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All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

VERITAS Observations of Day-scale Flaring of M 87 in 2010 April

VERITAS has been monitoring the very-high-energy (VHE; > 100 GeV) gamma-ray activity of the radio galaxy M 87 since 2007. During 2008, flaring activity on a timescale of a few days was observed with a peak flux of (0.70 +/- 0.16) x 10(exp -11)/sq cm/s at energies above 350 GeV. In 2010 April, VERITAS detected a flare from M 87 with peak flux of (2.71 +/- 0.68) x 10(exp -11)/sq cm/s for E > 350 GeV. The source was observed for six consecutive nights during the flare, resulting in a total of21 hr of good-quality data. The most rapid flux variation occurred on the trailing edge of the flare with an exponential flux decay time of 0,90 +0.22/-0.15 days, The shortest detected exponential rise time is three times as long, at 2.87 +1.65/-0.99 days. The quality of the data sample is such that spectral analysis can he performed for three periods: rising flux, peak flux, and falling flux. The spectra obtained are consistent with power-law forms. The spectral index at the peak of the flare is equal to 2.19 +/- 0.07, There is some indication that the spectrum is softer in the falling phase of the flare than the peak phase, with a confidence level corresponding to 3.6 standard deviations. We discuss the implications of these results for the acceleration and cooling rates of VHE electrons in M 87 and the constraints they provide on the physical size of the emitting region.

Perkins, J. S>↗
NASA NTRS2012

QuakeSim 2.0

QuakeSim 2.0 improves understanding of earthquake processes by providing modeling tools and integrating model applications and various heterogeneous data sources within a Web services environment. QuakeSim is a multisource, synergistic, data-intensive environment for modeling the behavior of earthquake faults individually, and as part of complex interacting systems. Remotely sensed geodetic data products may be explored, compared with faults and landscape features, mined by pattern analysis applications, and integrated with models and pattern analysis applications in a rich Web-based and visualization environment. Integration of heterogeneous data products with pattern informatics tools enables efficient development of models. Federated database components and visualization tools allow rapid exploration of large datasets, while pattern informatics enables identification of subtle, but important, features in large data sets. QuakeSim is valuable for earthquake investigations and modeling in its current state, and also serves as a prototype and nucleus for broader systems under development. The framework provides access to physics-based simulation tools that model the earthquake cycle and related crustal deformation. Spaceborne GPS and Inter ferometric Synthetic Aperture (InSAR) data provide information on near-term crustal deformation, while paleoseismic geologic data provide longerterm information on earthquake fault processes. These data sources are integrated into QuakeSim's QuakeTables database system, and are accessible by users or various model applications. UAVSAR repeat pass interferometry data products are added to the QuakeTables database, and are available through a browseable map interface or Representational State Transfer (REST) interfaces. Model applications can retrieve data from Quake Tables, or from third-party GPS velocity data services; alternatively, users can manually input parameters into the models. Pattern analysis of GPS and seismicity data has proved useful for mid-term forecasting of earthquakes, and for detecting subtle changes in crustal deformation. The GPS time series analysis has also proved useful as a data-quality tool, enabling the discovery of station anomalies and data processing and distribution errors. Improved visualization tools enable more efficient data exploration and understanding. Tools provide flexibility to science users for exploring data in new ways through download links, but also facilitate standard, intuitive, and routine uses for science users and end users such as emergency responders.

Donnellan, Andrea↗
NASA NTRS2015

Dissemination of Earth Remote Sensing Data for Use in the NOAA/NWS Damage Assessment Toolkit

The National Weather Service has developed the Damage Assessment Toolkit (DAT), an application for smartphones and tablets that allows for the collection, geolocation, and aggregation of various damage indicators that are collected during storm surveys. The DAT supports the often labor‐intensive process where meteorologists venture into the storm‐affected area, allowing them to acquire geotagged photos of the observed damage while also assigning estimated EF‐scale categories based upon their observations. Once the data are collected, the DAT infrastructure aggregates the observations into a server that allows other meteorologists to perform quality control and other analysis steps before completing their survey and making the resulting data available to the public. In addition to in‐person observations, Earth remote sensing from operational, polar-orbiting satellites can support the damage assessment process by identifying portions of damage tracks that may be missed due to road limitations, access to private property, or time constraints. Products resulting from change detection techniques can identify damage to vegetation and the land surface, aiding in the survey process. In addition, higher resolution commercial imagery can corroborate ground‐based surveys by examining higher‐resolution commercial imagery. As part of an ongoing collaboration, NASA and NOAA are working to integrate near real‐time Earth remote sensing observations into the NOAA/NWS Damage Assessment Toolkit. This presentation will highlight recent developments in a streamlined approach for disseminating Earth remote sensing data via web mapping services and a new menu interface that has been integrated within the DAT. A review of current and future products will be provided, including products derived from MODIS and VIIRS for preliminary track identification, along with conduits for higher‐resolution Landsat, ASTER, and commercial imagery as they become available. In addition to tornado damage assessments, the team is also investigating the use of near real‐time imagery for identifying hail damage to vegetation, which also results in large swaths of damage, particularly in the central United States during the peak growing season months of June, July, and August. This presentation will present an overview of recent activities, challenges and successes, best practices, and opportunities for future work and collaboration

Molthan, Andrew↗
DOE OSTI2022

LDRD 226360 Final Project Report: Simulated X-ray Diffraction and Machine Learning for Optimizing Dynamic Experiment Analysis

This report is the final documentation for the one-year LDRD project 226360: Simulated X-ray Diffraction and Machine Learning for Optimizing Dynamic Experiment Analysis. As Sandia has successfully developed in-house X-ray diffraction tools for study of atomic structure in experiments, it has become increasingly important to develop computational analysis methods to support these experiments. When dynamically compressed lattices and orientations are not known a priori, the identification requires a cumbersome and sometimes intractable search of possible final states. These final states can include phase transition, deformation and mixed/evolving states. Our work consists of three parts: (1) development of an XRD simulation tool and use of traditional data science methods to match XRD patterns to experiments; (2) development of ML-based models capable of decomposing and identifying the lattice and orientation components of multicomponent experimental diffraction patterns; and (3) conducting experiments which showcase these new analysis tools in the study of phase transition mechanisms. Our target material has been cadmium sulfide, which exhibits complex orientation-dependent phase transformation mechanisms. In our current one-year LDRD, we have begun the analysis of high-quality c-axis CdS diffraction data from DCS and Thor experiments, which had until recently eluded orientation identification.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1992

Knowledge based imaging for terrain analysis

A planetary rover will have various vision based requirements for navigation, terrain characterization, and geological sample analysis. In this paper we describe a knowledge-based controller and sensor development system for terrain analysis. The sensor system consists of a laser ranger and a CCD camera. The controller, under the input of high-level commands, performs such functions as multisensor data gathering, data quality monitoring, and automatic extraction of sample images meeting various criteria. In addition to large scale terrain analysis, the system's ability to extract useful geological information from rock samples is illustrated. Image and data compression strategies are also discussed in light of the requirements of earth bound investigators.

Holben, Rick↗
NASA NTRS2010

Applications of OMI Tropospheric NO(Sub 2) Data: Air Quality Trends in the US and Lightning NO(x) Source Strength

This talk will be presented in two parts: 1) an analysis of tropospheric column NO2 trends in the eastern half of the United States over the period 2005 to 2009 and 2) estimation of lightning NO(x) production rates based on OMI observations and lightning flash rate data. The air quality trends in the eastern US will be determined for specific subregions using tropospheric column NO2 data from OMI for 2005 through 2008 and from GOME-2 for 2007 through 2009. This period is characterized by significant NO(x) emission reductions at power plants within most of this region. The air quality trends will be compared with those estimated from continuous emission monitoring data from the power plants compiled by the US Environmental Protection Agency. OMI NO2 data have also been used to estimate lightning NOx production per flash in selected storms near Costa Rica and Panama during the 2007 NASA TC4 field campaign and over the continental US, Gulf of Mexico, and western Atlantic during the summers of 2005 and 2006. The lightning signal is extracted from the OMI data through a custom retrieval in which an NO2 profile representative of convective outflow is used in the airmass factor calculation and the background NO2 column is subtracted from the tropospheric column. When combined with NO(x)/NO2 ratios from the NASA GMT model and observed flash rates, the resulting estimates of NO(x) production per flash are comparable to those estimated obtained from analyses of aircraft data and cloud-resolving modeling.

Pickering, Kenneth↗
NASA NTRS1999

Laboratory Astrophysics Under the Ultraviolet, Visible, and Gravitational Astrophysics Research Program

Space-borne facilities, such as the Hubble Space Telescope, the recent ORFEUS-SPAS II Shuttle mission, and the soon-to-be launched Far Ultraviolet Spectroscopic Explorer, are providing data at ultraviolet wavelengths of unprecedented quality for spectroscopic studies of many astronomical environments. The first step in the analysis of these data involves the derivation of abundances. Obtaining accurate abundances is possible only when the correspondence between line strength and abundance is well known. The conversion of line strength to abundance relies on knowledge of transition probabilities and oscillator strengths, often obtained from mean lives branching fractions. For many ultraviolet transitions, the necessary atomic and molecular data are either relatively imprecise or not available. Our program addresses this need for accurate oscillator strengths; our focus is on transitions that probe the nature and composition of the interstellar medium.

Federman, Steven R.↗
NASA NTRS2014

Highlights from a Decade of OMI-TOMS Total Ozone Observations on EOS Aura

Total ozone measurements from OMI have been instrumental in meeting Aura science objectives. In the last decade, OMI has extended the length of the TOMS total ozone record to over 35 years to monitor stratospheric ozone recovery. OMI-TOMS total ozone measurements have also been combined synergistically with measurements from other Aura instruments and MLS in particular, which provides vertically resolved information that complements the total O3 mapping capability of OMI. With this combined approach, the EOS Aura platform has produced more accurate and detailed measurements of tropospheric ozone. This has led in turn to greater understanding of the sources and transport of tropospheric ozone as well as its radiative forcing effect. The combined use of OMI and MLS data was also vital to the analysis of the severe Arctic ozone depletion event of 2011. The quality of OMI-TOMS total O3 data used in these studies is the result of several factors: a mature and well-validated algorithm, the striking stability of the OMI instrument, and OMI's hyperspectral capabilities used to derive cloud pressures. The latter has changed how we think about the effects of clouds on total ozone retrievals. We will discuss the evolution of the operational V8.5 algorithm and provide an overview and motivation for V9. After reviewing results and developments of the past decade, we finally highlight how ozone observations from EOS Aura are playing an important role in new ozone mapping missions.

Ozone↗
NASA NTRS1993

Analysis of direct numerical simulation data of a Mach 4.5 transitional boundary-layer flow

This paper describes the creation, by temporal direct numerical simulation and the analysis based on the Reynolds stress transport equations, of a high-quality data set that represents the laminar-turbulent transition of a high-speed boundary-layer flow. Following Pruett and Zang (1992), and with the help of algorithmic refinements, the evolution of an axial, Mach 4.5 boundary-layer flow along a hollow cylinder is simulated numerically. Favre-averaged Reynolds stress transport equations are derived in generalized curvilinear coordinates and are then specialized to the cylindrical geometry at hand. Reynolds stresses and various turbulence quantities, such as turbulent kinetic energy and turbulent Mach number, are calculated from the numerical data at various stages of the transition process. The kinetic energy 'budgets' are constructed from the transport equations. Various contributing terms for the evolution of kinetic energy, like the rates of production and dissipation, transport, and diffusion, are presented. The compressible dissipation rate is small in comparison with the solenoidal dissipation rate for all times. The pressure-dilatation term is of the same order of magnitude as the compressible dissipation rate.

Dinavahi, Surya P. G.↗
NASA NTRS1990

Estimating short-period dynamics using an extended Kalman filter

An extended Kalman filter (EKF) is used to estimate the parameters of a low-order model from aircraft transient response data. The low-order model is a state space model derived from the short-period approximation of the longitudinal aircraft dynamics. The model corresponds to the pitch rate to stick force transfer function currently used in flying qualities analysis. Because of the model chosen, handling qualities information is also obtained. The parameters are estimated from flight data as well as from a six-degree-of-freedom, nonlinear simulation of the aircraft. These two estimates are then compared and the discrepancies noted. The low-order model is able to satisfactorily match both flight data and simulation data from a high-order computer simulation. The parameters obtained from the EKF analysis of flight data are compared to those obtained using frequency response analysis of the flight data. Time delays and damping ratios are compared and are in agreement. This technique demonstrates the potential to determine, in near real time, the extent of differences between computer models and the actual aircraft. Precise knowledge of these differences can help to determine the flying qualities of a test aircraft and lead to more efficient envelope expansion.

Bauer, Jeffrey E.↗
DOE OSTI2025

Pavement condition and climatic data in southeast Texas: A dataset for evaluating flood impacts on pavement performance

Effective pavement maintenance is essential for economic stability, optimal network performance, and roadway safety. Achieving this requires thorough evaluation of pavement conditions, including structural integrity, surface roughness, and distress characteristics. Pavement performance indicators play a critical role in influencing vehicle safety and ride quality. Recent advances have emphasized the use of data-driven modeling to anticipate pavement behavior, with the goal of optimizing resource allocation and refining Maintenance and Rehabilitation (M&R) strategies through accurate condition assessment. A foundational requirement for these modeling efforts is the availability of standardized, high-quality datasets that can support robust and reproducible infrastructure analysis. This data article presents a comprehensive dataset assembled to facilitate pavement performance prediction, with a geographic focus on Southeast Texas, particularly the flood-vulnerable area of Beaumont. The dataset encompasses pavement and traffic attributes, meteorological records, flood simulation outputs, ground deformation measurements, and topographic indices, enabling detailed examination of both load-associated and non-load-associated degradation mechanisms. Data preprocessing was performed using ArcGIS Pro, Microsoft Excel, and Python to ensure consistency and usability in data-driven modeling applications, including machine learning workflows. Key contributions of this dataset include its utility in analyzing the climatic and environmental factors affecting pavement conditions, identifying critical predictive features, and enabling in-depth correlation analysis across diverse variables. By filling existing gaps in input variable selection resources, this dataset supports the development of predictive tools for estimating future maintenance demand and enhancing the resilience of pavement networks in flood-impacted areas. The resource highlights the importance of standardized datasets for advancing pavement management practices and provides a robust foundation for ongoing infrastructure performance modeling.

42 ENGINEERING↗
NASA NTRS1979

Preliminary results of SAR soil moisture experiment, November 1975

The experiment was performed using the Environmental Research Institute of Michigan's (ERIM) dual-frequency and dual-polarization side-looking SAR system on board a C-46 aircraft. For each frequency, horizontally polarized pulses were transmitted and both horizontally and vertically polarized return signals were recorded on the signal film simultaneously. The test sites were located in St. Charles, Missouri; Centralia, Missouri; and Lafayette, Indiana. Each test site was a 4.83 km by 8.05 km (3 mile by 5 mile) rectangular strip of terrain. Concurrent with SAR overflight, ground soil samples of 0-to-2.5 cm and 0-to-15 cm layers were collected for soil moisture estimation. The surface features were also noted. Hard-copy image films and the digital data produced via optical processing of the signal films are analyzed in this report to study the relationship of radar backscatter to the moisture content and the surface roughness. Many difficulties associated with processing and analysis of the SAR imagery are noted. In particular, major uncertainty in the quantitative analysis appeared due to the difficulty of quality reproduction of digital data from the signal films.

Choudhury, B. J.↗
NASA NTRS2020

A Global End-Member Approach to Derive aCDOM(440) from Near-Surface Optical Measurements

This study establishes an optical inversion scheme for deriving the absorption coefficient of colored (or chromophoric, depending on the literature) dissolved organic material (CDOM) at the 440 nm wavelength, which can be applied to global water masses with near-equal efficacy. The approach uses a ratio of diffuse attenuation coefficient spectral end members, i.e., a short and long wavelength pair. The global perspective is established by sampling "extremely" clear water plus a generalized extent in turbidity and optical properties that each span three decades of dynamic range. A unique data set was collected in oceanic, coastal, and inland waters (as shallow as 0.6 m) from the North Pacific Ocean, the Arctic Ocean, Hawaii, Japan, Puerto Rico, and the east and west coasts of the United States. The data were partitioned using subjective categorizations to define a validation quality subset of conservative water masses, i.e., the inflow and outflow of properties constrain the range in the gradient of a constituent, plus 15 subcategories of water masses that were not evolving conservatively. The dependence on subcategories was confirmed with an objective methodology based on cluster analysis techniques. The latter defined five distinct classes with validation quality data present in all classes, but which also decreased in percent composition as a function of increasing class number and optical complexity. Four different algorithms based on different validation quality end members were validated with accuracies of 1.–6.2 %, wherein pairs with the largest spectral span were most accurate. Although algorithm accuracy decreased with the inclusion of more subcategories containing non-conservative water masses, changes to the algorithm fit were small when a preponderance of subcategories were included. The high accuracy for all end-member algorithms was the result of data acquisition and data processing improvements, e.g., increased vertical sampling resolution to less than 1mm and a boundary constraint to mitigate wave focusing effects, respectively. An independent evaluation with a historical database confirmed the consistency of the algorithmic approach and its application to quality assurance, e.g., to flag data outside expected ranges, identify suspect spectra, and objectively determine the in-water extrapolation interval by converging agreement for all applicable end-member algorithms. The legacy data exhibit degraded performance (as 44 % uncertainty) due to a lack of high-quality near-surface observations, especially for clear waters wherein wave-focusing effects are problematic. The novel optical approach allows the in situ estimation of an in-water constituent in keeping with the accuracy obtained in the laboratory.

Stanford B Hooker↗
NASA NTRS2006

The Atlanta Urban Heat Island Mitigation and Air Quality Modeling Project: How High-Resoution Remote Sensing Data Can Improve Air Quality Models

The Atlanta Urban Heat Island and Air Quality Project had its genesis in Project ATLANTA (ATlanta Land use Analysis: Temperature and Air quality) that began in 1996. Project ATLANTA examined how high-spatial resolution thermal remote sensing data could be used to derive better measurements of the Urban Heat Island effect over Atlanta. We have explored how these thermal remote sensing, as well as other imaged datasets, can be used to better characterize the urban landscape for improved air quality modeling over the Atlanta area. For the air quality modeling project, the National Land Cover Dataset and the local scale Landpro99 dataset at 30m spatial resolutions have been used to derive land use/land cover characteristics for input into the MM5 mesoscale meteorological model that is one of the foundations for the Community Multiscale Air Quality (CMAQ) model to assess how these data can improve output from CMAQ. Additionally, land use changes to 2030 have been predicted using a Spatial Growth Model (SGM). SGM simulates growth around a region using population, employment and travel demand forecasts. Air quality modeling simulations were conducted using both current and future land cover. Meteorological modeling simulations indicate a 0.5 C increase in daily maximum air temperatures by 2030. Air quality modeling simulations show substantial differences in relative contributions of individual atmospheric pollutant constituents as a result of land cover change. Enhanced boundary layer mixing over the city tends to offset the increase in ozone concentration expected due to higher surface temperatures as a result of urbanization.

Quattrochi, Dale A.↗
DOE OSTI2023

Locating Operational Events of the Cooling Tower of a Nuclear Reactor with a Very Local Seismic Network

Geolocation of emergent seismic signals is challenging at close distances. Here, we used three-component data from a seismic network and a targeted experiment at a research nuclear reactor to locate seismic sources. Utilizing known events collected during the targeted experiment, we were able to infer source locations with seismic amplitudes and polarization characteristics of the data. Although the resolution of the source location is not perfect, the seismic amplitudes and polarization analysis offer useful constraints. For the known events, the source region inferred with our analysis includes the true source locations. Synthetic tests indicate the resolution is largely due to limited data coverage and measurement uncertainties because the synthetic tests show similar results compared with the field data. We identified the source of the unknown event through spectrum cross correlation between the signals from the known events and an unknown event. Our findings were confirmed by operational staff at the facility. When the propagation medium properties (i.e., seismic velocity and quality factor for attenuation) are known, our analysis can be applied to continuous data from a seismic array to infer both source amplitude and location. If the medium properties are not known, a targeted experiment can be conducted to estimate them.

58 GEOSCIENCES↗
DOE OSTI2023

ProvSec: Open Cybersecurity System Provenance Analysis Benchmark Dataset with Labels

System provenance forensic analysis has been studied by a large body of research work. This area needs fine granularity data such as system calls along with event fields to track the dependencies of events. While prior work on security datasets has been proposed, we found a useful dataset of realistic attacks and details that are needed for high-quality provenance tracking is lacking. We created a new dataset of eleven vulnerable cases for system forensic analysis. It includes the full details of system calls including syscall parameters. Realistic attack scenarios with real software vulnerabilities and exploits are used. For each case, we created two sets of benign and adversary scenarios which are manually labeled for supervised machine-learning analysis. In addition, we present an algorithm to improve the data quality in the system provenance forensic analysis. We demonstrate the details of the dataset events and dependency analysis of our dataset cases.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1987

Assimilation of scalar versus horizontal gradient information from the VAS into a mesoscale model

Comparisons are made between analyses and forecasts which incorporate VAS geopotential data as either scalar or horizontal gradient information for a case study on the AVE/VAS day of Mar. 6, 1982. On this day, incorporating the VAS information in analysis as a variational constraint on horizontal geopotential gradients significantly mitigated the effects of large data biases which made VAS assimilation by standard scalar methods very difficult. A subsequent forecast made from the gradient assimilation was superior to one made from the standard analysis and of comparable quality in geopotentials to a control forecast from synoptic data. Most impact was noted in the forecasts of vertical motion and precipitation in the gradient vs this control simulation.

Diak, George↗
NASA NTRS1990

Getting started on metrics - Jet Propulsion Laboratory productivity and quality

A review is presented to describe the effort and difficulties of reconstructing fifteen years of JPL software history. In 1987 the collection and analysis of project data were started with the objective of creating laboratory-wide measures of quality and productivity for software development. As a result of this two-year Software Product Assurance metrics study, a rough measurement foundation for software productivity and software quality, and an order-of-magnitude quantitative baseline for software systems and subsystems are now available.

Bush, M. W.↗