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Development of a Fuzzy Inference System Based Rapid Visual Screening Method for Seismic Assessment of Buildings Presented on a Case Study of URM Buildings

Author

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  • Nurullah Bektaş

    (Department of Structural and Geotechnical Engineering, Széchenyi István University, 9026 Győr, Hungary)

  • Ferenc Lilik

    (Department of Telecommunications, Széchenyi István University, 9026 Győr, Hungary)

  • Orsolya Kegyes-Brassai

    (Department of Structural and Geotechnical Engineering, Széchenyi István University, 9026 Győr, Hungary)

Abstract

Many conventional rapid visual screening (RVS) methods for the seismic assessment of existing structures have been designed over the past three decades, tailored to site-specific building features. The objective of implementing RVS is to identify the buildings most susceptible to earthquake-induced damage. RVS methods are utilized to classify buildings according to their risk level to prioritize the buildings at high seismic risk. The conventional RVS methods are employed to determine the damage after an earthquake or to make safety assessments in order to predict the damage that may occur in a building before an impending earthquake. Due to the subjectivity of the screener based on visual examination, previous research has shown that these conventional methods can lead to vagueness and uncertainty. Additionally, because RVS methods were found to be conservative and to be partially accurate, as well as the fact that some expert opinion based developed RVS techniques do not have the capability of further enhancement, it was recommended that RVS methods be developed. Therefore, this paper discusses a fuzzy logic based RVS method development to produce an accurate building features responsive examination method for unreinforced masonry (URM) structures, as well as a way of revising existing RVS methods. In this context, RVS parameters are used in a fuzzy-inference system hierarchical computational pattern to develop the RVS method. The fuzzy inference system based RVS method was developed considering post-earthquake building screening data of 40 URM structures located in Albania following the earthquake in 2019 as a case study. In addition, FEMA P-154, a conventional RVS method, was employed to screen considered buildings to comparatively demonstrate the efficiency of the developed RVS method in this study. The findings of the study revealed that the proposed method with an accuracy of 67.5% strongly outperformed the conventional RVS method by 42.5%.

Suggested Citation

  • Nurullah Bektaş & Ferenc Lilik & Orsolya Kegyes-Brassai, 2022. "Development of a Fuzzy Inference System Based Rapid Visual Screening Method for Seismic Assessment of Buildings Presented on a Case Study of URM Buildings," Sustainability, MDPI, vol. 14(23), pages 1-27, December.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:23:p:16318-:d:995555
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    References listed on IDEAS

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    1. Luca Sbrogiò & Ylenia Saretta & Francesco Molinari & Maria Rosa Valluzzi, 2022. "Multilevel Assessment of Seismic Damage and Vulnerability of Masonry Buildings (MUSE-DV) in Historical Centers: Development of a Mobile Android Application," Sustainability, MDPI, vol. 14(12), pages 1-29, June.
    2. Nurullah Bektaş & Orsolya Kegyes-Brassai, 2022. "Conventional RVS Methods for Seismic Risk Assessment for Estimating the Current Situation of Existing Buildings: A State-of-the-Art Review," Sustainability, MDPI, vol. 14(5), pages 1-40, February.
    3. N. Alam & M. Alam & S. Tesfamariam, 2012. "Buildings’ seismic vulnerability assessment methods: a comparative study," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 62(2), pages 405-424, June.
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    Cited by:

    1. Maria Rosa Valluzzi & Veronica Follador & Luca Sbrogiò, 2023. "Vulnus Web: A Web-Based Procedure for the Seismic Vulnerability Assessment of Masonry Buildings," Sustainability, MDPI, vol. 15(8), pages 1-30, April.

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