• Safety and Health at Work
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• v.15 no.1
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• pp.33-41
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• 2024

Background: Dust generated during the processing of building materials enterprises can pose a serious health risk. The study aimed to compare and analyze the results of ART and the Monte Carlo model for the dust exposure assessment in building materials enterprises, to derive the application scope of the two models. Methods: First, ART and the Monte Carlo model were used to assess the exposure to dust in each of the 15 building materials enterprises. Then, a comparative analysis of the exposure assessment results was conducted. Finally, the model factors were analyzed using correlation analysis and the scope of application of the models was determined. Results: The results show that ART is mainly influenced by four factors, namely, localized controls, segregation, dispersion, surface contamination, and fugitive emissions, and applies to scenarios where the workplace information of the building materials enterprises is specific and the average dust concentration is greater than or equal to 1.5 mg/m³. The Monte Carlo model is mainly influenced by the dust concentration in the workplace of building materials enterprises and is suitable for scenarios where the dust concentration in the workplace of the building materials enterprises is relatively uniform and the average dust concentration is less than or equal to 6mg/m³. Conclusion: ART is most accurate when workplace information is specific and average dust concentration is > 1.5 mg/m³; whereas, The Monte Carlo model is the best when dust concentration is homogeneous and average dust concentration is < 6 mg/m³.

• Nuclear Engineering and Technology
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• v.44 no.2
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• pp.161-176
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• 2012

McCARD is a Monte Carlo (MC) neutron-photon transport simulation code. It has been developed exclusively for the neutronics design of nuclear reactors and fuel systems. It is capable of performing the whole-core neutronics calculations, the reactor fuel burnup analysis, the few group diffusion theory constant generation, sensitivity and uncertainty (S/U) analysis, and uncertainty propagation analysis. It has some special features such as the anterior convergence diagnostics, real variance estimation, neutronics analysis with temperature feedback, $B_1$ theory-augmented few group constants generation, kinetics parameter generation and MC S/U analysis based on the use of adjoint flux. This paper describes the theoretical basis of these features and validation calculations for both neutronics benchmark problems and commercial PWR reactors in operation.

• Transactions of the Korean Society of Mechanical Engineers
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• v.5 no.3
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• pp.244-250
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• 1981

The rediant heat tranfer and temperature distribution between infinite parallel gray plates at different temperatures separated by an absorbing and emitting gray gas with or without a sinusoidal heat source in the gas are analyzed by Monte Carlo method. The Monte Carlo result were compared with the numerical solution by Usiskin and Sparrow and the exact solution by Hottel in the case of similar problem limited black walls and gas optical thickness is less than two. For gray walls and large optical thichness the results were compared with modified diffusion approximate solution by Deissler.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 1995.11a
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• pp.152-157
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• 1995

The electron transport coefficients in $SP_{6}$ gas is calculated and analysed for range of E/N values from 150∼800(Td) by a Monte Carlo simulation, using a set of electron collision cross sections determined by the authors. The result of the Monte Carlo simulation such as electron drift velocity, ionization and electron attachment coefficients, longitudinal and transverse diffusion coefficients in neatly agreement with the respective experimental and theoretical for a range of E/N. The validity of the results obtained has been confirmed by a Monte Carlo simulation carried out parallel to the analysis.

• Nuclear Engineering and Technology
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• v.38 no.3
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• pp.225-230
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• 2006

With the advent of inexpensive computing power over the past two decades, applications of Monte Carlo radiation transport techniques have proliferated dramatically. At Los Alamos, the Monte Carlo codes MCNP5 and MCNPX are used routinely on personal computer platforms for radiation shielding analysis and dosimetry calculations. These codes feature a rich palette of variance reduction (VR) techniques. The motivation of VR is to exchange user efficiency for computational efficiency. It has been said that a few hours of user time often reduces computational time by several orders of magnitude. Unfortunately, user time can stretch into the many hours as most VR techniques require significant user experience and intervention for proper optimization. It is the purpose of this paper to outline VR strategies, tested in practice, optimized for several common radiation shielding tasks, with the hope of reducing user setup time for similar problems. A strategy is defined in this context to mean a collection of MCNP radiation transport physics options and VR techniques that work synergistically to optimize a particular shielding task. Examples are offered in the areas of source definition, skyshine, streaming, and transmission.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.04a
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• pp.73-78
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• 2003

Ultrasonic measurement is one of important technologies in the lift-time maintenance of nuclear poler plant. Ultrasonic inspection system is consisted of the operator, equipment and procedure. The reliability of ultrasonic inspection system is affected by its ability. The performance demonstration round robin was conducted to quantify the capability of ultrasonic inspection for in-service. The small number of teams who employed procedures that met or exceeded ASME Sec. XI Code requirements detected the piping of nuclear power plant with various cracks to evaluate the capability of detection and sizing. In this paper, the statistical reliability assessment of ultrasonic nondestructive inspection data using Monte Carlo simulation is presented. The results of the probability of detection (POD) analysis using Monte Carlo simulation are compared to these of logistic probability model. In these results, Monte Carlo simulation was found to be very useful to the reliability assessment f3r the small hit/miss data sets.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.636-638
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• 2003

This paper presents a new approach which is able to determine the reasonable incentive levels of direct load control using sequential Monte Carlo simulation techniques. The economic analysis needs to determine the reasonable incentive level. However, the conventional methods have been based on the scenario methods because they had not considered all cases of the direct load control situations. To overcome there problems, this paper proposes a new technique using sequential Monte Carlo simulation. The Monte Carlo method is a simple and flexible tool to consider large scale systems and complex models for the components of the system. To show its effectiveness, numerical studies were performed to indicate the possible applications of the proposed technique.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.11 no.7
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• pp.571-580
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• 1998

The numerical model that can describe the ignition of pseudospark discharge using hybrid fluid-particle(Monte Carlo )method has been developed. This model consists of the fluid expression for transport of electrons and ions and Poisson's equation in the electric field. The fluid equation determines the spatiotemporal dependence of charged particle densities and the ionization source term is computed using the Monte carlo method. This model has been used to study the evolution of a discharge in Argon at 0.5 torr, with an applied voltage if 1kV. The evolution process of the discharge has been divided into four phases along the potential distribution : (1) Townsend discharge, (2) plasma formation, (3) onset of hollow cathode effect, (4) plasma expansion. From the numerical results, the physical mechanisms that lead to the rapid rise in current associated with the onset of pseudospark could be identified.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1043-1050
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• 2022

Markov chains and Monte Carlo Simulation were applied to account for the probabilistic nature of pavement deterioration over time using data collected in the field. The primary purpose of this study was to evaluate pavement network performance of Western Australia (WA) by applying the existing pavement management tools relevant to WA road construction networks. Two approaches were used to analyze the pavement networks: evaluating current pavement performance data to assess WA State Road networks and predicting the future states using past and current pavement data. The Markov chains process and Monte Carlo Simulation methods were used to predicting future conditions. The results indicated that Markov chains and Monte Carlo Simulation prediction models perform well compared to pavement performance data from the last four decades. The results also revealed the impact of design, traffic demand, and climate and construction standards on urban pavement performance. This study recommends an appropriate and effective pavement engineering management system for proper pavement design and analysis, preliminary planning, future pavement maintenance and rehabilitation, service life, and sustainable pavement construction functionality.

• Journal of Korean Society for Atmospheric Environment
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• v.18 no.6
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• pp.465-474
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• 2002

In order to reflect variability due to exposure factors as well as to assess uncertainty associated with cancer risk posed by airborne trace metals, a Monte Calro analysis has been made in this study. Input parameters for Monte Carlo analysis were developed or adjusted using body weight, lifetime, and exposure frequency of Koreans. Ambient distributions of toxic metals were founded to be lognormal distributions for most of them using goodness-of-fit tests. Thus, the 95% UCL and 95% LCL of carcinogenic metals were estimated by H-statistic method for lognormal distribution, respectively. The results of Monte Carlo analysis of 95% UCL showed that the 95th percentile risks for men and women were 1.2 and 1.1 times higher than an acceptable risk of 10$^{-5}$ , respectively. The probabilities which those risks exceed the acceptable risk were estimated to be 8% and 6%, respectively, while to be 95% and 94%, respectively on the basis of the minimum acceptable risk of 10$^{-6}$ , respectively. Approximately 90% of total cancer risk came from human carcinogens such as arsenic and hexavalent chromium. Therefore, it is necessary to properly manage both arsenic and hexavalent chromium emissions in the study area.