WoS İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394

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Author: search.filters.author.Aydogan, Emel KizilkayaWoS Q: search.filters.wosQuartile.Q2

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  • Article
    Citation - WoS: 5
    Citation - Scopus: 7
    Robust Multicriteria Sustainability Assessment in Urban Transportation
    (ASCE-Amer Soc Civil Engineers, 2023-06) Gulcimen, Sedat; Aydogan, Emel Kizilkaya; Uzal, Nigmet
    Developing methodologies to facilitate the planning of sustainable transport systems for decision makers (DMs) is becoming more critical. This study proposed a methodological framework for sustainable urban transportation to make decisions during urban transportation's design and planning stages. Urban transportation alternatives were evaluated by sustainability indicators that considered a triple bottom line approach's environmental, economic, and social aspects. To choose the best alternative sustainable transportation scenarios, two multicriteria decision-making (MCDM) methods, for example, a hesitant fuzzy analytical hierarchy process (HF-AHP) and multiple attribute utility model (MAUT), were integrated. First, eight sustainable transportation indicators that considered data availability from the transport sector were selected. The weights of the selected indicators were calculated using an HF-AHP. These indicators included carbon dioxide (CO2) emissions, energy consumption, depletion of nonrenewable resources, operational and maintenance costs, fuel and taxes, the number of fatalities or injuries, and motor vehicles for public transport per 10,000 population. Finally, sensitivity analysis was applied to validate the robustness. Based on HF-AHP results, the number of fatalities or injuries was the most significant among the eight indicators, with a 0.158 normalized weight (N-i). The results of this integrated methodology highlighted that Alternative 11, which was dominated by low-motorized vehicles (low-MVs), was the best sustainable alternative and Alternative 1 was the worst sustainable alternative, which was dominated by high-MVs with 0.69 and 0.27 total utility values, respectively. Low-motorized urban transportation alternatives showed higher sustainable performances than the motorized and high-motorized alternatives. This study proposed a novel and robust methodology for decisions on sustainable urban transportation projects and renovating current urban transportation systems.
  • Article
    Citation - WoS: 34
    Citation - Scopus: 37
    Green Building Envelope Designs in Different Climate and Seismic Zones: Multi-Objective ANN-Based Genetic Algorithm
    (Elsevier, 2022-10) Himmetoglu, Salih; Delice, Yilmaz; Aydogan, Emel Kizilkaya; Uzal, Burak; Kızılkaya Aydoğan, Emel
    In recent years, the major component of green building designs adopted by governments in order to reduce CO2 emissions as well as energy consumption is the green building envelope. The green envelope has the most important share in terms of thermal energy consumption, environment, and indoor comfort criteria. Determining the most suitable building envelope combination in the building life cycle is an important problem for designers. This study presents a new multi-objective approach that determines the most suitable green envelope designs for the buildings in different climate and earthquake zones, taking into account CO2 emissions, heating/cooling energy consumption, and material cost in terms of life cycle cost analysis. To this end, EnergyPlus building performance simulation program, artificial neural network (ANN), and genetic algorithm are used together. After the heating and cooling energy consumption, CO2 emissions, and material cost values are obtained for a certain number of the envelope alternatives with the EnergyPlus, ANN models that learn the working mechanism of EnergyPlus are trained according to these values. An ANN-based genetic algorithm procedure is developed to search the whole envelope alternative space by using the trained ANN models with EnergyPlus. The proposed approach allows searching in a very short time the whole alternative space, which is almost impossible to scan with EnergyPlus by reducing the time spent and the number of alternatives required for the design and simulation processes of the green building envelope. The proposed approach is performed for a design-stage city hospital structure in Turkey. Window type, the internal/external plaster, wall, and insulation materials along with the thicknesses of these materials, which consist of 46 different variables, are determined as envelope attributes for four different climate and seismic zones. The green building envelope designs obtained with the proposed approach are entered into EnergyPlus and the consistency of the results is compared. ANN models with an average accuracy of over 97% are developed. Without the CO2 emission cost in the life cycle cost, the mean absolute percent error (MAPE) values for each region are 0.67%, 0.6%, 0.58%, and 1.78%, respectively. With the CO2 emission cost in life cycle cost, the MAPE values for each region are 0.96%, 0.88%, 0.86%, and 0.43%, respectively. According to the obtained results, there is a consistency of over 99% between EnergyPlus and the proposed approach.