Search NASA⌕ Search

SEARCH · Search NASA

Results for “Featurization”

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 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Two-Speed Rotorcraft Research Transmission Power-Loss Associated with the Lubrication and Hydraulic Rotating Feed-Through Design Feature

An investigation was completed into the power loss associated with a rotating feed-through (RFT) design feature used to transfer lubrication and a hydraulic control signal from the static reference frame to a rotating reference frame in the NASA GRC two-speed transmission tests conducted in the Variable-Speed Drive Test Rig. The RFT feature, not commercially available, was created specifically for this research project and is integral to all two-speed transmission configurations tested, as well as a variant concept design for a geared variable-speed transmission presented at AHS Forum 71 in 2015. The experimental set-up and results from measurements in the isolated rotating-feed-through (RFT) experiments are presented. Results were used in an overall power loss assessment for a scaled conceptual 1,000 horsepower inline concentric two-speed transmission to support a NASA Revolutionary Vertical Lift Technologies (RVLT) Technical Challenge, demonstrating 50% speed change with less than 2% power loss while maintaining current power-to-weight ratios.

Rotorcraft↗
NASA NTRS2018

Two-Speed Rotorcraft Research Transmission Power-Loss Associated with the Lubrication and Hydraulic Rotating Feed-Through Design Feature

An investigation was completed into the power loss associated with a rotating feed-through (RFT) design feature used to transfer lubrication and a hydraulic control signal from the static reference frame to a rotating reference frame in the NASA GRC two-speed transmission tests conducted in the Variable-Speed Drive Test Rig. The RFT feature, not commercially available, was created specifically for this research project and is integral to all two-speed transmission configurations tested, as well as a variant concept design for a geared variable-speed transmission presented at AHS Forum 71 in 2015. The experimental set-up and results from measurements in the isolated rotating-feed-through (RFT) experiments are presented. Results were used in an overall power loss assessment for a scaled conceptual 1,000 horsepower inline concentric two-speed transmission to support a NASA Revolutionary Vertical Lift Technologies (RVLT) Technical Challenge, demonstrating 50% speed change with less than 2% power loss while maintaining current power-to-weight ratios.

Rotorcraft↗
NASA NTRS2016

Cyclotron Resonant Scattering Feature Simulations I. Thermally Averaged Cyclotron Scattering Cross Sections, Mean Free Photon-Path Tables, and Electron Momentum Sampling

Electron cyclotron resonant scattering features (CRSFs) are observed as absorption-like lines in the spectra of X-ray pulsars. A significant fraction of the computing time for Monte Carlo simulations of these quantum mechanical features is spent on the calculation of the mean free path for each individual photon before scattering, since it involves a complex numerical integration over the scattering cross section and the (thermal) velocity distribution of the scattering electrons. We aim to numerically calculate interpolation tables which can be used in CRSF simulations to sample the mean free path of the scattering photon and the momentum of the scattering electron. The tables also contain all the information required for sampling the scattering electron's final spin. The tables were calculated using an adaptive Simpson integration scheme. The energy and angle grids were refined until a prescribed accuracy is reached. The tables are used by our simulation code to produce artificial CRSF spectra. The electron momenta sampled during these simulations were analyzed and justified using theoretically determined boundaries. We present a complete set of tables suited for mean free path calculations of Monte Carlo simulations of the cyclotron scattering process for conditions expected in typical X-ray pulsar accretion columns (0.01 B/B(sub crit) is less than or equal to 0.12, where B(sub crit) = 4.413 x 1013 G, and 3 keV kBT 15 keV). The sampling of the tables is chosen such that the results have an estimated relative error of at most 1/15 for all points in the grid. The tables are available online (see link in footnote, page 1).

Schwarm, F.-W.↗
NASA NTRS2018

NASA D3R: 2.0, Enhanced Radar with New Data and Control Features

The NASA dual-frequency, dual-polarization, Doppler radar (D3R) was developed to support development of algorithms and validation for the global precipitation measurement (GPM) missions dual-frequency precipitation radar (DPR). The D3R has participated extensively in various field campaigns in North America with geographic features covering both summer and winter climatic regimes. During the year 2017, D3R went through a major upgrade, specially with the digital receiver and waveform generation subsystems. In this work, the D3R systems upgrade will be discussed with a focus on key features of the new system. The new flexible architecture will enable new research capabilities that will be described.

Kumar, Mohit↗
NASA NTRS2019

Saturn Atmospheric Dynamics One Year After Cassini: Long-Lived Features and Time Variations in the Drift of the Hexagon

We examine Saturn's atmospheric dynamics with observations in the visible range from ground-based telescopes and Hubble Space Telescope (HST). We present a detailed analysis of observations acquired during 2018 obtaining drift rates of major meteorological systems from the equator to the North polar hexagon. A system of polar storms that appeared in the planet in March 2018 and remained active with a complex phenomenology at least until September is analyzed elsewhere [Sanchez-Lavega et al., 2019]. Many of the regular cloud features visible in 2018 are long-lived and can be identified in Saturn images in 2017, and in some cases, for up to a decade using also Cassini ISS images. Without considering the polar storms, the most interesting long-lived cloud systems are: i) A bright white spot in the Equatorial Zone that can be tracked continuously since 2014 with minimal changes in its zonal velocity, which was 444:3 +or- 3:1 ms(exp -1) in 2014 and 452:4 + or - 1:7 ms(exp -1) in 2018. This velocity is remarkably different from the zonal winds at the cloud level at its latitude during the Cassini mission, and is closer to zonal winds obtained at the time of the Voyagers flybys and to zonal winds from Cassini VIMS infrared images of the lower atmosphere. ii) A large long-lived Anticyclone Vortex, here AV, that formed after the Great White Spot of 2010-2011. This vortex has changed significantly in visual contrast, drift rate and latitude with minor changes in size over the last years. iii) A system of subpolar vortices at latitudes 60-65N present at least since 2011. These vortices and additional atmospheric features here studied follow drift rates consistent with zonal winds obtained by Cassini. We also present a study of the positions of the vertices of Saturn's North polar hexagon from 2015 to 2018. These measurements are compared with previous analyses during the Cassini mission (2007-2014), observations with HST in the 90s, and data from the Voyagers in 1980-1981 to explore the long term variability of the hexagon's drift rate. We find variations in the drift rate of the hexagon through these epochs that can not be fit by seasonal changes in the polar area. Instead, the different drift rates reinforce the role of the North Polar Spot that was present in the Voyager epoch and in the early 90s to cause a faster drift rate of the hexagon at that time compared with the current slower one.

R Hueso↗
NASA NTRS2019

Evaluating Precipitation Features and Rainfall Characteristics in a Multi-scale Modeling Framework

Cloud and precipitation systems over the tropics and subtropics are simulated with a multi-scale modeling framework (MMF) and compared against the TRMM radar precipitation features (RPFs) product. A methodology, in close analogy to the TRMM RPFs, is developed to analyze simulated cloud precipitating structures from the embedded two-dimensional cloud-resolving models (CRMs) within an MMF. Despite the two-dimensionality of the CRMs, the simulated RPFs population distribution, and horizontal and vertical structure are in good agreement with TRMM observations. However, some deficits are also found in the model simulations. The model tends to overestimate mean convective precipitation rates for RPFs with a size less than 100 km, contributing to the excessive precipitation biases in the warm pool and western Pacific, western and northern India Ocean, and eastern Pacific commonly found in most MMFs. For large features with a size greater than 150 km, both convective and stratiform rain rates are underestimated. The distribution of maximum radar echo top heights as a function of RPF size is well simulated except the model tends to underestimate the occurrence frequency of maximum heights greater than 15 km. The maximum echo top heights for convective cells embedded within large RPFs with a size greater than 150 km are also underestimated. The cyclic lateral boundary with a limited model domain generates artificial occurrences for RPFs with a size close to the model domain size, producing a significant contribution to the total rainfall due to their sizes. This cyclic lateral boundary effect can be easily identified and quantified in both probability and cumulative distribution functions of RPFs. The geophysical distribution of the population of the largest RPFs in the control experiment shows they are mainly located in the Subtropics but also partially contribute to the common MMF biases of excessive precipitation in the Tropics. Sensitivity experiments using CRMs with different domain sizes and different grid spacings show larger domains (higher resolution) tend to shift the RPFs distribution to large (small) sizes. The cyclic lateral boundary biases increase as CRM domain size decreases. The impacts of model horizontal and vertical resolution on simulated convective systems are also investigated.

Chern, Jiun-Dar↗
NASA NTRS2019

High Angular Resolution Astrophysics: Resolving Stellar Surface Features

We are now in an era where we can image details on the surfaces of stars. When resolving stellar surfaces, we see that every surface is uniquely complicated. Each imaged star provides insight into not only the stellar surface structures, but also the stellar interiors suggesting constraints on evolution and dynamo models. As more resources become operational in the coming years, imaging stellar surfaces should become commonplace for revealing the true nature of stars. Here, we discuss the main types of stars for which imaging surface features is currently useful and what improved observing techniques would provide for imaging stellar surface features.

Rachael M. Roettenbacher↗
NASA NTRS2020

SCExAO/CHARIS High-contrast Imaging of Spirals and Darkening Features in the HD 34700 A Protoplanetary Disk

We present Subaru/SCExAO+Coronagraphic High Angular Resolution Imaging Spectrograph (CHARIS) broadband (JHK-band) integral field spectroscopy of HD 34700 A. CHARIS data recover HD 34700 A's disk ring and confirm multiple spirals discovered by Monnier et al. We set limits on substellar companions of ∼12 MJup at 0.″3 (in the ring gap) and ∼5 M(Jup) at 0."75 (outside the ring). The data reveal darkening effects on the ring and spiral, although we do not identify the origin of each feature such as shadows or physical features related to the outer spirals. Geometric albedos converted from the surface brightness suggest a greater scale height and/or prominently abundant submicron dust at position angles between ∼45° and 90°. Spiral fitting resulted in very large pitch angles (∼30°–50°); a stellar flyby of HD 34700 B or infall from a possible envelope is perhaps a reasonable scenario to explain the large pitch angles.

Taichi Uyama↗
NASA NTRS2020

Evaluating Precipitation Features and Rainfall Characteristics in a Multi‐Scale Modeling Framework

Cloud and precipitation systems are simulated with a multi‐scale modeling framework (MMF) and compared over the Tropics and Subtropics against the Tropical Rainfall Measuring Mission (TRMM) Radar‐defined Precipitation Features (RPFs) product. A methodology, in close analogy to the TRMM RPFs, is developed to produce simulated precipitation features (PFs) from the output of the embedded two‐dimensional (2D) cloud‐resolving models (CRMs) within an MMF. Despite the limitations of 2D CRMs, the simulated population distribution, horizontal and vertical structure of PFs, and the geographical location and local rainfall contribution of mesoscale convective systems (MCSs) are in good agreement with the TRMM observations. However, some model discrepancies are found and can be identified and quantified within the PF distributions. Using model biases in relative population and rainfall contributions, PFs can be characterized into four size categories: small, medium to large, very large, and extremely large. Four different major mechanisms might account for the model biases in each different category: (1) the two‐dimensionality of the CRMs, (2) a positive convection‐wind‐evaporation feedback loop, (3) an artificial dynamic constraint in a bounded CRM domain with cyclic boundaries, and (4) the limited CRM domain size. The second and fourth mechanisms tend to contribute to the excessive tropical precipitation biases commonly found in most MMFs, whereas the other mechanisms reduce rainfall contributions from small and very large PFs. MMF sensitivity experiments with various CRM domain sizes and grid spacings showed that larger domains (higher resolutions) tend to shift PF populations toward larger (smaller) sizes.

Jiun-Dar Chern↗
NASA NTRSDate not supplied

Towards Thermal Protection System Certification by Analysis: Identification and Implication of Features

The thermal protection systems (TPS) to be used for upcoming sample return missions (e.g., Mars Sample Return) and future crewed missions to the Moon and Mars are subject to stringent reliability criteria. The certification of TPS is conducted through extensive testing, which can include Arc Jet testing to understand ablative behavior and non-destructive evaluation (NDE) to identify features that could lead to sub-optimal performance during entry. Unexpected features observed during fabrication of large-scale articles often require additional testing to certify, which in the very worst cases can impact schedule and contribute to cost.

J. B. Haskins↗
NASA NTRSDate not supplied

Dense Feature Tracking of Atmospheric Winds with Deep Optical Flow

Atmospheric winds are a key physical phenomenon impacting natural hazards, energy transport, ocean currents, large-scale circulation, and ecosystem fluxes. Observing winds is a complex process and presents a large gap in NASA’s Earth Observation System. Atmospheric motion vectors (AMVs) aim to fill this gap by making numerical estimates of cloud movement between sequences of multi-spectral satellite images, tracking clouds and water vapor. Recent imaging hardware and software advancements have enabled the use of numerical optical flow techniques to produce accurate and dense vector fields outperforming traditional methods. This work presents WindFlow as the first machine learning based system for feature tracking atmospheric motion using optical flow. Due to the lack of large-scale satellite-based observations, we leverage high-resolution numerical simulations from NASA's GEOS-5 Nature Run to perform supervised learning and transfer to satellite images. We demonstrate that our approach using deep learning based optical flow scales to ultra-high-resolution images of size 2881x5760 with less than 1 m/s bias and 2.5 m/s average error. Four network and learning architectures are compared and it is found that recurrent all-pairs field transforms (RAFT) produces the lowest errors on all metrics for wind speed and direction. Results on held out numerical outputs shows RAFT's good performance in each of the spatial, temporal, and physical dimensions. A comparison between WindFlow and an operational AMV product against rawinsonde observations show that RAFT transfers across simulations and thermal infrared satellite observations. This work shows that machine learning based optical flow is an efficient approach to generating robust feature tracking for AMVs consistently over large regions.

Atmospheric winds↗
NASA NTRS2023

NASA Engineering and Safety Center Technical Bulletin No. 23-01: Including Key Design Features in Safety-Critical Pyrotechnic Firing Circuits

Pyrotechnic systems often fall into a unique category in that inadvertent activation of these systems resulting from a fault and/or lack of safe margins can lead directly to loss of crew. For example, untimely activation of pyrotechnics used for a flight termination system could override an abort capability. Over the years, NASA and the military have learned lessons about safe pyrotechnic circuit design and test, many of which are codified. However, with NASA’s recent efforts to move toward a development model than leans more heavily on Commercial Partners these requirements have not always been directly levied on projects and in some cases been misinterpreted. This bulletin describes key safety features of pyrotechnic firing circuit design and provides rationale for inclusion of each feature.

Pyrotechnic Firing Curcuits↗
NASA NTRSDate not supplied

Leveraging the Multiplatform Precipitation Feature Database of Combined Ground Radar and Satellite Lightning Observations for Convective Studies

The Multiplatform Precipitation Feature (MPF) database combines coincident observations of lightning from space with satellite- and ground-based radar data in a storm-based, feature-defined framework. The concept for the MPF database stems from the motivation to extend the scale and scope of investigations into the complex connections between ice precipitation, updrafts, and lightning in thunderstorms. The earliest iteration of the MPF database incorporates NASA International Space Station Lightning Imaging Sensor (ISS LIS) observations alongside the NASA Global Precipitation Measurement (GPM) Mission Dual-frequency Precipitation Radar (DPR) and Validation Network (VN). Because of the specific role of the GPM VN in forming the first MPFs, this subset is referred to as the VNMPF database. The synthesis of these multi-scale and multi-resolution observations leveraged each platform’s unique insights into convective properties and processes, offering a more complete view of deep convection over the large viewing area afforded by satellite coverage. The VNMPF database established the feasibility and infrastructure to combine microphysical, kinematic, and lightning observations from multiple satellite- and ground-based platforms. Following this successful proof-of-concept, recent progress has expanded the MPF database to make use of coincident ISS LIS lightning observations and data from the operational Weather Surveillance Radar - 1988 Doppler (WSR-88D) network, where individual WSR-88D proximity facilitates vertical wind retrievals via dual-Doppler analysis. These database changes have expanded the scope of the dataset by removing the requirement for coincident GPM and ISS LIS overpasses. This increases the sample size dramatically and facilitates analysis of higher-resolution radar-derived properties. These advancements allow both storm-scale and unprecedented broad statistical analyses of deep convection from electrical, kinematic, and microphysical perspectives over the contiguous United States. This presentation outlines the construction of the new MPF database and introduces some preliminary analyses of the convection captured within it. Early results summarize relationships based on updraft characteristics ascertained from WSR-88D dual-Doppler three-dimensional wind retrievals, properties of ice microphysics gleaned from dual-polarization analyses, and electrical characteristics observed by the ISS LIS. The expanded scale and scope offered by more than five years of ISS LIS observations enable new insights into regional and seasonal variations in the microphysical, kinematic, and electrical relationships of convection. Analysis of the database highlights the potential for advancements in lightning meteorology made possible by combining large-scale spaceborne lightning detection and proven storm interrogation tools such as operational polarimetric Doppler radar.

Lightning↗
NASA NTRS2024

GCAS Visualization Codebase Augmentation Migration to Modern Standards and Feature Enhancements

The Glenn Research Center Communication Analysis Suite (GCAS) includes many analysis tools that can be used to support a wide range of scenarios. It includes a visualization tool that implements the three.js graphics library to display a three-dimensional (3D) representation of its results. This software will enable researchers, engineers, and mission planners to interact intuitively with and understand the results of their analyses, which might not be apparent from raw data. With NASA’s efforts to return humans to the Moon as a part of the Artemis missions, the GCAS has been used extensively for lunar terrain and landing system development analysis, which is vital to ensuring mission achievability and safety. This has created the need to add several significant features to the visualization tool, such as the ability to display the terrain of the lunar surface accurately and to provide information demonstrating how a given region might impact mission objectives. Many of the changes made to the visualization tool can be separated into one of three general advancements: code restructuring to adhere to modern coding standards and practices, new user camera controls for first-person and third-person perspective views, and a terrain generation feature to enable rendering highly accurate terrains based on any celestial body’s digital elevation model (DEM) in GeoTIFF format. These improvements notably elevate the visualization tool's functionality, accuracy, and user interaction while providing a robust foundation for future development.

Visualization↗
DOE OSTI2022

Next Generation System Analysis Model: Recently Added Features and Future Plans

To better enable informed decision-making regarding the back-end of the nuclear fuel cycle, the Integrated Waste Management System (IWMS) program within the U.S. Department of Energy, Office of Nuclear Energy (DOE-NE) has been sponsoring the development and application of system analysis tools capable of analyzing various system options for the management of spent nuclear fuel (SNF) and high-level radioactive waste (HLW).With these tools, IWMS architecture analyses are being conducted to support the future deployment of a comprehensive nuclear waste management system that considers all major back-end aspects of the nuclear fuel cycle (i.e., transportation, storage, and disposal). The Next Generation System Analysis Model (NGSAM) is an agent-based simulation software tool expressly designed to be capable of modeling features within various IWMS architectures. NGSAM imports data from Oak Ridge National Laboratory (ORNL)’s unified database (e.g., historic assembly information, thermal profiles for assembly heat, and at-reactor dry storage loadings) to ensure that each simulation initializes with a realistic representation of the state of commercial SNF in the U.S. Recent major enhancements implemented into NGSAM in the period since NGSAM was last presented at the WM2019 conference include: • Tracking of railroad escort car acquisition and buffer car acquisition • The addition of heavy haul truck (HHT) and barge routes for some sites, as well as support for user-defined inter-modal routes • Updates to the logic that checks the transportation cask thermal limit maps prior to package transport • An allocation method that predicts when reactor sites would pack assemblies from their spent fuel pools for dry storage, and prioritizes shipments directly from the pools of those reactor sites in the preceding periods (before the predicted loadings to dry storage), thus reducing the number of casks loaded into dry storage at reactor sites • The addition of “reactor site family” operational limits to restrict the number of loads of SNF taken from the pool and from dry storage at a given reactor site each year • Added support for multiple canister loading map options and packages with multiple compatible transportation overpacks • Updates to the handling of non-commercial SNF, including a new database that contains data to support the updates • Updates to allow analysis of hypothetical scenarios which include repackaging at reactor sites, e.g., for possible comparative analysis with other scenarios • Implementation of additional output reports, or modification of existing ones • The ability to generate and implement user edits via the NGSAM website • The ability to model loading SNF from pool storage at an interim storage facility (ISF) into dry storage at the ISF • The ability to model consolidating SNF from different existing storage containers at a DOE site into the same DOE standard canister • The ability to model transferring SNF casks from one transportation mode to another, e.g., from HHT to rail, referred to as transloading. These new features have improved NGSAM capabilities and users’ experience with the model. Preliminary NGSAM requirements for modeling advanced reactor fuels, reprocessing, treatment, and conditioning were considered, and this paper describes them at a high level. Other nuclear fuel cycle system analysis tools developed under sponsorship of DOE-NE, like the VISION code developed at Idaho National Laboratory, might be better suited for initial high-level analysis of those technologies and advanced fuel cycles. As technologies are developed and system concepts evolve, NGSAM could provide value by providing more detailed modeling of transport, storage, and disposal of spent fuel and wastes from advanced reactors and advanced fuel cycles at the fuel element and waste container level.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Verification of Upcoming MCNP Features For Estimating Nuclear Data Sensitivities in Fixed Source Simulations [Abstract]

Predictive simulation codes, like the Monte Carlo N-Particle (MCNP) transport code, are used throughout the nuclear community. These simulations are based on nuclear data. Maximizing the accuracy and precision of nuclear data maximizes the accuracy and precision of the overall simulation. This is imperative to applications that rely on simulations. For example, improving nuclear data for special nuclear material improves simulation accuracy in stockpile stewardship applications, which results in larger safety margins and decreased operational costs. The improvement and validation of nuclear data is completed through integral benchmark experiments. Past benchmarks have primarily been limited to focus on the effective multiplication factor ($\kappa$ eff ); broadening the purview of benchmarks beyond $\kappa$ eff -dependent nuclear data addresses nuclear data deficiencies. Different response types depend on different areas of nuclear data. This dependence is quantified as nuclear data sensitivity: the change in response due to perturbation of a contributing parameter. The larger the nuclear data sensitivity of a response, the more the experiment is influenced by the uncertainties of the nuclear data. The optimization of nuclear data sensitivities in future benchmarks would result in more detailed validation of lesser studied areas of nuclear data. Currently, direct sensitivity capabilities are not easily found for all experiment types and parameters. An MCNP tool to directly estimate the cross section sensitivities of tallied values is under development. Additionally, updates have been made to the perturbation feature of MCNP, which can be used in a less direct approach to estimating sensitivities. This work verifies these features to estimate nuclear data sensitivities in fixed source simulations of a 4.5-kg sphere of alpha- phase weapons-grade plutonium surrounded by differing amounts of copper and polyethylene. Integrated estimates made using MCNP’s tools were found to statistically agree with integrated estimates made from manual perturbation of nuclear data proving the validity of the MCNP tools.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

On Feature, Classifier and Detector Fusers for U-235 Signatures Using Gamma Spectral Counts

Three types of information fusion strategies are studied to assess the performance of classifiers for detecting low-level U-235 radiation sources, using features obtained from gamma spectra of NaI detectors. These three strategies are based on using two spectral region features, fusing eight classifiers of diverse designs, and fusing multiple detectors located at different positions around the source. The inner, middle and outer groups of detectors, within a formation of two concentric circles and a spiral of 21 detectors, are identified based on their distance to the source, which is located at the center. This study provides two main qualitative insights into this classification task. First,the fusion of detectors leads to an overall improved classification performance, least in the inner group, most in the outer group, and in between for the middle group. Second, several classifiers and fusers achieve lower training error which does not translate to lower generalization error, indicating their over-fitting to training data.

Rao, Nageswara↗
DOE OSTI2022

Methods and systems for obtaining reconstructed low-frequency seismic data for determining a subsurface feature

A computer-implemented method for obtaining reconstructed seismic data for determining a subsurface feature, includes: determining an initial training velocity model, training a machine learning model based on first training seismic data and second training seismic data generated from the training velocity model, the first training seismic data corresponding to one or more first frequencies, the second training seismic data corresponding to one or more second frequencies lower than the one or more first frequencies, obtaining, based on measured seismic data and the machine learning model, reconstructed seismic data corresponding to the one or more second frequencies, generating a velocity model based on the measured seismic data, the reconstructed seismic data, and a full waveform inversion (FWI), and when the generated velocity model does not satisfy a preset condition, updating the training velocity model based on the generated velocity model, to obtain updated reconstructed seismic data for determining a subsurface feature.

58 GEOSCIENCES↗