Sürdürülebilir Kalkınma Amaçları

  • ArticleAçık Erişim2026
    A Deep Learning-Based Decision Support System for Structural Component Detection From Architectural Floor Plans

    Karakose, Perihan; Ince, Elif Gokce; Eren, Erkin; Atar, Muhammed; Cakil, Burak; Ince, Ozan

    Earthquake-resistant design of reinforced concrete (RC) buildings is initiated during the architectural design stage, where the placement and directions of vertical load-bearing elements are defined. The configuration of these elements plays a critical role in the seismic performance of RC structures. In this study, a decision-support system is proposed to automatically identify load-bearing elements from architectural floor plans and to assess torsional irregularity and shear wall distribution. A dataset comprising 600 architectural floor plans of existing buildings was compiled, in which structural components were manually annotated and used to train a YOLO (You Only Look Once)-based detection model. The developed system detects vertical load bearing elements in the floor plan and subsequently evaluates their arrangement using structural engineering criteria, including torsional irregularity and shear wall ratio. The results show that the proposed approach enables rapid and accurate evaluation of architectural floor plans, offering effective support during the early design phase.

    • SDG 9 · Sanayi, Yenilikçilik ve Altyapı
    • SDG 11 · Sürdürülebilir Şehirler ve Topluluklar
    RDL Kalıcı Kaydıİncele
  • ArticleAçık Erişim2025
    Evaluation of the effect of frame discontinuity on earthquake performance in reinforced concrete buildings using nonlinear analysis

    Atar, Muhammed; Ince, Ozan; Çakıl, Burak; İnce, Elif Gökçe

    Earthquakes are natural events that challenge the limits of engineering designs through the forces they exert on structures. The devastating outcomes of the 2023 Kahramanmaraş earthquakes have underscored the urgent need to reassess the seismic safety of the building stock and current design practices. Frame continuity in reinforced concrete buildings is particularly vital for structural strength and earthquake resilience. This study examines the effects of frame discontinuity on the performance of reinforced concrete buildings using nonlinear analysis methods. As part of the research, three regular reinforced concrete buildings were initially designed and later re-modeled to incorporate frame discontinuities. Both building types were analyzed using the nonlinear pushover analysis method, and the resulting capacity curves and damage states were compared to evaluate the impact of frame discontinuity. The analysis results reveal the negative impact of frame continuity on the building performance.

    • SDG 11 · Sürdürülebilir Şehirler ve Topluluklar
    RDL Kalıcı Kaydıİncele
  • ArticleAçık Erişim2025
    Investigation of the Required Earthquake Gap Distance between Reinforced Concrete Buildings with Nonlinear Time History Analysis; [Betonarme Binalar Arasında Bırakılması Gereken Derz Mesafesinin Doğrusal Olmayan Zaman Tanım Alanında Analizler ile İncelenmesi]

    Cakil, Burak; Ince, Ozan; Atar, Muhammed; Ince, Elif Gokce

    Earthquakes are caused by movements of the Earth's crust, resulting in destructive impacts on structures. One of the factors that increase the destructiveness of earthquakes is the pounding effect between buildings. Reinforced concrete buildings need to displace freely during seismic events. However, when the gap between adjacent buildings is insufficient, collisions occur, causing significant structural damage. This phenomenon, known as the pounding effect, can lead to severe damage during earthquakes. In this study, nonlinear time history analyses were conducted for two types of reinforced concrete buildings, 5-storey and 10-storey structures, to obtain their maximum displacement values. The minimum separation distances required to prevent pounding when these buildings are constructed adjacently were calculated and compared with the values specified in the 2018 Turkish Building Earthquake Code (TBEC-2018). The analysis results revealed that the distances calculated according to TBEC-2018 are insufficient.

    • SDG 11 · Sürdürülebilir Şehirler ve Topluluklar
    RDL Kalıcı Kaydıİncele