• Nuclear Engineering and Technology
• /
• 제54권1호
• /
• pp.357-373
• /
• 2022

The high-temperature gas-cooled reactor pebble-bed module project is the first commercial Generation-IV NPP(Nuclear Power Plant) in China. A new joint is used for the vertical support of RPV(Reactor Pressure Vessel). The steel corbel is integrally embedded into the reactor-cabin wall through eight asymmetrically arranged pre-stressed high-strength bolts, achieving the different path transmission of shear force and moment. The vertical monotonic loading test of two specimens is conducted. The results show that the failure mode of the joint is bolt fracture. There is no prominent yield stage in the whole loading process. The stress of bolts is linearly distributed along the height of corbel at initial loading. As the load increases, the height of neutral axis of bolts gradually decreases. The upper and lower edges of the wall opening contact the corbel plate to restrict the rotation of the corbel. During the loading, the pre-stress of some bolts decreases. The increase of the pre-stress strength ratio of bolts has no noticeable effect on the structure stiffness, but it reduces the ultimate bearing capacity of the joint. A simplified calculation model for the elastic stage of the joint is established, and the estimation results are in good agreement with the experimental results.

• Nuclear Engineering and Technology
• /
• 제55권1호
• /
• pp.339-352
• /
• 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.

• 한국원자력학회:학술대회논문집
• /
• 한국원자력학회 2001년도 추계학술발표회요약집
• /
• pp.115-115
• /
• 2001

• 한국원자력학회:학술대회논문집
• /
• 한국원자력학회 2005년도 춘계학술발표회
• /
• pp.45-46
• /
• 2005

• 한국원자력학회:학술대회논문집
• /
• 한국원자력학회 2005년도 추계학술발표회
• /
• pp.9-10
• /
• 2005

• 한국원자력학회:학술대회논문집
• /
• 한국원자력학회 2003년도 춘계학술발표대회 요약집
• /
• pp.64.1-64.1
• /
• 2003

• 한국원자력학회:학술대회논문집
• /
• 한국원자력학회 2004년도 요약집 춘계학술발표대회
• /
• pp.116-116
• /
• 2004

• 한국원자력학회:학술대회논문집
• /
• 한국원자력학회 2005년도 추계학술발표회
• /
• pp.31-32
• /
• 2005

• 한국농공학회논문집
• /
• 제50권3호
• /
• pp.43-48
• /
• 2008

The economics of a passive solar heating system (PSHS) with the pebble bed heat storage was evaluated, and the applications of the PSHS were analyzed, in this study. The results are as follows: The heating load, solar heat gain, and stored heat/year of the PSHS in the solar house model were found to be 10,778MJ, 3,438MJ, and 11,682MJ, respectively. The yearly energy expenses of the PSHS and the alternative heating system (conventional coal heating system, CCHS), which uses coal, were found to be USD 1.60/year and USD 60.90/year, respectively, and the yearly expenses of the PSHS were found to be 38 times less than those of the alternative heating system (CCHS). If it will be supposed that the life cycle of the passive solar heating system, according to the results of the LCC analysis in the two systems, is 40 years, the total expenses for the life cycle of the PSHS and the CCHS will be USD 1,431.50 and USD 2,740.00, respectively. The period for the investment payback of the PSHS is six years.

• Nuclear Engineering and Technology
• /
• 제56권3호
• /
• pp.959-965
• /
• 2024

The High Temperature Test Unit (HTTU) was an experimental set-up to conduct separate and integral effects tests of the Pebble Bed Modular Reactor (PBMR) core. The annular core consisted of a randomly packed bed of uniform spheres. Natural convection tests using both nitrogen and helium, and forced convection tests using nitrogen, were conducted. The maximum material temperature achieved during forced convection testing was 1200 ℃. This paper presents the numerical analysis of the flow and temperature distribution for a forced convection test using 3D CFD as well as a 1D systems-CFD computer code. Several modelling approaches are possible, ranging from a fully explicit to a semi-implicit method that relies on correlations of their associated phenomena. For the comparison between codes, the analysis was performed using a porous media approach, where the conduction and radiative heat transfer were lumped together as an effective thermal conductivity and the convective heat transfer was correlated between the solid and gas phases. The results from both codes were validated against the experimental measurements. Favourable results were obtained, in particular by the systems-CFD code with minimal computational and time requirements.