Search NASA⌕ Search

SEARCH · Search NASA

Results for “Data Characterization”

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.

At least 1,405 records · Page 78
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Parameter Estimation for Decoding Sensor Signals

This paper introduces a parameter estimation approach for decoding digital sensor signals in a cyber-physical system. For unknown or not fully characterized digital sensor data, it can be difficult to decipher a desired signal from background or noise. In a cyber-physical system with networked sensors, we can leverage knowledge of the physical system to inform the decoding of the digital signals. This work in progress is a case study on deciphering commercial vehicle on-board sensor networks that communicate through the Controller Area Network (CAN). By understanding the stock vehicle sensor network, a vehicle can be extended into a scalable research platform with minimal instrumentation. Our challenge was to localize desired sensor signals encoded in network traffic that included other sensor data, control messages, as well as encoding and security overhead. Due to the vehicle’s unknown sensor network, our approach developed methods to efficiently analyze and identify key signals despite the large state-space for potential signal embeddings.

Nice, Matthew↗
DOE OSTI2023

Multisensor Agile Adaptive Sampling (MAAS): A Methodology to Collect Radar Observations of Convective Cell Life Cycle

Abstract Multisensor Agile Adaptive Sampling (MAAS), a smart sensing framework, was adapted to increase the likelihood of observing the vertical structure (with little to no gaps), spatial variability (at subkilometer scale), and temporal evolution (at ∼2-min resolution) of convective cells. This adaptation of MAAS guided two mechanically scanning C-band radars (CSAPR2 and CHIVO) by automatically analyzing the latest NEXRAD data to identify, characterize, track, and nowcast the location of all convective cells forming in the Houston domain. MAAS used either a list of predetermined rules or real-time user input to select a convective cell to be tracked and sampled by the C-band radars. The CSAPR2 tracking radar was first tasked to collect three sector plan position indicator (PPI) scans toward the selected cell. Edge computer processing of the PPI scans was used to identify additional targets within the selected cell. In less than 2 min, both the CSAPR2 and CHIVO radars were able to collect bundles of three to six range–height indicator (RHI) scans toward different targets of interest within the selected cell. Bundles were successively collected along the path of cell advection for as long as the cell met a predetermined set of criteria. Between 1 June and 30 September 2022 over 315 000 vertical cross-section observations were collected by the C-band radars through ∼1300 unique isolated convective cells, most of which were observed for over 15 min of their life cycle. To the best of our knowledge, this dataset, collected primarily through automatic means, constitutes the largest dataset of its kind.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Acute stress reduces population-level metabolic and proteomic variation

Abstract Background Variation in omics data due to intrinsic biological stochasticity is often viewed as a challenging and undesirable feature of complex systems analyses. In fact, numerous statistical methods are utilized to minimize the variation among biological replicates. Results We demonstrate that the common statistics relative standard deviation (RSD) and coefficient of variation (CV), which are often used for quality control or part of a larger pipeline in omics analyses, can also be used as a metric of a physiological stress response. Using an approach we term Replicate Variation Analysis (RVA), we demonstrate that acute physiological stress leads to feature-wide canalization of CV profiles of metabolomes and proteomes across biological replicates. Canalization is the repression of variation between replicates, which increases phenotypic similarity. Multiple in-house mass spectrometry omics datasets in addition to publicly available data were analyzed to assess changes in CV profiles in plants, animals, and microorganisms. In addition, proteomics data sets were evaluated utilizing RVA to identify functionality of reduced CV proteins. Conclusions RVA provides a foundation for understanding omics level shifts that occur in response to cellular stress. This approach to data analysis helps characterize stress response and recovery, and could be deployed to detect populations under stress, monitor health status, and conduct environmental monitoring.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Evaluating proxies for the drivers of natural gas productivity using machine-learning models

We report the extensive development of unconventional reservoirs using horizontal drilling and multistage hydraulic fracturing has generated large volumes of reservoir characterization and production data. The analysis of this abundant data using statistical methods and advanced machine-learning (ML) techniques can provide data-driven insights into well performance. Most predictive modeling studies have focused on the impact that different well completion and stimulation strategies have on well production but have not fully exploited the available in situ rock property data to determine its role in reservoir productivity. We have used machine-learning techniques to rank rock mechanical properties, microseismic attributes, and stimulation parameters in the order of their significance for predicting natural gas production from an unconventional reservoir. The data for this study came from a hydraulically fractured well in the Marcellus Shale in Monongalia County, West Virginia. The data classes included measurements aggregated by well completion stage that included (1) gas production, (2) well-log-derived measurements including bulk density, elastic moduli, shear impedance, compressional impedance, brittleness, and gamma measurements, (3) microseismic attributes, (4) long-period long-duration (LPLD) event counts, (5) fracture counts, and (6) stimulation parameters that included the fluid injection volume and average pumping pressure. To identify observable proxies for the drivers of gas production, we evaluated five commonly used ML approaches including multivariate adaptive regression spline, Gaussian mixture model, random forest, gradient boosting, and neural network. We selected five variables including LPLD event count, seismogenic b-value, hydraulic diffusivity, cumulative moment, and fluid volume as the features most likely to impact gas productivity at the stage level in the study area. The data-driven selection of these parameters for their importance in determining gas production can help reservoir engineers design more effective hydraulic-fracture treatments in the Marcellus Shale and other similar unconventional reservoirs. Plain language summary: We use machine-learning methods and data-driven selection of reservoir parameters to rank and better understand their importance in determining gas production, which can help reservoir engineers design more effective hydraulic-fracture treatments in the Marcellus Shale and other similar unconventional reservoirs.

58 GEOSCIENCES↗
DOE OSTI2024

DIRECT RF SAMPLING BASED LLRF CONTROL SYSTEM FOR C-BAND LINEAR ACCELERATOR

Low Level RF (LLRF) control systems of linear accel- erators (LINACs) are typically implemented with hetero- dyne based architectures, which have complex analog RF mixers for up and down conversion. The Gen 3 Radio Fre- quency System-on-Chip (RFSoC) device from AMD Xilinx integrates data converters with maximum RF frequency of 6 GHz. This enables direct RF sampling of C-band LLRF signal typically operated at 5.712 GHz without any analogue mixers, which can significantly simplify the system architec- ture. The data converters sample RF signals in higher order Nyquist zones and then up or down convert digitally by the integrated data path in RFSoC. The closed-loop feedback control firmware implemented in FPGA integrated in RF- SoC can process the base-band signal from the ADC data path and calculate the updated phase and amplitude to be up- mixed by the DAC data path. We have developed a C-band LLRF control RFSoC platform with direct RF sampling, which targets Cool Copper Collider (𝐶3) and other C or S band LINAC research and development projects. In this paper, the architecture of the platform will be described. We have optimized the configuration of the data converter and characterized performance of them with RF pulses. The test results for some of the key performance parameters for the LLRF platform with our custom solid-state amplifier, such as phase and amplitude stability, will be discussed in this paper.

Liu, C↗
DOE OSTI2018

Integrated Geologic Storage Prefeasibility Study Proximal to Dry Fork Power Station, Powder River Basin, Wyoming

The pre-feasibility study—funded by the Department of Energy CarbonSAFE program (DE-FE0029375)—is centred around Basin Electric’s Dry Fork Station (DFS) in Wyoming’s Powder River Basin. Dry Fork Station, completed in 2011, is a high efficient coal-fired power plant that emits 3.3 million tons of CO2 per annum. The DFS site also host’s the Wyoming Integrated Test Center (ITC) funded by a $15 million investment by the State of Wyoming. The ITC is a public-private partnership test bed for CCS technologies. Geologic storage sites are in immediate vicinity of the DFS providing significant opportunities for co-located source and saline storage. The Powder River Basin (PRB) of Wyoming and Montana, was identified by NETL (2010) as having a “high potential” for commercial-scale carbon sequestration. The basin contains as much as 17,000 feet of sedimentary rock and covers an area of approximately 24,000 square miles. The PRB has a long history of hydrocarbon production and remaining undiscovered reserves. Accumulations and production of hydrocarbons in the basin indicate the presence of reservoir formations with significant pore volumes and impermeable sealing formations. This attribute alone suggests the reservoir and seal characteristics of the formations provide significant opportunities for CO₂ storage in saline reservoirs. Four high quality potential reservoir and sealing complexes have been identified for geologic storage. These formations range in depth from 6,500-9,500 feet underneath DFS including: (1) the Pennsylvanian Minnelusa Formation reservoir and Permian Goose Egg Formation (Opeche Shale) seal; (2) the Jurassic Hulett and Canyon Springs Sandstones of the Sundance Formation sealed by the Late Jurassic Upper Sundance Member and Morrison Formation and (3) the Early Cretaceous Lakota and Dakota, and Muddy Formation reservoirs sealed by the Mowry Shale. The preliminary reservoir characterization results integrate data from petrophysical well logs, core measurements, faults/fractures analysis, artificial penetrations, and published literature to evaluate geologic storage capacity and potential risk, for the Powder River Basin. These reservoir and seal combinations reside within ideal depth constraints and show suitable reservoir and seal characteristics conducive to commercial-scale storage. Specifically, this paper presents 1) high level description of the geologic storage complex 2) a first order risk analysis associated with pre-existing oil and gas wells, and 3) preliminary storage capacity and Area of Review estimates.

Quillinan, Scott↗
DOE OSTI2015

Genome-Wide Analysis of miRNA targets in Brachypodium and Biomass Energy Crops

MicroRNAs (miRNAs) contribute to the control of numerous biological processes through the regulation of specific target mRNAs. Although the identities of these targets are essential to elucidate miRNA function, the targets are much more difficult to identify than the small RNAs themselves. Before this work, we pioneered the genome-wide identification of the targets of Arabidopsis miRNAs using an approach called PARE (German et al., Nature Biotech. 2008; Nature Protocols, 2009). Under this project, we applied PARE to Brachypodium distachyon (Brachypodium), a model plant in the Poaceae family, which includes the major food grain and bioenergy crops. Through in-depth global analysis and examination of specific examples, this research greatly expanded our knowledge of miRNAs and target RNAs of Brachypodium. New regulation in response to environmental stress or tissue type was found, and many new miRNAs were discovered. More than 260 targets of new and known miRNAs with PARE sequences at the precise sites of miRNA-guided cleavage were identified and characterized. Combining PARE data with the small RNA data also identified the miRNAs responsible for initiating approximately 500 phased loci, including one of the novel miRNAs. PARE analysis also revealed that differentially expressed miRNAs in the same family guide specific target RNA cleavage in a correspondingly tissue-preferential manner. The project included generation of small RNA and PARE resources for bioenergy crops, to facilitate ongoing discovery of conserved miRNA-target RNA regulation. By associating specific miRNA-target RNA pairs with known physiological functions, the research provides insights about gene regulation in different tissues and in response to environmental stress. This, and release of new PARE and small RNA data sets should contribute basic knowledge to enhance breeding and may suggest new strategies for improvement of biomass energy crops.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Land-Atmosphere Feedback Experiment (LAFE) Science Plan

The Land-Atmosphere Feedback Experiment (LAFE; pronounced “la-fey”) deploys several state-of-the-art scanning lidar and remote sensing systems to the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility’s Southern Great Plains (SGP) site. These instruments will augment the ARM instrument suite in order to collect a data set for studying feedback processes between the land surface and the atmosphere. The novel synergy of remote-sensing systems will be applied for simultaneous measurements of land-surface fluxes and horizontal and vertical transport processes in the atmospheric convective boundary layer (CBL). The impact of spatial inhomogeneities of the soil-vegetation continuum on land-surface-atmosphere (LSA) feedback will be studied using the scanning capability of the instrumentation. The time period of the observations is August 2017, because large differences in surface fluxes between different fields and bare soil can be observed, e.g., pastures versus fields where the wheat has already been harvested. The remote sensing system synergy will consist of three components: 1) The SGP water vapor and temperature Raman lidar (SRL), the SGP Doppler lidar (SDL), and the National Center for Atmospheric Research (NCAR) water vapor differential absorption lidar (DIAL) (NDIAL) mainly in vertical staring modes to measure mean profiles and gradients of moisture, temperature, and horizontal wind. They will also measure profiles of higher-order turbulent moments in the water vapor and wind fields and profiles of the latent heat flux. 2) A novel scanning lidar system synergy consisting of the National Oceanic and Atmospheric Administration (NOAA) High-Resolution Doppler lidar (HRDL), the University of Hohenheim (UHOH) water-vapor differential absorption lidar (UDIAL), and the UHOH temperature Raman lidar (URL). These systems will perform coordinated range-height indicator (RHI) scans from just above the canopy level to the lower troposphere, including the interfacial layer of the CBL. The optimal azimuth is to the ENE of the SGP central facility, which takes advantage of both changes in the surface elevation and different crop types planted along that path. 3) The University of Wisconsin Space Science and Engineering Center Portable Atmospheric Research Center (SPARC) and the University of Oklahoma Collaborative Lower Atmospheric Mobile Profiling System (CLAMPS) operating two vertically pointing atmospheric emitted radiance interferometers (AERIs) and two Doppler lidar (DL) systems scanning cross track to the central RHI for determining the surface friction velocity and the horizontal variability of temperature, moisture, and wind. Thus, both the variability of surface fluxes and CBL dynamics and thermodynamics over the SGP site will be studied for the first time. The combination of these three components will enable us to estimate both the divergence of the latent heat profile and the advection of moisture. Thus, the moisture budget in the SGP domain can be studied. Furthermore, the simultaneous measurements of surface and entrainment fluxes as well as the daily cycle of the CBL thermodynamic state will provide a unique data set for characterizing LSA interaction in dependence of large-scale and local conditions such as soil moisture and the state of the vegetation. The measurements will also be applied for the development of improved parameterizations of surface fluxes and turbulence in the CBL. The latter is possible because mean profiles, gradients, higher-order moments, and fluxes are measured simultaneously. The results will be used for the verification of simulations of LSA feedback in large-eddy simulation (LES) and mesoscale models, which are planned for the SGP site. Due to the strong connection between the pre-convective state of the CBL and the formation of clouds and precipitation, this new generation of experiments will strongly contribute to the improvement of their representation in weather, climate, and earth system models.

Southern Great Plains, atmospheric boundary layer,↗
DOE OSTI2014

Characterization & Modeling of Materials in Glass-To-Metal Seals: Part I

To support higher fidelity modeling of residual stresses in glass-to-metal (GTM) seals and to demonstrate the accuracy of finite element analysis predictions, characterization and validation data have been collected for Sandia’s commonly used compression seal materials. The temperature dependence of the storage moduli, the shear relaxation modulus master curve and structural relaxation of the Schott 8061 glass were measured and stress-strain curves were generated for SS304L VAR in small strain regimes typical of GTM seal applications spanning temperatures from 20 to 500 C. Material models were calibrated and finite element predictions are being compared to measured data to assess the accuracy of predictions.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Groundwater flow simulation of the Savannah River Site general separations area

The most recent groundwater flow model of the General Separations Area, Savannah River Site, is referred to as the “GSA/PORFLOW” model. GSA/PORFLOW was developed in 2004 by porting an existing General Separations Area groundwater flow model from the FACT code to the PORFLOW code. The preceding “GSA/FACT” model was developed in 1997 using characterization and monitoring data through the mid-1990’s. Both models were manually calibrated to field data. Significantly more field data have been acquired since the 1990’s and model calibration using mathematical optimization software has become routine and recommended practice. The current task involved updating the GSA/PORFLOW model using selected field data current through at least 2015, and use of the PEST code to calibrate the model and quantify parameter uncertainty. This new GSA groundwater flow model is named “GSA2016” in reference to the year in which most development occurred. The GSA2016 model update is intended to address issues raised by the DOE Low-Level Waste (LLW) Disposal Facility Federal Review Group (LFRG) in a 2008 review of the E-Area Performance Assessment, and by the Nuclear Regulatory Commission in reviews of tank closure and Saltstone Disposal Facility Performance Assessments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Status Report on the Water-Based NSTF RCCS Capability: Preparations and Design for the Transformation of the Natural Convection Shutdown Heat Removal Test Facility (NSTF) From Air to Water-based Cooling

The following report provides an overview of the current status of the water-based transformation, including details of the design, geometry, and fabrication of the test section and network piping, for the ½ scale water-based NSTF program at Argonne National Laboratory. In early FY2015, efforts towards a water-based design began in parallel with on-going air-based work, and began by identifying top level objectives of the transformation. Scaling studies and preparation tasks with computational modeling were carried out to guide the design decisions, minimize distortions, and ensure relevant data among scales. This entailed close collaboration with AREVA, whose water-based RCCS (included as part of their 625 MWt SC-HTGR) served as the primary design basis for incorporation into the NSTF. A literature review of previous works was made, with an emphasis placed on similar facilities, relevance to passive decay heat removal, and details pertaining to two-phase flow and measurement techniques. The study focused on input from key designers and a thermal analysis of existing cooling panels (e.g. at TAMU and UW-Madison) and two proposed AREVA cooling panels. A base case was used as a reference point for parametric studies of effects from varying tube spacing (pitch), tube diameter, fin thickness, and materials. Then, a structural analysis was performed to ensure safe material stresses during high temperature operation. Details of the pipe network geometry and guidelines for design of the water storage tank are finally presented, followed by engineering drawings in the appendix. The results of this study have identified a suitable configuration to support both the ANL/DOE project goals and the DOE vision to provide AREVA with data suitable for characterizing the RCCS of their full scale HTGR design. The dimensions were not selected for optimal RCCS performance, but instead to serve as a representative yet bounding configuration for future implementation into a full scale design. Scaling distortions are unavoidable; however, they can be accurately predicted based on earlier works of derived similarity solutions. Flexibility remained a primary design philosophy, and will allow the test facility to easily accommodate future alterations. The final design for the test section and network piping is as follows: riser tubes: 1.5” Schedule 160, 5.91” (150-mm) pitch, 304L stainless, heat transfer panels: 5/16” plates, 4.01” (102-mm) width, full penetration weld to risers, 304L stainless, split into 4 panels per riser separated by horizontal 1/8” gaps, test section: Eight (x8) riser tubes and nine (x9) heat transfer panels, fabricated into banks of two (x2) riser tubes and three (x3) fins, joined to form single section, and network geometry: 4.0” Schedule 40, 304L stainless. Details of the water storage tank will reflect competing effects such as thermal hydraulic phenomena during single and two-phase operation. These considerations include mixing during single-phase jet penetration, condensation of rising bubbles during two-phase discharge, bubble entrainment into the liquid outlet, and liquid carry-over into the steam outlet.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Operational History of the Area 3 Radioactive Waste Management Site

Report presents information based on characterization and monitoring data, historical documentation and records, modeling studies, evaluations, and process knowledge for the Area 3 Radioactive Waste Management Site on the Nevada National Security Site.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

MINOS Infrasound Analysis Synopsis

This report was written as a guide to working with infrasound data collected as part of the Multi-Informatics for Nuclear Operations Scenarios (MINOS)project, an NA-22 funded venture. The main purpose of overall MINOS project is the combination of multiple, disparate data modalities to characterize the operations at a nuclear facility, specifically instrumenting and studying the High-Flux Isotope Reactor (HFIR) and Radiochemical Engineering Development Center (REDC) locate at Oak Ridge National Laboratory in Oak Ridge, TN. HFIR is an 85 MW research reactor and is used primarily for production of medical radioisotopes, material irradiation experiments, neutron activation, and neutron scattering. Targets for the reactor are constructed, processed, and dissolved at REDC. REDC also hosts other glove-box and hot-cell type activities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Integrated Heat Exchanger-Phase Change Material Thermal Energy Storage System

The purpose of this study is to experimentally investigate the thermal performance of an innovative thermal energy storage (TES) system that combines the advantages of the phase-change material (PCM)/graphite foam latent heat TES medium developed at Argonne National Laboratory (Argonne) and the internally supported plate-fin (ISPE) cell architecture heat transfer fluid (HTF) flow channels developed at Brayton Energy (Brayton). Several essential tasks were accomplished: (1) Thermal property characterization. Thermal properties of the graphite foam were characterized, providing necessary data for experimental result analysis and numerical simulation. (2) Design and optimization of lab-scale test module. Based on Brayton’s full-scale heat exchanger (HX)-TES system, the experimental test module was designed, optimized, and fabricated. (3) Thermal performance testing and data analysis. Five cycle tests were successfully conducted—including one with approximately 3.5 psig of pressure applied to the diaphragms—to investigate the thermal performance of the experimental test module for charging and discharging. Temperature profiles were generated for each charging test and discharging test as a function of time. The temperature profiles clearly show three TES stages: sensible heat (temperature increase), latent heat (melting), and sensible heat (temperature increase) for the charging process. Similarly, the temperature profiles clearly show three thermal energy release stages: sensible heat (temperature decrease), latent heat (solidification), and sensible heat (temperature decrease). Melting and solidification of the PCM generally occurred in relatively narrow temperature ranges, indicated by the flattened temperature regions in the temperature profiles. These phase changes ranged approximately 3°C for melting and 3.5°C for solidification. The charging and discharging temperature profiles were similar for similar experimental parameter tests whether or not pressure was applied to the diaphragm to eliminate the gap between the HX surface and the TES subsystem. This indicates that the effect of a small gap between the HX surface and the TES subsystem is insignificant for charging and discharging. (4) Comparison of experimental data and simulation results. We compared the experimental data to the numerical simulation results. Numerical simulations were conducted by using the ANSYS FLUENT 2019 R3 commercial computational fluid dynamics software. The predicted phase-change times agreed reasonably well with those from the experimental data. In most cases, the estimated time differences between the relative phase changes were within 16%. The predicted start and end times for the charging process agreed well with those from the experimental data. However, the simulation results showed earlier start and end times than the experimental data for the discharging process. Overall, the experimental data and its comparison with the simulation predictions verified the technical viability of the integrated ISPF HX-PCM/graphite foam latent-heat TES system.

25 ENERGY STORAGE↗
DOE OSTI2021

Review of Neutron Uncertainty Types

The assessment of neutron data requires understanding the uncertainty. The uncertainty of the final quantities of interest, neutron multiplication and mass, is a combination of many other uncertainties because it is a combination of many other variables. The equations for the values of neutron multiplication and mass are quite complex. The relations between the many contributing variables and their uncertainties are complicated leading to complications in combining them. Additionally, some are statistical in nature, while others are systematic. In an effort to better understand and quantify the total uncertainty in neutron multiplication and SNM mass, they have been subdivided into four categories: setup, detector response, nuclear data, and object characterization. This paper discusses the four categories and what types of uncertainties are in each of them. This effort attempts to generalize this process for any neutron detector, but many of our examples show the Next Generation Multiplicity Detector (MC-15).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

CERES: CRISPR Engineering for the Rapid Enhancement of Strains

Previous strain development efforts for cyanobacteria have failed to achieve the necessary productivities needed to support economic biofuel production. We proposed to develop CRISPR Engineering for Rapid Enhancement of Strains (CERES). We developed genetic and computational tools to enable future high-throughput screening of CRISPR interference (CRISPRi) libraries in the cyanobacterium Synechococcus sp. PCC 7002, including: (1) Operon- SEQer: an ensemble of algorithms for predicting operon pairs using RNA-seq data, (2) experimental characterization and machine learning prediction of gRNA design rules for CRISPRi, and (3) a shuttle vector for gene expression. These tools lay the foundation for CRISPR library screening to develop cyanobacterial strains that are optimized for growth or metabolite production under a wide range of environmental conditions. The optimization of cyanobacterial strains will directly advance U.S. energy and climate security by enabling domestic biofuel production while simultaneously mitigating atmospheric greenhouse gases through photoautotrophic fixation of carbon dioxide.

09 BIOMASS FUELS↗
DOE OSTI2021

Locating Seismic Events with Local-Distance Data

As the seismic monitoring community advances toward detecting, identifying, and locating ever-smaller natural and anthropogenic events, the need is constantly increasing for higher resolution, higher fidelity data, models, and methods for accurately characterizing events. Local-distance seismic data provide robust constraints on event locations, but also introduce complexity due to the significant geologic heterogeneity of the Earth’s crust and upper mantle, and the relative sparsity of data that often occurs with small events recorded on regional seismic networks. Identifying the critical characteristics for improving local-scale event locations and the factors that impact location accuracy and reliability is an ongoing challenge for the seismic community. Using Utah as a test case, we examine three data sets of varying duration, finesse, and magnitude to investigate the effects of local earth structure and modeling parameters on local-distance event location precision and accuracy. We observe that the most critical elements controlling relocation precision are azimuthal coverage and local-scale velocity structure, with tradeoffs based on event depth, type, location, and range.

42 ENGINEERING↗