Macro-Block and DEM-Based Probabilistic Analysis to Predict In-Plane Structural Behavior of URM Pier–Spandrel Systems


Pulatsu B., Gonen S., Lourenço P. B., TUNCAY K.

Proceedings of theAnnual Conference of the Canadian Society of Civil Engineering 2022, Whistler, Kanada, 25 - 28 Mayıs 2022, cilt.348 LNCE, ss.209-222 identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 348 LNCE
  • Doi Numarası: 10.1007/978-3-031-34159-5_15
  • Basıldığı Şehir: Whistler
  • Basıldığı Ülke: Kanada
  • Sayfa Sayıları: ss.209-222
  • Anahtar Kelimeler: In-plane structural behavior, Probabilistic analysis, URM pier–spandrel systems
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

In the last several decades, computational modeling of unreinforced masonry buildings has been a subject of interest in the field of structural and conservation engineering. Different computational modeling techniques are being used by researchers and practitioners at various levels of complexity. However, most studies only focus on a single method, and they fail to compare different approaches. In this context, the present study aims to discuss both practice-oriented simplified macro-block analysis and advanced computational models based on the discrete element method (DEM). They are utilized to predict the structural behavior of a pier–spandrel system subjected to lateral forces. Moreover, the variability of the structural behavior and capacity of the system is explored by explicitly addressing uncertainties in the material properties. Probabilistic analyses considering the spatial variation of the material parameters are carried out using Monte Carlo simulations. The results show that considering spatial and non-spatial material properties in the advanced model improves our understanding of their effect on structural behavior and capacity. Specifically, two input parameters, joint tensile strength and friction angle, revealed a considerable effect on the load-carrying capacity of the pier–spandrel system. The results also indicate advantageous features of different approaches.