• Transactions of the Korean Society of Mechanical Engineers B
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• v.31 no.8
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• pp.663-671
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• 2007

In this work, shape optimization of a wire-wrapped fuel assembly in a liquid metal reactor has been carried out by combining a three-dimensional Reynolds-averaged Navier-Stokes analysis with the radial basis neural network method, a well known surrogate modeling technique for optimization. Sequential Quadratic Programming is used to search the optimal point from the constructed surrogate. Two geometric design variables are selected for the optimization and design space is sampled using Latin Hypercube Sampling. The optimization problem has been defined as a maximization of the objective function, which is as a linear combination of heat transfer and friction loss related terms with a weighing factor. The objective function value is more sensitive to the ratio of the wire spacer diameter to the fuel rod diameter than to the ratio of the wire wrap pitch to the fuel rod diameter. The optimal values of the design variables are obtained by varying the weighting factor.

• Earthquakes and Structures
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• v.14 no.5
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• pp.425-436
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• 2018

The design of seismically isolated structures considering the stochastic nature of excitations, base isolators' design parameters, and superstructure properties requires robust reliability analysis methods to calculate the failure probability of the entire system. Here, by applying artificial neural networks, we proposed a robust technique to accelerate the estimation of failure probability of equipped isolated structures. A three-story isolated building with susceptible facilities is considered as the analytical model to evaluate our technique. First, we employed a sensitivity analysis method to identify the critical sources of uncertainty. Next, we calculated the probability of failure for a particular set of random variables, performing Monte Carlo simulations based on the dynamic nonlinear time-history analysis. Finally, using a set of designed neural networks as a surrogate model for the structural analysis, we assessed once again the probability of the failure. Comparing the obtained results demonstrates that the surrogate model can attain precise estimations of the probability of failure. Moreover, our proposed approach significantly increases the computational efficiency corresponding to the dynamic time-history analysis of the structure.

• Analytical Science and Technology
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• v.13 no.6
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• pp.789-801
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• 2000

This analysis was conducted for PCDDs/PCDFs in sediment by isotope dilution HRGC/HRMS method. From the result, the mean recovery of surrogate standard was in the range of 70.1-80.8%. Among the distribution of 2, 3, 7, 8-substituted isomers, the concentration of OCDD represented almost 40.6-78.5% of total concentration and that of OCDF showed 6.6-14.7% and 1, 2, 3, 4, 6, 7, 8-HpCDD showed 5.1-7.7%. The portion of PCDDs represented 62.4-86.9% of total PCDDs/PCDFs. In the TEQ concentration 1, 2, 3, 4, 7, 8-PeCDF concentration represented 22.7-35.6 % of total TEQ concentration.

• Nuclear Engineering and Technology
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• v.52 no.1
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• pp.109-114
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• 2020

This work presents the results of laboratory scale tests of the CARBOFLUOREX (CARBOnate FLUORide EXtraction) process - a novel technology for the recovery of U and Pu from the solid fluorides residue (fluorination ash) of Fluoride Volatility Method (FVM) reprocessing of spent nuclear fuel (SNF). To study the oxidative leaching of U from the fluorination ash (FA) by Na₂CO₃ or Na₂CO₃-H₂O₂ solutions followed by solvent extraction by methyltrioctylammonium carbonate in toluene and purification of U from the fission products (FPs) impurities we used a surrogate of FA consisting of UF₄ or UO₂F₂, and FPs fluorides with stable isotopes of Ce, Zr, Sr, Ba, Cs, Fe, Cr, Ni, La, Nd, Pr, Sm. Purification factors of U from impurities at the solvent extraction refining stage reached the values of 10⁴-10⁵, and up to 10⁶ upon the completion of the processing cycle. Obtained results showed a high efficiency of the CARBOFLUOREX process for recovery and separating of U from FPs contained in FA, which allows completing of the FVM cycle with recovery of U and Pu from hardly processed FA.

• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.790-802
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• 2022

Large-scale reactor simulation often requires the use of Monte Carlo calculation techniques to estimate important reactor parameters. One drawback of these Monte Carlo calculation techniques is they inevitably result in some uncertainty in calculated quantities. The present study includes parametric uncertainty quantification (UQ) and sensitivity analysis (SA) on the Advanced Test Reactor Critical (ATRC) facility housed at Idaho National Laboratory (INL) and addresses some complications due to Monte Carlo uncertainty when performing these analyses. This approach for UQ/SA includes consideration of Monte Carlo code uncertainty in computed sensitivities, consideration of uncertainty from directly measured parameters and a comparison of results obtained from brute-force Monte Carlo UQ versus UQ obtained from a surrogate model. These methodologies are applied to the uncertainty and sensitivity of k_eff for two sets of uncertain parameters involving fuel plate geometry and fuel plate composition. Results indicate that the less computationally-expensive method for uncertainty quantification involving a linear surrogate model provides accurate estimations for k_eff uncertainty and the Monte Carlo uncertainty in calculated k_eff values can have a large effect on computed linear model parameters for parameters with low influence on k_eff.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.56 no.4
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• pp.428-437
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• 2023

A simultaneous analytical method was developed and validated for the analysis of prohibited fluoroquinolone (FQ) antibiotics including norfloxacin, ofloxacin, and pefloxacin, released by aquaculture in seawater and effluents. The samples were filtered, and extracts were obtained using a solid phase extraction cartridge with methanol (MeOH). The extracts were concentrated, and analyzed using ultra-performance liquid chromatography-tandem mass spectrometry. Two different columns and four different mobile phases were compared to achieve optimal separation and sensitivity for target compounds. Typical validation parameters including linearity, recovery of surrogate standard, instrument detection limit (IDL), limit of quantification (LOQ), and method detection limit (MDL) were evaluated. The linearity of calibration curves was over 0.999. Recoveries of surrogate ranged from 87.6% to 113%. The LOQ of target compounds was approximately 3-8 times lower than those reported in previous studies. The IDL and MDL were 0.06-0.57 and 0.06-0.37 ng/L, respectively. Seven effluent samples collected from an aquaculture located in Jeju were analyzed; however, not all target compounds were detected in the samples, suggesting that the banned antibiotics were not used. Overall, this established method was able to simultaneously analyze the three FQ antibiotics, and may be useful for monitoring prohibited antibiotics in the fishery industry.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2017.10a
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• pp.207-208
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• 2017

• Korean Journal of Fisheries and Aquatic Sciences
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• v.42 no.3
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• pp.238-242
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• 2009

Recently coastal seawater has been contaminated by enteric viruses such as the norovirus via untreated groundwater globally. Accordingly, the consumption of molluscan shellfish from seawater that has been contaminated with fecal material has become an important issues. The levels of enteric viruses in seawater are low and recovery and concentration of the virus from large volumes of water is difficult. We compared the effectiveness of two representative method of concentrating virus using negatively and positively charged filters. The mean retention of seeded FCV by HAMF and NCCF was 48% and 78%, respectively. Overall, the recovery of NCCF was 43.3$\pm$11% better than that of HAMF. However, the eluate obtained by using beef extract solution in the NCCF procedure caused an inhibitory effect on the RT-PCR; therefore, it was necessary to employ a PCR inhibitor removal procedure. The HAMF eluate contained no PCR inhibitors, but HAMF was not an effective method of concentrating the virus from large volumes of natural seawater due to clogging.

• Transactions of the Korean Society of Automotive Engineers
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• v.16 no.6
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• pp.74-80
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• 2008

A combustion of CAI engine is purely dominated by fuel chemical reactions. In order to simulate the combustion of CAI engine, it should be considered the effect of fuel components and chemical kinetics. So it needs enormous computational power. To overcome this problem reduced problem of needing massive computational power, chemical kinetic mechanism and multi-zone method is proposed here in this paper. A reduced chemical kinetic mechanism for a gasoline surrogate was used in this study for a CAI combustion. This gasoline surrogate was modeled as a blend of iso-octane, n-heptane, and toluene. For the analysis of CAI combustion, a multi-zone method as combustion model for a CAI engine was developed and incorporated into the computational fluid dynamics code, STAR-CD, for computing efficiency. This coupled multi-zone model can calculate 3 dimensional computational fluid dynamics and multi-zoned chemical reaction simultaneously in one time step. In other words, every computational cell interacts with the adjacent cells during the chemical reaction process. It can enhance the reality of multi-zone model. A greatly time-saving and yet still relatively accurate CAI combustion simulation model based on the above mentioned two efficient methodologies, is thus proposed.

• Structural Engineering and Mechanics
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• v.83 no.3
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• pp.293-304
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• 2022

In this work, a novel reliability approach for combined high and low cycle fatigue (CCF) estimation is developed by combining active learning strategy with least squares support vector machines (LS-SVM) (named as ALS-SVM) surrogate model to address the multi-resources uncertainties, including working loads, material properties and model itself. Initially, a new active learner function combining LS-SVM approach with Monte Carlo simulation (MCS) is presented to improve computational efficiency with fewer calls to the performance function. To consider the uncertainty of surrogate model at candidate sample points, the learning function employs k-fold cross validation method and introduces the predicted variance to sequentially select sampling. Following that, low cycle fatigue (LCF) loads and high cycle fatigue (HCF) loads are firstly estimated based on the training samples extracted from finite element (FE) simulations, and their simulated responses together with the sample points of model parameters in Coffin-Manson formula are selected as the MC samples to establish ALS-SVM model. In this analysis, the MC samples are substituted to predict the CCF reliability of turbine blades by using the built ALS-SVM model. Through the comparison of the two approaches, it is indicated that the reliability model by linear cumulative damage rule provides a non-conservative result compared with that by the proposed one. In addition, the results demonstrate that ALS-SVM is an effective analysis method holding high computational efficiency with small training samples to gain accurate fatigue reliability.