• Nuclear Engineering and Technology
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• v.21 no.4
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• pp.245-258
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• 1989

A 69-group cross section library consisting of more than 130 materials was generated for thermal reactor applications using the NJOY nuclear data processing system and the recent version of evaluated nuclear data files available from IAEA Nuclear Data Section. The multigroup library was validated through the analysis of various criticality experiments and depletion results of PWR. When used with the WIMS-KAERI code, the average $K_{eff}$ obtained for 47 uranium-oxide and 41 uranium metal fueled critical configurations is 0.9997 with a standard deviation of 0.69 percent. The calculated burnup dependent isotopic inventories of uranium and plutonium generally show good agreement with measured values obtained from depleted PWR pins.s.

• Nuclear Engineering and Technology
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• v.50 no.1
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• pp.107-115
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• 2018

To ensure the structural integrity of nuclear power plants, it is essential to predict the lifetime of Alloy 182 weld, which is used for welding in nuclear reactors. The lifetime of Alloy 182 weld is directly related to the crack initiation time. Owing to the large time scatter in most crack initiation tests, a probabilistic model, such as the Weibull distribution, has mainly been adopted for prediction. However, since statistically more advanced methods than current typical methods may be applied, we suggest a statistical procedure for parameter estimation of the crack initiation time of Alloy 182 weld, considering right-censored data and the covariate effect. Furthermore, we suggest a procedure for uncertainty evaluation of the estimators based on the bootstrap method. The suggested statistical procedure can be applied not only to Alloy 182 weld but also to any material degradation data set including right-censored data with covariate effect.

• Nuclear Engineering and Technology
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• v.53 no.9
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• pp.2830-2838
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• 2021

This work deals with the assessment of the burnup capabilities of the Serpent Monte Carlo code to predict spent nuclear fuel (SNF) isotopic concentrations for low-enriched uranium (LEU) fuel at different burnup levels up to 47 MWd/kgU. The irradiation of six UO₂ experimental samples in three different VVER-1000 reactor units has been simulated and the predicted concentrations of actinides up to ²⁴⁴Cm have been compared with the corresponding measured values. The results show a global good agreement between calculated and experimental concentrations, in several cases within the margins of the nuclear data uncertainties and in a few cases even within the reported experimental uncertainties. The differences in the performances of the JEFF3.1.1, ENDF/B-VII.1 and ENDF/B-VIII.0 nuclear data libraries (NDLs) have also been assessed and the use of the newly released ENDF/B-VIII.0 library has shown an increased accuracy in the prediction of the C/E's for some of the actinides considered, particularly for the plutonium isotopes. This work represents a step forward towards the validation of advanced simulation tools against post irradiation experimental data and the obtained results provide an evidence of the capabilities of the Serpent Monte-Carlo code with the associated modern NDLs to accurately compute SNF nuclide inventory concentrations for VVER-1000 type reactors.

• Nuclear Engineering and Technology
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• v.54 no.2
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• pp.644-652
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• 2022

During the pyroprocessing operation, various signals can be collected by process monitoring (PM). These signals are utilized to diagnose process states. In this study, feasibility of using PM for nuclear safeguards of electrorefining operation was examined based on the use of machine learning for detecting off-normal operations. The off-normal operation, in this study, is defined as co-deposition of key elements through reduction on cathode. The monitored process signal selected for PM was cathode potential. The necessary data were produced through electrodeposition experiments in a laboratory molten salt system. Model-based cathodic surface area data were also generated and used to support model development. Computer models for classification were developed using a series of recurrent neural network architectures. The concept of transfer learning was also employed by combining pre-training and fine-tuning to minimize data requirement for training. The resulting models were found to classify the normal and the off-normal operation states with a 95% accuracy. With the availability of more process data, the approach is expected to have higher reliability.

• Nuclear Engineering and Technology
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• v.56 no.8
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• pp.2999-3029
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• 2024

To improve the predictive capability of a nuclear thermal hydraulic safety analysis code by developing a better constitutive equation for individual phenomenon has been the general research direction until now. This paper proposes a new method to directly use complex experimental data obtained from integral effect test (IET) to improve constitutive models holistically and simultaneously. The method relies on the sensitivity of a simulation result of IET data to the multiple constitutive equations utilized during the simulation, and the sensitivity of individual model determines the direction of modification for the constitutive model. To develop a robust and generalized method, a clustering algorithm using an artificial neural network, sample space size determination using non-parametric statistics, and sampling method of Latin hypercube sampling are used in a combined manner. The value of the proposed methodology is demonstrated by applying the method to the ATLAS DSP-05 IET experiment. A sensitivity of each observation parameter to the constitutive models is analyzed. The new methodology suggested in the study can be used to improve the code prediction results of complex IET data by identifying the direction for constitutive equations to be modified.

• Nuclear Engineering and Technology
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• v.56 no.2
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• pp.463-471
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• 2024

Average and local convective heat transfer coefficients of nitrogen are measured experimentally in an electrically heated circular tube for a range of Reynolds number from 1.08 × 10⁴ to 3.60 × 10⁴, and wall-to-bulk temperature ratio from 1.01 to 1.77. The exit Mach number is up to 0.17, and the heat flux is up to 46 kW·m^-2. The molybdenum test section has a 62 diameters heated section with an inside diameter of 5 mm and a 30 diameters entrance section to ensure the fully-developed flow. Uncertainty of Nusselt number is less than 1.6 % in this study. The results indicate that the average heat transfer correlations evaluated by both the bulk and the modified film Reynolds numbers agree well with the experimental data. The local heat transfer results based on bulk properties are compared with previous empirical correlations. New prediction correlations are recommended which are significantly affected by the property variation and heated length. The comparison between the proposed correlations and experimental points shows that 88 % of experimental data fall into an error of 10 %, and almost all data are within an error of 20 %.

• Proceedings of the Korean Nuclear Society Conference
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• 2001.05a
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• pp.215-215
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• 2001

• Proceedings of the Korean Nuclear Society Conference
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• 1999.05a
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• pp.455-455
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• 1999

• Proceedings of the Korean Nuclear Society Conference
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• 2004.05a
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• pp.377.1-377.1
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• 2004

• Proceedings of the Korean Nuclear Society Conference
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• 2004.05a
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• pp.180.1-180.1
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• 2004