İşeri, Orçun Koral

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https://gcris.yasar.edu.tr/handle/123456789/13036
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Orçun Koral Iseri
Job Title
Öğrt.Gör.
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01.01.10.02. Mimarlık Bölümü
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Former Staff
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s4l2zioAAAAJ
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CWO-1855-2022

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8

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2016 IEEE Congress on Evolutionary Computation CEC 20161
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    Master Thesis
    Ön tasarım aşaması kararlarının enerji kullanımı üzerine etkisi: Duyarlıklık analizi ile kantitatif değerlendirme
    (2018) İşeri, Orçun Koral; Dursun, Onur
    Architectural design is a complex problem which contains multiple design parameters and constraints. Particularly, early architectural design includes all the major decision-making process that defines the framework of yearly energy demand of the unit. Due to time constraints and uncertainty of the energy demand at early design it is important to analyze the process starting from the early design. To reduce the complexity of model, quantify output uncertainty and lastly understand the relation between independent and dependent variables, in the current study, Morris and Sobol' global sensitivity analysis have applied for one zone office building to support a decision-making guidance for designers with regards to specified quasi random sampling methods. As energy modelling composes from physical properties of the building and weather type, procedure has been conducted for cold climate of Erzurum and hot-humid climate of Izmir. Firstly, ineffective parameters factor fixing is implied than factor prioritization is illustrated with Morris analysis. Afterwards, by using variance based Sobol' sensitivity analysis, first and total order effects are investigated for each climate. Thirdly, a performance filtering process has been executed for 100 best high energy performances of samples to illustrate each of them by presenting the valuable range values of parameters with Parallel Coordinate Plot (PCP). Lastly, a comparison has been implemented for how input parameter and its values are changing according to climate type. For further works, it is aiming to apply all the process for specified design of building by adding Monte Carlo filtering applications.
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    Conference Object
    Optimizing wall insulation material parameters in renovation projects using NSGA-II
    (Institute of Electrical and Electronics Engineers Inc., 2016) Hızır Gökhan Uyduran; Orçun Koral Iseri; Yarkin Ustunes; Onur Dursun
    Renovation works introduce numerous complexities that can only be addressed by those who excel in this specific design task. Such issues as energy consumption which requires examination of excessive alternatives is not of primary concern through the design process due further time limitations. However computational intelligence methods prove to be valuable decision support tools. To this end the current study aims to determine optimum wall insulation material parameters while minimizing optimization targets namely energy consumption and investment costs. To accomplish first energy model of an actual case located in the province of Selçuk was developed using OpenStudio cross platform. Following 54 simulations were run to generate the data base for the given parameters of selected insulation alternatives. Subsequently generated data base was employed to train predictive models of energy generation and investment costs. Finally optimization targets were minimized using NSGA-II algorithm. Results rigorously demonstrate that NSGA-II was able to converge a set of non-dominated set of solutions. © 2017 Elsevier B.V. All rights reserved.