Çavka, Hasan Burak
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Burak Cavka, Hasan
Cavka, Hasan B.
Çavka,H.B.
Cavka, Hasan Burak
Cavka, Hasan B.
Çavka,H.B.
Cavka, Hasan Burak
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hasancavka@iyte.edu.tr
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02.02. Department of Architecture
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Current Staff
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Sustainable Development Goals
1NO POVERTY
0
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2ZERO HUNGER
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3GOOD HEALTH AND WELL-BEING
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4QUALITY EDUCATION
3
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5GENDER EQUALITY
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6CLEAN WATER AND SANITATION
0
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7AFFORDABLE AND CLEAN ENERGY
0
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8DECENT WORK AND ECONOMIC GROWTH
3
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9INDUSTRY, INNOVATION AND INFRASTRUCTURE
5
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10REDUCED INEQUALITIES
0
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11SUSTAINABLE CITIES AND COMMUNITIES
3
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12RESPONSIBLE CONSUMPTION AND PRODUCTION
2
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13CLIMATE ACTION
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14LIFE BELOW WATER
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15LIFE ON LAND
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16PEACE, JUSTICE AND STRONG INSTITUTIONS
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17PARTNERSHIPS FOR THE GOALS
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Documents
12
Citations
345
h-index
5
Documents
9
Citations
261
Scholarly Output
13
Articles
4
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3246/1951
Supervised MSc Theses
3
Supervised PhD Theses
1
WoS Citation Count
5
Scopus Citation Count
14
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0
Projects
1
WoS Citations per Publication
0.38
Scopus Citations per Publication
1.08
Open Access Source
8
Supervised Theses
4
| Journal | Count |
|---|---|
| 41st Conference on Education and Research in Computer Aided Architectural Design in Europe (ECAADE) -- SEP 18-23, 2023 -- Graz Univ Technol, Graz, AUSTRIA | 2 |
| Engineering Proceedings | 2 |
| Proceedings of the International Conference on Education and Research in Computer Aided Architectural Design in Europe | 2 |
| Engineering, Construction and Architectural Management | 1 |
| Journal of Integrated Design & Process Science | 1 |
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13 results
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Now showing 1 - 10 of 13
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.Master Thesis Multidisciplinary Collaboration in the Current Architecture, Engineering, and Construction Education of Ethiopia(01. Izmir Institute of Technology, 2021) Tadesse, Nebiat Sentayehu; Tadesse, Nebiat Sentayehu; Çavka, Hasan Burak; Çavka, Hasan BurakThe architecture, engineering, and construction (AEC) industry realize the significance of multidisciplinary collaboration, and as a result, the industry has been improving its work trends towards a more collaborative way. However, such improvement has not yet been fully adopted in the academic sector. Since universities are one of the main resources for the job positions in the industry, the current state of curriculum plays an important role in preparing future practitioners and helping to change the industry to a more collaborative trend. Therefore, understanding how multidisciplinary collaboration is being addressed in the curriculum is essential. The purpose of this research is to investigate if a multidisciplinary collaborative approach is being addressed in the current Ethiopian AEC education sector towards the enhancement of collaborative, communicative, and coordinative skills of the students. Data is collected from multiple sources by using different collection methods in order to have a comprehensive understanding of the existing curriculum. Addis Ababa University (AAU), the first university in Ethiopia with the highest number of students in the AEC faculties, is taken as a representative case study. A survey of the students, interviews with academicians, and a comprehensive curriculum review of the available AEC departments has been completed. The convergence triangulation method is used to analyze the data collected from various sources simultaneously. The results of the analysis indicate that various modules, courses, and programs are available that help the students acquire cross-disciplinary and theoretical knowledge, however not enough practical multidisciplinary activities are available. The research also provides insights on the potential of the current AEC curriculum towards achieving a multidisciplinary education system.Article Citation - Scopus: 4An Investigation of Shopping Mall Design Requirements †(Multidisciplinary Digital Publishing Institute (MDPI), 2023) Çavka,H.B.Shopping malls may be considered as controversial structures since they sometimes fail to comply with the expectations of the project stakeholders throughout the project life cycle. New mall projects often attract the attention of people since such a structure has a potential to reshape the neighborhood it is located in; however, the impact is usually negative. On the other hand, the parties involved in mall projects may be subject to criticism from both the public and the industry during the design, construction, and operation. In this study we conducted semi-structured interviews with five managers of an international company that provides real estate services worldwide, and mainly focuses on managing shopping centers within the context of Turkiye. During the interviews, we collected insights on shopping mall design and criteria that have an impact on the operational success or failure. We analyzed the interview data to understand the shopping mall design requirements from the experts’ perspectives. We summarized our investigation under three main categories as location, shop and brand mix, and design. Analyzed data indicates that the requirements and use of shopping malls evolve and change over time. The change is driven by things such as changing habits and expectations of the users and new marketing approaches. Understanding such changes is essential for designers and investors to propose new design approaches and space compositions in order to be able to adapt to the changes. Through our analysis of the collected data, we provided insights on requirements and new trends that affect the design of malls. As further explained in this paper, our analysis indicates a number of important topics during design such as the need to design to fit ever-changing spatial needs, providing feel-good environment for users, correct placement of spaces and stores related to each other, designing circulation that supports commercial activities, and designing with a consideration of operation and maintenance. According to the collected data, the trend of shopping mall design is towards integration of hybrid uses, free forms, more open spaces, increased emphasis on gastronomy, and enabling socializing while leveraging technology and being more sustainable. © 2023 by the author.Conference Object Citation - Scopus: 1Classification of Turkish and Balkan House Architectures Using Transfer Learning and Deep Learning(Springer Science and Business Media Deutschland GmbH, 2024) Yönder,V.M.; İpek,E.; Çetin,T.; Çavka,H.B.; Apaydın,M.S.; Doğan,F.Classifying architectural structures is an important and challenging task that requires expertise. Convolutional Neural Networks (CNN), which are a type of deep learning (DL) approach, have shown successful results in computer vision applications when combined with transfer learning. In this study, we utilized CNN based models to classify regional houses from Anatolia and Balkans based on their architectural styles with various pretrained models using transfer learning. We prepared a dataset using various sources and employed data augmentation and mixup techniques to solve the limited data availability problem for certain regional houses to improve the classification performance. Our study resulted in a classifier that successfully distinguishes 15 architectural classes from Anatolia and Balkans. We explain our predictions using grad-cam methodology. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.Conference Object Decoding and Predicting the Attributes of Urban Public Spaces With Soft Computing Models and Space Syntax Approaches(Ecaade-education & Research Computer Aided Architectural design Europe, 2023) Yonder, Veli Mustafa; Dogan, Fehmi; Cavka, Hasan Burak; Tayfur, Gokmen; Dulgeroglu, OzumPeople 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.Master Thesis An Inquiry Into the Adoption Process of Building Information Modeling in Architectural Practice(01. Izmir Institute of Technology, 2021) Baçnak, Tuğçe Zeynep; Çavka, Hasan Burak; Doğan, FehmiArchitectural practice went through various changes in time to adopt emerging technologies. Current and developing Building Information Modelling (BIM) technologies enables the integration of project partners in early phases of a project life cycle, differing from traditional project delivery processes. Since BIM impacts people, process, and technology (PPT), the adoption of BIM invites radical transformations in these aspects. The aim of this study is to investigate BIM adoption in small design offices from a socio-technical perspective by focusing on individuals' experiences to analyze the motivation for BIM adoption, the factors in adoption, and the strategies through which BIM is integrated into the architectural design processes. Case study analysis is used as the research method and data was collected through five interviews from two offices. Afterwards, analytical coding was implemented to analyze the data. Findings demonstrated that the level of BIM adoption is related to the coevolution of PPT. The inefficient workflow of previous processes was found to be the main motivation for BIM adoption. Whereas the impact of people was a major factor in the adoption phases on the strategies for adoption and barriers in adoption were mainly human related. People were a critical factor in making the decision to go through the adoption. Technological aspects, instead, were considered later when the decision on adoption was given. These findings showed that the impacts of BIM adoption factors, PPT, vary throughout the BIM adoption phases. The major human-based issues in early phases of adoption showed that to implement BIM in current workflows a socio-technical approach is essential.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 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 The Role of the Computational Designer From Computer-Aided Design To Machine Learning-Aided Design a Study on Generative Models and Design Prompts(Ecaade-education & Research Computer Aided Architectural design Europe, 2023) Yonder, Veli Mustafa; Dulgeroglu, Ozum; Dogan, Fehmi; Cavka, Hasan BurakThe rising sophistication of digital design technologies and instruments requires computational designers to acquire a broader set of abilities, such as expertise in a variety of digital models, scripting languages, and the ability to manage complicated data models. In the field of design, the concepts of machine learning-aided design and data-driven techniques contribute to the production of various and numerous design possibilities. Ultimately, this will lead the computational designer to redefine his or her power over the design protocol. In this paper, ChatGPT-3.5, Dall-E v2, and Stable Diffusion, cutting-edge artificial intelligence models, are used to construct sample design scenarios. Using a text mining application, the scenario-specific prompts were examined to explore these models' computational design potential.Master Thesis Analysis of Building Information Modeling (bim) Performance Using Big Data From a Construction Project(01. Izmir Institute of Technology, 2023) Bostan, Berkay Batuhan; Çavka, Hasan BurakThis study aims to propose a systematical approach for evaluating BIM performance from a main contractor's perspective based on big data from a construction project. Retrospective case study is used as the research approach. Data is collected through interviews with the main contractor firm, and data from the logged project information in project databases including ACONEX and Microsoft Excel files. A framework containing performance metrics, specifically tailored to evaluate BIM performance based on big data, is developed from the combined analysis of literature review, interviews with main contractor, and overview of the project data. Collected project data and interview data are analyzed using the developed framework. Results of the data analysis are verified through follow-up interviews with the main contractor firm. Findings of the study suggest that it is possible to evaluate the BIM performance through analysis of collected BIM big data using the proposed systematical approach. Several performance problems were identified during the data analysis. Follow-up interviews revealed that identified performance problems from the data analysis largely coincided with the real-life experiences and accurate data entry is the key criterion for the analysis to yield correct results. The proposed framework should be tested in wider range of studies and may serve as a foundation for a future benchmarking system. Future work should focus on refining performance metrics, establishing a BIM big data database for benchmarking, exploring data's potential to be used for real-time performance assessment, and implementation of emerging Artificial Intelligence (AI) techniques for the analysis of big data.