the physical environment. However, too high background noise and low intelligibility lead to disturbance in hearing and understanding. Such problems mainly cause the lack of concentration, which disturb occupants’ satisfaction with the indoor acoustic environment. Both students and lecturers raise their voices to communicate better when there is poor reverberation and clarity. Yet, measures and precautions to improve one aspect are not enough. Designers/researchers can establish an integrated approach to deal with the aspects of daylighting and acoustics under common design criteria; since, one design alternative developed to improve sound distribution modifies the visual performance either in an effective way or in an unfavorable way. It is necessary to propose common design alternatives, such as ceiling geometry, seating layout and material combination to conclude simultaneous enhancement in visual and acoustic performance. To achieve that, this thesis presents analyses of DIALux and ODEON models of a lecture hall proposing design component choices for ceiling geometry, seating layout, and material combinations. Simulation findings direct out attention to how to design a lecture hall in an integrated approach.Master Thesis A Prediction Model for Daylighting Illuminance for Office Buildings(Izmir Institute of Technology, 2008) Binol, Selcen; Kazanasmaz, Zehra TuğçeDaylight is a primary light source for the office buildings where a comfortable and an efficient working environment should be provided mostly during day time. Evidence that daylight is desirable can be found in research as well as in observations of human behavior and the arrangement of office space. A prediction model was then developed to determine daylight illuminance for the office buildings by using Artificial Neural Networks (ANNs). A field study was performed to collect illuminance data for four months in the subject building of the Faculty of Architecture in .zmir Institute of technology. The study then involved the weather data obtained from the local Weather Station and building parameters from the architectural drawings. A three-layer ANNs model of feed-forward type was constructed by utilizing these parameters. Input variables were date, hour, outdoor temperature, solar radiation, humidity, UV Index, UV dose, distance to windows, number of windows, orientation of rooms, floor identification, room dimensions and point identification. Illuminance was used as the output variable. The first 80 of the data sets were used for training and the remaining 20 for testing the model. Microsoft Excel Solver used simplex optimization method for the optimal weights. Results showed that the prediction power of the model was almost 97.8%. Thus the model was successful within the sample measurements. NeuroSolutions Software performed the sensitivity analysis of the model. On the top of daylight consideration, this model can supply beneficial inputs in designing stage and in daylighting performance assessment of buildings by making predictions and comparisons. Investigation about this subject can be able to support the office buildings. having intended daylighting comfort conditions.
