Using Waveform Cross Correlation for Detection, Location, and Identification of Aftershocks of the 2017 Nuclear Explosion at the North Korea Test Site
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An outline of a Bayesian source location framework for using seismic and acoustic observations is developed and tested on synthetic and real data. Seismic and acoustic phenomena are both commonly used in detection and location of a variety of natural or man–made events, such as volcanic eruptions, quarry blasts, and military exercises. Typically, seismic and acoustic observations have been utilized independently of each other. Here, we outline a Bayesian formulation for combining the two observations in a single estimate of the location and origin time. Using realistic estimates of uncertainty, we subsequently explore how combining the different observation types can benefit event location at local to near–regional distances. We apply the method to synthetic data and to real observations from a mining blast in Bingham Mine in Utah. Our findings suggest that, for relatively sparse or azimuthally limited observations, the relative strengths of the two different phenomenologies enable more precise joint–event localization than either seismic or infrasonic measurements alone.
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A validation study is performed using the hydrodynamics code PAGOSA to assess the accuracy of reflected shock, burn front propagation, and Photon Doppler Velocimetry (PDV) predictions using several burn models and strength models. Experimental data collected from proton radiography (pRad) is compared to burn front propagation times and reflected shock patterns. Burn front isochrones are computed and the lag time for the burn front is quantified for a given burn model. The effect of strength models and damage are assessed by comparison of simulations to experimental PDV data.
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Assessing impact of high-altitude electromagnetic pulses (HEMP) resulting from the effects of nuclear weapons is a problem of great concern. Some previous studies have estimated the extent and duration of an outage to be severe. In this report, we quantify the extent and duration of an outage resulting from HEMP E1 to the best of our ability given existing knowledge and tools. Our analysis focuses on the impact to civilian consumer of electricity as opposed to the impact on military responsiveness.
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SURF is an acronym for Scaled-Unified-Reactive-Front, invented by R. Menikoff and S. Shaw. What follows is a brief synopsis of this model as used for the validation study discussed here. For more details see the xrage user manual and the references cited there.
GW170817 demonstrated the potential of GW+EM observations of NS mergers: most direct observation of r-process production to date. But what can we really learn from the observations. Getting from the observations to constraining properties of the merger ejecta requires multiple aspects of simulation (merger, disk calculations, and radiation flow) and physics (atomic, nuclear cross-section, dense nuclear matter, neutrino, …). Can we maximize what we can do with observations.
With a brilliant hot flash and a loud boom, the giant mushroom cloud with its fiery core filled the predawn sky above the New Mexico desert. The nuclear age had begun. It was 75 years ago on July 16, 1945, that Los Alamos scientists changed the world with the successful detonation of “the Gadget” – the device created to test the Fat Man implosion-type plutonium weapon before it was taken into combat. However, the road to Trinity, as the test was named by J. Robert Oppenheimer, who is thought to have been inspired by a line in a John Donne poem, was a difficult one.
Advanced reactive burn models enable phenomena to be modeled that aren’t possible with programmed burn. Programmed burn propagates a burn front at a prescribed speed from a prescribed initiation point. Reactive burn uses the hydro variables (pressure, temperature, etc.) to determine when, how rapidly, and to what extent a zone detonates. This enables a completely new set of problems to be simulated. Our goal in this milestone has been to improve the usability of reactive burn modes. Thus, the closure criteria are: 1. Perform code and solution verification of the reactive burn models using appropriate solutions and simplified HE setups. 2. Perform validation assessments using small-scale experiments. 3. Evaluate sensitivities and quantify uncertainties due to model form variations and mesh dependencies.
On June 30, 2020, a 0.87 gram PETN charge being pressed in the Rapid Prototyping Facility (RPF), unexpectedly initiated, resulting in destruction of the pressing fixture but no injuries or facility damage. In response, the Safety Review Board (SRB) met on Aug. 13, 2020 and Oct. 1, 2020 to review information collected following the incident, consider likely direct causes, and form recommendations.