• Journal of Information Processing Systems
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• v.17 no.4
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• pp.737-753
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• 2021

As the demand for high-quality rendering for mixed reality, videogame, and simulation has increased, global illumination has been actively researched. Monte Carlo path tracing can realize global illumination and produce photorealistic scenes that include critical effects such as color bleeding, caustics, multiple light, and shadows. If the sampling rate is insufficient, however, the rendered results have a large amount of noise. The most successful approach to eliminating or reducing Monte Carlo noise uses a feature-based filter. It exploits the scene characteristics such as a position within a world coordinate and a shading normal. In general, the techniques are based on the denoised pixel or sample and are computationally expensive. However, the main challenge for all of them is to find the appropriate weights for every feature while preserving the details of the scene. In this paper, we compare the recent algorithms for removing Monte Carlo noise in terms of their performance and quality. We also describe their advantages and disadvantages. As far as we know, this study is the first in the world to compare the artificial intelligence-based denoising methods for Monte Carlo rendering.

• Nuclear Engineering and Technology
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• v.54 no.5
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• pp.1902-1908
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• 2022

In many of the complex systems modeled in the field of nuclear engineering, it is often useful to use linear regression-based analyses to analyze relationships between model parameters and responses of interests. In cases where the response of interest is calculated by a simulation which uses Monte Carlo methods, there will be some uncertainty in the responses. Further, the reduction of this uncertainty increases the time necessary to run each calculation. This paper presents some discussion on how the Monte Carlo error in the response of interest influences the error in computed linear regression coefficients. A mathematical justification is given that shows that when performing linear regression in these scenarios, the error in regression coefficients can be largely independent of the Monte Carlo error in each individual calculation. This condition is only true if the total number of calculations are scaled to have a constant total time, or amount of work, for all calculations. An application with a simple pin cell model is used to demonstrate these observations in a practical problem.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2004.11a
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• pp.210-215
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• 2004

In can occur to many problems on progressing step without close scope definition, interrelation definition between activities, resource plan, and schedule plan on planning step. But it have not closely defined performance system on planning step because of many constraints of domestic construction industry. Therefore this paper intends to discuss a method of calculating optimal cost and duration using Linear Programming that solves maximing or minimizing problems among decision making methodology and Monte Carlo Simulation that decreases to probability errors. With outcoms applying Linear programming and Monte Carlo Simulation for calculating optimal cost and duration, follow as : With outcomes applying Monte Carlo Simulation, it could calculate reliable estimator about project duration through removing various constraints. With outcomes applying Linear programming, it could calculate optimal value about project cost through defining various variables and constraints on many activities.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.27 no.12
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• pp.1758-1765
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• 2003

Monte Carlo simulation(MC) method was used as an uncertainty assessment tool for gas flow measurement in this paper. Uncertainty sources for gas flow measurement were analyzed, and probability distribution characteristics of each source were discussed. Detailed MC methodology was described including the effect of the number of simulation. The uncertainty result was compared with that of the conventional sensitivity coefficient method, and it was revealed that the results were different from each other for this particular gas flow measurement case of which the modelling equation was nonlinear. The MC was comparatively simple, convenient and accurate as an uncertainty assessment method, especially in cases of complex, nonlinear measurement modelling equations. It was noted that the uncertainty assessment method should be selected carefully according to the mathematical characteristics of the measurement.

• Journal of Ocean Engineering and Technology
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• v.28 no.6
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• pp.566-573
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• 2014

This paper presents the results of an integrated navigation performance analysis for selecting the sensor of an unmanned underwater vehicle (UUV) using Monte Carlo numerical simulation. An inertial measurement unit (IMU) and Doppler velocity log (DVL) are considered to build the integrated navigation system. The position error and price of the sensor are selected as performance indices to evaluate the volunteer integrated navigation systems. Monte-Carlo simulation is introduced to analyze the circular error probability (CEP) and its variance. Simulation results provide the proper sensor combination for integrated navigation in relation to the performance and price.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.60 no.3
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• pp.105-109
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• 2011

Drift Velocity of Electrons in pure $CF_4$, $CH_4$ and mixtures of $CF_4$ and Ar. Have been analyzed over a range of the reduced electric field strength between 0.1 and 350[Td] by the two-term approximation of the Boltzmann equation (BEq.) method and the Monte Carlo simulation (MCS). The results of the Boltzmann equation and the Monte Carlo simulation have been compared with the data presented by several workers. The deduced transport coefficients for electrons agree reasonably well with the experimental and simulation data obtained by Nakamura and Hayashi. The energy distribution function of electrons in $CF_4$-Ar mixtures shows the Maxwellian distribution for energy. That is, f(${\varepsilon}$) has the symmetrical shape whose axis of symmetry is a most probably energy. The measured results and the calculated results have been compared each other.

• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1114-1116
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• 1999

This paper presents a new algorithm which evaluates production cost and reliability indices under various constraints of the thermal generation system. In order to consider the operational constraints of thermal units effectively, the proposed algorithm is based on Monte Carlo techniques instead of analytical ones which have difficulty in modelling the units with additional constraints. At that point, generating units are modelled into two types, base load units and peaking units. These generating unit models are used in state duration sampling simulation for which approach can readily consider the peaking unit operating cycles and easily calculates frequency-duration indices. The proposed production simulation algorithm is applied to the IEEE Reliability Test System, and performs the production simulation under the given constraints. The results show that the proposed algorithm is accurate, reliable and useful.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.485-488
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• 2002

In order to understand and quantitatively analyze the physical phenomena and behavior of each component of mammography system during the breast imaging, we simulated mammography imaging using Monte Carlo simulation codes. MCNP4B code was used for our simulation purpose, and we investigated the effect of target material, anode angle, filtration, peak voltage and exposure on the image quality of mammograms. From the simulation results we expect that optimized operation condition of mammography system can be found.

• KCI Concrete Journal
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• v.12 no.2
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• pp.11-21
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• 2000

It is not easy to correctly predict deflections of reinforced concrete beams and one-way slabs due to the variability of parameters involved in the calculation of deflections. Monte Carlo simulation is used to assess the variability of deflections with known statistical data and probability distributions of variables. A deterministic deflection value is obtained using the layered beam model based on the finite element approach in which a finite element is divided into a number of layers over the depth. The model takes into account nonlinear effects such as cracking, creep and shrinkage. Statistical parameters were obtained from the literature. For the assessment of variability of deflections, 12 cases of one-way slabs and T-beams are designed on the basis of ultimate moment capacity. Several results of a probabilistic study are presented to indicate general trends indicated by results and demonstrate the effect of certain design parameters on the variability of deflections. From simulation results, the variability of deflections relies primarily on the ratio of applied moment to cracking moment and the corre-sponding reinforcement ratio.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.63 no.1
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• pp.19-23
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• 2014

This paper describes the electron transport characteristics in $SF_6$-He gas calculated E/N values 0.1~700[Td] by the Monte Carlo simulation and Boltzmann equation method using a set of electron collision cross sections determined by the authors and the values of electron swarm parameters obtained by TOF method. This study gained the values of the electron swarm parameters such as the electron drift velocity, the electron ionization or attachment coefficients, longitudinal and transverse diffusion coefficients for $SF_6$-He gas at a range of E/N. A set of electron collision cross section has been assembled and used in Monte Carlo simulation to predict values of swarm parameters. The result of Boltzmann equation and Monte Carlo Simulation has been compared with experimental data by Ohmori, Lucas and Carter. The swarm parameter from the swarm study are expected to sever as a critical test of current theories of low energy scattering by atoms and molecules.