scholarly journals Application of Monte Carlo techniques with delay-time analysis to assess maintenance and inspection policies for marine systems

2016 ◽  
Vol 231 (2) ◽  
pp. 89-106 ◽  
Author(s):  
D McNamara ◽  
A Cunningham ◽  
R Riahi ◽  
I Jenkinson ◽  
J Wang
Keyword(s):  
Monte Carlo ◽  
Delay Time ◽  
Monte Carlo Model ◽  
Spare Part ◽  
Time Analysis ◽  
Factors Affecting ◽  
Monte Carlo Techniques ◽  
Marine System ◽  
Maintenance And Inspection ◽  
The Impact

This paper presents a novel methodology applying Monte Carlo methods with delay-time analysis to test the effects of scheduled maintenance and inspection actions on factors affecting the operational efficiency of a marine system which is subject to degradation. The aim is to demonstrate how a Monte Carlo model incorporated into delay-time analysis can be used to predict the transition behaviour of a system under analysis. The model presented in this paper focuses on the effects on system failure probability and downtime of various maintenance and inspection policies. The impact on spare part requirements is also investigated.

scholarly journals Examples of Monte Carlo techniques applied for nuclear data uncertainty propagation

2019 ◽  
Vol 211 ◽  
pp. 07008 ◽  
Author(s):  
Oscar Cabellos ◽  
Luca Fiorito
Keyword(s):  
Monte Carlo ◽  
Large Scale ◽  
Uncertainty Propagation ◽  
Nuclear Data ◽  
Monte Carlo Technique ◽  
Data Uncertainty ◽  
Design Parameters ◽  
Monte Carlo Techniques ◽  
Bayesian Monte Carlo ◽  
The Impact

The aim of this work is to review different Monte Carlo techniques used to propagate nuclear data uncertainties. Firstly, we introduced Monte Carlo technique applied for Uncertainty Quantification studies in safety calculations of large scale systems. As an example, the impact of nuclear data uncertainty of JEFF-3.3 235U, 238U and 239Pu is demonstrated for the main design parameters of a typical 3-loop PWR Westinghouse unit. Secondly, the Bayesian Monte Carlo technique for data adjustment is presented. An example for 235U adjustment using criticality and shielding integral benchmarks shows the importance of performing joint adjustment based on different set of integral benchmarks.

scholarly journals Monte Carlo Study of UAV-Measurable Albedo over Arctic Sea Ice

2018 ◽  
Vol 35 (1) ◽  
pp. 57-66 ◽  
Author(s):  
Igor Podgorny ◽  
Dan Lubin ◽  
Donald K. Perovich
Keyword(s):  
Monte Carlo ◽  
Sea Ice ◽  
Energy Budget ◽  
Monte Carlo Model ◽  
Lower Troposphere ◽  
Monte Carlo Study ◽  
Open Water ◽  
Arctic Sea Ice ◽  
Inhomogeneous Surface ◽  
The Impact

AbstractIn anticipation that unmanned aerial vehicles (UAVs) will have a useful role in atmospheric energy budget studies over sea ice, a Monte Carlo model is used to investigate three-dimensional radiative transfer over a highly inhomogeneous surface albedo involving open water, sea ice, and melt ponds. The model simulates the spatial variability in 550-nm downwelling irradiance and albedo that a UAV would measure above this surface and underneath an optically thick, horizontally homogeneous cloud. At flight altitudes higher than 100 m above the surface, an airborne radiometer will sample irradiances that are greatly smoothed horizontally as a result of photon multiple reflection. If one is interested in sampling the local energy budget contrasts between specific surface types, then the UAV must fly at a low altitude, typically within 20 m of the surface. Spatial upwelling irradiance variability in larger open water features, on the order of 1000 m wide, will remain apparent as high as 500 m above the surface. To fully investigate the impact of surface feature variability on the energy budget of the lower troposphere ice–ocean system, a UAV needs to fly at a variety of altitudes to determine how individual features contribute to the area-average albedo.

A simple Monte Carlo model for electron-probe quantitation

1992 ◽  
Vol 50 (2) ◽  
pp. 1674-1675
Author(s):  
Peter Duncumb
Keyword(s):  
Monte Carlo ◽  
Cross Section ◽  
Electron Scattering ◽  
Electron Probe ◽  
Monte Carlo Model ◽  
Correction Procedure ◽  
Backscatter Coefficient ◽  
X Ray ◽  
Monte Carlo Techniques

Since the early work of Bishop in the 1960's, many have used Monte Carlo techniques for studying the role of electron scattering in the X-ray production process, but the simulation of individual trajectories has always proved too slow to be of use for online analysis. The paper describes a simple model for calculating the distribution curves of ionisation with depth ϕ(ρz) for a variety of target conditions, which are then characterised by a type of exponential expression capable of much faster computation. This expression is built into a practical correction procedure which can be applied to the analysis of all elements from boron upwards.The Monte Carlo model uses a simple multiple scattering cross-section with 50-step trajectories. This cross-section is adjusted to give the correct variation of backscatter coefficient with target atomic number, as shown in Figure 1, and this is the only physical parameter which it is necessary to fit empirically.

scholarly journals Application of delay-time analysis via Monte Carlo simulation

2011 ◽  
Vol 10 (3) ◽  
pp. 57-72 ◽  
Author(s):  
A Cunningham ◽  
W Wang ◽  
E Zio ◽  
A Wall ◽  
D Allanson ◽  
...  
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Delay Time ◽  
Time Analysis

scholarly journals Including operational data in QMRA model: development and impact of model inputs

2008 ◽  
Vol 7 (1) ◽  
pp. 77-95 ◽  
Author(s):  
Kenza Jaidi ◽  
Benoit Barbeau ◽  
Annie Carrière ◽  
Raymond Desjardins ◽  
Michèle Prévost
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Model ◽  
Model Development ◽  
Microbial Risk ◽  
Relative Risks ◽  
The Mean ◽  
Log Normal ◽  
Simplified Calculation ◽  
The Impact ◽  
Selection Of

A Monte Carlo model, based on the Quantitative Microbial Risk Analysis approach (QMRA), has been developed to assess the relative risks of infection associated with the presence of Cryptosporidium and Giardia in drinking water. The impact of various approaches for modelling the initial parameters of the model on the final risk assessments is evaluated. The Monte Carlo simulations that we performed showed that the occurrence of parasites in raw water was best described by a mixed distribution: log-Normal for concentrations > detection limit (DL), and a uniform distribution for concentrations < DL. The selection of process performance distributions for modelling the performance of treatment (filtration and ozonation) influences the estimated risks significantly. The mean annual risks for conventional treatment are: 1.97E−03 (removal credit adjusted by log parasite = log spores), 1.58E−05 (log parasite = 1.7 × log spores) or 9.33E−03 (regulatory credits based on the turbidity measurement in filtered water). Using full scale validated SCADA data, the simplified calculation of CT performed at the plant was shown to largely underestimate the risk relative to a more detailed CT calculation, which takes into consideration the downtime and system failure events identified at the plant (1.46E−03 vs. 3.93E−02 for the mean risk).

Temporal dispersion of the emergence of intelligence: an inter-arrival time analysis

2011 ◽  
Vol 10 (2) ◽  
pp. 131-135 ◽  
Author(s):  
Thomas W. Hair
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Arrival Time ◽  
Time Analysis ◽  
Arrival Times ◽  
The Galaxy ◽  
Sphere Of Influence ◽  
The Impact ◽  
Temporal Dispersion

AbstractMany reasons for why extraterrestrial intelligences might avoid communications with our civilization have been proposed. One possible scenario is that all civilizations follow the lead of some particularly distinguished civilization. This paper will examine the impact the first successful civilization could have on all other subsequent civilizations within its sphere of influence and the ramifications of this as it relates to the Fermi Paradox. Monte Carlo simulation is used to map the inter-arrival times of early civilizations and to highlight the immense epochs of time that the earliest civilizations could have had the Galaxy to themselves.

A Monte Carlo Model for Light Scattering by Dark Nebulae

1979 ◽  
Vol 3 (5) ◽  
pp. 312-315
Author(s):  
M. I. Darby ◽  
D. J. King ◽  
K. N. R. Taylor
Keyword(s):  
Monte Carlo ◽  
Light Scattering ◽  
Surface Brightness ◽  
Transfer Problem ◽  
Dust Cloud ◽  
Monte Carlo Model ◽  
Radiative Transfer Problem ◽  
Monte Carlo Techniques ◽  
Dust Grain ◽  
Model Approach

The Thumbprint Nebula (TPN) in Chamaeleon (first described by Fitzgerald (1974), and shown in Figure 1) is a good example of the class of dense, dark nebulae that exhibit dark cores and bright rims, and have been referred to (Lynds 1967) as ‘bright dark nebulae’. Early observations of these nebulae established that the dust grains within them were strongly forward-scattering (Struve and Elvey 1936, Struve 1937). However, the treatment of the radiative transfer problem was too inadequate to permit more than tentative conclusions regarding the nebulae. In more recent years, with the advent of modern computers, the transfer of radiation through a dust cloud has been treated more rigorously, using Monte Carlo techniques (Mattila 1970, Witt and Stephens 1974). Witt and Stephens (1974) have demonstrated that for a dense nebula the surface brightness profile is sensitive to the dust grain density distribution within the cloud and to the scattering properties of the grains. The scattering model approach can be valuable in the investigation of very opaque dark nebulae that cannot be studied by conventional star counting techniques. This has been demonstrated in the case of the TPN by Fitzgerald et al (1976), who used the Witt and Stephens model.

scholarly journals Gold Nanoparticle DNA Damage by Photon Beam in a Magnetic Field: A Monte Carlo Study

Nanomaterials ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1751
Author(s):  
Mehwish Jabeen ◽  
James C. L. Chow
Keyword(s):  
Magnetic Field ◽  
Dna Damage ◽  
Monte Carlo ◽  
Gold Nanoparticle ◽  
Monte Carlo Model ◽  
Photon Beam ◽  
Dose Enhancement ◽  
The Impact ◽  
The Magnetic Field ◽  
Field Strengths

Ever since the emergence of magnetic resonance (MR)-guided radiotherapy, it is important to investigate the impact of the magnetic field on the dose enhancement in deoxyribonucleic acid (DNA), when gold nanoparticles are used as radiosensitizers during radiotherapy. Gold nanoparticle-enhanced radiotherapy is known to enhance the dose deposition in the DNA, resulting in a double-strand break. In this study, the effects of the magnetic field on the dose enhancement factor (DER) for varying gold nanoparticle sizes, photon beam energies and magnetic field strengths and orientations were investigated using Geant4-DNA Monte Carlo simulations. Using a Monte Carlo model including a single gold nanoparticle with a photon beam source and DNA molecule on the left and right, it is demonstrated that as the gold nanoparticle size increased, the DER increased. However, as the photon beam energy decreased, an increase in the DER was detected. When a magnetic field was added to the simulation model, the DER was found to increase by 2.5–5% as different field strengths (0–2 T) and orientations (x-, y- and z-axis) were used for a 100 nm gold nanoparticle using a 50 keV photon beam. The DNA damage reflected by the DER increased slightly with the presence of the magnetic field. However, variations in the magnetic field strength and orientation did not change the DER significantly.

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