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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

Analysis of seismic body waves excited by the Mount St. Helens eruption of May 18, 1980

Seismic body waves which were excited by eruption of Mt. St. Helens, and recorded by the Global Digital Seismographic Network (GDSN) stations are analyzed to determine the nature and the time sequence of the events associated with the eruption. The polarity of teleseismic P waves (period 20 sec) is identical at six stations which are distributed over a wide azimuthal range. This observation, together with a very small S to P amplitude ratio (at 20 sec), suggests that the source is a nearly vertical single force that represents the counter force of the eruption. The time history of the vertical force suggests two distinct groups of events, about two minutes apart, each consisting of several subevents with a duration of about 25 sec. The magnitude of the force is approximately 2.6 to the 17th power dyne. This vertical force is in contrast with the long period (approximately 150 sec) southward horizontal single force which was determined by a previous study and interpreted to be due to the massive landslide. Previously announced in STAR as N83-15968

Kanamori, H.↗
DOE OSTI2024

Probing the evolution of fault properties during the seismic cycle with deep learning

We use seismic waves that pass through the hypocentral region of the 2016 M6.5 Norcia earthquake together with Deep Learning (DL) to distinguish between foreshocks, aftershocks and time-to-failure (TTF). Binary and N-class models defined by TTF correctly identify seismograms in test with > 90% accuracy. We use raw seismic records as input to a 7 layer CNN model to perform the classification. Here we show that DL models successfully distinguish seismic waves pre/post mainshock in accord with lab and theoretical expectations of progressive changes in crack density prior to abrupt change at failure and gradual postseismic recovery. Performance is lower for band-pass filtered seismograms (below 10 Hz) suggesting that DL models learn from the evolution of subtle changes in elastic wave attenuation. Tests to verify that our results indeed provide a proxy for fault properties included DL models trained with the wrong mainshock time and those using seismic waves far from the Norcia mainshock; both show degraded performance. Our results demonstrate that DL models have the potential to track the evolution of fault zone properties during the seismic cycle. If this result is generalizable it could improve earthquake early warning and seismic hazard analysis.

58 GEOSCIENCES↗
DOE OSTI2025

The Role of Dislocations in the Anelasticity of the Upper Mantle

Dislocation‐based dissipation mechanisms potentially control the viscoelastic response of Earth's upper mantle across a variety of geodynamic contexts, including glacial isostatic adjustment, postseismic creep, and seismic‐wave attenuation. However, there is no consensus on which dislocation‐based, microphysical process controls the viscoelastic behavior of the upper mantle. Although both intergranular (plastic anisotropy) and intragranular (backstress) mechanisms have been proposed, there is currently insufficient laboratory data to discriminate between those mechanisms. Here, we present the results of forced‐oscillation experiments in a deformation‐DIA apparatus at confining pressures of 3–7 GPa and temperatures of 298–1370 K. Our experiments tested the viscoelastic response of polycrystalline olivine—the main constituent of the upper mantle—at stress amplitudes from 70 to 2,800 MPa. Mechanical data are complemented by microstructural analyses of grain size, crystallographic preferred orientation, and dislocation density. We observe amplitude‐ and frequency‐dependent attenuation and modulus relaxation and find that numerical solutions of the backstress model match our results well. Therefore, we argue that interactions among dislocations, rather than intergranular processes (e.g., plastic anisotropy or grain boundary sliding), control the viscoelastic behavior of polycrystalline olivine in our experiments. In addition, we present a linearized version of the constitutive equations of the backstress model and extrapolate it to conditions typical of seismic‐wave propagation in the upper mantle. Our extrapolation demonstrates that the backstress model can explain the magnitude of seismic‐wave attenuation in the upper mantle, although some modification is required to explain the weak frequency dependence of attenuation observed in nature and in previous experimental work.

Hein, Diede [Univ. of Minnesota, Minneapolis, MN (↗
DOE OSTI2026

owl

O4921: Open Wave Library for seismic wave modeling and FWI

Gao, Kai [Los Alamos National Laboratory]↗
NASA NTRS1985

On the relative scattering of P- and S-waves

Using a single-scattering approximation, equations for the scattering attenuation coefficients of P-body and S-body waves are derived. The results are discussed in the light of the energy-renormalization approaches of Wu (1980, 1982) and Sato (1982) to seismic wave scattering. Practical methods for calculating the scattering attenuation coefficients for various earth models are emphasized. The conversions of P-waves to S-waves and S-waves to P-waves are included in the theory. The earth models are assumed to be randomly inhomogeneous, with their properties known only through their average-wavenumber power spectra. The power spectra are approximated with piecewise constant functions, each segment of which contributes to the net frequency-dependent scattering attenuation coefficient. The smallest and largest wavenumbers of a segment can be plotted along with the wavevectors of the incident and scattered waves on a wavenumber diagram. This diagram gives a geometric interpretation for the frequency behavior associated with each spectral segment, including a transition peak that is due entirely to the wavenumber limits of the segment. For regions of the earth where the inhomogeneity spectra are concentrated in a band of wavenumbers, it should be possible to observe such a peak in the apparent attenuation of seismic waves. Both the frequency and distance limits on the accuracy of the theoretical results are given.

Malin, P. E.↗
NASA NTRS1976

Lunar seismic profiling experiment natural activity study

The Lunar Seismic Experiment Natural Activity Study has provided a unique opportunity to study the high frequency (4-20 Hz) portion to the seismic spectrum on the moon. The data obtained from the LSPE was studied to evaluate the origin and importance of the process that generates thermal moonquakes and the characteristics of the seismic scattering zone at the lunar surface. The detection of thermal moonquakes by the LSPE array made it possible to locate the sources of many events and determine that they are definitely not generated by astronaut activities but are the result of a natural process on the moon. The propagation of seismic waves in the near-surface layers was studied in a qualitative manner. In the absence of an adequate theoretical model for the propagation of seismic waves in the moon, it is not possible to assign a depth for the scattering layer. The LSPE data does define several parameters which must be satisfied by any model developed in the future.

Duennebier, F. K.↗
NASA NTRS2012

Seismic Imager Space Telescope

A concept has been developed for a geostationary seismic imager (GSI), a space telescope in geostationary orbit above the Pacific coast of the Americas that would provide movies of many large earthquakes occurring in the area from Southern Chile to Southern Alaska. The GSI movies would cover a field of view as long as 300 km, at a spatial resolution of 3 to 15 m and a temporal resolution of 1 to 2 Hz, which is sufficient for accurate measurement of surface displacements and photometric changes induced by seismic waves. Computer processing of the movie images would exploit these dynamic changes to accurately measure the rapidly evolving surface waves and surface ruptures as they happen. These measurements would provide key information to advance the understanding of the mechanisms governing earthquake ruptures, and the propagation and arrest of damaging seismic waves. GSI operational strategy is to react to earthquakes detected by ground seismometers, slewing the satellite to point at the epicenters of earthquakes above a certain magnitude. Some of these earthquakes will be foreshocks of larger earthquakes; these will be observed, as the spacecraft would have been pointed in the right direction. This strategy was tested against the historical record for the Pacific coast of the Americas, from 1973 until the present. Based on the seismicity recorded during this time period, a GSI mission with a lifetime of 10 years could have been in position to observe at least 13 (22 on average) earthquakes of magnitude larger than 6, and at least one (2 on average) earthquake of magnitude larger than 7. A GSI would provide data unprecedented in its extent and temporal and spatial resolution. It would provide this data for some of the world's most seismically active regions, and do so better and at a lower cost than could be done with ground-based instrumentation. A GSI would revolutionize the understanding of earthquake dynamics, perhaps leading ultimately to effective warning capabilities, to improved management of earthquake risk, and to improved public safety policies. The position of the spacecraft, its high optical quality, large field of view, and large field of regard will make it an ideal platform for other scientific studies. The same data could be simply reused for other studies. If different data, such as multi-spectral data, is required, additional instruments could share the telescope.

Sidick, Erkin↗
NASA NTRS1965

Shear-wave detection

Angular accelerometers and transducers compared in detection of seismic waves and shear waves

TRANSDUCER↗
NASA NTRS1989

Neutron starquakes and the nature of gamma-ray bursts

The possibility that gamma-ray bursts originate from quakes deep in the solid crust of a neutron star is investigated. Seismic waves are radiated if shear stress is relieved by brittle fracture. However they cannot propagate directly to the surface but are temporarily trapped below a reflecting layer. The shaking of the stellar surface couples the seismic waves to Alfven waves which propagate out into the magnetosphere. The crust-magnetosphere transmission coefficient strongly increases with wave frequency and magnetic field strength. Alfven wave luminosities sufficient to power galactic gamma-ray bursts are possible if magnetic fields greater than 100 billion G cover at least part of the stellar surface. As the Alfven waves propagate out into the low density magnetosphere, they become increasingly charge starved, thereby accelerating particles to relativistic energies.

Madau, P.↗
NASA NTRS1977

Internal structure and properties of Mars

Theoretical physical models of the Martian interior are presented in the light of recent and revised data and constraints. These models include thermal evolution, densities, and seismic-wave velocities. The interior of Mars appears to be earthlike in many respects. Although thermal models indicate that Mars has passed its peak of evolution, it may still have an asthenosphere and may be moderately active tectonically. Mars has an Fe-FeS core with a radius of 1500-2000 km. The mantle is enriched in FeO with an olivine composition of about Fo75. Theoretically determined seismic-wave velocities are relatively well constrained in the mantle, with upper-mantle P-wave velocities ranging from 7.64 to 7.80 km/sec. However, there are wide variations in P-wave velocity in the core, dependent on composition. The shadow zone due to the core is larger than earth's.

Johnston, D. H.↗
NASA NTRSDate not supplied

A Notional Artemis Lunar Surface Exploration Package (ArLSEP) based on the Gandalf Staff Platform

Introduction: The Artemis program is planning to deliver crew and cargo to the lunar surface, but there is no current package for supporting lunar in-struments and experiments similar to the Apollo Lunar Surface Exploration Package (ALSEP). This abstract provides a possible concept for such a package using the Gandalf Staff Platform as a common core. Gandalf Staff: The Gandalf Staff is an early prototype system developed over FY’21/FY’22 using NASA Science Technology Mission Directorate (STMD) Center Information Fund (CIF) grants to de-sign, build and test “proof-of-concept” components. These components include a 24v battery powered monopole that powers a suite of subsystems, including a Graphical User Interface (GUI) for crew, surface voice and data communications, Lunar Search and Rescue (LunaSAR) navigation and communications, LiDAR, field site external lighting, 360-degree camera, and a geothermal instrument for measuring sub-surface temperature gradient. The staff can be carried independently by an Extra-Vehicular Activity (EVA) astronaut, or can be mounted into a tripod for “hands free” support at a surface site being investigated. The staff can be attached to an external solar array and power storage system for long-duration operations. [1,2] ALSEP: An ASLEP flew on each mission Apollo 12 to Apollo 17. For Apollo 11, a simplified packaged called the Early Apollo Scientific Experiments Pack-age (EASEP) was flown. Each package included a “Central Station” that provided the power and communications connected to a variety of instruments and sensors. The power was provided by a Radioisotope Thermoelectric Generator (RTG) fueled by Plutoni-um-238 generating 70 watts of power (initially, decayed over time) [3]. The communications system provide for direct to Earth data transfer from the lunar surface. Each pack-age was stowed externally in the Lunar Module (LM) Scientific Equipment (SEQ) bay with a mass up to 163 kg (Apollo 17). The crew unloaded the ALSEP from the LM and deployed the instruments on the lunar surface. Although designed to operate for only 1 year, many sites operated for up to 8 years successfully [4]. The Active Seismic Experiment (ASE) included 3 geophones for detecting seismic waves created by mortars and thumpers deployed by the crew. Other active experiments measured the lunar atmosphere, the heat flow in the subsurface, the lunar gravity and potential gravity waves, the lunar magnetic field, the solar wind and plasma interactions in cislunar space. Passive experiments included collectors for dust and cosmic rays, and retroreflectors for precise measurements of distance using a laser from Earth. The ALSEP program continues to generate insights into lunar formation and evolution. ArLSEP Concepts: The lunar surface science package for the Artemis program will hopefully exceed the capability of the ALSEP. There are multiple issues for discussion leading to the design of a new ArLSEP, needing requirements definition from the science community, NASA mission architecture, and NASA budget planners. 1. Delivery Mechanism Two possible projects currently provide capability to deliver scientific cargo to the lunar surface: 1) the Commercial Lunar Payload Services (CLPS) [5] and the Human Landing System (HLS) [6, 7]. Each project is controlled by a different organization within NASA and budgeted with different criteria although both support lunar exploration. The HLS system delivers crew (and potentially cargo) to human landing sites. If an ArLSEP is “predeployed” to such a site, the design must include power (either from the vehicle or independently) to keep the electronics functioning until deployed by the crew. If an ArLSEP is delivered on a vehicle after the crew is present on the lunar surface, safety protocols require adequate distance from the humans for impact from descent propelled sur-face regolith ejecta. This distance can not exceed the capability of the crew to walk (if no rover) to the vehicle for ArLSEP deployment. 2. Overall Guidelines The general design of ArLSEP will likely follow the ALSEP with a common system for communications and power; however, significant architecture differences between Apollo and Artemis exist. Power: The RTG will not be available for early Artemis missions nor likely follow-on Lunar Exploration Transportation Services (LETS) missions [8]. Thus, ArLSEP power must be supplied by solar arrays with sufficient battery capability to “keep alive” necessary electronics during any lunar surface eclipse period. Communication: The Artemis program is developing a series of communications satellites for lunar orbit to provide surface transmission of data and voice to Earth. Called “LunaNET”, this network is component useful for ArLSEP since south polar locations may not always have direct “line-of-sight” to Earth [9]. 3. Concept of Operations (ConOps) The general ConOps for ArLSEP is to deliver the package to lunar surface before the crew arrives, and then have the crew deploy the package after some period of time. This requires coordinated design (for power systems) and launch window (for schedule) on both the cargo and crew missions. Once the ArLSEP is deployed, it will operate autonomously for a number of years. It should be designed to be EVA compatible for crew maintenance and upgrade. 4. Notional Design (for discussion purpose only) The landing site near the South Pole is expected to have no eclipse cycle exceeding 5 days, so the “keep alive” power is 144 hours (6 days to include margin). A 12v ArLSEP will use rechargeable LiFePO4 cells, which are common in the Electric Vehicle (EV) industry. With a current of 5 amps and a 125 watt system, the mass is about 90kg. The comm. system and structure adds another 10kg, thus the “Central Station” is approximately 100kg. The solar power is collected on four arrays (each 2m above the surface), and the entire ArLSEP is designed to stow in a 2m x 1m x 1m volume. The experiment and instrument design will vary for each installation and add mass to the total (although they are expected to fit within the 2m3 volume). Seismic wave generation will likely not be provided with mortars, thus an electric “thumper” will be required. Active instruments such as imaging systems and sensing instruments will benefit from the additional power and communication capability provided by ArLSEP. Passive systems such as retroreflectors, witness plates, and cosmic dust collectors can be added to either the landing vehicle and/or the ArLSEP. With repeated HLS missions to the same human site, the ArLSEP can be expanded and easily maintained for long duration science collection on the lunar surface.

ALSEP↗
NASA NTRS1975

Seismically induced modification of lunar surface features

The formation of large impact craters and basins produced not only large volumes of ejecta but also catastrophic seismic waves. Theoretical models, extrapolation of terrestrial explosion data, and extrapolation of lunar impact data suggest surface displacements of 1-10 m at four crater radii from a Copernicus-size impact (4 x 10 to the 30th power ergs). Independent estimates of impact-generated stresses indicate that regions within 4 crater radii of an impact will receive shock waves with pressures exceeding 1 kbar. Greater areas also may receive shock effects as elastic waves following deep ray paths transform into shock waves near the surface. Additional seismic energy will be generated by impacts from secondary ejecta. The resulting large and long-lasting surface movement may contribute to the subdued appearance of the continuous ejecta blanket and secondary craters around large impact craters and to the degradation of small craters outside these zones.

Schultz, P. H.↗
NASA NTRS1979

Planetary seismology and interiors

This report briefly summarizes knowledge gained in the area of planetary seismology in the period 1969-1979. Attention is given to the seismic instruments, the seismic environment (noise, characteristics of seismic wave propagation, etc.), and the seismicity of the moon and Mars as determined by the Apollo missions and Viking Lander experiments, respectively. The models of internal structures of the terrestrial planets are discussed, with the earth used for reference.

Toksoz, M. N.↗
DOE OSTI2025

Machine Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties

This project developed machine learning (ML) methods, lab data sets, and field data to advance geothermal exploration and geothermal energy production. The work had three focus areas. One involved the development of ML methods to use microearthquakes (MEQs) for imaging geothermal reservoir properties and improving subsurface characterization – most importantly the evolution of permeability within the evolving reservoir. This part of the work included development of ML approaches for automated MEQ location, focal mechanism determination and identification of earthquake precursors. The second area focused on using MEQ signals generated by geothermal exploration and production to predict the relationship between fluid injection and seismicity. Here, we extended to reservoir scale our success in using ML to predict laboratory earthquakes and fault zone stress state. The third focus area was on lab experiments. Here, we developed new ML models for lab earthquake prediction and identification of precursors to failure to improve earthquake forecasting and early warning in geothermal settings. Major outcomes of our work include ML models that learn from MEQ signals during geothermal exploration and production to predict induced seismicity. MEQs occur naturally in connection with drilling and energy production. We developed ML methods to use the seismic waves from these events to characterize the elastic, hydraulic and poromechanical properties of reservoirs. Our work illuminated fracture geometry and the evolution of fracture permeability by incorporating seismic coda wave analysis and ML methods to relate fluid injection and seismicity. We significantly expanded laboratory earthquake prediction to include methods that use both passive measurements of microearthquakes within the lab fault zones and also active source acoustic measurements of fault zone elastic properties. These methods can now predict fault zone stress state, time to failure and the magnitude of lab earthquakes. Our work showed that repetitive stick- slip failure events during frictional sliding (the lab equivalent of earthquakes) are preceded by a cascade of micro-failure events that radiate energy in a manner that foretells unstable failure – manifest as laboratory MEQs. We documented a mapping between fracture properties and statistical attributes of elastic radiation. We extended existing works to geothermal reservoir scale and developed ML methods to determine reservoir permeability, fracture properties, and their evolution during geothermal energy production. An attractive feature of ML algorithms is their ability to handle big datasets and reveal patterns and correlations that may remain invisible to conventional analyses. Our work connected data from field, laboratory and intermediate scales to study permeability, stress, strength, fracture stiffness and geometry. At the field scale we used data from the Newberry Volcano field site, UtahFORGE, EGS Collab, and also the Bedretto underground research lab in Switzerland. These data sets are bridging the gap between the lab scale, theory, and reservoir scale. Our work produced plain language summaries to improve public understanding of DOE research. We also developed openly distributed ML and seismicity datasets for use by all researchers and we published connections between induced seismicity in geothermal areas and reservoir properties including permeability, fracture properties, and stress state. Our models are designed for the large data sets of induced seismicity typically associated with geothermal sites. We produced labeled event catalogs and used them on geothermal data to assess how ML can facilitate geothermal production and exploration. All datasets are available on the GDR Productivity: The project produced 32 publications in peer reviewed journals (two are in review). It supported the work of 6 PhD students, 40 conference presentations, 6 keynote talks at national meetings, and mentoring and professional development for 4 postdoctoral fellows.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Microstructure and CPO evolution of dynamically recrystallized olivine during complex deformation conditions: a full-field numerical modeling approach

The rheological properties of mantle rocks are strongly dependent on their crystallographic preferred orientation (CPO). Olivine CPO, defined by the orientation of seismically fast [100] axes parallel to flow direction, is also thought to be a dominant contributor to seismic anisotropy in the Earth's upper mantle. However, the amount of deformation needed to overprint a new CPO on a pre-existing fabric and the impact of the inherited CPOs on the transient microstructure evolution, remain unknown. This study employs a full-field numerical approach (VPFFT-ELLE) to explore the dynamic recrystallization and microstructural evolution of olivine polycrystalline aggregates under complex deformation conditions. We test four combinations of successive pure shear and simple shear boundary conditions. Findings indicate that inherited CPOs influence subsequent deformation in a manner dependent on the kinematic relationship between successive stages. In all cases, a minor strain increment (ε ∼0.3–0.6) is sufficient to erase the previous microstructure and CPO. However, when deformation conditions change dramatically (e.g., stretching direction changes orthogonally), the intensity of the new CPO developed is significantly lower and strain distribution are specially altered. During a transient strain stage, pre-existing microstructures undergo extensive reworking, especially when deformation conditions are changed dramatically, such as switching from simple shear to a pure shear condition with a parallel shortening direction relative to the stretching direction. We estimate the significance of these results in interpreting observations of seismic velocity anisotropy, concluding that P-wave seismic anisotropy is significantly and positively correlated with the evolution of olivine CPO with deformation history. This research underscores the transient nature of microstructural rearrangement in olivine aggregates and the necessity for caution in interpreting seismic anisotropy in regions with complex deformation histories, as inherited CPOs can influence current fabric development and induce deviation to the present deformation conditions.

36 MATERIALS SCIENCE↗
NASA NTRS1980

Velocity model of the shallow lunar crust

The travel times of the seismic waves obtained for the Apollo-14 and -16 active seismic experiments and the Apollo-16 grenade launches are shown to be consistent with a powder-layer model of the shallow lunar crust. The velocity variation with depth determined from these data is: V(z) = approximately 110 z to the 1/6 power m/sec for z less than 10 meters and V(z) is nearly = to 250 m/sec for z greater than 10 meters. The velocity values found for the 10 meter depth are similar to those found by Kovach, et al. (1972). The z to the 1/6 power depth dependence for the velocity of the topmost layer is that predicted on the basis of a powder layer (Gangi, 1972). The Amplitude variation of the direct waves as a function of source-to-receiver separation, x, is A(x) = A(o)x to the -n power exp(-ax) where 1.5 n 2.2 and a is nearly = to 0.047 neper/m. Velocity-spectra analyses of the direct, surface-reflected, bottom-reflected and refracted waves give results that are consistent with the velocity model inferred from the traveltime data.

Gangi, A. F.↗
NASA NTRSDate not supplied

Constraints on the Lunar Interior Through Comparison of Observed Apollo Seismic Travel Time With Simulated Lunar Interiors

Understanding the current state of the lunar interior is key to evaluating its formation history and evolution. The analyses of seismic waves recorded by 5 years of the Apollo passive seismic network, from 1972-1977, have provided some fundamental constraints on the lunar interior structure. Here, we show that comparisons between (a) calculated seismic velocities of simulated lunar interiors and (b) measured Apollo seismic velocities can resolve new solutions. Specifically, we show that comparison of seismic travel times can be used to constrain the lower bound of possible selenotherms.

Moon↗