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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

Precipitable Water Variability Using SSM/I and GOES VAS Pathfinder Data Sets

Determining moisture variability for all weather scenes is critical to understanding the earth's hydrologic cycle and global climate changes. Remote sensing from geostationary satellites provides the necessary temporal and spatial resolutions necessary for global change studies. Due to antenna size constraints imposed with the use of microwave radiometers, geostationary satellites have carried instruments passively measuring radiation at infrared wavelengths or shorter. The shortfall of using infrared instruments in moisture studies lies in its inability to sense terrestrial radiation through clouds. Microwave emissions, on the other hand, are mostly unaffected by cloudy atmospheres. Land surface emissivity at microwave frequencies exhibit both high temporal and spatial variability thus confining moisture retrievals at microwave frequencies to over marine atmospheres (a near uniform cold background). This study intercompares the total column integrated water content Precipitable Water, (PW) as derived from both the Special Sensor Microwave Imager (SSM/I) and the Geostationary Operational Environmental Satellite (GOES) VISSR Atmospheric Sounder (VAS) pathfinder data sets. PW is a bulk parameter often used to quantify moisture variability and is important to understanding the earth's hydrologic cycle and climate system. This research has been spawned in an effort to combine two different algorithms which together can lead to a more comprehensive quantification of global water vapor. The approach taken here is to intercompare two independent PW retrieval algorithms and to validate the resultant retrievals against an existing data set, namely the European Center for Medium range Weather Forecasts (ECMWF) model analysis data.

Lerner, Jeffrey A.↗
NASA NTRS2017

The Mars Science Laboratory Curiosity Rover Mastcam Instruments: Preflight and In-Flight Calibration, Validation, and Data Archiving

The NASA Curiosity rover Mast Camera (Mastcam) system is a pair of fixed-focal length, multispectral, color CCD imagers mounted approximately 2 m above the surface on the rover's remote sensing mast, along with associated electronics and an onboard calibration target. The left Mastcam (M-34) has a 34 mm focal length, an instantaneous field of view (IFOV) of 0.22 mrad, and a FOV of 20 deg × 15 deg over the full 1648 × 1200 pixel span of its Kodak KAI-2020 CCD. The right Mastcam (M-100) has a 100 mm focal length, an IFOV of 0.074 mrad, and a FOV of 6.8 deg × 5.1 deg using the same detector. The cameras are separated by 24.2 cm on the mast, allowing stereo images to be obtained at the resolution of the M-34 camera. Each camera has an eight-position filter wheel, enabling it to take Bayer pattern red, green, and blue (RGB) 'true color' images, multispectral images in nine additional bands spanning approximately 400-1100 nm, and images of the Sun in two colors through neutral density-coated filters. An associated Digital Electronics Assembly provides command and data interfaces to the rover, 8 Gb of image storage per camera, 11 bit to 8 bit companding, JPEG compression, and acquisition of high-definition video. Here we describe the preflight and in-flight calibration of Mastcam images, the ways that they are being archived in the NASA Planetary Data System, and the ways that calibration refinements are being developed as the investigation progresses on Mars. We also provide some examples of data sets and analyses that help to validate the accuracy and precision of the calibration.

MSL Mastcam; quantitative multispectral↗
NASA NTRS2001

Validation of the galactic cosmic ray and geomagnetic transmission models

A very high-momentum resolution particle spectrometer called the Alpha Magnetic Spectrometer (AMS) was flown in the payload bay of the Space Shuttle in a 51.65 degrees x 380-km orbit during the last solar minimum. This spectrometer has provided the first high statistics data set for galactic cosmic radiation protons, and helium, as well as limited spectral data on carbon and oxygen nuclei in the International Space Station orbit. First measurements of the albedo protons at this inclination were also made. Because of the high-momentum resolution and high statistics, the data can be separated as a function of magnetic latitude. A related investigation, the balloon borne experiment with a superconducting solenoid spectrometer (BESS), has been flown from Lynn Lake, Canada and has also provided excellent high-resolution data on protons and helium. These two data sets have been used here to study the validity of two galactic cosmic ray models and the geomagnetic transmission function developed from the 1990 geomagnetic reference field model. The predictions of both the CREME96 and NASA/JSC models are in good agreement with the AMS data. The shape of the AMS measured albedo proton spectrum, up to 2 GeV, is in excellent agreement with the previous balloon and satellite observations. A new LIS spectrum was developed that is consistent with both previous and new BESS 3He observations. Because the astronaut radiation exposures onboard ISS will be highest around the time of the solar minimum, these AMS measurements and these models provide important benchmarks for future radiation studies. AMS-02 slated for launch in September 2003, will provide even better momentum resolution and higher statistics data. Published by Elsevier Science Ltd.

unmanned↗
DOE OSTI2025

Beyond Optimization: Exploring Novelty Discovery in Autonomous Experiments

Autonomous experiments (AEs) are transforming how scientific research is conducted by integrating artificial intelligence with automated experimental platforms. Current AEs primarily focus on the optimization of a predefined target; while accelerating this goal, such an approach limits the discovery of unexpected or unknown physical phenomena. Here, we introduce a novel framework, INS 2 ANE (Integrated Novelty Score−Strategic Autonomous Non-Smooth Exploration), to enhance the discovery of novel phenomena in autonomous microscopy experimentation. Our method integrates two key components: (1) a novelty scoring system that evaluates the uniqueness of experimental results and (2) a strategic sampling mechanism that promotes exploration of under-sampled regions even if they appear less promising by conventional criteria. We validate this approach on a preacquired data set with a known ground truth comprising of image−spectral pairs. We further implement the process on autonomous scanning probe microscopy experiments. INS 2 ANE significantly increases the diversity of explored phenomena in comparison to conventional optimization routines, enhancing the likelihood of discovering previously unobserved phenomena. These results demonstrate the potential for autonomous microscopy experiments to enhance the scientific discovery by navigating complex experimental spaces to uncover novel phenomena.

Materials↗
NASA NTRS1981

Satellite and correlative measurements of the stratospheric aerosol. II Comparison of measurements made by SAM II, dustsondes and airborne lidar

Results are shown from the first set of measurements conducted to validate extinction data from the Stratospheric Aerosol Measurement II (SAM II). Dustsonde-measured number density profiles and lidar-measured backscattering profiles for two days are converted to extinction profiles, and are shown to agree within their respective uncertainties at all heights above the tropopause. Near the tropopause, agreement depends on use of model size distributions with larger particles, having radii greater than 0.6 microns. The presence of such large particles is supported by measurements made elsewhere, is suggested by the in situ size distribution measurements reported, and is likely to have an important bearing on the radiative impact of the total stratospheric aerosol. It is concluded that the SAM II extinction data and uncertainty estimates are supported.

Russell, P. B.↗
NASA NTRS1985

Understanding the Radiant Scattering Behavior of Vegetated Scenes

Knowledge of the physics of the scattering behavior of vegetation will ultimately serve the remote sensing and earth science community in many ways. For example, it will provide: (1) insight and guidance in developing new extraction techniques of canopy characteristics, (2) a basis for better interpretation of off-nadir satellite and aircraft data, (3) a basis for defining specifications of future earth observing sensor systems, and (4) a basis for defining important aspects of physical and biological processes of the plant system. The overall objective of the three-year study is to improve our fundamental understanding of the dynamics of directional scattering properties of vegetation canopies through analysis of field data and model simulation data. The specific objectives are to: (1) collect directional reflectance data covering the entire exitance hemisphere for several common vegetation canopies with various geometric structure (both homogeneous and row crop structures), (2) develop a scene radiation model with a general mathematical framework which will treat 3-D variability in heterogeneous scenes and account for 3-D radiant interactions within the scene, (3) conduct validations of the model on collected data sets, and (4) test and expand proposed physical scattering mechanisms involved in reflectance distribution dynamics by analyzing both field and modeling data.

Kimes, D. S.↗
NASA NTRS1986

Detailed near-wake flowfield surveys with comparison to an Euler method of an aspect ratio 4 rectangular wing

An experimental investigation of the flowfield in the near-wake of an aspect ratio 4 rectangular wing was conducted, providing a complete detailed set of data for use in the validation of computational methods. An angle of attack of 8 degrees and two Reynolds numbers 530,000 and 391,000 were investigated using pitot and six-hole probes. In addition, two types of flow visualization were employed. The data presented includes contours of total pressure, mean velocity, flow angularity, and vorticity distribution data at five chordwise stations of the near-wake ranging from 0.167 to 5.00 chord lengths aft of the trailing edge. The experimental results were compared to the predicted results of a 2-D Euler numerical method. The results predicted by an Euler method failed to accurately define the flowfield. Tangential velocities remained relatively constant over the range of X/C considered though increased in angle of attack and Reynolds number did bring about corresponding increases. Axial velocities also increased with angle of attack and Reynolds number but showed greater sensitivity to increases in X/C. Graphic displays and contours of the total pressure data indicate that roll-up of the wing tip vortex is essentially complete one and one half chords downstream of the trailing edge.

Klinge, M. D.↗
NASA NTRS1992

Full-scale high angle-of-attack tests of an F/A-18

This paper presents an overview of high angle-of-attack tests of a full-scale F/A-18 in the 80- by 120-Foot Wind Tunnel of the National Full-Scale Aerodynamic Complex at NASA Ames Research Center at Moffett Field, California. A production aircraft was tested over an angle-of-attack range of 18 to 50 deg and at wind speeds of up to 100 knots. These tests had three primary test objectives. Pneumatic and mechanical forebody flow control devices were tested at full-scale and shown to produce significant yawing moments for lateral control of the aircraft at high angles of attack. Mass flow requirements for the pneumatic system were found to scale with freestream density and speed rather than freestream dynamic pressure. Detailed measurements of the pressures buffeting the vertical tail were made and spatial variations in the buffeting frequency were found. The LEX fence was found to have a significant effect on the frequency distribution on the outboard surface of the vertical fin. In addition to the above measurements, an extensive set of data was acquired for the validation of computational fluid dynamics codes and for comparison with flight test and small-scale wind tunnel test results.

Meyn, Larry A.↗
NASA NTRS1994

Data pre-processing: Stratospheric aerosol perturbing effect on the remote sensing of vegetation: Correction method for the composite NDVI after the Pinatubo eruption

An operational stratospheric correction scheme used after the Mount Pinatubo (Phillipines) eruption (Jun. 1991) is presented. The stratospheric aerosol distribution is assumed to be only variable with latitude. Each 9 days the latitudinal distribution of the optical thickness is computed by inverting radiances observed in the NOAA AVHRR channel 1 (0.63 micrometers) and channel 2 (0.83 micrometers) over the Pacific Ocean. This radiance data set is used to check the validity of model used for inversion by checking consistency of the optical thickness deduced from each channel as well as optical thickness deduced from different scattering angles. Using the optical thickness profile previously computed and radiative transfer code assuming Lambertian boundary condition, each pixel of channel 1 and 2 are corrected prior to computation of NDVI (Normalized Difference Vegetation Index). Comparison between corrected, non corrected, and years prior to Pinatubo eruption (1989 to 1990) NDVI composite, shows the necessity and the accuracy of the operational correction scheme.

Vermote, E.↗
NASA NTRS2003

Recent Experimental Results Related to Ejector Mode Studies of Rocket-Based Combined Cycle (RBCC) Engines

Contents include the folloving: 1. Motivation. Support NASA's 3d generation launch vehicle technology program. RBCC is promising candidate for 3d generation propulsion system. 2. Approach. Focus on ejector mode p3erformance (Mach 0-3). Perform testing on established flowpath geometry. Use conventional propulsion measurement techniques. Use advanced optical diagnostic techniques to measure local combustion gas properties. 3. Objectives. Gain physical understanding of detailing mixing and combustion phenomena. Establish an experimental data set for CFD code development and validation.

Cramer, J. M.↗
NASA NTRS2011

Development and Validation of a Multidisciplinary Tool for Accurate and Efficient Rotorcraft Noise Prediction (MUTE)

A physics-based, systematically coupled, multidisciplinary prediction tool (MUTE) for rotorcraft noise was developed and validated with a wide range of flight configurations and conditions. MUTE is an aggregation of multidisciplinary computational tools that accurately and efficiently model the physics of the source of rotorcraft noise, and predict the noise at far-field observer locations. It uses systematic coupling approaches among multiple disciplines including Computational Fluid Dynamics (CFD), Computational Structural Dynamics (CSD), and high fidelity acoustics. Within MUTE, advanced high-order CFD tools are used around the rotor blade to predict the transonic flow (shock wave) effects, which generate the high-speed impulsive noise. Predictions of the blade-vortex interaction noise in low speed flight are also improved by using the Particle Vortex Transport Method (PVTM), which preserves the wake flow details required for blade/wake and fuselage/wake interactions. The accuracy of the source noise prediction is further improved by utilizing a coupling approach between CFD and CSD, so that the effects of key structural dynamics, elastic blade deformations, and trim solutions are correctly represented in the analysis. The blade loading information and/or the flow field parameters around the rotor blade predicted by the CFD/CSD coupling approach are used to predict the acoustic signatures at far-field observer locations with a high-fidelity noise propagation code (WOPWOP3). The predicted results from the MUTE tool for rotor blade aerodynamic loading and far-field acoustic signatures are compared and validated with a variation of experimental data sets, such as UH60-A data, DNW test data and HART II test data.

Liu, Yi↗
NASA NTRS2018

Comparison of Space Radiation GCR Models to Recent AMS Data

This paper is the third in a series of comparisons of American (NASA) and Russian (ROSCOSMOS) space radiation calculations. The present work focuses on calculation of fluxes of galactic cosmic rays (GCR), which are a constant source of radiation that constitutes one of the major hazards during deep space exploration missions for both astronauts/cosmonauts and hardware. In this work, commonly used GCR models are compared with recently published measurements of cosmic ray Hydrogen, Helium, and the Boron-to-Carbon ratio from the Alpha Magnetic Spectrometer (AMS). All of the models were developed and calibrated prior to the publication of the AMS data, therefore this an opportunity to validate the models against an independent data set.

John W. Norbury↗
NASA NTRS2019

Comparison of Space Radiation GCR Models to AMS Heavy Ion Data

Galactic cosmic rays (GCR) are a constant source of radiation that constitutes one of the major hazards during deep space exploration missions for both astronauts and hardware. In this work, GCR models commonly used by the space radiation protection community are compared with recently published high-precision, high- resolution measurements of cosmic ray lithium, beryllium, boron, carbon, nitrogen, and oxygen fluxes along with their ratios (Li/B, Li/C, Li/O, Be/B, Be/C, Be/O, B/C, B/O, C/O, N/B, N/O) from the Alpha Magnetic Spectrometer (AMS). All of the models were developed and calibrated prior to the publication of this AMS data, therefore this is an opportunity to validate the models against an independent data set. This paper is a compliment to the previously published comparison of GCR models with AMS hydrogen, helium, and the boron-to-carbon ratio.

Whitman, Kathryn↗
NASA NTRS1990

FIRE Science Results 1989

FIRE (First ISCCP Regional Experiment) is a U.S. cloud-radiation research program formed in 1984 to increase the basic understanding of cirrus and marine stratocumulus cloud systems, to develop realistic parameterizations for these systems, and to validate and improve ISCCP cloud product retrievals. Presentations of results culminating the first 5 years of FIRE research activities were highlighted. The 1986 Cirrus Intensive Field Observations (IFO), the 1987 Marine Stratocumulus IFO, the Extended Time Observations (ETO), and modeling activities are described. Collaborative efforts involving the comparison of multiple data sets, incorporation of data measurements into modeling activities, validation of ISCCP cloud parameters, and development of parameterization schemes for General Circulation Models (GCMs) are described.

Mcdougal, David S.↗
NASA NTRS1984

First global analysis of SEASAT scatterometer winds and potential for meteorological research

The first global wind fields from SEASAT-A scatterometer (SASS) data were produced. Fifteen days of record are available on tape, with unique wind directions indicated for each observation. The methodology of the production of this data set is described, as well as the testing of its validity. A number of displays of the data, on large and small scales, analyzed and gridded, are provided.

Peteherych, S.↗
DOE OSTI2025

Validation of the DESI 2024 Lyα forest BAO analysis using synthetic datasets

The first year of data from the Dark Energy Spectroscopic Instrument (DESI) contains the largest set of Lyman-α (Lyα) forest spectra ever observed. This data, collected in the DESI Data Release 1 (DR1) sample, has been used to measure the Baryon Acoustic Oscillation (BAO) feature at redshift z = 2.33. In this work, we use a set of 150 synthetic realizations of DESI DR1 to validate the DESI 2024 Lyα forest BAO measurement presented in [1]. The synthetic data sets are based on Gaussian random fields using the log-normal approximation. We produce realistic synthetic DESI spectra that include all major contaminants affecting the Lyα forest. The synthetic data sets span a redshift range 1.8 < z < 3.8, and are analyzed using the same framework and pipeline used for the DESI 2024 Lyα forest BAO measurement. To measure BAO, we use both the Lyα auto-correlation and its cross-correlation with quasar positions. We use the mean of correlation functions from the set of DESI DR1 realizations to show that our model is able to recover unbiased measurements of the BAO position. We also fit each mock individually and study the population of BAO fits in order to validate BAO uncertainties and test our method for estimating the covariance matrix of the Lyα forest correlation functions. Finally, we discuss the implications of our results and identify the needs for the next generation of Lyα forest synthetic data sets, with the top priority being to simulate the effect of BAO broadening due to non-linear evolution.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

AI-Batt (Autonomous Identification of Battery Life Models) [SWR 21-36]

Autonomous Identification of Battery Life Models (AI-Batt) AI-Batt is a MATLAB code base for developing lifetime models for batteries from accelerated aging data. The code base provides many functions for processing, visualizing, and modeling battery aging data, making the data processing, exploration, and modeling workflow substantially faster. These tools are tailored for working with battery aging data sets, which usually consist of many separate time-series for each cell, with many test conditions and possible replicates at each condition, which makes it difficult to simply process or visualize the data set. Complex modeling tasks, such as cross-validation, sensitivity analysis, and uncertainty quantification have been implemented to enable thorough statistical investigation of model predictions. Additionally, several machine-learning algorithms are implemented to autonomously identify suitable models via symbolic regression. Data processing functions automatically cast data from the struct data type, which is commonly used to store experimental data, but is not an acceptable input for most algorithms, to the table data type, which can be easily used as input to any optimization algorithm. Also, the data can be separated into time-invariant and time-variant data tables, which is helpful for exploring the data set as well as developing separate models for time-variant and time-invariant aging mechanisms. For example, in aging tests with constant temperature, temperature is a time-invariant experimental condition. Visualization tools enable plotting of data, model fits, and model simulations possible with single-line function calls, empowering data exploration of complex data sets with both time-varying and time-invariant trends. Plots can be automatically generated for the whole data set, or separated by data group (groups of test replicates) or individual data series. Data points or data series can be automatically colored by the value of a variable with a variety of color maps, and model predictions can also be colored by the value of a fit statistic. Comparisons between data sets and the predictions/simulations of different models on the same data set can be easily plotted as well. Distributions of parameter values from bootstrap resampling can be plotted to visualize the reliability of parameter estimation, or determine any correlations between parameters. Modeling tools handle the complex task of creating and parsing symbolic equations for modeling battery lifetime. Equations are parsed to grab relevant data variables, parameter values, or specified sub-models for input into optimization, evaluation, or simulation functions. Models can be optimized locally (one set of parameters for each data series), bi-level (some parameters shared across the data set), or globally (single set of parameters for all data). Functions implementing symbolic regression algorithms help users to discover effective model equations, even in poorly sampled, high-dimensional data.

Smith, Kandler [National Renewable Energy Lab. (NR↗
NASA NTRS2012

Validation of MODIS FLH and In Situ Chlorophyll a from Tampa Bay, Florida (USA)

Satellite observation of phytoplankton concentration or chlorophyll-a (chla) is an important characteristic, critically integral to monitoring coastal water quality. However, the optical properties of estuarine and coastal waters are highly variable and complex and pose a great challenge for accurate analysis. Constituents such as suspended solids and dissolved organic matter and the overlapping and uncorrelated absorptions in the blue region of the spectrum renders the blue-green ratio algorithms for estimating chl-a inaccurate. Measurement of suninduced chlorophyll fluorescence, on the other hand, which utilizes the near infrared portion of the electromagnetic spectrum may, provide a better estimate of phytoplankton concentrations. While modelling and laboratory studies have illustrated both the utility and limitations of satellite algorithms based on the sun induced chlorophyll fluorescence signal, few have examined the empirical validity of these algorithms or compared their accuracy against bluegreen ratio algorithms . In an unprecedented analysis using a long term (2003-2011) in situ monitoring data set from Tampa Bay, Florida (USA), we assess the validity of the FLH product from the Moderate Resolution Imaging Spectrometer against a suite of water quality parameters taken in a variety of conditions throughout this large optically complex estuarine system. . Overall, the results show a 106% increase in the validity of chla concentration estimation using FLH over the standard chla estimate from the blue-green OC3M algorithm. Additionally, a systematic analysis of sampling sites throughout the bay is undertaken to understand how the FLH product responds to varying conditions in the estuary and correlations are conducted to see how the relationships between satellite FLH and in situ chlorophyll-a change with depth, distance from shore, from structures like bridges, and nutrient concentrations and turbidity. Such analysis illustrates that the correlations between FLH and in situ chla measurements increases with increasing distance between monitoring sites and structures like bridges and shore. Due probably to confounding factors, expected improvement in the FLH- chla relationship was not clearly noted when increasing depth and distance from shore alone (not including bridges). Correlations between turbidity and nutrient concentrations are discussed further and principle component analyses are employed to address the relationships between the multivariate data sets. A thorough understanding of how satellite FLH algorithms relate to in situ water quality parameters will enhance our understanding of how MODIS s global FLH algorithm can be used empirically to monitor coastal waters worldwide.

Fischer, Andrew↗