SEARCH · Search NASA

Results for “Observation Data”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,009 records · Page 56

All sources NASA NTRS DOE OSTI

NASA NTRS1986

FEDS - An experiment with a microprocessor-based orbit determination system using TDRS data

An experiment in microprocessor-based onboard orbit determination has been conducted at NASA's Goddard Space Flight Center. The experiment collected forward-link observation data in real time from a prototype transponder and performed orbit estimation on a typical low-earth scientific satellite. This paper discusses the hardware and organizational configurations of the experiment, the structure of the onboard software, the mathematical models, and the experiment results.

Shank, D.↗

DOE OSTI2025

In-orbit performance of the soft X-ray imaging telescope Xtend aboard XRISM

Here, we present a summary of the in-orbit performance of the soft X-ray imaging telescope Xtend onboard the X-Ray Imaging and Spectroscopy Mission (XRISM), based on in-flight observation data, including first-light celestial objects, calibration sources, and results from the cross-calibration campaign with other currently operating X-ray observatories. XRISM/Xtend has a large field of view of ${38{^{\prime }_{.}}5}$ $\times$ ${38{^{\prime }_{.}}5}$, covering an energy range of 0.4–13 keV, as demonstrated by the first-light observation of the galaxy cluster Abell 2319. It also features an energy resolution of 170–180 eV at 6 keV, which meets the mission requirement and enables us to resolve He-like and H-like Fe K$\alpha$ lines. Throughout the observation during the performance verification phase, we confirm that two issues identified in the Soft X-ray Imager (SXI) onboard the previous Hitomi mission—light leakage and crosstalk events—are addressed and suppressed in the case of Xtend. A joint cross-calibration observation of the bright quasar 3C 273 results in an effective area measured to be $\sim$420 cm$^{2}$ at1.5 keV and $\sim$310 cm$^{2}$ at 6.0 keV, which matches values obtained in ground tests. We also continuously monitor the health of Xtend by analyzing overclocking data, calibration source spectra, and day-Earth observations; the readout noise is stable and low, and contamination is negligible even one year after launch. A low background level compared with other major X-ray instruments onboard satellites, combined with the largest grasp ($\Omega _{\rm eff}\sim 60$ cm$^2$ deg$^2$) of Xtend, will not only support Resolve analysis, but also enable significant scientific results on its own. This includes near-future follow-up observations and transient searches in the context of time-domain and multi-messenger astrophysics.

instrumentation: detectors: Xtend↗

NASA NTRS1984

The v = 0 - 0 spectrum of H2

Ground-state rotational parameters for molecular hydrogen are evaluated using a combination of laboratory and observational data. High-accuracy v = 0 - 0 S(0)-S(5) frequencies from infrared laboratory measurements are analyzed simultaneously with available observed frequencies for the S(8), S(9), S(12), S(13), S(14), and S(15) Orion emission lines. The laboratory and Orion measurements are consistent with each other within their measurement errors. The combined data set yields a determination of five v = 0 rotational parameters and an improvement in the high-J calculated line positions. The analysis produces the parameters (in per cm): B(0) = 59.334627(30), D(0) = 0.0456912(30), H(0) = 4.8974(90) x 10 to the -5th, L(0) = -6.320(110) x 10 to the -8th, M(0) = 7.19(30) x 10 to the -11th, where a correction is made for the estimated contribution of sixth and higher orders.

Jennings, D. E.↗

NASA NTRS2016

A Global Capacity Building Vision for Societal Applications of Earth Observing Systems and Data: Key Questions and Recommendations

Capacity building using Earth observing (EO) systems and data (i.e., from orbital and nonorbital platforms) to enable societal applications includes the network of human, nonhuman, technical, nontechnical, hardware, and software dimensions that are necessary to successfully cross the valley [of death; see NRC (2001)] between science and research (port of departure) and societal application (port of arrival). In many parts of the world (especially where ground-based measurements are scarce or insufficient), applications of EO data still struggle for longevity or continuity for a variety of reasons, foremost among them being the lack of resilient capacity. An organization is said to have resilient capacity when it can retain and continue to build capacity in the face of unexpected shocks or stresses. Stresses can include intermittent power and limited Internet bandwidth, constant need for education on ever-increasing complexity of EO systems and data, communication challenges between the ports of departure and arrival (especially across time zones), and financial limitations and instability. Shocks may also include extreme events such as disasters and losing key staff with technical and institutional knowledge.

shocks↗

NASA NTRS1975

A determination of the sea level muon spectrum using accelerator data and some implications

The differential sea-level muon spectrum is calculated from first principle for a pure beam of cosmic-ray protons cascading in the atmosphere by using a representation of the invariant cross section that describes the observed data from 6 GeV to 1500 GeV. This spectrum is compared with the observed muon spectrum to deduce information on the interaction characteristics of nuclei-nuclei collisions.

Badhwar, G. D.↗

NASA NTRS2002

Decadal Changes in Global Ocean Annual Primary Production

The Sea-viewing Wide Field-of-View Sensor (SeaWiFS) has produced the first multi-year time series of global ocean chlorophyll observations since the demise of the Coastal Zone Color Scanner (CZCS) in 1986. Global observations from 1997-present from SeaWiFS combined with observations from 1979-1986 from the CZCS should in principle provide an opportunity to observe decadal changes in global ocean annual primary production, since chlorophyll is the primary driver for estimates of primary production. However, incompatibilities between algorithms have so far precluded quantitative analysis. We have developed and applied compatible processing methods for the CZCS, using modern advances in atmospheric correction and consistent bio-optical algorithms to advance the CZCS archive to comparable quality with SeaWiFS. We applied blending methodologies, where in situ data observations are incorporated into the CZCS and SeaWiFS data records, to provide improvement of the residuals. These re-analyzed, blended data records provide maximum compatibility and permit, for the first time, a quantitative analysis of the changes in global ocean primary production in the early-to-mid 1980's and the present, using synoptic satellite observations. An intercomparison of the global and regional primary production from these blended satellite observations is important to understand global climate change and the effects on ocean biota. Photosynthesis by chlorophyll-containing phytoplankton is responsible for biotic uptake of carbon in the oceans and potentially ultimately from the atmosphere. Global ocean annual primary decreased from the CZCS record to SeaWiFS, by nearly 6% from the early 1980s to the present. Annual primary production in the high latitudes was responsible for most of the decadal change. Conversely, primary production in the low latitudes generally increased, with the exception of the tropical Pacific. The differences and similarities of the two data records provide evidence of how the Earth's climate may be changing and how ocean biota respond. Furthermore, the results have implications for the ocean carbon cycle.

Gregg, Watson↗

DOE OSTI2025

Identifying Nuclear Data Correlated Through Predicting Bias in Integral Experiments via Applying Principal Component Analysis to Random Forest

ABSTRACT Nuclear data (ND) are the input data for neutron‐transport simulations to answer questions related to nuclear technologies. Subsets of ND, here > 20,000 data points, are validated with respect to thousands of criticality experiments that represent various applications on a small scale. The aim of validation with these experiments is to find errors in ND or methods. The key challenge here is that several hundreds of ND are used to simulate one integral value. Hence, one cannot clearly identify what ND are leading to bias in criticality measurements. In fact, a mistake in one nuclear‐data observable can be compensated with an error in another, and the predicted criticality value would still be predicted in agreement with experimental data. Random forest (RF) was previously employed to predict bias in criticality measurements using sensitivities of simulated criticality experiments to ND. The SHapley Additive exPlanations (SHAP) metric was then applied to attribute the importance of each ND experiment and observable to bias prediction. This, however, did not highlight what ND were jointly related to predicting bias. This is important as it could inform us about where compensating errors in ND could hide. We tackle this shortcoming here by first decomposing the ND sensitivities to integral‐experiment simulations into principal components. Then we use principal component projections to predict bias via the RF and SHAP. The SHAP values and principal components are employed to reconstruct detailed SHAP values for each ND observable. We demonstrate that these extended SHAP bias predictions are more robust, less noisy, and more efficient. In addition, we show that this approach accounts for covariance in ND sensitivities and automates the identification of where compensating errors could hide in ND.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

An Efficient Numerical Algorithm for Solving Data Driven Feedback Control Problems

The goal of this paper is to solve a class of stochastic optimal control problems numerically, in which the state process is governed by an Itô type stochastic differential equation with control process entering both in the drift and the diffusion, and is observed partially. The optimal control of feedback form is determined based on the available observational data. In this work, we call this type of control problems the data driven feedback control. The computational framework that we introduce to solve such type of problems aims to find the best estimate for the optimal control as a conditional expectation given the observational information. To make our method feasible in providing timely feedback to the controlled system from data, we develop an efficient stochastic optimization algorithm to implement our computational framework.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Reconciling Observed and Predicted Tropical Rainforest OH Concentrations

We present OH observations made in Amazonas, Brazil during the Green Ocean Amazon campaign (GoAmazon2014/5) from February to March of 2014. The average diurnal variation of OH peaked with a midday (10:00–15:00) average of 1.0 × 10 6 (±0.6 × 10 6 ) molecules cm -3 . This was substantially lower than previously reported in other tropical forest photochemical environments (2–5 × 10 6 molecules cm -3 ) while the simulated OH reactivity was lower. The observational data set was used to constrain a box model to examine how well current photochemical reaction mechanisms can simulate observed OH. We used one near-explicit mechanism (MCM v3.3.1) and four condensed mechanisms (i.e., RACM2, MOZART-T1, CB05, CB6r2) to simulate OH. A total of 14 days of analysis shows that all five chemical mechanisms were able to explain the measured OH within instrumental uncertainty of 40% during the campaign in the Amazonian rainforest environment. Future studies are required using more reliable NO x and VOC measurements to further investigate discrepancies in our understanding of the radical chemistry in the tropical rainforest.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Near real-time streaming analysis of big fusion data

Experiments on fusion plasmas produce high-dimensional data time series with ever-increasing magnitude and velocity, but turn-around times for analysis of this data have not kept up. For example, many data analysis tasks are often performed in a manual, ad-hoc manner some time after an experiment. In this article, we introduce the Delta framework that facilitates near real-time streaming analysis of big and fast fusion data. By streaming measurement data from fusion experiments to a high-performance compute center, Delta allows computationally expensive data analysis tasks to be performed in between plasma pulses. This article describes the modular and expandable software architecture of Delta and presents performance benchmarks of individual components as well as of an example workflow. Focusing on a streaming analysis workflow where electron cyclotron emission imaging (ECEi) data is measured at KSTAR on the National Energy Research Scientific Computing Center's (NERSC's) supercomputer we routinely observe data transfer rates of about 4 Gigabit per second. In NERSC, a demanding turbulence analysis workflow effectively utilizes multiple nodes and graphical processing units and executes them in under 5 min. We further discuss how Delta uses modern database systems and container orchestration services to provide web-based real-time data visualization. For the case of ECEi data we demonstrate how data visualizations can be augmented with outputs from machine learning models. Here, by providing session leaders and physics operators, results of higher-order data analysis using live visualizations may make more informed decisions on how to configure the machine for the next shot.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2018

nbodykit: An Open-source, Massively Parallel Toolkit for Large-scale Structure

We present nbodykit, an open-source, massively parallel Python toolkit for analyzing large-scale structure (LSS) data. Using Python bindings of the Message Passing Interface, we provide parallel implementations of many commonly used algorithms in LSS. nbodykit is both an interactive and scalable piece of scientific software, performing well in a supercomputing environment while still taking advantage of the interactive tools provided by the Python ecosystem. Existing functionality includes estimators of the power spectrum, two- and three-point correlation functions, a friends-of-friends grouping algorithm, mock catalog creation via the halo occupation distribution technique, and approximate N-body simulations via the FastPM scheme. The package also provides a set of distributed data containers, insulated from the algorithms themselves, that enables nbodykit to provide a unified treatment of both simulation and observational data sets. nbodykit can be easily deployed in a high-performance computing environment, overcoming some of the traditional difficulties of using Python on supercomputers. We provide performance benchmarks illustrating the scalability of the software. The modular, component-based approach of nbodykit allows researchers to easily build complex applications using its tools. The package is extensively documented at http://nbodykit.readthedocs.io, which also includes an interactive set of example recipes for new users to explore. As open-source software, we hope nbodykit provides a common framework for the community to use and develop in confronting the analysis challenges of future LSS surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2017

Dynamical Timescale of Pre-collapse Evolution Inferred from Chemical Distribution in the Taurus Molecular Cloud-1 (TMC-1) Filament

We present observations and analyses of the low-mass star-forming region, Taurus Molecular Cloud-1 (TMC-1). CS ( J = 2–1)/N{sub 2}H{sup +} ( J = 1–0) and C{sup 17}O ( J = 2–1)/C{sup 18}O ( J = 2–1) were observed with the Five College Radio Astronomy Observatory and the Seoul Radio Astronomy Observatory, respectively. In addition, Spitzer infrared data and 1.2 mm continuum data observed with Max-Planck Millimetre Bolometer are used. We also perform chemical modeling to investigate the relative molecular distributions of the TMC-1 filament. Based on Spitzer observations, there is no young stellar object along the TMC-1 filament, while five Class II and one Class I young stellar objects are identified outside the filament. The comparison between column densities calculated from dust continuum and C{sup 17}O 2–1 line emission shows that CO is depleted much more significantly in the ammonia peak than in the cyanopolyyne peak, while the column densities calculated from the dust continuum are similar at the two peaks. N{sub 2}H{sup +} is not depleted much in either peak. According to our chemical calculation, the differential chemical distribution in the two peaks can be explained by different timescales required to reach the same density, i.e., by different dynamical processes.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2018

AAF_UHSAS-air_CACTI

The UHSAS-air is the bench version of the UHSAS that measures particle size from 0.06 to 1.0 micro-meters. Aerosol passes through a laser beam and the resulting intensity of scattered light is directly correlated to the diameter of the particle passing through the beam. This isntrument has been modified to volumetricaly control the Sheath Flow using an Alicat flow controller. Data is reported at 1.000s and missing data is reported as -9999 Multiple data flags are present in this version. Counts?: The coincident error is deemed minimal until the counts exceed 4000. Counts between 3000 and 4000 are flagged with a caution flag (1). After 4000 counts a bad flag (2) is triggered and the data should not be used. Noise?: Instrument noise detected in 65-75nm size range. 1: Caution slight noise observed. 2: High amount of noise observed data should not be used. Total? Sum of all the flags triggered Max Flag: Max flag triggered by the above QC test CloudFlag: Warns of the presence of a cloud. Clouds can cause shattering on the probe and result in questionable measurements. Data during these periods of thin clouds (1) or heavy clouds (2) should be used with extreme caution.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1980

On the method of least squares

A method for fitting models to observed data by least squares when the data appear nonlinearly in the equations of condition, where there are nonlinear constraints among model parameters, and where the observations may be correlated, is described. The method is independent of the form in which the equations of condition are expressed, and is a generalization of the classical technique. The method is nearly as simple to apply in practice as the classical method of least squares.

Jefferys, W. H.↗

NASA NTRS1985

Solar pressure and molecular decay in cometary atmospheres

The effects of solar pressure and molecular decay on number density in cometary atmospheres are rigorously separated and scale lengths for each are determined from an analysis of observed brightness profiles in the solar and antisolar directions. It is found that the pressure scale length of CN is approximately 160,000 km and that of C2 is approximately 110,000 km. The scale length for molecular decay, heretofore incorrectly inferred from the observational data, is approximately 3 times as long as the pressure scale lengths. It is difficult to determine adequately from observations that extend no more than about 100,000 km from the comet nucleus. The scale length for molecular decay by photodissociation or whatever cause is found to be about 350,000 km for C2 and 500,000 km for CN.

Beard, D. B.↗

NASA NTRS1990

Three-dimensional simulation of the Denver 11 July Storm of 1988 - An intense microburst event

An account is given of results from a numerical simulation of an intense microburst-generating storm observed near Denver during a test operation of the Terminal Doppler Radar System, on July 11, 1988. The numerical simulation encompassed comparisons with 'observed' data from measurements by Doppler radar, aircraft flight data recorders, and surface field instruments. Model results are in excellent qualitative and quantitative agreement with major storm feature observations. The intense microburst that was generated some distance 'downshear' of the primary precipitation area was driven by cooling due to sublimating snow.

Proctor, Fred H.↗

NASA NTRS2011

Application of ESE Data and Tools to Air Quality Management: Services for Helping the Air Quality Community use ESE Data (SHAirED)

The goal of this REASoN applications and technology project is to deliver and use Earth Science Enterprise (ESE) data and tools in support of air quality management. Its scope falls within the domain of air quality management and aims to develop a federated air quality information sharing network that includes data from NASA, EPA, US States and others. Project goals were achieved through a access of satellite and ground observation data, web services information technology, interoperability standards, and air quality community collaboration. In contributing to a network of NASA ESE data in support of particulate air quality management, the project will develop access to distributed data, build Web infrastructure, and create tools for data processing and analysis. The key technologies used in the project include emerging web services for developing self describing and modular data access and processing tools, and service oriented architecture for chaining web services together to assemble customized air quality management applications. The technology and tools required for this project were developed within DataFed.net, a shared infrastructure that supports collaborative atmospheric data sharing and processing web services. Much of the collaboration was facilitated through community interactions through the Federation of Earth Science Information Partners (ESIP) Air Quality Workgroup. The main activities during the project that successfully advanced DataFed, enabled air quality applications and established community-oriented infrastructures were: develop access to distributed data (surface and satellite), build Web infrastructure to support data access, processing and analysis create tools for data processing and analysis foster air quality community collaboration and interoperability.

Falke, Stefan↗

NASA NTRS2017

Modeling Meteor Flares for Spacecraft Safety

NASA's Meteoroid Environment Office (MEO) is tasked with assisting spacecraft operators and engineers in quantifying the threat the meteoroid environment poses to their individual missions. A more complete understanding of the meteoroid environment for this application requires extensive observations. One manner by which the MEO observes meteors is with dedicated video camera systems that operate nightly. Connecting the observational data from these video cameras to the relevant physical properties of the ablating meteoroids, however, is subject to sizable observational and theoretical uncertainties. Arguably the most troublesome theoretical uncertainty in ablation is a model for the structure of meteoroids, as observations clearly show behaviors wholly inconsistent with meteoroids being homogeneous spheres. Further complicating the interpretation of the observations in the context of spacecraft risk is the ubiquitous process of fragmentation and the flares it can produce, which greatly muddles any attempts to estimating initial meteoroid masses. In this talk a method of estimating the mass distribution of fragments in flaring meteors using high resolution video observations will be dis- cussed. Such measurements provide an important step in better understanding of the structure and fragmentation process of the parent meteoroids producing these flares, which in turn may lead to better constraints on meteoroid masses and reduced uncertainties in spacecraft risk.

Ehlert, Steven↗