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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 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
NASA NTRS1961

Study of a Solar Sensor for use in Space Vehicle Orientation Control Systems

The solar sensor described herein may be used for a variety of space operations requiring solar orientation. The use of silicon solar cells as the sensing elements provides the sensor with sufficient capability to withstand the hazards of a space environment. A method of arranging the cells in a sensor consists simply of mounting them at a large angle to the base. The use of an opaque shield placed between the cells and perpendicular to the base enhances the small-angle sensitivity while adding slightly to the bulk of the sensor. The difference in illumination of these cells as the result of an oblique incidence of the light rays from the reference source causes an electrical error signal which, when used in a battery-bridge circuit, requires a minimum of electrical processing for use in a space-vehicle orientation control system. An error which could occur after prolonged operation of the sensor is that resulting from asymmetrical aging of opposite cells. This could be periodically corrected with a balance potentiometer. A more routine error in the sensor is that produced by reflected earth radiation. This error may be eliminated over a large portion of the operation time by restricting the field of view and, consequently, the capture capability. A more sophisticated method of eliminating this error is to use separate sensors, for capture and fine pointing, along with a switching device. An experimental model has been constructed and tested to yield an output sensitivity of 1.2 millivolts per second of arc with a load resistance of 1,000 ohms and a reference light source of approximately 1,200 foot-candles delivered at the sensor.

Spencer, Paul R.↗
NASA NTRS2014

Combined Uncertainty and A-Posteriori Error Bound Estimates for General CFD Calculations: Theory and Software Implementation

This workshop presentation discusses the design and implementation of numerical methods for the quantification of statistical uncertainty, including a-posteriori error bounds, for output quantities computed using CFD methods. Hydrodynamic realizations often contain numerical error arising from finite-dimensional approximation (e.g. numerical methods using grids, basis functions, particles) and statistical uncertainty arising from incomplete information and/or statistical characterization of model parameters and random fields. The first task at hand is to derive formal error bounds for statistics given realizations containing finite-dimensional numerical error [1]. The error in computed output statistics contains contributions from both realization error and the error resulting from the calculation of statistics integrals using a numerical method. A second task is to devise computable a-posteriori error bounds by numerically approximating all terms arising in the error bound estimates. For the same reason that CFD calculations including error bounds but omitting uncertainty modeling are only of limited value, CFD calculations including uncertainty modeling but omitting error bounds are only of limited value. To gain maximum value from CFD calculations, a general software package for uncertainty quantification with quantified error bounds has been developed at NASA. The package provides implementations for a suite of numerical methods used in uncertainty quantification: Dense tensorization basis methods [3] and a subscale recovery variant [1] for non-smooth data, Sparse tensorization methods[2] utilizing node-nested hierarchies, Sampling methods[4] for high-dimensional random variable spaces.

CFD↗
DOE OSTI2014

TEST OF THE HEMISPHERIC RULE OF MAGNETIC HELICITY IN THE SUN USING THE HELIOSEISMIC AND MAGNETIC IMAGER (HMI) DATA

Magnetic twist in solar active regions (ARs) has been found to have a hemispheric preference in sign (hemisphere rule): negative in the northern hemisphere and positive in the southern. The preference reported in previous studies ranges greatly, from ∼ 58% to 82%. In this study, we examine this hemispheric preference using vector magnetic field data taken by Helioseismic and Magnetic Imager and find that 75% ± 7% of 151 ARs studied obey the hemisphere rule, well within the preference range in previous studies. If the sample is divided into two groups—ARs having magnetic twist and writhe of the same sign and having opposite signs—the strength of the hemispheric preference differs substantially: 64% ± 11% for the former group and 87% ± 8% for the latter. This difference becomes even more significant in a sub-sample of 82 ARs having a simple bipole magnetic configuration: 56% ± 16% for the ARs having the same signs of twist and writhe, and 93% with lower and upper confidence bounds of 80% and 98% for the ARs having the opposite signs. The error reported here is a 95% confidence interval. This may suggest that, prior to emergence of magnetic tubes, either the sign of twist does not have a hemispheric preference or the twist is relatively weak.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1990

Retrieval methods for ground-based millimeter-wave measurements for the network for the detection of stratospheric change

The fundamental objective is to determine the information available in ground-based millimeter-wave measurements of stratospheric constituent profiles, to identify the optimum method of retrieving this profile information, and to characterize the errors in the final result. A secondary objective is to produce retrieval software for operational use with Network for the Detection of Stratospheric Change (NDSC) measurements of O3, H2O, ClO, and perhaps N2O. Tests were performed on existing ozone retrieval programs in support of ongoing NDSC field measurements. The results show that if random spectral errors and retrieval bias errors are considered, accuracy of the retrieved profile is about 5 percent from 20-50 km, and about 10 percent from 50-60 km.

Connor, Brian J.↗
DOE OSTI2015

A MULTIWAVELENGTH STUDY OF TADPOLE GALAXIES IN THE HUBBLE ULTRA DEEP FIELD

Multiwavelength data are essential in order to provide a complete picture of galaxy evolution and to inform studies of galaxies’ morphological properties across cosmic time. Here we present the results of a multiwavelength investigation of the morphologies of “tadpole” galaxies at intermediate redshift (0.314 < z < 3.175) in the Hubble Ultra Deep Field. These galaxies were previously selected from deep Hubble Space Telescope (HST) F775W data based on their distinct asymmetric knot-plus-tail morphologies. Here we use deep Wide Field Camera 3 near-infrared imaging in addition to the HST optical data in order to study the rest-frame UV/optical morphologies of these galaxies across the redshift range 0.3 < z < 3.2. This study reveals that the majority of these galaxies do retain their general asymmetric morphology in the rest-frame optical over this redshift range, if not the distinct “tadpole” shape. The average stellar mass of tadpole galaxies is lower than that of field galaxies, with the effect being slightly greater at higher redshift within the errors. Estimated from spectral energy distribution fits, the average age of tadpole galaxies is younger than that of field galaxies in the lower-redshift bin, and the average metallicity is lower (whereas the specific star formation rate for tadpoles is roughly the same as field galaxies across the redshift range probed here). These average effects combined support the conclusion that this subset of galaxies is in an active phase of assembly, either late-stage merging or cold gas accretion causing localized clumpy star formation.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1995

Analysis of an astrometric Fizeau interferometer for GAIA

The concepts related to the operation and design of the global astrometric interferometer for astrophysics (GAIA) bring together solutions chosen for the astrometry satellite and interferometric techniques. Like the Hipparcos satellite, GAIA is a continuously scanning instrument for which the integration time on any observed object is limited by the field of view of the detector. If a final astrometric accuracy of 10 microarcsec is aimed at, a field of 1 deg in diameter is needed. A design is presented for the proposed 2.6 m baseline Fizeau interferometer with two 40 cm apertures and overall dimensions compatible with the size of the Ariane 5 payload shroud. It has a 0.9 deg diffraction limited field of view. The response of the optical system to small perturbations on each optical element is given in terms of the fringe visibility, which is shown to be dependent on the sub-aperture spot separation. The robustness of the design to thermal, mechanical and manufacturing errors is discussed. The unavoidable distortion present in wide field optical systems is analyzed in terms of displacement of the interference fringes.

Loiseau, Sacha↗
DOE OSTI2019

TROPoe retrievals from SGP C1

The TROPoe (formerly called AERIoe) algorithm (Turner and L&ouml;hnert 2014, 2021; Turner and Blumberg 2019) retrieves profiles of temperature and water vapor mixing ratio, together with cloud properties for a single-layer cloud (i.e., LWP, effective radius), from AERI-observed infrared radiance spectrum. The data can be used to characterize the evolution of the planetary boundary layer and boundary layer clouds. This data set was collected at the ARM SGP Central Facility (CF) during and after the MicroPulse DIAL Demonstration (MPDDEMO) field campaign. The TROPoe retrieval was run at 5-minute resolution, but retrievals can be performed at the maximum temporal resolution of the AERI instrument (order 30 s) -- if this higher temporal resolution is desired, please contact Dave Turner. This is a physical-iterative retrieval method. The retrieval of thermodynamic profiles from spectral infrared radiance observations is an ill-posed problem, and thus constraints need to be included in the retrieval algorithm to provide physically plausible results. Here, we use a climatology of radiosonde profiles collected at the ARM SGP site during the summer as our prior information in an optimal estimation framework. Surface meteorology and output from the rapid-refresh (RAP) numerical weather prediction model (above 4 km) were used as additional constraints by the retrieval. As the method uses an optimal estimation framework, a full error covariance matrix of each solution is included in the output file. The 1-sigma uncertainty of each retrieved variable, which is derived from the error covariance matrix, is included for each scientific field and is named "sigma_X", where "X" is the name of the scientific field (e.g., 'temperature'). The information content in the AERI observations, which is in the "dfs" field, on the thermodynamic profiles is primarily concentrated in the lowest 3 km or up to cloud base; the retrieved data should not be used above that level (or used with caution). There is an overall "qc_flag" field that is set when a retrieval should not be trusted. However, the logic that sets this flag did not work correctly, and it should not be used. Instead, consider all retrievals that have a value for "converged_flag" greater than 0 as valid. If you have any questions, contact Dave Turner. This is Release_2_12 of the TROPoe algorithm.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1976

Models and error analyses in urban air quality estimation

Estimation theory has been applied to a wide range of aerospace problems. Application of this expertise outside the aerospace field has been extremely limited, however. This paper describes the use of covariance error analysis techniques in evaluating the accuracy of pollution estimates obtained from a variety of concentration measuring devices. It is shown how existing software developed for aerospace applications can be applied to the estimation of pollution through the processing of measurement types involving a range of spatial and temporal responses. The modeling of pollutant concentration by meandering Gaussian plumes is described in some detail. Time averaged measurements are associated with a model of the average plume, using some of the same state parameters and thus avoiding the problem of state memory. The covariance analysis has been implemented using existing batch estimation software. This usually involves problems in handling dynamic noise; however, the white dynamic noise has been replaced by a band-limited process which can be easily accommodated by the software.

Englar, T., Jr.↗
NASA NTRS1990

Automatic recognition of intermittent failures - An experimental study of field data

A methodology is proposed for recognizing the symptoms of persistent problems in large systems. The system error rate is used to identify the error states among which relationships may exist. Statistical techniques are used to validate and quantify the strength of the relationship among these error states. As input, the approach takes the raw error logs containing a single entry for each error that is detected as an isolated event. As output, it produces a list of symptoms that characterize persistent errors. Thus, given a failure, it is determined whether the failure is an intermittent manifestation of a common fault or whether it is an isolated (transient) incident. The technique is shown to work on two CYBER systems and an IBM 3081 multiprocessor system. Comparisons to real failure/repair information obtained from field engineers show that, in about 85 percent of the cases, the error symptoms recognized by this approach correspond to real problems. The remaining 15 percent of the cases, although not directly supported by field data, are confirmed as being valid problems.

Iyer, Ravishankar K.↗
NASA NTRS2013

Spatial Statistical Data Fusion (SSDF)

As remote sensing for scientific purposes has transitioned from an experimental technology to an operational one, the selection of instruments has become more coordinated, so that the scientific community can exploit complementary measurements. However, tech nological and scientific heterogeneity across devices means that the statistical characteristics of the data they collect are different. The challenge addressed here is how to combine heterogeneous remote sensing data sets in a way that yields optimal statistical estimates of the underlying geophysical field, and provides rigorous uncertainty measures for those estimates. Different remote sensing data sets may have different spatial resolutions, different measurement error biases and variances, and other disparate characteristics. A state-of-the-art spatial statistical model was used to relate the true, but not directly observed, geophysical field to noisy, spatial aggregates observed by remote sensing instruments. The spatial covariances of the true field and the covariances of the true field with the observations were modeled. The observations are spatial averages of the true field values, over pixels, with different measurement noise superimposed. A kriging framework is used to infer optimal (minimum mean squared error and unbiased) estimates of the true field at point locations from pixel-level, noisy observations. A key feature of the spatial statistical model is the spatial mixed effects model that underlies it. The approach models the spatial covariance function of the underlying field using linear combinations of basis functions of fixed size. Approaches based on kriging require the inversion of very large spatial covariance matrices, and this is usually done by making simplifying assumptions about spatial covariance structure that simply do not hold for geophysical variables. In contrast, this method does not require these assumptions, and is also computationally much faster. This method is fundamentally different than other approaches to data fusion for remote sensing data because it is inferential rather than merely descriptive. All approaches combine data in a way that minimizes some specified loss function. Most of these are more or less ad hoc criteria based on what looks good to the eye, or some criteria that relate only to the data at hand.

Braverman, Amy J.↗
DOE OSTI2021

An in-depth field validation of “DUSST”: A novel low-maintenance soiling measurement device

This study presents indoor and field validation results for two versions of the “DUSST” optical soiling sensor, intended to be a low-cost and low-maintenance device for measuring photovoltaic soiling losses. Indoor testing covers irradiance calibration and temperature dependencies, which are necessary to achieve high accuracy, low uncertainty field measurements. Field testing includes an array of different environments including Saudi Arabia, California, Utah, and Colorado. DUSST versions include a configuration with a 530-nm light emitting diode (LED) (discussed in previous work) and a unit with seven white LEDs and a polycarbonate collimating optic. The new design increases light intensity fivefold and demonstrates a single linear calibration coefficient is effective to measure soiling losses as high as 75%. Field data from Utah and California demonstrate that daily soiling loss measurements and soiling rate calculations closely match both reference cell and full-size module measurements of soiling losses and soiling rates. Corrective methods employed on the Utah DUSST sensor suggest that it is possible to achieve measurement errors as low as ±0.1% at two standard deviations. Field data from both Colorado and Saudi Arabia demonstrate that LED lens soiling can occur and that further design optimizations are needed. The lesson learned from all the field deployment locations suggests directions for future design improvements.

14 SOLAR ENERGY↗
NASA NTRS1990

Analysis of AVHRR, CZCS and historical in situ data off the Oregon Coast

The original scientific objectives of this grant were to: (1) characterize the seasonal cycles and interannual variability for phytoplankton concentrations and sea surface temperature (SST) in the California Current using satellite data; and (2) to explore the spatial and temporal relationship between these variables and surface wind forcing. An additional methodological objective was to develop statistical methods for forming mean fields, which minimize the effects of random data gaps and errors in the irregularly sampled CZCS (Coastal Zone Color Scanner) and AVHRR (Advanced Very High Resolution Radiometer) satellite data. A final task was to evaluate the level of uncertainty in the wind fields used for the statistical analysis. Funding in the first year included part of the cost of an image processing system to enable this and other projects to process and analyze satellite data. This report consists of summaries of the major projects carried out with all or partial support from this grant. The appendices include a list of papers and professional presentations supported by the grant, as well as reprints of the major papers and reports.

Strub, P. Ted↗
NASA NTRS1963

The World Magnetic Survey

The mathematical and graphical description of the earth's main field has been, and is, a "data limited" problem. The World Magnetic Survey (WMS) is an endeavor to minimize this limitation by rapidly and comprehensively blanketing the earth with magnetic field measurements. Satellite surveys, which will play a key role in the W MS, are the principal topic of this paper. Existing magnetic field descriptions, the expected results from new surveys, and the methods of obtaining these results with the POGO satellite are emphasized. It is anticipated on the basis of extrapolation from Vanguard 3 results and other considerations that a factor of 10 improvement will be obtained. This means that the average errors of 1 to 3 percent now present in field charts and spherical harmonic descriptions should be reduced to 0.1 to 0.3 percent as a result of the survey.

MATHEMATICS↗
DOE OSTI2014

Intensity Modulated Proton Therapy for Craniospinal Irradiation: Organ-at-Risk Exposure and a Low-Gradient Junctioning Technique

Purpose: To compare field junction robustness and sparing of organs at risk (OARs) during craniospinal irradiation (CSI) using intensity modulated proton therapy (IMPT) to conventional passively scattered proton therapy (PSPT). Methods and Materials: Ten patients, 5 adult and 5 pediatric patients, previously treated with PSPT-based CSI were selected for comparison. Anterior oblique cranial fields, using a superior couch rotation, and posterior spinal fields were used for IMPT planning. To facilitate low-gradient field junctioning along the spine, the inverse-planning IMPT technique was divided into 3 stages. Dose indices describing target coverage and normal tissue dose, in silico error modeling, and film dosimetry were used to assess plan quality. Results: Field junction robustness along the spine was improved using the staged IMPT planning technique, reducing the worst case impact of a 4-mm setup error from 25% in PSPT to <5% of prescription dose. This was verified by film dosimetry for clinical delivery. Exclusive of thyroid dose in adult patients, IMPT plans demonstrated sparing of organs at risk as good or better than PSPT. Coverage of the cribriform plate for pediatric (V95% [percentage of volume of the target receiving at least 95% of the prescribed dose]; 87 ± 11 vs 92 ± 7) and adult (V95%; 94 ± 7 vs 100 ± 1) patients and the clinical target in pediatric (V95%; 98 ± 2 vs 100 ± 1) and adult (V95%; 100 ± 1 vs 100 ± 1) patients for PSPT and IMPT plans, respectively, were comparable or improved. For adult patients, IMPT target dose inhomogeneity was increased, as determined by heterogeneity index (HI) and inhomogeneity coefficient (IC). IMPT lowered maximum spinal cord dose, improved spinal dose homogeneity, and reduced exposure to other OARs. Conclusions: IMPT has the potential to improve CSI plan quality and the homogeneity of intrafractional dose at match lines. The IMPT approach developed may also simplify treatments and reduce workload per patient relative to PSPT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Evaluation of KDP Estimation Algorithm Performance in Rain Using a Known-Truth Framework

Accurate estimation of specific differential phase ( K DP ) is necessary for rain rate estimation, attenuation correction, and hydrometeor classification algorithms. There are numerous published methods to process polarimetric radar observations of propagation differential phase shift (Φ DP ) and estimate K DP , but the corresponding K DP estimate uncertainty is unquantified. This study provides guidance on how commonly used K DP estimation algorithms perform in various environments. Here, we create numerous synthetic (“true”) K DP profiles, integrate over them to obtain “smoothed” Φ DP , and then add noise typical of S-band operational weather radar measurements. Each algorithm is applied to our noisy Φ DP profiles and compared to the true K DP profile such that the errors and uncertainty are quantified. The synthetic K DP profiles are Gaussian in shape, which allows systematic variations in their magnitude and width to determine how each algorithm performs in smooth, slowly changing K DP profiles, as well as steep profiles. Results demonstrate that algorithm performance is dependent on the Φ DP field received. These results are further supported by an error analysis of each algorithm for two more complicated synthetic K DP profiles. Some K DP algorithms allow users to change various tuning parameters; a subset of these tuning parameters is tested to provide guidance on how changing these parameters impacts algorithm performance. We then provide evidence that our known-truth framework provides insight into algorithm performance in observed data through two case studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Suppressing Coherent Gauge Drift in Quantum Simulations

Simulations of field theories on noisy quantum computers must contend with errors introduced by that noise. For gauge theories, a large class of errors violate gauge symmetry, and thus may result in unphysical processes occurring in the simulation. We present a method, applicable to non-Abelian gauge theories, for suppressing coherent gauge drift errors through the repeated application of pseudorandom gauge transformation. In cases where the dominant errors are gauge-violating, we expect this method to be a practical way to improve the accuracy of NISQ-era simulations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2010

A GPS-Based Pitot-Static Calibration Method Using Global Output-Error Optimization

Pressure-based airspeed and altitude measurements for aircraft typically require calibration of the installed system to account for pressure sensing errors such as those due to local flow field effects. In some cases, calibration is used to meet requirements such as those specified in Federal Aviation Regulation Part 25. Several methods are used for in-flight pitot-static calibration including tower fly-by, pacer aircraft, and trailing cone methods. In the 1990 s, the introduction of satellite-based positioning systems to the civilian market enabled new inflight calibration methods based on accurate ground speed measurements provided by Global Positioning Systems (GPS). Use of GPS for airspeed calibration has many advantages such as accuracy, ease of portability (e.g. hand-held) and the flexibility of operating in airspace without the limitations of test range boundaries or ground telemetry support. The current research was motivated by the need for a rapid and statistically accurate method for in-flight calibration of pitot-static systems for remotely piloted, dynamically-scaled research aircraft. Current calibration methods were deemed not practical for this application because of confined test range size and limited flight time available for each sortie. A method was developed that uses high data rate measurements of static and total pressure, and GPSbased ground speed measurements to compute the pressure errors over a range of airspeed. The novel application of this approach is the use of system identification methods that rapidly compute optimal pressure error models with defined confidence intervals in nearreal time. This method has been demonstrated in flight tests and has shown 2- bounds of approximately 0.2 kts with an order of magnitude reduction in test time over other methods. As part of this experiment, a unique database of wind measurements was acquired concurrently with the flight experiments, for the purpose of experimental validation of the optimization method. This paper describes the GPS-based pitot-static calibration method developed for the AirSTAR research test-bed operated as part of the Integrated Resilient Aircraft Controls (IRAC) project in the NASA Aviation Safety Program (AvSP). A description of the method will be provided and results from recent flight tests will be shown to illustrate the performance and advantages of this approach. Discussion of maneuver requirements and data reduction will be included as well as potential applications.

Foster, John V.↗
DOE OSTI2025

Computational screening of fly ash zeolite sorbents for boric acid removal

In the United States, many impoundments at coal-fired power plants contain elevated contaminants like arsenic, boron, barium, and selenium. Zeolites synthesized from fly ash show promise as sorbents for these contaminants. However, optimizing sorption capacity is challenging due to numerous possible topologies, silicon to aluminum (Si/Al) ratios, and cation types. In this study, molecular simulations are used to design cationic zeolites for boric acid adsorption. Force field models based on quantum mechanical calculations (PBE + D2) for Na-, Ca-, Mn-, and Fe-exchanged chabazite and LTA are presented. The new D2FF force fields reproduce DFT energies with about half the error of UFF. Zeolite performance depends on Si/Al ratio and cation type, with low Si/Al ratio chabazite (CHA) and phillipsite (PHI) zeolite frameworks exchanged with Ca 2+ or Na + /Ca 2+ mixtures showing the highest adsorption. In conclusion, these findings suggest tailored fly ash-derived zeolites could provide effective boron removal from leachate ponds.

CCR impoundment↗