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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Global Positioning System (GPS) data are useful for understanding both interseismic and postseismic deformation. Models of GPS data suggest that the lower crust, lateral heterogeneity, and fault slip, all provide a role in the earthquake cycle.
The M7.1 Hector Mine earthquake ruptured the Lavic Lake fault near Twentynine Palms, CA at 09:46 UTC October 16, 1999.
Study of the September-October 1997 Umbria-Marche earthquakes that took place in Italy. Use joint inversion of GPS and SAR interferometry data.
The presentations explores kinematics of the Wenchaun-Beichuan earthquake using data from ALOS, Envisat, and teleseismic recordings. Topics include geomorphic mapping, ALOS PALSAR range offsets, ALOS PALSAR interferometry, Envisat IM interferometry, Envisat ScanSAR, Joint GPS-InSAR inversion, and joint GPS-teleseismic inversion (static and kinematic).
The locations of earthquakes with depth in the mantle provide direct evidence of the trajectory and state of stress of subducting lithosphere.
Geodetic time series detemined with the Global Positioning System indicate that the geodetic rate of a permanent site in Pasadena, Califonia (JPLM) changed significantly after the 17 January 1994 Northridge California earthquake.
We develop here a map of the coseismic displacement field resulting from the Landers, Ca., June 28, 1992 earthquake derived using data acquired from an orbiting high resolution radar system only,and achieve results more accurate than previous space studies and similar in accuracy to those obtained by conventional field survey techniques.
Global Positioning System (GPS) observations indicate that significant aseismic deformation occurred in the year following the January 17, 1994 Northridge earthquake.
Overview of Rock Valley Earthquake Relocation for the 2021 Nuclear Explosion Monitoring Program Review
Abstract The northwestern part of the Gulf of Mexico has undergone two episodes of continental rifting and collision and produced structural artifacts that are now buried under many kilometers of sediments, complicating investigations of the region. The deep sedimentary package precludes outcrops and points to a need for the application of seismic techniques, but low rates of seismicity in the region and sparse seismic monitoring limit the utility of traditional seismic methods. We therefore use diverse data to perform two‐dimensional seismic tomography across the dry land portion of the margin. Data are gleaned from teleseismic and regional earthquakes, postcritical SsPmp arrivals, and direct P wave energy identified with seismic interferometry that were recorded by a broadband, three‐component array and partially overlapping short‐period, vertical‐component array. The Pn and postcritical SsPmp phase help constrain the Moho discontinuity, which a previous receiver function study suggested was absent beneath the seaward portion of this transect. A high‐velocity body is observed in the crust at the same location as the Houston Magnetic Anomaly, possibly marking rocks from the Alleghenian continental assembly. The crust thins from NW to SE, indicating that extension occurred mostly to the south of the Ouachita orogeny. Our model indicates that the margin's sediment package reaches a maximum thickness of ~15 km at the coast and becomes unresolvably thin near the Llano Uplift.
We report that fault slip rates are critical to quantify continental deformation. Those along the Karakax fault (northwestern Altyn Tagh Fault: ATF) have been debated, even though it is one of Tibet's most outstanding active faults. At Taersa, using LiDAR measurements of terrace and fan riser offsets (~6 to ~500 m) and 10 Be/ 26 Al dating of alluvial surfaces (<210 ka), we obtain a late Quaternary slip rate of ~2.5 ± 0.5 mm/yr. This doubles the ~2.6 ± 0.5 mm/yr rate time span found to the east and west. We interpret the ~150 km-long, free-faced rupture along the fault to be that of the M ~ 7.6 event felt in Hotan in 1882. Characteristic slip (~6 m) during four large earthquakes since ~10 ka implies a ~2500 ± 500 years return time. A ~3 mm/yr rate is consistent with the ~80 km offset of the Karakax river since uplift of the West Kunlun range and sediment deposition in the Tarim foreland accelerated, ~24 Ma ago. The faster slip rate (~10.5 mm/yr) on the central ATF matches the sum of those along the reactivated West Tibetan terrane boundaries (Karakax and Longmu-Gozha Co faults) at the Uzatagh triple junction (~36°N, 83°E). The abrupt termination and altitude drop of the Karakorum range where the Longmu Co and Karakorum faults meet (Angmong junction), also reflect triple junction kinematics. Such localized changes account for the rise of the Karakorum and West Kunlun ranges and support lithospheric block tectonics rather than diffusely distributed deformation.
This paper combines the power of deep-learning with the generalizability of physics-based features, to present an advanced method for seismic discrimination between earthquakes and explosions. The proposed method contains two branches: a deep learning branch operating directly on seismic waveforms or spectrograms, and a second branch operating on physics-based parametric features. These features are high-frequency P/S amplitude ratios and the difference between local magnitude (ML) and coda duration magnitude (MC). The combination achieves better generalization performance when applied to new regions than models that are developed solely with deep learning. Further, we also examined which parts of the waveform data dominate deep learning decisions (i.e., via Grad-CAM). Such visualization provides a window into the black-box nature of the machine-learning models and offers new insight into how the deep learning derived models use data to make decisions.
Abstract High-voltage operation is essential for the energy and power densities of battery cathode materials, but its stabilization remains a universal challenge. To date, the degradation origin has been mostly attributed to cycling-initiated structural deformation while the effect of native crystallographic defects induced during the sophisticated synthesis process has been significantly overlooked. Here, using in situ synchrotron X-ray probes and advanced transmission electron microscopy to probe the solid-state synthesis and charge/discharge process of sodium layered oxide cathodes, we reveal that quenching-induced native lattice strain plays an overwhelming role in the catastrophic capacity degradation of sodium layered cathodes, which runs counter to conventional perception—phase transition and cathode interfacial reactions. We observe that the spontaneous relaxation of native lattice strain is responsible for the structural earthquake (e.g., dislocation, stacking faults and fragmentation) of sodium layered cathodes during cycling, which is unexpectedly not regulated by the voltage window but is strongly coupled with charge/discharge temperature and rate. Our findings resolve the controversial understanding on the degradation origin of cathode materials and highlight the importance of eliminating intrinsic crystallographic defects to guarantee superior cycling stability at high voltages.
Abstract Mechanical stress acting in the Earth’s crust is a fundamental property that is important for a wide range of scientific and engineering applications. The orientation of maximum horizontal compressive stress can be estimated by inverting earthquake source mechanisms and measured directly from borehole-based measurements, but large regions of the continents have few or no observations. Here we present an approach to determine the orientation of maximum horizontal compressive stress by measuring stress-induced anisotropy of nonlinear susceptibility, which is the derivative of elastic modulus with respect to strain. Laboratory and Earth experiments show that nonlinear susceptibility is azimuthally dependent in an anisotropic stress field and is maximum in the orientation of maximum horizontal compressive stress. We observe this behavior in the Earth—in Oklahoma and New Mexico, U.S.A, where maximum nonlinear susceptibility coincides with the orientation of maximum horizontal compressive stress measured using traditional methods. Our measurements use empirical Green’s functions and solid-earth tides and can be applied at different temporal and spatial scales.
This package contains the code for the paper Combining Deep Learning with Physics Based Features in Explosion-Earthquake Discrimination published at Geophysical Research Letters. There are two Jupyter notebooks, one for building and training the two-branch model, and the other is visualizing the deep learning branch using GradCAM.
This package contains the code for the paper Evaluating Physics Informed Neural Network Performance for Seismic Discrimination Between Earthquake published at Seismological Research Letters. There are one Jupyter notebook and demo data so that the audience can run build a machine learning model with the P/S ratios as a physics loss in addition to the data driven loss.t
The effects of the co-seismic static offset (known as fling step) and associated velocity pulses on civil structures have been difficult to study because the static offset is typically removed during the processing of earthquake ground motion records. Simulated ground motions contain fling features and require no processing; therefore, they create new opportunities for representing fling features in seismic hazard analysis and assessing their influence on the seismic demands on near-fault structures. We use physics-based fault rupture simulations to study the characteristics of ground motions with fling step and the sensitivity of the near-fault structural demands to strong fling features. We uncover that simulated ground motions with a large fling step tend to have higher spectral intensity than those without a fling step at the same rupture distance, especially at periods longer than 2 s. As a result, the structural demands on flexible buildings tend to be the most sensitive to the fling features. Statistical analysis suggests that the ground motion spectral shape (represented by spectral accelerations at multiple periods) is—in most cases—a sufficient predictor of the structural demands on near-fault low-rise and mid-rise buildings at locations that are susceptible to strong fling effects. Finally, ground motion record selection experiments reveal that representing the spectral shape features at periods that are most relevant to a given structure may be an effective strategy to reduce the bias in the estimated demands on near-fault long-period structures when the available database of records is considered deficient in fling features.
The nature of seismic sources for moderately large (moment magnitude, M w 5.0–6.5) events are commonly characterized by their moment tensor (MT) solutions and obtained by inversion of regional distance (200–1600 km) long‐period (20–50 s) waveforms. Regional MT estimates are often calculated from average plane‐layered, one‐dimensional (1D) velocity models. However, 1D model calculations can produce misfits in the arrival times and waveform shapes that introduce errors, particularly at longer distances or for shorter periods, which are necessary for analyzing lower magnitude events. Approximate Earth models (e.g., 1D) representing broad areas may be inadequate, particularly in the crust and uppermost mantle of tectonically complex regions. In this study, we show how a three‐dimensional (3D) Earth model obtained from full waveform inversion tomography can improve waveform fits and decrease phase errors. We developed a platform and workflow to perform routine 3D MT inversions and inverted MTs for 25 earthquakes in the western United States and seven nuclear explosions using an average 1D and a recent 3D Earth model, WUS256 (Rodgers et al., 2022). Using the 3D model improves waveform fits (variance reduction and phase time shifts) compared with the 1D model, and the 3D MT solutions are stable across large distances. This study shows that 3D models obtained from full waveform tomography can improve MTs and source characterization especially at far regional distances (>800 km).