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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Satellite IR Thermal Measurements Prior to the September 2004 Earthquakes in Central California

We present and discuss observed variations in thermal transients and radiation fields prior to the earthquakes of September 18 near Bodie (M5.5) and September 28,2004 near Parkfield(M6.0) in California. Previous analysis of earthquake events have indicated the presence of a thermal anomaly, where temperatures increased or did not return to its usual nighttime value. The procedures used in our work is to analyze weather satellite data taken at night and to record the general condition where the ground cools after sunset. Two days before the Bodie earthquake lower temperature radiation was observed by the NOAA/AVHRR satellite. This occurred when the entire region was relatively cloud-free. IR land surface nighttime temperature from the MODIS instrument rose to +4 C in a 100 km radius around the Bodie epicenter. The thermal transient field recorded by MODIS in the vicinity of Parkfield, also with a cloud free environment, was around +l C and it is significantly smaller than the Parkfield epicenter, however, for that period showed a steady increase 4 days prior to the earthquake and a significant drop of the night before the quake. Geosynchronous weather satellite thermal IR measurements taken every half hour from sunset to dawn, were also recorded for 10 days prior to the Parkfield event and 5 days after as well as the day of the quake. To establish a baseline we also obtained GOES data for the same Julian sets were then used to systematically observe and record any thermal anomaly prior to the events that deviated from the baseline. Our recent results support the hypothesis of a possible relationship between an thermodynamic processes produced by increasing tectonic stress in the Earth's crust and a subsequent electro-chemical interaction between this crust and the atmosphere/ionosphere.

Ouzounov, D.↗
NASA NTRS1979

Earthquake Testing

During NASA's Apollo program, it was necessary to subject the mammoth Saturn V launch vehicle to extremely forceful vibrations to assure the moonbooster's structural integrity in flight. Marshall Space Flight Center assigned vibration testing to a contractor, the Scientific Services and Systems Group of Wyle Laboratories, Norco, California. Wyle-3S, as the group is known, built a large facility at Huntsville, Alabama, and equipped it with an enormously forceful shock and vibration system to simulate the liftoff stresses the Saturn V would encounter. Saturn V is no longer in service, but Wyle-3S has found spinoff utility for its vibration facility. It is now being used to simulate earthquake effects on various kinds of equipment, principally equipment intended for use in nuclear power generation. Government regulations require that such equipment demonstrate its ability to survive earthquake conditions. In upper left photo, Wyle3S is preparing to conduct an earthquake test on a 25ton diesel generator built by Atlas Polar Company, Ltd., Toronto, Canada, for emergency use in a Canadian nuclear power plant. Being readied for test in the lower left photo is a large circuit breaker to be used by Duke Power Company, Charlotte, North Carolina. Electro-hydraulic and electro-dynamic shakers in and around the pit simulate earthquake forces.

Source record↗
NASA NTRS2010

Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) Model - An Unified Concept for Earthquake Precursors Validation

The paper presents a conception of complex multidisciplinary approach to the problem of clarification the nature of short-term earthquake precursors observed in atmosphere, atmospheric electricity and in ionosphere and magnetosphere. Our approach is based on the most fundamental principles of tectonics giving understanding that earthquake is an ultimate result of relative movement of tectonic plates and blocks of different sizes. Different kind of gases: methane, helium, hydrogen, and carbon dioxide leaking from the crust can serve as carrier gases for radon including underwater seismically active faults. Radon action on atmospheric gases is similar to the cosmic rays effects in upper layers of atmosphere: it is the air ionization and formation by ions the nucleus of water condensation. Condensation of water vapor is accompanied by the latent heat exhalation is the main cause for observing atmospheric thermal anomalies. Formation of large ion clusters changes the conductivity of boundary layer of atmosphere and parameters of the global electric circuit over the active tectonic faults. Variations of atmospheric electricity are the main source of ionospheric anomalies over seismically active areas. Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) model can explain most of these events as a synergy between different ground surface, atmosphere and ionosphere processes and anomalous variations which are usually named as short-term earthquake precursors. A newly developed approach of Interdisciplinary Space-Terrestrial Framework (ISTF) can provide also a verification of these precursory processes in seismically active regions. The main outcome of this paper is the unified concept for systematic validation of different types of earthquake precursors united by physical basis in one common theory.

Pulinets, S.↗
NASA NTRS2011

Contribution of Satellite Gravimetry to Understanding Seismic Source Processes of the 2011 Tohoku-Oki Earthquake

The 2011 great Tohoku-Oki earthquake, apart from shaking the ground, perturbed the motions of satellites orbiting some hundreds km away above the ground, such as GRACE, due to coseismic change in the gravity field. Significant changes in inter-satellite distance were observed after the earthquake. These unconventional satellite measurements were inverted to examine the earthquake source processes from a radically different perspective that complements the analyses of seismic and geodetic ground recordings. We found the average slip located up-dip of the hypocenter but within the lower crust, as characterized by a limited range of bulk and shear moduli. The GRACE data constrained a group of earthquake source parameters that yield increasing dip (7-16 degrees plus or minus 2 degrees) and, simultaneously, decreasing moment magnitude (9.17-9.02 plus or minus 0.04) with increasing source depth (15-24 kilometers). The GRACE solution includes the cumulative moment released over a month and demonstrates a unique view of the long-wavelength gravimetric response to all mass redistribution processes associated with the dynamic rupture and short-term postseismic mechanisms to improve our understanding of the physics of megathrusts.

Han, Shin-Chan↗
NASA NTRS2013

Space-borne Observations of Atmospheric Pre-Earthquake Signals in Seismically Active Areas: Case Study for Greece 2008-2009

We are conducting theoretical studies and practical validation of atm osphere/ionosphere phenomena preceding major earthquakes. Our approach is based on monitoring of two physical parameters from space: outgoi ng long-wavelength radiation (OLR) on the top of the atmosphere and e lectron and electron density variations in the ionosphere via GPS Tot al Electron Content (GPS/TEC). We retrospectively analyzed the temporal and spatial variations of OLR an GPS/TEC parameters characterizing the state of the atmosphere and ionosphere several days before four m ajor earthquakes (M>6) in Greece for 2008-2009: M6.9 of 02.12.08, M6. 2 02.20.08; M6.4 of 06.08.08 and M6.4 of 07.01.09.We found anomalous behavior before all of these events (over land and sea) over regions o f maximum stress. We expect that our analysis reveal the underlying p hysics of pre-earthquake signals associated with some of the largest earthquakes in Greece.

Ouzounov, D. P.↗
NASA NTRS2009

Use of QuakeSim and UAVSAR for Earthquake Damage Mitigation and Response

Spaceborne, airborne, and modeling and simulation techniques are being applied to earthquake risk assessment and response for mitigation from this natural disaster. QuakeSim is a web-based portal for modeling interseismic strain accumulation using paleoseismic and crustal deformation data. The models are used for understanding strain accumulation and release from earthquakes as well as stress transfer to neighboring faults. Simulations of the fault system can be used for understanding the likelihood and patterns of earthquakes as well as the likelihood of large aftershocks from events. UAVSAR is an airborne L-band InSAR system for collecting crustal deformation data. QuakeSim, UAVSAR, and DESDynI (following launch) can be used for monitoring earthquakes, the associated rupture and damage, and postseismic motions for prediction of aftershock locations.

fault systems↗
NASA NTRS2017

Thermal Radiation Anomalies Associated with Major Earthquakes

Recent developments of remote sensing methods for Earth satellite data analysis contribute to our understanding of earthquake related thermal anomalies. It was realized that the thermal heat fluxes over areas of earthquake preparation is a result of air ionization by radon (and other gases) and consequent water vapor condensation on newly formed ions. Latent heat (LH) is released as a result of this process and leads to the formation of local thermal radiation anomalies (TRA) known as OLR (outgoing Longwave radiation, Ouzounov et al, 2007). We compare the LH energy, obtained by integrating surface latent heat flux (SLHF) over the area and time with released energies associated with these events. Extended studies of the TRA using the data from the most recent major earthquakes allowed establishing the main morphological features. It was also established that the TRA are the part of more complex chain of the short-term pre-earthquake generation, which is explained within the framework of a lithosphere-atmosphere coupling processes.

Ouzounov, Dimitar↗
DOE OSTI2020

Preseismic Fault Creep and Elastic Wave Amplitude Precursors Scale With Lab Earthquake Magnitude for the Continuum of Tectonic Failure Modes

Tectonic faults fail in a continuum of modes from slow earthquakes to elastodynamic rupture. Precursory variations in elastic wavespeed and amplitude, interpreted as indicators of imminent failure, have been observed in limited natural settings and lab experiments where they are thought to arise from contact rejuvenation and microcracking within and around the fault zone. However, the physical mechanisms and connections to fault creep are poorly understood. Here we vary loading stiffness during frictional shear to generate a range of slip modes and measure fault zone properties using transmitted elastic waves. We find that elastic wave amplitudes show clear changes before fault failure. The temporal onset of amplitude reduction scales with lab earthquake magnitude and the magnitude of this reduction varies with fault slip. Our data provide clear evidence of precursors to lab earthquakes and suggest that continuous seismic monitoring could be useful for assessing fault state and seismic hazard potential.

58 GEOSCIENCES↗
DOE OSTI2024

Generalization of Deep-Learning Models for Classification of Local Distance Earthquakes and Explosions across Various Geologic Settings

Although accurately classifying signals from earthquakes and explosions at local distance (<250 km) remains an important task for seismic network operations, the growing volume of available seismic data presents a challenge for analysts using traditional source discrimination techniques. In recent years, deep-learning models have proven effective at discriminating between low-magnitude earthquakes and explosions measured at local distances, but it is not clear how well these models are capable of generalizing across different geological settings. To address the issue of generalization between regions, we train deep-learning models (convolutional neural networks [CNNs]) on time–frequency representations (scalograms) of three-component earthquake and explosion signals from eight different regions in the continental United States. We explore scenarios where models are trained on data from all regions, individual regions, or all but one region. We find that although CNN models trained on individual regions do not necessarily generalize well across different settings, models trained on multiple regions that include diverse path coverage generalize to new regions, with station-level accuracy of up to 90% or more for data sets from unseen regions. In general, CNN-based discrimination models significantly outperform models based on uncorrected P/S ratio (measured in the 10–18 Hz frequency band), even when CNN models are tested on data from entirely unseen regions.

58 GEOSCIENCES↗
DOE OSTI2023

Impacts of a Cascadia Subduction Zone Earthquake on Water Levels and Wetlands of the Lower Columbia River and Estuary

Abstract Subsidence after a subduction zone earthquake can cause major changes in estuarine bathymetry. Here, we quantify the impacts of earthquake‐induced subsidence on hydrodynamics and habitat distributions in a major system, the lower Columbia River Estuary, using a hydrodynamic and habitat model. Model results indicate that coseismic subsidence increases tidal range, with the smallest changes at the coast and a maximum increase of ∼10% in a region of topographic convergence. All modeled scenarios reduce intertidal habitat by 24%–25% and shifts ∼93% of estuarine wetlands to lower‐elevation habitat bands. Incorporating dynamic effects of tidal change from subsidence yields higher estimates of remaining habitat by multiples of 0–3.7, dependent on the habitat type. The persistent tidal change and chronic habitat disturbance after an earthquake poses strong challenges for estuarine management and wetland restoration planning, particularly when coupled with future sea‐level rise effects.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Network analysis of earthquake ground motion spatial correlation: a case study with the San Jacinto seismic nodal array

SUMMARY The spatial correlation of earthquake ground motion intensity can be measured from strong motion data; however, the data used in past studies is sparsely sampled in space, and only the interstation distance was considered as a correlation variable. These limitations mean that we have only weak constraints on the true correlation structure of ground motion and that potentially important aspects of spatial correlation are unconstrained. In this study, we combine a large-N seismic array and graph analytics to explore this issue at a local scale using small local and regional earthquakes. Our result suggests site conditions, and how they interact with the incident seismic wavefield, strongly condition the spatial correlation of ground motion. Future progress in characterizing ground motion spatial variability will require dense wavefield measurements, either through nodal deployments, or perhaps distributed acoustic sensing measurements, of seismic wavefields. Aftershock sequences of major earthquakes would provide particularly data-rich targets of opportunity.

58 GEOSCIENCES↗
DOE OSTI2024

Performance-based earthquake early warning for tall buildings

The ShakeAlert Earthquake Early Warning (EEW) system aims to issue an advance warning to residents on the West Coast of the United States seconds before the ground shaking arrives, if the expected ground shaking exceeds a certain threshold. However, residents in tall buildings may experience much greater motion due to the dynamic response of the buildings. Therefore, there is an ongoing effort to extend ShakeAlert to include the contribution of building response to provide a more accurate estimation of the expected shaking intensity for tall buildings. Currently, the supposedly ideal solution of analyzing detailed finite element models of buildings under predicted ground-motion time histories is not theoretically or practically feasible. The authors have recently investigated existing simple methods to estimate peak floor acceleration (PFA) and determined these simple formulas are not practically suitable. Instead, this article explores another approach by extending the Pacific Earthquake Engineering Research Center (PEER) performance-based earthquake engineering (PBEE) to EEW, considering that every component involved in building response prediction is uncertain in the EEW scenario. Additionally, while this idea is not new and has been proposed by other researchers, it has two shortcomings: (1) the simple beam model used for response prediction is prone to modeling uncertainty, which has not been quantified, and (2) the ground motions used for probabilistic demand models are not suitable for EEW applications. In this article, we address these two issues by incorporating modeling errors into the parameters of the beam model and using a new set of ground motions, respectively. We demonstrate how this approach could practically work using data from a 52-story building in downtown Los Angeles. Using the criteria and thresholds employed by previous researchers, we show that if peak ground acceleration (PGA) is accurately estimated, this approach can predict the expected level of human comfort in tall buildings.

58 GEOSCIENCES↗
DOE OSTI2024

A Complete Machine-Learning-Based Workflow to Illuminate Earthquake Processes

Under this grant we developed, tested, and made available, machine learning models to improve the tasks in the earthquake monitoring workflow (Figure 1). We implemented these models as a part of an end-to-end workflow for seismic network processing and demonstrated, in a variety of settings, that these methods generalize and that they result in dramatically more comprehensive earthquake catalogs. These catalogs illuminate earthquake processes in detail and to an extent that had previously not been possible, and they do so for both tectonic seismicity and seismicity induced by fluid injection related to unconventional hydrocarbon development. This report summarizes the results from the 15 publications that resulted from this grant. Those contributes are divided into: (1) the development of specific tasks related to monitoring (7 publications), (2) the organization of those tasks into workflows for seismic monitoring (2 publications), and (3) applications of those workflows to data (6 publications).

58 GEOSCIENCES↗
NASA NTRS2008

Understanding Earthquake Fault Systems Using QuakeSim Analysis and Data Assimilation Tools

We are using the QuakeSim environment to model interacting fault systems. One goal of QuakeSim is to prepare for the large volumes of data that spaceborne missions such as DESDynI will produce. QuakeSim has the ability to ingest distributed heterogenous data in the form of InSAR, GPS, seismicity, and fault data into various earthquake modeling applications, automating the analysis when possible. Virtual California simulates interacting faults in California. We can compare output from long time history Virtual California runs with the current state of strain and the strain history in California. In addition to spaceborne data we will begin assimilating data from UAVSAR airborne flights over the San Francisco Bay Area, the Transverse Ranges, and the Salton Trough. Results of the models are important for understanding future earthquake risk and for providing decision support following earthquakes. Improved models require this sensor web of different data sources, and a modeling environment for understanding the combined data.

earthquake simulations↗
DOE OSTI2023

3-D Simulations of earthquakes rupture jumps: 1. Homogeneous pre-stress conditions

SUMMARY Observational and modelling studies indicate that earthquake ruptures can jump between fault sections as large as ∼3 and ∼5 km for compressional and extensional offsets, respectively. Here, we compare characteristics of the rupture jump process on parallel but offset fault sections from traditional 3-D dynamic rupture simulations governed by slip weakening friction using the finite element code, FaultMod, to those from quasi-dynamic simulations governed by rate- and state-dependent friction (rate-state friction) using the code RSQSim. These simulations use spatially uniform initial stresses. For a variety of measures the rupture renucleation position on the offset fault, the rate-state friction and slip weakening friction models produce very similar results. The principal difference is the additional occurrence of delayed rupture jumps that arise from the time- and stress-dependent nucleation that is characteristic of rate-state friction. For immediate rupture jumps, models with slip weakening friction span greater offsets than those with rate-state friction. However the jump distances are nearly identical when delayed rupture jumps are included in the comparisons. We propose that delayed rupture jumps are the likely mechanism for adjacent large-earthquake pairs and clusters. Based on the similarity of renucleation positions with both dynamic and quasi-dynamic models, we conclude that the renucleation positions for rupture initiation on the receiver fault (separated by less than ∼3 km from the source fault) are primarily controlled by static stress changes induced by slip on the initiating fault. However, in light of the slightly greater maximum jump distances (>3 km) seen with the dynamic slip weakening friction model, dynamic stress changes from seismic waves play an increasingly important role as offset distances increase.

, RSQSim↗
DOE OSTI2020

Probing Slow Earthquakes With Deep Learning

Abstract Slow earthquakes may trigger failure on neighboring locked faults that are stressed sufficiently to break, and slow slip patterns may evolve before a nearby great earthquake. However, even in the clearest cases such as Cascadia, slow earthquakes and associated tremor have only been observed in intermittent and discrete bursts. By training a convolutional neural network to detect known tremor on a single seismic station in Cascadia, we isolate and identify tremor and slip preceding and following known larger slow events. The deep neural network can be used for the detection of quasi‐continuous tremor, providing a proxy that quantifies the slow slip rate. Furthermore, the model trained in Cascadia recognizes tremor in other subduction zones and also along the San Andreas Fault at Parkfield, suggesting a universality of waveform characteristics and source processes, as posited from experiments and theory.

58 GEOSCIENCES↗
DOE OSTI2020

Acoustic Energy Release During the Laboratory Seismic Cycle: Insights on Laboratory Earthquake Precursors and Prediction

Abstract Machine learning can predict the timing and magnitude of laboratory earthquakes using statistics of acoustic emissions. The evolution of acoustic energy is critical for lab earthquake prediction; however, the connections between acoustic energy and fault zone processes leading to failure are poorly understood. Here, we document in detail the temporal evolution of acoustic energy during the laboratory seismic cycle. We report on friction experiments for a range of shearing velocities, normal stresses, and granular particle sizes. Acoustic emission data are recorded continuously throughout shear using broadband piezo‐ceramic sensors. The coseismic acoustic energy release scales directly with stress drop and is consistent with concepts of frictional contact mechanics and time‐dependent fault healing. Experiments conducted with larger grains (10.5 μm) show that the temporal evolution of acoustic energy scales directly with fault slip rate. In particular, the acoustic energy is low when the fault is locked and increases to a maximum during coseismic failure. Data from traditional slide‐hold‐slide friction tests confirm that acoustic energy release is closely linked to fault slip rate. Furthermore, variations in the true contact area of fault zone particles play a key role in the generation of acoustic energy. Our data show that acoustic radiation is related primarily to breaking/sliding of frictional contact junctions, which suggests that machine learning‐based laboratory earthquake prediction derives from frictional weakening processes that begin very early in the seismic cycle and well before macroscopic failure.

58 GEOSCIENCES↗
DOE OSTI2020

The Spatiotemporal Evolution of Granular Microslip Precursors to Laboratory Earthquakes

Laboratory earthquake experiments provide important observational constraints for our understanding of earthquake physics. Here we leverage continuous waveform data from a network of piezoceramic sensors to study the spatial and temporal evolution of microslip activity during a shear experiment with synthetic fault gouge. We combine machine learning techniques with ray theoretical seismology to detect, associate, and locate tens of thousands of microslip events within the gouge layer. Microslip activity is concentrated near the center of the system but is highly variable in space and time. While microslip activity rate increases as failure approaches, the spatiotemporal evolution can differ substantially between stick-slip cycles. These results illustrate that even within a single, well-constrained laboratory experiment, the dynamics of earthquake nucleation can be highly complex.

58 GEOSCIENCES↗