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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Dynamic Analyses of the Proposed Habitable Exoplanet Astrophysics Facility

The proposed Habitable Exoplanet (HabEx) astrophysics facility is one of four large such facilities being proposed to the 2020 decadal. It is a large telescope that is sensitive to ultraviolet, optical, and near-infrared photons. The proposed design’s overall length is on the order of 17.2 m and its maximum cross section is on the order of 5.25 X 5.25 m. The primary mirror is 4 m in diameter. A transient dynamic analysis was performed to estimate the order of magnitude of ring down time after moving the telescope and pointing at a new target for science planning purposes. Without uncertainty factors, results from a simple re-pointing maneuver indicate that primary to secondary mirror LOS errors are on the order of 10-4 pico-m after 5 minutes. Also, a frequency response analysis was performed to predict the impact of planned micro-thruster vibrations on required stability. Based on provided noise level associated with the micro-thrusters and loading assumptions and without uncertainty factors, the assessed vibrations do not impact predicted performance requirements.

Knight, J. Brent↗
NASA NTRS2016

Benefit of Modeling the Observation Error in a Data Assimilation Framework Using Vegetation Information Obtained From Passive Based Microwave Data

A primary operational goal of the United States Department of Agriculture (USDA) is to improve foreign market access for U.S. agricultural products. A large fraction of this crop condition assessment is based on satellite imagery and ground data analysis. The baseline soil moisture estimates that are currently used for this analysis are based on output from the modified Palmer two-layer soil moisture model, updated to assimilate near-real time observations derived from the Soil Moisture Ocean Salinity (SMOS) satellite. The current data assimilation system is based on a 1-D Ensemble Kalman Filter approach, where the observation error is modeled as a function of vegetation density. This allows for offsetting errors in the soil moisture retrievals. The observation error is currently adjusted using Normalized Difference Vegetation Index (NDVI) climatology. In this paper we explore the possibility of utilizing microwave-based vegetation optical depth instead.

Vegetation↗
NASA NTRS1991

Using a focal-plane array to estimate antenna pointing errors

The use of extra collecting horns in the focal plane of an antenna as a means of determining the Direction of Arrival (DOA) of the signal impinging on it, provided it is within the antenna beam, is considered. Our analysis yields a relatively simple algorithm to extract the DOA from the horns' outputs. An algorithm which, in effect, measures the thermal noise of the horns' signals and determines its effect on the uncertainty of the extracted DOA parameters is developed. Both algorithms were implemented in software and tested in simulated data. Based on these tests, it is concluded that this is a viable approach to the DOA determination. Though the results obtained are of general applicability, the particular motivation for the present work is their application to the pointing of a mechanically deformed antenna. It is anticipated that the pointing algorithm developed for a deformed antenna could be obtained as a small perturbation of the algorithm developed for an undeformed antenna. In this context, it should be pointed out that, with a deformed antenna, the array of horns and its associated circuitry constitute the main part of the deformation-compensation system. In this case, the pointing system proposed may be viewed as an additional task carried out by the deformation-compensation hardware.

Zohar, S.↗
NASA NTRS2011

Estimation of Smoothing Error in SBUV Profile and Total Ozone Retrieval

Data from the Nimbus-4, Nimbus-7 Solar Backscatter Ultra Violet (SBUV) and seven of the NOAA series of SBUV/2 instruments spanning 41 years are being reprocessed using V8.6 algorithm. The data are scheduled to be released by the end of August 2011. An important focus of the new algorithm is to estimate various sources of errors in the SBUV profiles and total ozone retrievals. We discuss here the smoothing errors that describe the components of the profile variability that the SBUV observing system can not measure. The SBUV(/2) instruments have a vertical resolution of 5 km in the middle stratosphere, decreasing to 8 to 10 km below the ozone peak and above 0.5 hPa. To estimate the smoothing effect of the SBUV algorithm, the actual statistics of the fine vertical structure of ozone profiles must be known. The covariance matrix of the ensemble of measured ozone profiles with the high vertical resolution would be a formal representation of the actual ozone variability. We merged the MLS (version 3) and sonde ozone profiles to calculate the covariance matrix, which in general case, for single profile retrieval, might be a function of the latitude and month. Using the averaging kernels of the SBUV(/2) measurements and calculated total covariance matrix one can estimate the smoothing errors for the SBUV ozone profiles. A method to estimate the smoothing effect of the SBUV algorithm is described and the covariance matrixes and averaging kernels are provided along with the SBUV(/2) ozone profiles. The magnitude of the smoothing error varies with altitude, latitude, season and solar zenith angle. The analysis of the smoothing errors, based on the SBUV(/2) monthly zonal mean time series, shows that the largest smoothing errors were detected in the troposphere and might be as large as 15-20% and rapidly decrease with the altitude. In the stratosphere above 40 hPa the smoothing errors are less than 5% and between 10 and 1 hPa the smoothing errors are on the order of 1%. We validate our estimated smoothing errors by comparing the SBUV ozone profiles with other ozone profiling sensors.

Kramarova, N. A.↗
DOE OSTI2023

Towards operational atmospheric correction of airborne hyperspectral imaging spectroscopy: Algorithm evaluation, key parameter analysis, and machine learning emulators

Atmospheric correction of airborne hyperspectral imaging spectroscopy (AHIS) to obtain high-quality surface reflectance is the prerequisite for remote sensing applications. Over the last decades, different atmospheric correction methods have been developed based on radiative transfer models (RTMs), however, the relative performances of different algorithms are unclear. Automated operational atmospheric correction methods to process large-volume AHIS data in a high-accurate and high-throughput manner are still lacking. Therefore, this study proposed an operational atmospheric correction pipeline for deriving surface reflectance from AHIS data. To ensure the accuracy and efficiency of the pipeline, we focused on three specific aspects: (1) selecting a suitable RTM for the development of atmospheric lookup tables (LUTs) by comparing the commercial MODerate resolution atmospheric TRANsmission (MODTRAN) and open-sourced Library for Radiative TRANsfer (LibRadTRAN) models, where the widely-used software, Atmospheric/Topographic Correction for Airborne Imagery (ATCOR), was used as benchmarks; (2) identifying key atmospheric correction parameters and determining suitable sources for parameter retrievals including AHIS, Moderate Resolution Imaging Spectroradiometer (MODIS), and AErosol RObotic NETwork (AERONET); and (3) testing the performance of using machine learning emulators to speed up the RTM-based atmospheric correction. Results indicate that (1) atmospheric correction based on MODTRAN LUTs can produce surface reflectance accurately with mean absolute errors < 0.05 and cosine similarities > 0.98 compared to field measurements, which is comparable to the software ATCOR and slightly outperforms the LibRadTRAN LUTs; (2) sobol global sensitivity analysis demonstrates that in the atmospheric correction, visibility and water vapor are two key parameters that can be accurately derived from AHIS in contrast to MODIS or AERONET data; and (3) Random Forest emulators can produce accurate estimations of surface reflectance with mean absolute errors < 0.03 and cosine similarities > 0.98 for higher processing efficiency and determine a suitable set of wavelengths for retrieving atmospheric visibility and water vapor. In conclusion, the proposed atmospheric correction pipeline also improved the four-stream radiative transfer theory for airborne applications by considering adjacent effects from airborne surrounding pixels and can also be applied for atmospheric correction of hyperspectral data from spaceborne missions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

HPC Network Simulation Tuning via Automatic Extraction of Hardware Parameters

Popular HPC network interconnection simulators such as SST/macro provide a variety of configurable parameters to explore the design space of hardware components such as network interface cards (NIC), switches, and links among them. While such knobs provide flexibility to explore design trade-offs for novel hardware, manually configuring simulations for matching configurations of the existing hardware to focus on topology exploration can be cumbersome and error-prone, leading to widely inaccurate simulations. This challenge is compounded when specifications of various (proprietary) technologies are not readily available or intentionally omitted. In this work, we propose a framework to autotune the multiple network models’ simulation configurations within SST/macro using Tree-structured Parzen Estimator-based Bayesian optimization to observe the effect on simulation accuracy across different message regimes. These regimes consist of small to large message sizes and latency to bandwidth-bound messages. We provide a detailed analysis of the simulation error for four representative HPC systems. Our Bayesian optimization based autotuning framework for network models achieves a maximum of 5x improvement in accuracy over best-effort manual configurations based on available hardware specifications.

Simulation, autotuning↗
DOE OSTI2023

Performance of methods for SARS-CoV-2 variant detection and abundance estimation within mixed population samples

The accurate identification of SARS-CoV-2 (SC2) variants and estimation of their abundance in mixed population samples (e.g., air or wastewater) is imperative for successful surveillance of community level trends. Assessing the performance of SC2 variant composition estimators (VCEs) should improve our confidence in public health decision making. Here, we introduce a linear regression based VCE and compare its performance to four other VCEs: two re-purposed DNA sequence read classifiers (Kallisto and Kraken2), a maximum-likelihood based method (Lineage deComposition for Sars-Cov-2 pooled samples (LCS)), and a regression based method (Freyja). We simulated DNA sequence datasets of known variant composition from both Illumina and Oxford Nanopore Technologies (ONT) platforms and assessed the performance of each VCE. We also evaluated VCEs performance using publicly available empirical wastewater samples collected for SC2 surveillance efforts. Bioinformatic analyses were performed with a custom NextFlow workflow (C-WAP, CFSAN Wastewater Analysis Pipeline). Relative root mean squared error (RRMSE) was used as a measure of performance with respect to the known abundance and concordance correlation coefficient (CCC) was used to measure agreement between pairs of estimators. Based on our results from simulated data, Kallisto was the most accurate estimator as it had the lowest RRMSE, followed by Freyja. Kallisto and Freyja had the most similar predictions, reflected by the highest CCC metrics. We also found that accuracy was platform and amplicon panel dependent. For example, the accuracy of Freyja was significantly higher with Illumina data compared to ONT data; performance of Kallisto was best with ARTICv4. However, when analyzing empirical data there was poor agreement among methods and variations in the number of variants detected (e.g., Freyja ARTICv4 had a mean of 2.2 variants while Kallisto ARTICv4 had a mean of 10.1 variants). This work provides an understanding of the differences in performance of a number of VCEs and how accurate they are in capturing the relative abundance of SC2 variants within a mixed sample (e.g., wastewater). Such information should help officials gauge the confidence they can have in such data for informing public health decisions.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1992

Analysis of a spatial tracking subsystem for optical communications

Spatial tracking plays a very critical role in designing optical communication systems because of the small angular beamwidth associated with the optical signal. One possible solution for spatial tracking is to use a nutating mirror which dithers the incoming beam at a rate much higher than the mechanical disturbances. A power detector then senses the change in detected power as the signal is reflected off the nutating mirror. This signal is then correlated with the nutator driver signals to obtain estimates of the azimuth and elevation tracking signals to control the fast scanning mirrors. A theoretical analysis is performed for a spatial tracking system using a nutator disturbed by shot noise and mechanical vibrations. Contributions of shot noise and mechanical vibrations to the total tracking error variance are derived. Given the vibration spectrum and the expected signal power, there exists an optimal amplitude for the nutation which optimizes the receiver performance. The expected performance of a nutator based system is estimated based on the choice of nutation amplitude.

Win, Moe Z.↗
NASA NTRS1992

Signal processing for airborne doppler radar detection of hazardous wind shear as applied to NASA 1991 radar flight experiment data

Radar data collected during the 1991 NASA flight tests have been selectively analyzed to support research directed at developing both improved as well as new algorithms for detecting hazardous low-altitude windshear. Analysis of aircraft attitude data from several flights indicated that platform stability bandwidths were small compared to the data rate bandwidths which should support an assumption that radar returns can be treated as short time stationary. Various approaches at detection of weather returns in the presence of ground clutter are being investigated. Non-coventional clutter rejection through spectrum mode tracking and classification algorithms is a subject of continuing research. Based upon autoregressive modeling of the radar return time sequence, this approach may offer an alternative to overcome errors in conventional pulse-pair estimates. Adaptive filtering is being evaluated as a means of rejecting clutter with emphasis on low signal-to-clutter ratio situations, particularly in the presence of discrete clutter interference. An analysis of out-of-range clutter returns is included to illustrate effects of ground clutter interference due to range aliasing for aircraft on final approach. Data are presented to indicate how aircraft groundspeed might be corrected from the radar data as well as point to an observed problem of groundspeed estimate bias variation with radar antenna scan angle. A description of how recorded clutter return data are mixed with simulated weather returns is included. This enables the researcher to run controlled experiments to test signal processing algorithms. In the summary research efforts involving improved modelling of radar ground clutter returns and a Bayesian approach at hazard factor estimation are mentioned.

Baxa, Ernest G., Jr.↗
DOE OSTI2025

CFDverify

Estimating the discretization error of computational fluid dynamics (CFD) or other scientific codes as part of solution verification is often a non-trivial part of the analysis process. Methods can be complicated and may include assumptions/qualifications that need to be checked during analysis. CFD analysts, therefore, are likely to make errors when trying to conduct this necessary analysis on their own in not knowing about the best method for their problem, not correctly implementing a method, or in not have diagnostic tools to determine if the method was correctly applied.

Weinmeister, Justin [Oak Ridge National Laboratory↗
DOE OSTI2022

A coupled ground heat flux–surface energy balance model of evaporation using thermal remote sensing observations

Abstract. One of the major undetermined problems in evaporation (ET) retrieval using thermal infrared remote sensing is the lack of a physically based ground heat flux (G) model and its integration within the surface energy balance (SEB) equation. Here, we present a novel approach based on coupling a thermal inertia (TI)-based mechanistic G model with an analytical surface energy balance model, Surface Temperature Initiated Closure (STIC, version STIC1.2). The coupled model is named STIC-TI. The model is driven by noon–night (13:30 and 01:30 local time) land surface temperature, surface albedo, and a vegetation index from MODIS Aqua in conjunction with a clear-sky net radiation sub-model and ancillary meteorological information. SEB flux estimates from STIC-TI were evaluated with respect to the in situ fluxes from eddy covariance measurements in diverse ecosystems of contrasting aridity in both the Northern Hemisphere and Southern Hemisphere. Sensitivity analysis revealed substantial sensitivity of STIC-TI-derived fluxes due to the land surface temperature uncertainty. An evaluation of noontime G (Gi) estimates showed 12 %–21 % error across six flux tower sites, and a comparison between STIC-TI versus empirical G models also revealed the substantially better performance of the former. While the instantaneous noontime net radiation (RNi) and latent heat flux (LEi) were overestimated (15 % and 25 %), sensible heat flux (Hi) was underestimated (22 %). Overestimation (underestimation) of LEi (Hi) was associated with the overestimation of net available energy (RNi−Gi) and use of unclosed surface energy balance flux measurements in LEi (Hi) validation. The mean percent deviations in Gi and Hi estimates were found to be strongly correlated with satellite day–night view angle difference in parabolic and linear pattern, and a relatively weak correlation was found between day–night view angle difference versus LEi deviation. Findings from this parameter-sparse coupled G–ET model can make a valuable contribution to mapping and monitoring the spatiotemporal variability of ecosystem water stress and evaporation using noon–night thermal infrared observations from future Earth observation satellite missions such as TRISHNA, LSTM, and SBG.

Bhattacharya, Bimal K.↗
DOE OSTI2022

Quantifying uncertainty in Pareto estimates of global lake area

This software contains the code for Bayesian uncertainty analysis of global lake area. Computed uncertainties are compared against more conventional estimation using lake size-abundance distributions. Routines are included to explore sensitivity to observational errors and ad-hoc "censoring" strategies.

Stachelek, Jemma↗
NASA NTRS1975

Error magnitude estimation in model-reference adaptive systems

A second order approximation is derived from a linearized error characteristic equation for Lyapunov designed model-reference adaptive systems and is used to estimate the maximum error between the model and plant states, and the time to reach this peak following a plant perturbation. The results are applicable in the analysis of plants containing magnitude-dependent nonlinearities.

Colburn, B. K.↗
NASA NTRS1996

Coherent Lidar Design and Performance Verification

This final report summarizes the investigative results from the 3 complete years of funding and corresponding publications are listed. The first year saw the verification of beam alignment for coherent Doppler lidar in space by using the surface return. The second year saw the analysis and computerized simulation of using heterodyne efficiency as an absolute measure of performance of coherent Doppler lidar. A new method was proposed to determine the estimation error for Doppler lidar wind measurements without the need for an independent wind measurement. Coherent Doppler lidar signal covariance, including wind shear and turbulence, was derived and calculated for typical atmospheric conditions. The effects of wind turbulence defined by Kolmogorov spatial statistics were investigated theoretically and with simulations. The third year saw the performance of coherent Doppler lidar in the weak signal regime determined by computer simulations using the best velocity estimators. Improved algorithms for extracting the performance of velocity estimators with wind turbulence included were also produced.

Frehlich, Rod↗
NASA NTRS1994

Spectroscopy of Solid State Laser Materials

We retrieved the vertical distribution of ozone from a series 0.005-0.013/cm resolution infrared solar spectra recorded with the McMath Fourier Transform spectrometer at the Kitt Peak National Solar Observatory. The analysis is based on a multi-layer line-by-line forward model and a semi-empirical version of the optimal estimation inversion method by Rodgers. The 1002.6-1003.2/cm spectral interval has been selected for the analysis on the basis of synthetic spectrum calculations. The characterization and error analysis of the method have been performed. It was shown that for the Kitt Peak spectral resolution and typical signal-to-noise ratio (greater than or equal to 100) the retrieval is stable, with the vertical resolution of approximately 5 km attainable near the surface degrading to approximately 10 km in the stratosphere. Spectra recorded from 1980 through 1993 have been analyzed. The retrieved total ozone and vertical profiles have been compared with total ozone mapping spectrometer (TOMS) satellite total columns for the location and dates of the Kitt Peak Measurements and about 100 ozone ozonesoundings and Brewer total column measurements from Palestine, Texas, from 1979 to 1985. The total ozone measurements agree to +/- 2%. The retrieved profiles reproduce the seasonally averaged variations with altitude, including the ozone spring maximum and fall minimum measured by Palestine sondes, but up to 15% differences in the absolute values are obtained.

Buoncristiani, A. M.↗
NASA NTRS2000

Systems Engineering Programmatic Estimation Using Technology Variance

Unique and innovative system programmatic estimation is conducted using the variance of the packaged technologies. Covariance analysis is performed on the subsystems and components comprising the system of interest. Technological "return" and "variation" parameters are estimated. These parameters are combined with the model error to arrive at a measure of system development stability. The resulting estimates provide valuable information concerning the potential cost growth of the system under development.

Mog, Robert A.↗
NASA NTRS2000

Systems Engineering Programmatic Estimation Using Technology Variance

Unique and innovative system programmatic estimation is conducted using the variance of the packaged technologies. Covariance analysis is performed oil the subsystems and components comprising the system of interest. Technological "returns" and "variation" parameters, are estimated. These parameters are combined with the model error to arrive at a measure of system development stability. The resulting estimates provide valuable information concerning the potential cost growth of the system under development.

Mog, Robert A.↗
NASA NTRS2002

Adjoint-Based, Three-Dimensional Error Prediction and Grid Adaptation

Engineering computational fluid dynamics (CFD) analysis and design applications focus on output functions (e.g., lift, drag). Errors in these output functions are generally unknown and conservatively accurate solutions may be computed. Computable error estimates can offer the possibility to minimize computational work for a prescribed error tolerance. Such an estimate can be computed by solving the flow equations and the linear adjoint problem for the functional of interest. The computational mesh can be modified to minimize the uncertainty of a computed error estimate. This robust mesh-adaptation procedure automatically terminates when the simulation is within a user specified error tolerance. This procedure for estimating and adapting to error in a functional is demonstrated for three-dimensional Euler problems. An adaptive mesh procedure that links to a Computer Aided Design (CAD) surface representation is demonstrated for wing, wing-body, and extruded high lift airfoil configurations. The error estimation and adaptation procedure yielded corrected functions that are as accurate as functions calculated on uniformly refined grids with ten times as many grid points.

Park, Michael A.↗