Analysis and Modeling of High-frequency Emission and Deep Seismic Sources of Sunquakes
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The internal structures of the earth and the moon are compared in the light of the latest extensive data on the earth structure, mobility of the earth outer layers, and the properties of lunar crust. The Monte Carlo method is applied to develop an earth model by a stepwise process beginning with a random distribution of two elastic velocities and the density as a function of de pth. Lunar seismic, magnetic, and rock analysis data are used to infer the properties of the moon. The marked planetological contrast between the earth and the moon is shown to consist in that the earth is highly differentiated and still undergoes a large-scale differentiation, while the moon has lost its volatiles in its early history and has a cold dynamically inactive shell which has been without basic changes for three billion years.
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The ITER electron cyclotron emission (ECE) diagnostic system is located at diagnostics shielding module 2 (DSM2), equatorial port 9 (EP9), to measure electron temperature profile and electron temperature fluctuations, and also assess nonthermal electron distributions via the oblique view. Therefore, ECE has both radial and oblique views with two hot sources for calibration and two couples of mirrors for two different optical views. It shall receive that the large electromagnetic (EM) loads up to 100-MN/m3 force density due to the eddy currents on the copper mirrors generated by the short transient plasma disruption. The simplified EM analysis model using magnetic field ( B ) data and flux variations (dB/dt) method based on the worst case of plasma disruption, MD_DW_EXP16MS_CATIII, has been developed to calculate the force and moments for each ECE component and support structure for EP9 DSM2 Bay2 and Bay3. The B and dB/dt methods use the constant B and dB/dt assumed for each local bay space, but the real B and dB/dt are basically varied along the radial direction of each bay. The complex global model with the local ECE components and support structure using Maxwell transient has been developed to do EM analysis to compare the results of the B and dB/dt models. The volumetric EM force density of the whole ECE components and support structure can be used for the subsequent structural analysis. In conclusion, combined with the thermal and nuclear loads and seismic and initial loads, the ECE integration analysis can be finalized for the operation case.
The rate of detection of meteoroid impacts on the moon by the lunar seismic network shows a characteristic diurnal variation. Assuming that these meteoroids have a flux and a preimpact orbital distribution similar to that of fireballs observed by terrestrial camera networks, one can compute the expected diurnal variation for a given set of parameters that describe the seismic wave generation and transmission on the moon. An iterative process to match the theoretical variation with the observed one has led us to the following results: (1) the majority of the detected impact events occur within a closer range of the network than was believed earlier. This results in higher meteoroid flux estimates from lunar seismic data that agree with the terrestrially measured flux. (2) For meteoroid masses smaller than 1000 g, seismic amplitude is approximately proportional to the one-fifth power of the impact speed; for larger masses it is approximately proportional to the eight-fifth power, provided that the terrestrial meteor data used for analysis are not biased. (3) Seismic efficiency of meteoroids smaller than 1000 g is significantly less than that of large meteoroids. (4) Using orbits of fireballs that represent meteorites, we predict that the share of meteorites among the detected impacts is approximately 15 percent assuming that seismic efficiency of the high-density meteorites is the same as that of average meteoroids. A greatly increased seismic efficiency for these high-density objects is not likely.
The proliferation of low-cost sensors in smartphones has facilitated numerous applications; however, large-scale deployments often encounter performance issues. Sensing heterogeneity, which refers to varying data quality due to factors such as device differences and user behaviors, presents a significant challenge. In this research, we perform an extensive analysis of 3-axis accelerometer data from the MyShake system, a global seismic network utilizing smartphones. We systematically evaluate the quality of approximately 22 million 3-axis acceleration waveforms from over 81 thousand smartphone devices worldwide, using metrics that represent sampling rate and noise level. We explore a broad range of factors influencing accelerometer data quality, including smartphone and accelerometer manufacturers, phone specifications (release year, RAM, battery), geolocation, and time. Our findings indicate that multiple factors affect data quality, with accelerometer model and smartphone specifications being the most critical. In addition, we examine the influence of data quality on earthquake parameter estimation and show that removing low-quality accelerometer data enhances the accuracy of earthquake magnitude estimation.
Impact investigations will be an important aspect of the InSight mission. One of the scientific goals of the mission is a measurement of the current impact rate at Mars. Impacts will additionally inform the major goal of investigating the interior structure of Mars. In this paper, we review the current state of knowledge about seismic signals from impacts on the Earth, Moon, and laboratory experiments. We describe the generalized physical models that can be used to explain these signals. A discussion of the appropriate source time function for impacts is presented, along with spectral characteristics including the cutoff frequency and its dependence on impact momentum. Estimates of the seismic efficiency (ratio between seismic and impact energies) vary widely. Our preferred value for the seismic efficiency at Mars is 5 × 10−4, which we recommend using until we can measure it during the InSight mission, when seismic moments are not used directly. Effects of the material properties at the impact point and at the seismometer location are considered. We also discuss the processes by which airbursts and acoustic waves emanate from bolides, and the feasibility of detecting such signals. We then consider the case of impacts on Mars. A review is given of the current knowledge of present-day cratering on Mars: the current impact rate, characteristics of those impactors such as velocity and directions, and the morphologies of the craters those impactors create. Several methods of scaling crater size to impact energy are presented. The Martian atmosphere, although thin, will cause fragmentation of impactors, with implications for the resulting seismic signals. We also benchmark several different seismic modeling codes to be used in analysis of impact detections, and those codes are used to explore the seismic amplitude of impactinduced signals as a function of distance from the impact site. We predict a measurement of the current impact flux will be possible within the timeframe of the prime mission (one Mars year) with the detection of ∼ a few to several tens of impacts. However, the error bars on these predictions are large. Specific to the InSight mission, we list discriminators of seismic signals from impacts that will be used to distinguish them from marsquakes. We describe the role of the InSight Impacts Science Theme Group during mission operations, including a plan for possible night-time meteor imaging. The impacts detected by these methods during the InSight mission will be used to improve interior structure models, measure the seismic efficiency, and calculate the size frequency distribution of current impacts.
Infrasound data from arrays can be used to detect, locate, and quantify a variety of natural and anthropogenic sources from local to remote distances. However, many array processing methods use a single broad frequency range to process the data, which can lead to signals of interest being missed due to the choice of frequency limits or simultaneous clutter sources. In this work, we introduce a new open-source Python code that processes infrasound array data in multiple sequential narrow frequency bands using the least-squares approach. We test our algorithm on a few examples of natural sources (volcanic eruptions, mass movements, and bolides) for a variety of array configurations. Our method reduces the need to choose frequency limits for processing, which may result in missed signals, and it is parallelized to decrease the computational burden. Improvements of our narrow-band least-squares algorithm over broad-band least-squares processing include the ability to distinguish between multiple simultaneous sources if distinct in their frequency content (e.g., microbarom or surf vs. volcanic eruption), the ability to track changes in frequency content of a signal through time, and a decreased need to fine-tune frequency limits for processing. We incorporate a measure of planarity of the wavefield across the array (sigma tau, στ) as well as the ability to utilize the robust least trimmed squares algorithm to improve signal processing and insight into array performance. Our implementation allows for more detailed characterization of infrasound signals recorded at arrays that can improve monitoring and enhance research capabilities.
In this report, we describe how to estimate the time-variable components of the seismic moment tensor and compare these estimates to the more conventional analysis that incorporates an assumption of the source time function (STF) across all components of the seismic moment tensor. The advantage of our method is that we are able to independently estimate the time-evolution of each component of the seismic moment tensor, which may help to resolve the complex source phenomena associated with buried explosions. By performing an eigen decomposition of the time-evolving seismic moment tensor components, we are able to plot the seismic mechanism as a trajectory on a lune diagram. This technique enables interpretation of the seismic mechanism as a function of time, as opposed to the more conventional analysis which assumes that the seismic mechanism is time invariant. Finally, we describe the differences between the seismic moment and the seismic moment rate STFs, how to implement each one in inversion schemes, and the relative strengths/weaknesses of each. Our key take-away is that we are able to distinguish nearly-overlapping sources with highly different mechanisms, such as an explosion immediately following an earthquake, by estimating moment rate from seismic data through a STF-invariant inversion for the full time-variable moment tensor.
Moment tensors (MTs) have long been used in earthquake and explosion source analysis, and there has been a renewed interest in how they can inform us about the seismic source, particularly in the geophysical monitoring community due to its application in event identification and yield analysis. However, parameter uncertainties in seismic MT inversion are rarely available. The inverse procedure often does not quantify MT model errors such as event location, data noise and Earth model that are essential for estimating solution robustness. To address this need, we propose to adopt the Bayesian probabilistic framework to incorporate uncertainties in MT inversions. In this study, we present the theoretical background of a probabilistic Bayesian framework for MT inversion accounting for model and measurements errors and illustrate the implementation of the method using a synthetic example.
Condensate storage tanks (CSTs) in nuclear power plants (NPPs) are classified as critical equipment capable of surviving strong shaking in a design basis earthquake to assure the ability to subsequently provide cooling water. Structural modeling and dynamic analysis of CSTs are complicated due to fluid-structure interaction (FSI) and coupling issues, which could have significant effects on seismic response. The capability of a number of approximate models to capture seismic response is investigated using dynamic analysis results from detailed finite element models. Modal analyses and time history analyses are carried out using both 2D and 3D models to predict the dynamic behavior of CSTs as a function of ground motion intensity. Although 2D simplified models can be used to quickly evaluate the dynamic response of CSTs when there is substantial margin to failure, a detailed 3D model is required when it is necessary to examine a limit state associated with the failure mode of the tank. The findings show good agreement between the natural frequencies of convective modes determined from the 2D and 3D CST models. The difference between the frequencies of impulsive modes were found to be equal to or less than 25%.
Brief cessations of geothermal production can induce seismicity, a phenomenon that has drawn increasing attention in recent years. Such observations are rare, and the underlying mechanism requires careful analysis. In April 2022, a dense seismic and hydrologic monitoring system was deployed at the San Emidio geothermal field, Nevada, to accompany a planned power plant shutdown. Using the dense seismic array data, we detected and located ∼1,800 microseismic events (MSEs) and developed a high-resolution tomographic P-wave velocity model. We observed substantially increased microseismicity during shutdown. Most MSEs occurred on pre-existing normal faults, which are contained within extremely low-velocity zones that are likely damaged, fluid-filled, and hydraulically connected to nearby production wells. Hydrologic data show rapid fluid pressure increases of <60 kPa following the shutdown. We suggest that the cessation of production rapidly increased fluid pressures along pre-existing fault zones, activating critically stressed fault patches and fractures and producing microseismicity.
Seismoacoustic signals at local distance (<~10 km) are widely used as important constraints on source parameters for near-surface events, yet the seismoacoustic wave generation and energy partitioning are not fully understood. Spatially dense sensors could provide observations in high resolution to capture the full wavefield for better understanding wave propagation and improving source estimation. Recently, spatially dense observations of the local seismoacoustic wavefield produced by a pair of 1-ton surface explosions have been recorded using a large-N seismic array. This large-N array consists of 446 geophones and covers an area of approximately 2×2.5 km 2 . The two surface explosions occur at the same location but at different times with different atmospheric conditions. Both seismic and air–ground coupled acoustic waves from the two surface explosions are well observed. Analyses of signals recorded by the large-N seismic array show different acoustic wave speed and amplitude for the two explosions. A strong spatial variability in acoustic wave speed and amplitude for each explosion is also observed. Finally, the observations suggest the important role of local atmosphere state on wave propagation and source estimation and demonstrate how the use of a large-N capability can improve characterization of the propagation medium and source.
The latest catastrophic earthquake in Japan (March 2011) has renewed interest in the important question of the existence of pre-earthquake anomalous signals related to strong earthquakes. Recent studies have shown that there were precursory atmospheric/ionospheric signals observed in space associated with major earthquakes. The critical question, still widely debated in the scientific community, is whether such ionospheric/atmospheric signals systematically precede large earthquakes. To address this problem we have started to investigate anomalous ionospheric / atmospheric signals occurring prior to large earthquakes. We are studying the Earth's atmospheric electromagnetic environment by developing a multisensor model for monitoring the signals related to active tectonic faulting and earthquake processes. The integrated satellite and terrestrial framework (ISTF) is our method for validation and is based on a joint analysis of several physical and environmental parameters (thermal infrared radiation, electron concentration in the ionosphere, lineament analysis, radon/ion activities, air temperature and seismicity) that were found to be associated with earthquakes. A physical link between these parameters and earthquake processes has been provided by the recent version of Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) model. Our experimental measurements have supported the new theoretical estimates of LAIC hypothesis for an increase in the surface latent heat flux, integrated variability of outgoing long wave radiation (OLR) and anomalous variations of the total electron content (TEC) registered over the epicenters. Some of the major earthquakes are accompanied by an intensification of gas migration to the surface, thermodynamic and hydrodynamic processes of transformation of latent heat into thermal energy and with vertical transport of charged aerosols in the lower atmosphere. These processes lead to the generation of external electric currents in specific regions of the atmosphere and the modifications, by dc electric fields, in the ionosphere-atmosphere electric circuit. We retrospectively analyzed temporal and spatial variations of four different physical parameters (gas/radon counting rate, lineaments change, long-wave radiation transitions and ionospheric electron density/plasma variations) characterizing the state of the lithosphere/atmosphere coupling several days before the onset of the earthquakes. Validation processes consist in two phases: A. Case studies for seven recent major earthquakes: Japan (M9.0, 2011), China (M7.9, 2008), Italy (M6.3, 2009), Samoa (M7, 2009), Haiti (M7.0, 2010) and, Chile (M8.8, 2010) and B. A continuous retrospective analysis was preformed over two different regions with high seismicity- Taiwan and Japan for 2003-2009. Satellite, ground surface, and troposphere data were obtained from Terra/ASTER, Aqua/AIRS, POES and ionospheric variations from DEMETER and COSMIC-I data. Radon and GPS/TEC were obtaining from monitoring sites in Taiwan, Japan and Italy and from global ionosphere maps (GIM) respectively. Our analysis of ground and satellite data during the occurrence of 7 global earthquakes has shown the presence of anomalies in the atmosphere. Our results for Tohoku M9.0 earthquake show that on March 7th, 2011 (4 days before the main shock and 1 day before the M7.2 foreshock of March 8, 2011) a rapid increase of emitted infrared radiation was observed by the satellite data and an anomaly was developed near the epicenter. The GPS/TEC data indicate an increase and variation in electron density reaching a maximum value on March 8. From March 3 to 11 a large increase in electron concentration was recorded at all four Japanese ground-based ionosondes, which returned to normal after the main earthquake. Similar approach for analyzing atmospheric and ionospheric parameters has been applied for China (M7.9, 2008), Italy (M6.3, 2009), Samoa (M7, 2009), Haiti (M7.0, 2010) and Chile (M8.8, 2010) eahquakes. Results have revealed the presence of related variations of these parameters implying their connection with the earthquake process. The second phase (B) of this validation included 102 major earthquakes (M>5.9) in Taiwan and Japan. We have found anomalous behavior before all of these events with no false negatives. False alarm ratio for false positives is less then 10% and has been calculated for the same month of the earthquake occurrence for the entire period of analysis (2003-2009). The commonalities for detecting atmospheric/ionospheric anomalies are: i.) Regularly appearance over regions of maximum stress (i.e., along plate boundaries); ii.) Anomaly existence over land and sea; and iii) association with M>5.9 earthquakes not deeper than 100km. Due to their long duration over the same region these anomalies are not consistent with a meteorological origin. Our initial results from the ISTF validation of multi-instrument space-borne and ground observations show a systematic appearance of atmospheric anomalies near the epicentral area, one to seven (average) days prior to the largest earthquakes, and suggest that it could be explained by a coupling process between the observed physical parameters and the pre-earthquake preparation processes.
Concrete structures in nuclear installations are subject to time-dependent degradation mechanisms that can deteriorate their physical and mechanical properties, potentially exacerbating the risk of structural failure under external forces such as a seismic event. Previous research has extensively investigated the seismic response of nuclear concrete structures and the associated risk, as well as their effect on structural components safety margins. However, substantial work is still necessary to incorporate concrete aging effects into such evaluations. In fact, most models in the literature assume pristine concrete conditions and do not account for the impact of aging on the structural components’ fragility curves. This work identifies relevant time-dependent degradation mechanisms and provides simplified models to predict the the evolution of key material properties based on data from the literature. Namely, this work focuses on the aging effects of corrosion, alkali–silica reaction (ASR), and irradiation on reinforced concrete within US Department of Energy (DOE) nuclear facilities and nuclear power plants (NPP) structures. Furthermore, degradation models based on literature data are presented that define the relationship between probabilistic material properties and the concrete’s age. In this work, sampled material properties served as input for a simplified finite element model (FEM) of a critical nuclear structural system, with the output of the FEM being the seismic response for a given ground motion. The results of the FEM were then used within a probabilistic performance assessment with a statistically significant number of samples. The research presented herein addresses the detrimental effects of hazards caused by natural phenomena on deteriorated concrete elements of nuclear installations. This work directly benefits the safety analysis performed on US DOE/ National Nuclear Security Administration (NNSA) nuclear facilities located in areas prone to seismic activity. The results presented herein could aid in the improvement of DOE-STD-1020, the DOE Standard that addresses seismic risk analysis and capacity evaluation in DOE facilities. DOE-STD-1020 refers to the requirements in American Society of Civil Engineers (ASCE) 4-98, now superseded by ASCE 4-16, that shall be met in performing dynamic response analyses and generating in-structure response spectra, provided that such requirements are consistent with the requirements of ASCE/Structural Engineering Institute (SEI) 43-05. Moreover, the results presented herein could also aid in the updating of section C3.1.1. of ASCE 4-16 to account for the effects of aging on the stiffness of reinforced elements and American Concrete Institute (ACI) 349.3R-18, “Report on Evaluation and Repair of Existing Nuclear Safety-Related Concrete Structures.” Ultimately, this work can assist the risk assessment of potential lifetime extension of the existing US commercial nuclear fleet (light water reactors) and the safety analysis of the emerging advanced nuclear reactors. The proposed proof-of-concept methodology employs open-source DOE computational tools and is transferable to commercial software commonly used by engineering firms.
The Large Surface Explosion Coupling Experiment (LSECE) is a chemical explosion experiment conducted in Yucca Flat at the Nevada National Security Site in 2020. The experiment included two surface detonations of ~1000 kg trinitrotoluene equivalent. The main goal of this experiment was to provide the ground-truth data for seismoacoustic wave excitation by large chemical explosions near the ground surface. The seismic and acoustic energy partitioning between the surface is strongly governed by the depth or height of explosions, and either seismic or acoustic-only analysis may have inherent ambiguity in determining explosion yield and depth simultaneously. Previous studies suggested that joint seismoacoustic analysis can resolve the trade-off and reduce the uncertainty of yield and depth estimation dramatically. Here we demonstrate the capability of seismoacoustic analysis to improve the accuracy of explosion yield and depth estimation with the LSECE data. Local acoustic wave propagation in the atmosphere can be substantially affected by constantly varying weather conditions. Consisting of two detonations before dawn and in the afternoon, LSECE provides unique data to evaluate the model accuracy of acoustic wave propagation and seismoacoustic energy partitioning depending on local atmospheric conditions. We quantitatively evaluate the accuracy of yield and depth estimation depending on atmospheric variability and the improvement achieved by the joint seismoacoustic approach.
Abstract We present a suite of strain rate models for the western United States based on geologic and geodetic data. The geologic data consist of Quaternary fault-slip rates and the geodetic data consists of a new compilation of Global Positioning System (GPS) velocities derived from continuous, semicontinuous, and campaign measurements. We remove postseismic deformation from the GPS time series in order for our geodetic strain rate model to best capture the interseismic strain accumulation rate. We present models based on either geologic or geodetic data, but also create a hybrid model. Although there are some differences between the models, the large-scale features are the same, with the noticeable exception for the Pacific Northwest where interseismic strain is naturally more distributed than the long-term strain release. We also present a map of earthquake rate densities based on mainshocks, and the result has similar spatial features similar to the strain rate models (at least in the southwestern United States). We perform a general correlation analysis between strain rate and seismicity rate (south of Cascadia) and find a change in linearity between seismicity and strain rates from slow to faster deforming areas with seismicity rates relatively lower for the latter. The extent of that change depends a bit on assumptions made on the declustering and completeness of the catalog, but the finding of a change in slope is robust across the different strain rate models. Linearity for all areas is only expected when Gutenberg–Richter parameters and parameters involved in the conversion from strain to moment rate are uniform across the study area. We discuss these qualifications, but find no single satisfactory explanation for our observation. Moreover, when considering a rather short time and space, theoretical considerations of sampling from a power-law distribution actually predict there to be a power law instead of a linear relationship, generally consistent with our observation.