Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Retrospective Bim Performance Analysis Based on Construction Big Data(Emerald Group Publishing Ltd, 2025) Bostan, Berkay Batuhan; Çavka, Hasan Burak; Cavka, Hasan Burak; Citipitioglu, Ahmet Muhtar; Pehlivan, Deniz ZiyaPurposeThe literature suggests employing big data and Building Information Modeling (BIM) to examine building projects from several perspectives. Nevertheless, the literature is deficient in thorough BIM performance evaluation methods grounded in big construction project data. This paper presents an evaluation framework outlining the data input requirements and necessary data to conduct research leveraging big data for the analysis of BIM performance.Design/methodology/approachData parameters and performance metrics included in the evaluation framework are derived from a synthesis of literature review, data overview and interviews. The construction data was analyzed using PowerBI after undergoing a quality control process. Analysis results were verified through interviews with the main contractor. The project data served to assess the evaluation framework.FindingsThe evaluation framework has ten data parameters, and six performance metrics categorized into three main categories. The findings indicate that the evaluation framework can be utilized to comment on BIM performance in a project, with a level of accuracy. Results indicated that ensuring the quality of tracked project data is crucial for obtaining reliable analysis results. Determining performance metrics and data parameters prior to data recording processes can help simplify the analysis process and ensure accurate analysis results.Originality/valueThe proposed framework offers a comprehensive performance evaluation methodology that leverages the innovative application of unique and challenging to acquire big data, allowing practitioners to assess BIM performance in relation to project time, cost and scope. Identified data parameters and novel performance metrics may provide the foundation of a guideline for construction project data logging to facilitate accurate BIM performance monitoring.Article An Analysis of Visitors’ Perceptions of Shopping Malls †(MDPI, 2023) Çavka, Hasan BurakShopping malls have been a significant part of our daily lives for decades. Their significance is derived from the use of these spaces based on great numbers of people, as well as the role malls play in culture. On the other hand, the design of malls has been constantly evolving according to the needs of users and the market. This study is based on survey data that we collected from ninety visitors of a shopping mall located in Izmir, Turkiye. Through the survey, we collected data on topics such as the participants’ visit frequency and reasons for visiting the mall, architectural and spatial features they favor and/or dislike, their opinions on where they perceive malls in everyday life, and their opinions on alternative spaces to malls. The data collection was finalized right before the pandemic, which significantly changed the way we think about public spaces, as well as malls, in relation to architecture. Analyzing collected data provides further insight into surveyed customers’ perception of spaces, the design of shopping malls, the use of the space, the preferred design features, as well as design features that drive customers away from the mall. The analysis was later compared and linked to studies in the literature. These research findings have the potential to be used in studies that evaluate mall design and space use, as well as in studies that compare the post-pandemic perception of spaces and the use of shopping malls. © 2023 by the author.Conference Object Citation - Scopus: 1Decoding and Predicting the Attributes of Urban Public Spaces With Soft Computing Models and Space Syntax Approaches(Education and research in Computer Aided Architectural Design in Europe, 2023) Yönder, Veli Mustafa; Doğan, Fehmi; Çavka, Hasan Burak; Tayfur, Gökmen; Dülgeroğlu, ÖzümPeople spend a considerable amount of time in public spaces for a variety of reasons, albeit at various times of the day and during season. Therefore, it is of utmost importance for both urban designers and local authorities to try to gain an understanding of the architectural qualities of these spaces. Within the scope of this study, squares and green parks in Izmir, the third largest city in Turkey, were analyzed in terms of their dimensions, landscape characteristics, the quality of their semi-open spaces, their landmarks, accessibility, and overall aesthetic quality. Using linear predictor, general regression neural networks, multilayer feed-forward neural networks (2-3-4-5-6 nodes), and genetic algorithms, soft computing models were trained in accordance with the results of the conducted analyses. Meanwhile, using space syntax methodologies, a visibility graph analysis and axial map analysis were conducted. The training results (i.e., root mean square error, mean absolute error, bad prediction rates for testing and training phases, and standard deviation of absolute error) were obtained in a comparative table based on training times and root mean square error values. According to the benchmarking table, the network that most accurately predicts the aesthetic score is the 2-node MLFNN, whereas the 6-node MLFN network is the least successful network. © 2023, Education and research in Computer Aided Architectural Design in Europe. All rights reserved.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.