Stochastic assessment of concrete core strength in fire exposed specimens simulating non-engineered RC structures in Turkey


BİRİNCİ KAYAALP F. , Yurdakul Ö., Routil L.

Construction and Building Materials, cilt.289, 2021 (SCI Expanded İndekslerine Giren Dergi) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 289
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1016/j.conbuildmat.2021.123133
  • Dergi Adı: Construction and Building Materials

Özet

© 2021 Elsevier LtdThe spatial variability of concrete compressive strength over the specific region is simulated by the stochastic approach. The compressive strength of cores taken from fire-exposed beams simulating non-engineered structures in Turkey is obtained. Therefore, improper mix-design and low strength concrete are targeted. Then, the uneven distribution of the concrete compressive strength along the fire exposed specimens is handled by the random fields approach. Thus, the adverse effect of the fire is not only established by the compressive test results but also the scatter in the core results is estimated by the stochastic method. The stochastic model accounting for the scatter in the core results is generated from the given distribution and mean cylindrical compressive strength values. The concrete compressive strength is not distributed evenly but established stronger and weaker regions over the specimen in the stochastic models. The statistical samples are generated by the Monte Carlo-type stratified sampling method, which is Latin Hypercube Sampling (LHS). A total of 500 random samples closely predicts the scatter in the compressive strength at each temperature level with a range of 25–700 °C. The variability at different geometrical positions on the fire-exposed beam specimens with low strength concrete is characterized as well. Overall, the experimentally observed uncertainties arising from uneven distribution of concrete compressive strength over the fire-exposed beams simulating non-engineered structures in Turkey are accurately reproduced by the random fields approach.