Surface-induced disordering at first-order transitions in body-centered cubic binary alloys: A Monte-Carlo simulation

1990 ◽  
Vol 80 (3) ◽  
pp. 401-413 ◽  
Author(s):  
W. Helbing ◽  
B. D�nweg ◽  
K. Binder ◽  
D. P. Landau
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Binary Alloys ◽  
Body Centered Cubic ◽  
First Order

Reliability Estimation of Buried Pipeline Using FORM, SORM and Monte Carlo Simulation

2006 ◽  
Vol 326-328 ◽  
pp. 597-600 ◽  
Author(s):  
Ouk Sub Lee ◽  
Dong Hyeok Kim
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Exposure Time ◽  
Failure Probability ◽  
Reliability Estimation ◽  
Buried Pipeline ◽  
First Order Reliability Method ◽  
First Order ◽  
Reliability Method ◽  
The Difference

In this paper, the failure probability is estimated by using the FORM (first order reliability method), the SORM (second order reliability method) and the Monte Carlo simulation to evaluate the reliability of the corroded pipeline. It is found that the FORM technique is more effective in estimating the failure probability than the SORM technique for B31G and MB31G models with three different corrosion models. Furthermore, it is noted that the difference between the results of the FORM, the SORM and the Monte Carlo simulation decreases with the increase of the exposure time.

Determination of Failure Probabilities and Sensitivity Factors Based on First Order Reliability Method

1994 ◽  
Author(s):  
Nataraj Parameswaran ◽  
Lidvin Kjerengtroen
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Transfer Problem ◽  
First Order Reliability Method ◽  
First Order ◽  
Advantages And Disadvantages ◽  
Distributed Parameters ◽  
Reliability Method ◽  
Sensitivity Factors ◽  
Failure Probabilities

Abstract Traditionally, most engineering problems are modeled in such a manner that all the variables involved in the design equations are deterministic. By nature, however, seldom does such a phenomenon exist. Most of the variables involved are randomly distributed with a certain mean and standard deviation and follow a certain type of statistical distribution. This investigation compares two such statistical based design processes to evaluate failure probabilities of a one dimensional heat transfer problem with various statistically distributed parameters in its performance function. The methods developed are the Monte Carlo simulation and First Order Reliability Method (FORM). Comparison is made between the Monte Carlo simulation and FORM based upon the investigated problem and the relative advantages and disadvantages of both methods are noted at the end of the investigation. The investigation demonstrates that FORM can be used effectively to determine failure probabilities and sensitivity factors in a manner better than Monte Carlo simulation.

Improving the first-order structural reliability estimation by Monte Carlo simulation

2017 ◽  
Vol 170 (7) ◽  
pp. 532-540 ◽  
Author(s):  
Mohsen Ali Shayanfar ◽  
Mohammad Ali Barkhordari ◽  
Moien Barkhori ◽  
Mohammad Barkhori
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Structural Reliability ◽  
Reliability Estimation ◽  
First Order

Monte Carlo simulation on the first-order melting transition of high-Tcsuperconductors inB‖c^

1998 ◽  
Vol 58 (6) ◽  
pp. 3438-3445 ◽  
Author(s):  
Xiao Hu ◽  
Seiji Miyashita ◽  
Masashi Tachiki
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Melting Transition ◽  
First Order
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