• Nuclear Engineering and Technology
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• v.36 no.3
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• pp.248-262
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• 2004

Turbulence models are separately assessed for a three dimensional thermal-hydraulic analysis of the integral reactor SMART. Seven models (mixing length, k-l, standard $k-{\epsilon},\;k-{\epsilon}-f{\mu},\;k-{\epsilon}-v2$, RRSM, and ERRSM) are investigated for flat plate channel flow, rotating channel flow, and square sectioned U-bend duct flow. The results of these models are compared to the DNS data and experiment data. The results are assessed in terms of many aspects such as economical efficiency, accuracy, theorization, and applicability. The standard $k-{\epsilon}$ model (high Reynolds model), the $k-{\epsilon}-v2$ model, and the ERRSM (low Reynolds models) are selected from the assessment results. The standard $k-{\epsilon}$ model using small grid numbers predicts the channel flow with higher accuracy in comparison with the other eddy viscosity models in the logarithmic layer. The elliptic-relaxation type models, $k-{\epsilon}-v2$, and ERRSM have the advantage of application to complex geometries and show good prediction for near wall flows.

• Nuclear Engineering and Technology
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• v.53 no.12
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• pp.4060-4066
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• 2021

Flow-accelerated corrosion (FAC) of carbon steel piping is a significant problem in nuclear power plants. The basic process of FAC is currently understood relatively well; however, the accuracy of prediction models of the wall-thinning rate under an FAC environment is not reliable. Herein, we propose a methodology to construct pipe wall-thinning rate prediction models using artificial neural networks and a convolutional neural network, which is confined to a straight pipe without geometric changes. Furthermore, a methodology to generate training data is proposed to efficiently train the neural network for the development of a machine learning-based FAC prediction model. Consequently, it is concluded that machine learning can be used to construct pipe wall thinning rate prediction models and optimize the number of training datasets for training the machine learning algorithm. The proposed methodology can be applied to efficiently generate a large dataset from an FAC test to develop a wall thinning rate prediction model for a real situation.

• Nuclear Engineering and Technology
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• v.39 no.2
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• pp.129-132
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• 2007

It is generally known that software reliability growth models such as the Jelinski-Moranda model and the Goel-Okumoto's non-homogeneous Poisson process (NHPP) model cannot be applied to safety-critical software due to a lack of software failure data. In this paper, by applying two of the most widely known software reliability growth models to sample software failure data, we demonstrate the possibility of using the software reliability growth models to prove the high reliability of safety-critical software. The high sensitivity of a piece of software's reliability to software failure data, as well as a lack of sufficient software failure data, is also identified as a possible limitation when applying the software reliability growth models to safety-critical software.

• Journal of the Korea Society of Computer and Information
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• v.27 no.5
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• pp.101-107
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• 2022

Modeling and simulation is a technique used for operational verification, performance analysis, operational optimization, and prediction of target systems. Discrete Event System Specification (DEVS) of this representative technology defines models with a strict formalism and stratifies the structures between the models. When the atomic DEVS models operate with an intention different the target system, the simulation may lead to erroneous decision-making. However, most DEVS systems have the exclusion of the model test or provision of the manual test, so developers spend a lot of time verifying the atomic models. In this paper, we propose a script-based automated test system for accurate and fast validation of atomic models in Python-based DEVS. The proposed system uses both the existing method of manual testing and the new method of the script-based testing. As Experimental results in our system, the script-based test method was executed within 24 millisecond when the script was executed 10 times consecutively. Thus, the proposed system guarantees a fast verification time of the atomic models in our script-based test and improves the reusability of the test script.

• Journal of Energy Engineering
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• v.13 no.3
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• pp.181-190
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• 2004

Computational models for analyzing the in-reactor behavior of metallic fuel pins under transient conditions in liquid-metal reactors are developed and implemented in the TRAMAC (TRAnsient thermo-Mechanical Analysis Code) for a metal fuel rod under transient operation conditions. Not only the basic models for a fuel rod performance but also some sub-models used for transient condition are installed in TRAMAC. Among the models, a fission gas release model, which takes the multi-bubble size distribution into account to characterize the lenticular bubble shape and the saturation condition on the grain boundary and the cladding deformation model have been developed based mainly on the existing models in the MAC-SIS code. Finally, cladding strains are calculated from the amount of thermal creep, irradiation creep, and irradiation swelling. The cladding strain model in TRAMAC predicts well the absolute magnitudes and gen-eral trends of their predictions compared with those of experimental data. TRAMAC results for the FH-1,2,6 pins are more conservative than experimental data and relatively reasonable than those of FPIN2 code. From the calculation results of TRAMAC, it is apparent that the code is capable of predicting fission gas release, and cladding deformation for LMR metal fuel finder transient operation conditions. The results show that in general, the predictions of TRAMAC agree well with the available irradiation data.

• Proceedings of the Korean Nuclear Society Conference
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• 1998.10a
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• pp.162-162
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• 1998

• Nuclear Engineering and Technology
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• v.41 no.9
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• pp.1143-1156
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• 2009

The SPACE code that is based on a multi-dimensional two-fluid, three-field model is under development for licensing purposes of pressurized water reactors in Korea. Among the participating research and industrial organizations, KAERI is in charge of developing the physical models and correlation packages for the constitutive equations. This paper introduces a developed wall-to-fluid heat transfer package for the SPACE code. The wall-to-fluid heat transfer package consists of twelve heat transfer subregions. For each sub-region, the models in the existing safety analysis codes and the leading models in literature have been peer reviewed in order to determine the best models which can easily be applicable to the SPACE code. Hence a wall-to-fluid heat transfer region selection map has been developed according to the non-condensable gas quality, void fraction, degree of subcooling, and wall temperature. Furthermore, a partitioning methodology which can take into account the split heat flux to the continuous liquid, entrained droplet, and vapor fields is proposed to comply fully with the three-field formulation of the SPACE code. The developed wall-to-fluid heat transfer package has been pre-tested by varying the independent parameters within the application range of the selected correlations. The smoothness between two adjacent heat transfer regimes has also been investigated. More detailed verification work on the developed wall-to-fluid heat transfer package will be carried out when the coupling of a hydraulic solver with the constitutive equations is brought to completion.

• Proceedings of the Korean Nuclear Society Conference
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• 2005.05a
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• pp.493-494
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• 2005

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2018.11a
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• pp.231-232
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• 2018

• Nuclear Engineering and Technology
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• v.37 no.6
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• pp.587-594
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• 2005

In an effort to develop a thermal-hydraulic (TH) safety analysis code for Gas-cooled Reactors (GCRs), the MARS code, which was primarily developed for TH analysis of water reactor systems, has been extended here for application to GCRs. The modeling requirements of the system code were derived from a review of major processes and phenomena that are expected to occur during normal and accident conditions of GCRs. Models fur code improvement were then identified through a review of existing MARS code capability. Among these, the following priority models necessary fur the analysis of limiting high and low pressure conduction cooling events were evaluated and incorporated in MARS-GCR/V1 : 1) Helium (He) and Carbon Dioxide ($CO_2$) as main system fluids, 2) gas convection heat transfer, 3) radiation heat transfer, and 4) contact heat transfer models. Each model has been assessed using various conceptual problems for code-to-code benchmarks and it was demonstrated that MARS-GCR/V1 is capable of capturing the relevant phenomena. This paper describes the models implemented in MARS-GCR/V1 and their verification and validation results.