scholarly journals Study on Structural Reliability of Prestressed Reinforced Concrete Beam Bridges Based on Full Probability Analysis

2021 ◽  
Vol 1210 (1) ◽  
pp. 012003
Author(s):  
Yubao Liu ◽  
Hanxiong Liu ◽  
Shouyi Sun
Keyword(s):  
Finite Element ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Probability Distribution ◽  
Reliability Index ◽  
Limit State ◽  
State Equation ◽  
Distribution Model ◽  
State Equations ◽  
The Monte Carlo Method

Abstract A three dimensional(3D) finite element model is established for a prestressed concrete girder bridge, list the limit state equation and variable probability distribution model, obtain the failure probability and reliability index of the limit state equation based on the Monte-Carlo method, investigate the reliability index’s sensitivity to random variables for limit state equations of bridge bearing capacity. The specific method of the research on the structure reliability index calculation is to select a suitable way that can fit the research’s object among the center point method, the checking-point method, the Monte-Carlo method, the importance sampling method, and so on. Authors use finite element software ANSYS to build model and perform 3D force analysis. According to the results, authors can determine the bridges’ failure modes under the state of 3D stress. Then, authors can list the possible limit state equations related to Stiffness, strength, function, durability, and some character else. After determining the bridge’s structural limit state equation and the probability distribution model of the variables, determine the distribution function of each impact factor and its characteristic parameters through the site survey data and other related data surveys. Then, use the Monte-Carlo method for the calculation of bridge reliability index, obtain the failure probability and reliability index of each limit state equation, analyze the sensitivity of each variable to the reliability index under the ultimate state of the bridge’s bearing capacity. At last, authors give construction quality control plans and suggestions according to the data above.

scholarly journals Prediksi Tingkat Penerimaan Lulusan Siswa Kejuruan dalam Dunia Usaha dan Industri Menggunakan Metode Monte Carlo

2020 ◽  
pp. 84-89
Author(s):  
Hasanatul Iftitah ◽  
Y Yuhandri
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Probability Distribution ◽  
Prediction Accuracy ◽  
Vocational School ◽  
Vocational Schools ◽  
Random Numbers ◽  
Vocational High School ◽  
The Monte Carlo Method ◽  
Academic Year

Vocational High School (SMK) Negeri 4 Kota Jambi is one of the favorite vocational schools in Jambi City which is also the only pure tourism vocational school in Jambi Province. SMK Negeri 4 Kota Jambi has several vocational majors, namely culinary, beauty, fashion and hospitality. In general, students who choose to attend vocational schools have the hope of being able to work immediately after graduating from school, they do not need to continue to study to be able to work. In this study, researchers will predict the level of acceptance of students from SMK Negeri 4 Kota Jambi in the business and industrial world using the Monte Carlo method. Monte Carlo is a method that can find values ​​that are close to the actual value of events that will occur based on the distribution of sampling data. The technique of this method is to select random numbers from the probability distribution to perform the simulation. The data used in this study is the data of students from SMK Negeri 4 Kota Jambi who worked from the 2015/2016 Academic Year to the 2018/2019 Academic Year. Furthermore, the data will be processed using the Monte Carlo method. The simulation will be implemented using PHP programming. The result of this research is the level of prediction accuracy of students of SMK Negeri 4 Kota Jambi who are accepted in the business and industrial world using the Monte Carlo method is 84%.

scholarly journals Analysis of the Accuracy of the Calculation of the Diaphragm Area by the Monte Carlo Method

2020 ◽  
pp. 22-26
Author(s):  
O. D. Kupko
Keyword(s):  
Monte Carlo ◽  
Standard Deviation ◽  
Monte Carlo Method ◽  
Probability Distribution ◽  
Circular Aperture ◽  
The Monte Carlo Method ◽  
Relative Standard ◽  
Uniform Probability Distribution ◽  
Standard Deviations ◽  
The Difference

The process of measuring the area of a circular diaphragm using a device that determines the coordinates of the boundary of the diaphragm is theoretically considered. The Monte Carlo method with a small number of implementations was used. The procedure for calculating the area is described in detail. We considered a circular aperture with a precisely known radius. On the circumference of the diaphragm, the coordinate measuring points vibrated through 0.1, 0.3, 0.6, and π/2 radians vibrated. To simulate random deviations (uncertainties) when measuring coordinates, random additives were used with a uniform probability distribution and a given standard deviation. For each case, the areas were calculated in accordance with the proposed procedure. The difference in the results of calculating the area from the true area depending on the number of measurement points and the standard deviation of random additives is analyzed. It is shown that the ratio of the relative standard deviations of the area to the relative standard deviations of the coordinates is approximately the same for each number of measurements. The dependence of this relationship on the number of measurements is determined. The results obtained are analyzed.

Mechanical Component’s Dimension Design With Required Reliability by the Monte Carlo Method

2020 ◽  
Author(s):  
Xiaobin Le
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Failure Mode ◽  
Failure Modes ◽  
Limit State ◽  
Design Parameters ◽  
Mechanical Component ◽  
Component Design ◽  
The Monte Carlo Method ◽  
State Functions

Abstract Since the main design parameters in a mechanical component design have some uncertainties and should be treated as random variables, the reliability of a component is a better measurement of the safe status of a component. A component will not be reliable unless it is designed with specified reliability. Therefore, the mechanical component design should be a dimension design with the required reliability. The fundamental concept of the Monte Carlo method is to plug-in randomly generated numerical values into the governing equation of a design problem to get a trial result. The Monte Carlo method has become so powerful numerical simulation approach in almost every field such as optimization, numerical integration, and reliability calculation. But for reliability engineering, most of the literature shows how to use the Monte Carlo method to calculate the reliability of a component. This paper will propose the modified Monte Carlo method to determine a component dimension with required reliability. This paper first discusses and establishes typical limit state functions of a component under static loads. These limit state functions cover two failure modes including the failure mode due to strength and the failure mode due to excessive deformation. Then, the procedure and the flowchart of the modified Monte Carlo method will be explained in detail. The provided procedure and the flowchart are easy to be followed for compiling a MATLAB program to conduct a dimension design with required reliability. Two examples will show how to implement the proposed new method for conducting a dimension design with required reliability.

The Reliability Analysis of Wheel Groove Milling Machine's Column Based on Probability Finite Element Method

2014 ◽  
Vol 532 ◽  
pp. 487-490 ◽  
Author(s):  
Fan Jie Luo ◽  
Dan Lu Song
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Monte Carlo ◽  
Elastic Modulus ◽  
Monte Carlo Method ◽  
Reliability Analysis ◽  
Structure Design ◽  
Column Height ◽  
Milling Machine ◽  
The Monte Carlo Method

Taking the column of the wheel groove milling machine as the research object, the randomness of the structure design parameter is simulated with the PDS of the ANSYS procedure, by taking the column height, load and elastic modulus as input random variables. The reliability analysis for the column deformation has been done with the Monte Carlo method. The results showed that the column reliability is 100% under the sample for 1000 times, and the number of simulation meets accuracy requirements. The evaluation of the probabilistic sensitivities showed that: the elastic modulus is the most important factor affecting the column reliability, and the reliability of column can be improved by decreasing the dispersion of the property parameters of the material.

The Application of Artificial BP Neural Networks and Monte-Carlo Method for the Reliability Analysis on Frame Structure

2012 ◽  
Vol 204-208 ◽  
pp. 3256-3259 ◽  
Author(s):  
Zhi Cheng Xue ◽  
Hai Jun Wang
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Reliability Analysis ◽  
Limit State ◽  
Frame Structure ◽  
State Function ◽  
Range Data ◽  
Limit State Function ◽  
The Monte Carlo Method ◽  
Wide Range

In order to conduct the reliability analysis of frame structure, the limit state function was first fitted by artificial BP neural network. Then considering the orthogonal array method, sample data was arranged. After that an improved network modes was trained for the probabilistic analysis on a wide range data with the Monte-Carlo method. The mean and standard deviation for the limit state function was easily obtained and the reliability index on the structure can be also calculated. Finally, the example indicated that this method used in the reliability analysis for frame structure was feasible.

scholarly journals Reliability-based Design of Network Structure Systems Using the Monte-Carlo Method

2020 ◽  
pp. short55-1-short55-8
Author(s):  
Aleksander Moshnikov
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Network Structure ◽  
Reliability Index ◽  
Software Implementation ◽  
Enterprise Management ◽  
R Language ◽  
Reliability Based Design ◽  
The Monte Carlo Method ◽  
Enterprise Management System

The article is devoted to the choice of reliability-oriented solutions for building an enterprise management system. The Monte Carlo method is used as a tool for reliability analysis, which provides an estimate of the reliability index with a given confidence probability. A software implementation in the R language is proposed. A quantitative example is provided.

Random Variation of Soil Parameters on the Reliability of Slope Stability

2011 ◽  
Vol 243-249 ◽  
pp. 3056-3061
Author(s):  
Hai Yu Ge ◽  
Jin Song Tu ◽  
Song Xia ◽  
Qing Yun Ge
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Slope Stability ◽  
Reliability Index ◽  
High Reliability ◽  
Limit Equilibrium ◽  
Soil Parameters ◽  
State Function ◽  
The Monte Carlo Method ◽  
Coefficients Of Variation

An expression for slope stability and safety factor is established herein by using inclined slice method based on limit equilibrium condition theory. A limit state function for the reliability analysis of slope stability is established as well. Such analysis is carried out by using the Monte Carlo method so as to study effects of random variables of soil parameters such as adhesive force, internal frictional angle and average values of soil density, together with their coefficients of variation, on reliability index of soil. As demonstrated by the examples described herein, these coefficients of variation are linear with the reliability indexβ, which indicates that soil of low discreteness is available with high reliability index and vice versa. As such, the analysis by using the Monte Carlo method can provide theoretical basis for determination of stability of soil and thus is highly practicable in actual engineering and construction.

Study on Critical Corrosive Ratio of Reinforced Concrete Based on Monte-Carlo Method

2011 ◽  
Vol 105-107 ◽  
pp. 1060-1064
Author(s):  
Yue Shun Chen ◽  
Li Liu
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Probability Distribution ◽  
Model Simulation ◽  
Protective Layer ◽  
Statistical Characteristics ◽  
Constant Current ◽  
Accelerated Corrosion ◽  
The Monte Carlo Method ◽  
Good Agreement

Based on the relationship between the displacement and the corresponding strain in protective layer concrete during their corrosive expanding, the strain in protective layer arrives the critical strain have been think as the cracking condition, then a certainty critical corrosive ratio model has been constructed in this paper. Considering the probability distribution and the statistical characteristics of concrete protective layer thickness c, reinforced bar diameter dst and the effectively volume expansion coefficient neff, the Monte-Carlo method have been used to simulate the critical corrosive ratio ρcr, its probability distribution has been shown in good agreement with Weibull distribution and lognormal distribution in results. Through the constant current polarization accelerated corrosion test, the critical corrosive model has been validated. With comparison of critical corrosive ratio which be obtained with the test and the model simulation results respectively, where a good agreement have been shown.

scholarly journals Prediksi Tingkat Penerimaan Lulusan Siswa Kejuruan dalam Dunia Usaha dan Industri Menggunakan Metode Monte Carlo

2020 ◽  
pp. 84-89
Author(s):  
Hasanatul Iftitah ◽  
Yuhandri Yunus
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Probability Distribution ◽  
Prediction Accuracy ◽  
Vocational School ◽  
Vocational Schools ◽  
Random Numbers ◽  
Vocational High School ◽  
The Monte Carlo Method ◽  
Academic Year

Vocational High School (SMK) Negeri 4 Kota Jambi is one of the favorite vocational schools in Jambi City which is also the only pure tourism vocational school in Jambi Province. SMK Negeri 4 Kota Jambi has several vocational majors, namely culinary, beauty, fashion and hospitality. In general, students who choose to attend vocational schools have the hope of being able to work immediately after graduating from school, they do not need to continue to study to be able to work. In this study, researchers will predict the level of acceptance of students from SMK Negeri 4 Kota Jambi in the business and industrial world using the Monte Carlo method. Monte Carlo is a method that can find values ​​that are close to the actual value of events that will occur based on the distribution of sampling data. The technique of this method is to select random numbers from the probability distribution to perform the simulation. The data used in this study is the data of students from SMK Negeri 4 Kota Jambi who worked from the 2015/2016 Academic Year to the 2018/2019 Academic Year. Furthermore, the data will be processed using the Monte Carlo method. The simulation will be implemented using PHP programming. The result of this research is the level of prediction accuracy of students of SMK Negeri 4 Kota Jambi who are accepted in the business and industrial world using the Monte Carlo method is 84%.

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