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.

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.

LASSO reconstruction scheme to predict radioactive source distributions inside reactor building rooms; Theory & demonstration

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

Proceedings of Waste Management Symposia 2023 (WM2023) (Internet), 8 Pages, 2023/02

Thermal behavior, structure, dynamic properties of aqueous glycine solutions confined in mesoporous silica MCM-41 investigated by X-ray diffraction and quasi-elastic neutron scattering

Yoshida, Koji*; Inoue, Takuya*; Torigoe, Motokatsu*; Yamada, Takeshi*; Shibata, Kaoru; Yamaguchi, Toshio*

Journal of Chemical Physics, 149(12), p.124502_1 - 124502_10, 2018/09

https://doi.org/10.1063/1.5039892

Differential scanning calorimetry, X-ray diffraction, and quasi-elastic neutron scattering (QENS) measurements of aqueous glycine solutions confined in mesoporous silica (MCM-41) were performed at different glycine concentrations, pH, and loading ratio (= mass of glycine solution / mass of dry MCM-41) in the temperature range from 305 to 180 K to discuss the confinement effect on the thermal behavior, the structure, and the dynamic properties of the solutions.

Natural circular dichroism of amino acid films observed in soft X-ray and VUV region using polarizing undulator

Nakagawa, Kazumichi*; Kaneko, Fusae*; Ota, Yoshimi*; Tanaka, Masahito*; Kitada, Tomo*; Agui, Akane; Fujii, Kentaro; Yokoya, Akinari; Watanabe, Kazutoshi*; Yamada, Toru*

Journal of Electron Spectroscopy and Related Phenomena, 144-147, p.271 - 273, 2005/06

https://doi.org/10.1016/j.elspec.2005.01.189

no abstracts in English

Development of the novel maintenance conservation method for infrastructures by using the laser technology

Hasegawa, Noboru*; Nishikino, Masaharu*; Mikami, Katsuhiro*; Okada, Hajime*; Kondo, Shuji*; Kawachi, Tetsuya*; Shimada, Yoshinori*; Kurahashi, Shinri*; Kitamura, Toshiyuki*; Kotyaev, O.*; et al.

no journal, , 

no abstracts in English

Development of exposure reduction technologies by digitalization of environment and radioactive source distribution, 2; R&D of engines for radioactive source reconstruction, air dose rate estimation, and their visualization

Machida, Masahiko; Shi, W.*; Yamada, Susumu; Miyamura, Hiroko; Numata, Yoshiaki*; Sato, Tomoki*; Tobita, Yasuhiro*; Yoshida, Toru*; Yanagi, Hideaki*; Furutachi, Naoya*; et al.

no journal, , 

no abstracts in English