The phenomenon of fretting wear due to the flow-induced vibration in steam generator (SG) tube is a significant degradation mechanism in nuclear power plants. Fretting wear in SG tube is primarily attributed to the friction and impact forces between the SG tube and the tube support structures, experienced during nuclear power plants operation. While the Archard model has generally been used for the prediction of fretting wear in SG tube, it is limited by its linear nature. In this study, we introduced an "Impact Shear Work-rate" (ISW) model, which takes into account the combined effects of impact and sliding. The ISW model was evaluated using existing experimental data on fretting wear in SG tube and was compared against the Archard model. The prediction results using the ISW model were more accurate than those using the Archard model, particularly for impact forces.

The paper presents the results investigating the effect of aircraft engine impact location on the intended function evaluation results of spent nuclear fuel transport cask. As a result of the investigation, it is found that the structural integrity is maintained as the maximum accumulated equivalent plastic strain is below the acceptable criterion regardless of the collision location. It is identified that when the aircraft engine collided with the upper part of the transport cask without considering impact limiter the containment performance is weakened compared to when the aircraft engine collided with the central part.

For three-dimensional finite element welding residual stress simulation, several methods are available. Two widely used methods are the moving heat source model using heat flux and the temperature boundary condition model using the temperature profile of the welded beads. However, each model has pros and cons in terms of calculation times and difficulties in determining welding parameters. In this paper, a new method using the moving temperature profile model is proposed to perform efficiently 3-D FE welding residual stress analysis for large structures. Comparison with existing experimental residual stress measurement data of two-pass welding pipe and SNL(Sandia National Laboratories) mock-up canister shows the accuracy and efficiency of the proposed method.

As temporary storage facilities for spent nuclear fuels in domestic nuclear power plants are expected to be saturated, external intermediate storage facilities would be required in the future. Spent nuclear fuels are stored in metal canisters and then placed in a dry environment within concrete or metal casing for operation. In the United States, the dry storage method for spent nuclear fuels has been operated for an extended period. Based on the corrosion experiences of dry storage canisters in chloride environments, numerous studies have been conducted to reduce corrosion in welds. With the construction of intermediate storage facilities in Korea for spent nuclear fuels expected near coastal areas adjacent to nuclear power plants, there is a need for research on the corrosion occurrence of welds and mitigation methods for canisters in chloride environments. In this paper, we measured and compared the residual stresses in the Heat-Affected Zones (HAZ) after electron beam welding (EBW) and gas tungsten arc welding (GTAW) processes for candidate materials such as 304L, 316L, and duplex stainless steel(DSS). We investigated the possibility of microstructure control through the application of surface modification processes using friction stir processing (FSP). Corrosion tests on each welded specimen revealed a higher corrosion rate in EBW welds compared to GTAW. Furthermore, it was confirmed that corrosion resistance improved due to phase refinement and redistribution of precipitates when FSP was applied.

In this study, a deep learning algorithm was used to diagnose electric potential signals obtained through CIPS and DCVG, used indirect inspection methods to confirm the soundness of buried pipes. The deep learning algorithm consisted of CNN(Convolutional Neural Network) model for diagnosing the electric potential signal and Grad CAM(Gradient-weighted Class Activation Mapping) for showing the flaw prediction point. The CNN model for diagnosing electric potential signals classifies input data as normal/abnormal according to the presence or absence of flaw in the buried pipe, and for abnormal data, Grad CAM generates a heat map that visualizes the flaw prediction part of the buried pipe. The CIPS/DCVG signal and piping layout obtained from the 3D finite element model were used as input data for learning the CNN. The trained CNN classified the normal/abnormal data with 93% accuracy, and the Grad-CAM predicted flaws point with an average error of 2m. As a result, it confirmed that the electric potential signal of buried pipe can be diagnosed using a CNN-based deep learning algorithm.

A Chloride-induced stress corrosion cracking (CISCC) of austenite stainless steel in dry cask storage system (DCSS) can occur with extending service time than originally designed. Cold spray coating (CSC) not only form a very dense microstructure that can protect from corrosive environments, but also can generate compressive stress on the surface. This characteristic of CSC process is very helpful to increase the resistance for CISCC. CSC with several powders, such as 304L, 316L and Ni can be optimized to form very dense coating layer. In addition, the impact energy generated as the CSC powder collides with the surface of base metal at a speed of Mach 2 or more can remove the residual tensile stress of welding area and serve the compress stress. CSC layers include no oxidation and no contamination with under 0.2% porosity, which is enough to protect from the penetration of corrosive chloride. Therefore, the CSC coating layer can be accompanied by a function that can be disconnected from the corrosive environment and an effect of improving the residual stress that causes CISCC, so the canister's CISCC resistance can be increased.

This study presents a CRUD modelling to simulate the thermal resistance behavior of CRUD, deposited on the surface of a cladding tube of a fuel assembly. When heat produced from fuels transfers to a coolant through a cladding tube, the CRUD acting as an additional thermal resistance is expressed as two layers, i.e., a solid oxide layer and an imaginary fluid layer, which are added to the experimental tube's heat structure of the MARS-KS input data. The validation calculation for the experiments performed in UNIST-DISNY facility showed that the center and surface temperatures of the cladding tube increased as the porosity and the steam amount inside pores of the CRUD got higher. In addition, the temperature gradient in the imaginary fluid layer was calculated to be larger than that in the solid oxide part, indicating that the steam amount inside the layer acted more largely as thermal resistance. It was also evaluated through sensitivity calculations that the cladding tube temperature was more sensitive to the CRUD porosity and the steam amount in pores than to the inlet flow rate of the coolant.

Hydrogen embrittlement of a pipe is an important factor in hydrogen transport. To characterize hydrogen embrittlement, tensile and fracture toughness tests should be conducted. However, in the case of hydrogen-embrittled materials, it is difficult to perform tests in hydrogen environment, particularly at low temperatures. It would be useful to develop a methodology to predict the fracture toughness of hydrogen-embrittled materials at low temperatures using more efficient tests. In this study, the fracture toughness of API X52 steels in hydrogen at low temperatures is predicted from numerical simulation using coupled finite element (FE) damage analyses with FE diffusion analysis, calibrated by analyzing small punch test data.

This paper examines the quantification of uncertainty for welding residual stresses in dissimilar metal welds used in nuclear power plants. A mock-up of a dissimilar metal weld pipe, consisting of carbon and stainless steel pipes, was fabricated to measure the residual stress. A Round-Robin analysis was conducted by Korean institutions to assess the welding residual stress. The analysis was carried out in the second order, and the data obtained by each institution was evaluated based on the information provided. Using the Round-Robin results, the distribution of uncertainty in welding residual stresses among Korean institutions was evaluated. The quantification of uncertainty for Korean institutions was found to have a wider range compared to the distribution of welding residual stresses observed in overseas institutions. This study is considered useful in the establishment of comprehensive strategies for evaluating welding residual stress analysis methods used by domestic institutions.

When performing stress analysis for a nozzle in nuclear power plants, the nozzle loads should be determined conservatively. Existing stress analysis report of 3-D nozzle loads in nuclear power plants often provide only load magnitude not the sign (direction). Since calculated stress distribution depends on load direction, determining critical load directions for conservative stress analysis is crucial. In this study, an efficient method for determining critical load directions in nozzle loads is proposed. In the proposed method, stresses are firstly calculated using elastic finite element (FE) analysis for the uni-axial load in each direction. Then stress distributions for the multi-axial loads are analytically calculated using the principle of superposition. The calculated stress values are verified by comparing with FE analysis results under multi-axial loading. By using this method, the complex task of determining conservative load directions can be simplified.

In nuclear power plants, ultrasonic test for pipe wall thickness measurement is used during periodic inspections to prevent pipe rupture due to pipe wall thinning. However, when measuring pipe wall thickness using ultrasonic test, a significant amount of measurement error occurs due to the on-site conditions of the nuclear power plant. If the maximum pipe wall thinning rate is decided by the measured pipe wall thickness containing a significant error, the pipe wall thinning rate data have significant uncertainty and systematic overestimation. This study proposes preprocessing of pipe wall thinning measurement data using support vector machine regression algorithm. By using support vector machine, pipe wall thinning measurement data can be smoothened and accordingly uncertainty and systematic overestimation of the estimated pipe wall thinning rate data can be reduced.

In nuclear power plants, the flow rate information is a major indicator of the performance of rotating equipment such as pumps, and is a very important one required for facility operation and maintenance. To measure a flow rate, various types of methods have been developed and used. Among them, the differential pressure type using orifice and the direct doppler type using ultrasonic waves are the most commonly used. However, these flow rate measurement methods have limitations in installation, conditions and status of the measuring part, etc. To solve this problem, we have studied a new technique for measuring flow rate from scratch. In this paper, we have devised a technique to estimate the flow rate using an average moving velocity of large-scale eddy in turbulence that occurs in the piping flow field. The velocity of the large-scale eddy can be measured using the pressure fluctuation signals on the inner surface of the pipe. To estimate the flow rate, at first a cross-correlation function is applied to the two pressure fluctuation signals located at different positions in the down stream for calculating the time delay between the moving eddies. In order to validate the proposed flow rate estimation method, CFD analyses for the internal turbulence flow in pipe are conducted with a fixed flow condition, where the pressure fluctuation signals on the pipe inner surface are simulated. And then the average flow velocity of the large scale eddy is to be estimated. The estimated flow velocity is turned out to be similar to the fixed (known) flow rate.

Since spent nuclear fuel assemblies (SFA) are transported to interim storage or final disposal facility after cooling the decay heat, finite element analysis (FEA) with simplification is widely used to show their integrity against cladding failure to cause dispersal of radioactive material. However, there is a lack of research addressing the comprehensive impact of shape and element simplification on analysis results. In this study, for the optimization of a typical pressurized water reactor SFA, different types of finite element models were generated by changing number of fuel rods, fuel rod element type and assembly length. A series of FEA in use of these different models were conducted under a shock load data obtained from surrogate fuel assembly transportation test. Effects of number of fuel rods, element type and length of assembly were also analyzed, which shows that the element type of fuel rod mainly affected on cladding strain. Finally, an optimal finite element model was determined for other practical application in the future.

For the phase boundary crack found in the gasket made of cast austenitic stainless steel in the nuclear power plant, the oxide layers were analyzed through SEM and TEM. The results showed that cracks initiated and propagated along the austenite/δ-ferrite phase boundary, the propagation path was changed to penetrate the inside of the phase. The oxide layer located at the periphery of the crack along the phase boundary was identified as a complex multi-layered spinel structure, and Cr-rich carbides were also detected in the oxide. The cracks that propagated inside the austenite matrix were attributed to the presence of high external stresses and impurities.