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Uesawa, Shinichiro; Hiramatsu, Natsuki*; Ono, Koji*; Yoshida, Hiroyuki
Dai-53-Kai Kashika Joho Shimpojiumu Koen Rombunshu (Internet), 3 Pages, 2026/08
To realize the early practical application of innovative reactors, it is essential to utilize numerical simulations as alternatives to large-scale mock-up tests. To clarify the validity, we are developing measurement techniques capable of capturing instantaneous and local gas-liquid interface information. In this study, a measurement technique based on deep learning is being developed to obtain instantaneous and local bubble characteristics, such as bubble diameter, bubble velocity, and aspect ratio, for validating detailed two-phase flow simulations. This presentation introduces visualization results in a rod bundle flow channel for acquiring bubble characteristics. To enable visualization of the entire flow channel, a 4
4 rod bundle test section was fabricated using perfluoroalkoxy (PFA) tubes with a refractive index close to that of water as simulated fuel rods. Bubble behavior was captured using two high-speed video cameras arranged orthogonally. The three-dimensional distribution of bubbles was reconstructed from the images obtained from the two viewing directions. In addition, void fraction measurements were conducted under the same conditions using a wire-mesh sensor, and the validity and applicability of the present experimental method were examined through comparisons with the visualization measurement results.
Hiramatsu, Natsuki*; Ono, Koji*; Uesawa, Shinichiro; Yoshida, Hiroyuki
Dai-53-Kai Kashika Joho Shimpojiumu Koen Rombunshu (Internet), 3 Pages, 2026/08
For the early practical deployment of innovative reactors, the use of detailed two-phase flow analysis is being considered as an alternative or complementary approach to large-scale mock-up experiments. In this study, we are developing a technique to calculate bubble centroid positions, diameters, and velocities and to reconstruct the three-dimensional bubble distribution by applying image segmentation, bounding-box-based tracking, and bubble matching between images acquired from two different directions, in order to validate the detailed two-phase flow analysis. This presentation reports the current status of the development of this technique and evaluates the impact of using not only experimental data but also numerical simulation data as training data on the detection accuracy.
Uesawa, Shinichiro; Maeshima, Takahiro*; Okada, Makoto*; Tomita, Hirobumi*; Tate, Naofumi*; Aoki, Kunitomo*; Hiramatsu, Natsuki*; Ono, Koji*; Yoshida, Hiroyuki
Konsoryu Shimpojiumu 2026 Koen Rombunshu (Internet), 2 Pages, 2026/08
To use detailed two-phase flow simulations as an alternative or complement to large-scale mockup experiments, quantitative validation of instantaneous and local gas-liquid interfacial information is required in addition to flow-regime reproducibility. However, conventional wire-mesh sensors (WMSs) cannot measure void fraction distributions at a spatial resolution finer than the wire-crossing interval. To overcome this limitation, we are developing a technique to estimate high accurate, high-resolution void fraction distributions from WMS signals by combining WMS measurements, detailed two-phase flow simulations, electrostatic field analysis, and generative AI. This presentation reports on the development status of a Pix2Pix-based model and its application to experimentally obtain WMS signals in a 33 rod-bundle channel.
Kawabe, Tomosaburo*; Sano, Yoshihiko*; Kuwahara, Fujio*; Uesawa, Shinichiro; Yoshida, Hiroyuki
Dai-63-Kai Nihon Dennetsu Shimpojiumu Koen Rombunshu (Internet), 1 Pages, 2026/05
To estimate the thermal behavior of fuel debris inside the Primary Containment Vessels (PCVs) of TEPCO's Fukushima Daiichi Nuclear Power Station, a simulation method has been developed using the JUPITER code with porous medium models. However, it has been found that the selection of models and parameters according to the internal structure of the porous media significantly affects the accuracy of simulation results, highlighting the need for appropriate model selection strategies. In this study, we focus on packed beds with particles as one form of porous media and investigate a methodology for determining model parameters that characterize their flow behavior. Systematic knowledge of packed beds with heterogeneous particle size ratios and packing structures remains limited, and comprehensive organization accounting for structural differences has not yet been fully established. Therefore, numerical simulations were employed to evaluate the permeability and Forchheimer coefficient of packed beds with different particle size ratios and packing structures. Based on the obtained results, a method for appropriately determining these parameters according to the structural characteristics of packed beds is proposed, and insights are provided that contribute to improving the accuracy of flow analysis models in porous media.
Uesawa, Shinichiro; Ono, Ayako; Yoshida, Hiroyuki
Haikan Gijutsu, 68(4, 増刊号), p.52 - 56, 2026/03
This paper introduces a new measurement technique for visualizing the three-dimensional distribution of bubbles in a complex channel such as a nuclear reactor fuel assembly. Bubbly flow is important in many engineering fields, and especially in nuclear engineering, where bubble behavior significantly affects the performance and safety of nuclear reactors, and thus requires detailed understanding. Conventional rule-based image recognition has difficulty identifying bubbles overlapping in the line-of-sight direction, but in this study, deep learning (Mask R-CNN and Swin Transformer) is used to achieve highly accurate bubble detection with a small amount of training data. Furthermore, the tracking technique using ByteTrack made it possible to track many bubbles with complex motions, and by combining images taken from different viewpoints using two high-speed cameras and reconstructing the 3D shape of the bubbles using the ellipsoid approximation, 3D instantaneous local information such as bubble position, diameter, and velocity was obtained. To eliminate the effects of refraction and obstruction of vision by structures in the channel, a simulated fuel rod was made of a transparent material (PFA tube) with a refractive index similar to that of water, enabling distortion-free imaging and measurement even in channels with complex structures. This enabled 3D visualization of bubble behavior in complex channels, which had been difficult to achieve in the past. Since this technology enables highly accurate 3D visualization with a small number of cameras and a small amount of learning, it is expected to be applied to objects other than bubbles.
Uesawa, Shinichiro; Yoshida, Hiroyuki
Journal of Nuclear Science and Technology, 24 Pages, 2026/00
Times Cited Count：0In void-fraction measurements using conductance-type wire-mesh sensors (WMSs) in rod-bundle flows, the measurement accuracy is governed by the non-uniform electric current density formed near the electrodes. This non-uniformity causes the instantaneous WMS signal to be strongly affected by the bubble position and shape, thereby introducing systematic errors specific to rod-bundle geometries. However, these errors have not been sufficiently evaluated. In this study, three-dimensional electrostatic simulations were performed to clarify the mechanisms and magnitudes of these errors. The current density distributions and WMS signal responses were analyzed for the subchannel, inter-subchannel, and corner-subchannel regions while varying the bubble position, bubble shape, and transmitter-receiver layer distance. The results demonstrated that the spatial characteristics of the current-density distribution differ among the three channel types. Consequently, the correlation between the WMS signal and void fraction was not unique, and the channel-dependent variations in the correlation were confirmed to arise from differences in bubble position, bubble shape, and layer distance. By consolidating these correlations, representative void-fraction conversion formulas incorporating quantitative systematic errors were developed. The findings of this study provide a quantitative basis for improving the reliability of WMS measurements and for evaluating experimental uncertainties in the validation of two-phase flow CFD simulation codes.
Sano, Yoshihiko*; Ota, Kensuke*; Kuwahara, Fujio*; Uesawa, Shinichiro; Yoshida, Hiroyuki
Nihon Kikai Gakkai Netsu Kogaku Konfuarensu 2025 Koen Rombunshu, 1 Pages, 2025/10
To estimate the thermal behavior of fuel debris inside the Primary Containment Vessels (PCVs) of TEPCO's Fukushima Daiichi nuclear power station, a simulation method has been developed using the JUPITER code with porous medium models. However, it has been found that the selection of models and parameters according to the internal structure of the porous media significantly affects the accuracy of simulation results, highlighting the need for appropriate model selection strategies. In this study, we investigated methods for calculating macroscopic model constants that characterize flow behavior in porous media. These properties are influenced not only by the volume ratio of solid and gas phases but also by the structural features of the porous media. Focusing on packed beds composed of particles with varying diameters, we conducted numerical simulations to evaluate permeability and Forchheimer coefficient across diverse structural configurations. Based on the results, we propose a method for appropriately determining these parameters according to the structure of the packed bed, thereby contributing to the improvement of the porous media heat transfer and flow model.
Fukuda, Takanari; Uesawa, Shinichiro; Yamashita, Susumu
Proceedings of 2025 International Congress on Advances in Nuclear Power Plants (ICAPP 2025) (Internet), 12 Pages, 2025/09
A comparative study was conducted on three interface capturing schemes (ICSs) of the VOF method: THINC/WLIC, THINC/AWLIC, and PLIC for simulating gas-liquid two-phase flow in a BWR reactor core. The simulations in a rod bundle geometry were compared qualitatively and quantitatively with experimental data obtained with a high-speed camera and wire mesh sensors. The results showed that the all ICSs yielded reasonable agreements with experimental data, but THINC/WLIC had a significant issue in which the VOF value diffuses and dissipates over the simulation geometry. THINC/AWLIC, developed by the authors, improved the VOF diffusion issue of the THINC/WLIC and predicted the void fraction close to that of the highly accurate ICS of PLIC, despite its simpler algorithm. However, the numerical bubble coalescence was still an issue, particularly at low gas flow rates, which calls for further research to refine the simulation results to better reflect actual bubble behavior.
Uesawa, Shinichiro; Ono, Ayako; Yoshida, Hiroyuki
Gazo Rabo, p.1 - 5, 2025/08
This paper introduces a new measurement technique for visualizing the three-dimensional distribution of bubbles in a complex channel such as a nuclear reactor fuel assembly. Bubbly flow is important in many engineering fields, and especially in nuclear engineering, where bubble behavior significantly affects the performance and safety of nuclear reactors, and thus requires detailed understanding. Conventional rule-based image recognition has difficulty identifying bubbles overlapping in the line-of-sight direction, but in this study, deep learning (Mask R-CNN and Swin Transformer) is used to achieve highly accurate bubble detection with a small amount of training data. Furthermore, the tracking technique using ByteTrack made it possible to track many bubbles with complex motions, and by combining images taken from different viewpoints using two high-speed cameras and reconstructing the 3D shape of the bubbles using the ellipsoid approximation, 3D instantaneous local information such as bubble position, diameter, and velocity was obtained. To eliminate the effects of refraction and obstruction of vision by structures in the channel, a simulated fuel rod was made of a transparent material (PFA tube) with a refractive index similar to that of water, enabling distortion-free imaging and measurement even in channels with complex structures. This enabled 3D visualization of bubble behavior in complex channels, which had been difficult to achieve in the past. Since this technology enables highly accurate 3D visualization with a small number of cameras and a small amount of learning, it is expected to be applied to objects other than bubbles.
Muhammad, I.; Nagatake, Taku; Uesawa, Shinichiro; Ono, Ayako
Proceedings of 21st International Topical Meeting on Nuclear Reactor Thermal Hydraulics (NURETH-21) (Internet), 12 Pages, 2025/08
This research aims to validate ACE-3D using data from a two-phase flow experiment. For this purpose, a two-phase flow experiment was conducted in a four-by-four unheated fuel assembly. In the experiment, the time-averaged void fraction distribution was measured using a wire mesh sensor system under high temperatures and high-pressure conditions. The experimental results were analyzed, and the data were visualized to understand better the behavior and characteristics of the two-phase flow in the fuel assembly. A two-phase flow data set is being developed, covering a wide range of experimental conditions, including higher-pressure regions, which can be used for validating thermal-hydraulic codes. Finally, the ACE-3D code was applied to the two-phase flow experiment. The calculation results were then compared to the experimental ones, and the issues were identified for improving ACE-3D in future simulations.
Uesawa, Shinichiro; Yamashita, Susumu; Sano, Yoshihiko*; Yoshida, Hiroyuki
Journal of Nuclear Science and Technology, 62(6), p.523 - 541, 2025/06
Times Cited Count：0 Percentile：0.00(Nuclear Science & Technology)Japan Atomic Energy Agency (JAEA) has developed a numerical method with the JUPITER code with a porous medium model to calculate the thermal behavior in PCVs of 1F. In this study, we performed an experiment and numerical simulation of the natural convective heat transfer with the porous medium to validate JUPITER with the porous medium model. In comparison of the temperature and velocity distributions between the experiment and simulation, the temperature distribution in the simulation was in good agreement with the distribution in the experiment except the temperature near the top surface of the porous medium. The velocity distribution also agreed qualitatively with the experimental result. In addition, we also performed the numerical simulations with various effective thermal conductivity models to discuss the effect of the conductivity based on the internal structure of porous media on the natural convective heat transfer. The result indicated that the temperature distribution in the porous medium and the velocity distribution of the natural convection were significantly different for each model, and thus the conductivity of the fuel debris was one of the key parameters of in the thermal behavior analysis in 1F.
Uesawa, Shinichiro; Ono, Ayako; Nagatake, Taku; Yamashita, Susumu; Yoshida, Hiroyuki
Journal of Nuclear Science and Technology, 62(5), p.432 - 456, 2025/05
Times Cited Count：1 Percentile：0.00(Nuclear Science & Technology)We performed electrostatic simulations of a wire-mesh sensor (WMS) for a single spherical bubble and bubbly flow to clarify the accuracy of the WMS. The electrostatic simulation for the single bubble showed the electric current density distribution and the electric current path from the excited transmitter to receivers for various bubble locations. It indicated systematic errors based on the nonuniform current density distribution around the WMS. The electrostatic simulation for the bubbly flow calculated by the computational fluid dynamics code, JAEA Utility Program for Interdisciplinary Thermal-hydraulics Engineering and Research (JUPITER), indicated that the WMS had difficulty in quantitatively measuring the intermediate values of the instantaneous void fraction between 0 and 1 because they cannot be estimated by previous transformation methods from the WMS signal to the void fraction, such as linear approximation or Maxwell's equation, and have a significant deviation of the void fraction of 
0.2 for the WMS signal. However, the electrostatic simulation indicated that the time-averaged void fractions around the center of the flow channel can be estimated using linear approximation, and the time-averaged void fraction near the wall of the flow channel can be estimated using Maxwell's equation.
Uesawa, Shinichiro; Ono, Ayako; Yoshida, Hiroyuki
Konsoryu, 39(1), p.61 - 71, 2025/03
Bubble visualization using a high-speed video-camera has been used as a measurement technique of bubble diameters and velocities. However, the bubble detection was difficult under the condition of the high void fraction because the overlapping bubbles for the sight direction of the camera increased with the void fraction. Additionally, the visualization for a system with objects, such as rod bundle flow channels, becomes more difficult. In this study, we applied a deep learning-based bubble detection technique with Shifted Window Transformer to bubble images shoot from two directions to identify the bubble size, three-dimensional (3D) positions of bubbles, 3D bubble trajectories in the rod bundle flow channel. Furthermore, we used perfluoroalkoxy alkane tubes with almost the same reflection as water in the channel to visualize the bubbly flow in the whole of the flow channel. We confirmed that the detection technique can segment individual bubbles in overlapping bubbles and bubbles behind the rod. By using the detection results, we estimated the diameter and velocity of each bubble and cross-sectional void fraction.
Uesawa, Shinichiro; Yoshida, Hiroyuki
Journal of Nuclear Science and Technology, 61(11), p.1438 - 1452, 2024/11
Times Cited Count：4 Percentile：62.23(Nuclear Science & Technology)We developed a deep learning-based bubble detector with a Shifted window Transformer (Swin Transformer) to detect and segment individual bubbles among overlapping bubbles. To verify the performance of the detector, we calculated its average precision (AP) with different number of training images. The mask AP increased with the increase in the number of training images when there were less than 50 images but remained constant when there were more than 50 images. It was observed that the AP for the Swin Transformer and ResNet were almost the same when there were more than 50 images; however, when few training images were used, the AP of the Swin Transformer were higher than that of the ResNet. Furthermore, with regard to the increase in void fraction, the AP of the Swin Transformer showed a decrease similar to that in the case of the ResNet; however, for few training images, the AP of the Swin Transformer was higher than that of the ResNet in all void fractions. Moreover, we confirmed the detector trained with synthetic bubble images was able to segment overlapping bubbles and deformed bubbles in a bubbly flow experiment. Thus, we verified that the new bubble detector with Swin Transformer provided higher AP than the detector with ResNet for fewer training images.
Uesawa, Shinichiro; Ono, Ayako; Yamashita, Susumu; Yoshida, Hiroyuki
Proceedings of 13th Korea-Japan Symposium on Nuclear Thermal Hydraulics and Safety (NTHAS13) (Internet), 7 Pages, 2024/11
A conductance-typed wire-mesh sensor (WMS), utilizing the difference in conductivity between gas and liquid phases between the electrodes, is one of the practical measurement techniques of a cross-sectional void fraction distribution in a flow path. In this study, we performed two-phase computational fluid dynamics (CFD) and electrostatic simulations around a WMS for a single spherical bubble and bubbly flow to clarify the systematic error in the WMS. The results for the single bubble indicated that there were systematic errors based on the non-uniform current density distribution around the WMS. The correlation between instantaneous void fractions and WMS signals is not uniquely determined for positions of the single bubble moving across the WMS, even for the same bubble. Moreover, the correlation between the instantaneous void fractions and the WMS signals did not fit in a linear approximation and Maxwell's equation, which traditionally used transformation methods from the WMS signal to the void fraction. The results for the bubbly flow indicated that the WMS had difficulty in quantitative measurements of the instantaneous void fraction because the values had a significant deviation of the void fraction of approximately 0.2. On the other hand, time-averaged void fraction values had relatively small deviation. Thus, we concluded that the WMS, using existing transformation methods, can measure time-averaged void fractions, but it is difficult to measure quantitatively instantaneous void fractions.
Uesawa, Shinichiro; Ono, Ayako; Yoshida, Hiroyuki
Konsoryu Shimpojiumu 2024 Koen Rombunshu (Internet), 2 Pages, 2024/09
Bubble visualization using a high-speed video-camera has been used as measurement techniques of bubble diameters, interfacial area concentrations, and void fractions in dispersed bubbly flow. However, the bubble detection was difficult under the condition of the high void fraction because the overlapping bubbles for the sight direction of the camera increased with the increase in the void fraction. In this study, we developed the deep learning-based bubble detector with Shifted window Transformer (Swin Transformer) to overcome the issue. To verify the performance, we used the synthetic bubble images obtained by Generative Adversarial Networks (GAN) and obtained average precisions (APs) for the number of the training dataset. The result showed that the AP was large enough for 50 datasets, and bubble detection was possible even with a small number of the training data. Additionally, we confirmed that the detector can detect and segment individual bubbles in overlapping bubbles obtained in the visualization experiments of pipe and bundle flows. By using the detection results, we estimated the interfacial area concentrations and void fractions. In comparison with commonly used relations, the results were in good agreement with the relations. Thus, the detector can measure not only bubble diameters but also interfacial area concentrations and void fractions.
Uesawa, Shinichiro; Ono, Ayako; Yoshida, Hiroyuki
Dai-52-Kai Kashika Joho Shimpojiumu Koen Rombunshu (Internet), 2 Pages, 2024/07
In order to obtain 3D behavior of bubbles, visualization using high-speed video-cameras has been used to identify 3D positions of bubbles. However, it was difficult to apply the technique to bubbly flow with the high void fraction because overlapping bubbles for the sight direction of the camera increased with the increase in the void fraction. JAEA has developed the deep learning-based bubble detector with Shifted window Transformer (Swin Transformer) to overcome the issue for the overlapping bubbles. In this study, we applied the bubble detection technique to images of bubble swarms visualized from two directions other than the direction of main flow and visualized 3D behavior of dispersed bubbles. The result showed that individual bubbles in bubble swarms were detected, and bubble diameters and aspect ratios were measured. Additionally, we obtained 3D positions of bubbles and 3D bubble velocities by linking the bubble positions for the direction of main flow in both images.
4 simulated fuel bundle for validation of thermal-hydraulics simulation codesOno, Ayako; Nagatake, Taku; Uesawa, Shinichiro; Shibata, Mitsuhiko; Yoshida, Hiroyuki
Proceedings of Specialist Workshop on Advanced Instrumentation and Measurement Techniques for Nuclear Reactor Thermal-Hydraulics and Severe Accidents (SWINTH-2024) (USB Flash Drive), 7 Pages, 2024/06
Japan Atomic Energy Agency (JAEA) is developing a neutronics/thermal-hydraulics coupling simulation code for light-water reactors. Thermal-hydraulic simulation codes applied to the coupling code are expected to calculate the void fraction distribution in a rod bundle under operational conditions, which are necessary for neutron transport simulation, and need to be validated using void fraction distribution data in a rod bundle under high-temperature and high-pressure conditions. Therefore, we have conducted the measurement of the instantaneous void distribution in the 4 4 simulated fuel bundle using a developed wire mesh sensor, which is installed in the pressurized two-phase flow experimental loop of JAEA to obtain the data for code validation.
Koyama, Shinichi; Ikeuchi, Hirotomo; Mitsugi, Takeshi; Maeda, Koji; Sasaki, Shinji; Onishi, Takashi; Tsai, T.-H.; Takano, Masahide; Fukaya, Hiroyuki; Nakamura, Satoshi; et al.
Hairo, Osensui, Shorisui Taisaku Jigyo Jimukyoku Homu Peji (Internet), 216 Pages, 2023/11
In FY 2021 and 2022, JAEA perfomed the subsidy program for "the Project of Decommissioning and Contaminated Water Management (Development of Analysis and Estimation Technology for Characterization of Fuel Debris (Development of Technologies for Enhanced Analysis Accuracy, Thermal Behavior Estimation, and Abbreviated Analysis))" started in FY 2021. This presentation material summarized the results of the project, which will be available shortly on the website of Management Office for the Project of Decommissioning, Contaminated Water and Treated Water Management.
4 simulated fuel bundle for validation of thermal-hydraulics simulation codesNagatake, Taku; Shibata, Mitsuhiko; Uesawa, Shinichiro; Ono, Ayako; Yoshida, Hiroyuki
Dai-27-Kai Doryoku, Enerugi Gijutsu Shimpojiumu Koen Rombunshu (Internet), 5 Pages, 2023/09
JAEA is developing a neutronics/thermal-hydraulics coupling simulation code for light-water reactors. Thermal-hydraulic simulation codes applied to the platform are expected to evaluate void fraction distributions in fuel assemblies under operational conditions, which is necessary for neutron transport simulation, and need to be validated using void fraction distribution data in a rod bundle under high-temperature and high-pressure conditions. To obtain the data for code validation, we have been measuring the instantaneous void fraction distribution in a 44 simulated fuel assembly by a wire mesh sensor. In this paper, we report the results of the experiments with pressure and flow rate as parameters at a maximum pressure of 2.6 MPa.
