Uncertainty and sensitivity analyses for the reduction factor of sheltering for radiation exposures

Hirouchi, Jun; Takahara, Shogo; Komagamine, Hiroshi*

Journal of Radiological Protection, 42(4), p.041503_1 - 041503_12, 2022/12

https://doi.org/10.1088/1361-6498/aca0ff

Sheltering is one of the countermeasures against radiation exposure during nuclear accidents. The effectiveness of sheltering for inhalation exposure is often expressed by the reduction factor, which is defined as the ratio of the indoor to the outdoor cumulative radioactivity concentrations or doses. The indoor concentration is mainly controlled by the air exchange rate, penetration factor, and indoor deposition rate. Meanwhile, the air exchange rate depends on surrounding environmental conditions: the wind speed, leakage area normalized by the floor area of the house, and gross building coverage ratio. In this study, the ranges of the uncertainty of the reduction factors for particles and I were investigated under various environmental conditions, and sensitivity analyses were conducted to understand the parameter with the most influence on the uncertainty of the reduction factor. From the results of the uncertainty analyses, the calculated reduction factor was highly variable depending on the environmental condition and the airtightness of the houses. The uncertainty ranges of the reduction factor for particles and I were up to 0.9 and 0.3, respectively, and were smaller for newer houses. From the results of the sensitivity analyses, the wind speed was the most influential parameter on the reduction factor. Additionally, the wind speed was less influential for the reduction factor in newer houses.

K setting approaches for rocks for the performance assessment of geological disposal; Application for granitic rocks

Tachi, Yukio; Suyama, Tadahiro*; Shibutani, Sanae*

Genshiryoku Bakkuendo Kenkyu (CD-ROM), 24(2), p.109 - 133, 2017/12

https://doi.org/10.3327/jnuce.24.2_109

For performance assessment (PA), the distribution coefficient (K) need to be determined taking into account the specific PA conditions, including geochemical variability or uncertainty. The K setting approach for rocks was developed by integrating three methods; (i) direct use of measured K data extracted from the sorption database, (ii) semi-quantitative estimation by scaling differences between experimental and PA conditions, and (iii) thermodynamic sorption models. This approach was tested for granitic rock by comparing K values and their uncertainties of Cs and Am. The results indicated that K can be quantitatively evaluated by all approaches when adequate data and models are available. The K dataset for safety-relevant 25 radionuclides was developed based on the direct use of measured data, and compared with the recent K dataset in European PA projects. This K setting approaches allowed to estimate the K values and their uncertainties under the expected site conditions.

Nuclide migration uncertainty study in channel network model approximation

; *

JNC TN8400 2001-010, 25 Pages, 2001/03

JNC-TN8400-2001-010.pdf:4.4MB

Performance assessment in geosphere for the JNC's 2nd progress report was based on nuclide migration calculation results by discrete fracture network model. The channel network model approximated from fracture network model with considering fracture connectivity was applied for nuclide migration analysis, since fracture network model had too large data to calculate nuclide migration. However, there are many options in the process of approximation from fracture network model to channel network model. In case of analyzing nuclide migration for above report, so-called "base case", one option was chosen from many options, arbitrarily. In this report, the sensitivity of these options to nuclide migration calculation results was studied. As a result, there was no significant impact to nuclide migration although connectivity of channel and flow characteristics of the model slightly changed among different options. Based on above studies, we concluded that an option used for the base case was appropriate.

None

Takeda, Seietsu; ; ; Nakatsuka, Noboru; Nakano, Katsushi; ; Ishimaru, Tsunenori

JNC TN7410 2000-003, 65 Pages, 2000/11

JNC-TN7410-2000-003.pdf:5.09MB

None

*; Fusaeda, Shigeki*

JNC TJ1400 2000-004, 245 Pages, 2000/02

JNC-TJ1400-2000-004.pdf:8.57MB

no abstracts in English

None

*; *; *; *; Morooka, Koichi*; *

JNC TJ1400 99-025, 483 Pages, 1999/02

JNC-TJ1400-99-025.pdf:20.57MB

no abstracts in English

None

Tsujimura, Norio; Shinohara, Kunihiko; Momose, Takumaro

PNC TN8510 98-001, 13 Pages, 1998/07

PNC-TN8510-98-001.pdf:0.63MB

None

None

PNC TJ1281 96-005, 75 Pages, 1996/03

PNC-TJ1281-96-005.pdf:2.97MB

None

None

PNC TJ1222 95-005, 552 Pages, 1995/03

PNC-TJ1222-95-005.pdf:19.35MB

None

Seismic fragility evaluation of nuclear power plants based on bayesian inference

Yamaguchi, Akira

PNC TN9410 94-070, 51 Pages, 1994/02

PNC-TN9410-94-070.pdf:2.09MB

Seismic fragilities of equipment and systems are evaluated in a seismic probabilistic safety analysis (PSA). The seismic fragility is defined as the failure probability and its uncertainty at various ground acceleration levels. One evaluates the seismic fragility efficiently by making most use of available information in the seismic PSA. This study is related to a Bayesian inference method to reflect the information to the seismic fragility evaluation. Information that can be used in the Bayesian inference is (1)seismic experience data, (2)expert judgment on the seismic fragility, (3)seismic test data. The generic fragility database was used as the prior fragility that was to be updated. The acceleration level of the seismic experience and test data is much lower than the median value of the seismic capacity level of equipment. However, it is useful to cut down the lower tail of the fragility curves thus the modeling uncertainty. As the results, it is has been found that the annual frequency of failure that is calculated by the convolution of the fragility with seismic hazard curves is reduced considerably. Furthermore, the author has proposed the concept of entropy to quantify the value of the information used in the Bayesian inference. The combined use of the Bayesian inference and the entropy is a useful method to propose a cost-effective seismic test for the fragility evaluation. Findings obtained from the seismic PSA are taken into consideration in achieving more reasonable safety design. It should be noted that the findings are strongly affected by the uncertainty. Hence the reduction is necessary of the uncertainty of the contributive equipment from the viewpoint of seismic safety. Specific analysis and test of the contributive equipment is an effective way of reducing the uncertainty.