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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 415 records · Page 23

Adaptive planning for applications with dynamic objectives

We devise a qualitative control layer to be integrated into a real-time multi-agent reactive planner. The reactive planning system consists of distributed planning agents attending to various perspectives of the task environment. Each perspective corresponds to an objective. The set of objectives considered are sometimes in conflict with each other. Each agent receives information about events as they occur, and a set of actions based on heuristics can be taken by the agents. Within the qualitative control scheme, we use a set of qualitative feature vectors to describe the effects of applying actions. A qualitative transition vector is used to denote the qualitative distance between the current state and the target state. We will then apply on-line learning at the qualitative control level to achieve adaptive planning. Our goal is to design a mechanism to refine the heuristics used by the reactive planner every time an action is taken toward achieving the objectives, using feedback from the results of the actions. When the outcome is compared with expectations, our prior objectives may be modified and a new set of objectives (or a new assessment of the relative importance of the different objectives) can be introduced. Because we are able to obtain better estimates of the time-varying objectives, the reactive strategies can be improved and better prediction can be achieved.

Hadavi, Khosrow↗

Effects of data selection on the assimilation of AIRS data

The Atmospheric InfraRed Sounder (AIRS), flying aboard NASA's Earth Observing System (EOS) Aqua satellite with the Advanced Microwave Sounding Unit-A (AMSU-A), has been providing data for use in numerical weather prediction (NWP) and data assimilation systems (DAS) for over three years. The full AIRS data set is currently not transmitted in near-real-time (NRT) to the NWP centers. Instead, data sets with reduced spatial and spectral information are produced and made available in NRT. In this paper, we evaluate the use of different channel selections and error specifications. We achieved significant positive impact from the Aqua AIRS/AMSU-A combination in both hemispheres during our experimental time period of January 2003. The best results were obtained using a set of 156 channels that did not include any in the 6.7micron water vapor band. The latter have a large influence on both temperature and humidity analyses. If observation and background errors are not properly specified, the partitioning of temperature and humidity information from these channels will not be correct, and this can lead to a degradation in forecast skill. We found that changing the specified channel errors had a significant effect on the amount of data that entered into the analysis as a result of quality control thresholds that are related to the errors. However, changing the channel errors within a relatively small window did not significantly impact forecast skill with the 155 channel set. We also examined the effects of different types of spatial data reduction on assimilated data sets and NWP forecast skill. Whether we picked the center or the warmest AIRS pixel in a 3x3 array affected the amount of data ingested by the analysis but had a negligible impact on the forecast skill.

Joiner, Joanna↗

Huntsville Operations Support Center

Information is given in viewgraph form on the Huntsville Operations Support Center (HOSC). The HOSC is a multi-mission control and support facility designed to provide simultaneous support to several diverse missions, using a common set of processing equipment and facilities. Information is given on the missions supported by the HOSC; facility layout; generic system goals; HOSC existing computer architecture; current mission requirements; currently employed hardware and software; front end processing; central processing; peripheral processors; audio and video communications; and upgrading plans.

Bailey, Darrell G.↗

Smart Congestion Control for Delay- and Disruption Tolerant Networks

In this paper, we propose a novel congestion control framework for delay- and disruption tolerant networks (DTNs). The proposed framework, called Smart-DTN-CC, adjusts its operation automatically as a function of the dynamics of the underlying network. It employs reinforcement learning, a machine learning technique known to be well suited to problems in which the environment, in this case the network, plays a crucial role; yet, no prior knowledge about the target environment can be assumed, i.e., the only way to acquire information about the environment is to interact with it through continuous online learning. Smart-DTN-CC nodes get input from the environment (e.g., its buffer occupancy, set of neighbors, etc), and, based on that information, choose an action to take from a set of possible actions. Depending on an action’s effectiveness in controlling congestion, it will be given a reward. Smart-DTN-CC’s goal is to maximize the overall reward which translates to minimizing congestion. To our knowledge, Smart-DTN-CC is the first DTN congestion control framework that has the ability to automatically and continuously adapt to the dynamics of the target environment which allows Smart-DTNCC to deliver adequate performance in a variety of DTN applications and scenarios. As demonstrated by our experimental evaluation, Smart-DTN-CC is able to consistently outperform existing DTN congestion control mechanisms under a wide range of network conditions and characteristics.

Hirata, Celso M.↗

Automated Machine Learning to Evaluate the Information Content of Tropospheric Trace Gas Columns for Fine Particle Estimates Over India: A Modeling Testbed

India is largely devoid of high-quality and reliable on-the-ground measurements of fine particulate matter (PM 2.5 ). Ground-level PM 2.5 concentrations are estimated from publicly available satellite Aerosol Optical Depth (AOD) products combined with other information. Prior research has largely overlooked the possibility of gaining additional accuracy and insights into the sources of PM using satellite retrievals of tropospheric trace gas columns. We evaluate the information content of tropospheric trace gas columns for PM 2.5 estimates over India within a modeling testbed using an Automated Machine Learning (AutoML) approach, which selects from a menu of different machine learning tools based on the data set. We then quantify the relative information content of tropospheric trace gas columns, AOD, meteorological fields, and emissions for estimating PM 2.5 over four Indian sub-regions on daily and monthly time scales. Our findings suggest that, regardless of the specific machine learning model assumptions, incorporating trace gas modeled columns improves PM 2.5 estimates. We use the ranking scores produced from the AutoML algorithm and Spearman’s rank correlation to infer or link the possible relative importance of primary versus secondary sources of PM 2.5 as a first step toward estimating particle composition. Our comparison of AutoML-derived models to selected baseline machine learning models demonstrates that AutoML is at least as good as user-chosen models. The idealized pseudo-observations (chemical-transport model simulations) used in this work lay the groundwork for applying satellite retrievals of tropospheric trace gases to estimate fine particle concentrations in India and serve to illustrate the promise of AutoML applications in atmospheric and environmental research.

Machine learning↗

Space Station Information System requirements for integrated communications

Space Station Information System (SSIS) requirements for integrated end-to-end communications are presented. The SSIS is defined as the integrated set of space and ground data and information systems and networks which will provide required data services to the Space Station flight crew, ground operations personnel, and customer communities. This model is based on the International Standards Organization (ISO) layered model for Open System Interconnection (OSI). These SSIS requirements include grades of service, priority classifications, systems management, flow control, bandwidth allocation, and standard SSIS data services.

Marker, W.↗

Discerning Trends in Performance Across Multiple Events

Mass Data is a computer program that enables rapid, easy discernment of trends in performance data across multiple flights and ground tests. The program can perform Fourier analysis and other functions for the purposes of frequency analysis and trending of all variables. These functions facilitate identification of past use of diagnosed systems and of anomalies in such systems, and enable rapid assessment of related current problems. Many variables, for computation of which it is usually necessary to perform extensive manual manipulation of raw downlist data, are automatically computed and made available to all users, regularly eliminating the need for what would otherwise be an extensive amount of engineering analysis. Data from flight, ground test, and simulation are preprocessed and stored in one central location for instantaneous access and comparison for diagnostic and trending purposes. Rules are created so that an event log is created for every flight, making it easy to locate information on similar maneuvers across many flights. The same rules can be created for test sets and simulations, and are searchable, so that information on like events is easily accessible.

Slater, Simon↗

The Relationship Of Size Distributions To Spectral (300 - 700 Nm) Extinction Parameterization Of Ambient In Situ Aerosols Measured During FIREX-AQ And The Influence Of Aerosol Composition

Hyperspectral (300 - 700 nm, 0.7 nm resolution) aerosol extinction spectra were measured at seven fires in six states in the western United States during the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) field campaign in July and August 2019. Obtained using an in situ aerosol sampling method, these spectra are directly comparable to other in situ aerosol measurements such as size distribution and composition. A previous deployment of the in situ Spectral Aerosol Extinction (SpEx) instrument that measured fine mode aerosols (50% size cut of 1.3 µm particle diameter) around the Korean peninsula showed that over this spectral range 2nd order polynomials provided a better fit to the logarithmically transformed spectra than linear fits (representative of Ångström exponents). The two fit parameters (a1, a2) of the polynomials are related to the classic Ångström exponent but provide additional information via their two-dimensional parameter space. The previous work was limited by the lack of commensurate size distribution information. Here, using the FIREX-AQ spectra set it is possible to expand on the previous analysis in three specific ways: 1) size distribution information is available to further elucidate how size distribution maps into (a1, a2) space, 2) the sampled size distributions include larger particles than the Korean study, and 3) the FIREX-AQ data set exhibits smoke-related spectral features in the UV part of the spectrum that are not present in background air nor were they observed previously in the Korean study. The UV spectral features are particularly intriguing as they likely arise from the absorption component of the extinction measurement and therefore may be related to composition. The relationships between the ambient in situ aerosol size distributions, the extinction spectra, and composition will be presented.

Carolyn Jordan↗

BOREAS TE-7 Dendrology Data

The BOREAS TE-7 team collected data sets in support of its efforts to characterize and interpret information on the sapflow and dendrology of boreal vegetation. This data set contains dendrology measurements, consisting of tree ring width and density taken at several points within each ring,.Measurements were taken near the TE towers at the OJP and OBS sites in NSA. In the SSA, measurements were taken near the TE towers at the MIX, OBS, and OJP sites; at the AIM- 1 3 and BMH-9 sites; and near the TF-YJP site. All data were collected during the summer of 1994. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Hall, Forrest G.↗

An Analysis of Rocket Propulsion Testing Costs

The primary mission at NASA Stennis Space Center (SSC) is rocket propulsion testing. Such testing is commonly characterized as one of two types: production testing for certification and acceptance of engine hardware, and developmental testing for prototype evaluation or research and development (R&D) purposes. For programmatic reasons there is a continuing need to assess and evaluate the test costs for the various types of test campaigns that involve liquid rocket propellant test articles. Presently, in fact, there is a critical need to provide guidance on what represents a best value for testing and provide some key economic insights for decision-makers within NASA and the test customers outside the Agency. Hence, selected rocket propulsion test databases and references have been evaluated and analyzed with the intent to discover correlations of technical information and test costs that could help produce more reliable and accurate cost projections in the future. The process of searching, collecting, and validating propulsion test cost information presented some unique obstacles which then led to a set of recommendations for improvement in order to facilitate future cost information gathering and analysis. In summary, this historical account and evaluation of rocket propulsion test cost information will enhance understanding of the various kinds of project cost information; identify certain trends of interest to the aerospace testing community.

Ramirez, Carmen↗

Radiation Quality Effects on Transcriptome Profiles in 3-d Cultures After Particle Irradiation

In this work, we evaluate the differential effects of low- and high-LET radiation on 3-D organotypic cultures in order to investigate radiation quality impacts on gene expression and cellular responses. Reducing uncertainties in current risk models requires new knowledge on the fundamental differences in biological responses (the so-called radiation quality effects) triggered by heavy ion particle radiation versus low-LET radiation associated with Earth-based exposures. We are utilizing novel 3-D organotypic human tissue models that provide a format for study of human cells within a realistic tissue framework, thereby bridging the gap between 2-D monolayer culture and animal models for risk extrapolation to humans. To identify biological pathway signatures unique to heavy ion particle exposure, functional gene set enrichment analysis (GSEA) was used with whole transcriptome profiling. GSEA has been used extensively as a method to garner biological information in a variety of model systems but has not been commonly used to analyze radiation effects. It is a powerful approach for assessing the functional significance of radiation quality-dependent changes from datasets where the changes are subtle but broad, and where single gene based analysis using rankings of fold-change may not reveal important biological information. We identified 45 statistically significant gene sets at 0.05 q-value cutoff, including 14 gene sets common to gamma and titanium irradiation, 19 gene sets specific to gamma irradiation, and 12 titanium-specific gene sets. Common gene sets largely align with DNA damage, cell cycle, early immune response, and inflammatory cytokine pathway activation. The top gene set enriched for the gamma- and titanium-irradiated samples involved KRAS pathway activation and genes activated in TNF-treated cells, respectively. Another difference noted for the high-LET samples was an apparent enrichment in gene sets involved in cycle cycle/mitotic control. It is plausible that the enrichment in these particular pathways results from the complex DNA damage resulting from high-LET exposure where repair processes are not completed during the same time scale as the less complex damage resulting from low-LET radiation.

Patel, Z. S.↗

Statistical Properties of Maximum Likelihood Estimators of Power Law Spectra Information

A simple power law model consisting of a single spectral index, a is believed to be an adequate description of the galactic cosmic-ray (GCR) proton flux at energies below 10(exp 13) eV, with a transition at the knee energy, E(sub k), to a steeper spectral index alpha(sub 2) greater than alpha(sub 1) above E(sub k). The Maximum likelihood (ML) procedure was developed for estimating the single parameter alpha(sub 1) of a simple power law energy spectrum and generalized to estimate the three spectral parameters of the broken power law energy spectrum from simulated detector responses and real cosmic-ray data. The statistical properties of the ML estimator were investigated and shown to have the three desirable properties: (P1) consistency (asymptotically unbiased). (P2) efficiency asymptotically attains the Cramer-Rao minimum variance bound), and (P3) asymptotically normally distributed, under a wide range of potential detector response functions. Attainment of these properties necessarily implies that the ML estimation procedure provides the best unbiased estimator possible. While simulation studies can easily determine if a given estimation procedure provides an unbiased estimate of the spectra information, and whether or not the estimator is approximately normally distributed, attainment of the Cramer-Rao bound (CRB) can only he ascertained by calculating the CRB for an assumed energy spectrum-detector response function combination, which can be quite formidable in practice. However. the effort in calculating the CRB is very worthwhile because it provides the necessary means to compare the efficiency of competing estimation techniques and, furthermore, provides a stopping rule in the search for the best unbiased estimator. Consequently, the CRB for both the simple and broken power law energy spectra are derived herein and the conditions under which they are attained in practice are investigated. The ML technique is then extended to estimate spectra information from an arbitrary number of astrophysics data sets produced by vastly different science instruments. This theory and its successful implementation will facilitate the interpretation of spectral information from multiple astrophysics missions and thereby permit the derivation of superior spectral parameter estimates based on the combination of data sets.

Howell, L. W.↗

Integrated identification and robust control tuning for large space structures

System identification is studied for the explicit purpose of supporting modern H-infinity robust control design objectives. In the analysis, the true plant is not assumed to be in the identification model set. An integrated identification/robust control problem is posed in which the optimal solution guarantees the best robust performance relative to the system information contained in a given experimental data set. A numerical example demonstrating an approximate solution to the problem indicates the usefulness of the approach.

Yam, Y.↗

New Attitude Sensor Alignment Calibration Algorithms

Accurate spacecraft attitudes may only be obtained if the primary attitude sensors are well calibrated. Launch shock, relaxation of gravitational stresses and similar effects often produce large enough alignment shifts so that on-orbit alignment calibration is necessary if attitude accuracy requirements are to be met. A variety of attitude sensor alignment algorithms have been developed to meet the need for on-orbit calibration. Two new algorithms are presented here: ALICAL and ALIQUEST. Each of these has advantages in particular circumstances. ALICAL is an attitude independent algorithm that uses near simultaneous measurements from two or more sensors to produce accurate sensor alignments. For each set of simultaneous observations the attitude is overdetermined. The information content of the extra degrees of freedom can be combined over numerous sets to provide the sensor alignments. ALIQUEST is an attitude dependent algorithm that combines sensor and attitude data into a loss function that has the same mathematical form as the Wahba problem. Alignments can then be determined using any of the algorithms (such as the QUEST quaternion estimator) that have been developed to solve the Wahba problem for attitude. Results from the use of these methods on active missions are presented.

Hashmall, Joseph A.↗

NASA/EOSDIS Persistent Identifier Implementation

This presentation briefly summarizes the NASA Earth Science Data & Information Systems (ESDIS) Project’s approach to persistent identifiers for Earth science data sets and documentation in the Earth Observing System Data & Information System (EOSDIS). It briefly summarizes the ESDIS Project’s policies, and implementation approach, using Digital Object Identifiers.

Persistent Identifiers↗

Quantum Search in Hilbert Space

A proposed quantum-computing algorithm would perform a search for an item of information in a database stored in a Hilbert-space memory structure. The algorithm is intended to make it possible to search relatively quickly through a large database under conditions in which available computing resources would otherwise be considered inadequate to perform such a task. The algorithm would apply, more specifically, to a relational database in which information would be stored in a set of N complex orthonormal vectors, each of N dimensions (where N can be exponentially large). Each vector would constitute one row of a unitary matrix, from which one would derive the Hamiltonian operator (and hence the evolutionary operator) of a quantum system. In other words, all the stored information would be mapped onto a unitary operator acting on a quantum state that would represent the item of information to be retrieved. Then one could exploit quantum parallelism: one could pose all search queries simultaneously by performing a quantum measurement on the system. In so doing, one would effectively solve the search problem in one computational step. One could exploit the direct- and inner-product decomposability of the unitary matrix to make the dimensionality of the memory space exponentially large by use of only linear resources. However, inasmuch as the necessary preprocessing (the mapping of the stored information into a Hilbert space) could be exponentially expensive, the proposed algorithm would likely be most beneficial in applications in which the resources available for preprocessing were much greater than those available for searching.

Zak, Michail↗

An investigation of fluid flow during induction stroke of a water analog model of an IC engine using an innovative optical velocimetry concept: LIPA

Optical measurements on an axisymmetrical quartz component engine research model were made to evaluate the flow field encountered during induction. The measurement technique is LIPA (Laser Induced Photochemical Anemometry), a non-intrusive velocimetry concept that provides an investigator of fluid flow with a tool to attain planar information about three-dimensional velocity and vorticity vectors in a single measurement step. The goal of this investigation is to further develop this measurement technique and apply it to study the induction stroke of a water analog model of a four-stroke internal combustion engine. The research conducted in the water analog model is a fundamental scientific inquiry into the flow fields that develop in the induction stroke of an engine at idling engine speeds. As this is the first investigation of its kind using LIPA technique, our goal has been to quantify, in a preliminary manner, the flow field features that develop during the intake stroke. In the process a more comprehensive understanding of the flow field features was developed, and tied to the quantification. The study evaluated the flow field of the intake stroke by estimating fields of velocity and vorticity. On the basis of these data, information about fluid dynamics during induction at engine speeds of 10, 20, and 30 RPM (corresponding to 170, 340, and 510 RPM respectively, when air is the flowing medium) for three different valve lifts was obtained. The overall development of the flow field, its energy content (kinetic, fluctuation) for the different settings of the engine parameters, vorticity information, and cyclic variations have been quantified. These have been discussed in terms of mixing performance.

Stier, Bernd↗

Process and representation in graphical displays

How people comprehend graphics is examined. Graphical comprehension involves the cognitive representation of information from a graphic display and the processing strategies that people apply to answer questions about graphics. Research on representation has examined both the features present in a graphic display and the cognitive representation of the graphic. The key features include the physical components of a graph, the relation between the figure and its axes, and the information in the graph. Tests of people's memory for graphs indicate that both the physical and informational aspect of a graph are important in the cognitive representation of a graph. However, the physical (or perceptual) features overshadow the information to a large degree. Processing strategies also involve a perception-information distinction. In order to answer simple questions (e.g., determining the value of a variable, comparing several variables, and determining the mean of a set of variables), people switch between two information processing strategies: (1) an arithmetic, look-up strategy in which they use a graph much like a table, looking up values and performing arithmetic calculations; and (2) a perceptual strategy in which they use the spatial characteristics of the graph to make comparisons and estimations. The user's choice of strategies depends on the task and the characteristics of the graph. A theory of graphic comprehension is presented.

Gillan, Douglas J.↗