Modeling the Effects of Meteorological Conditions on the Neutron Flux
Abstract
The neutron background at sea level is seen to vary by as much as 20 within a 24 hour period. These short term variations are primarily driven by environmental factors. Radiation sensors detect a signal in a noisy background, so the variation of the background must be understood for sensors to be effective. Neutron sensors are used in the search for transported materials that can be used to make a nuclear weapon. The purpose of this project was to develop a statistical model that predicts environmental neutron background as a function of five meteorological variables: inverse barometric pressure, temperature, local humidity, precipitation, and cloud cover. Neutron data were collected using moderated 3He neutron detection systems located in Annapolis, MD. Data collected using a large neutron sensor in Annapolis show the neutron background varying from 13, 000 counts per hour to 9, 000 counts per hour, a 20 variation, over five months of data collection with large variation between days. Meteorological data were collected with two commercially available weather stations in Annapolis, MD along with sensors installed at a nearby airport. Synchronization of the weather and neutron data was an important part of this study and dictated the time interval that could be chosen for the modeling process. Linear autoregression was used to estimate the effects of the meteorological variables on neutron flux while accounting for the correlation among errors at previous time intervals. The dominant variable of the model was inverse barometric pressure with a contribution an order of magnitude larger than any other variables contribution. The resulting model can predict neutron background with errors of a predictable magnitude.
Document Details
- Document Type
- Technical Report
- Publication Date
- May 22, 2017
- Accession Number
- AD1036652
Entities
People
- Thomas J Wilson