This study was performed to evaluate the probabilistic characteristics of the flexural strength of reinforced concrete (RC) flexural members adopted for underground box culverts. These probabilistic models were developed to be adopted for the development of limit state load combination formats for underground RC box culverts. The probabilistic models of uncertainties inherent in the basic design variables were developed to evaluate flexural strength using field material test data as well as field survey data collected from various domestic construction sites of underground box culverts in Korea. The basic design variables include concrete strength, steel rebar strength, and section dimensions, such as slab thickness and rebar locations. Some design variables are assumed to have inherent construction error characteristics, which may be different from those inherent in the RC members for buildings and bridges. The bias models on flexural strength were evaluated based on the experimental results of four-point flexural tests on one-way RC slabs, which were fabricated following the general practice adopted in the local underground box culvert construction process. Based on the probabilistic models of basic design variables, as well as the bias models of flexural strength, Monte Carlo simulations were performed to examine the probabilistic characteristics of both ultimate flexural strength and yield moment strength of RC slab members. Some sensitivity analyses were performed to confirm the soundness of various probability models and the assumptions adopted in the development procedure. The proposed procedure may be applied to develop probabilistic resistance models for structural members, in which the construction error characteristics are assumed to be different from other practices.
|Journal||Applied Sciences (Switzerland)|
|Publication status||Published - 2021 Sept|
Bibliographical noteFunding Information:
Funding: This research work was supported by the Korea Electric Power Research Institute (Grant R18SA02) as well as the Korea Institute of Energy Technology Evaluation and Planning (KETEP) and the Ministry of Trade, Industry and Energy (MOTIE) of the Republic of Korea. (No. 20194030202460).
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.
All Science Journal Classification (ASJC) codes
- Materials Science(all)
- Process Chemistry and Technology
- Computer Science Applications
- Fluid Flow and Transfer Processes