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Goodwin, M.

Publications and source records attributed to Goodwin, M..

A multi-Physics Experiment for Low-Yield Nuclear Explosion Monitoring

A series of multi-physics experiments, referred to as Physics Experiment 1 (PE1) is underway at the United States’ Nevada National Security Site (NNSS). The PE1 series includes detonations of three underground chemical explosions in P-tunnel, with fully coupled (PE1 A), partially decoupled (PE1 D L ), and fully decoupled (PE1 B) emplacements. Canisters with gas tracers are imbedded in the explosives, and the tracers are released when the canister is destroyed by the detonation. A dedicated electromagnetic (EM) experiment (EMX) generates well-characterized EM signals at an underground location near the chemical explosive experiments. A series of atmospheric experiments (METEX, REACT, and METREX) release smoke and radioactive tracers around Aqueduct Mesa to test gas transport in complex topography. Each of the chemical explosive experiments includes a network of sensors to record seismic, acoustic, and electromagnetic waves, measurement of atmospheric conditions, and air sample collection for measurement of tracer concentration. EMX records EM signals underground and on the surface of Aqueduct Mesa. METEX, REACT, and METREX include measurement of atmospheric condition, as well as tracking smoke releases. REACT and METREX add low-level radioactive gas tracers to the atmospheric releases.

58 GEOSCIENCES↗

Third international challenge to model the medium- to long-range transport of radioxenon to four Comprehensive Nuclear-Test-Ban Treaty monitoring stations

In 2015 and 2016, atmospheric transport modeling challenges were conducted in the context of the Comprehensive Nuclear-Test-Ban Treaty (CTBT) verification, however, with a more limited scope with respect to emission inventories, simulation period and number of relevant samples (i.e., those above the Minimum Detectable Concentration (MDC)) involved. Therefore, a more comprehensive atmospheric transport modeling challenge was organized in 2019. Stack release data of Xe-133 were provided by the Institut National des Radioéléments/IRE (Belgium) and the Canadian Nuclear Laboratories/CNL (Canada) and accounted for in the simulations over a three (mandatory) or six (optional) months period. Best estimate emissions of additional facilities (radiopharmaceutical production and nuclear research facilities, commercial reactors or relevant research reactors) of the Northern Hemisphere were included as well. Model results were compared with observed atmospheric activity concentrations at four International Monitoring System (IMS) stations located in Europe and North America with overall considerable influence of IRE and/or CNL emissions for evaluation of the participants’ runs. Participants were prompted to work with controlled and harmonized model set-ups to make runs more comparable, but also to increase diversity. It was found that using the stack emissions of IRE and CNL with daily resolution does not lead to better results than disaggregating annual emissions of these two facilities taken from the literature if an overall score for all stations covering all valid observed samples is considered. A moderate benefit of roughly 10% is visible in statistical scores for samples influenced by IRE and/or CNL to at least 50% and there can be considerable benefit for individual samples. Effects of transport errors, not properly characterized remaining emitters and long IMS sampling times (12–24 h) undoubtedly are in contrast to and reduce the benefit of high-quality IRE and CNL stack data. Complementary best estimates for remaining emitters push the scores up by 18% compared to just considering IRE and CNL emissions alone. Despite the efforts undertaken the full multi-model ensemble built is highly redundant. An ensemble based on a few arbitrary runs is sufficient to model the Xe-133 background at the stations investigated. The effective ensemble size is below five. An optimized ensemble at each station has on average slightly higher skill compared to the full ensemble. However, the improvement (maximum of 20% and minimum of 3% in RMSE) in skill is likely being too small for being exploited for an independent period.

54 ENVIRONMENTAL SCIENCES↗