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Analysis of the C-10 Research and Education Foundation Dataset

Analysis of the C-10 Research and Education Foundation Dataset. Presented by Norman Shippee Plymouth State University Advisor: Dr. Samuel T.K. Miller. Overview. I. About C-10 II. History of C-10 III. Monitoring Network IV. The Dataset VI. Data Analysis VII. Results and Discussion

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Analysis of the C-10 Research and Education Foundation Dataset

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  1. Analysis of the C-10 Research and Education Foundation Dataset Presented by Norman Shippee Plymouth State University Advisor: Dr. Samuel T.K. Miller

  2. Overview • I. About C-10 • II. History of C-10 • III. Monitoring Network • IV. The Dataset • VI. Data Analysis • VII. Results and Discussion • VIII. References and Acknowledgements

  3. About C-10 • Established in 1991 • Non-profit organization • Mission is to monitor potential radiological emissions from the Seabrook nuclear reactor in southeastern New Hampshire

  4. About C-10 • Operates and maintains the Citizens Radiological Monitoring Network (CRMN) • Partially funded by State of Massachusetts • 25 automated monitoring stations, mounted on homes, schools, and businesses

  5. About C-10 • Stations record temperature, wind, and radiological data once per minute • Average horizontal spacing is consistent with a small meso-γ (2 – 20 km) or a large microscale (< 2 km) network

  6. The CRMN NH Seabrook Station MA 10KM

  7. The CRMN Dataset • The dataset consists of minute-by-minute observations of: • Ionizing radiation (two channels) • Wind (direction and speed) • Air temperature • Data set length: July 1996 – Jan 2007 • Average Data set length: 7 years

  8. The CRMN Dataset • Average file contains 3.15 million lines of data • The length of the dataset allows for detection of very small variations with 95 percent confidence

  9. Problems encountered • The C-10/REF dataset is very large (total of ~2.5 GB for all .txt files) • Impossible to read entire unified files into computer memory • Necessary to use creative programming to better utilize memory (e.g. reading and writing simultaneously)

  10. Analysis and Results • Main Goal of Research • To subject the meteorological and radiological data recorded by C-10’s Citizens Radiological Monitoring Network to rigorous scientific analysis

  11. Filtering Missing Data Flags

  12. Results • First, completing spectral analysis of the station data sets for the radiation allowed us to look for certain patterns in the data • Yearly cycle • Longer period cycles • Shorter period cycles

  13. Station 01 Spectral Analysis Short period cycle Yearly Cycle

  14. Spectral Analysis • Here we see a yearly peak outlined in the previous figures of radiation spectra. This is most visible in the analysis of linear scaling • We also see a smaller peak in the radiation continuum around the value of 11.5 hours. This peak shows up in the data set in multiple stations • Looking for possible solutions, we tried to compare with the U and V component of the wind for a possible 11.5 hr cycle

  15. Comparison of Spectral Analysis Radiation U Component V Component

  16. Spectral Analysis • As the short period peak could be seen in the U and V components of the wind, we decided to attempt to find the direction of the wind that had the most correlation with radiation values • U and V component were then converted into directions from 010 to 360

  17. Correlation of Wind and Radiation • Wind in U and V components was broken into 10 degree increments about the compass • These increments were then cross-correlated with the radiation data • Correlation of 0.2% is statistically significant

  18. The CRMN NH MA 10KM

  19. Correlation of Wind and Radiation • Following figures depict the correlation series of the wind around the compass • Direction of maximum correlation is consistent with the direction that the wind is blowing towards

  20. Stations and Maximum Correlations Correlation of 0.2% is statistically significant

  21. Correlations with Time Lags • Stations 24 and 09 showed maximum positive correlations with winds from the WNW and W respectively • Time lag analysis shows that a time lag of -11 hours for station 24 and -5 hours for station 09 • This means that the radiation leads the wind, or highest levels of radiation occur before the wind from the specified direction

  22. Correlations with Time Lags • Stations 28 and 04 showed maximum positive correlations with winds from the W and SSE respectively • Time lag analysis shows that a time lag of +11 hours for both stations 28 and 04 • This means that the radiation follows the wind, or highest levels of radiation occur after the wind from the specified direction

  23. Predicted Results Negative Lags (Radiation Leads Wind) Positive Lags (Radiation Follows Wind)

  24. Summary • Spectral analysis shows recurring peaks in the radiation and wind data at yearly and about 12 hour intervals • Correlations of radiation and wind data show a clockwise turning of the wind vectors with maximum correlations from west to east • Time lags seem to be positive to the more inland stations and negative for the coastal stations

  25. References and Acknowledgements • Dr. Samuel T.K. Miller, Research Advisor • Ms. Sandra Gavutis, Executive Director of C-10 • Plymouth State University JGMI • Matthew Bedard

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