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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Aerosol Indirect Effect Studies at Southern Great Plains During the May 2003 Intensive Operations Period

During May 2003 the Department of Energy's Atmospheric Radiation Measurement Program conducted an Intensive Operations Period (IOP) to measure the radiative effects of aerosol and clouds. A suite of both in situ and remote sensing measurements were available to measure aerosol and cloud parameters. This paper has three main goals: First, it focuses on comparison between in situ retrievals of the radiatively important drop effective radius r(sub e) and various satellite, airborne, and surface remote sensing retrievals of the same parameter. On 17 May 2003, there was a fortuitous, near-simultaneous sampling of a stratus cloud by five different methods. The retrievals of r(sub e) agree with one another to within approx.20%, which is approximately the error estimate for most methods. Second, a methodology for deriving a best estimate of r(sub e) from these different instruments, with their different physical properties and sampling volumes, is proposed and applied to the 17 May event. Third, the paper examines the response of r(sub e) to changes in aerosol on 3 days during the experiment and examines the consistency of remote sensing and in situ measurements of the effect of aerosol on r(sub e). It is shown that in spite of the generally good agreement in derived r(sub e), the magnitude of the response of r(sub e), to changes in aerosol is quite sensitive to the method of retrieving r(sub e) and to the aerosol proxy for cloud condensation nuclei. Nonphysical responses are sometimes noted, and it is suggested that further work needs to be done to refine these techniques.

Feingold, Graham↗
NASA NTRS1983

Crop area estimation based on remotely-sensed data with an accurate but costly subsample

Alternatives to sampling-theory stratified and regression estimators of crop production and timber biomass were examined. An alternative estimator which is viewed as especially promising is the errors-in-variable regression estimator. Investigations established the need for caution with this estimator when the ratio of two error variances is not precisely known.

Gunst, R. F.↗
DOE OSTI2021

Immobilization of Cyanines in DNA Produces Systematic Increases in Fluorescence Intensity

Cyanines are useful fluorophores for a myriad of biological labeling applications, but their interactions with biomolecules are unpredictable. Cyanine fluorescence intensity can be highly variable due to complex photoisomerization kinetics, which are exceedingly sensitive to the surrounding environment. This introduces large errors in Förster resonance energy transfer (FRET)-based experiments where fluorescence intensity is the output parameter. However, this environmental sensitivity is a strength from a biological sensing point of view if specific relationships between biomolecular structure and cyanine photophysics can be identified. We describe a set of DNA structures that modulate cyanine fluorescence intensity through the insertion of adenine or thymine bases. These structures simultaneously provide photophysical predictability and tunability. We characterize these structures using steady-state fluorescence measurements, fluorescence correlation spectroscopy (FCS), and time-resolved photoluminescence (TRPL). Here, we find that the photoisomerization rate decreases over an order of magnitude across the adenine series, which is consistent with increasing immobilization of the cyanine moiety by the surrounding DNA structure.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Flight Considerations and Hyperspectral Image Classifications for Dryland Vegetation Management from a Fixed-wing UAS

Unmanned Aerial Systems (UAS)-based hyperspectral remote sensing capabilities developed by the Idaho National Lab and Boise Center Aerospace Lab were tested via demonstration flights that explored the influence of altitude on geometric error, image mosaicking, and dryland vegetation classification. The motivation for this study was to better understand the challenges associated with UAS-based hyperspectral data for distinguishing native grasses such as Sandberg bluegrass ( Poa secunda ) from invasives such as burr buttercup ( Ranunculus testiculatus) in a shrubland environment. The test flights successfully acquired usable flightline data capable of supporting classifiable composite images. Unsupervised classification results support vegetation management objectives that rely on mapping shrub cover and distribution patterns. However, supervised classifications performed poorly despite spectral separability in the image-derived endmember pixels. In many cases, the supervised classifications accentuated noise or features in the mosaic that were artifacts of color balancing and feathering in areas of flightline overlap. Future UAS flight missions that optimize flight planning; minimize illumination differences between flightlines; and leverage ground reference data and time series analysis should be able to effectively distinguish native grasses such as Sandberg bluegrass from burr buttercup.

58 GEOSCIENCES↗
NASA NTRS1972

Microscale photo interpretation of forest and nonforest land classes

Remote sensing of forest and nonforest land classes are discussed, using microscale photointerpretation. Results include: (1.) Microscale IR color photography can be interpreted within reasonable limits of error to estimate forest area. (2.) Forest interpretation is best on winter photography with 97 percent or better accuracy. (3.) Broad forest types can be classified on microscale photography. (4.) Active agricultural land is classified most accurately on early summer photography. (5.) Six percent of all nonforest observations were misclassified as forest.

Aldrich, R. C.↗
NASA NTRS1972

Rotating pressure measuring system for turbine cooling investigations

The development of a 10-channel rotating pressure measuring system capable of operation to speeds of 9000 rpm at transducer temperatures of about 320 K (120 F) is described. Variable-reluctance pressure transducers were mounted in the rotating system for sensing pressure. Rotating performance tests on a spin rig showed that the output data from 7 of the 10 transducers tested were within a desired system error of 3 percent. However, the error of the output data from three other transducers was as large as 8 percent of 9000 rpm. It was concluded from these test results that a rotating screening method was necessary to evaluate each pressure transducer channel within a system that will be used under rotating conditions.

Pollack, F. G.↗
NASA NTRS1985

Infrared horizon sensor modeling for attitude determination and control: Analysis and mission experience

The work performed by the Attitude Determination and Control Section at the National Aeronautics and Space Administration/Goddard Space Flight Center in analyzing and evaluating the performance of infrared horizon sensors is presented. The results of studies performed during the 1960s are reviewed; several models for generating the Earth's infrared radiance profiles are presented; and the Horizon Radiance Modeling Utility, the software used to model the horizon sensor optics and electronics processing to computer radiance-dependent attitude errors, is briefly discussed. Also provided is mission experience from 12 spaceflight missions spanning the period from 1973 to 1984 and using a variety of horizon sensing hardware. Recommendations are presented for future directions for the infrared horizon sensing technology.

Phenneger, M. C.↗
NASA NTRS2001

Battery Cell By-Pass Circuit

The invention is a circuit and method of limiting the charging current voltage from a power supply net work applied to an individual cell of a plurality of cells making up a battery being charged in series. It is particularly designed for use with batteries that can be damaged by overcharging, such as Lithium-ion type batteries. In detail. the method includes the following steps: 1) sensing the actual voltage level of the individual cell; 2) comparing the actual voltage level of the individual cell with a reference value and providing an error signal representative thereof; and 3) by-passing the charging current around individual cell necessary to keep the individual cell voltage level generally equal a specific voltage level while continuing to charge the remaining cells. Preferably this is accomplished by by-passing the charging current around the individual cell if said actual voltage level is above the specific voltage level and allowing the charging current to the individual cell if the actual voltage level is equal or less than the specific voltage level. In the step of bypassing the charging current, the by-passed current is transferred at a proper voltage level to the power supply. The by-pass circuit a voltage comparison circuit is used to compare the actual voltage level of the individual cell with a reference value and to provide an error signal representative thereof. A third circuit, designed to be responsive to the error signal, is provided for maintaining the individual cell voltage level generally equal to the specific voltage level. Circuitry is provided in the third circuit for bypassing charging current around the individual cell if the actual voltage level is above the specific voltage level and transfers the excess charging current to the power supply net work. The circuitry also allows charging of the individual cell if the actual voltage level is equal or less than the specific voltage level.

Evers, Jeffrey↗
NASA NTRS2001

Battery Cell By-Pass Circuit

The invention is a circuit and method of limiting the charging current voltage from a power supply net work applied to an individual cell of a plurality of cells making up a battery being charged in series. It is particularly designed for use with batteries that can be damaged by overcharging, such as Lithium-ion type batteries. In detail. the method includes the following steps: 1) sensing the actual voltage level of the individual cell; 2) comparing the actual voltage level of the individual cell with a reference value and providing an error signal representative thereof; and 3) by-passing the charging current around individual cell necessary to keep the individual cell voltage level generally equal a specific voltage level while continuing to charge the remaining cells. Preferably this is accomplished by by-passing the charging current around the individual cell if said actual voltage level is above the specific voltage level and allowing the charging current to the individual cell if the actual voltage level is equal or less than the specific voltage level. In the step of bypassing the charging current, the by-passed current is transferred at a proper voltage level to the power supply. The by-pass circuit a voltage comparison circuit is used to compare the actual voltage level of the individual cell with a reference value and to provide an error signal representative thereof. A third circuit, designed to be responsive to the error signal, is provided for maintaining the individual cell voltage level generally equal to the specific voltage level. Circuitry is provided in the third circuit for bypassing charging current around the individual cell if the actual voltage level is above the specific voltage level and transfers the excess charging current to the power supply net work. The circuitry also allows charging of the individual cell if the actual voltage level is equal or less than the specific voltage level.

Susan J Mumaw↗
NASA NTRS2003

Using X-band Weather Radar Measurements to Monitor the Integrity of Digital Elevation Models for Synthetic Vision Systems

Synthetic Vision Systems (SVS) provide pilots with displays of stored geo-spatial data representing terrain, obstacles, and cultural features. As comprehensive validation is impractical, these databases typically have no quantifiable level of integrity. Further, updates to the databases may not be provided as changes occur. These issues limit the certification level and constrain the operational context of SVS for civil aviation. Previous work demonstrated the feasibility of using a realtime monitor to bound the integrity of Digital Elevation Models (DEMs) by using radar altimeter measurements during flight. This paper describes an extension of this concept to include X-band Weather Radar (WxR) measurements. This enables the monitor to detect additional classes of DEM errors and to reduce the exposure time associated with integrity threats. Feature extraction techniques are used along with a statistical assessment of similarity measures between the sensed and stored features that are detected. Recent flight-testing in the area around the Juneau, Alaska Airport (JNU) has resulted in a comprehensive set of sensor data that is being used to assess the feasibility of the proposed monitor technology. Initial results of this assessment are presented.

Young, Steve↗
NASA NTRS2019

Soil Moisture Data Assimilation to Estimate Irrigation Water Use

Knowledge of irrigation is essential to support food security, manage depleting water resources, and comprehensively understand the global water and energy cycles. Despite the importance of understanding irrigation, little consistent information exists on the amount of water that is applied for irrigation. In this study, we develop and evaluate a new method to predict daily to seasonal irrigation magnitude using a particle batch smoother data assimilation approach, where land surface model soil moisture is applied in different configurations to understand how characteristics of remotely sensed soil moisture may impact the performance of the method. The study employs a suite of synthetic data assimilation experiments, allowing for systematic diagnosis of known error sources. Assimilation of daily synthetic soil moisture observations with zero noise produces irrigation estimates with a seasonal bias of 0.66% and a correlation of 0.95 relative to a known truth irrigation. When synthetic observations were subjected to an irregular overpass interval and random noise similar to the Soil Moisture Active Passive satellite (0.04 cm(exp 3) cm(exp -3)), irrigation estimates produced a median seasonal bias of <1% and a correlation of 0.69. When systematic biases commensurate with those between NLDAS‐2 land surface models and Soil Moisture Active Passive are imposed, irrigation estimates show larger biases. In this application, the particle batch smoother outperformed the particle filter. The presented framework has the potential to provide new information into irrigation magnitude over spatially continuous domains, yet its broad applicability is contingent upon identifying new method(s) of determining irrigation schedule and correcting biases between observed and simulated soil moisture, as these errors markedly degraded performance.

R Abolafia-Rosenzweig↗
NASA NTRS2022

Compressive Sensing Based Space Flight Instrument Constellation for Measuring Gravitational Microlensing Parallax

In this work, we provide a compressive sensing architecture for implementing on a space based observatory for detecting transient photometric parallax caused by gravitational microlensing events. Compressive sensing (CS) is a simultaneous data acquisition and compression technique, which can greatly reduce on-board resources required for space flight data storage and ground transmission. We simulate microlensing parallax observations using a space observatory constellation, based on CS detectors. Our results show that average CS error is less than 0.5% using 25% Nyquist rate samples. The error at peak magnification time is significantly lower than the error for distinguishing any two microlensing parallax curves at their peak magnification. Thus, CS is an enabling technology for detecting microlensing parallax, without causing any loss in detection accuracy.

compressive sensing↗
NASA NTRS1998

Design and Calibration of the X-33 Flush Airdata Sensing (FADS) System

This paper presents the design of the X-33 Flush Airdata Sensing (FADS) system. The X-33 FADS uses a matrix of pressure orifices on the vehicle nose to estimate airdata parameters. The system is designed with dual-redundant measurement hardware, which produces two independent measurement paths. Airdata parameters that correspond to the measurement path with the minimum fit error are selected as the output values. This method enables a single sensor failure to occur with minimal degrading of the system performance. The paper shows the X-33 FADS architecture, derives the estimating algorithms, and demonstrates a mathematical analysis of the FADS system stability. Preliminary aerodynamic calibrations are also presented here. The calibration parameters, the position error coefficient (epsilon), and flow correction terms for the angle of attack (delta alpha), and angle of sideslip (delta beta) are derived from wind tunnel data. Statistical accuracy of' the calibration is evaluated by comparing the wind tunnel reference conditions to the airdata parameters estimated. This comparison is accomplished by applying the calibrated FADS algorithm to the sensed wind tunnel pressures. When the resulting accuracy estimates are compared to accuracy requirements for the X-33 airdata, the FADS system meets these requirements.

Whitmore, Stephen A.↗
NASA NTRS2007

The Influence of Antenna Pattern on Faraday Rotation in Remote Sensing at L-band

Faraday rotation is a change in the polarization vector of electromagnetic radiation that occurs as the waves propagate from the Earth surface through the ionosphere to a spaceborne sensor. This change can cause errors in monitoring parameters at the surface such as soil moisture and sea surface salinity and it is an important consideration for radiometers on future missions in space such as NASA's Aquarius mission and ESA's SMOS mission. Two prominent strategies for compensating for Faraday rotation are using a sum of the signal at two polarizations and using the correlation between the signals at the two polarizations. These strategies work for an idealized antenna. This paper evaluates the strategies in the context of realistic antennas such as will be built for the Aquarius radiometer. Realistic antennas will make small differences that need to be included in planning for retrieval algorithms in future missions.

LeVine, David M.↗
NASA NTRS2004

Experimental Verification of Dispersed Fringe Sensing as a Segment Phasing Technique using the Keck Telescope

Dispersed Fringe Sensing (DFS) is an efficient and robust method for coarse phasing of segmented primary mirrors (from a quarter of a wavelength up to the depth of focus of a single segment, typically several tens of microns). Unlike phasing techniques currently used for ground-based segmented telescopes; this makes it particularly well-suited to the phasing of space-borne segmented telescopes, such as the James Webb Space Telescopes (JWST). In this work we validate DFS by using it to measure the pistons of the segments of one of the Keck telescopes; the results agree with those of the Shack-Hartmann based phasing scheme currently in use at Keck to within 2% over a range of initial piston errors of +/-16 microns.

dispersed fringe sensors↗
DOE OSTI2018

Compressive Sensing with Cross-Validation and Stop-Sampling for Sparse Polynomial Chaos Expansions

Here, compressive sensing is a powerful technique for recovering sparse solutions of underdetermined linear systems, which is often encountered in uncertainty quantification analysis of expensive and high-dimensional physical models. We perform numerical investigations employing several compressive sensing solvers that target the unconstrained LASSO formulation, with a focus on linear systems that arise in the construction of polynomial chaos expansions. With core solvers l1_ls, SpaRSA, CGIST, FPC_AS, and ADMM, we develop techniques to mitigate overfitting through an automated selection of regularization constant based on cross-validation, and a heuristic strategy to guide the stop-sampling decision. Practical recommendations on parameter settings for these techniques are provided and discussed. The overall method is applied to a series of numerical examples of increasing complexity, including large eddy simulations of supersonic turbulent jet-in-crossflow involving a 24-dimensional input. Through empirical phase-transition diagrams and convergence plots, we illustrate sparse recovery performance under structures induced by polynomial chaos, accuracy, and computational trade-offs between polynomial bases of different degrees, and practicability of conducting compressive sensing for a realistic, high-dimensional physical application. Across test cases studied in this paper, we find ADMM to have demonstrated empirical advantages through consistent lower errors and faster computational times.

97 MATHEMATICS AND COMPUTING↗