TR-Dizin İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/396
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Article Spatial Dimension of the Local Phenomenon in Kayseri(Gazi University, Faculty of Engineering Architecture, 2025-12-31) Ozmen, Nihan Mus; Asiliskender, BurakKayseri is in the centre of Anatolia, at the intersection of trade and military routes, and possesses a rich cultural heritage. Throughout its history, the city has hosted various civilizations, developing around a central castle and continuing to expand, particularly after the 19th century. Kayseri has long served as a meeting point for diverse cultures. Within this diversity, families known as locals, whose origins date back to the oldest neighbourhoods within the city walls, have held significant mercantile power. These local families regard themselves as the actual owners of Kayseri and have influenced the city's developmental trajectory. Over time, they have moved outward from the centre to newly developed neighbourhoods, first to the north and then to the east. This study examines the urban development of Kayseri in the 20th century and the spatial mobility of these local families. It employs qualitative methods such as ethnographic observation, oral history interviews, and GIS-based thematic mapping to analyse these movements in a multi-layered way. The study also aims to understand Kayseri's socio-cultural dynamics and historical texture by investigating the role of local families in the city's physical and functional transformations. In this context, it addresses the physical and functional changes in neighbourhoods vacated by these relocations.Article Forecasting the Consumer Price Index in Türkiye Using Machine Learning Models: A Comparative Analysis(Gazi Univ, 2025-09-01) Söylemez, İsmet; Ünlü, Ramazan; Nalici, Mehmet ErenThis study utilizes machine learning models to forecast Türkiye's Consumer Price Index (CPI), thereby addressing a critical gap in inflation prediction methodologies. The central research problem involves the forecasting of CPI in a volatile economic environment, which is essential for informed policymaking. The primary objective of this study is to evaluate the performance of three machine learning models, such as Decision Tree (DT), Random Forest (RF), and Support Vector Machine (SVM), in forecasting CPI over periods ranging from one to six months, utilizing data from 2012 to 2024. The study's unique contribution lies in the application of the \"SelectKBest\" method, which identifies the most relevant indices, thereby enhancing the efficiency of the models. An ensemble method, Averaging Voting, is also employed to combine the strengths of these models, producing more accurate and robust predictions. The findings indicate that while the RF model consistently generates the most accurate forecasts across all shifts, the SVM model demonstrates a particular strength in the domain of short-term predictions. The ensemble model demonstrates a substantial performance improvement, with a R2 value of 0.962 for one-month ahead of estimates and 0.956 for five-month forecasts. This combined approach has been shown to outperform individual models, offering a more reliable framework for CPI forecasting. The findings offer valuable insights for economic policymakers, enabling more precise and stable inflation predictions in Türkiye.Article Thermal Stresses in SOFC Stacks: The Role of Mismatch Among Thermal Conductivity of Adjacent Components(Tubitak Scientific & Technological Research Council Turkey, 2021-06-30) Aydin, Ozgur; Matsumoto, Go; Shiratori, YusukeGenerating power from renewable biogas in solid oxide fuel cells (SOFCs) is an environment-friendly, efficient, and promising energy conversion process. Biogas can be used in SOFCs via a reforming process for which dry reforming is more suitable as the reforming agent exists in the biogas mixture. Biogas can be directly reformed to H-2 -rich fuel stream in the anode chamber of a SOFC by the heat released during power generation. Exploiting the heat and water produced in the SOFC for internal reforming of biogas makes the energy conversion process very efficient; however, various challenges are reported. Thus, indirect internal reforming is opted for which a separate reforming domain is required. In an indirect internal reformer operating at usual conditions, dry reforming rate is quite high in the inlet and it decreases steeply toward the fuel outlet. Great temperature gradients develop over the reformer, since the dry reforming reaction is strongly endothermic. The abruptly varying rate of the reforming reaction affects the temperature fields in the adjacent components of SOFC and hence intolerable thermal stresses emerge on the SOFC components. In our preceding study, we graded the reforming domain, homogenized the temperature profile over the reforming domain, and executed performance and durability experiments. However, most of the experiments failed due to fracturing SOFC components hinting at existence of thermal stresses. In that study, we focused on minimizing the temperature gradients within the reforming domain; namely, we neglected the other processes. To eliminate the thermal stresses, we modeled the entire module of SOFC equipped with a reformer featuring a graded reforming domain. We found that the mismatch between the thermal conductivities of the adjacent module components is the major reason for the thermal stresses. When the mismatch is eliminated, thermal stresses disappear even if the reforming domain is not graded.Article Citation - WoS: 1Citation - Scopus: 1The Comparison of Fragility Curves of Moment-Resisting and Braced Frames Used in Steel Structures Under Varying Wind Load(Turkish Chamber Civil Engineers, 2025-03-01) Ozalp, Abdulkadir; Gokdemir, Hande; Ciftci, CihanIn this study, the performance of two different steel structure types (moment-resisting frame and braced frame) under wind loading was compared by addressing the fragility curves of these structure types. To perform this comparison, the dimensions of the members of these structural systems were first determined. Then, nonlinear static pushover analyses were conducted to assess the performance levels of each frame type. After applying these analyses, time-history analyses were performed with 100 different wind loads for each varying equivalent mean wind speed. Afterwards, the probability of exceeding the predetermined structural performance limits of the structure types was determined using Monte Carlo simulation method. Finally, the results of the simulation method were used to adapt the maximum likelihood estimation method to obtain the fragility curves of the structures. To conclude, it has been revealed that the material cost of the structure doubles when diagonal elements are used, but the wind speed required for a 100% collapse probability to occur in the braced frame is twice as high compared to the moment-resisting frame.Article 3D Sampling of K-Space With Non-Cartesian Trajectories in MR Imaging(Gazi Univ, Fac Engineering Architecture, 2025-02-03) Dundar, Mehmet Sait; Gumus, Kazim Z.; Yilmaz, BulentThis study presents an innovative approach to 3D k-space sampling in MR imaging using non-Cartesian concentric shell trajectories. The method involves 32 concentric shells of varying radii, allowing for rapid data acquisition through undersampling techniques. Simulations using IDEA software demonstrate that this approach can fill the k-space in less than one second, a significant time reduction compared to traditional FLASH sequences that can take 3-4 minutes. The concentric shell model enhances imaging efficiency by minimizing artifacts and ensuring uniform k-space filling, leading to higher resolution and faster scans. This technique shows promise for clinical applications, particularly in dynamic imaging scenarios such as acute stroke and pediatric radiology, where speed and precision are critical. As illustrated in Figure A, the concentric shell trajectories enable uniform k-space filling, significantly reducing scan times and improving image quality. These results are based on the simulations conducted with IDEA software.