Application of the Monte-Carlo Simulation Procedure in the Near Continuum Regime

1981 ◽  
pp. 256-268 ◽  
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Simulation Procedure

Assessing Wear Evolutions in Railway Wheelsets Using a Survival Modeling Approach

2021 ◽  
Author(s):  
Guilerme A. C. Caldeira ◽  
JoaquimAP Braga ◽  
António R. Andrade
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Life Cycle ◽  
Condition Based Maintenance ◽  
Monitoring Systems ◽  
Simulation Procedure ◽  
Condition Monitoring Systems ◽  
Survival Modeling ◽  
Wheel Profile ◽  
Independence Of Events

Abstract The present paper provides a method to predict maintenance needs for the railway wheelsets by modeling the wear out affecting the wheelsets during its life cycle using survival analysis. Wear variations of wheel profiles are discretized and modelled through a censored survival approach, which is appropriate for modeling wheel profile degradation using real operation data from the condition monitoring systems that currently exist in railway companies. Several parametric distributions for the wear variations are modeled and the behavior of the selected ones is analyzed and compared with wear trajectories computed by a Monte Carlo simulation procedure. This procedure aims to test the independence of events by adding small fractions of wear to reach larger wear values. The results show that the independence of wear events is not true for all the established events, but it is confirmed for small wear values. Overall, the proposed framework is developed in such a way that the outputs can be used to support predictions in condition-based maintenance models and to optimize the maintenance of wheelsets.

Deriving Proven Oil Reserves Comments on the Monte Carlo Simulation Procedure

1993 ◽  
Vol 11 (1) ◽  
pp. 62-65
Author(s):  
Mark Wallace
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Basic Principles ◽  
Oil Reserves ◽  
Confidence Levels ◽  
Simulation Procedure ◽  
Probabilistic Distribution ◽  
Reservoir Description ◽  
Definition Of

The definition of reserves categories is frequently related directly back to the probabilistic distribution of reserves in the field. Most developments are planned around the P50 or “most likely” expectation for the field a level which incorporates the Proven plus Probable categories. The Proven category is usually backed out from the resulting reserves distribution by assuming an arbitrary P90 or P80 value, similarly upside or the Reserves including the Possible category are allocated a P20 or P10 value. This approach provides an “accepted” range to the reserves but is essentially reliant upon applying a range to a set of deterministric parameters. This approach assumes the basic principles of reservoir description are correct and can be applied at all confidence levels (P90-P10). In complex reservoirs this is less of a valid assumption, and running deterministic cases using pessimistic and optimistic data interpretations is the realistic way to determine the reserves range for the field.

Analysis of the Household Distribution of Trachoma in a Gambian Village Using a Monte Carlo Simulation Procedure

1989 ◽  
Vol 18 (4) ◽  
pp. 944-951 ◽  
Author(s):  
R BAILEY ◽  
C OSMOND ◽  
D C W MABEY ◽  
H C WHITTLE ◽  
M E WARD
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Simulation Procedure

Exceedance Probabilities of MDOF-Systems Under Stochastic Excitation

1997 ◽  
Vol 50 (11S) ◽  
pp. S168-S173 ◽  
Author(s):  
H. J. Pradlwarter ◽  
G. I. Schue¨ller
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Numerical Procedure ◽  
Random Excitation ◽  
Stochastic Excitation ◽  
First Passage ◽  
Simulation Procedure ◽  
Mdof Systems ◽  
Low Probability ◽  
Probability Domain

A numerical procedure of evaluating the exceedance probabilities of MDOF-systems under non-stationary random excitation is presented. The method is based on a newly developed Controlled Monte Carlo simulation procedure applicable to dynamical systems. It uses “Double and Clump” to assess the low probability domain and employs further intermediate thresholds to increase the efficiency of MCS for estimating first passage probabilities. Applied to a hysteretic type of MDOF-system, the method shows good results when compared with direct MCS.

A Study of the Microstructure and Grain Size at the Welding Heat Affected Zone of a Ferrite Stainless Steel

2008 ◽  
Vol 575-578 ◽  
pp. 627-632 ◽  
Author(s):  
Shi Xing Zhang ◽  
Shao Kang Guan ◽  
Xin Tian Liu ◽  
Chun Li Mo
Keyword(s):  
Experimental Data ◽  
Monte Carlo Simulation ◽  
Grain Size ◽  
Stainless Steel ◽  
Monte Carlo ◽  
Kinetic Equation ◽  
Heat Affected Zone ◽  
Real Experiment ◽  
Simulation Procedure ◽  
Monte Carlo Simulation Result

A method of Monte Carlo combined with welding experiments was adopted to study the grain size and microstructure in welding heat affected zone of the ferrite stainless steel. Firstly, the kinetic equation of grain growth was established with the experimental data . Then , a simulation procedure based on the kinetic equation was worked out. Agreement between Monte Carlo simulation result and the real experiment results was obtained.

scholarly journals Monte Carlo Simulation-based Approach to Optimal Bus Stops Allocation in the Municipality of Laško

2012 ◽  
Vol 23 (4) ◽  
pp. 265-278 ◽  
Author(s):  
Dejan Dragan ◽  
Tomaž Kramberger ◽  
Martin Lipičnik
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Service Area ◽  
Transportation Costs ◽  
Working Mechanism ◽  
Bus Stop ◽  
Simulation Procedure ◽  
Simulation Based ◽  
Bus Stops ◽  
Reduction Of Costs

The paper addresses the problem of optimal bus stop allocation. The aim is to achieve reduction of costs on account of appropriate re-design of the process of obligatory transportation of children from their homes to the corresponding schools in the Laško municipality. The proposed algorithm relies on optimization based on the Monte Carlo simulation procedure. The number of calculated bus stops is required to be minimal possible, which can still assure maximal service area within the prescribed radius, while keeping the minimal walking distances pupils have to go across from their homes to the nearest bus stop and vice versa. The main issues of the proposed algorithm are emphasised and the working mechanism is explained. The presentation of calculated results is given and comparison with some other existing algorithms is provided. The positions of the calculated bus stops are going to be used for the purpose of physical bus stops implementation in order to decrease the current transportation costs.

Electron Scattering in Solids

1990 ◽  
Vol 48 (2) ◽  
pp. 4-5
Author(s):  
Ryuichi Shimizu ◽  
Ze-Jun Ding
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Angular Distribution ◽  
Elastic Scattering ◽  
Electron Scattering ◽  
Cross Sections ◽  
Expansion Method ◽  
Electron Excitation ◽  
Partial Wave Expansion ◽  
Backscattered Electrons

Monte Carlo simulation has been becoming most powerful tool to describe the electron scattering in solids, leading to more comprehensive understanding of the complicated mechanism of generation of various types of signals for microbeam analysis.The present paper proposes a practical model for the Monte Carlo simulation of scattering processes of a penetrating electron and the generation of the slow secondaries in solids. The model is based on the combined use of Gryzinski’s inner-shell electron excitation function and the dielectric function for taking into account the valence electron contribution in inelastic scattering processes, while the cross-sections derived by partial wave expansion method are used for describing elastic scattering processes. An improvement of the use of this elastic scattering cross-section can be seen in the success to describe the anisotropy of angular distribution of elastically backscattered electrons from Au in low energy region, shown in Fig.l. Fig.l(a) shows the elastic cross-sections of 600 eV electron for single Au-atom, clearly indicating that the angular distribution is no more smooth as expected from Rutherford scattering formula, but has the socalled lobes appearing at the large scattering angle.

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