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At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Permeability Prediction Using Vision Transformers

Accurate permeability predictions remain pivotal for understanding fluid flow in porous media, influencing crucial operations across petroleum engineering, hydrogeology, and related fields. Traditional approaches, while robust, often grapple with the inherent heterogeneity of reservoir rocks. With the advent of deep learning, convolutional neural networks (CNNs) have emerged as potent tools in image-based permeability estimation, capitalizing on micro-CT scans and digital rock imagery. This paper introduces a novel paradigm, employing vision transformers (ViTs)—a recent advancement in computer vision—for this crucial task. ViTs, which segment images into fixed-sized patches and process them through transformer architectures, present a promising alternative to CNNs. We present a methodology for implementing ViTs for permeability prediction, its results on diverse rock samples, and a comparison against conventional CNNs. The prediction results suggest that, with adequate training data, ViTs can match or surpass the predictive accuracy of CNNs, especially in rocks exhibiting significant heterogeneity. This study underscores the potential of ViTs as an innovative tool in permeability prediction, paving the way for further research and integration into mainstream reservoir characterization workflows.

58 GEOSCIENCES↗
NASA NTRS1990

Forcing of Climate Variations by Mev-gev Particles

Changes in ionization production in the lower stratosphere by a few percent during Forbush decreases have been shown to correlate well with changes in winter tropospheric dynamics by a similar relatively small amount. Changes in ionization production by tens of percent on the decadal time scale have been shown to be correlated with changes in winter storm frequencies by tens of percent in the western North Atlantic. Changes in total solar irradiance or solar UV do not have time variations to match the tropospheric variations on the day to day time scales discussed here. Forcing related to magnetic activity is not supported. Thus solar wind/MeV-GeV particle changes appear to be the only viable forcing function for these day to day variations. If solar wind/particle forcing of a few percent amplitude can produce short term weather responses, then observed changes by tens of percent on the decadal and centennial time scale could produce climate changes on these longer time scales. The changes in circulation involved would produce regional climate changes, as observed. At present the relations between stratospheric ionization, electric fields and chemistry and aerosol and cloud microphysics are as poorly known as the relations between the latter and storm feedback processes. However, the capability for investigating these relationships now exists and has recently been most successfully used for elucidating the stratospheric chemistry and cloud microphysics associated with the Antarctic ozone hole. The economic benefits of being able to predict winter severity on an interannual basis, and the extent to which climate change related to solar variability will add to or substract from the greenhouse effect, should be more than adequate to justify support for research in this area.

Tinsley, Brian A.↗
NASA NTRSDate not supplied

Improved Prediction of Losses with Large Eddy Simulation in a Low-Pressure Turbine

There is a need to improve predictions of losses resulting from large eddy simulations (LES) of low-pressure turbines (LPT) in gas turbines. This may be done by assessing the accuracy of predictions against validation data and understanding the source of any inaccuracies. LES is a promising approach for capturing the laminar/turbulent transition process in a LPT. In previous studies, the authors utilized LES to model the flow field over a Variable Speed Power Turbine (VSPT) blade and successfully captured characteristic features of separation/reattachment and transition on the suction side at both the cruise (positive incidence) and take-off conditions (negative incidence) and as well, simulated the effect of freestream turbulence (FST) on those phenomena. The predicted pressure loading profiles agreed well with the experimental data for both a high and a low FST case at a Reynolds number of Reex=220,000. In this paper, we present wake profiles resulting from computations for a range of FST values. Although the predicted wake profiles for the lowest FST case (Tu=0.5%) matched the experimental data, at higher FST (Tu=10-15%,) the wake was wider than the experimentally measured wake and for both cases were displaced laterally when compared to the experimental measurements. In our investigation of the causes of the said discrepancies we have identified important effects which could strongly influence the predicted wake profile. Predicted losses were improved by assuring the validity of the flow solution. This was done by utilizing spectral analysis to scrutinize the dynamic behavior of the wake and determine solution accuracy resulting from low mesh density and low accuracy of convective modeling.

CFD↗
DOE OSTI2011

Long gravitational-wave transients and associated detection strategies for a network of terrestrial interferometers

Searches for gravitational waves (GWs) traditionally focus on persistent sources (e.g., pulsars or the stochastic background) or on transients sources (e.g., compact binary inspirals or core-collapse supernovae), which last for time scales of milliseconds to seconds. We explore the possibility of long GW transients with unknown waveforms lasting from many seconds to weeks. We propose a novel analysis technique to bridge the gap between short O(s)''burst'' analyses and persistent stochastic analyses. Our technique utilizes frequency-time maps of GW strain cross power between two spatially separated terrestrial GW detectors. The application of our cross power statistic to searches for GW transients is framed as a pattern recognition problem, and we discuss several pattern-recognition techniques. We demonstrate these techniques by recovering simulated GW signals in simulated detector noise. We also recover environmental noise artifacts, thereby demonstrating a novel technique for the identification of such artifacts in GW interferometers. We compare the efficiency of this framework to other techniques such as matched filtering.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Double Higgs production at NNLO interfaced to parton showers in GENEVA

In this work, we study the production of Higgs boson pairs at next-to-next-to-leading order in QCD matched to parton showers, using the Geneva framework and working in the heavy-top-limit approximation. This includes the resummation of large logarithms of the zero-jettiness T 0 up to the next-to-next-to-next-to-leading-log accuracy. This process features an extremely large momentum transfer, which makes its study particularly relevant for matching schemes such as that employed in Geneva, where the resummation of a variable different from that used in the ordering of the parton shower is used. To further study this effect, we extend the original shower interface designed for Pythia8 to include other parton showers, such as Dire and Sherpa.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Transverse momentum dependent PDFs at N3LO

We compute the quark and gluon transverse momentum dependent parton distribution functions at next-to-next-to-next-to-leading order (N 3 LO) in perturbative QCD. Our calculation is based on an expansion of the differential Drell-Yan and gluon fusion Higgs production cross sections about their collinear limit. This method allows us to employ cutting edge multiloop techniques for the computation of cross sections to extract these universal building blocks of the collinear limit of QCD. The corresponding perturbative matching kernels for all channels are expressed in terms of simple harmonic polylogarithms up to weight five. As a byproduct, we confirm a previous computation of the soft function for transverse momentum factorization at N 3 LO. Our results are the last missing ingredient to extend the q T subtraction methods to N 3 LO and to obtain resummed q T spectra at N 3 LL' accuracy both for gluon as well as for quark initiated processes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Quantum kinetics of anomalous and nonlinear Hall effects in topological semimetals

Highlights: • Linear and photogalvanic anomalous Hall responses are systematically derived. • Extrinsic mechanisms of AHE include Gaussian, diffractive, hybrid skew scattering. • Diagrammatic calculations are matched to semiclassical picture of AHE. • The Pancharatnam phase of multifold fermions determines the skew scattering amplitude. • Photon-induced interband scattering are accompanied by coordinate shifts. We present a systematic microscopic derivation of the semiclassical Boltzmann equation for band structures with the finite Berry curvature based on Keldysh technique of nonequilibrium systems. In the analysis, an AC electrical driving field is kept up to quadratic order, and both cases of small and large frequencies corresponding to intra- and interband transitions are considered. In particular, this formulation is suitable for the study of nonlinear Hall effect and photogalvanic phenomena. The role of impurity scattering is carefully addressed. Specifically, in addition to previously studied side-jump and skew-scattering processes, quantum interference diffractive contributions are now explicitly incorporated within the developed framework. This theory is applied to multifold fermions in topological semimetals, for which the generic formula for the skew scattering rate from the Pancharatnam phase is obtained along with the corresponding anomalous Hall conductivity.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The Illumination of Thunderclouds by Lightning: 3. Retrieving Optical Source Altitude

Abstract Optical space‐based lightning sensors such as the Geostationary Lightning Mapper (GLM) detect and geolocate lightning by recording rapid changes in cloud top illumination. While lightning locations can be determined to within a pixel on the GLM imaging array, these instruments are not individually able to natively report lightning altitude. It has previously been shown that thunderclouds are illuminated differently based on the altitude of the optical source. In this study, we examine how altitude information can be extracted from the spatial distributions of GLM energy recorded from each optical pulse. We match GLM “groups” with Lightning Mapping Array (LMA) source data that accurately report the 3‐D positions of coincident Radio‐Frequency (RF) emitters. We then use machine learning methods to predict the mean LMA source altitudes matched to GLM groups using metrics from the optical data that describe the amplitude, breadth, and texture of the group spatial energy distribution. The resulting model can predict the LMA mean source altitude from GLM group data with a median absolute error of <1.5 km, which is sufficient to determine the location of the charge layer where the optical energy originated. This model is able to capture changes to the source altitude distribution in response to convective processes in the thunderstorm, and the GLM predictions can reveal the vertical structure of individual flashes ‐ enabling 3‐D flash geolocation with GLM for the first time. Future work will account for differences in thunderstorm charge/precipitation structures and viewing angle across the GLM Field of View.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Integrating solids and gases for attosecond pulse generation

Here, control of the field of few-cycle optical pulses has had an enormous impact on attosecond science. Subcycle pulses open the potential for non-adiabatic phase matching while concentrating the electric field so it can be used most efficiently. However, subcycle field transients have been difficult to generate. We exploit the perturbative response of a sub-100 µm thick monocrystalline quartz plate irradiated by an intense few-cycle 1.8 µm pulse, which creates a phase-controlled supercontinuum spectrum. Within the quartz, the pulse becomes space–time coupled as it generates a parallel second harmonic. Vacuum propagation naturally leads to a subcycle electric-field transient whose envelope is sculpted by the carrier envelope phase of the incident radiation. We show that a second medium (either gas or solid) can generate isolated attosecond pulses in the extreme ultraviolet region. With no optical elements between the components, the process is scalable to very high energy pulses and allows the use of diverse media.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

2022 AI Testbed Expeditions Report

By exploiting the coherent properties of a light source, coherent diffraction imaging (CDI) is able to obtain the sample image at a nanoscale resolution using the measured diffraction pattern. Bragg Coherent Diffraction Imaging (BCDI) has become valuable for recovering the displacement and strain field of crystals, providing a valuable tool in material science and solid-state physics. X-ray ptychography is another emerging CDI technique that can produce a high-resolution image of the extended sample and has become popular in many research areas (e.g., materials science, biology, electronics, and optics characterization). CDI including BCDI and ptychography has become an established technique in Synchrotron Facilities including the Advanced Photon Source (APS) and will greatly benefit from the 100x coherent flux increase of the upcoming APS Upgrade (APSU). The current image formation process in CDI employs iterative phase retrieval algorithms, which is a time-consuming and computationally expensive process. Especially after APSU, the traditional iterative methods will not be able to match the experimental data acquisition speed. We employ deep learning (DL) approach to replace the iterative approaches, therefore allowing hundreds of times faster recovery of the object. We developed AutoPhaseNN, a DL-based approach which learns to solve the inverse problem without labeled data. Taking 3D BCDI as a representative technique, AutoPhaseNN has been demonstrated to be one hundred times faster than traditional iterative phase retrieval methods while providing comparable image quality. The current network is trained with 64 x 64 x 64 data size, to achieve higher resolution imaging, we will need to scale the network to input and train/infer 3D arrays of size 256 x 256 x 256 (today) and of size 2560x2560x2560 (APSU). However, the scalability of the network is restricted due to the memory-intensive training process. To perform the training for a 256 x 256 x 256 data size, the required memory exceeds the capacity of the current machine. In this project, we explore using Sambanova system to train the network for the direct data inversion for CDI.

36 MATERIALS SCIENCE↗
NASA NTRS1994

A high resolution atlas of the galactic plane at 12 microns and 25 microns

High resolution images of the 12 micron and 25 micron IRAS survey data from each HCON crossing the Galactic Plane are being created for those regions that the original IRAS processing labeled as confused. This encompasses the area within 100 deg longitude of the Galactic Center and within 3 deg to 10 deg of the Plane. The procedures used to create the images preserve the spatial resolution inherent in the IRAS instrument. The images are separated into diffuse and point source components and candidate sources are extracted from the point source image after non-linear spatial sharpening. Fluxes are estimated by convolving the candidate sources with the point response function and cross-correlating with the original point source image. A source is considered real if it is seen on at least two HCON's with a rather generous flux match but a stringent position criterion. A number of fields spanning a range of source densities from low to high have been examined. Initial analysis indicates that the imaging and extraction works quite well up to a source density of about 100 sources per square degree or down to roughly 0.8 Janskys.

Price, Stephan D.↗
NASA NTRS2019

Human Performance Contributions to Safety in Commercial Aviation

Every day in aviation, pilots, air traffic controllers, and other front-line personnel perform countless correct judgments and actions in a variety of operational environments. These judgments and actions are often the difference between an accident and a non-event. Ironically, data on these behaviors are rarely collected or analyzed. Data-driven decisions about safety management and design of safety-critical systems are limited by the available data, which influence how decision makers characterize problems and identify solutions. Large volumes of data are collected on the failures and errors that result in infrequent incidents and accidents, but in the absence of data on behaviors that result in routine successful outcomes, safety management and system design decisions are based on a small sample of nonrepresentative safety data. This assessment aimed to find and document “safety successes” made possible by human operators. With many Aeronautics Research Mission Directorate (ARMD) Programs and Projects focusing on increased automation and autonomy and decreased human involvement, failure to fully consider the human contributions to successful system performance in civil aviation represents a significant risk — a risk that has not been recognized to date. Without understanding how humans contribute to safety, any estimate of predicted safety of autonomous capabilities is incomplete and inherently suspect. Furthermore, understanding the ways in which humans contribute to safety can promote strategic interactions among safety technologies, functions, procedures and the people using them. Without this understanding, the full benefits of an integrated, optimized human/technology or autonomous system will not be realized. Historically, safety has been consistently defined in terms of the occurrence of accidents or recognized risks (i.e., in terms of things that go wrong). These adverse outcomes are explained by identifying their causes, and safety is restored by eliminating or mitigating these causes. An alternative to this approach is to focus on what goes right and identify how to replicate that process. Focusing on the rare cases of failures attributed to “human error” provides little information about why human performance routinely prevents adverse events. Hollnagel has proposed that things go right because people continuously adjust their work to match their operating conditions. These adjustments become increasingly important as systems continue to grow in complexity. Thus, the definition of safety should reflect not only “avoiding things that go wrong” but “ensuring that things go right.” The basis for safety management requires developing an understanding of everyday activities. However, few mechanisms to monitor everyday work exist in the aviation domain, which limits opportunities to learn how designs function in reality. This concept of safety thinking and safety management is reflected in the emerging field of resilience engineering. According to Hollnagel, a system is resilient if it can sustain required operations under expected and unexpected conditions by adjusting its functioning prior to, during, or following changes, disturbances, and opportunities. To explore “positive” behaviors that contribute to resilient performance in commercial aviation, the assessment team examined a range of existing sources of data about pilot and air traffic control (ATC) tower controller performance, including subjective interviews with domain experts and objective aircraft flight data records. These data were used to identify strategies that support resilient performance, methods for exploring and refining those strategies in existing data, and proposed methods for capturing and analyzing new data.

Null, Cynthia H.↗
DOE OSTI2018

Monojet signatures from heavy colored particles: future collider sensitivities and theoretical uncertainties

In models with colored particle Q that can decay into a dark matter candidate X, the relevant collider process pp→$Q\bar{Q}$→$X\bar{X}$+ jets gives rise to events with significant transverse momentum imbalance. When the masses of Q and X are very close, the relevant signature becomes monojet-like, and Large Hadron Collider (LHC) search limits become much less constraining. In this paper, we study the current and anticipated experimental sensitivity to such particles at the High-Luminosity LHC at s√=14 TeV with L=3 ab -1 of data and the proposed High-Energy LHC at s√=27 TeV with L=15 ab -1 of data. We estimate the reach for various Lorentz and QCD color representations of Q. Identifying the nature of Q is very important to understanding the physics behind the monojet signature. Therefore, we also study the dependence of the observables built from the pp→$Q\bar{Q}$ + j process on Q itself. Here, using the state-of-the-art Monte Carlo suites MadGraph5_aMC@NLO+Pythia8 and Sherpa, we find that when these observables are calculated at NLO in QCD with parton shower matching and multijet merging, the residual theoretical uncertainties are comparable to differences observed when varying the quantum numbers of Q itself. We find, however, that the precision achievable with NNLO calculations, where available, can resolve this dilemma.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1982

Design, production, and testing of field effect transistors

Cryogenic MOSFETS (CRYOFETS), specifically designed for low temperature preamplifier application with infrared extrinsic detectors were produced and comparatively tested with p-channel MOSFETs under matched conditions. The CRYOFETs exhibit lower voltage thresholds, high source-follower gains at lower bias voltage, and lower dc offset source voltage. The noise of the CRYOFET is found to be 2 to 4 times greater than the MOSFET with a correspondingly lower figure of merit (which is established for source-follower amplifiers). The device power dissipation at a gain of 0.98 is some two orders of magnitude lower than for the MOSFET. Further, CRYOFETs are free of low temperature I vs V character hysteresis and balky conduction turn-on effects and operate effectively in the 2.4 to 20 K range. These devices have promise for use on long term duration sensor missions and for on-focal-plane signal processing at low temperatures.

Sclar, N.↗
DOE OSTI2016

SU-F-T-658: Out-Of-Field Dose Comparison for TrueBeam Low Energy Beams for Extended Distances: Measurement Vs Monte Carlo Simulation

Purpose: Patient dose far from the treatment field is comprised of scatter from within the patient, and treatment head leakage. We quantify the treatment head leakage for TrueBeam linear accelerator for 6X and 6X-FFF beams by comparing measurements to Monte Carlo simulations for a variety of jaw sizes and collimator rotations. This work is conceptually similar to that of Kry et al. (Medical Physics 2006; 33: 4405), who considered a Clinac linear accelerator. Methods: Measurements were made using an EXRADIN A101 ion chamber positioned in the patient plane, at distances up to 100 cm from isocenter. Simulations were done using VirtuaLinac, the GEANT4-based Monte Carlo model of the TrueBeam treatment head, and an in-house (U. Virginia) GEANT4-based code. In-house code modelled an ion chamber with build-up, based on a CT scan of the chamber. VirtuaLinac included a detailed model of the treatment head shielding, and was run on the Amazon Web Services cloud to generate spherical phase space files surrounding the treatment head. These phase space files were imported into the in-house code. Results: Initial comparisons between measurements and simulation showed an excess of dose in the in-plane direction, away from the gantry, in the simulations. This was traced to an incomplete model of the shielding—specifically, the component holding the primary collimator was smaller in the model than in the TrueBeam. Modifications were made to VirtuaLinac to more closely match the engineering drawings. In the in-plane direction, the lowest out of field dose was away from gantry (negative abscissa values) at around 60 cm from isocenter, for fields smaller than 10×10 cm2. Out of field dose decreased with decreasing jaw size. Flattening-filter free beam produced out-of-field doses as low as 65% of those with flattened beam. Conclusion: Doses determined from simulation and measurement were in close agreement. Funding support from the Jefferson Trust Foundation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

PySIDT: Subgraph Isomorphic Decision Trees for Molecular Property Prediction

Accurate molecular property prediction is important across all fields of chemistry. Deep neural networks (DNNs) have become increasingly popular due to their ability to train automatically, avoiding the incredibly tedious process of constructing and extending traditional property estimation schemes. However, DNNs require large amounts of training data, are challenging to interpret, require large amounts of memory to load even during inference, and have severe difficulties incorporating qualitative chemical knowledge, which are often desired for molecular property prediction tasks. Here, in this study, we present PySIDT (https://github.com/zadorlab/PySIDT), a software for training and running inference on Subgraph Isomorphic Decision Trees (SIDTs). SIDTs are graph-based decision trees made of nodes associated with molecular substructures. Inference is done by descending target molecular structures down the decision tree to nodes with matching subgraph isomorphic substructures and making predictions based on the final (most specific) nodes matched. SIDTs scale down well to dataset sizes much smaller than is feasible for DNNs. As trees of molecular substructures, SIDTs are inherently readable and easy to visualize, making them easy to analyze. They are also straightforward to extend and retrain, facilitate uncertainty estimation, and enable easy integration of expert knowledge. We demonstrate the SIDT approach discussing its application to a diverse range of molecular prediction tasks: rate coefficient estimation, diffusion coefficient estimation, thermochemistry estimation, transition state bond stretch prediction, p K a prediction, stability of molecular structures, stability of surface structures, and prediction of surface lateral interaction energetics. Additionally, we demonstrate the power of the SIDT algorithms in two direct learning curve vanilla comparisons with the popular DNN-based software Chemprop and the popular gradient boosted trees-based software XGBoost on enthalpy of formation and rate coefficient prediction tasks. In particular, in the enthalpy of formation case, vanilla PySIDT is able to outperform vanilla Chemprop and XGBoost across the full range of training/validation set sizes out to 11,560 data points.

Johnson, Matthew Sean [Sandia National Laboratorie↗
DOE OSTI2017

Final report of a scalable, automated, semipermanent seismic array (SASSA) method for detecting CO 2 extent during geologic CO 2 injection

The scalable, automated, semipermanent seismic array (SASSA) project led and managed by the Energy & Environmental Research Center (EERC) was designed as a 3-year proof-of-concept study to evaluate and demonstrate an innovative application of the seismic method. The concept was to use a sparse surface array of 96 nodal seismic sensors paired with a single, remotely operated active seismic source at a fixed location to monitor for CO 2 saturation changes in a subsurface reservoir by processing the data for time-lapse changes at individual, strategically chosen reservoir reflection points. The combination of autonomous equipment and modern processing algorithms was used to apply the seismic method in a manner different from the normal paradigm of collecting a spatially dense data set to produce an image. It was used instead to monitor individual, strategically chosen reservoir reflection points for detectable signal character changes that could be attributed to the passing of a CO 2 saturation front or, possibly, changes in reservoir pressure. Data collection occurred over the course of 1 year at an oil field undergoing CO 2 injection for enhanced oil recovery (EOR) and focused on four overlapping “five-spot” EOR injector–producer patterns. Selection, procurement, configuration, installation, and testing of project equipment and collection of five baseline data sets were completed in advance of CO 2 injection within the study area. Weekly remote data collection produced 41 incremental time-lapse records for each of the 96 nodes. Validation was provided by two methods: 1) a conventional 2-D seismic line acquired through the center of the study area before injection started and again after the project ended and processed in a time-lapse manner and 2) by CO 2 saturation maps created from reservoir simulations based on injection and production history matching. Interpreted results were encouraging but mixed, with indications of changes likely due to the presence of CO 2 on some node reflection points where and when effects would be expected and noneffects where no CO 2 was expected, while results at some locations where simulation outputs suggested CO 2 should be present were ambiguous. Acquisition noise impacted interpretation of data at several locations. Many lessons learned were generated by the study to inform and improve results on a follow-up study. The ultimate aim of the project was to evaluate whether deployment of a SASSA technology can provide a useful and cost-effective monitoring solution for future CO 2 injection projects. The answer appears to be affirmative, with the expectation that lessons learned applied to future iterations, together with technology advances, will likely result in significant improvements.

58 GEOSCIENCES↗
NASA NTRS1981

Automatic cloud tracking applied to GOES and Meteosat observations

An improved automatic processing method for the tracking of cloud motions as revealed by satellite imagery is presented and applications of the method to GOES observations of Hurricane Eloise and Meteosat water vapor and infrared data are presented. The method is shown to involve steps of picture smoothing, target selection and the calculation of cloud motion vectors by the matching of a group at a given time with its best likeness at a later time, or by a cross-correlation computation. Cloud motion computations can be made in as many as four separate layers simultaneously. For data of 4 and 8 km resolution in the eye of Hurricane Eloise, the automatic system is found to provide results comparable in accuracy and coverage to those obtained by NASA analysts using the Atmospheric and Oceanographic Information Processing System, with results obtained by the pattern recognition and cross correlation computations differing by only fractions of a pixel. For Meteosat water vapor data from the tropics and midlatitudes, the automatic motion computations are found to be reliable only in areas where the water vapor fields contained small-scale structure, although excellent results are obtained using Meteosat IR data in the same regions. The automatic method thus appears to be competitive in accuracy and coverage with motion determination by human analysts.

Endlich, R. M.↗