SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Advanced research results on the seismology of the Sun and distant stars is presented. Topics presented include: (1) detection of global convective wave flows; (2) observation of low degree p-mode oscillations; and (3) techniques for spectral deconvolution.
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).
Considerable controversy has arisen regarding the existence of water and water ice below the surface of Mars. Results of laboratory internal friction measurements on strongly outgassed rocks, recently made as part of an effort to interpret the high seismic Q values observed in the lunar crust, show that moisture absorbed in pores and cracks causes the low Q values. Unfortunately, the Viking seismology investigation found a surprisingly inactive planet. This note makes the case for active seismic exploration in order to ascertain the existence of liquid water in the crust from Q determinations.
Determining ages of stars for reconstructing the history of the Milky Way remains one of the most difficult tasks in astrophysics. This involves knowing when it is possible to relate the stellar mass with its age and when it is not. The young α-rich (YAR) stars present such a case in which we are still not sure about their ages because they are relatively massive, implying young ages, but their abundances are α-enhanced, which implies old ages. We report the results from new observations from a long-term radial-velocity-monitoring campaign complemented with high-resolution spectroscopy, as well as new astrometry and seismology of a sample of 41 red giants from the third version of APOKASC, which includes YAR stars. The aim is to better characterize the YAR stars in terms of binarity, mass, abundance trends, and kinematic properties. The radial velocities of HERMES, APOGEE, and Gaia were combined to determine the binary fraction among YAR stars. In combination with their mass estimate, evolutionary status, chemical composition, and kinematic properties, it allowed us to better constrain the nature of these objects. We found that stars with M < 1 M ⊙ were all single, whereas stars with M > 1 M ⊙ could be either single or binary. This is in agreement with theoretical predictions of population synthesis models. Studying their [C/N], [C/Fe], and [N/Fe], trends with mass, it became clear that many YAR stars do not follow the APOKASC stars, favoring the scenario that most of them are the product of mass transfer. Our sample further includes two likely undermassive stars, that is to say of such as low mass that they cannot have reached the red clump within the age of the Universe, unless their low mass is the signature of mass loss in previous evolutionary phases. These stars do not show signatures of currently being binaries. Both YAR and undermassive stars might show some anomalous APOGEE abundances for the elements N, Na, P, K, and Cr; although, higher-resolution optical spectroscopy might be needed to confirm these findings. Considering the significant fraction of stars that are formed in pairs and the variety of ways that makes mass transfer possible, the diversity in properties in terms of binarity, and chemistry of the YAR and undermassive stars studied here implies that most of these objects are likely not young.
The overall objective of this project is to develop a framework for reliable characterization and prediction of the state of stress in the overburden and underburden (including the basement) in CO 2 storage reservoirs using machine learning and integrated geomechanics and geophysical methods. Specifically, we propose to develop workflow encompassing of technologies and/or methods to predict stress and pressure changes due to CO 2 injection in an active tertiary recovery site and their impacts on subtle fault activation, fractures and occurrence of microseismic events and compare responses to field observations. In this project, we anticipate using dataset from the Farnsworth field Unit (FWU) which is operated by Purdure Petroleum. A novel elastic-waveform VSP inversion technique will be used to estimate high-resolution spatial and temporal changes of elastic moduli in CO 2 storage reservoirs, which will be combined with velocity-stress relationship derived from laboratory tests to obtain subsurface pressure and stress. Clustered microseismic data will be jointly inverted for improved focal mechanisms. Least-squares reverse-time migration of microseismic waveform data will be performed to directly image fracture/fault zones. Additionally, a deep neural network machine learning technique with convolutional and recurrent layers will be used for learning the spectro-temporal structures in microseismic waveforms. The results of this geotechnical data analysis will be integrated to develop a high-resolution 3D mechanical earth model extending from the overburden sealing formations to the underburden including the basement. Mechanical properties will be derived through integration of mechanical logs, tests, available results from chemo-mechanical laboratory tests, and elastic inversion of seismic data using a combination of Bayesian and stochastic methods as well as machine learning technique. Failure features (faults/fractures) will be represented and/or modeled based on seismic and core data analysis. A transient hydrodynamic-geomechanical model will be developed through coupling with the calibrated FWU reservoir simulation model. The full physics coupled model will be used to train a reduced order proxy model using machine learning algorithm for estimating stress which will then be used with appropriate constitutive relationships and forward seismological models to simulate pressure changes and induced microseismicity. An advanced optimization framework will be developed to perform a history match to minimize error between field observations and simulated. The history matched proxy model will be verified against the full-physics equivalent. The field observations that will be used in the coupled model calibration process include pressure/stress inverted from VSP, moment magnitude from microseismic analysis, real time downhole pressure measurements, production and injection data. Parameter sensitivity and uncertainty analysis will be performed to characterize the impact of model parameter uncertainty on stress estimates. The proposed project will have significant impact on future field implementation of the proposed technology. Because the project field site is an ongoing CO 2 EOR development, the value of the new technology will be demonstrated in an operational context and evaluated as a viable risk mitigation strategy. Cost/benefit will be evaluated together with the various commercial incentives for CO 2 sequestration available to oil and gas operators. The extensive available dataset and ongoing data acquisition under the SWP Phase III work plan provides flexibility for investigation of multiple approaches and reduces technical risk.
The Z Machine at Sandia National Laboratories is a pulsed power facility for high-energy density physics experiments that can shock materials to extreme temperatures and pressures through a focused energy release of up to ~ 25 MJ in < 100 nanoseconds. It has been in operation for more than two decades and conducts up to ~ 100 experiments, or “shots,” per year. Based on a set of 74 known shot times from 2018, we determined that Z Machine shots produce detectable ~ 3–17 Hz ground motion 12 km away at the Albuquerque Seismological Laboratory, New Mexico (ANMO), borehole seismograph, with peak signal at ~ 7 Hz. The known shot waveforms were used to create a three-component template, leading to the detection of 2339 Z Machine shots since 1998 through single-station cross-correlation. Local seismic magnitude estimates range from local magnitude (M L ) —2 to —1.3 and indicate that only a small fraction of the shot energy is transmitted by seismic phases observable at 12 km distance. The most recent major facility renovation, which was intended to decrease mechanical dissipation, is associated with an abrupt decrease in observed seismic amplitudes at ANMO despite stable maximum shot energy. The highly repetitive impulsive sources are well suited to coda-wave interferometry to investigate time-dependent velocity structures. Relative velocity variations (dv/v) show an annual cycle with amplitude of ~ 0.2%. Local minima are observed in the late spring, and dv/v increases through the summer monsoon rainfall, possibly reflecting patchy saturation as rainfall infiltrates near the eastern edge of the Albuquerque basin. Importantly, the cumulative results demonstrate that forensic seismology can provide insight into long-term operation of facilities such as pulsed-power laboratories, and that their recurring signals may be valuable for studies of time-dependent structure
A presentation is made of the known geological, geophysical, and geochemical data on the Azores. The regional setting of the islands is described; under the geological heading, surface geology and petrochemistry are discussed; and paleomagnetism, marine magnetic surveys, gravity, seismology, and heat flow are treated in the geophysics category. A model for the origin of the Azores is constructed on the basis of these observations.
The Incorporated Research Institutes for Seismology (IRIS) approached NASA Headquarters in 1986 about the need to collect data daily from seismic stations around the world as part of the Earth Observing System (EOS) mission. A typical IRIS Seismic Station generates 16 Megabytes of data per day when there is seismic activity. The Preliminary Design Parameters of the Wide Band Data Collection System are summarized.
We have cataloged 196 filament oscillations from the Global Oscillation Network Group Hα network data during several months near the maximum of solar cycle 24 (2014 January–June). Selected examples from the catalog are described in detail, along with our statistical analyses of all events. Oscillations were classified according to their velocity amplitude: 106 small-amplitude oscillations (SAOs), with velocities <10 km s-1, and 90 large-amplitude oscillations (LAOs), with velocities >10 km s-1. Both SAOs and LAOs are common, with one event of each class every two days on the visible side of the Sun. For nearly half of the events, we identified their apparent trigger. The period distribution has a mean value of 58 ± 15 minutes for both types of oscillations. The distribution of the damping time per period peaks at τ/P = 1.75 and 1.25 for SAOs and LAOs, respectively. We confirmed that LAO damping rates depend nonlinearly on the oscillation velocity. The angle between the direction of motion and the filament spine has a distribution centered at 27° for all filament types. This angle agrees with the observed direction of filament-channel magnetic fields, indicating that most of the cataloged events are longitudinal (i.e., undergo field-aligned motions). We applied seismology to determine the average radius of curvature in the magnetic dips, R ≈ 89 Mm, and the average minimum magnetic field strength, B ≈ 16 G. The catalog is available to the community online and is intended to be expanded to cover at least 1 solar cycle.
The association of phase picks to form events is one of the fundamental components of seismology. Large and dense sensor networks, such as >1000 geophone arrays (and distributed acoustic sensing), offer unique challenges in association due to the vast numbers of observations and high likelihood of errant picks. In addition, the large number of stations can greatly increase the time it takes to perform the association. For this reason, machine learning (ML) methods might provide a more optimal method of association for such networks. In this work, we examine how well ML methods (e.g., Gaussian mixture model association, PhaseLink, and Graph Earthquake Neural Interpretation Engine) can incorporate dense seismic arrays into regional networks and how well they handle the increasing numbers of stations. Here, we test their capabilities on two dense seismic deployments, one within Rock Valley Nevada (52 nodes and a 9-station sparse local network), and the LArge-n Seismic Survey in Oklahoma dense nodal array (>1800 vertical-component geophones). Processing data from these two different styles of dense seismic deployments allows testing of how the ML algorithms can merge array data with a broader regional network, how they deal with poorly picked phases, and how they handle anthropogenic noise. We compare the ML-associated bulletins to those obtained using the Rapid Earthquake Association and Location algorithm, a more traditional method of association. We find that there are very small differences in results between the methods for small networks (<100 stations) with low pick rates. For large networks (>1000), there are enough errant picks that some of the ML methods start to create false events out of noise. We also find that the ML methods vary in computation time significantly but are all faster than the traditional method tested here.
Low degree p-modes of the Sun have been measured in spatially integrated sunlight (the Sun as a star) both in Doppler shift and in intensity fluctuations. These observations are a good starting point for the discussion of the best way to collect equivalent data on other stars. It is assumed that the Sun is removed far enough in space to become an ordinary star of magnitude zero to one. Evidently another star will oscillate with different frequencies and different amplitudes, but some reference must be made to start with. Using this scheme, a detailed investigation of the limitations of observational accuracy in the search for global p-modes is made. The sources of noise stand in the Sun itself, in the instrumentation, in the observing time duration, in the corpuscular nature of the light and mostly in the Earth atmosphere in the case of ground based observations.
Coronal loops, constituting the basic building blocks of the active Sun, serve as primary targets to help understand the mechanisms responsible for maintaining multi-million Kelvin temperatures in the solar and stellar coronae. Despite significant advances in observations and theory, our knowledge on the fundamental properties of these structures is limited. Here, we present unprecedented observations of accelerating slow magnetoacoustic waves along a coronal loop that show differential propagation speeds in two distinct temperature channels, revealing the multi-stranded and multithermal nature of the loop. Utilizing the observed speeds and employing nonlinear force free magnetic field extrapolations, we derive the actual temperature variation along the loop in both channels, and thus are able to resolve two individual components of the multithermal loop for the first time. The obtained positive temperature gradients indicate uniform heating along the loop, rather than isolated foot point heating.
Marley (1990) and Marley and Porco (1993) proposed that f-mode oscillations of Saturn could excite resonant density and bending waves in the inner C-ring. They hypothesized that certain wave features discovered by Rosen et al. (1991) that were not associated with known satellite resonances could be the result of such resonant interactions with the planetary oscillation modes. They also predicted that if this was the case the waves would be found to be density (and not bending) waves by Cassini and predicted the azimuthal wave number of the C-ring waves m. Employing Cassini VIMS stellar occultation data Hedman and Nicholson (2013) have now confirmed the predictions and demonstrated that at least some of the C-ring features identified by Rosen et al. are indeed likely caused by resonant oscillation modes of Saturn. Given this context we have taken a fresh look at the Saturn ring seismology. First we propose that an apparent bending wave denoted 'j' by Rosen may be a second order outer vertical resonance with the l=3, m=2 f-mode of Saturn and discuss the locations of other plausible second order resonances in the rings. Since only a handful of ring resonances have been identified, measuring even one or two additional planetary mode frequencies would substantially assist the process of inverting mode frequencies to constrain Saturn interior's structure. Using the available mode frequencies, modern inversion technique employed in stellar seismology, and a recent set of Saturn interior models we provide an initial estimation of what available mode frequencies are telling us about the interior structure of the planet. Since the f-modes are confined relatively closely to the planetary surface, most of the observed modes probe only the outermost layers of the planet that are already comparatively well understood. However the l = 2 mode does probe relatively deeply into the planet and we will discuss the potential the measurement of this mode frequency has for placing new constraints on the interior structure.
The spectral method for distinguishing crustal from core-source magnetic fields has been re-examined, modified and applied to both a comprehensive geomagnetic field model and an altitude normalized magnetic map of Mars. These observational spectra are fairly fitted by theoretical forms expected from certain elementary classes of magnetic sources. For Earth we found fields from a core of radius 3512 plus or minus 64 km, in accord with the 3480 km seismologic radius, and a crust represented by a shell of random dipolar sources at radius 6367 plus or minus 14 km, just beneath the 6371.0 km mean radius. For Mars we found only a field from a crust represented in same way, but 46 plus or minus 10 km below the planetary mean radius of 3389.5 km, and with sources about 9.6 plus or minus 3.2 times stronger than Earth's. It is remarkable that the same simple theoretical form should fairly fit crustal magnetic spectra for both worlds and return crustal-source depth estimates of plausible magnitude. Evidently, the idea of an ensemble of compact, quasi-independent, magnetized regions within these planetary crusts has some merit. Yet such estimates, at best a kind of average, depend upon both the observational spectrum fitted and the physical basis of the theoretical spectrum.
The Permanent GPS Geodetic Array (PGGA) is a network of permanent monitoring GPS stations in southern California devoted to the continuous measurement of crustal deformation in near real-time. The PGGA plays a unique role in studies of the kinematics of crustal deformation and the earthquake cycle in southern California because it is also providing temporally dense geodetic measurements of crustal motion over periods of minutes to variations in regional crustal strain. As it expands and matures the PGGA will play an increasingly important role in the study of active tectonics of southern California by bridging the frequency range between seismology, observatory geodesy, paleoseismology, and geology. In Indonesia GPS data is used for measurement of a large scale crustal deformation, extending from north China to the Indonesian archipelago. Indonesia offers a tremendous laboratory to study some of the processes that build continents, and mountains are active there. We began GPS observations in August 1989 on mainland Sumatra and the Mentawai Islands to study the phenomena of oblique plate convergence. We have analyzed the Indonesian data in conjunction with data collected on Christmas and Cocos Islands and at Darwin, Australia, and with the triangulation data in Sumatra.
The study of planetary dynamics and geodesy is a difficult subject. This is so, not simply because of the complexity of the interactions between several scientific disciplines, including geophysics, geology, geochemistry, seismology, celestial mechanics, radar astronomy, and meteoritics, but perhaps more fundamentally, because of a lack of data. Although it is true that the space age has brought about important new observational techniques, which are responsible in large part for the rapid developments in planetary science over the past decade, and although we should expect to see significant progress in the field over the next few years, it is still a sad fact that data will be severely limited for an indefinite period of time in the future. The basic problem is that we can observe and study, at present, only one planetary system in the universe. This system, our solar system, contains only four major planets, five terrestrial planets, where we are inclined to include the moon but exclude Pluto, and a fairly limited collection of debris, presumably left over from some inadequately understood formation process. Thus it is impossible to base the study of planets on a significant statistical sample.
The WHOLESCALE acronym stands for Water & Hole Observations Leverage Effective Stress Calculations and Lessen Expenses. The goal of the WHOLESCALE project is to simulate the spatial distribution and temporal evolution of stress in the geothermal system at San Emidio in Nevada, United States. To reach this goal, the WHOLESCALE team has developed a methodology to incorporate and interpret data from four methods of measurement into a multi-physics model that couples thermal, hydrological, and mechanical (T H-M) processes. The WHOLESCALE team has applied this methodology at the San Emidio geothermal field, located ~100 km north of Reno, Nevada in the northwestern Basin and Range province. The WHOLESCALE team includes 30 individuals working at two universities, two national laboratories, and one industry partner. Two master-degree students and five post-doctoral researchers have gained professional experience and earned partial financial support via the WHOLESCALE project. The WHOLESCALE team has taken advantage of the perturbations created by changes in pumping operations during planned shutdowns in 2016, 2021, and 2022 to infer temporal changes in the state of stress in the geothermal system at San Emidio, Nevada, U.S. The WHOLESCALE results support the working hypothesis that increasing pore-fluid pressure reduces the effective normal stress acting across fault zones. During normal operations, pumping in deep production wells decreases fluid pressures and thus increases the effective normal stresses on faults, reducing microseismicity. During planned shutdowns, the cessation of production increases pore-fluid pressure and reduces effective normal stress. The WHOLESCALE products generated during the 4-year period between 2020 and 2024 include: three articles published in the open-access, peer-reviewed scientific literature, two master’s theses, 20 presentations or papers at scientific conferences, and 17 data sets available on public repositories. The WHOLESCALE project has been completed in two phases that included three performance periods separated by two Go/No-go Stage Gate Reviews. Tasks were classified by data type (i.e., Geologic Structure, Borehole, Geodesy, Hydrology, Seismology, and Modeling). The first phase of the project started July 31, 2020 and included ongoing project coordination (Task 1), a project kickoff (Task 2), analysis of existing data (Task 3), development of the initial stress model & deployment design (Task 4), and Go/No-go Decision Point #1 (Task 5). Phase II began with implementing the 2022 deployment (Task 6), followed by Go/No-go Decision Point #2 (Task 7) The remainder of Phase II consisted of analyzing data collected during deployment (Task 8), calibration of the stress model on all observations (Task 9), and the Final Review (August 23, 2024) & Reporting (Task 10).
Active region seismology is concerned with the determination and interpretation of the interaction of the solar acoustic oscillations with near-surface target structures, such as magnetic flux concentration, sunspots, and plage. Recent observations made with a high spatial resolution and a long temporal duration enabled measurements of the scattering matrix for sunspots and solar active regions to be carried out as a function of the mode properties. Based on this information, the amount of p-mode absorption, partial-wave phase shift, and mode mixing introduced by the sunspot, could be determined. In addition, the possibility of detecting the presence of completely submerged magnetic fields was raised, and new procedures for performing acoustic holography of the solar interior are being developed. The accumulating evidence points to the mode conversion of p-modes to various magneto-atmospheric waves within the magnetic flux concentration as being the unifying physical mechanism responsible for these diverse phenomena.