Probabilistic Analyses of Root-Reinforced Slopes Using Monte Carlo Simulation

نویسندگان

چکیده

Among measures that are used to prevent the triggering of shallow landslides and for erosion control, root reinforcement has spread out widely as its contribution environmental sustainability is high. Although in recent years reliability-based design (RBD) been applied increasingly assessment slope stability address shortcomings deterministic approach (which does not consider geotechnical uncertainties explicitly), there still a lack application this method reinforcement. Plants characterised by high inherent uncertainty, making it necessary investigate level reliability these soil-bioengineering techniques. In context, determine whether or root-reinforced slopes designed according Eurocodes (that is, applying their statistical partial factors), providing satisfactory factors safety, may lead probability failure contrast, unacceptable, Authors carried several probabilistic analyses using Monte Carlo simulation (MCS). MCS was simplified Bishop Method modified bear pseudo-static forces representing earthquake loading mind. To take into account mechanical effect provided roots, an apparent cohesion added Mohr–Coulomb criterion. Results showed every configuration satisfies safety criterion acceptable levels reliability, evidence caused variability parameters.

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Monte Carlo simulation technique for assessment of earthquake-induced displacement of slopes

The dynamic response of slopes against earthquake is commonly characterized by the earthquake-induced displacement of slope (EIDS). The EIDS value is a function of several variables such as the material properties, slope geometry, and earthquake acceleration. This work is aimed at the prediction of EIDS using the Monte Carlo simulation method (MCSM). Hence, the parameters height, unit specific ...

متن کامل

Probabilistic analysis of stability of chain pillars in Tabas coal mine in Iran using Monte Carlo simulation

Performing a probabilistic study rather than a determinist one is a relatively easy way to quantify the uncertainty in an engineering design. Due to the complexity and poor accuracy of the statistical moment methods, the Monte Carlo simulation (MCS) method is wildly used in an engineering design. In this work, an MCS-based reliability analysis was carried out for the stability of the chain pill...

متن کامل

Monte Carlo Simulation using Excel

A Monte-Carlo Simulation using Excel Spreadsheet has been used to determine the reliability of a geothermal power plant. This simulation technique utilizes the powerful mathematical and statistical capabilities of Excel. Simulation time is dependent on the complexity of the system, computer speed and the accuracy desired, so a simulation may range from a few minutes to a few hours.

متن کامل

Bremsstrahlung imaging from the liver using the Monte Carlo simulation

Introduction: Most beta and gamma radiation radioisotopes used for treatment are not suitable for imaging. The bremsstrahlung images on a conventional gamma camera helped to localize the radionuclide within and outside of the lesion. Secondary scattering of gamma rays of higher energy and bremsstrahlung causes contamination in the energy window and reducing the contrast and resolution of the im...

متن کامل

Method of Moments Using Monte Carlo Simulation

We present a computational approach to the method of moments using Monte Carlo simulation. Simple algebraic identities are used so that all computations can be performed directly using simulation draws and computation of the derivative of the log-likelihood. We present a simple implementation using the Newton-Raphson algorithm, with the understanding that other optimization methods may be used ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Geosciences

سال: 2023

ISSN: ['2076-3263']

DOI: https://doi.org/10.3390/geosciences13030075