Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Simultaneous Topology Design and Optimization of Pde Constrained Processes Based on Mixed Integer Formulations(Elsevier, 2024) Ertürk, Emrullah; Deliismail, Özgün; Şıldır, HasanSimultaneous topological design and optimization of complex processes that are described by partial differential equations is a challenging but promising research area. Widely adopted nested and sequential approaches are mostly applicable based on heuristic solutions, hindering the theoretical improvement potential due to decentralized decision-making in subsequent stages with a significant number of trial-and-error procedures. This study introduces a mixed integer formulation addressing the governing equations and case-dependent topological constraints at each discretization point, enabling solutions through rigorous solvers under process-related constraints and objectives. Nonlinear expressions in the formulations are further tailored using piecewise linear approximations, still representing the major nonlinear trends through a mixed-integer linear nature to favor global optimality and benefit from computational advancements, when needed. Heat and Stokes flow problems are used as case studies to demonstrate the applicability of the methodology. © 2024 Elsevier B.V.Article Citation - WoS: 5Citation - Scopus: 6An Investigation of the Design Process's Effect on a High-Performance Building's Actual Energy System Performance(Ios Press, 2022) Terim Çavka, Belgin; Çavka, Hasan Burak; Salehi, M. MahdiThe design intent and the performance targets of projects may sometimes fail to match a building's actual post-occupancy performance. The mismatch of intended and actual building performance can be attributed to multifarious reasons. This study focuses on the role of project decisions made during design as one of the reasons of shortfall. The aim of the study is to unveil the design decision-making process of a state-of-the-art research building through the analysis of project's available set of IDP (Integrated Design Process) documentation. To understand the relationship and correlation between the energy performance gap and the decision-making process of the case building, we investigated the design decisions' effect on the actual performance. The particular emphasis is on the decisions that were based on assumptions rather than measured actual test data for the proposed innovative building systems. The designed heat recovery system, which was dependent on recovered heat from the neighboring research building, had a significant effect on the building's poor energy performance. We investigated collected project data from coordination meetings, thoroughly analyzed project documentation, and quantified the building's actual energy performance data. The analysis of the project information shows the ripple effect of decisions that were made based on assumptions, that triggered shortfalls in the building's overall actual performance. Our qualitative analysis indicates that the poor system performance during operations was related with the design decisions that were not based on the measurement of the actual performance of the existing systems in the neighboring building. The performance of the heat recovery from the neighboring building as a highly dependent Energy Conservation Measure (ECM) analyzed through collected documents and data. The ambiguity of the available heat potential from the neighboring building and related testing issues defined on an explanatory timeline of process coding. The conclusion includes recommendations for the design decision-making process for innovative system integrations for high-performance buildings, and underlines the importance of IDP for complex buildings.Article Citation - WoS: 17Citation - Scopus: 22Exploring the Factors Influencing Big Data Technology Acceptance(Institute of Electrical and Electronics Engineers Inc., 2023) Rahman, Nayem; Daim, Tuğrul U.; Başoğlu, Ahmet NuriBig Data has received great attention in academic literature and industry papers. Most of the experiments and studies focused on publishing results of big data technologies development, machine learning algorithms, and data analytics. To the best of our knowledge, there is not yet any comprehensive empirical study in the academic literature on big data technology acceptance. The statistical results of this model provide a compelling explanation of the relationships among the antecedent variables and the dependent variables. The analysis of the structural model reveals that the hypothesis tests are significant for 8 out of 12 path relationships. IEEEArticle Citation - WoS: 6Citation - Scopus: 7Determination of Optimum Environmental Conservation: Using Multi-Criteria Decision-Making Techniques(Taylor and Francis Ltd., 2011) Çelik, Hüseyin Murat; Türk, ErsinThe type and degree of conservation areas in Turkey legally dictate the kind of land uses that can and cannot take place in a conservation area. Thus, the conservation scheme is one of the most important criteria in designing an urban land-use plan. The aim of this study is to analyse the effects of various conservation decisions on land-use allocation holding everything else constant. This study uses a land-allocation mathematical programme formulated by Hanink and Cromley [(1998) Land-use allocation in the absence of complete market values, Journal of Regional Science, 38, pp. 465-480] that integrates the geographical information systems with a generalized assignment problem to determine an optimum level of conservation scheme in Cesme/Izmir, a coastal resort in Turkey. The findings state that the proposed technique is indeed very useful and promising to answer diversified practical issues on a more rational basis.Article Citation - WoS: 66Citation - Scopus: 76Using Decision Trees for Determining Attribute Weights in a Case-Based Model of Early Cost Prediction(American Society of Civil Engineers (ASCE), 2008) Doğan, Sevgi Zeynep; Arditi, David; Günaydın, Hüsnü MuratThis paper compares the performance of three different decision-tree-based methods of assigning attribute weights to be used in a case-based reasoning (CBR) prediction model. The generation of the attribute weights is performed by considering the presence, absence, and the positions of the attributes in the decision tree. This process and the development of the CBR simulation model are described in the paper. The model was tested by using data pertaining to the early design parameters and unit cost of the structural system of residential building projects. The CBR results indicate that the attribute weights generated by taking into account the information gain of all the attributes performed better than the attribute weights generated by considering only the appearance of attributes in the tree. The study is of benefit primarily to researchers, as it compares the impact of attribute weights generated by three different methods and, hence, highlights the fact that the prediction rate of models such as CBR largely depends on the data associated with the parameters used in the model.Article Citation - WoS: 87Citation - Scopus: 100Determining Attribute Weights in a Cbr Model for Early Cost Prediction of Structural Systems(American Society of Civil Engineers (ASCE), 2006) Doğan, Sevgi Zeynep; Arditi, David; Günaydın, Hüsnü MuratThis paper compares the performance of three optimization techniques, namely feature counting, gradient descent, and genetic algorithms (GA) in generating attribute weights that were used in a spreadsheet-based case based reasoning (CBR) prediction model. The generation of the attribute weights by using the three optimization techniques and the development of the procedure used in the CBR model are described in this paper in detail. The model was tested by using data pertaining to the early design parameters and unit cost of the structural system of 29 residential building projects. The results indicated that GA-augmented CBR performed better than CBR used in association with the other two optimization techniques. The study is of benefit primarily to researchers as it compares the impact attribute weights generated by three different optimization techniques on the performance of a CBR prediction tool.