Nuclear explosion monitoring network design considerations

Abstract

Design of an efficient monitoring network requires information on the type and size of releases to be detected, the accuracy and reliability of the measuring equipment, and the desired network performance. This work provides a scientific basis for optimizing or minimizing networks of 133Xe samplers to achieve a desired performance level for different levels of release. The approach of this work varies the density of sampling locations to find optimal location subsets, and to explore the properties of variations of those subsets – how crucial is a specific subset; are substitutions problematic? The choice of possible station locations is arbitrary but constrained to some extent by the location of islands, land masses, difficult topography (mountains, etc.) and the places where infrastructure exists to run and support a sampler. Performance is evaluated using hypothetical releases and atmospheric transport models that cover an entire year.Three network performance metrics are calculated: the probability of detecting the releases, the expected number of stations to detect the releases, and the expected number of samples that detect the releases. The quantitative measures support picking optimal or near-optimal network of a specific station density. If a detection probability of 90% (high) was desired for a design basis release of 1014 Bq (1% of 133Xe production from a 1 kt explosion), then a very high density would be required using today's sampling and measurement technology. If the design basis release were raised to 1015 Bq, then the station density could be lowered by a factor of 3. To achieve a location goal of three station detections on average, posited here for the first time, would also require very high station density for a release of 1014 Bq.