Volume 3, Issue 3 (3-2019)                   NMCE 2019, 3(3): 1-12 | Back to browse issues page

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Shojaeian A, Askari F. Variables Characteristics Effects on Static and Pseudo-Static Reliability-Based Design of Near Slope Shallow Foundations. NMCE. 2019; 3 (3) :1-12
URL: http://nmce.kntu.ac.ir/article-1-177-en.html
Associate Professor, International Institute of Earthquake Engineering and seismology, Tehran, Iran. , askari@iiees.ac.ir
Abstract:   (309 Views)
Given the concept of reliability-based design (RBD) and the growing risk management trend in geotechnical engineering, proper understanding and quantification of uncertainties are very important. The complexity of methods and a large volume of calculations of probabilistic design methods are the most critical reasons for civil engineers not to be comfortable using these approaches. In this research, a practical probabilistic innovative approach is used to calculate the reliability index by applying the first-order reliability method (FORM). To analyze the bearing capacity of foundations, the Hansen method is used, and both static and seismic designs have been carried out. A scenario where the foundation is located above flat ground and another scenario where the foundation is located near the slope are both considered. Different angles of the slope are also considered. The reason for choosing two different angles for the slope is to examine the effect of slope increase on RBD. As we know, in the RBD of geotechnical structures, our knowledge of the statistical characteristics of variables is significant. That is why, in this paper, the effect of the parameters distribution type (normal or non-normal), the variables dependence, as well as the effect of coefficient of variation in the design results is evaluated. It is found that assuming normal distribution and independence of the variables yields conservative results. The coefficient of variation (COV) of variables is very influential on the results of RBD, and the effect of variation in the internal friction angle (φ) is more significant than variation in the other parameters.
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Type of Study: Research | Subject: General

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