3D Orthorhombic Earth Model Effects on Seismic Source Characterization.
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Presented by NETL at the 43rd International Technical Conference on Clean Energy, 6/18
In this paper, a Bayesian approach is applied to the estimation of source characteristics for above ground explosive events using infrasonic observations at propagation distances of hundreds of kilometers. Propagation-based, stochastic path geometry models have previously been investigated for infrasonic source localization with promising results; here, statistical transmission loss models are investigated using archived atmospheric specifications and propagation simulation tools to demonstrate that such an approach is applicable to source characterization. The resulting transmission loss models models are utilized in estimating near-source spectral characteristics for explosive events from infrasonic observations at regional distances of several hundred kilometers or more using a Bayesian framework to compute a combined estimate. The near-source spectral characterization can be used along with a simplistic explosive source model to compute an estimate of explosive yield with quantifiable uncertainty. Finally, the yield estimation framework is evaluated using above-ground explosive events from the western US during the fall of 2012 with promising results.
Seismic source characterization is an essential function of global nuclear explosion monitoring (NEM). While large events (roughly with moment magnitude, M w , greater than 5.0) can often be easily detected, located and identified with high signal-to-noise ratios at teleseismic distances (> 20°), trends in NEM research require confident source characterization at much lower magnitudes (say down to 3.0) and exploitation of sparse observations (from only a few stations) at regional distance (< 20°). Regional distance waveform inversion to characterize sources is now widely used and effective (e.g. Ford et al., 2009; Alvizuri and Tape, 2018; Alvizuri et al., 2018; Chiang et al., 2018; Ford et al., 2022). These methods obtain the magnitude, depth and seismic moment tensor, which represents the forces that excited the observed seismic waves (slip on an earthquake fault, explosion, collapse or a combination of various forces). Common to many problems in seismology, the isolation of the source 2 properties requires removal of path propagation effects that waves experience while traveling through the three-dimensional (3D) Earth (the structure exists due to different rock types, material properties, temperature and tectonic processes).
Characterizing glycans is analytically challenging since glycans are heterogeneous, branched polymers with different three-dimensional conformations. Hydrogen/deuterium exchange-mass spectrometry (HDX-MS) has been used to analyze native conformations and dynamics of biomolecules by measuring the mass increase of analytes as labile protons are replaced with deuterium following exposure to deuterated solvents. The rate of exchange is dependent on the chemical functional group, the presence of hydrogen bonds, pH, temperature, charge, and solvent accessibility. HDX-MS of carbohydrates is challenging due to the rapid exchange rate of hydroxyls. Here, we describe an observed HDX reaction associated with residual solvent vapors saturating electrospray sources. When undeuterated melezitose was infused after infusing D{sub 2}O, samples with up to 73% deuterium exchange were detected. This residual solvent HDX was observed for both carbohydrates and peptides in multiple instruments and dependent on sample infusion rate, infusion time, and deuterium content of the solvent. This residual solvent HDX was observed over several minutes of sample analysis and persisted long enough to alter the measured deuterium labeling and possibly change the interpretation of the results. This work illustrates that residual solvent HDX competes with in-solution HDX for rapidly exchanging functional groups. Thus, we propose conditions to minimize this effect, specifically for top-down, in-electrospray ionization, and quench-flow HDX experiments. .
The objective of our study is to analyze the performance of characterized heterogeneous rupture models in simulations of near-fault ground motion from the M7 Kumamoto, Japan earthquake, using Graves and Pitarka (2016) broad-band simulation method. We developed a kinematic earthquake rupture generator that combines the Graves and Pitarka (2016) (GP2016) rupture model with the multiple asperity characterized rupture model of Irikura and Miyake (IM2011), also known as Irikura recipe (Irikura and Miyake, 2011). The proposed kinematic rupture model incorporates distinct features of both original rupture models such as small-scale stochastic rupture variability, and shallow areas with large slip separated from areas with high sliprate, inherited from the GP2016, and desired near-fault large-scale rupture directivity effects produced by the multiple asperity model IM2011.
In this work, experimental data, together with interpretive modeling tools, are examined to study trends in the tungsten (W) source in the all-W environment of the WEST tokamak, both from the divertor and from the main chamber. In particular, a poloidal limiter protecting an ion cyclotron resonance heating (ICRH) antenna is used as proxy for main chamber sourcing. The key study is carried out by stepping up lower hybrid current drive (LHCD) power, as the only auxiliary power source. Limiter and divertor W sources exhibit a qualitatively similar proportionality to the total power crossing the separatrix, P SEP , although the main chamber source remains substantially lower than the divertor source, for the range of P SEP accessible in the experiments. Intepretive modeling of the limiter source is carried out with a particle-in-cell (PIC) sheath model coupled to a surface sputtering model. Oxygen is used as a proxy for all light impurity species allowing for characterization of the critical W erosion regions. To get a good quantitative match to the data, it is necessary to assume that the oxygen arrives at the surface mostly at high ionization stages (4+ and above). A separate simulation with SOLEDGE-EIRENE, constrained to measured upstream scrape-off-layer plasma profiles, gives oxygen fractional abundances that are compatible with the PIC simulation result. This is understood to arise from transport processes that dominate over recombination. Substituting the LHCD by ICRH, in an equivalent experiment, the local W source exhibits a 3× enhancement. This can be matched by the simulation, by assuming local RF electric field rectification, based on ~100 eV peak-to-peak, near-antennna electric field. This work has highlighted the particular importance of understanding the ion charge state balance of light impurities as these are most likely the dominant sputtering species in fusion devices with high-Z walls.
X-ray calorimeters routinely achieve very high spectral resolution, typically a few eV full width at half maximum (FWHM). Measurements of calorimeter line shapes are usually dominated by the natural linewidth of most laboratory calibration sources. This compounds the data acquisition time necessary to statistically sample the instrumental line broadening and can add systematic uncertainty if the intrinsic line shape of the source is not well known. To address these issues, we have built a simple, compact monochromatic x-ray source using channel cut crystals. A commercial x-ray tube illuminates a pair of channel cut crystals that are aligned in a dispersive configuration to select the Kα1 line of the x-ray tube anode material. The entire device, including the x-ray tube, can be easily hand-carried by one person and may be positioned manually or using a mechanical translation stage. The output monochromatic beam provides a collimated image of the anode spot with magnification of unity in the dispersion direction (typically 100 μm–200 μm for the x-ray tubes used here) and is unfocused in the cross-dispersion direction so that the source image in the detector plane appears as a line. We measured output count rates as high as 10 count/s/pixel for the Hitomi soft x-ray spectrometer, which had 819 μm square pixels. We implemented different monochromator designs for energies of 5.4 keV (one design) and 8.0 keV (two designs), which have effective theoretical FWHM energy resolution of 0.125 eV, 0.197 eV, and 0.086 eV, respectively; these are well-suited for optimal calibration measurements of state-of-the art x-ray calorimeters. We measured an upper limit for the energy resolution of our Cr Kα1 monochromator of 0.7 eV FWHM at 5.4 keV, consistent with the theoretical prediction of 0.125 eV.
The Subsurface Tunnel Imaging LeveraGed by Analysis of Rayleigh wave ellipticity (STILGAR) project demonstrated an integrated geophysical approach for detecting, locating, and characterizing underground structural changes using dense seismic arrays and advanced inversion techniques. Field campaigns were conducted at two operational mines—the Redmond salt mine (Utah) and Graymont Pleasant Gap limestone mine (Pennsylvania)—providing real-world testbeds for monitoring anthropogenic subsurface activity. At the Redmond salt mine, seismic interferometry combined with back-projection inversion successfully identified continuous, low-amplitude signals from mining operations. The approach differentiated stationary from migrating anthropogenic sources, captured daily operational cycles, and validated the potential of passive seismic monitoring for remote detection of underground activity. At the Graymont Pleasant Gap mine, two dense seismic deployments in the spring and fall of 2023 generated over 4 TB of high-resolution data. Key outcomes included the relocation of 199 underground and 8 surface explosions with accuracies within tens of meters and the development of a 3D P-wave velocity model using the triple-difference tomography algorithm (tomoTD) that resolved major structural features such as the mine entrance, low-velocity tunnels, and roof-collapse areas. Ambient noise cross-correlation and back-projection analyses revealed persistent sources linked to ongoing mining activity, whereas horizontal-to-vertical spectral ratio (HVSR) and ellipticity studies confirmed stable site responses across seasons and identified soil thickness trends consistent with regional erosional and depositional processes. Checkerboard and sensitivity tests further validated the robustness of the tomographic results. Overall, the findings emphasize that although significant progress has been made in subsurface imaging, further work is needed to enhance the detection and localization of underground structures. Accurate imaging requires higher frequencies, yet anthropogenic sources tend to dominate the seismic record at those frequencies, and high-frequency surface waves are affected by higher modes that complicate interpretation. The improved detection and localization of human-induced signals enabled detailed temporal and spatial mapping of daily mine operations, demonstrating the feasibility of continuous anthropogenic source monitoring. Sensitivity to signals from nontraditional sources, such as fan operations, highlights the broader applicability of this approach to other industrial environments in which continuous and impulsive signals are present. The field campaigns produced a substantial volume of high-quality seismic data, supporting the development and testing of new methods for seismic source characterization and subsurface imaging. Future deployments should include sensors capable of recording lower frequencies to probe deeper structures, increase bandwidth to enhance resolution and sensitivity to both shallow and deep targets, and collect additional large-scale datasets to refine imaging and source characterization techniques. Moreover, conducting 3D modeling studies of seismic wavefields at higher frequencies will provide a better understanding of wave scattering and cavity–wavefield interactions in complex underground environments. In conclusion, the STILGAR project demonstrated that integrated seismic monitoring can effectively characterize underground operations, capturing both natural and anthropogenic signals. The approaches developed provide a foundation for improved detection, localization, and imaging of subsurface structures and are directly transferable to broader industrial monitoring applications.
Dirty bombs are considered one of the easiest forms of radiological terrorism, a form of terrorism based on the deliberate use of radiological material to cause adverse effects in a target population. One U.S. Government official has even described a dirty bomb attack as “all but inevitable”. While people in the vicinity of the blast may experience acute radiation effects, people downwind may unknowingly be contaminated by the radioactive airborne particulate and face increased long-term cancer risk. The likelihood of increased cancer risk depends on the radionuclide used and its specific activity, its aerosolization potential, the particle sizes generated in the blast, and where a person is with respect to the detonation. Different studies have reported that plausible radionuclides for dirty bomb include 60 Co, 90 Sr, 137 Cs, 192 Ir, 241 Am based on their availability in commercial sources as well as safeguards, the amount needed for adverse health effects, previous mishandling of radionuclides and malicious uses. In order to have increased long-term cancer risk, the radionuclide would have to deposit inside the body by entering the respiratory tract and then possibly migrate to other organs or bones (ground shine is not considered in this paper because areas affected by the event will likely become inaccessible). This implies that the particles will have to be smaller than 10 μm to be inhaled. Experiments involving the detonation of dirty bombs have shown that particles or droplets smaller than 10 μm are generated, independently from the initial radionuclide or its state (e.g., powder, solution). Atmospheric tests have shown that in unobstructed terrain, the radionuclide laden cloud can travel kilometers downwind even for relatively small amounts of explosives. Furthermore, buildings in the path of the cloud can change the dose rate. For instance, in one experiment with a single building, the dose rate was 1–2 orders of magnitude lower behind the obstacle compared to its front face. For people walking around, the amount of particulate deposited on them and inhaled will depend on their path relative to the cloud, resulting in the counterintuitive result that the closer people may actually not be the ones more at risk because they could simply miss the bulk of the cloud in their wandering. In summary, the long-term cancer risk for people caught in a dirty bomb cloud away from the detonation requires considering where and when the people are, which radionuclide was used, and the layout of the obstacles (e.g., buildings, vegetation) in the path of the cloud.
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Wide Pedestal QH-mode (WPQH) plasmas in the DIII-D tokamak show a sheath limited SOL, where electron density and temperature remain nearly constant along field lines from the midplane to the divertor. Consequently, parallel gradients are weak. The first Langmuir probe measurements in this regime point to a high sheath temperature with target electron temperature T e up to ~150 eV, leading to high carbon self-sputtering. Midplane carbon densities from SOLPS-ITER modeling of these plasmas in a double-null configuration fall far below experimental measurements unless full drifts are activated. In the drift-dependent SOLPS-ITER modeling, anomalous poloidally uniform, radially varying transport is adjusted to match measured radial electron temperature and density profiles in the pedestal and SOL region. The resulting carbon density (C6+) matches measured carbon densities just inside the separatrix. The C2+ density near the outer strike point is also consistent with spectroscopic imaging. With the ion B×∇B drift towards the X-point, carbon in the lower divertors is redistributed from the private flux region to the high field side (HFS) and pushed upstream in the SOL by poloidal E×B drifts. The B × ∇B drift dominates the radial flow of carbon as it moves upstream. Simulations with reversed toroidal field (ion B × ∇B drift away from the X-point) show a radically different behavior, where carbon accumulates on the low field side in lower divertors, and is pushed towards the HFS in the upper divertors, indicating a strong effect of particle drifts on impurity distribution. In double-null configurations which are usually used in WPQH plasmas, these drift effects tend to counterbalance, so that the carbon density and Z eff are reduced at the outer mid-plane only modestly, by around 7% in the modeling. Further predictive modeling indicates that the carbon density can be significantly reduced by an order of magnitude by implementing a single-null shape with reversed toroidal field.
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Abstract. Ice-nucleating particles (INPs) initiate primary ice formation in Arctic mixed-phase clouds (MPCs), altering cloud radiative properties and modulating precipitation. For atmospheric INPs, the complexity of their spatiotemporal variations, heterogeneous sources, and evolution via intricate atmospheric interactions challenge the understanding of their impact on microphysical processes in Arctic MPCs and induce an uncertain representation in climate models. In this work, we performed a comprehensive analysis of atmospheric aerosols at the Arctic coastal site in Ny-Ålesund (Svalbard, Norway) from October to November 2019, including their ice nucleation ability, physicochemical properties, and potential sources. Overall, INP concentrations (NINP) during the observation season were approximately up to 3 orders of magnitude lower compared to the global average, with several samples showing degradation of NINP after heat treatment, implying the presence of proteinaceous INPs. Particle fluorescence was substantially associated with INP concentrations at warmer ice nucleation temperatures, indicating that in the far-reaching Arctic, aerosols of biogenic origin throughout the snow- and ice-free season may serve as important INP sources. In addition, case studies revealed the links between elevated NINP and heat lability, fluorescence, high wind speeds originating from the ocean, augmented concentration of coarse-mode particles, and abundant organics. Backward trajectory analysis demonstrated a potential connection between high-latitude dust sources and high INP concentrations, while prolonged air mass history over the ice pack was identified for most scant INP cases. The combination of the above analyses demonstrates that the abundance, physicochemical properties, and potential sources of INPs in the Arctic are highly variable despite its remote location.
Abstract A self‐potential (SP) data‐inversion algorithm was developed and tested on an analytical model of electrical‐potential profile data attributed to single and multiple polarized electrical sources. The developed algorithm was then validated by an application to SP‐monitoring field data measured on the floodplain of East Fork Poplar Creek, Oak Ridge, Tennessee, to image electrical sources in areas conducive to preferential flow into the flood plain from the bedrock‐lined riverbed. The algorithm combined stochastic source‐localization by particle‐swarm‐optimization (PSO) of electrical sources characterized by simplified geometries with source tomography by regularized weighted least‐squares minimization of a quadratic objective function. Prior information was incorporated by preconditioning the tomography algorithm by PSO results. Variable percentages of random noise were added to analytical‐model data to evaluate the algorithm performance. Results indicated that true parameters of single‐source models were inverted and approximated with small residual error, whereas inversion of analytical‐model data representing multiple electrical sources accurately approximated the locations of the sources but miscalculated some parameters because of the non‐uniqueness of the inverse‐model solution. Source tomography applied to analytical model data during testing produced a spatially continuous parameter field that identified the locations of point‐scale synthetic dipole sources of electrical current flow with varying degrees of accuracy depending on the prior information incorporated into the tomography. When applied to SP‐monitoring field data, the algorithm imaged electrical sources within a known fault that intersects the bedrock riverbed and flood plain of East Fork Poplar Creek and depicted dynamic electrical conditions attributed to hyporheic exchange.
We conduct X-ray spectral fits on 184 likely counterparts to Fermi-LAT 3FGL unassociated sources. Characterization and classification of these sources allows for more complete population studies of the high-energy sky. Most of these X-ray spectra are well fit by an absorbed power-law model, as expected for a population dominated by blazars and pulsars. A small subset of seven X-ray sources have spectra unlike the power law expected from a blazar or pulsar and may be linked to coincident stars or background emission. We develop a multiwavelength machine learning classifier to categorize unassociated sources into pulsars and blazars using gamma-ray and X-ray observations. Training a random forest (RF) procedure with known pulsars and blazars, we achieve a cross-validated classification accuracy of 98.6%. Applying the RF routine to the unassociated sources returned 126 likely blazar candidates (defined as P {sub bzr} ≥ 90%) and five likely pulsar candidates (P {sub bzr} ≤ 10%). Our new X-ray spectral analysis does not drastically alter the RF classifications of these sources compared to previous works, but it builds a more robust classification scheme and highlights the importance of X-ray spectral fitting. Our procedure can be further expanded with UV, visual, or radio spectral parameters or by measuring flux variability.