Real-time inversion of radioactive source distribution using air dose rate measurements via least absolute shrinkage and selection operator method

Shi, W.*; Machida, Masahiko; Okamoto, Koji*; Luo, X.*; Feng, W.*; Liu, X.*

Reliability Engineering & System Safety, 272, Part1, p.112538_1 - 112538_18, 2026/08

http://doi.org/10.1016/j.ress.2026.112538

The reliability of emergency response in severe nuclear accidents critically depends on robust real-time monitoring of radioactive source distributions. However, this safety function is challenged by physical constraints that create monitoring blind spots and by the inadequacy of static methods in tracking dynamic releases. To enhance the reliability and robustness of source term estimation, this study proposes a dynamic reconstruction framework based on LASSO regression with temporal regularization. A sliding-window time-penalty mechanism is introduced, imposing -norm constraints on inter-step source variations to ensure physical continuity. The contribution matrix and measurement vector are normalized to counteract biases from radiation shielding and time-varying intensities. Validation using a two-room model with internal shielding, with PHITS Monte Carlo simulation, demonstrates accurate reconstruction of dynamic sources from remote measurements. Temporal regularization enhances situational awareness by suppressing spatial aliasing: at sliding-window width (no regularization), hotspot locations fluctuate significantly, with quantitative mean absolute error fluctuations at around , whereas yields improved spatial consistency and the fluctuation quantities decrease to the range. Comparative analysis identifies as optimal in balancing accuracy and computational cost. This work establishes a more reliable pathway for dynamic hazard assessment, enabling accurate localization and intensity tracking under challenging conditions. The proposed framework provides a decision-support tool enhancing the resilience and safety of emergency management in nuclear facilities.

Annual report of Engineering Services Department on JFY2024

Engineering Services Department, Nuclear Science Research Institute

JAEA-Review 2026-011, 97 Pages, 2026/06

JAEA-Review-2026-011.pdf:4.39MB

The Engineering Services Department is in charge of operation and maintenance of utility facilities (water distribution systems, electricity supply systems, steam generation systems and drain water systems etc.) in whole of the institute. Furthermore, it also oversees the operation and maintenance of specific systems (power receiving and transforming facilities, an emergency electric power supply system, an air/liquid waste treatment system, a compressed air supply system) in nuclear reactor facilities, nuclear fuel material usage facilities and usual facilities or buildings. In addition, the department is in charge of maintenance of buildings, design and repair of electrical/mechanical equipment. This annual report describes summary of activities, operation and maintenance data and technical developments of the department carried out in JFY 2024. We hope that this report may help to future work.

Development of LASSO based optimized scheme for reconstructing radioactive source distributions using monitoring air dose rates

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

Measurement, 258(Part D), p.119444_1 - 119444_15, 2026/01

https://doi.org/10.1016/j.measurement.2025.119444

Development of reconstruction method of void distribution for ultrasonic tomography using a machine learning algorithm

Kojima, Yuya*; Murakawa, Hideki*; Sugimoto, Katsumi*; Kondo, Teppei*; Abe, Yuta; Aizawa, Kosuke

Proceedings of 13th International Symposium on Measurement Techniques for Multiphase Flows (ISMTMF 2025) (Internet), 5 Pages, 2025/10

Annual report of Engineering Services Department on JFY2023

Engineering Services Department, Nuclear Science Research Institute

JAEA-Review 2025-018, 83 Pages, 2025/09

JAEA-Review-2025-018.pdf:4.99MB

The Engineering Services Department is in charge of operation and maintenance of utility facilities (water distribution systems, electricity supply systems, steam generation systems and drain water systems etc.) in whole of the institute. And also is in charge of operation and maintenance of specific systems (power receiving and transforming facilities, an emergency electric power supply system, an air/liquid waste treatment system, a compressed air supply system) in nuclear reactor facilities, nuclear fuel material usage facilities and usual facilities or buildings. In addition, the department is in charge of maintenance of buildings, design and repair of electrical/mechanical equipment. This annual report describes summary of activities, operation and maintenance data and technical developments of the department carried out in JFY 2023. We hope that this report may help to future work.

Experimental study of two-phase flow in a four-by-four unheated rod bundle for validation of thermal-hydraulics simulation codes

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.

Two-group drift-flux model for upward cap-bubbly two-phase flows in large square channels

Sun, Haomin; Hibiki, Takashi*

International Journal of Heat and Mass Transfer, 237, p.126445_1 - 126445_14, 2025/02

https://doi.org/10.1016/j.ijheatmasstransfer.2024.126445

Quantifying uncertainty induced by scattering angle distribution using maximum entropy method

Maruyama, Shuhei; Yamamoto, Akio*; Endo, Tomohiro*

Annals of Nuclear Energy, 205, p.110591_1 - 110591_13, 2024/09

https://doi.org/10.1016/j.anucene.2024.110591

Study on cavitation damage evolution influenced by input power

Wakui, Takashi; Takagishi, Yoichi*; Futakawa, Masatoshi

Zairyo, 73(6), p.520 - 526, 2024/06

https://doi.org/10.2472/jsms.73.520

Cavitation damage is one of crucial issues to predict the structural endurability of the mercury targets for highly intensive pulsed neutron sources. Based on the comparison with numerical simulation on the pit shape and results of the basic test, the cavitation bubble collapsing was assumed to be resulted in the micro jet with the impact velocity of 160-200 m/s, imposing then impact pressure of 3-4 GPa at the input power simulating the operation condition in the mercury targets. It was statistically understandable that cavitation damage evolution was proportional to 4th power of the input power approximately, as taking the aggressivity of cavitation bubbles, the distribution of the maximum diameter of grown bubbles and the space of distribution of bubbles in the mercury into account.

Estimation of continuous distribution of iterated fission probability using an artificial neural network with Monte Carlo-based training data

Tuya, D.; Nagaya, Yasunobu

Journal of Nuclear Engineering (Internet), 4(4), p.691 - 710, 2023/11

https://doi.org/10.3390/jne4040043

The Monte Carlo method is used to accurately estimate various quantities such as k-eigenvalue and integral neutron flux. However, when a distribution of a quantity is desired, the Monte Carlo method does not typically provide continuous distribution. Recently, the functional expansion tally and kernel density estimation methods have been developed to provide continuous distribution. In this paper, we propose a method to estimate a continuous distribution of a quantity using artificial neural network (ANN) model with Monte Carlo-based training data. As a proof of concept, a continuous distribution of iterated fission probability (IFP) is estimated by ANN models in two systems. The IFP distributions by the ANN models were compared with the Monte Carlo-based data and the adjoint angular neutron fluxes by the PARTISN code. The comparisons showed varying degrees of agreement or discrepancy; however, it was observed that the ANN models learned the general trend of the IFP distributions.