• Nuclear Engineering and Technology
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• v.51 no.2
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• pp.546-555
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• 2019

Since the first nuclear reactor first critical, nuclear systems has gone through four generations of history, and the fourth generation nuclear system will be truly realized in the near future. The notions of SVBR and lead-bismuth eutectic alloy coolant put forward by Russia were well received by the international nuclear science community. Lead-bismuth eutectic alloy with the ability of the better neutron economy, the low melting point, the high boiling point, the chemical inertness to water and air and other features, which was considered the most promising coolant for the 4th generation nuclear reactors. This study mainly focuses on the structural design optimization of the 4th-generation reactor coolant pump, including analysis of external characteristics, inner flow, and transient characteristic. It was found that: the reactor coolant pump with a central symmetrical dual-outlet volute structure has better radial-direction balance, the pump without guide vane has better hydraulic performance, and the pump with guide vanes has worse torsional vibration and pressure pulsation. This study serves as experience accumulation and technical support for the development of the 4th generation nuclear energy system.

• Nuclear Engineering and Technology
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• v.51 no.2
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• pp.561-572
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• 2019

In the design criterion for the nuclear power plant piping system, the limit state of the piping against an earthquake is assumed to be plastic collapse. The failure of a common piping system, however, means the leakage caused by the cracks. Therefore, for the seismic fragility analysis of a nuclear power plant, a method capable of quantitatively expressing the failure of an actual piping system is required. In this study, it was conducted to propose a quantitative failure criterion for piping system, which is required for the seismic fragility analysis of nuclear power plants against critical accidents. The in-plane cyclic loading test was conducted to propose a quantitative failure criterion for steel pipe elbows in the nuclear power plant piping system. Nonlinear analysis was conducted using a finite element model, and the results were compared with the test results to verify the effectiveness of the finite element model. The collapse load point derived from the experiment and analysis results and the damage index based on the stress-strain relationship were defined as failure criteria, and seismic fragility analysis was conducted for the piping system of the BNL (Brookhaven National Laboratory) - NRC (Nuclear Regulatory Commission) benchmark model.

• Nuclear Engineering and Technology
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• v.50 no.8
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• pp.1217-1233
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• 2018

Following a surge of interest in multi-unit risk in the last few years, many recent studies have suggested methods for multi-unit probabilistic safety assessment (MUPSA) and addressed several related aspects. Most of the existing studies though focused on two-unit nuclear power plant (NPP) sites or used rather simplified probabilistic safety assessment (PSA) models to demonstrate the proposed approaches. When considering an NPP site with three or more units, some approaches are inapplicable or yield very conservative results. Since the number of such sites is increasing, there is a strong need to develop and validate practical approaches to the related MUPSA. This article provides several detailed approaches that are applicable to multi-unit Level 1 PSA for sites with up to six or more reactor units. To validate the approaches, a multi-unit Level 1 PSA model is developed and the site core damage frequency is estimated for each of four representative multi-unit initiators, as well as for the case of a simultaneous occurrence of independent single-unit initiators in multiple units. For this purpose, an NPP site with six identical OPR-1000 units is considered, with full-scale Level 1 PSA models for a specific OPR-1000 plant used as the base single-unit models.

• Design & Manufacturing
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• v.15 no.3
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• pp.1-6
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• 2021

An artificial neural network model based on a deep learning algorithm is known to be more accurate than humans in image classification, but there is still a limit in the sense that there needs to be a lot of training data that can be called big data. Therefore, various techniques are being studied to build an artificial neural network model with high precision, even with small data. The transfer learning technique is assessed as an excellent alternative. As a result, the purpose of this study is to develop an artificial neural network system that can classify burr images of light guide plate products with 99% accuracy using transfer learning technique. Specifically, for the light guide plate product, 150 images of the normal product and the burr were taken at various angles, heights, positions, etc., respectively. Then, after the preprocessing of images such as thresholding and image augmentation, for a total of 3,300 images were generated. 2,970 images were separated for training, while the remaining 330 images were separated for model accuracy testing. For the transfer learning, a base model was developed using the NASNet-Large model that pre-trained 14 million ImageNet data. According to the final model accuracy test, the 99% accuracy in the image classification for training and test images was confirmed. Consequently, based on the results of this study, it is expected to help develop an integrated AI production management system by training not only the burr but also various defective images.

• Nuclear Engineering and Technology
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• v.54 no.4
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• pp.1343-1354
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• 2022

Experiments were performed to measure the critical heat flux (CHF) on a vertical surface abutting a coarse packed bed of spherical particles. This geometry is representative of a CANDU reactor calandria tubesheet facing the end shield cavity during the in-vessel retention (IVR) phase of a severe accident. Deionized light water was used as the working fluid. Low carbon steel shielding balls with diameters ranging from 6.4 to 12.7 mm were used, allowing for the development of an empirical correlation of CHF as a function of shielding ball diameter. Previously published data is used to develop a more comprehensive empirical correlation accounting for the impacts of both shielding ball diameter and heating surface height. Tests using borosilicate shielding balls demonstrated that the dependence of CHF on shielding ball thermal conductivity is insignificant. The deposition of iron oxide particles transported from shielding balls to the heating surface is verified to increase CHF non-trivially. The results presented in this paper improve the state of the knowledge base permitting quantitative prediction of CHF in the CANDU end shield, refining our ability to assess the feasibility of IVR. The findings clarify the mechanisms governing CHF in this scenario, permitting identification of potential future research directions.

• Nuclear Engineering and Technology
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• v.54 no.1
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• pp.117-129
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• 2022

The downward discharge of the molten fuel to the lower structure of the fuel assembly could increase of the pressure drop and degrade of coolability of the assembly. To analyze the phenomena, experiments for the generation of the debris bed were conducted as LOF-DT series. Based on the debris bed in the LOF-DT, pressure drop experiment was conducted with intact and blocked component. Parametric study on the pressure drop was conducted by CFD. The LOF-DT experiments were conducted for the position and porosity of the debris bed. 85% of the debris were sedimented in the lower reflector, and 15% were in the nose piece, approximately. Porosity of the debris bed were about 0.7 and 0.85 in the lower reflector and nose piece, respectively. Pressure drop increased significantly with debris bed, especially in the lower reflector. More than 120 time of the pressure drop increased in the lower reflector, while only 10% increased in the nose piece. According to the parametric study, mass of the debris was the most important for pressure drop. The lower discharge phenomena could have a significant effect to the total pressure drop of the fuel assembly, approximately 10.8 times for the base case.

• Nuclear Engineering and Technology
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• v.54 no.6
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• pp.1962-1971
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• 2022

The liquid lead-lithium (Pb-17Li) blanket has many applications in fusion reactors due to its good tritium breeding performance, high heat transfer efficiency and safety. The compatibility of liquid Pb-17Li alloy with the structural material of blanket under magnetic field is one of the concerns. In this study, corrosion experiments China low activation martensitic (CLAM) steel and 316L steel were carried out in a forced convection Pb-17Li loop under 1.0 T magnetic field at 480 ℃ for 1000 h. The corrosion results on 316L steel showed the characteristic with a superficial porous layer resulted from selective leaching of high-soluble alloy elements and subsequent phase transformation from austenitic matrix to ferritic phase. Then the porous layers were eroded by high-velocity jet fluid. The main corrosion mechanism of CLAM steel was selective dissolution-base corrosion attack on the microstructure boundary regions and exclusively on high residual stress areas. CLAM steel performed a better corrosion resistance than that of 316L steel. The high Ni dissolution rate and the erosion of corroded layers are the main causes for the severe corrosion of 316L steel.

• Nuclear Engineering and Technology
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• v.54 no.6
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• pp.2147-2155
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• 2022

Nuclear safety-related underground liquid storage tanks, such as those used to store fuel for emergency diesel generators, are critical components for safety of hundreds of existing nuclear power plants (NPP) worldwide. Since most of those NPP will continue to operate for decades, a beyond design base (BDB) seismic screening of safety-related underground tanks in those NPP is beneficial and essential to public safety. The analytical methodology for buried tank subjected to seismic effect, including a BDB seismic evaluation, needs to consider both soil-structure and fluid-structure interaction effects. Comprehensive analysis of such a soil-structure-fluid system is costly and time consuming, often subjected to availability of state-of-art finite element tools. Simple, but practically and reasonably accurate techniques for seismic evaluation of underground liquid storage tanks have not been established. In this study, a mechanics based solution is proposed for the evaluation of a cylindrical underground liquid storage tank using hand calculation methods. For validation, a practical example of two underground diesel fuel tanks in an existing nuclear power plant is presented and application of the proposed method is confirmed by using published results of the computer-aided System for Analysis of Soil Structural Interaction (SASSI). The proposed approach provides an easy to use tool for BDB seismic assessment prior to making decision of applying more costly technique by owner of the nuclear facility.

• Nuclear Engineering and Technology
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• v.54 no.8
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• pp.2755-2770
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• 2022

The need for Dissimilar Welded Joint (DWJ) in the power plant components arises in order to increase the overall efficiency of the plant and to avoid premature failure in the component welds. The Activated-Tungsten Inert Gas (A-TIG) welding process, which is a variant of Tungsten Inert Gas (TIG) welding, is focus of this review work concerning the DWJ of nuclear grade creep-strength enhanced ferritic/martensitic (CSEF/M) steels and austenitic steels. A-TIG DWJs are compared with Multipass-Tungsten Inert Gas (M-TIG) DWJ based on their mechanical and microstructural properties. The limitations of multipass welding have put A-TIG welding in focus as A-TIG provides a weld with increased depth of penetration (DOP) and enhanced mechanical properties. Hence, this review article covers the A-TIG welding principle and working parameters along with detailed analysis of role played by the flux in welding procedure. Further, weld characteristics of martensitic and austenitic steel DWJ developed with the A-TIG welding process and the M-TIG welding process are compared in this study as there are differences in mechanical, microstructural, creep-related, and residual stress obtained in both TIG variants. The mechanics involved in the welding process is deliberated which is revealed by microstructural changes and behavior of base metals and WFZ.

• Advances in nano research
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• v.12 no.5
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• pp.489-499
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• 2022

Nanofluids have recently triggered a substantial scientific interest as cooling media. However, their stability is challenging for successful engagement in industrial applications. Different factors, including temperature, nanoparticles and base fluids characteristics, pH, ultrasonic power and frequency, agitation time, and surfactant type and concentration, determine the nanofluid stability regime. Indeed, it is often too complicated and even impossible to accurately find the conditions resulting in a stabilized nanofluid. Furthermore, there are no empirical, semi-empirical, and even intelligent scenarios for anticipating the stability of nanofluids. Therefore, this study introduces a straightforward and reliable intelligent classifier for discriminating among the stability regimes of alumina-water nanofluids based on the Zeta potential margins. In this regard, various intelligent classifiers (i.e., deep learning and multilayer perceptron neural network, decision tree, GoogleNet, and multi-output least squares support vector regression) have been designed, and their classification accuracy was compared. This comparison approved that the multilayer perceptron neural network (MLPNN) with the SoftMax activation function trained by the Bayesian regularization algorithm is the best classifier for the considered task. This intelligent classifier accurately detects the stability regimes of more than 90% of 345 different nanofluid samples. The overall classification accuracy and misclassification percent of 90.1% and 9.9% have been achieved by this model. This research is the first try toward anticipting the stability of water-alumin nanofluids from some easily measured independent variables.