• Nuclear Engineering and Technology
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• 제51권8호
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• pp.1970-1977
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• 2019

Understanding the irradiation hardening effect of structural steels under various irradiation conditions plays an important role in developing advanced nuclear systems. Such being the case, a crystal plasticity model for body-centered cubic (BCC) crystal based on the density of dislocations and irradiation defects is summarized and numerically implemented in this paper. Based on this model, nano-indentation hardness of Chinese A508-3 steels with ion irradiation is calculated. Very good agreement is observed between simulation and experimental data of several different irradiation doses subjected to various operating temperatures, from which, it can be concluded that indentation hardness increases with increasing irradiation dose at both room temperature and high temperature. Consequently, the validity of this model has been proved properly, and furthermore, the model established in this paper could guide the study of irradiation hardening effect and temperature effect to some extent.

• Nuclear Engineering and Technology
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• 제55권4호
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• pp.1350-1364
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• 2023

2D/1D coupling method is an important neutron transport calculation method due to its high accuracy and relatively low computation cost. However, 2D/1D coupling method may diverge especially in small axial mesh size. To analyze the convergence behavior of 2D/1D coupling method, a Fourier analysis for k-eigenvalue neutron transport problems is implemented. The analysis results present the divergence problem of 2D/1D coupling method in small axial mesh size. Several common attempts are made to solve the divergence problem, which are to increase the number of inner iterations of the 2D or 1D calculation, and two times 1D calculations per outer iteration. However, these attempts only could improve the convergence rate but cannot deal with the divergence problem of 2D/1D coupling method thoroughly. Moreover, the choice of axial solvers, such as DGFEM SN and traditional SN, and its effect on the convergence behavior are also discussed. The results show that the choice of axial solver is a key point for the convergence of 2D/1D method. The DGFEM SN based 2D/1D method could converge within a wide range of optical thickness region, which is superior to that of traditional SN method.

• Nuclear Engineering and Technology
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• 제53권5호
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• pp.1416-1428
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• 2021

Pebble flow characteristics can be significantly affected by the configuration of pebble bed, especially for HTGR pebble beds. How to achieve a desired uniform flow pattern without stagnation is the top priority for reactor design. Pebbles flows inside some specially designed pebble bed with arc-shaped contraction configurations at the bottom, including both concave-inward and convex-outward shapes are explored based on discrete element method. Flow characteristics including pebble retention, residence-time frequency density, flow uniformity as well as axial velocity are investigated. The results show that the traditionally designed pebble bed with cone-shape bottom is not the most preferred structure with respect to flow pattern for reactor design. By improving the contraction configuration, the flow performance can be significantly enhanced. The flow in the convex-shape configuration featured by uniformity, consistency and less stagnation, is much more desirable for pebble bed design. In contrast, when the shape is from convex-forward to concave-inward, the flow shows more nonuniformity and stagnation in the corner although the average cross-section axial velocity is the largest due to the dominant middle pebbles.

• Nuclear Engineering and Technology
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• 제55권6호
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• pp.2288-2297
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• 2023

Current designs of both large reactor units and small modular reactors utilize a nuclear fuel with increasing enrichment. This increasing demand for better nuclear fuel utilization is a challenge for nuclear fuel handling facilities. The operation with higher enriched fuels leads to reduced reserves to legislative and safety criticality limits of spent fuel transport, storage and final disposal facilities. Design changes in these facilities are restricted due to a boron content in steel and aluminum alloys that are limited by rolling, extrusion, welding and other manufacturing processes. One possible solution for spent fuel pools and casks is the burnup credit method that allows decreasing very high safety margins associated with the fresh fuel assumption in spent fuel facilities. This solution can be supplemented or replaced by an alternative solution based on placing the neutron absorber material directly into the fuel assembly, where its efficiency is higher than between fuel assemblies. A neutron absorber permanently fixed in guide tubes decreases system reactivity more efficiently than absorber sheets between the fuel assemblies. The paper summarizes possibilities of fixed neutron absorbers for various nuclear fuel and fuel handling facilities. Moreover, an absorber material was optimized to propose alternative options to boron. Multiple effective absorbers that do not require steel or aluminum alloy compatibility are discussed because fixed absorbers are placed inside zirconium or steel cladding.

• 기술혁신연구
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• 제24권4호
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• pp.221-248
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• 2016

본 연구는 원자력기술의 혁신특성을 심층조사 함으로써 4세대 원자력에너지기술의 전환 시 발생 가능한 이슈를 이해하고 한국의 정책현황을 분석하여 4세대 원자력에너지기술의 성공적 안착을 위한 시사점을 도출하였다. 이는 현재 세계 5강의 원자력에너지기술 강국인 한국에서 4세대 원자력에너지기술의 도래에도 지속가능한 경쟁력을 유지하기 위한 중요한 정책적인 시사점으로 활용할 수 있을 것으로 사료된다. 정성적 문헌연구방법을 통해 원자력기술혁신에 관한 문헌들을 조사한 결과, 4세대 원자력 에너지기술의 전환에 영향을 미치는 요인은 크게 4가지로 확인할 수 있었다. 이는 장기간의 안정적인 자원 할당, 혁신을 위한 이해당사자 간의 지속적인 상호작용, 완전한 시스템을 위한 기술과 노하우의 축적, 적용 및 실증을 위한 정책적인 시장이었다. 이를 한국의 4세대 원자력에너지기술과 연관한 정책을 대상으로 적용하여 사례분석을 한 결과, 현재 4세대 기술이 기술개발의 초기단계에서 실증단계로 넘어가는 시점임을 감안하더라도 연관한 정책은 실증과 운영을 위한 전문인력의 체계적인 양성 방안, 사회적 수용성과 저항에 대한 대응, 실증에 대한 구체적인 계획 수립, 4세대 원자력시스템을 적용하기 위한 정책적인 시장을 제안하는 장기적인 노력, 이해당사자들 간의 구체적이고 지속적인 상호작용을 적극 장려하는 것이 체계적으로 필요함을 제시하였다.

• Nuclear Engineering and Technology
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• 제55권1호
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• pp.339-352
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• 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
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• 제56권9호
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• pp.3835-3850
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• 2024

The high-temperature gas-cooled reactor (HTGR) with spherical fuel elements contains complex pebble flow. The flow behavior of pebbles is influenced by various factors, such as pebble density, friction coefficient, wall structure, and discharge port size. Using a GPU-DEM numerical model, the effects of the friction coefficient on the cyclic loading and unloading of pebbles in the full-scale HTR-PM are studied. Numerical simulations with up to 420,000 spherical pebbles are conducted. Four sets of friction coefficient values are determined for comparative analysis based on experimental measurements. Discharging speed, residence time, stress, porosity, and velocity distribution are quantitatively analyzed. In addition, a comparison with the CT-PFD experiment is carried out to validate the numerical model. The results show that near-wall retention phenomena are observed in the reactor core only when using large friction coefficients. However, using friction coefficient values closer to the measured experimental values, the pebble bed in HTR-PM exhibited good flow characteristics. Furthermore, the friction coefficient also influences the porosity and velocity distribution of the pebble bed, with lower friction coefficients resulting in lower overall stress in the bed. The discharge outlet's influence varies with different friction coefficient values. In summary, this study demonstrates that the value of the friction coefficient has a complex influence on the pebble flow in HTR-PM, which provides important insights for future numerical and experimental studies in this field.

• Nuclear Engineering and Technology
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• 제50권4호
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• pp.599-605
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• 2018

Fault diagnosis depends critically on the selection of sensors monitoring crucial process variables. Boolean network (BN) is composed of nodes and directed edges, where the node state is quantized to the Boolean values of True or False and is determined by the logical functions of the network parameters and the states of other nodes with edges directed to this node. Since BN can describe the fault propagation in a sensor network, it can be applied to propose sensor selection strategy for fault diagnosis. In this article, a sufficient condition for parameter identifiability of BN is first proposed, based on which the sufficient condition for fault identifiability of a sensor network is given. Then, the fault identifiability condition induces a sensor selection strategy for sensor selection. Finally, the theoretical result is applied to the fault diagnosis-oriented sensor selection for a nuclear heating reactor plant, and both the numerical computation and simulation results verify the feasibility of the newly built BN-based sensor selection strategy.

• Nuclear Engineering and Technology
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• 제56권3호
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• pp.1037-1051
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• 2024

This paper presents the construction results and design of the UNIST Reactor Innovation platform for small modular reactors as a versatile testbed for exploring innovative technologies. The platform uses simulant fluids to simulate the thermal-hydraulic behavior of a reference small modular reactor design, allowing for cost-effective design modifications. Scaling analysis results for single and two-phase natural circulation flows are outlined based on the three-level scaling methodology. The platform's capability to simulate natural circulation behavior was validated through performance calculations using the 1-D system thermal-hydraulic code-based calculation. The strategies for evaluating cutting-edge technologies, such as the integration of a solid oxide electrolysis cell for hydrogen production into a small modular reactor, are presented. To overcome experimental limitations, the hardware-in-the-loop technique is proposed as an alternative, enabling real-time simulation of physical phenomena that cannot be implemented within the experimental facility's hardware. Overall, the proposed versatile innovation platform is expected to provide valuable insights for advancing research in the field of small modular reactors and nuclear-based hydrogen production.

• Nuclear Engineering and Technology
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• 제54권4호
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• pp.1301-1311
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• 2022

Global climate change brings environmental quality sensitivity, especially in developed countries. Developed countries use non-renewable energy sources intensively both in their own countries and in other countries, they make productions that cause an enormous rate of increase in CO₂ emissions and unsustainable environmental costs. This has increased the interest in environmentally friendly alternative energy sources. The aim of this study is to investigate the impact of nuclear energy consumption and technological innovation on environmental quality in G7 countries using annual data over the period 1970-2015. The Panel Threshold Regression Model was used for the analysis. Empirical findings have indicated that the relationship between nuclear energy consumption and carbon emissions differs according to innovation for nuclear power plants. It was also concluded that nuclear energy consumption reduces carbon emissions more after a certain level of innovation. This result shows that the increase in innovative technologies for nuclear power plants not only increases energy efficiency but also contributes positively to environmental quality.