• Journal of Radiation Protection and Research
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• v.47 no.1
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• pp.50-57
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• 2022

Background: There are several proton therapy facilities in operation or planned in Taiwan, and these facilities are anticipated to not only treat cancer but also provide beam services to the industry or academia. The simplified approach based on the Monte Carlo-based data sets (source terms and attenuation lengths) with the point-source line-of-sight approximation is friendly in the design stage of the proton therapy facilities because it is intuitive and easy to use. The purpose of this study is to expand the Monte Carlo-based data sets to allow the simplified approach to cover the application of proton beams more widely. Materials and Methods: In this work, the MCNP6 Monte Carlo code was used in three simulations to achieve the purpose, including the neutron yield calculation, Monte Carlo-based data sets generation, and dose assessment in simple cases to demonstrate the effectiveness of the generated data sets. Results and Discussion: The consistent comparison of the simplified approach and Monte Carlo simulation results show the effectiveness and advantage of applying the data set to a quick shielding design and conservative dose assessment for proton therapy facilities. Conclusion: This study has expanded the existing Monte Carlo-based data set to allow the simplified approach method to be used for dose assessment or shielding design for beam services in proton therapy facilities. It should be noted that the default model of the MCNP6 is no longer the Bertini model but the CEM (cascade-exciton model), therefore, the results of the simplified approach will be more conservative when it was used to do the double confirmation of the final shielding design.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.34D no.7
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• pp.37-44
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• 1997

A dadaptive refinement tetrahedron mesh has been presented for using in full band GaAs monte carlo simulation. A uniform tetrahedron mesh is used without regard to energy values and energy variety in case of the past full band simulation. For the uniform tetrahedron mesh, a fine tetrahedron is demanded for keeping up accuracy of calculation in the low energy region such as .GAMMA.-valley, but calculation time is vast due to usin gthe same tetrahedron in the high energy region. The mesh of this study, thererfore, is consisted of the fine mesh in the low energy and large variable energy region and rough mesh n the high energy. The density of states (DOS) calculated with this mesh is compared with the one of the uniform mesh. The DOS of this mesh is improved th efive times or so in root mean square error and the ten times in the correlation coefficient than the one of a uniform mesh. This refinement mesh, therefore, can be used a sthe basic mesh for the full band GaAs monte carlo simulation.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.18 no.2
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• pp.187-193
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• 2009

Dynamic response of an elastic pendulum system under random excitations was studied by using the Lagrangian equations of motion which uses the kinetic and potential energy of a target system. The responses of random excitations were calculated by using Monte Carl simulation which uses the series of random numbers. The procedure of Monte Carlo simulation is generation of random numbers, system model, system output, and statistical management of output. When the levels of random excitations were changed, the expected responses of the pendulum system showed various responses.

• Journal of Ocean Engineering and Technology
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• v.34 no.5
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• pp.316-324
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• 2020

This paper presents comparative studies of reliability analysis and meta-modeling using the sampling method of Monte Carlo simulation for the structure design of an automatic ocean salt collector (AOSC). The thickness sizing variables of structure members are considered as random variables. Probabilistic performance functions are selected from strength performances evaluated via the finite element analysis of an AOSC. The sampling methods used in the comparative studies are simple random sampling and Sobol sequences with varied numbers of sampling. Approximation methods such as the Kriging model is applied to the meta-model generation. Reliability performances such as the probability failure and distribution are compared based on the variation of the sampling method of Monte Carlo simulation. The meta-modeling accuracy is evaluated for the Kriging model generated from the Monte Carlo simulation and Sobol sequence results. It is discovered that the Sobol sequence method is applicable to not only to the reliability analysis for the structural design of marine equipment such as the AOSC, but also to Kriging meta-modeling owing to its high numerical efficiency.

• Nuclear Engineering and Technology
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• v.53 no.9
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• pp.2788-2802
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• 2021

Multigroup cross section (MG XS) generation by the UNIST in-house Monte Carlo (MC) code MCS for fast reactor analysis using nodal diffusion codes is reported. The feasibility of the approach is quantified for two sodium fast reactors (SFRs) specified in the OECD/NEA SFR benchmark: a 1000 MW_th metal-fueled SFR (MET-1000) and a 3600 MW_th oxide-fueled SFR (MOX-3600). The accuracy of a few-group XSs generated by MCS is verified using another MC code, Serpent 2. The neutronic steady-state whole-core problem is analyzed using MCS/RAST-K with a 24-group XS set. Various core parameters of interest (core k_eff, power profiles, and reactivity feedback coefficients) are obtained using both MCS/RAST-K and MCS. A code-to-code comparison indicates excellent agreement between the nodal diffusion solution and stochastic solution; the error in the core k_eff is less than 110 pcm, the root-mean-square error of the power profiles is within 1.0%, and the error of the reactivity feedback coefficients is within three standard deviations. Furthermore, using the super-homogenization-corrected XSs improves the prediction accuracy of the control rod worth and power profiles with all rods in. Therefore, the results demonstrate that employing the MCS MG XSs for the nodal diffusion code is feasible for high-fidelity analyses of fast reactors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.10
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• pp.3355-3372
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• 2022

Composing music is an inspired yet challenging task, in that the process involves many considerations such as assigning pitches, determining rhythm, and arranging accompaniment. Algorithmic composition aims to develop algorithms for music composition. Recently, algorithmic composition using artificial intelligence technologies received considerable attention. In particular, computational intelligence is widely used and achieves promising results in the creation of music. This paper attempts to provide a survey on the music generation based on the Monte Carlo (MC) algorithm. First, transform the MIDI music format files to digital data. Among these data, use the logistic fitting method to fit the time series, obtain the time distribution regular pattern. Except for time series, the converted data also includes duration, pitch, and velocity. Second, using MC simulation to deal with them summed up their distribution law respectively. The two main control parameters are the value of discrete sampling and standard deviation. Processing the above parameters and converting the data to MIDI file, then compared with the output generated by LSTM neural network, evaluate the music comprehensively.

• Bulletin of the Korean Chemical Society
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• v.30 no.1
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• pp.97-101
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• 2009

A new approach was applied to examine the charge generation and transport in organic photoconductive devices by Monte‐Carlo simulation utilizing multiple site interactions of carriers with all other charges within Coulomb radius. Stepwise generation frame was considered first by a charge separation process that was counted in two separate transactions, i.e., hopping against physical decay and dissociation against recombination. Thereafter, diffusion/ drifting process of free carriers was counted to follow. This method enables to examine readily the photocurrent generated alongside the charge generation efficiency. The field and temperature dependences of the efficiency and photocurrent were obtained comparable to Onsager’s and experimental data.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.5
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• pp.45-53
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• 2011

This paper presents a novel random sampling method for generation adequacy assessment including wind-power. Although a time sequential sampling has advantages than a random sampling in its assessment results, it takes long assessment time. Therefore, an effective random sampling method for generation adequacy assessment is highly recommended to get specific reliability indices quickly. The proposed method is based on the Monte-Carlo simulation with state sampling and it can be applied to generation adequacy assessment with other intermittent power sources.

• Journal of the Korean Society of Safety
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• v.32 no.6
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• pp.29-33
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• 2017

In order to solve this sort of electrostatic failure in Display and Semiconductor process, Soft X-ray ionizer is mainly used. Soft X-ray Ionizer does not only generate electrical noise and minute particle but also is efficient to remove electrostatic as it has a wide range of ionization. There exist variable factors such as type of tungsten thickness deposited on target, Anode voltage etc., and it takes a lot of time and financial resource to find optimal performance by manufacturing with actual X-ray tube source. Here, MCNPX (Monte Carlo N-Particle Extended) is used for simulation to solve this kind of problem, and optimum efficiency of X-ray generation is anticipated. In this study, X-ray generation efficiency was compared according to target material thickness using MCNPX and actual X-ray tube source under the conditions that tube voltage is 5 keV, 10 keV, 15 keV and the target Material is Tungsten(W). At the result, In Tube voltage 5 keV and distance 100 mm, optimal target thickness is $0.05{\mu}m$ and fastest decay time appears + decay time 0.28 sec. - deacy time 0.30 sec. In Tube voltage 10keV and distance 100 mm, optimal target Thickness is $0.16{\mu}m$ and fastest decay time appears + decay time 0.13 sec. - deacy time 0.12 sec. In the tube voltage 15 keV and distance 100 mm, optimal target Thickness is $0.28{\mu}m$ and fastest decay time appears + decay time 0.04 sec. - deacy time 0.05 sec.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.4
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• pp.337-344
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• 2001

As cost invested in developing the specified technology is increasing, investors are paying more attention to cost to benefit analysis (CBA). One of the basic elements of CBA for new technological development is the diffusion pattern of demand of such technology. Many studies of technology evaluation have adopted a single generation model to simulate the diffusion pattern of demand. This approach, however, considers the diffusion of the new technology itself, not taking into account a newer generation that can replace the one just invented. In this paper, we show how a multi-generation technology diffusion model can be applied for more accurate CBA for information technology. Monte Carlo simulation is performed to find influential factors on the CBA of a Cybernetic Building System.