Volume 22, Issue 1 (2022)
MCEJ 2022, 22(1): 53-66 |
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Reyhani A, Shahraki H. Parametric and sensitivity analysis in assessment the probabilistic vulnerability of RC short columns. MCEJ 2022; 22 (1) :53-66
URL: http://mcej.modares.ac.ir/article-16-47726-en.html
URL: http://mcej.modares.ac.ir/article-16-47726-en.html
1- Civil Engineering Department, University of Bojnord, Bojnord, Iran
2- Civil Engineering Department, University of Bojnord, Bojnord, Iran , h.shahraki@ub.ac.ir
2- Civil Engineering Department, University of Bojnord, Bojnord, Iran , h.shahraki@ub.ac.ir
Abstract: (730 Views)
There are many sources of aleatory uncertainty in the design of RC structures. Contrary to what is commonly thought, to assessment the safety of RC structures, the parameters related to the resistance of structural members and loads are non - deterministic, so that the description of the actual behavior of the structure without considering the uncertainties in these parameters will be impossible. The safety and performance of a RC structure is a function of the safety of its components, especially columns. Therefore, estimating the safety of RC columns with respect to these sources of uncertainty seems necessary and the inevitable result of inattention to it is a risk that threatens the expected performance of the structures. Achieving this goal is possible by analyzing reliability, through which various sources of uncertainty can be considered by applying probabilistic mathematics and a systematic process during the analysis and design process, and the achievement of the desired functions can be quantitatively evaluated. In most studies on the reliability of RC columns, the uncertainty in the load eccentricity is ignored and the load eccentricity is considered a deterministic and fixed quantity. the fixed eccentricity criterion means that the axial load and the bending moment are perfectly correlated and a linear relationship is established between them. When axial force and moment are perfectly correlated, this does not cause any problems; but when this is not the case, the reliability analysis results are only approximate. In fact, axial force and bending moment are not perfectly correlated in many cases, so to assessment the safety of RC columns, it is necessary to consider the uncertainty in the load eccentricity. Identifying and determining the relative importance of each of the uncertainties in the analysis of the reliability of the columns is an interesting and important issue, so that according to the results, can be seriously focus on the very important sources of uncertainty and Considered other uncertain parameters with their best estimates. Such an approach significantly reduces computational efforts and will be very practical and useful for large and real civil infrastructure. In this research an efficient approach for modeling sources of uncertainty in the safety assessment of RC short column with square and rectangular sections is proposed based on the first - order reliability method ( FORM ). In the proposed approach, limit state function is defined according to the interaction effect of axial force - bending moment of the column and considering modeling error which is a function of load eccentricity. The results show that various parameters such as correlation, cross-sectional shape, longitudinal reinforcement ratio of steel, load ratio, load eccentricity and distribution of longitudinal reinforcement in cross section are very influential on the values of the probability of failure of the column. Finally, according to the results, the coefficients of importance for identifying the most important parameters affecting the probability of failure of sample columns at various load eccentricities were presented which demonstrate that the compressive strength of concrete, modeling error and live load compared to other variables are of the greatest importance, which should be considered in the design and implementation of this important point.
Article Type: Original Research |
Subject:
Civil and Structural Engineering
Received: 2020/11/17 | Accepted: 2021/06/30 | Published: 2023/01/30
Received: 2020/11/17 | Accepted: 2021/06/30 | Published: 2023/01/30
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