• Nuclear Engineering and Technology
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• v.48 no.5
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• pp.1273-1279
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• 2016

Production of iodine-131 by neutron activation of tellurium in tellurium dioxide ($TeO_2$) material requires a target that meets the safety requirements. In a radiopharmaceutical production unit, a new lid for a can was designed, which permits tight sealing of the target by using tungsten inert gaswelding. The leakage rate of all prepared targets was assessed using a helium mass spectrometer. The accepted leakage rate is ${\leq}10^{-4}mbr.L/s$, according to the approved safety report related to iodine-131 production in the TRIGA Mark II research reactor (TRIGA: Training, Research, Isotopes, General Atomics). To confirm the resistance of the new design to the irradiation conditions in the TRIGA Mark II research reactor's central thimble, a study of heat effect on the sealed targets for 7 hours in an oven was conducted and the leakage rates were evaluated. The results show that the tightness of the targets is ensured up to $600^{\circ}C$ with the appearance of deformations on lids beyond $450^{\circ}C$. The study of heat transfer through the target was conducted by adopting a one-dimensional approximation, under consideration of the three transfer modes-convection, conduction, and radiation. The quantities of heat generated by gamma and neutron heating were calculated by a validated computational model for the neutronic simulation of the TRIGA Mark II research reactor using the Monte Carlo N-Particle transport code. Using the heat transfer equations according to the three modes of heat transfer, the thermal study of I-131 production by irradiation of the target in the central thimble showed that the temperatures of materials do not exceed the corresponding melting points. To validate this new design, several targets have been irradiated in the central thimble according to a preplanned irradiation program, going from4 hours of irradiation at a power level of 0.5MWup to 35 hours (7 h/d for 5 days a week) at 1.5MW. The results showthat the irradiated targets are tight because no iodine-131 was released in the atmosphere of the reactor building and in the reactor cooling water of the primary circuit.

• Journal of The Korean Society of Agricultural Engineers
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• v.46 no.5
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• pp.27-39
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• 2004

In the first part of this study, five homogeneous regions in view of topographical and geographically homogeneous aspects except Jeju and Ulreung islands in Korea were accomplished by K-means clustering method. A total of 57 rain gauges were used for the regional frequency analysis with minimum rainfall series for the consecutive durations. Generalized Extreme Value distribution was confirmed as an optimal one among applied distributions. Drought rainfalls following the return periods were estimated by at-site and regional frequency analysis using L-moments method. It was confirmed that the design drought rainfalls estimated by the regional frequency analysis were shown to be more appropriate than those by the at-site frequency analysis. In the second part of this study, LH-moment ratio diagram and the Kolmogorov-Smirnov test on the Gumbel (GUM), Generalized Extreme Value (GEV), Generalized Logistic (GLO) and Generalized Pareto (GPA) distributions were accomplished to get optimal probability distribution. Design drought rainfalls were estimated by both at-site and regional frequency analysis using LH-moments and GEV distribution, which was confirmed as an optimal one among applied distributions. Design rainfalls were estimated by at-site and regional frequency analysis using LH-moments, the observed and simulated data resulted from Monte Carlotechniques. Design drought rainfalls derived by regional frequency analysis using L1, L2, L3 and L4-moments (LH-moments) method have shown higher reliability than those of at-site frequency analysis in view of RRMSE (Relative Root-Mean-Square Error), RBIAS (Relative Bias) and RR (Relative Reduction) for the estimated design drought rainfalls. Relative efficiency were calculated for the judgment of relative merits and demerits for the design drought rainfalls derived by regional frequency analysis using L-moments and L1, L2, L3 and L4-moments applied in the first report and second report of this study, respectively. Consequently, design drought rainfalls derived by regional frequency analysis using L-moments were shown as more reliable than those using LH-moments. Finally, design drought rainfalls for the classified five homogeneous regions following the various consecutive durations were derived by regional frequency analysis using L-moments, which was confirmed as a more reliable method through this study. Maps for the design drought rainfalls for the classified five homogeneous regions following the various consecutive durations were accomplished by the method of inverse distance weight and Arc-View, which is one of GIS techniques.

• Journal of Computational Design and Engineering
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• v.3 no.3
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• pp.179-190
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• 2016

A kind of modified epoxy resin sheet molding compounds of the impeller has been designed. Through the test, the non-metal impeller has a better environmental aging performance, but must do the waterproof processing design. In order to improve the stability of the impeller vibration design, the influence of uncertainty factors is considered, and a multi-objective robust optimization method is proposed to reduce the weight of the impeller. Firstly, based on the fluid-structure interaction, the analysis model of the impeller vibration is constructed. Secondly, the optimal approximate model of the impeller is constructed by using the Latin hypercube and radial basis function, and the fitting and optimization accuracy of the approximate model is improved by increasing the sample points. Finally, the micro multi-objective genetic algorithm is applied to the robust optimization of approximate model, and the Monte Carlo simulation and Sobol sampling techniques are used for reliability analysis. By comparing the results of the deterministic, different sigma levels and different materials, the multi-objective optimization of the SMC molding impeller can meet the requirements of engineering stability and lightweight. And the effectiveness of the proposed multi-objective robust optimization method is verified by the error analysis. After the SMC molding and the robust optimization of the impeller, the optimized rate reached 42.5%, which greatly improved the economic benefit, and greatly reduce the vibration of the ventilation system.

• Journal of radiological science and technology
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• v.38 no.3
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• pp.237-244
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• 2015

Health professionals in nuclear medicine were known that they get high radiation exposure. To reduce radiation exposure, using shielding materials is needed. In this study, we analyzed the shielding effect about apron during 18F-FDG treatment by using simulation based on Monte Carlo techniques and actual measurement. As a result, absorbed dose distribution of organ varies with handling position of the source. Dose reduction ratio by lead thickness of apron tended to decease, when handling position of the source come close to organ and away from radiation source for simulation. In the case of actual measurement with the dosimetry device, It showed that mean spatial dose distribution was different due to characteristics of dosimetry device. However, spatial dose rate was exponentially reduced according to distance with increasing lead content.

• Smart Structures and Systems
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• v.22 no.5
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• pp.561-574
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• 2018

In this paper, for efficiently reducing the computational cost of the model updating during the optimization process of damage detection, the structural response is evaluated using properly trained surrogate model. Furthermore, in practice uncertainties in the FE model parameters and modelling errors are inevitable. Hence, an efficient approach based on Monte Carlo simulation is proposed to take into account the effect of uncertainties in developing a surrogate model. The probability of damage existence (PDE) is calculated based on the probability density function of the existence of undamaged and damaged states. The current work builds a framework for Probability Based Damage Detection (PBDD) of structures based on the best combination of metaheuristic optimization algorithm and surrogate models. To reach this goal, three popular metamodeling techniques including Cascade Feed Forward Neural Network (CFNN), Least Square Support Vector Machines (LS-SVMs) and Kriging are constructed, trained and tested in order to inspect features and faults of each algorithm. Furthermore, three wellknown optimization algorithms including Ideal Gas Molecular Movement (IGMM), Particle Swarm Optimization (PSO) and Bat Algorithm (BA) are utilized and the comparative results are presented accordingly. Furthermore, efficient schemes are implemented on these algorithms to improve their performance in handling problems with a large number of variables. By considering various indices for measuring the accuracy and computational time of PBDD process, the results indicate that combination of LS-SVM surrogate model by IGMM optimization algorithm have better performance in predicting the of damage compared with other methods.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.276-286
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• 2013

SVD-based deconvolution algorithm has been known as the most effective technique for CT perfusion image analysis. In this algorithm, in order to reduce noise effects, SVD coefficients smaller than a certain threshold are removed. As the truncation threshold, either a fixed value or a variable threshold yielding a predetermined OI (oscillation index) is frequently employed. Each of these two thresholding methods has an advantage to the other either in accuracy or efficiency. In this paper, we propose a Monte Carlo simulation method to evaluate the accuracy of the two methods. An extension of the proposed method is presented as well to measure the effects of image smoothing on the accuracy of the thresholding methods. In this paper, after the simulation method is described, experimental results are presented using both simulated data and real CT images.

• Textile Coloration and Finishing
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• v.20 no.2
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• pp.19-28
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• 2008

The objective of this study was to apply the statistical technique known as design of experiments to optimize the % exhaustion variables for phthalocyanine dyeing of nylon fiber. In this study, a three-factor Central Composite Rotatable Design (CCRD) was used to establish the optimum conditions for the phthalocyanine reactive dyeing of nylon fiber. Temperature, pH and liquor ratio were considered as the variable of interest. Acidic solution with higher temperature and lower liquor ratio were found to be suitable conditions for higher % exhaustion. These three variables were used as independent variables, whose effects on % exhaustion were evaluated. Significant polynomial regression models describing the changes on % exhaustion and % fixation with respect to independent variables were established with coefficient of determination, R2, greater than 0.90. Close agreement between experimental and predicted yields was obtained. Optimum conditions were obtained using surface plots and Monte Carlo simulation techniques where maximum dyeing efficiency is achieved. The significant level of both the main effects and interaction was observed by analysis of variance (ANOVA) approach. Based on the statistical analysis, the results have provided much valuable information on the relationship between response variables and independent variables. This study demonstrates that the CCRD could be efficiently applied for the empirical modeling of % exhaustion and % fixation in dyeing. It also shows that it is an economical way of obtaining the maximum amount of information in a short period of time with least number of experiments.

• Journal of Advanced Navigation Technology
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• v.8 no.1
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• pp.26-37
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• 2004

Consistent and realistic error covariance information is important for position estimation, error analysis, fault detection, and integer ambiguity resolution for differential GNSS. In designing a position domain carrier-smoothed-code filter where incremental carrier phases are used for time-propagation, formulation of consistent error covariance information is not easy due to being bounded and temporal correlation of propagation noises. To provide consistent and correct error covariance information, this paper proposes two recursive filter algorithms based on carrier-smoothed-code techniques: (a) the stepwise optimal position projection filter and (b) the stepwise unbiased position projection filter. A Monte-Carlo simulation result shows that the proposed filter algorithms actually generate consistent error covariance information and the neglection of carrier phase noise induces optimistic error covariance information. It is also shown that the stepwise unbiased position projection filter is attractive since its performance is good and its computational burden is moderate.

• The Korean Journal of Applied Statistics
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• v.19 no.1
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• pp.97-110
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• 2006

Since it is well-established that even high quality data tend to contain outliers, one would expect fat? greater reliance on robust regression techniques than is actually observed. But most of all robust regression estimators suffers from the computational difficulties and the lower efficiency than the least squares under the normal error model. The weighted self-tuning estimator (WSTE) recently suggested by Lee (2004) has no more computational difficulty and it has the asymptotic normality and the high break-down point simultaneously. Although it has better properties than the other robust estimators, WSTE does not have full efficiency under the normal error model through the weighted least squares which is widely used. This paper introduces a new approach as called the reweighted WSTE (RWSTE), whose scale estimator is adaptively estimated by the self-tuning constant. A Monte Carlo study shows that new approach has better behavior than the general weighted least squares method under the normal model and the large data.

• Nuclear Engineering and Technology
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• v.52 no.3
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• pp.633-646
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• 2020

Imaging and scattering techniques using thermal neutrons allow to analyze complex specimens in scientific and industrial researches. Owing to this advantage, there have been a considerable demand for neutron facilities in the industrial sector. Among neutron sources, an accelerator driven compact neutron source is the only one that can satisfy the various requirements-construction budget, facility size, and required neutron flux-of industrial applications. In this paper, a target, moderator, and reflector (TMR) system for low-energy proton-accelerator driven compact thermal neutron source was designed via Monte Carlo simulations. For 10-30 MeV proton beams, the optimal conditions of the beryllium target were determined by considering the neutron yield and the blistering of the target. For a non-borated polyethylene moderator, the neutronic properties were verified based on its thickness. For a reflector, three candidates-light water, beryllium, and graphite-were considered as reflector materials, and the optimal conditions were identified. The results verified that the neutronic intensity varied in the order beryllium > light water > graphite, the compacter size in the order light water < beryllium < graphite and the shorter emission time in the order graphite < light water < beryllium. The performance of the designed TMR system was compared with that of existing facilities and were laid between performance of existing facilities.