Engineering topics
Publications and source records attributed to Stead, Richard J..
The data sources tend to have the highest quality data and metadata, particularly for more recent data sets. Early data from sources such as IRIS tend to have some metadata issues.
SUMMARY An underground nuclear explosion (UNE) couples mechanical energy into crustal rock, which propagates as seismic and acoustic waves. These different physical phenomena transport, by different pathways, to standoff detectors at varying distances. The transport pathways attenuate the original signal but in different ways. Enabled by correct statistical weighting, signal attenuation models can be used to combine these disparate sensor data to estimate the yield of an UNE. Contemporaneous statistical models, used in yield estimation, can be improved with an advanced partition of error for these physical signal propagation models. We present an advanced multivariate approach to error modelling of multiphenomenology physical signatures. In addition to measurement error, our error model represents physical model biases as random with a physics-based covariance structure. To illustrate this proposed framework, we demonstrate the estimation of explosion yield using openly available seismic and acoustic data from chemical single-point explosions.
Transportability, yield and discrimination questions were addressed and a new model method described.
With an intense work ethic, and high levels of devotion to their craft, seismologists continue to battle the elements and wrestle with complex logistics in their efforts to field instrumentation over the entire globe. We are fortunate to see data volumes accelerating in size, and quality continuing to improve; for example, universal timing issues can now be considered rare. However, instrument response issues are still common, and can hinder research that seeks to understand amplitudes of seismic wavefields. We are interested in using the accumulations of seismic data to develop models that will predict high frequency (0.2-20 Hz, and higher) signal amplitudes for explosion monitoring purposes over broad areas, which requires large data sets and extensive quality control. To identify response and station health issues, we have collected noise time histories for global seismic data, focusing on measurements near (but not restricted to) midnight to eliminate diurnal variations, and have manually determined time intervals that appear inconsistent with background behavior. We assign descriptive labels, but do not attempt to diagnose causes. We use these intervals to discard data. To date, we have examined 39,260 channels from 11,105 stations, heavily weighted toward IRIS holdings, dates through 2017 (depending on station, roughly the date we started our manual review), bands between 1 and 8 Hz, finding 24,733 anomalous time intervals. The great majority (90%) of these intervals appear to be shifts of constant offset, often bounded by times of known instrument changes, likely the result of poor documentation of response parameters at one of many stages between the field and the plotter. We hope these results can be of use to our colleagues, and would encourage community efforts to diagnose anomalous behavior, and fix poor responses. We also hope these results will support automation efforts, including application of supervised learning techniques.
In 1996, negotiations between the National Nuclear Center of the Republic of Kazakhstan (NNC), the U.S. Defense Special Weapons Administration (DSWA) and the U.S. Department of Energy led to an agreement for a joint series of experiments at the former Soviet nuclear test site Semipalatinsk (STS). These experiments had a dual purpose: to close holes and tunnels originally created for the purpose of testing nuclear weapons, and to characterize explosive sources at a former nuclear test site. This report covers the recovery of legacy data from the experiments conduct in 1997 and 1998. Two teams collected data. Los Alamos National Laboratory (LANL), in collaboration with the NNC, collected the near-source (local) data out to approximately 20 km. Lamont-Doherty Earth Observatory (LDEO), with funding from Lawrence Livermore Laboratory (LLNL), also in collaboration with NNC, collected regional data, 200 – 1000 km distant, leveraging the KZ regional seismic network that LDEO had recently installed in collaboration with NNC. The two teams also worked together to some extent, regarding instrumentation and planning. This report primarily addresses the near-source data collected by the LANL/NNC team.