Refine your search:     
Report No.
 - 
Search Results: Records 1-3 displayed on this page of 3
  • 1

Presentation/Publication Type

Initialising ...

Refine

Journal/Book Title

Initialising ...

Meeting title

Initialising ...

First Author

Initialising ...

Keyword

Initialising ...

Language

Initialising ...

Publication Year

Initialising ...

Held year of conference

Initialising ...

Save select records

Journal Articles

Optimizing long-term monitoring of radiation air-dose rates after the Fukushima Daiichi Nuclear Power Plant

Sun, D.*; Wainwright-Murakami, Haruko*; Oroza, C. A.*; Seki, Akiyuki; Mikami, Satoshi; Takemiya, Hiroshi; Saito, Kimiaki

Journal of Environmental Radioactivity, 220-221, p.106281_1 - 106281_8, 2020/09

 Times Cited Count:9 Percentile:43.42(Environmental Sciences)

We have developed a methodology for optimizing the monitoring locations of radiation air dose-rate monitoring. For the method, we use a Gaussian mixture model to identify the representative locations among multiple environmental variables, such as elevation and land-cover types. Next, we use a Gaussian process model to capture and estimate the heterogeneity of air-dose rates across the domain. Our results have shown that this approach allows us to select monitoring locations in a systematic manner such that the heterogeneity of air dose rates is captured by the minimal number of monitoring locations.

Journal Articles

Optimizing long-term monitoring of radiation air dose rates

Wainwright, Haruko*; Oroza, C.*; Sun, D.*; Seki, Akiyuki; Mikami, Satoshi; Saito, Kimiaki

45th Annual Waste Management Conference (WM 2019); Encouraging Young Men & Women to Achieve Their Goals in Radwaste Management, Vol.7, p.4346 - 4356, 2020/01

In this work, we have developed a methodology for optimizing the sampling locations of radiation air dose-rate monitoring. Three steps are taken in order to determine sampling locations in a systematic manner: (1) prioritizing the critical locations, such as schools or regulatory requirement locations, (2) diversifying locations across the key environmental controls that are known to influence contaminant mobility and distributions, and (3) capturing the heterogeneity of radiation air dose rates across the domain. Our results have shown that increasing the number of sampling locations can better capture the heterogeneity of dose rates, although the estimation error does not decrease further after a certain number of samples. We have also found that when there are restrictions such as pre-existing monitoring locations or the ones along roads, the spatial estimation becomes poor even with the same number of monitoring locations.

Oral presentation

Optimizing long-term monitoring of radiation air dose rates near the Fukushima Daiichi Nuclear Power Plant

Murakami, Haruko*; Sun, D.*; Oroza, C.*; Seki, Akiyuki; Mikami, Satoshi; Takemiya, Hiroshi; Saito, Kimiaki

no journal, , 

In this study, we have developed a methodology for optimizing the monitoring locations of radiation air dose rates. It is based on (1) a Gaussian mixture model to diversify locations across the key environmental controls that are known to influence cesium mobility and distributions, and (2) a Gaussian process model to capture the heterogeneity of radiation air dose rates across the domain.

3 (Records 1-3 displayed on this page)
  • 1