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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.

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At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Specification of the ISS Plasma Environment Variability

Quantifying the spacecraft charging risks and corresponding hazards for the International Space Station (ISS) requires a plasma environment specification describing the natural variability of ionospheric temperature (Te) and density (Ne). Empirical ionospheric specification and forecast models such as the International Reference Ionosphere (IRI) model typically only provide estimates of long term (seasonal) mean Te and Ne values for the low Earth orbit environment. Knowledge of the Te and Ne variability as well as the likelihood of extreme deviations from the mean values are required to estimate both the magnitude and frequency of occurrence of potentially hazardous spacecraft charging environments for a given ISS construction stage and flight configuration. This paper describes the statistical analysis of historical ionospheric low Earth orbit plasma measurements used to estimate Ne, Te variability in the ISS flight environment. The statistical variability analysis of Ne and Te enables calculation of the expected frequency of Occurrence of any particular values of Ne and Te, especially those that correspond to possibly hazardous spacecraft charging environments. The database used in the original analysis included measurements from the AE-C, AE-D, and DE-2 satellites. Recent work on the database has added additional satellites to the database and ground based incoherent scatter radar observations as well. Deviations of the data values from the IRI estimated Ne, Te parameters for each data point provide a statistical basis for modeling the deviations of the plasma environment from the IRI model output. This technique, while developed specifically for the Space Station analysis, can also be generalized to provide ionospheric plasma environment risk specification models for low Earth orbit over an altitude range of 200 km through approximately 1000 km.

Minow, Joseph I.↗
NASA NTRS2002

Specifying the ISS Plasma Environment

Quantifying the spacecraft charging risks and corresponding hazards for the International Space Station (ISS) requires a plasma environment specification describing the natural variability of ionospheric temperature (Te) and density (Ne). Empirical ionospheric specification and forecast models such as the International Reference Ionosphere (IN) model typically only provide estimates of long term (seasonal) mean Te and Ne values for the low Earth orbit environment. Knowledge of the Te and Ne variability as well as the likelihood of extreme deviations from the mean values are required to estimate both the magnitude and frequency of occurrence of potentially hazardous spacecraft charging environments for a given ISS construction stage and flight configuration. This paper describes the statistical analysis of historical ionospheric low Earth orbit plasma measurements used to estimate Ne, Te variability in the ISS flight environment. The statistical variability analysis of Ne and Te enables calculation of the expected frequency of occurrence of any particular values of Ne and Te, especially those that correspond to possibly hazardous spacecraft charging environments. The database used in the original analysis included measurements from the AE-C, AE-D, and DE-2 satellites. Recent work on the database has added additional satellites to the database and ground based incoherent scatter radar observations as well. Deviations of the data values from the IRI estimated Ne, Te parameters for each data point provide a statistical basis for modeling the deviations of the plasma environment from the IRI model output.

Minow, Joseph I.↗
NASA NTRS2011

Receiver Gain Modulation Circuit

A receiver gain modulation circuit (RGMC) was developed that modulates the power gain of the output of a radiometer receiver with a test signal. As the radiometer receiver switches between calibration noise references, the test signal is mixed with the calibrated noise and thus produces an ensemble set of measurements from which ensemble statistical analysis can be used to extract statistical information about the test signal. The RGMC is an enabling technology of the ensemble detector. As a key component for achieving ensemble detection and analysis, the RGMC has broad aeronautical and space applications. The RGMC can be used to test and develop new calibration algorithms, for example, to detect gain anomalies, and/or correct for slow drifts that affect climate-quality measurements over an accelerated time scale. A generalized approach to analyzing radiometer system designs yields a mathematical treatment of noise reference measurements in calibration algorithms. By treating the measurements from the different noise references as ensemble samples of the receiver state, i.e. receiver gain, a quantitative description of the non-stationary properties of the underlying receiver fluctuations can be derived. Excellent agreement has been obtained between model calculations and radiometric measurements. The mathematical formulation is equivalent to modulating the gain of a stable receiver with an externally generated signal and is the basis for ensemble detection and analysis (EDA). The concept of generating ensemble data sets using an ensemble detector is similar to the ensemble data sets generated as part of ensemble empirical mode decomposition (EEMD) with exception of a key distinguishing factor. EEMD adds noise to the signal under study whereas EDA mixes the signal with calibrated noise. It is mixing with calibrated noise that permits the measurement of temporal-functional variability of uncertainty in the underlying process. The RGMC permits the evaluation of EDA by modulating the receiver gain using an external signal. Without the RGMC, samples of calibrated references from radiometers form an ensemble data set of the natural occurring fluctuations within a receiver. By driving the gain of an otherwise stable receiver with an external signal, the conceptual framework and generalization of the mathematics of EDA can be tested. A series of measurements was conducted to evaluate and characterize the performance of the RGMC. Test signals stepped the RGMC across its dynamic range of performance using a radiometer that sampled four noise references; analysis indicates that the RGMC successfully modulated the receiver gain with an external signal. Calibration algorithms applied to four noise references demonstrate the RGMC produced ensemble data sets of the external signal.

Jones, Hollis↗
DOE OSTI2025

Lost and Found: Rediscovering Microbiome-Associated Phenotypes that Reshape Agricultural Sustainability

Overview Code and data repository for NIL Manuscript. Documentation includes sequence processing examples and data analysis. Supplemental sequence processing and R statistical analysis for publication, which compares the microbiome of teosinte-B73 Near Isogenic Lines. Sample Data Amplicon sequence data for 16S rRNA genes, the fungal ITS2 region, and nitrogen-cycling functional genes are available through the NCBI Sequence Read Archive (SRA) under accession number PRJNA1042643(https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1042643). Raw metabolomic data are available on Metabolomics Workbench, Project ID: PR002654. This study is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org where it has been assigned Study ID ST004211. The data can be accessed directly via its Project DOI: http://dx.doi.org/10.21228/M8KV8T.

Near Isogeneic Lines↗
NASA NTRS1986

Information extraction from multivariate images

An overview of several multivariate image processing techniques is presented, with emphasis on techniques based upon the principal component transformation (PCT). Multiimages in various formats have a multivariate pixel value, associated with each pixel location, which has been scaled and quantized into a gray level vector, and the bivariate of the extent to which two images are correlated. The PCT of a multiimage decorrelates the multiimage to reduce its dimensionality and reveal its intercomponent dependencies if some off-diagonal elements are not small, and for the purposes of display the principal component images must be postprocessed into multiimage format. The principal component analysis of a multiimage is a statistical analysis based upon the PCT whose primary application is to determine the intrinsic component dimensionality of the multiimage. Computational considerations are also discussed.

Park, S. K.↗
NASA NTRS1992

Reliability evaluation methodology for NASA applications

Liquid rocket engine technology has been characterized by the development of complex systems containing large number of subsystems, components, and parts. The trend to even larger and more complex system is continuing. The liquid rocket engineers have been focusing mainly on performance driven designs to increase payload delivery of a launch vehicle for a given mission. In otherwords, although the failure of a single inexpensive part or component may cause the failure of the system, reliability in general has not been considered as one of the system parameters like cost or performance. Up till now, quantification of reliability has not been a consideration during system design and development in the liquid rocket industry. Engineers and managers have long been aware of the fact that the reliability of the system increases during development, but no serious attempts have been made to quantify reliability. As a result, a method to quantify reliability during design and development is needed. This includes application of probabilistic models which utilize both engineering analysis and test data. Classical methods require the use of operating data for reliability demonstration. In contrast, the method described in this paper is based on similarity, analysis, and testing combined with Bayesian statistical analysis.

Taneja, Vidya S.↗
NASA NTRS1999

Current and Future Plans of the NASA Data Assimilation Office (DAO)

The mission of the Data Assimilation Office (DAO) is to advance the state of the art of data assimilation and produce research-quality assimilated data sets which make optimal use of space-based observations. Development efforts over the last few years have focused on delivering a production data assimilation system in support of NASA's Terra platform. That system, called the Goddard Earth Observing System - version 2 or GEOS-2, represents a major upgrade to the baseline GEOS-1 system employed in NASA's first reanalysis effort. GEOS-2 includes a physical-space three dimensional variational analysis algorithm (the Physical-space Statistical Analysis System or PSAS) and numerous improvements to the general circulation model. The latter include a Soil-Vegetation-Atmosphere Transfer (SVAT) land surface scheme, a level 2.5 moist turbulence scheme and new Short Wave (SW) and Long Wave (LW) radiation code. The system also includes an off-line ozone assimilation system, and the capability to assimilate scatterometer surface winds, and TIROS Operational Vertical Sounder (TOVS) and Special Sensor Microwave Imager (SSM/I) moisture data. GEOS-2 is currently run at 1 degree horizontal resolution and 48 levels extending to O.Olmb. Experimental versions of GEOS-2 are run with a global stretched grid allowing enhanced (e.g. 1/4 deg) regional resolution. Other capabilities being developed include, the assimilation of Tropical Rainfall Measuring Mission (TRMM) precipitation and Global Positioning System (GPS) data, an off-line land surface assimilation system, and a retrospective analysis scheme. The DAO is also engaged in a number of collaborative efforts to help accelerate the development of the next generation data assimilation system. These include, a joint modeling effort between the DAO and NCAR/CGDD to develop a new Global Circulation Model (GCM), and a Department of Energy Lawrence Livermore National Laboratory (DOE/LLNL) collaboration on model parallelization. Plans for the next reanalysis will be discussed in the context of current and near term system quality and computing capabilities, and the need for multiple reanalysis products.

Atlas, Robert↗
NASA NTRS2001

The Computational Complexity, Parallel Scalability, and Performance of Atmospheric Data Assimilation Algorithms

The computational complexity of algorithms for Four Dimensional Data Assimilation (4DDA) at NASA's Data Assimilation Office (DAO) is discussed. In 4DDA, observations are assimilated with the output of a dynamical model to generate best-estimates of the states of the system. It is thus a mapping problem, whereby scattered observations are converted into regular accurate maps of wind, temperature, moisture and other variables. The DAO is developing and using 4DDA algorithms that provide these datasets, or analyses, in support of Earth System Science research. Two large-scale algorithms are discussed. The first approach, the Goddard Earth Observing System Data Assimilation System (GEOS DAS), uses an atmospheric general circulation model (GCM) and an observation-space based analysis system, the Physical-space Statistical Analysis System (PSAS). GEOS DAS is very similar to global meteorological weather forecasting data assimilation systems, but is used at NASA for climate research. Systems of this size typically run at between 1 and 20 gigaflop/s. The second approach, the Kalman filter, uses a more consistent algorithm to determine the forecast error covariance matrix than does GEOS DAS. For atmospheric assimilation, the gridded dynamical fields typically have More than 10(exp 6) variables, therefore the full error covariance matrix may be in excess of a teraword. For the Kalman filter this problem can easily scale to petaflop/s proportions. We discuss the computational complexity of GEOS DAS and our implementation of the Kalman filter. We also discuss and quantify some of the technical issues and limitations in developing efficient, in terms of wall clock time, and scalable parallel implementations of the algorithms.

Lyster, Peter M.↗
NASA NTRS2004

Geomorphologic Studies of a Very Long Lava Flow in Tharsis, Mars

CEPS has undertaken an extended study of long lava flows on the terrestrial planets, their location, morphology, and potential modes of emplacement. As part of this ongoing investigation, we have concentrated on a single large flow in Tharsis, with noted similarities to several terrestrial analogs. An impressive series of lava flows emerges from the topographic saddle between Ascraeus and Pavonis Mons. The most prominent of these (hereafter referred to as the 'Saddle Flow') has distinct margins that can be traced for over 480 km in the Viking images, although its exact source cannot be identified. A multimodal approach is utilized in the examination of the Saddle Flow, including image interpretation (VIKING and THEMIS, MOLA topographic analysis and flow profiling, downflow behavior statistical analysis, rheologic modeling, and GIS modeling and integration.

Peitersen, M. N.↗