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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Contemporary Trends in the Acid-Base Status of the Two Acid-Sensitive Streams in Western Maryland

Recovery of streamwater acid neutralizing capacity (ANC) resulting from declines in regional acid deposition was examined using contemporary (1990-2005) data from two long-term monitoring stations located on the Appalachian Plateau in western Maryland, U.S. Two computational methods were used to estimate daily, monthly, and annual fluxes and discharge-weighted concentrations of ANC, sulfate, nitrate, and base cations over the period of record, and two statistical methods were used to evaluate long-term trends in fluxes and concentrations. The methods used to estimate concentrations, as well as the, statistical techniques, produced very similar results, underlining the robustness of the identified trends. We found clear evidence that streamwater sulfate concentrations have declined at an average rate of about 3 (microns)eq L(exp -1) yr(exp -1) at the two sites due to a 34% reduction in wet atmospheric sulfur deposition. Trends in nitrate concentrations appear to be related to other watershed factors, especially forest disturbance. The best evidence of recovery is based on a doubling of ANC (from 21 to 42 (microns)eq L(exp -1) at the more acid-sensitive site over the 16-year period. A slowing, or possible reversal, in the sulfate, nitrate, and SBC trends is evident in our data and may portend a decline in the rate of--or end to--further recovery.

Eshleman, Keith N.↗
NASA NTRSDate not supplied

Deep Learning System for Efficient Processing of Geostationary Satellite Imagery

Improved capabilities of Earth monitoring satellites are enabling a wide range of studies on the environmental effects of climate change, often leveraging the recent advancements in machine learning. At the same time, the new capabilities, including higher spatial resolution and temporal frequency, are expanding the amount of data generated at exponential rates. Further, a large majority of archived datasets generated by scientific processing is never used. This motivates the development of an efficient machine learning system for end-to-end processing of multi-level satellite datasets, from level 1 top of atmosphere observations to user friendly environmental variables of interest. Using current generation geostationary satellites GOES-16/17 (NOAA/NASA), and Himawari-8/9 (JAXA), we present an interchangeable set of machine models to perform spectral adjustment among sensors, physical model emulation, LEO-GEO emulation, and optical flow in a high performance computing environment. We use these tools on the NASA Earth eXchange (NEX) to generate consistent virtual observations across sensors, perform atmospheric correction and cloud detection, and estimate surface reflectance, surface temperature and atmospheric winds. This approach aims to improve the robustness of remotely sensed data processing by learning from diverse sets of observations while enabling near real-time and on-demand capabilities.

Thomas Vandal↗
NASA NTRS2022

Gravity Poppers: Hopping Probes for the Internal Mapping of Small Solar System Bodies

This paper presents the results of NIAC Phase I study into the feasibility of a novel mission architecture for highresolution gravity science on small Solar System bodies. The “Gravity Poppers” mission concept (see Fig. 1) consists of a swarm of small, minimalistic probes that are deployed from a mother spacecraft to the surface of a small body and which periodically and randomly hop around the surface. By tracking the ballistic sub-orbital trajectories of this hopping swarm, a very high resolution gravity field can be measured, which can then be used to answer a number of scientific questions of interest regarding the interior mass distribution of the body. This paper describes the three core focus areas of our study to demonstrate concept feasibility: (1) the design of hopping probes to be small, simple, robust, and “visible” to a distant spacecraft, (2) the tracking strategy for detecting and estimating the trajectories of a large number of ballistic probes, and (3) the algorithmic framework by which such measurements can be used to estimate the body’s gravity field. Our results suggest the ability to estimate the gravity field of a 500m asteroid beyond degree-and-order 40 through days to weeks of optical tracking of several LED-strobing probes, with a mass of only 200 g each. Collectively, this study demonstrates that the high-resolution gravity mapping of small body interiors is technically possible, economically feasible, and would enable a compelling set of science objectives aligned with NASA’s goals in planetary science, planetary defense, and future interests in resource prospecting.

McMahon, Jay↗
NASA NTRS1990

A real time neural net estimator of fatigue life

A neural net architecture is proposed to estimate, in real-time, the fatigue life of mechanical components, as part of the Intelligent Control System for Reusable Rocket Engines. Arbitrary component loading values were used as input to train a two hidden-layer feedforward neural net to estimate component fatigue damage. The ability of the net to learn, based on a local strain approach, the mapping between load sequence and fatigue damage has been demonstrated for a uniaxial specimen. Because of its demonstrated performance, the neural computation may be extended to complex cases where the loads are biaxial or triaxial, and the geometry of the component is complex (e.g., turbopump blades). The generality of the approach is such that load/damage mappings can be directly extracted from experimental data without requiring any knowledge of the stress/strain profile of the component. In addition, the parallel network architecture allows real-time life calculations even for high frequency vibrations. Owing to its distributed nature, the neural implementation will be robust and reliable, enabling its use in hostile environments such as rocket engines. This neural net estimator of fatigue life is seen as the enabling technology to achieve component life prognosis, and therefore would be an important part of life extending control for reusable rocket engines.

Troudet, T.↗
NASA NTRS2002

Cost Estimation and Control for Flight Systems

Good program management practices, cost analysis, cost estimation, and cost control for aerospace flight systems are interrelated and depend upon each other. The best cost control process cannot overcome poor design or poor systems trades that lead to the wrong approach. The project needs robust Technical, Schedule, Cost, Risk, and Cost Risk practices before it can incorporate adequate Cost Control. Cost analysis both precedes and follows cost estimation -- the two are closely coupled with each other and with Risk analysis. Parametric cost estimating relationships and computerized models are most often used. NASA has learned some valuable lessons in controlling cost problems, and recommends use of a summary Project Manager's checklist as shown here.

Hammond, Walter E.↗
NASA NTRS2017

Methodology for Time-Domain Estimation of Storm Time Geoelectric Fields Using the 3-D Magnetotelluric Response Tensors

Geoelectric fields at the Earth's surface caused by magnetic storms constitute a hazard to the operation of electric power grids and related infrastructure. The ability to estimate these geoelectric fields in close to real time and provide local predictions would better equip the industry to mitigate negative impacts on their operations. Here we report progress toward this goal: development of robust algorithms that convolve a magnetic storm time series with a frequency domain impedance for a realistic three-dimensional (3-D) Earth, to estimate the local, storm time geoelectric field. Both frequency domain and time domain approaches are presented and validated against storm time geoelectric field data measured in Japan. The methods are then compared in the context of a real-time application.

Kelbert, Anna↗
NASA NTRSDate not supplied

OCO-2 Satellite-imposed Constraints on Terrestrial Biospheric CO2 Flux over South Asia

The spatiotemporal variability of terrestrial biospheric carbon dioxide (CO2) flux over South Asia is poorly understood. The inverse model “top-down” CO2 flux estimates which rely on atmospheric CO2 observational data are impeded by sparse in situ measurements over this region. The Orbiting Carbon Observatory 2 (OCO-2) provides much needed global retrievals of column-average CO2 dry-air mole fraction (XCO2) with the finest spatial and temporal resolution and highest sensitivity to surface fluxes available to-date. This study conducted global inverse model simulations as part of the second OCO-2 Multi-model Intercomparison Project assimilating version 9 of the OCO-2 XCO2 retrievals in land nadir (LN) and land glint (LG) observing modes and global in situ (IS) measurements. The four-dimensional variational assimilation system with the GEOS-Chem global chemical transport model was used to estimate CO2 fluxes from 2015 to 2018. We then assessed the spatiotemporal variability of optimized CO2 Net ecosystem Exchange (NEE) fluxes aggregated over the South Asia region. The most robust result found by assimilating OCO-2 observations was the constraints imposed on the seasonal cycle of terrestrial biospheric fluxes over South Asia. The seasonality of South Asian NEE estimated by assimilating OCO-2 or global IS data showed a larger seasonal cycle compared to the current understanding of NEE in this region (represented by the prior NEE used in the model). The satellite-in situ joint inversion (IS + LN + LG) led to land flux seasonal amplitude (absolute magnitude of the difference between peak and trough of monthly mean values over a year) of 4.0 PgC yr-1, compared to the prior model (1.5 PgC yr-1). Moreover, OCO-2 data imposed a phase shift in the seasonal cycle, resulting in a large CO2 source in April and a large uptake in September. Most of the features in the seasonal cycle imposed by OCO-2 data are in agreement with previous “top-down” studies assimilating regional aircraft observations. Nevertheless, we recommend a closer examination of the novel features highlighted by the OCO-2 column data over South Asia in future studies by conducting regional inverse modelling with denser in situ and vertically-resolved regional observations along with satellite data.

OCO-2↗
NASA NTRS2001

State Estimation for K9

The goal of 'Estimate' is to take advantage of attitude information to produce better pose while staying flexible and robust. Currently there are several instruments that are used for attitude: gyros, inclinometers, and compasses. However, precise and useful attitude information cannot come from one instrument. Integration of rotational rates, from gyro data for example, would result in drift. Therefore, although gyros are accurate in the short-term, accuracy in the long term is unlikely. Using absolute instruments such as compasses and inclinometers can result in an accurate measurement of attitude in the long term. However, in the short term, the physical nature of compasses and inclinometers, and the dynamic nature of a mobile platform result in highly volatile and therefore useless data. The solution then is to use both absolute and relative data. Kalman Filtering is known to be able to combine gyro and compass/inclinometer data to produce stable and accurate attitude information. Since the model of motion is linear and the data comes in as discrete samples, a Discrete Kalman Filter was selected as the core of the new estimator. Therefore, 'Estimate' can be divided into two parts: the Discrete Kalman Filter and the code framework.

Xu, Ru-Gang↗
NASA NTRS2004

Intelligent, Robust Control of Deteriorated Turbofan Engines via Linear Parameter Varying Quadratic Lyapunov Function Design

A method for accommodating engine deterioration via a scheduled Linear Parameter Varying Quadratic Lyapunov Function (LPVQLF)-Based controller is presented. The LPVQLF design methodology provides a means for developing unconditionally stable, robust control of Linear Parameter Varying (LPV) systems. The controller is scheduled on the Engine Deterioration Index, a function of estimated parameters that relate to engine health, and is computed using a multilayer feedforward neural network. Acceptable thrust response and tight control of exhaust gas temperature (EGT) is accomplished by adjusting the performance weights on these parameters for different levels of engine degradation. Nonlinear simulations demonstrate that the controller achieves specified performance objectives while being robust to engine deterioration as well as engine-to-engine variations.

Turso, James A.↗
NASA NTRS1996

Moving Through Time: The Utility of a Temporal Metric for Vehicular Control

Recent work on time-to-contact (TTC) and time-to-passage (TTP) estimation have revealed conflicting evidence. On the one hand, when tau information is available, observers often fail to use it properly. For instance, absolute size of the object, rotation, and contrast all interfere with estimation accuracy. That is, the visual system often is unable to isolate tau. On the other hand, judgments are remarkably robust when invariant information is no longer available. Observers seem to adjust to many disturbances. This symposium intends to stimulate a discussion of recent findings within visual and auditory TTC paradigms. Alternative concepts that are able to accommodate these findings should be entertained and, if found valid, incorporated into the classic theory of temporal-range estimation.

Kaiser, Mary K.↗
NASA NTRS2004

IVS Tropospheric Parameters: Comparison with DORIS and GPS for CONT02

In April 2002 the IVS (International VLBI Service for Geodesy and Astrometry) set up the Pilot Project - Tropospheric Parameters, and the Institute of Geodesy and Geophysics (IGG), Vienna, was put in charge of coordinating the project. Seven IVS Analysis Centers have joined the project and regularly submitted their estimates of tropospheric parameters (wet and total zenith delays, horizontal gradients) for all IVS-R1 mid IVS-R4 sessions since January 1st, 2002. The individual submissions are combined by a two-step procedure to obtain stable, robust and highly accurate tropospheric parameter time series with one hour resolution (internal accuracy: 2-4 ram). Starting with July 2003, the combined tropospheric estimates became operational IVS products. In the second half of October 2002 the VLBI campaign CONT02 was observed with 8 stations participating around the globe. At four of them (Gilmore Creek, U.S.A.; Hartebeesthoek, South Africa; Kokee Park, U.S.A.; Ny-Alesund, Norway) also total zenith delays from DORIS (Doppler Orbitography and Radiopositioning Integrated by Satellite) are available and these estimates are compared with those from the IGS (International GPS Service) and the IVS. The distance from the DORIS beacons to the co-located GPS and VLBI stations is around 2 km or less for the four sites mentioned above.

Schuh, Harald↗
NASA NTRS2013

Estimating Root Mean Square Errors in Remotely Sensed Soil Moisture over Continental Scale Domains

Root Mean Square Errors (RMSE) in the soil moisture anomaly time series obtained from the Advanced Scatterometer (ASCAT) and the Advanced Microwave Scanning Radiometer (AMSR-E; using the Land Parameter Retrieval Model) are estimated over a continental scale domain centered on North America, using two methods: triple colocation (RMSETC ) and error propagation through the soil moisture retrieval models (RMSEEP ). In the absence of an established consensus for the climatology of soil moisture over large domains, presenting a RMSE in soil moisture units requires that it be specified relative to a selected reference data set. To avoid the complications that arise from the use of a reference, the RMSE is presented as a fraction of the time series standard deviation (fRMSE). For both sensors, the fRMSETC and fRMSEEP show similar spatial patterns of relatively highlow errors, and the mean fRMSE for each land cover class is consistent with expectations. Triple colocation is also shown to be surprisingly robust to representativity differences between the soil moisture data sets used, and it is believed to accurately estimate the fRMSE in the remotely sensed soil moisture anomaly time series. Comparing the ASCAT and AMSR-E fRMSETC shows that both data sets have very similar accuracy across a range of land cover classes, although the AMSR-E accuracy is more directly related to vegetation cover. In general, both data sets have good skill up to moderate vegetation conditions.

Remotely sensed soil moisture validation↗
NASA NTRS1985

Robust detection, isolation, and accommodation for sensor failures

Recent advances in multivariable robust control system design are extended to sensor failure, detection, isolation, and accommodation (FDIA) and estimator design. A new concept called threshold selector is introduced. It represents a significant and innovative tool for the analysis and synthesis of FDIA algorithms. Analytical results are obtained for the SISO case to compute optimal thresholds and size of minimum detectable failures, and a computer-aided technique is developed for the multivariable case. The techniques have been applied to sensor FDIA for an aircraft turbine engine control system.

Emami-Naeini, A.↗
NASA NTRS1986

Design of a multivariable flutter control/gust load alleviation system

This paper discusses the use of eigenspace techniques for the design of an active flutter control/gust load alleviation system for a hypothetical research drone. One leading edge and two trailing edge aerodynamic surfaces are available for control. Full state control laws are designed for two combinations of control surfaces by selecting feedback gains which place closed loop eigenvalues and shape closed loop eigenvectors so as to stabilize wing flutter and reduce gust loads at the wing root while yielding acceptable robustness and satisfying constraints on rms control surface activity. These controllers are realized by state estimators designed using an eigenvalue placement/eigenvector shaping technique which results in recovery of the loop transfer characteristics of the full state feedback systems. The resulting feedback compensators are shown to perform almost as well as the full state designs. They also exhibit acceptable performance in situations in which the failure of an actuator is simulated.

Liebst, B. S.↗
NASA NTRS1987

Eigenspace techniques for active flutter suppression

The use of eigenspace techniques for the design of an active flutter suppression system for a hypothetical research drone is discussed. One leading edge and two trailing edge aerodynamic control surfaces and four sensors (accelerometers) are available for each wing. Full state control laws are designed by selecting feedback gains which place closed loop eigenvalues and shape closed loop eigenvectors so as to stabilize wing flutter and reduce gust loads at the wing root while yielding accepatable robustness and satisfying constrains on rms control surface activity. These controllers are realized by state estimators designed using an eigenvalue placement/eigenvector shaping technique which results in recovery of the full state loop transfer characteristics. The resulting feedback compensators are shown to perform almost as well as the full state designs. They also exhibit acceptable performance in situations in which the failure of an actuator is simulated.

Garrard, William L.↗
NASA NTRS2000

Water Vapor Winds and Their Application to Climate Change Studies

The retrieval of satellite-derived winds and moisture from geostationary water vapor imagery has matured to the point where it may be applied to better understanding longer term climate changes that were previously not possible using conventional measurements or model analysis in data-sparse regions. In this paper, upper-tropospheric circulation features and moisture transport covering ENSO periods are presented and discussed. Precursors and other detectable interannual climate change signals are analyzed and compared to model diagnosed features. Estimates of winds and humidity over data-rich regions are used to show the robustness of the data and its value over regions that have previously eluded measurement.

Jedlovec, Gary J.↗
NASA NTRS2012

Difficulties in Using GRBs as Standard Candles

Gamma-Ray Bursts have been detected uniformly all over the observable universe, ranging in comoving distance from a few hundred Mpc to a few thousand Mpc, representing the farthest observable objects in the universe. This large distance coverage is highly attractive to those who study cosmology and the history of the early universe since there are no other observed objects that represent such a deep and comprehensive probe of the history of the universe. For this reason, there have been extensive studies into the possibility of using GRBs as standard candles much like Type Ia Supernovae, even though little is known about the physical mechanism that produces the observed burst of gamma-rays. We discuss the attempts at defining GRBs as standard candles, such as the search for a robust luminosity indicator, pseudo-redshift predictions, the complications that emission collimation introduces into the estimation of the rest-frame energetics, and the difficulty introduced by the widely varying observed properties of GRBs. These topics will be examined with supporting data and analyses from both Fermi and Swift observations. Problems with current studies using GRBs as standard candles will be noted as well as potential paths forward to solve these problems.

Goldstein, Adam↗