• Macromolecular Research
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• v.15 no.6
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• pp.491-497
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• 2007

NPT Monte Carlo simulations were performed to calculate the molecular properties of syndiotactic poly(vinyl chloride) (PVC) and syndiotactic poly(vinyl alcohol) (PVA) melts using the configurational bias Monte Carlo move, concerted rotation, reptation, and volume fluctuation. The density, mean square backbone end-to-end distance, mean square radius of gyration, fractional free-volume distribution, distribution of torsional angles, small molecule solubility constant, and radial distribution function of PVC at 0.1 MPa and above the glass transition temperature were calculated/measured, and those of PVA were calculated. The calculated results were compared with the corresponding experimental data and discussed. The calculated densities of PVC and PVA were smaller than the experimental values, probably due to the very low molecular weight of the model polymer used in the simulation. The fractional free-volume distribution and radial distribution function for PVC and PVA were nearly independent of temperature.

• Bulletin of the Korean Chemical Society
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• v.23 no.6
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• pp.811-817
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• 2002

Gibbs ensemble Monte Carlo simulations were performed to calculate the vapor-liquid coexistence properties for the binary mixtures $CO_2/CH_3OH$, $CO_2/C_2H_5OH$, and $CO_2/CH_3CH_2CH_2OH.$ The configurational bias Monte Carlo method was used in the simulation of alcohol. Density of the mixture, composition of the mixture, the pressure-composition diagram, and the radial distribution function were calculated at vapor-liquid equilibrium. The composition and the density of both vapor and liquid from simulation agree considerably well with the experimental values over a wide range of pressures. The radial distribution functions in the liquid mixtures show that $CO_2$ molecules interact more stogly with methyl group than methylene group of $C_2H_5OH$ and $CH_3CH_2CH_2OH$ due to the steric effects of the alcohol molecules.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.6
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• pp.135-142
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• 2004

The severe frontal crash tests are NCAP with belted occupant at 35mph and FMVSS 208 with unbelted occupant at 25mph, This paper describes the design process of occupant protection systems, airbag and seat belt, under the two tests. In this study, NCAP simulations are performed by Monte Carlo search method and cluster analysis. The Monte Carlo search method is a global optimization technique and requires execution of a series of deterministic analyses, The procedure is as follows. 1) Define the region of interest 2) Perform Monte Carlo simulation with uniform distribution 3) Transform output to obtain points grouped around the local minima 4) Perform cluster analysis to obtain groups that are close to each other 5) Define the several feasible design ranges. The several feasible designs are acquired and checked under FMVSS 208 simulation with unbelted occupant at 25mph.

• Bulletin of the Korean Chemical Society
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• v.21 no.7
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• pp.697-700
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• 2000

A method of calculating the excess Helmholtz free energy from the average of the bent effective acceptance ratio for two-center-Lennard-Jones liquids has been presented. The bent effective acceptance ratio has been newly composed from the acceptan ce ratio for the potential energy difference between a configuration in the Metropolis Monte Carlo procedure and random virtual configuration generated by the separate parallel Monte Carlo procedure and the Boltzmann factor for half the potential energy difference. The excess Helmholtz free energy was calculated directly from the average of the bent effective acceptance ratio through a single Metropolis Monte Carlo run. Because the separate parallel Monte Carlo procedure was used, this method can be applied to molecular dynamics simulations. For two-center-Lennard-Jones liquids, the average of the bent effective acceptance ratio gave better results than use of the modified effective acceptance ratio in the previous work.

• Current Optics and Photonics
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• v.5 no.6
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• pp.617-626
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• 2021

A parallel Monte Carlo photon migration algorithm for graphics processing units that implements an improved load-balancing strategy is presented. Conventional parallel Monte Carlo photon migration algorithms suffer from a computational bottleneck due to their reliance on a simple load-balancing strategy that does not take into account the different length of the mean free paths of the photons. In this paper, path-partition load balancing is proposed to eliminate this computational bottleneck based on a mathematical formula that parallelizes the photon path tracing process, which has previously been considered non-parallelizable. The performance of the proposed algorithm is tested using three-dimensional photon migration simulations of a human skin model.

• 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.

• Nuclear Engineering and Technology
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• v.55 no.7
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• pp.2712-2722
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• 2023

For an accurate and efficient time-dependent Monte Carlo (TDMC) neutron transport analysis, several advanced methods are newly developed and implemented in the Seoul National University Monte Carlo code, McCARD. For an efficient control of the neutron population, a dynamic weight window method is devised to adjust the weight bounds of the implicit capture in the time bin-by-bin TDMC simulations. A moving geometry module is developed to model a continuous insertion or withdrawal of a control rod. Especially, the history-based batch method for the TDMC calculations is developed to predict the unbiased variance of a bin-wise mean estimate. The developed methods are verified for three-dimensional problems in the C5G7-TD benchmark, showing good agreements with results from a deterministic neutron transport analysis code, nTRACER, within the statistical uncertainty bounds. In addition, the TDMC analysis capability implemented in McCARD is demonstrated to search the optimum detector positions for the pulsed-neutron-source experiments in the Kyoto University Critical Assembly and AGN201K.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.116-118
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• 2002

It has been noted that Monte Carlo simulations are the most accurate method to calculate dose distributions in any material and geometry. Monte Carlo transport algorithms determine the absorbed dose by following the path of representative particles as they travel through the medium. Accurate Monte Carlo dose calculations rely on detailed modeling of the radiation source. We modeled the effects of beam modifiers such as collimators, blocks, wedges, etc. of our accelerator, Varian Clinac 600C/D to ensure accurate representation of the radiation source using the EGSnrc based BEAM code. These were used in the EGSnrc based DOSXYZ code for the simulation of particles transport through a voxel based Cartesian coordinate system. Because Monte Carlo methods use particle-by-particle methods to simulate a radiation transport, more particle histories yield the better representation of the actual dose. But the prohibitively long time required to get high resolution and accuracy calculations has prevented the use of Monte Carlo methods in the actual clinical spots. Our ultimate aim is to develop a Monte Carlo dose calculation system designed specifically for radiation therapy planning, which is distinguished from current dose calculation methods. The purpose of this study in the present phase was to get dose calculation results corresponding to measurements within practical time limit. We used parallel processing and some variance reduction techniques, therefore reduced the computational time, preserving a good agreement between calculations of depth dose distributions and measurements within 5% deviations.

• 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.

• Nuclear Engineering and Technology
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• v.49 no.6
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• pp.1165-1171
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• 2017

The traditional form of parallelism in Monte Carlo particle transport simulations, wherein each individual particle history is considered a unit of work, does not lend itself well to data-level parallelism. Event-based algorithms, which were originally used for simulations on vector processors, may offer a path toward better utilizing data-level parallelism in modern computer architectures. In this study, a simple model is developed for estimating the efficiency of the event-based particle transport algorithm under two sets of assumptions. Data collected from simulations of four reactor problems using OpenMC was then used in conjunction with the models to calculate the speedup due to vectorization as a function of the size of the particle bank and the vector width. When each event type is assumed to have constant execution time, the achievable speedup is directly related to the particle bank size. We observed that the bank size generally needs to be at least 20 times greater than vector size to achieve vector efficiency greater than 90%. When the execution times for events are allowed to vary, the vector speedup is also limited by differences in the execution time for events being carried out in a single event-iteration.