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.

Study on Reliability of Jacket Offshore Platform by Seismic Action Based on ANSYS

2010 ◽  
Vol 163-167 ◽  
pp. 3023-3028
Author(s):  
Qing Zhi Yan ◽  
Zhan Zhang ◽  
Liang Cui ◽  
Yan Hua Wang
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Failure Mode ◽  
Safety Assessment ◽  
Offshore Platform ◽  
Seismic Action ◽  
Structure Reliability ◽  
The Monte Carlo Method ◽  
Jacket Offshore Platform ◽  
Main Factor

Jacket Offshore Platform is a complex statically indeterminate structure, reliability of which is impacted by many factors, and the earthquake is a main factor. This paper simplify the significant failure mode of Jacket Offshore Platform by standard. Calculate the reliability of Jacket Offshore Platform under the effect of earthquake with the Monte Carlo method based on ANSYS. The result can provide evidence for safety assessment of Jacket Offshore Platform.

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 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.

UGR CALCULATION BASED ON THE LUMINANCE SPATIAL-ANGULAR DISTRIBUTION

2020 ◽  
Vol 2020 (4) ◽  
pp. 25-32
Author(s):  
Viktor Zheltov ◽  
Viktor Chembaev
Keyword(s):  
Monte Carlo ◽  
Angular Distribution ◽  
Monte Carlo Method ◽  
Visual Task ◽  
New Method ◽  
Lighting System ◽  
Preliminary Assessment ◽  
System A ◽  
The Monte Carlo Method

The article has considered the calculation of the unified glare rating (UGR) based on the luminance spatial-angular distribution (LSAD). The method of local estimations of the Monte Carlo method is proposed as a method for modeling LSAD. On the basis of LSAD, it becomes possible to evaluate the quality of lighting by many criteria, including the generally accepted UGR. UGR allows preliminary assessment of the level of comfort for performing a visual task in a lighting system. A new method of "pixel-by-pixel" calculation of UGR based on LSAD is proposed.

PSHA software review based on the Monte Carlo method

2020 ◽  
pp. 14-24
Author(s):  
V.A. Mironov ◽  
S.A. Peretokin ◽  
K.V. Simonov
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Seismic Hazard ◽  
Hazard Analysis ◽  
Software Review ◽  
Seismic Hazard Analysis ◽  
Probabilistic Seismic Hazard ◽  
Test Calculation ◽  
Seismic Surveys ◽  
The Monte Carlo Method

The article is a continuation of the software research to perform probabilistic seismic hazard analysis (PSHA) as one of the main stages in engineering seismic surveys. The article provides an overview of modern software for PSHA based on the Monte Carlo method, describes in detail the work of foreign programs OpenQuake Engine and EqHaz. A test calculation of seismic hazard was carried out to compare the functionality of domestic and foreign software.

Application of the Monte Carlo Method for the Prediction of Behavior of Peptides

2019 ◽  
Vol 20 (12) ◽  
pp. 1151-1157 ◽  
Author(s):  
Alla P. Toropova ◽  
Andrey A. Toropov
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Natural Sciences ◽  
Monte Carlo Technique ◽  
Quantitative Structure ◽  
Structure Property ◽  
The Monte Carlo Method ◽  
Modern Natural

Prediction of physicochemical and biochemical behavior of peptides is an important and attractive task of the modern natural sciences, since these substances have a key role in life processes. The Monte Carlo technique is a possible way to solve the above task. The Monte Carlo method is a tool with different applications relative to the study of peptides: (i) analysis of the 3D configurations (conformers); (ii) establishment of quantitative structure – property / activity relationships (QSPRs/QSARs); and (iii) development of databases on the biopolymers. Current ideas related to application of the Monte Carlo technique for studying peptides and biopolymers have been discussed in this review.

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