Daniel T. Trugman

Much simplified ion-beam assisted deposition-TiN template for high-performance coated conductors

A much simplified template, i.e., two nonsuperconducting layers between the superconducting YBa2Cu3O7−δ (YBCO) and the polycrystalline metal substrate, has been developed for high-performance coated conductors by using biaxially aligned TiN as a seed layer. A combination of a thin TiN (∼10 nm by ion-beam assisted deposition) layer and an epitaxial buffer LaMnO3 layer (∼120 nm) allows us to grow epitaxial YBCO films with values of full width at half-maximum around 3.5° and 1.7° for the ϕ-scan of (103) and rocking curve of (005) YBCO, respectively. The YBCO films grown on electropolished polycrystalline Hastelloy using this two-layer template exhibited a superconducting transition temperature of 89.5 K, a critical current density of 1.2 MA/cm2 at 75.5 K, and an α value (proportional factor of critical current density Jc∼H−α) of around 0.33, indicating a high density of pinning centers and an absence of weak links.

GrowClust: A Hierarchical Clustering Algorithm for Relative Earthquake Relocation, with Application to the Spanish Springs and Sheldon, Nevada, Earthquake Sequences

Accurate earthquake locations are essential for providing reliable hazard assessments, understanding the physical mechanisms driving extended earthquake sequences, and interpreting fault structure. Techniques based on waveform cross correlation can significantly improve the precision of the relative locations of event pairs observed at a set of common stations. Here we describe GrowClust, an open‐source, relative relocation algorithm that can provide robust relocation results for earthquake sequences over a wide range of spatial and temporal scales. The method uses input differential travel times, cross‐correlation values, and reference starting locations, and applies a hybrid, hierarchical clustering algorithm to simultaneously group and relocate events within similar event clusters. The method is computationally efficient and numerically stable in its capacity to process large data sets and naturally applies greater weight to more similar event pairs. Additionally, it outputs location error estimates that can be used to help interpret the reliability and resolution of relocation results. As an example, we apply the GrowClust method to the recent Spanish Springs and Sheldon, Nevada, earthquake swarms. These sequences highlight the future potential for applying the GrowClust relocation method on a much larger scale within the region, where existing relocation results are sparse but vital for understanding the seismotectonics and seismic hazard of Nevada and eastern California.

A comparison of long‐term changes in seismicity at The Geysers, Salton Sea, and Coso geothermal fields

Geothermal energy is an important source of renewable energy, yet its production is known to induce seismicity. Here we analyze seismicity at the three largest geothermal fields in California: The Geysers, Salton Sea, and Coso. We focus on resolving the temporal evolution of seismicity rates, which provides important observational constraints on how geothermal fields respond to natural and anthropogenic loading. We develop an iterative, regularized inversion procedure to partition the observed seismicity rate into two components: (1) the interaction rate due to earthquake-earthquake triggering and (2) the smoothly varying background rate controlled by other time-dependent stresses, including anthropogenic forcing. We apply our methodology to compare long-term changes in seismicity to monthly records of fluid injection and withdrawal. At The Geysers, we find that the background seismicity rate is highly correlated with fluid injection, with the mean rate increasing by approximately 50% and exhibiting strong seasonal fluctuations following construction of the Santa Rosa pipeline in 2003. In contrast, at both Salton Sea and Coso, the background seismicity rate has remained relatively stable since 1990, though both experience short-term rate fluctuations that are not obviously modulated by geothermal plant operation. We also observe significant temporal variations in Gutenberg-Richter b value, earthquake magnitude distribution, and earthquake depth distribution, providing further evidence for the dynamic evolution of stresses within these fields. The differing field-wide responses to fluid injection and withdrawal may reflect differences in in situ reservoir conditions and local tectonics, suggesting that a complex interplay of natural and anthropogenic stressing controls seismicity within Californias geothermal fields.

A 2D Pseudodynamic Rupture Model Generator for Earthquakes on Geometrically Complex Faults

Abstract Geologic observations indicate that faults are fractally rough surfaces, with deviations from planarity at all length scales. Fault roughness introduces complexity in the rupture process and resulting ground motion. We present a 2D kinematic rupture generator that emulates the strong dependence of earthquake source parameters on local fault geometry observed in dynamic models of ruptures on nonplanar faults. This pseudodynamic model is based on a statistical analysis of ensembles of 2D plane strain rupture simulations on fractally rough faults with rate‐weakening friction and off‐fault viscoplasticity. We observe strong anticorrelation of roughness‐induced fluctuations in final slip, rupture velocity, and peak slip velocity with the local fault slope for right‐lateral strike‐slip ruptures. Spatial variability in these source parameters excites high‐frequency seismic waves that are consistent with observed strong‐motion records. Although accurate modeling of this high‐frequency motion is critical to seismic‐hazard analysis, dynamic rupture simulations are currently too computationally inefficient to be of practical use in such applications. We find that the seismic waves excited by the pseudodynamic model have similar intensity and spectral content to the corresponding dynamic model. Although the method has been developed in 2D, we envision that a similar approach could be taken for the 3D problem, provided that computational resources are available to generate an ensemble set of 3D dynamic rupture simulations. The resulting methodology is expected to find future application in efficient earthquake simulations that accurately quantify high‐frequency ground motion.

Did stresses from the Cerro Prieto Geothermal Field influence the El Mayor‐Cucapah rupture sequence?

The Mw 7.2 El Mayor-Cucapah (EMC) earthquake ruptured a complex fault system in northern Baja California that was previously considered inactive. The Cerro Prieto Geothermal Field (CPGF), site of the worlds second largest geothermal power plant, is located approximately 15 km to the northeast of the EMC hypocenter. We investigate whether anthropogenic fluid extraction at the CPGF caused a significant perturbation to the stress field in the EMC rupture zone. We use Advanced Land Observing Satellite interferometric synthetic aperture radar data to develop a laterally heterogeneous model of fluid extraction at the CPGF and estimate that this extraction generates positive Coulomb stressing rates of order 15 kPa/yr near the EMC hypocenter, a value which exceeds the local tectonic stressing rate. Although we cannot definitively conclude that production at the CPGF triggered the EMC earthquake, its influence on the local stress field is substantial and should not be neglected in local seismic hazard assessments.

Application of an improved spectral decomposition method to examine earthquake source scaling in Southern California

Earthquake source spectra contain fundamental information about the dynamics of earthquake rupture. However, the inherent tradeoffs in separating source and path effects, when combined with limitations in recorded signal bandwidth, make it challenging to obtain reliable source spectral estimates for large earthquake data sets. We present here a stable and statistically robust spectral decomposition method that iteratively partitions the observed waveform spectra into source, receiver, and path terms. Unlike previous methods of its kind, our new approach provides formal uncertainty estimates and does not assume self-similar scaling in earthquake source properties. Its computational efficiency allows us to examine large data sets (tens of thousands of earthquakes) that would be impractical to analyze using standard empirical Greens function-based approaches. We apply the spectral decomposition technique to P wave spectra from five areas of active contemporary seismicity in Southern California: the Yuha Desert, the San Jacinto Fault, and the Big Bear, Landers, and Hector Mine regions of the Mojave Desert. We show that the source spectra are generally consistent with an increase in median Brune-type stress drop with seismic moment but that this observed deviation from self-similar scaling is both model dependent and varies in strength from region to region. We also present evidence for significant variations in median stress drop and stress drop variability on regional and local length scales. These results both contribute to our current understanding of earthquake source physics and have practical implications for the next generation of ground motion prediction assessments.

Source spectral properties of small-to-moderate earthquakes in southern Kansas†

The source spectral properties of injection-induced earthquakes give insight into their nucleation, rupture processes, and influence on ground motion. Here we apply a spectral decomposition approach to analyze P-wave spectra and estimate Brune-type stress drop for more than 2000 ML1.5–5.2 earthquakes occurring in southern Kansas from 2014 to 2016. We find that these earthquakes are characterized by low stress drop values (median ∼0.4MPa) compared to natural seismicity in California. We observe a significant increase in stress drop as a function of depth, but the shallow depth distribution of these events is not by itself sufficient to explain their lower stress drop. Stress drop increases with magnitude from M1.5–M3.5, but this scaling trend may weaken above M4 and also depends on the assumed source model. Although we observe a nonstationary, sequence-specific temporal evolution in stress drop, we find no clear systematic relation with the activity of nearby injection wells.

Strong Correlation between Stress Drop and Peak Ground Acceleration for Recent M 1–4 Earthquakes in the San Francisco Bay AreaCorrelation between Stress Drop and PGA for Recent Earthquakes in San Francisco Bay Area

Theoretical and observational studies suggest that between-event variability in the median ground motions of larger (M ≥ 5) earthquakes is controlled primarily by the dynamic properties of the earthquake source, such as Brune-type stress drop. Analogous results remain equivocal for smaller events due to the lack of comprehensive and overlapping ground-motion and source-parameter datasets in this regime. Here, we investigate the relationship between peak ground acceleration (PGA) and dynamic stress drop for a new dataset of 5297 earthquakes that occurred in the San Francisco Bay area from 2002 through 2016. For each event, we measure PGA on horizontal-component channels of stations within 100 km and estimate stress drop from P-wave spectra recorded on vertical-component channels of the same stations. We then develop a nonparametric ground-motion prediction equation (GMPE) applicable for the moderate (M 1–4) earthquakes in our study region, using a mixed-effects generalization of the Random Forest algorithm. We use the Random Forest GMPE to model the joint influence of magnitude, distance, and near-site effects on observed PGA. We observe a strong correlation between dynamic stress drop and the residual PGA of each event, with the events with higher-than-expected PGA associated with higher values of stress drop. The strength of this correlation increases as a function of magnitude but remains significant even for smaller magnitude events with corner frequencies that approach the observable bandwidth of the acceleration records. Mainshock events are characterized by systematically higher stress drop and PGA than aftershocks of equivalent magnitude. Coherent local variations in the distribution of dynamic stress drop provide observational constraints to support the future development of nonergodic GMPEs that account for variations in median stress drop at different source locations. Electronic Supplement: Figures showing the relation between Mw and ML, comparison of the ground-motion measurements from this study with the cross-listed records in the Next Generation Attenuation ground-motion database, the validation curve used to select the optimal tree depth for the Random Forest ground-motion prediction equation (GMPE) used in this study, the between-event ground-motion residual is plotted versus: (a) stress drop, (b) magnitude-adjusted stress drop, (c) depth, and (d) depth-adjusted stress drop, a table containing the ground-motion and stressdrop measurements associated with this study, and an example Python notebook.

Afterslip Enhanced Aftershock Activity During the 2017 Earthquake Sequence Near Sulphur Peak, Idaho

An energetic earthquake sequence occurred during September to October 2017 near Sulphur Peak, Idaho. The normal-faulting Mw 5.3 mainshock of 2 September 2017 was widely felt in Idaho, Utah, and Wyoming. Over 1,000 aftershocks were located within the first 2 months, 29 of which had magnitudes ≥4.0 ML. High-accuracy locations derived with data from a temporary seismic array show that the sequence occurred in the upper (<10 km) crust of the Aspen Range, east of the northern section of the range-bounding, west-dipping East Bear Lake Fault. Moment tensors for 77 of the largest events show normal and strike-slip faulting with a summed aftershock moment that is 1.8–2.4 times larger than the mainshock moment. We propose that the unusually high productivity of the 2017 Sulphur Peak sequence can be explained by aseismic afterslip, which triggered a secondary swarm south of the coseismic rupture zone beginning ~1 day after the mainshock. Plain Language Summary During the fall of 2017, an energetic sequence of earthquakes was recorded in southeastern Idaho. The mainshock had a moment magnitude of Mw 5.3, yet thousands of aftershocks were detected. We found that the unusually high productivity of this earthquake sequence can be explained by extra sliding that occurred just after the mainshock. This extra sliding happened too slowly to generate seismic waves, but it was large enough to alter the stress in the crust such that the extra aftershocks were created. Our finding suggests that in this region of Idaho, some of the strain that is built up by tectonic forces is released in slow-slip or creep events. This discovery will ultimately lead to more accurate forecasts of seismic hazard in the region.