• Journal of Digital Convergence
• /
• v.20 no.4
• /
• pp.529-539
• /
• 2022

This study analyzed the index change in efficiency and productivity for the tax reorganization project of the regional headquarters of Korea Asset Management Corporation using panel data for 3 years from 2017 to 2019 using the DEA-Malmquist analysis model. According to the DEA analysis result, the average of the efficiency by the CCR model of the regional headquarters tax reorganization project of the Korea Asset Management Corporation was 0.671 in 2017, 0.772 in 2018, and 0.699 in 2019, and the average of the efficiency by the BCC model was 0.798 in 2017, 0.851 in 2018 and 0.771 in 2019. As a result of analyzing the Malmquist productivity index, the time series average productivity index MPI increased by 4.5%. These results appear to be attributable to the increase in technological efficiency, technological change, and scale-efficiency change rather than the decrease in net efficiency change. Looking at the change in MPI by year, it decreased by 14.6% in 2017-2018, but increased significantly to 27.8% in 2018-2019. Through the results of DEA analysis of specific tax projects of public corporations, each regional headquarters of Korea Asset Management Corporation will be able to contribute to reinforcing business capabilities through mutual benchmarking.

• Nuclear Engineering and Technology
• /
• v.53 no.1
• /
• pp.61-68
• /
• 2021

Experiments of vertically upward steam-water two-phase flow have been carried out in single-side heated narrow rectangular channel with a gap of 3 mm. Flow patterns were identified and classified through visualization directly. Slug flow was only observed at 0.2 MPa but replaced by block-bubble flow at 1.0 MPa. Flow pattern maps at the pressure of 0.2 MPa and 1.0 MPa were plotted and the difference was analyzed. The experimental data has been compared with other flow pattern maps and transition criteria. The results show reasonable agreement with Hosler's, while a wide discrepancy is observed when compared with air-water two-phase experimental data. Current criteria developed based on air-water experiments poorly predict bubble-slug flow transition due to the different formation and growth of bubbles. This work is significant for researches on heat transfer, bubble dynamics and flow instability.

• Journal of the Society of Disaster Information
• /
• v.19 no.1
• /
• pp.18-30
• /
• 2023

Purpose: This study is to contribute to the development of monitoring technology through the increase of confidence in construction monitoring by deriving the analysis of construction monitoring cost and improvement measures of railway tunnel construction in Seoul. Method: It presents the status on design and contract of construction monitoring cost, status on application construction monitoring cost and its analysis, analysis on safety management cost and quality management cost, expansion of application of the price calculation standard for monitoring management services to improve this, and monitoring for direct order of ordering organization. Results: If the monitoring management service that was meanwhile ordered as included in the construction work is performed by the directly selected company of ordering organization through the preliminary screening for bidding qualification, then the improvement of monitoring quality and the accurate monitoring data can be secured. Conclusion: For the price calculation standard for monitoring management service, the application of actual cost addition method under the Engineering Promotion Act and the calculation standard of monitoring management cost for standard estimation for ground survey should be extended through the direct order of ordering organization, not the method to be included in the net construction cost where it is performed by a subcontractor via contractor.

• Journal of the Society of Disaster Information
• /
• v.18 no.4
• /
• pp.899-907
• /
• 2022

Purpose: Although many studies on seismic fragility analysis of general bridges have been conducted using machine learning methods, studies on curved bridge structures are insignificant. Therefore, the purpose of this study is to analyze the seismic fragility of bridges with I-shaped curved girders based on the machine learning method considering the material property and geometric uncertainties. Method: Material properties and pier height were considered as uncertainty parameters. Parameters were sampled using the Latin hypercube technique and time history analysis was performed considering the seismic uncertainty. Machine learning data was created by applying artificial neural network and response surface analysis method to the original data. Finally, earthquake fragility analysis was performed using original data and learning data. Result: Parameters were sampled using the Latin hypercube technique, and a total of 160 time history analyzes were performed considering the uncertainty of the earthquake. The analysis result and the predicted value obtained through machine learning were compared, and the coefficient of determination was compared to compare the similarity between the two values. The coefficient of determination of the response surface method was 0.737, which was relatively similar to the observed value. The seismic fragility curve also showed that the predicted value through the response surface method was similar to the observed value. Conclusion: In this study, when the observed value through the finite element analysis and the predicted value through the machine learning method were compared, it was found that the response surface method predicted a result similar to the observed value. However, both machine learning methods were found to underestimate the observed values.

• Nuclear Engineering and Technology
• /
• v.55 no.8
• /
• pp.2773-2784
• /
• 2023

It is essential to evaluate the blasting-enhanced permeability (BEP) feasibility of a low-permeability sandstone-type uranium deposit. In this work, the mineral composition, reservoir physical properties and rock mechanical properties of samples from sandstone-type uranium deposits were first measured. Then, the reformability evaluation method was established by the analytic hierarchy process-entropy weight method (AHP-EWM) and the fuzzy mathematics method. Finally, evaluation results were verified by the split Hopkinson Pressure Bar (SHPB) experiment and permeability test. Results show that medium sandstone, argillaceous sandstone and siltstone exhibit excellent reformability, followed by coarse sandstone and fine sandstone, while the reformability of sandy mudstone is poor and is not able to accept BEP reservoir stimulation. The permeability improvement and the distribution of damage fractures before and after the SHPB experiment confirm the correctness of evaluation results. This research provides a reformability evaluation method for the BEP of the low-permeability sandstone-type uranium deposit, which contributes to the selection of the appropriate regional and stratigraphic horizon of the BEP and the enhanced ISL of the low-permeability sandstone-type uranium deposit.

• Nuclear Engineering and Technology
• /
• v.54 no.12
• /
• pp.4660-4670
• /
• 2022

Hydroxyurea (HU) is a novel salt-free reductant used potentially for the separation of U/Pu in the advanced PUREX process. In this work, the radiation stability of HU were systematically investigated in solution by examining the effects of the type of rays (α, β, and γ irradiations), the absorbed dose (10-50 kGy), and the HNO₃ concentration (0-3 mol L^-1). The influence degree on HU radiolysis rates followed the order of the absorbed dose > the ray type > the HNO₃ concentration, but the latter two had moderate effects on HU radiolysis products where NH₄⁺ and NO₂^- were found to be the most abundant ones, suggesting that the differences of α, β, and γ rays should be considered in the study of irradiation effects. The radiolysis mechanism was explored using density functional theory (DFT) calculations, and it proposed the dominant radiolysis paths of HU, indicating that the radiolysis of HU was mainly a free radical reaction among ·H, e_aq^-, H₂O, intermediates, and the radiolytic free radical fragments of HU. The results reported here provide valuable insights into the mechanistic understanding of HU radiolysis under α, β, and γ irradiations and reliable data support for the application of HU in the reprocessing of spent fuel.

• Nuclear Engineering and Technology
• /
• v.55 no.1
• /
• pp.339-352
• /
• 2023

Prediction of the time-related traits of pebble flow inside pebble-bed HTGRs is of great significance for reactor operation and design. In this work, an image-driven approach with the aid of a convolutional neural network (CNN) is proposed to predict the remaining time of initially loaded pebbles and the time interval of paired flow images of the pebble bed. Two types of strategies are put forward: one is adding FC layers to the classic classification CNN models and using regression training, and the other is CNN-based deep expectation (DEX) by regarding the time prediction as a deep classification task followed by softmax expected value refinements. The current dataset is obtained from the discrete element method (DEM) simulations. Results show that the CNN-aided models generally make satisfactory predictions on the remaining time with the determination coefficient larger than 0.99. Among these models, the VGG19+DEX performs the best and its CumScore (proportion of test set with prediction error within 0.5s) can reach 0.939. Besides, the remaining time of additional test sets and new cases can also be well predicted, indicating good generalization ability of the model. In the task of predicting the time interval of image pairs, the VGG19+DEX model has also generated satisfactory results. Particularly, the trained model, with promising generalization ability, has demonstrated great potential in accurately and instantaneously predicting the traits of interest, without the need for additional computational intensive DEM simulations. Nevertheless, the issues of data diversity and model optimization need to be improved to achieve the full potential of the CNN-aided prediction tool.

• Nuclear Engineering and Technology
• /
• v.55 no.3
• /
• pp.1061-1070
• /
• 2023

Over the last few years, lead-free inorganic metal perovskites have gained impressive ground in empowering satellites in space exploration owing to their material stability and performance evolution under extreme space environments. The present work has examined the versatility of eight such perovskites as space radiation shielding materials by computing their photon, charged particles and neutron interaction parameters. Photon interaction parameters were calculated for a wide energy range using PAGEX software. The ranges of heavy charged particles (H, He, C, N, O, Ne, Mg, Si and Fe ions) in these perovskites were estimated using SRIM software in the energy range 1 keV-10 GeV, and that of electrons was computed using ESTAR NIST software in the energy range 0.01 MeV-1 GeV. Further, the macroscopic fast neutron removal cross-sections were also calculated to estimate the neutron shielding efficiencies. The examined shielding parameters of the perovskites varied depending on the radiation type and energy. Among the selected perovskites, Cs₂TiI₆ and Ba₂AgIO₆ displayed superior photon attenuation properties. A 3.5 cm thick Ba₂AgIO₆-based shield could reduce the incident radiation intensity to half its initial value, a thickness even lesser than that of Pb-glass. Besides, CsSnBr₃ and La_0.8Ca_0.2Ni_0.5Ti_0.5O₃ displayed the highest and lowest range values, respectively, for all heavy charged particles. Ba₂AgIO₆ showed electron stopping power (on par with Kovar) better than that of other examined materials. Interestingly, La_0.8Ca_0.2Ni_0.5Ti_0.5O₃ demonstrated neutron removal cross-section values greater than that of standard neutron shielding materials - aluminium and polyethylene. On the whole, the present study not only demonstrates the employment prospects of eco-friendly perovskites for shielding space radiations but also suggests future prospects for research in this direction.

• Nuclear Engineering and Technology
• /
• v.55 no.5
• /
• pp.1593-1603
• /
• 2023

In deterministic and Monte Carlo transport codes, b-delayed emission is included using a group structure where all of the precursors are grouped together in 6 groups or families, but given the increase in computational power, nowadays there is no reason to keep this structure. Furthermore, there have been recent efforts to compile and evaluate all the available b-delayed neutron emission data and to measure new and improved data on individual precursors. In order to be able to perform a transient Monte Carlo simulation, data from individual precursors needs to be implemented in a transport code. This work is the first step towards the development of a tool to explore the effect of individual precursors in a fissile system. In concrete, individual precursor data is included by expanding the capabilities of the open source Monte Carlo code OpenMC. In the modified code - named Time Dependent OpenMC or OpenMC(TD)- time dependency related to β-delayed neutron emission was handled by using forced decay of precursors and combing of the particle population. The data for continuous energy neutron cross-sections was taken from JEFF-3.1.1 library. Regarding the data needed to include the individual precursors, cumulative yields were taken from JEFF-3.1.1 and delayed neutron emission probabilities and delayed neutron spectra were taken from ENDF-B/VIII.0. OpenMC(TD) was tested in a monoenergetic system, an energy dependent unmoderated system where the precursors were taken individually or in a group structure, and in a light-water moderated energy dependent system, using 6-groups, 50 and 40 individual precursors. Neutron flux as a function of time was obtained for each of the systems studied. These results show the potential of OpenMC(TD) as a tool to study the impact of individual precursor data on fissile systems, thus motivating further research to simulate more complex fissile systems.

• Nuclear Engineering and Technology
• /
• v.55 no.5
• /
• pp.1802-1813
• /
• 2023

Conjugate heat transfer between liquid metal and solid is a common phenomenon in a liquid-metal-cooled fast reactor's fuel assembly and heat exchanger, dramatically affecting the reactor's safety and economy. Therefore, comprehensively studying the sophisticated conjugate heat transfer in a liquid-metal-cooled fast reactor is profound. However, it has been evidenced that the traditional Simple Gradient Diffusion Hypothesis (SGDH), assuming a constant turbulent Prandtl number (Pr_t,, usually 0.85 - 1.0), is inappropriate in the Computational Fluid Dynamics (CFD) simulations of liquid metal. In recent decades, numerous studies have been performed on the four-equation model, which is expected to improve the precision of liquid metal's CFD simulations but has not been introduced into the conjugate heat transfer calculation between liquid metal and solid. Consequently, a four-equation model, consisting of the Abe k - ε turbulence model and the Manservisi k_𝜃 - ε_𝜃 heat transfer model, is applied to study the conjugate heat transfer concerning liquid metal in the present work. To verify the numerical validity of the four-equation model used in the conjugate heat transfer simulations, we reproduce Johnson's experiments of the liquid lead-bismuth-cooled turbulent pipe flow using the four-equation model and the traditional SGDH model. The simulation results obtained with different models are compared with the available experimental data, revealing that the relative errors of the local Nusselt number and mean heat transfer coefficient obtained with the four-equation model are considerably reduced compared with the SGDH model. Then, the thermal-hydraulic characteristics of liquid metal turbulent pipe flow obtained with the four-equation model are analyzed. Moreover, the impact of the turbulence model used in the four-equation model on overall simulation performance is investigated. At last, the effectiveness of the four-equation model in the CFD simulations of liquid sodium conjugate heat transfer is assessed. This paper mainly proves that it is feasible to use the four-equation model in the study of liquid metal conjugate heat transfer and provides a reference for the research of conjugate heat transfer in a liquid-metal-cooled fast reactor.