Uncertainty analysis of the inverse LASSO estimation scheme on radioactive source distributions inside reactor building rooms from air does rate measurements

Shi, W.*; Machida, Masahiko; Yamada, Susumu; Okamoto, Koji

Progress in Nuclear Energy, 184, p.105710_1 - 105710_10, 2025/06

https://doi.org/10.1016/j.pnucene.2025.105710

Very recently, Least Absolute Shrinkage and Selection Operator (LASSO) has been proposed as a scheme capable to inversely estimate radioactive source distributions inside reactor building rooms from air dose rate measurements together with the predicted lower bound of the measurement numbers for successful reconstructions. However, no one has ever analyzed how the uncertainty of input data including the measurement errors influences the accuracy of the inverse estimation results. In this paper, we therefore perform uncertainty analysis of the LASSO scheme and suggest an uncertainty estimation function derived based on the theory of Candes. We actually demonstrate in two types of numerical tests with different input uncertainties obtained by using Monte Carlo code, Particle and Heavy Ion Transport code System (PHITS) that the calculated errors obey the proposed uncertainty estimation function. Thus, the LASSO scheme allows to successfully estimate radioactive distributions within the predicted uncertainty.

Effects of magnetic ordering on the ground-state energy of plutonium dioxide; A Study using adiabatic connection fluctuation-dissipation theory

Nakamura, Hiroki; Machida, Masahiko

Proceedings of 31st International Conference on Nuclear Engineering (ICONE31) (Internet), 5 Pages, 2024/11

https://doi.org/10.1115/ICONE31-134660

Efficiency and safety improvements in nuclear fuel development demand a comprehensive understanding of the thermal properties of PuO. Because of difficulty of experiments at high temperatures, they have been supplemented by numerical simulations, such as density functional theory (DFT). While DFT struggles to replicate the nonmagnetic insulating ground state of PuO, DFT+U can reproduce nonmagnetic insulating state. However, the obtained state remains less stable than magnetic states and is not the ground state. Adiabatic connection fluctuation-dissipation theory (ACFDT) is expected to be a promising solution, addressing higher-order correlations and exact exchange energies. In this study, we evaluate the ground state energy using ACFDT and find that the nonmagnetic state can be the ground state. This result successfully reproduces the observed nonmagnetic ground state of PuO and has the potential to improve predictions of the thermal properties of nuclear fuel materials.

R&D status of digital technology on inverse estimation of radioactive source distributions and related source countermeasures; Fast Digital Twin Tech. in Decommissioning Field: 3D-ADRES-Indoor FrontEnd

Machida, Masahiko; Yamada, Susumu; Kim, M.; Tanaka, Satoshi*; Tobita, Yasuhiro*; Iwata, Ayako*; Aoki, Yuto; Aoki, Kazuhisa; Yanagisawa, Kenichi*; Yamaguchi, Takashi; et al.

RIST News, (70), p.3 - 22, 2024/09

Inside the Fukushima Daiichi Nuclear Power Plant (1F), there are many locations with high radiation levels due to contamination by radioactive materials that leaked from the reactor. These pose a significant obstacle to the smooth progress of decommissioning work. To help solve this issue, the Japan Atomic Energy Agency (JAEA), under a subsidy from the Ministry of Economy, Trade, and Industry's decommissioning and contaminated water management project, is conducting research and development on digital technologies to improve the radiation environment inside the decommissioning site. This project, titled "Development of Technology to Improve the Environment Inside Reactor Buildings (Enhancing Digital Technology for Environment and Source Distribution to Reduce Radiation Exposure)," began in April of FY 2023. In this project, the aim is to develop three interconnected systems: FrontEnd, Pro, and BackEnd. The FrontEnd system, based on the previously developed 3D-ADRES-Indoor (prototype) from FY 2021-2022, will be upgraded to a high-speed digital twin technology usable on-site. The Pro system will carry out detailed analysis in rooms such as the new office building at 1F, while the BackEnd system will serve as a database to centrally manage the collected and analyzed data. This report focuses on the FrontEnd system, which will be used on-site. After point cloud measurement, the system will quickly create a 3D mesh model, estimate the radiation source from dose rate measurements, and refine the position and intensity of the estimated source using recalculation techniques (re-observation instructions and re-estimation). The results of verification tests conducted on Unit 5 are also presented. Furthermore, the report briefly discusses the future research and development plans for this project.

A Science-based mixed oxide property model for developing advanced oxide nuclear fuels

Kato, Masato; Oki, Takumi; Watanabe, Masashi; Hirooka, Shun; Vauchy, R.; Ozawa, Takayuki; Uwaba, Tomoyuki; Ikusawa, Yoshihisa; Nakamura, Hiroki; Machida, Masahiko

Journal of the American Ceramic Society, 107(5), p.2998 - 3011, 2024/05

https://doi.org/10.1111/jace.19609

Effectiveness of fused LASSO for prediction of distribution of radioactive materials in reactor buildings

Yamada, Susumu; Yoshida, Toru*; Hasegawa, Yukihiro*; Machida, Masahiko

Proceedings of Waste Management Symposia 2024 (WM2024) (Internet), 15 Pages, 2024/03

In order to safely carry out the decommission of reactor buildings, it is extremely important to identify the radiation source distribution. It has been reported that when the structural model of the building is constructed by uniform cells, the source distribution can be estimated from the measured air dose rates by minimizing an evaluation function using the Least Absolute Shrinkage and Selection Operator (LASSO). Moreover, if cells are non-uniform, we can estimate the distribution using the fused LASSO which minimizes the evaluation function that takes account of the connectivity between the adjacent cells. However, when a group of some cells is considered disconnected from the surrounding ones due to the precision of the measured structural data, the concentration of the group can be singularly high. Therefore, in order to avoid the problem, we propose a new evaluation function that can prevent the singularity. We estimated the distribution for the test model using the proposed evaluation function and confirmed the validity of the function. Moreover, we succeeded in estimating the source distribution in the pool canal circulation system room in JMTR in the Japan Atomic Energy Agency by the fused LASSO for the new function more accurately than previous analysis.

Uranium-plutonium-americium cation interdiffusion in polycrystalline (U,Pu,Am)O mixed oxides

Vauchy, R.; Matsumoto, Taku; Hirooka, Shun; Uno, Hiroki*; Tamura, Tetsuya*; Arima, Tatsumi*; Inagaki, Yaohiro*; Idemitsu, Kazuya*; Nakamura, Hiroki; Machida, Masahiko; et al.

Journal of Nuclear Materials, 588, p.154786_1 - 154786_13, 2024/01

https://doi.org/10.1016/j.jnucmat.2023.154786

Survey of air dose rate distribution inside and outside of wooden houses in Fukushima Prefecture; Actual condition of dose reduction factor

Kim, M.; Malins, A.*; Machida, Masahiko; Yoshimura, Kazuya; Saito, Kimiaki; Yoshida, Hiroko*

Nihon Genshiryoku Gakkai Wabun Rombunshi (Internet), 22(4), p.156 - 169, 2023/11

https://doi.org/10.3327/taesj.J23.001

Dose reduction factor of a Japanese house is important information in the external exposure estimation of returning residents. In 2019, a total of 19 wooden houses were surveyed in Iitate Village and Namie Town using a gamma plotter that can continuously measure the air dose rate. In addition, the characteristics of the reduction factor were investigated from the measured air dose rate. In the vicinity of houses, uncontaminated areas exist underneath houses and, the ratio of paved surfaces such as asphalt roads is relatively high; furthermore, the pavement has a tendency for the radiation source to decay quickly. Therefore, the air dose rate near the house showed a relatively low value in common at all sites. Air dose rates above unpaved surfaces showed higher values and larger variations than those above paved surfaces within a radius of 50 m form the center of a house. The reduction factor was widely distributed even for one house, if the ratio of every air dose rate observed inside and outside the house is considered. It is suggested that a realistic reduction factor may not be obtained when the reduction factor is obtained based on the measured values at a small number of points that do not have the representativeness of the radiation field to be measured.

Machine learning molecular dynamics reveals the structural origin of the first sharp diffraction peak in high-density silica glasses

Kobayashi, Keita; Okumura, Masahiko; Nakamura, Hiroki; Itakura, Mitsuhiro; Machida, Masahiko; Urata, Shingo*; Suzuya, Kentaro

Scientific Reports (Internet), 13, p.18721_1 - 18721_12, 2023/11

https://doi.org/10.1038/s41598-023-44732-0

The first sharp peak diffraction peak (FSDP) in the structure factor of amorphous materials is thought to reflect the medium-range order structure in amorphous materials, and the structural origin of the FSDP has been a subject of ongoing debate. In this study, we employed machine learning molecular dynamics (MLMD) with nearly first-principles calculation accuracy to investigate the structural origin of the FSDP in high-density silica glass. First, we successfully reproduced various experimental data of high-density silica glass using MLMD. Furthermore, we revealed that the development (or reduction) of the FSDP in high-density silica glass is characterized by the deformation behavior of ring structures in Si-O covalent bond networks under compression.

Inverse estimation scheme of radioactive source distributions inside building rooms based on monitoring air dose rates using LASSO; Theory and demonstration

Shi, W.*; Machida, Masahiko; Yamada, Susumu; Yoshida, Toru*; Hasegawa, Yukihiro*; Okamoto, Koji*

Progress in Nuclear Energy, 162, p.104792_1 - 104792_19, 2023/08

https://doi.org/10.1016/j.pnucene.2023.104792

Predicting radioactive source distributions inside reactor building rooms based on monitoring air dose rates is one of the most essential steps towards decommissioning of nuclear power plants. However, the attempt is rather a difficult task, because it can be generally mapped onto mathematically ill-posed problem. Then, in order to successfully perform the inverse estimations on radioactive source distributions even in such ill-posed conditions, we suggest that a machine learning method, least absolute shrinkage and selection operator (LASSO) minimizing the loss function, is a promising scheme. For the purpose of its feasibility demonstrations in real building rooms, we employ PHITS code to make LASSO input as the above matrix C connecting the radioactive source vector P defined on surface meshes of structural materials with the air dose rate vector Q measured at internal positions inside the rooms. We develop a mathematical criterion on the number of monitoring points to correctly predict source distributions based on the theory of Candes and Tao. Then, we confirm that LASSO actually shows extremely high possibility for source distribution reconstructions as far as the number of detection points satisfies our criterion. Moreover, we verify that radioactive hot spots can be truly reconstructed in an experiment setup. At last, we examine an influence factor like detector-source distance to enhance the predicting possibility in the inverse estimation. From the above demonstrations, we propose that LASSO scheme is a quite useful way to explore hot spots as seen in damaged nuclear power plants like Fukushima Daiichi nuclear power plants.

Promotive effects of siltfence on deposition of suspended particles; Evaluations of diffusion suppression of radionuclides in rectangular open channel via numerical simulations

Yamada, Susumu; Machida, Masahiko; Arikawa, Taro*

Nihon Genshiryoku Gakkai Wabun Rombunshi (Internet), 22(2), p.73 - 86, 2023/06

https://doi.org/10.3327/taesj.J21.028

no abstracts in English