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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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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

A synthetic seismicity model for the Middle America Trench

A novel iterative technique, based on the concept of fault segmentation and computed using 2D static dislocation theory, for building models of seismicity and fault interaction which are physically acceptable and geometrically and kinematically correct, is presented. The technique is applied in two steps to seismicity observed at the Middle America Trench. The first constructs generic models which randomly draw segment strengths and lengths from a 2D probability distribution. The second constructs predictive models in which segment lengths and strengths are adjusted to mimic the actual geography and timing of large historical earthquakes. Both types of models reproduce the statistics of seismicity over five units of magnitude and duplicate other aspects including foreshock and aftershock sequences, migration of foci, and the capacity to produce both characteristic and noncharacteristic earthquakes. Over a period of about 150 yr the complex interaction of fault segments and the nonlinear failure conditions conspire to transform an apparently deterministic model into a chaotic one.

Ward, Steven N.↗
NASA NTRSDate not supplied

The Stop-and-Go Mechanism: Towards an Integrated Approach to Model Seismicity, Outgassing, Deformation, and Thermal Unrest at Active Volcanoes

Connecting the geophysical and geochemical signals recorded at and above the surface of volcanoes with source mechanisms is fundamental to understand transitions from quiescence to eruption, and to integrate the behavior of volcanoes with their regional seismotectonic and hydrological context. Some of these signals include shallow volcanic tremor, a long-lasting (minutes-to-years) ground vibration detected in volcanic areas during unrest; volcanic outgassing, which shows intriguing periodicities over multiple scales, as revealed by space-borne instruments and by ground-based, high-frequency (~1 Hz), sampling methods; inflation and deflation of volcanic edifices, commonly associated with subsurface volume changes; and large-scale (from a few to tens of km2), low-temperature, thermal anomalies, a newly-discovered signal that has been observed to emerge on volcanic flanks from months-to-years prior to gas- and magma-driven eruptions. Traditionally, these geophysical and geochemical signals have been modelled independently, which limits our interpretation of subsurface processes and thus our assessment of unrest. In this work, we show through lumped-parameter models, numerical simulations, and preliminary laboratory experiments that many of the signals recorded around volcanoes can be integrated into a common “stop-and-go” mechanism. In particular, we found that they can arise spontaneously when taking into account the feedbacks between the temporary accumulation of gas and/or magma in the crust (“stop”), and the diffusive transfer of gas and heat towards the surface (“go”). For example, we find that the “stop-and-go” mechanism can explain: (i) the emergence of monochromatic, broadband, and harmonic tremor; (ii) the periodic components commonly observed in volcanic outgassing time series; (iii) the link between large-scale thermal anomalies and shallow hydrothermal systems; (iv) the reported time lags between large-scale thermal anomalies and deformation; and (v) the breathing of potentially destructive volcanic calderas. The “stop-and-go” mechanism provides a consistent and realistic framework to link multiple geophysical and geochemical signals with the processes leading to volcanic unrest and eruption.

volcanoes↗
DOE OSTI2024

Deep Learning for Full Waveform Inversion of Elastic Active-Source Seismic Data to Estimate P-Wave Velocity Models

Seismic imaging methods are critical for Global Security and Energy & Homeland Security missions and activities that rely on subsurface characterization, but traditional methods remain computationally expensive and require significant labor hours and expertise to execute. Within the past few years, machine learning (ML), namely deep learning (DL), has been used to develop data-driven end-to-end full waveform inversion (FWI) methods to estimate 2D P-wave velocity (Vp) models in a fraction of the time as conventional FWI. These methods, however, are trained on simplistic acoustic wave seismic data and Vp models that are not realistic nor representative of real-world observations, leaving a large gap between the state-of-the-art and deployable, feasible, and practical DL FWI methods. Here, we generate a synthetic active-source, 3D, elastic wave seismic data set and a variety of Vp models with realistic geologic structure for training DL FWI methods. We evaluate six different methods that have performed well for acoustic DL FWI or medical imaging tasks using our more realistic dataset. We find that these six trained models do not match the performance of published acoustic end-to-end DL FWI methods, indicating more training data may be needed, physics may need to be incorporated to achieve good accuracy at the sacrifice of the end-to-end advantage, and/or novel methods need to be developed to enable end-to-end DL FWI methods to perform well for real-world seismic data.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
NASA NTRS1978

The viscoelastic stiffness model of seismicity

A viscoelastic stiffness model of seismicity is developed by introducing a viscoelastic element into the stiffness model for fault dynamics. The introduction of this element permits modeling of transient anelastic deformations in response to stress loading and relaxation and provides a mechanism for partial stress recovery following an earthquake. As a consequence, several phenomena not present in elastic stiffness theory emerge. These include postseismic creep, foreshocks, and aftershocks. Numerical simulations of fault motion also reveal episodes of stable sliding, tertiary creep preceeding earthquakes, and long-term aseismic creep.

Cohen, S. C.↗
DOE OSTI2024

Utah FORGE: Composite 3D Seismic Velocity Model

This is a composite 3D seismic velocity that was constructed from compiled information from several local studies regarding seismic velocities and structural information. This seismic velocity model is provided in NonLinLoc format (slow_len), which is readily usable in NonLinLoc software. Other model formats and versions of the model can be produced using the Python script provided with this data set. Details on how the model was created and prior velocity and structural information was used is provided in the accompanying documentation.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Modeling of Seismic Waves Through Geologic Metamaterials

This project conducted a modeling study on seismic invisibility cloaks that render geologic targets invisible to seismic waves, using the concept of seismic metamaterials. We present a parametric numerical study on the behaviors of seismic waves through cloaks with different design parameters as well as degrees of geologic heterogeneity. In addition, a seismic cloaking strategy is proposed for a future field-scale experiment at a real-world test bed. This feasibility study will guide future field experiment designs and ultimately allow us to conduct systematic field-scale tests employing Sandia’s existing resources and field expertise. The ultimate goal is to develop methods and design parameters of seismic invisibility cloaks to protect against natural and man-made seismic waves. Seismic cloaking has potential applications in several areas of national security, energy, and natural hazard reduction.

58 GEOSCIENCES↗
NASA NTRS1994

Dynamical influences on the moment of inertia tensor from lateral viscosity variations inferred from seismic tomographic models

We have investigated the influences of lateral variations of viscosity on the moment of inertia tensor from viscous flows due to the density anomalies in the mantle inferred from seismic tomographic models. The scaling relations between the density and the seismic anomalies is taken as either a constant or a function increasing with depth in accord with the recent high-pressure experimental studies. The viscosity is taken as an exponential function of the 3D density anomaly. In models with an isoviscous background, the effects on the perturbed moment of inertia tensor from the lateral viscosity variations are smaller than those due to variations in the radial viscosity profiles. In mantle models with a background viscosity increasing with depth, the influences of the lateral viscosity variations are significant. The most striking feature in the latter case is that the two off-diagonal elements delta I(sub xz) and delta I(sub yz) in the inertia tensor exhibit greatest sensitivity to lateral variations of the viscosity. While the other elements of the inertia change by only about a few tens of percent in the range of lateral viscosity contrast considered (less than 300), delta I(sub xz) and delta I(sub yz) can vary up to 40 times even with a change in sign, depending on the radial viscosity stratification and the location of the strongest lateral variations. The increase in the velocity-density scaling relation with depth can reduce the influences of the lateral viscosity variations, but it does not change the overall sensitive nature of delta I(sub xz) and delta I(sub yz). This study demonstrates clearly that the lateral viscosity variations, especially in the upper mantle, must be considered in the determination of long-term polar wander, since the variations in the delta I(sub xz) and delta I(sub yz) terms are directly responsible for exciting rotational movements.

Zhang, Shuxia↗
DOE OSTI2025

Data-informed grid refinement to improve traveltime accuracy in the regional seismic traveltime (RSTT) model

The regional seismic traveltime (RSTT) model predicts traveltimes of regional seismic phases accounting for 3-D structure of the crust and the upper mantle on a global scale. Previous versions of the RSTT model have been implemented using nodes separated by ∼1° spacing across the globe. A regional-scale study using regional Pn and Pg traveltimes across Israel and the Middle East demonstrated that data driven, systematic grid refinement reduces traveltime residuals and enhances resolution of smaller tectonic features in regions having dense ray coverage. High density Pn ray coverage in the western US, Europe, Middle East and East Asia can likewise provide the resolution that allows systematic global grid refinement of the RSTT model. In this study, we use a large number of Pn ray paths originating from events located with an epicentral location uncertainty of 25 km (GT25) or better. We conduct targeted grid refinements at 1.0°, 0.5°, 0.25° and 0.125° on a global scale, producing a refined RSTT model that yields a 21.6 per cent reduction in median event location error in Europe and the Middle East, when compared with the original global RSTT model presented in Begnaud et al. The new model also resolves finer tectonic structures in regions with high Pn ray density.

58 GEOSCIENCES↗
DOE OSTI2024

Enhancing Regional Seismic Velocity Models With Higher‐Resolution Local Results Using Sparse Dictionary Learning

Abstract We use sparse dictionary learning to develop transformations between seismic velocity models of different resolution and spatial extent. Starting with data in the common region of both models, the method can enhance a regional lower‐resolution model to match the style and resolution of local higher‐resolution results while preserving its regional coverage. The method is demonstrated by applying it to two‐dimensional V S and three‐dimensional V P and V S regional and local velocity models in southern California. The enhanced reconstructed regional results exhibit clear visual improvements, especially in the reconstructed V P / V S ratios, and better correlations with geological features. Moreover, the reconstructed regional V P , V S models outperform the original ones in comparison of simulated earthquake waveforms to observations. The improved fitting to observed waveforms extends beyond the domain of the overlapping region. The developed dictionary learning approach provides physically interpretable results and offers a powerful tool for additional applications of data enhancement in earth sciences.

Geochemistry & Geophysics↗
DOE OSTI2024

The Collaborative Seismic Earth Model: Generation 2

Geological interpretations, earthquake source inversions and ground motion modeling, among other applications, require models that jointly resolve crustal and mantle structure. With the second generation of the Collaborative Seismic Earth Model (CSEM2), we present a global multi-resolution tomographic Earth model that serves this purpose. The model evolves through successive regional- and global-scale refinements. While the first generation aggregated regional models, with this study, we ensure consistency between all individual submodels, resulting in a model that accurately explains wave propagation across scales. Recent regional tomographic models were incorporated, comprising continental-scale inversions for Asia and Africa, as well as regional inversions for the Western US, Central Andes, Iran, and Southeast Asia. Across all regional refinements, over 793,000 source-receiver pairs contributed. Moreover, the long-wavelength Earth model (LOWE) introduces large-scale structures outside of pre-existing local refinements. A full-waveform inversion for global anisotropic P-and S-wave speed structure over a total of 194 iterations with a minimum period of 50 s on a large data set of 1 hr of waveform data from 2,423 earthquakes and over 6 million source-receiver pairs ensures that regional updates in the crust and uppermost mantle translate into updates of deeper, global-scale structure. To test the performance of CSEM2, we evaluate waveform fits between observed and synthetic seismograms at 50 s for an independent data set on the global scale, and on the regional scale for lower periods. We accurately simulate waveforms within and across regional refinements, maintaining the original resolution of the submodels embedded in the global framework.

58 GEOSCIENCES↗
DOE OSTI2024

Graph-learning approach to combine multiresolution seismic velocity models

SUMMARY The resolution of velocity models obtained by tomography varies due to multiple factors and variables, such as the inversion approach, ray coverage, data quality, etc. Combining velocity models with different resolutions can enable more accurate ground motion simulations. Toward this goal, we present a novel methodology to fuse multiresolution seismic velocity maps with probabilistic graphical models (PGMs). The PGMs provide segmentation results, corresponding to various velocity intervals, in seismic velocity models with different resolutions. Further, by considering physical information (such as ray path density), we introduce physics-informed probabilistic graphical models (PIPGMs). These models provide data-driven relations between subdomains with low (LR) and high (HR) resolutions. Transferring (segmented) distribution information from the HR regions enhances the details in the LR regions by solving a maximum likelihood problem with prior knowledge from HR models. When updating areas bordering HR and LR regions, a patch-scanning policy is adopted to consider local patterns and avoid sharp boundaries. To evaluate the efficacy of the proposed PGM fusion method, we tested the fusion approach on both a synthetic checkerboard model and a fault zone structure imaged from the 2019 Ridgecrest, CA, earthquake sequence. The Ridgecrest fault zone image consists of a shallow (top 1 km) high-resolution shear-wave velocity model obtained from ambient noise tomography, which is embedded into the coarser Statewide California Earthquake Center Community Velocity Model version S4.26-M01. The model efficacy is underscored by the deviation between observed and calculated traveltimes along the boundaries between HR and LR regions, 38 per cent less than obtained by conventional Gaussian interpolation. The proposed PGM fusion method can merge any gridded multiresolution velocity model, a valuable tool for computational seismology and ground motion estimation.

Geochemistry & Geophysics↗
NASA NTRS1988

Lunar composition - A geophysical and petrological synthesis

Lunar compositional constraints are derived on the basis of geophysical data (in particular, the lunar seismic model as revised by Nakamura) and petrological arguments. Only in the case of extreme assumptions can critical aspects of bulk lunar composition be demonstrated to be equivalent to the present-day terrestrial mantle; specifically, the moon has an Mg number that is too low and an alumina abundance that is too high. Over a broad range of crustal densities the presence of a metallic core at least 150 km in radius is necessary to reconcile the upper mantle lunar seismic model with mass and moment of inertia constraints. A significant seismic discontinuity at 500 km depth may mark the lowest extent of early lunar differentiation, possibly representing a transition between highly fractionated upper mantle and less fractionated, perhaps even primordial, middle/lower mantle.

Mueller, Steve↗
DOE OSTI2026

Seismic velocity modeling and earthquake relocations for the southern Nevada National Security Site (NNSS), with a focus on Rock Valley

The Rock Valley Direct Comparison (RV/DC) is the third phase of the Source Physics Experiment (SPE; Snelson et al., 2014), a project aimed at improving seismic discrimination between explosive sources and natural earthquakes. Phases I and II of SPE focused on studying the generation of shear waves in endmember geologies (granite and alluvium, respectively), while Phase III aims to detonate a chemical explosion co-located with the source region of the 1993 Rock Valley earthquake sequence, located in the Rock Valley Fault Zone (RVFZ), in the southern portion of the Nevada Test Site (now the Nevada National Security Site, or NNSS).

58 GEOSCIENCES↗