Computers and Concrete

  • 제31권3호
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  • Pages.185-195
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  • 2023
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  • 1598-8198(pISSN)
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  • 1598-818X(eISSN)
테크노프레스 (Techno-Press)
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A comparative study on rapid seismic risk prioritization for reinforced concrete buildings in Antalya, Türkiye

  • Engin Kepenek (Department of City and Regional Planning, College of Architecture, Akdeniz University) ;
  • Kasim A. Korkmaz (College of Engineering and Technology, Eastern Michigan University) ;
  • Ziya Gencel (Department of City and Regional Planning, College of Architecture, Akdeniz University)
  • 투고 : 2022.04.04
  • 심사 : 2022.11.29
  • 발행 : 2023.03.25
⟨ 이전 논문 다음 논문 ⟩

초록

Antalya is located south part of minor Asia, one of the biggest cities in Türkiye. As a result of population growth and vast migration to Antalya, many parts of the city that were not suitable for construction due to its geological conditions have become urban areas, and most of these urban areas are full of poorly engineered buildings. Poor engineering has been combined with unplanned urbanization, that causes utter vulnerability to disasters in Antalya. When an earthquake-prone city, Antalya faces with an earthquake risk, fear arises in society. To overcome this problem, it has become necessary to investigate the building stock, expressed in hundreds of thousands, in a fast and reliable way and then perform an urban transformation to create the perception of structural safety. However, the excessive building stock, labor, and economic problems made the implementation stage challenging and revealed the necessity of finding alternative solutions in the field. The present study presents a novel approach for assessment and model based on a rapid visual inspection method to transform areas under earthquake risk in Türkiye. The approach aimed to rank the interventions for decision-making mechanisms by making comparisons in the scale hierarchy. In the present study, to investigate the proposed approach, over 26,000 buildings were examined in Antalya, which is the fifth largest city in Türkiye that has a population of over 2.5 Million. In the results of the study, the risk classification was defined in the framework of building, block, street, neighborhood, and district scales.

키워드

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