• Clean Technology
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• v.17 no.2
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• pp.103-109
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• 2011

The process optimization was carried out to improve the throwing power (TP) and the thickness uniformity of the electroless copper (Cu) plating, which plays a seed layer for the subsequent electroplating. The DOE (design of experiment) was employed to screen key factors out of all available operation parameters to influence the TP and thickness uniformity the most. It turned out that higher Cu ion concentration and lower plating temperature are advantageous to accomplish uniform via filling and they are accounted for based on the surface reactivity. To visualize what occurred experimentally and evaluate the phenomena qualitatively, the kinetic Monte Carlo (MC) simulation was introduced. The combination of neatly designed experiments by DOE and supporting theoretical simulation is believed to be inspiring in solving similar kinds of problems in the relevant field.

• Journal of Radiation Protection and Research
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• v.47 no.3
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• pp.152-157
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• 2022

Background: The hemi-body electron beam irradiation (HBIe^-) technique has been proposed for the treatment of mycosis fungoides. It spares healthy skin using an electron shield. However, shielding electrons is complicated owing to electron scattering effects. In this study, we developed a thimble-like head bolus shield that surrounds the patient's entire head to prevent irradiation of the head during HBIe^-. Materials and Methods: The feasibility of a thimble-like head bolus shield was evaluated using a simplified Geant4 Monte Carlo (MC) simulation. Subsequently, the head bolus was manufactured using a three-dimensional (3D) printed mold and Ecoflex 00-30 silicone. The fabricated head bolus was experimentally validated by measuring the dose to the Rando phantom using a metal-oxide-semiconductor field-effect transistor (MOSFET) detector with clinical configuration of HBIe^-. Results and Discussion: The thimble-like head bolus reduced the electron fluence by 2% compared with that without a shield in the MC simulations. In addition, an improvement in fluence degradation outside the head shield was observed. In the experimental validation using the inhouse-developed bolus shield, this head bolus reduced the electron dose to approximately 2.5% of the prescribed dose. Conclusion: A thimble-like head bolus shield for the HBIe^- technique was developed and validated in this study. This bolus effectively spares healthy skin without underdosage in the region of the target skin in HBIe^-.

• Structural Engineering and Mechanics
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• v.81 no.3
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• pp.293-303
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• 2022

As infrastructure ages and traffic load increases, serious public concerns have arisen for the well-being of bridges. The current health monitoring practice focuses on large-scale bridges rather than short span bridges. However, it is critical that more attention should be given to these behind-the-scene bridges. The relevant information about the construction methods and as-built properties are most likely missing. Additionally, since the condition of a bridge has unavoidably changed during service, due to weathering and deterioration, the material properties and boundary conditions would also have changed since its construction. Therefore, it is not appropriate to continue using the design values of the bridge parameters when undertaking any analysis to evaluate bridge performance. It is imperative to update the model, using finite element (FE) analysis to reflect the current structural condition. In this study, a FE model is established to simulate a concrete culvert bridge in New South Wales, Australia. That model, however, contains a number of parameter uncertainties that would compromise the accuracy of analytical results. The model is therefore updated with a neural network (NN) optimisation algorithm incorporating Monte Carlo (MC) simulation to minimise the uncertainties in parameters. The modal frequency and strain responses produced by the updated FE model are compared with the frequency and strain values on-site measured by sensors. The outcome indicates that the NN model updating incorporating MC simulation is a feasible and robust optimisation method for updating numerical models so as to minimise the difference between numerical models and their real-world counterparts.

• Progress in Medical Physics
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• v.33 no.4
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• pp.129-135
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• 2022

Purpose: A full-energy-peak (FEP) efficiency correction is required through a Monte Carlo simulation for accurate radioactivity measurement, considering the geometrical characteristics of the detector and the sample. However, a relative deviation (RD) occurs between the measurement and calculation efficiencies when modeling using the data provided by the manufacturers due to the randomly generated dead layer. This study aims to optimize the structure of the detector by determining the dead layer thickness based on Monte Carlo simulation. Methods: The high-purity germanium (HPGe) detector used in this study was a coaxial p-type GC2518 model, and a certified reference material (CRM) was used to measure the FEP efficiency. Using the MC N-Particle Transport Code (MCNP) code, the FEP efficiency was calculated by increasing the thickness of the outer and inner dead layer in proportion to the thickness of the electrode. Results: As the thickness of the outer and inner dead layer increased by 0.1 mm and 0.1 ㎛, the efficiency difference decreased by 2.43% on average up to 1.0 mm and 1.0 ㎛ and increased by 1.86% thereafter. Therefore, the structure of the detector was optimized by determining 1.0 mm and 1.0 ㎛ as thickness of the dead layer. Conclusions: The effect of the dead layer on the FEP efficiency was evaluated, and an excellent agreement between the measured and calculated efficiencies was confirmed with RDs of less than 4%. It suggests that the optimized HPGe detector can be used to measure the accurate radioactivity using in dismantling and disposing medical linear accelerators.

• Journal of the Korean Society of Radiology
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• v.10 no.3
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• pp.153-159
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• 2016

This study investigated relationship between secondary electrons produced from single gold nanoparticle as a result of its interaction with radiation and particle size and incidence energy, provided basic data related to the dose enhancement effect based on gold nanoparticles. Monte Carlo simulation was applied by using MCNPX MC code, 50, 100, 150 kV and 6, 15 MV x-ray energy was used. In a water phantom, single gold nanoparticles that are 30, 50, 70, 90, and 110 nm in diameter were placed and the tally volume was designated at every 10 nm. Difference in electrons produced from gold nanoparticles was normalized based on absence of nanoparticle. When the X ray energy decreased and the diameter of gold particles increased, more electrons were produced. When the energy was lower, in the linear formula related to nanoparticle size and electron production, the gradient was higher. And, in comparison to the MV X-ray, at kV X-ray, significantly more electrons were produced. This study can be used as data to understand the dose enhancement effect based on gold nanoparticles, and further research related to various materials that dose enhancement including gold nanoparticles needs to be conducted.

• Nuclear Engineering and Technology
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• v.54 no.8
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• pp.3073-3084
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• 2022

The propagation of radiation source uncertainties in spent nuclear fuel (SNF) cask shielding calculations is presented in this paper. The uncertainty propagation employs the depletion and source term outputs of the deterministic code STREAM as input to the transport simulation of the Monte Carlo (MC) codes MCS and MCNP6. The uncertainties of dose rate coming from two sources: nuclear data and modeling parameters, are quantified. The nuclear data uncertainties are obtained from the stochastic sampling of the cross-section covariance and perturbed fission product yields. Uncertainties induced by perturbed modeling parameters consider the design parameters and operating conditions. Uncertainties coming from the two sources result in perturbed depleted nuclide inventories and radiation source terms which are then propagated to the dose rate on the cask surface. The uncertainty analysis results show that the neutron and secondary photon dose have uncertainties which are dominated by the cross section and modeling parameters, while the fission yields have relatively insignificant effect. Besides, the primary photon dose is mostly influenced by the fission yield and modeling parameters, while the cross-section data have a relatively negligible effect. Moreover, the neutron, secondary photon, and primary photon dose can have uncertainties up to about 13%, 14%, and 6%, respectively.

• Nuclear Engineering and Technology
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• v.54 no.10
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• pp.3943-3948
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• 2022

Single-photon emission computed tomography is one of the reliable pin-by-pin verification techniques for spent-fuel assemblies. One of the challenges with this technique is to increase the total fuel assembly verification speed while maintaining high verification accuracy. The aim of the present study, therefore, was to develop an artificial intelligence (AI) algorithm-based tomographic image analysis technique for partial-defect verification of fuel assemblies. With the Monte Carlo (MC) simulation technique, a tomographic image dataset consisting of 511 fuel-rod patterns of a 3 × 3 fuel assembly was generated, and with these images, the VGG16, GoogLeNet, and ResNet models were trained. According to an evaluation of these models for different training dataset sizes, the ResNet model showed 100% pattern estimation accuracy. And, based on the different tomographic image qualities, all of the models showed almost 100% pattern estimation accuracy, even for low-quality images with unrecognizable fuel patterns. This study verified that an AI model can be effectively employed for accurate and fast partial-defect verification of fuel assemblies.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.127-127
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• 2021

In order to estimate parameter uncertainty of hydrological models, the consideration of the likelihood functions which provide reliable parameters of model is necessary. In this study, the Bayesian Markov Chain Monte Carlo (MCMC) method with informal likelihood functions is used to analyze the uncertainty of parameters of the SURR model for estimating the hourly streamflow of Gunnam station of Imjin basin, Korea. Three events were used to calibrate and one event was used to validate the posterior distributions of parameters. Moreover, the performance of four informal likelihood functions (Nash-Sutcliffe efficiency, Normalized absolute error, Index of agreement, and Chiew-McMahon efficiency) on uncertainty of parameter is assessed. The indicators used to assess the uncertainty of the streamflow simulation were P-factor (percentage of observed streamflow included in the uncertainty interval) and R-factor (the average width of the uncertainty interval). The results showed that the sensitivities of parameters strongly depend on the likelihood functions and vary for different likelihood functions. The uncertainty bounds illustrated the slight differences from various likelihood functions. This study confirms the importance of the likelihood function selection in the application of Bayesian MCMC to the uncertainty assessment of the SURR model.

• Nuclear Engineering and Technology
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• v.56 no.5
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• pp.1754-1761
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• 2024

In hadrontherapy, secondary fragments are generated by nuclear interactions of the incident heavy ion beam with the atomic nuclei of the target. It is important to determine the yield of production and the dose contribution of these secondary fragments in order to determine the radiobiological effectiveness more accurately. This work aims to fully identify the secondary fragments generated by nuclear interactions of proton and helium (⁴He) ion beams in a High-Density Polyethylene (HDPE) target and to investigate the dose contributions by secondary fragments. Incident protons with energies of 55.90 MeV and 105.20 MeV and helium ions with energies of 52.55 MeV/u and 103.50 MeV/u in the HDPE phantom have been investigated by the means of Geant4 Monte Carlo (MC) simulations. Simulated results were validated using NASA Space Radiation Laboratory (NSRL) Bragg curves experimental data. The results showed that the dose contribution of secondary fragments deriving from helium ion beams is three times higher than in the case of proton beams. This is due to a higher production of nuclear fragments in the case of helium ion beams. This work contributes to a better understanding of secondary fragments generated by protons and helium ions in the HDPE target.

• Radiation Oncology Journal
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• v.28 no.4
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• pp.224-230
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• 2010

Purpose: We designed the aft-multiple-slit (AMS) system to reduce scatter in cone-beam computed tomography (CBCT). As a preliminary study, we performed a Monte Carlo N-Particle Transport Code (MCNP) simulation to verify the effectiveness of this system. Materials and Methods: The MCNPX code was used to build the AMS geometry. An AMS is an equi-angled arc to consider beam divergence. The scatter-reduced projection images were compared with the primary images only and the primary plus scatter radiation images with and without AMS to evaluate the effectiveness of scatter reduction. To obtain the full 2 dimensional (2D) projection image, the whole AMS system was moved to obtain closed septa of the AMS after the first image acquisition. Results: The primary radiation with and without AMS is identical to all the slit widths, but the profiles of the primary plus scattered radiation varied according to the slit widths in the 2D projection image. The average scatter reduction factors were 29%, 15%, 9%, and 8% when the slit widths were 5 mm, 10 mm, 15 mm, and 20 mm, respectively. Conclusion: We have evaluated the scatter reduction effect of the AMS in CBCT imaging using the Monte Carlo (MC) simulations. A preliminary study based on the MCNP simulations showed a mount of scatter reduction with the proposed system.