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

A Monte Carlo Simulation of Melting in Prototype Crystal

2010 ◽  
Vol 654-656 ◽  
pp. 1512-1515
Author(s):  
Kazufumi Sato ◽  
Satoshi Takizawa ◽  
Tetsuo Mohri
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Atomic Displacement ◽  
Typical Feature ◽  
Melting Transition ◽  
Temperature Hysteresis ◽  
Discontinuous Change ◽  
First Order ◽  
Voronoi Polyhedron ◽  
First Order Transition

We investigate the melting transition of the solids interacting through a simple pairwise potential using conventional and Wang-Landau Monte Carlo simulation. In the simulations, the atomic displacement is discretized for describing the atomic vibration and each atom is confined within its Voronoi polyhedron. The melting point can be uniquely determined by Wang-Landau approach while the temperature hysteresis inevitably appears in the conventional method. The obtained results show typical feature of first-order transition which is the discontinuous change in the internal energy. We discuss the relation between the limit of superheated state and intrinsic instability of the system through the comparison with two results.

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
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