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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 - PowerPoint PPT Presentation
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Analysis of the C-10 Research and Education Foundation
Dataset
Presented by Norman ShippeePlymouth 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 VIII. References and
Acknowledgements
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
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
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
The CRMN
NH
MA
10KM
Seabrook Station
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
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
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)
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
Filtering Missing Data Flags
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
Yearly Cycle
Short period cycle
Station 01 Spectral Analysis
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
Comparison of Spectral Analysis
Radiation
V ComponentU Component
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
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
The CRMN
NH
MA
10KM
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
Stations and Maximum Correlations
Station Number Wind Direction Maximum Correlation
04 340° 11.4%
09 100° 12.8%
24 120° 9.23%
28 100° 3.24%
Correlation of 0.2% is statistically significant
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
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
Positive Lags(Radiation
Follows Wind)
Negative Lags(Radiation
Leads Wind)
Predicted Results
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
References and Acknowledgements
Dr. Samuel T.K. Miller, Research Advisor
Ms. Sandra Gavutis, Executive Director of C-10
Plymouth State University JGMI
Matthew Bedard