التحليل المعتمد على الموثوقية للأسس الشريطية المستندة على تربة متغيرة الخواص
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2022-06-21
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During the previous years, the level of safety for potential problems in the soil
was taken into account with a global safety factor because of this factor's role
in overcoming all risks resulting from possible errors that may arise during tests
and examinations, whether on-site or in the laboratory, there is no scientific
basis on which to determine the value of the common safety factor other than
the engineering experience possessed by the engineer.
For most structures which are related to soil mechanics, the safety factor is
suggested to be equal to (3). This value does not consider the impact of all
factors affecting the properties of the soil separately.
The main objective of this thesis is to provide a more efficient approaches to
assessing the safety level of structure foundations, which is the probabilistic
approach. In this approach, the uncertainty in soil properties, caused by
potential sources of errors, is considered, and the percentage of probability of
failure of a foundation is expressed (Pf).
Within the framework of the probabilistic methods, two types of analysis can
be distinguished. The first type is taking into account the uncertainty in the
properties of the soil by considering the properties of the soil as random
variables, which means taking one model to simulate the soil, and the soil in
this type is a suitable material with characteristics of homogeneous. Still, in
nature, the soil is a heterogeneous substance whose properties differ spatially in
both horizontal and vertical directions. This ultimately leads to the necessity of
representing soil properties as random fields with marginal probability
functions and a self-correlation function.
Within this thesis, different methods of the probabilistic approach are used
to achieve the main objective of this research:
i- The most powerful and accurate method, is Monte Carlo Simulation Method
(MCS), is used for probabilistic analysis in simulating uncertain soil properties
through random variables.
ii- Subset Simulation approach (SS) is used as newest and highly efficient
probabilistic method, through which effort and time are reduced compared to
the Monte Carlo method, which is used to simulate uncertain soil properties
through random variables that have proven their efficiency. Through the results
obtained in a probabilistic analysis of a vertically loaded strip base on multilayered
soil with spatially variable properties.
iii- This study uses AK-MCS approach which considers the most recent and
efficient probabilistic method, a combination of the Monte Carlo and Kriging
methods, called the Adaptive Kriging Monte Carlo Simulation method (AKMCS),
which is used to reduce computational effort and time consumption for
periods. It simulated uncertain soil properties through random variables and
random fields. Perform a probabilistic analysis of a vertically loaded based soil
with spatially variable properties.
The results obtained in this thesis showed the importance of applying the
probabilistic approach to analyzing the foundations of structures instead of
using the traditional method, which depends on the use of the safety factor.