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ÇALIŞ USLU, BANU

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ÇALIŞ USLU

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    Energy saving potential and energy audit of a faculty building at Marmara University in Turkiye
    (2022-10-01) VARBAK NEŞE, SEÇİL; ÇALIŞ USLU, BANU; AKPOLAT, ALPER NABİ; DURSUN, ERKAN; Sönmez T., Varbak Neşe S., Çaliş Uslu B., Akpolat A. N. , Dursun E.
    According to the Council of Higher Education\"s records in 2022, one hundred thirty-one public universities operate in Turkiye. If the energy efficiency in faculty buildings is improved by 20%, 1.458 million U.S. dollars savings per year would be possible. This paper presents the energy profile and energy audit of the Faculty of Technology at Marmara University, in Istanbul Türkiye. The energy efficiency opportunities for faculty building are investigated depending on the energy audit results. The fact that the faculty building is uninsulated therefore this situation causes severe energy losses. The annual heating energy requirement of this university building, which has an average construction area of 15,000 m², is 297,728 kWh. Only an average of 56,987 kWh in fuel consumption and up to 20% energy savings can be achieved with thermal insulation. However, when the existing lighting fixtures are replaced with Light Emitting Diode (LED) fixtures, the annual savings amount is $6,198. The results of this study enable search of sustainable solutions for reducing energy consumption and improving energy audits for faculty buildings.
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    Municipal solid waste management: A case study utilizing DES and GIS
    (2023-10-02) ÇALIŞ USLU, BANU; DOĞAN, BUKET; ÜLKÜ, EYÜP EMRE; Çaliş Uslu B., Kerçek V. A., Şahin E., Perera T., Doğan B., Ülkü E. E.
    This research aims to compare two well-known solution methodologies, namely Geographical Information Systems (GIS) and Discrete Event Simulation (DES), which are used to design, analyze, and optimize the solid waste management system based on the locations of the garbage bins. A significant finding of the study was that the application of the simulation methodology for a geographical area of a size of 278km2was challenging in that the addition of the geographical conditions to the developed model proved to be time-consuming. On the other hand, the simulation model that was developed without adding geographical conditions revealed that the number of bins could be reduced by 60.3% depending on the population size and garbage density. However, this model could not be implemented since the required walking distance was higher than 75 m, which is greater than the distance the residents could be reasonably expected to travel to reach a bin. Thus, using a cutoff value of 75 m, the total number of bins can be reduced by 30% on average with regard to the result obtained from the GIS-based solution. This can lead to an annual cost reduction of 93.706 € on average in the collection process and carbon dioxide release reduction of 18% on average.