Effects of Partially-Filled Containers in Dynamic Behavior of Tanker Trains Traveling on Curved Tracks

2008 ◽  
Author(s):  
Iman Hazrati Ashtiani ◽  
Davood Younesian ◽  
Mehrnoosh Abedi ◽  
Ebrahim Esmailzadeh
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Dynamic System ◽  
Dynamic Analysis ◽  
Parametric Study ◽  
Fluid Density ◽  
Moment Arms ◽  
Rail Irregularities ◽  
Curved Track ◽  
The Moment

Dynamic analysis of a partially-filled tanker train traveling on a curved track is studied in this paper. A partially-filled tanker is dynamically modeled when it is traveling along a real curved track. For three classes of tracks, rail irregularities are randomly generated by using Monte-Carlo simulation. An equivalent dynamic system is used to model sloshing motion of the fluid. Two derailment indexes i.e. derailment quotient and unloading ratio are obtained numerically as safety indicators. A parametric study is carried out to investigate how different parameters like the operational speed, fluid modeling, rail irregularities, and fluid density may affect the derailment potential. It is found that descending of the center of gravity and consequently reduction of the moment arms is more dominant than the oscillating forces due to sloshing motion.

Monte Carlo simulation of damaged ship survivability

2005 ◽  
Vol 219 (1) ◽  
pp. 25-35 ◽  
Author(s):  
T A Santos ◽  
C Guedes Soares
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Vertical Position ◽  
Sea State ◽  
Direct Estimate ◽  
Monte Carlo Simulation Technique ◽  
The Moment ◽  
Damage Condition ◽  
Equivalent Method ◽  
Damaged Ship

A probabilistic methodology for assessing damaged ship survivability based on Monte Carlo simulation is proposed. The damage condition is generated using statistical distributions of damage location and extent, derived during a recent research project, coupled to an algorithm that identifies the damaged compartments. Survivability of the ship in each damage condition is evaluated using the formulae recently proposed in Report SLF 46, which are partly based on the static equivalent method and partly on a more conventional approach. The Monte Carlo simulation technique is applied taking into consideration random quantities related to the damage and loading conditions at the time of accident. This methodology is applied to a passenger roll-on roll-off ship, allowing for a direct estimate of the damaged ship survivability in terms of the number of simulated ship capsizes. The effects of changes in the vertical position of the centre of gravity and in the sea state distribution at the moment of accident are also evaluated.

scholarly journals Value at Risk Dinâmico: um Estudo Comparativo entre os Modelos Heterocedásticos e a Simulação de Monte Carlo

2006 ◽  
Vol 4 (2) ◽  
pp. 181
Author(s):  
Marcos Roberto Gois de Oliveira ◽  
Charles Ulises de Montreuil Carmona ◽  
José Lamartine Távora Junior
Keyword(s):  
At Risk ◽  
Monte Carlo Simulation ◽  
Risk Management ◽  
Monte Carlo ◽  
Dynamic Analysis ◽  
Value At Risk ◽  
Garch Models ◽  
Efficient Market

The objective of this paper was to analyze the risk management of a portfolio composed by Petrobras PN, Telemar PN and Vale do Rio Doce PNA stocks. It was verified if the modeling of Value-at-Risk (VaR) through the place Monte Carlo simulation with volatility of GARCH family is supported by hypothesis of efficient market. The results have shown that the statistic evaluation in inferior to dynamics, evidencing that the dynamic analysis supplies support to the hypothesis of efficient market of the Brazilian share holding market, in opposition of some empirical evidences. Also, it was verified that the GARCH models of volatility is enough to accommodate the variations of the shareholding Brazilian market, since the model is capable to accommodate the great dynamic of the Brazilian market.

scholarly journals Normal-G Class of Probability Distributions: Properties and Applications

Symmetry ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 1407 ◽  
Author(s):  
Fábio V. J. Silveira ◽  
Frank Gomes-Silva ◽  
Cícero C. R. Brito ◽  
Moacyr Cunha-Filho ◽  
Felipe R. S. Gusmão ◽  
...  
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Probability Distributions ◽  
Moment Generating Function ◽  
Maximum Likelihood Estimates ◽  
Simulation Studies ◽  
Mathematical Properties ◽  
Parsimonious Models ◽  
The Moment ◽  
Probability Density Function Pdf

In this paper, we propose a novel class of probability distributions called Normal-G. It has the advantage of demanding no additional parameters besides those of the parent distribution, thereby providing parsimonious models. Furthermore, the class enjoys the property of identifiability whenever the baseline is identifiable. We present special Normal-G sub-models, which can fit asymmetrical data with either positive or negative skew. Other important mathematical properties are described, such as the series expansion of the probability density function (pdf), which is used to derive expressions for the moments and the moment generating function (mgf). We bring Monte Carlo simulation studies to investigate the behavior of the maximum likelihood estimates (MLEs) of two distributions generated by the class and we also present applications to real datasets to illustrate its usefulness.

Dynamic System Simulation for Decision Support

2011 ◽  
pp. 306-312
Author(s):  
Norman Pendegraft ◽  
Mark Rounds
Keyword(s):  
Computer Simulation ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Decision Support ◽  
Dynamic System ◽  
Discrete Event Simulation ◽  
System Simulation ◽  
Discrete Event ◽  
Event Simulation

Simulation is a powerful methodology for decision support because it allows managers to experiment with models prior to implementing a policy or decision. There are several approaches to computer simulation: continuous event simulation, discrete event simulation, and Monte Carlo simulation. Continuous event simulation can be used to model dynamic system which cannot otherwise be easily modeled.

scholarly journals The Alpha-Beta Skew Generalized t Distribution: Properties and Applications

2019 ◽  
pp. 605-616
Author(s):  
Fazlollah Lak ◽  
Morad Alizadeh ◽  
Mohammad Esmaeil Dehghan Monfared ◽  
Hamid Esmaeili
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Maximum Likelihood ◽  
Asymptotic Properties ◽  
Likelihood Estimation ◽  
Moment Generating Function ◽  
Alpha Beta ◽  
The Moment ◽  
T Distribution ◽  
New Distribution

n this paper, we propose a new distribution, namely alpha-beta-skew generalized tdistribution. The proposed distribution is really flxible and includes as special models some important distributions like Normal, t-student, Cauchy and etc as its marginal component distributions. It features a probability density function with up to three modes. The moment generating function as well as the main moments are provided. Inference is based on a usual maximum-likelihood estimation approach and a small Monte Carlo simulation is conducted for studying the asymptotic properties of the maximum-likelihood estimate. The usefulness of the new model is illustrated in a real data

Dynamic Reliability Based on Perturbation Stochastic Finite Element

2012 ◽  
Vol 155-156 ◽  
pp. 47-50
Author(s):  
Wen Hui Mo
Keyword(s):  
Monte Carlo Simulation ◽  
Finite Element ◽  
Monte Carlo ◽  
Computer Program ◽  
Dynamic Analysis ◽  
Stochastic Finite Element ◽  
Dynamic Reliability ◽  
Numerical Example ◽  
Mean And Variance ◽  
The Mean

This paper proposes a method of calculating dynamic reliability using perturbation stochastic finite element. Dynamic analysis of perturbation stochastic finite element is introduced and the mean and variance of the stress can be obtained. Samples of stress and strength are generated by computer program. The Monte Carlo simulation is proposed to compute dynamic reliability of structure. Dynamic reliability of structure is computed by the stress-strength interference model. The proposed methods are demonstrated by a numerical example of axle.

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