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NASA NTRSDate not supplied

CFD Validation Study of a Hypersonic Cone-Slice-Flap Variable Geometry Configuration

Model validation is the process of determining the degree of accuracy between physical reality and the model. The result of model validation can either be used to improve the model through calibration or quantify the model-form uncertainty. This work focuses on providing the model-form uncertainty through an area metric for a hypersonic cone-slice-flap variable geometry configuration given uncertainty in both the simulation and experimental data. For a variable geometry, performing uncertainty quantification to capture the model-form uncertainty on every configuration is computationally challenging. This work lays out a procedure that can give an accurate representation of the model-form uncertainty using a small number of high-fidelity runs and many low-fidelity runs on multiple configurations. Running this comparison provides a quantifiable measurement for the accuracy of each turbulence model for this type of design. The high-fidelity CFD solver used was VULCAN-CFD and the low-fidelity results came from Cart3D. The experimental data came from the 20-Inch Mach 6 Tunnel located at NASA Langley Research Center. The present work showed that the turbulence simulation overpredicted the drag and lift coefficient, while underpredicting the pitching moment coefficient. The model-form uncertainty estimate resulted up to a 13.6% change in the total uncertainty for the drag coefficient, up to a 57.4% change in total uncertainty for the lift coefficient, and up to a 100% change in total uncertainty for the pitching moment coefficient.

Laura White↗

NASA NTRS1994

Measurement of the fluorescence of crop residues: A tool for controlling soil erosion

Management of crop residues, the portion of a crop left in the field after harvest, is an important conservation practice for minimizing soil erosion and for improving water quality. Quantification of crop residue cover is required to evaluate the effectiveness of conservation tillage practices. Methods are needed to quantify residue cover that are rapid, accurate, and objective. The fluorescence of crop residue was found to be a broadband phenomenon with emission maxima at 420 to 495 nm for excitations of 350 to 420 nm. Soils had low intensity broadband emissions over the 400 to 690 nm region for excitations of 300 to 600 nm. The range of relative fluorescence intensities for the crop residues was much greater than the fluorescence observed of the soils. As the crop residues decompose their blue fluorescence values approach the fluorescence of the soil. Fluorescence techniques are concluded to be less ambiguous and better suited for discriminating crop residues and soils than reflectance methods. If properly implemented, fluorescence techniques can be used to quantify, not only crop residue cover, but also photosynthetic efficiency in the field.

Daughtry, C. S. T.↗

NASA NTRS1977

Fundamental Analysis of the Linear Multiple Regression Technique for Quantification of Water Quality Parameters from Remote Sensing Data

Constituents with linear radiance gradients with concentration may be quantified from signals which contain nonlinear atmospheric and surface reflection effects for both homogeneous and non-homogeneous water bodies provided accurate data can be obtained and nonlinearities are constant with wavelength. Statistical parameters must be used which give an indication of bias as well as total squared error to insure that an equation with an optimum combination of bands is selected. It is concluded that the effect of error in upwelled radiance measurements is to reduce the accuracy of the least square fitting process and to increase the number of points required to obtain a satisfactory fit. The problem of obtaining a multiple regression equation that is extremely sensitive to error is discussed.

Whitlock, C. H., III↗

NASA NTRS2017

Uncertainty Aware Structural Topology Optimization Via a Stochastic Reduced Order Model Approach

This work presents a stochastic reduced order modeling strategy for the quantification and propagation of uncertainties in topology optimization. Uncertainty aware optimization problems can be computationally complex due to the substantial number of model evaluations that are necessary to accurately quantify and propagate uncertainties. This computational complexity is greatly magnified if a high-fidelity, physics-based numerical model is used for the topology optimization calculations. Stochastic reduced order model (SROM) methods are applied here to effectively 1) alleviate the prohibitive computational cost associated with an uncertainty aware topology optimization problem; and 2) quantify and propagate the inherent uncertainties due to design imperfections. A generic SROM framework that transforms the uncertainty aware, stochastic topology optimization problem into a deterministic optimization problem that relies only on independent calls to a deterministic numerical model is presented. This approach facilitates the use of existing optimization and modeling tools to accurately solve the uncertainty aware topology optimization problems in a fraction of the computational demand required by Monte Carlo methods. Finally, an example in structural topology optimization is presented to demonstrate the effectiveness of the proposed uncertainty aware structural topology optimization approach.

Aguilo, Miguel A.↗

NASA NTRS1974

An evaluation of contractor projected and actual costs

GSFC contractors with cost-plus contracts provide cost estimates for each of the next four quarters on a quarterly basis. Actual expenditures over a two-year period were compared to the estimates, and the data were sorted in different ways to answer several questions and give quantification to observations, such as how much does the accuracy of estimates degrade as they are made further into the future? Are estimates made for small dollar amounts more accurate than for large dollar estimates? Other government agencies and private companies with cost-plus contracts may be interested in this analysis as potential methods of contract management for their organizations. It provides them with the different methods one organization is beginning to use to control costs.

Kwiatkowski, K. A.↗

NASA NTRSDate not supplied

Illuminating Albedo: Using MOSAiC Data to Assess the CERES Cloud Radiative Swath (CRS) Albedo Quantification Process

Increasing surface and lower tropospheric air temperatures as a result of rising greenhouse gases are expected to be most pronounced over the Arctic. Such rapid changes alter the surface climate of the region, and impacts can be observed atmospherically, oceanographically, and biogeophysically. Accurately quantifying the impact of decreasing surface albedo on the surface energy budget with satellite observations alone is complicated by a lack of shortwave radiation during winter and seasonal/spatial heterogeneity of surface type and associated spectral albedo. NASA’s Clouds and the Earth’s Radiant Energy System (CERES) project features the Cloud Radiative Swath (CRS) product, which builds upon the Single Scanner Footprint (SSF) product by using the NASA Langley Fu-Liou radiative transfer model to calculate a robust and high-quality array of surface and atmospheric radiative fluxes on an instantaneous, footprint-level scale. This study aims to use MOSAiC and CRS data to illuminate potential uncertainties in the CERES albedo production process, with goals of determining 1) spectral albedo under clear sky conditions when stratified by ice concentration, 2) the uncertainty associated with CERES surface albedo “history maps” when compared against observations captured during MOSAiC, and 3) the magnitude of variation between meteorological inputs compared to those from MOSAiC.

Emily Monroe↗

NASA NTRS2020

Battery Health Quantification for TDRS Spacecraft by Using Signature Discriminability Measurement

The NASA/GSFC Space Network Project Office (SN) currently operates a constellation of ten geosynchronous TDRS spacecraft launched over the past 30 years. The SN project collects up to 16.5 Gigabytes of telemetry every month. Generally, the spacecraft health and functionality are obtained by the use of real-time telemetry data for the multiple spacecraft subsystems, which are transmitted to the main ground station at the White Sands Complex in Las Cruces, NM. Recently, the SN has instituted a program of Big Data to analyze the large amounts of data using a variety of tools including Machine Learning, Artificial Intelligence, development of training sets, and a variety of mathematical modeling tools. The goal is to improve spacecraft management and obtain a more accurate prediction of the spacecraft end of life. The combination of these efforts with those of the Aerospace Corporation, which has a contract with the SN to produce yearly reliability estimates for the TDRS fleet, will be performed. This paper presents a new concept called telemetry quality quantification (TQQ) and discusses the progress that has been made in battery performance estimation for the second-generation TDRS spacecraft using a signature discriminability measures (SDM) algorithm combined with the Aerospace Corp. battery life estimation models. This activity is important because many of the TDRS fleet of spacecraft have exceeded their on-orbit design lifetime and, therefore, NASA must carefully manage the spacecraft to continue operations while avoiding an end-of-mission scenario that leaves a non-functioning spacecraft in geosynchronous orbit.

Ma, Kenneth Y.↗

NASA NTRS2015

Plasma Perturbations in High-Speed Probing of Hall Thruster Discharge Chambers: Quantification and Mitigation

An experimental investigation is presented to quantify the effect of high-speed probing on the plasma parameters inside the discharge chamber of a 6-kW Hall thruster. Understanding the nature of these perturbations is of significant interest given the importance of accurate plasma measurements for characterizing thruster operation. An array of diagnostics including a high-speed camera and embedded wall probes is employed to examine in real time the changes in electron temperature and plasma potential induced by inserting a high-speed reciprocating Langmuir probe into the discharge chamber. It is found that the perturbations onset when the scanning probe is downstream of the electron temperature peak, and that along channel centerline, the perturbations are best characterized as a downstream shift of plasma parameters by 15-20% the length of the discharge chamber. A parametric study is performed to investigate techniques to mitigate the observed probe perturbations including varying probe speed, probe location, and operating conditions. It is found that the perturbations largely disappear when the thruster is operated at low power and low discharge voltage. The results of this mitigation study are discussed in the context of recommended methods for generating unperturbed measurements of the discharge chamber plasma.

Jorns, Benjamin A.↗

NASA NTRS2003

The Interaction Between an Insoluble Particle and an Advancing Solid/Liquid Interface: Micro-Gravity Experiments and Theoretical Developments

The interaction of an insoluble particle with an advancing solid/liquid interface (SLI) has been a subject of investigation for the past four decades. While the original interest stemmed from geology applications (e.g., frost heaving in soil), researchers soon realized that the complex science associated with such an interaction is relevant to many other scientific fields encompassing metal matrix composites (MMCs), high temperature superconductors, inclusion management in steel, growth of monotectics, and preservation of biological cells. During solidification of a liquid containing an insoluble particle, three distinct interaction phenomena have been experimentally observed: instantaneous engulfment of the particle, continuous pushing, and particle pushing followed by engulfment. It was also observed that for given experimental conditions and particle size there is a critical solidification velocity, V(sub cr), above which a particle is engulfed. During solidification of MMCs pushing leads to particle agglomeration at the grain boundaries and this has detrimental effects on mechanical properties of the casting. Consequently, the process must be designed for instantaneous engulfment to occur. This implies the development of accurate theoretical models to predict V(sub cr), and perform benchmark experiments to test the validity of such models. Although considerable progress has been made in understanding the pushing/engulfment phenomenon (PEP), its quantification in terms of the material and processing parameters remains a focus of research. Since natural convection currents occurring during terrestrial solidification experiments complicate the study of PEP, execution of experiments on the International Space Station (ISS) has been approved and funded by NASA. Extensive terrestrial (1g) experiments and preliminary micro-gravity (mu g) experiments on two space shuttle missions have been conducted in preparation for future experiments on the ISS. The investigated systems included metal-ceramic particles (pure aluminum - zirconia particles) and transparent organic - non-reactive particles (succinonitrile - polystyrene and biphenyl - glass). This paper will discuss the experimental results obtained in both lg and pg conditions and the influence of the natural convection on V(sub cr). A summary of past mathematical models and our recent theoretical developments will also be presented to explain the experimentally observed particle/SLI interaction.

Catalina, Adrian V.↗

NASA NTRS2015

Probabilistic Fatigue Damage Prognosis Using a Surrogate Model Trained Via 3D Finite Element Analysis

Utilizing inverse uncertainty quantification techniques, structural health monitoring can be integrated with damage progression models to form probabilistic predictions of a structure's remaining useful life. However, damage evolution in realistic structures is physically complex. Accurately representing this behavior requires high-fidelity models which are typically computationally prohibitive. In the present work, a high-fidelity finite element model is represented by a surrogate model, reducing computation times. The new approach is used with damage diagnosis data to form a probabilistic prediction of remaining useful life for a test specimen under mixed-mode conditions.

Leser, Patrick E.↗

NASA NTRS2000

Passive, Direct-Read Monitoring System for Selective Detection and Quantification of Hydrogen Chloride

Monitoring the exposure of an employee to hydrogen chloride or hydrochloric acid in the presence of other acids has been a challenge to the industrial hygiene community. The capability of a device to differentiate the levels of acid vapors would allow for more accurate determinations of exposure and therefore improved occupational health. In this work, a selective direct-read colorimetric badge system was validated for Short Term Exposure Limit (STEL) monitoring of hydrogen chloride. The passive colorimetric badge system consists of a direct reading badge and a color scale. The badge has a coated indicator layer with a diffusive resistance in the shape of an exclamation mark. An exclamation mark will appear if hydrogen chloride is present in the atmosphere at concentrations at or above 2.0 ppm. By using the color scale, the intensity of the color formed on the badge can be further quantified up to 25 ppm. The system was validated according to a protocol based on the NIOSH Protocol for the Evaluation of Passive Monitors. The badge was exposed to relative humidities ranging from 11% to 92%, temperatures ranging from 7 C to 400 C and air velocities ranging from 5 cm/sec to 170 cm/sec. All experiments were conducted in a laboratory vapor generation system. Hydrofluoric acid, nitric acid, sulfuric acid, chlorine, hydrogen sulfide and organic acids showed no effect on the performance of the hydrogen chloride monitoring system. The passive badge and color scale system exceeded the accuracy requirements as defined by NIOSH. At ambient conditions, the mean coefficient of variation was 10.86 and the mean bias was 1.3%. This data was presented previously at the American Industrial Hygiene Conference and Exposition in Toronto, Canada in June 1999.

Chapman, K. B.↗

NASA NTRS1982

Cloud cover sampling capability of various satellite combinations for ISCCP

One of the most important objectives of the International Satellite Cloud Climatology Project (ISCCP) is the quantification of cloud cover and associated radiation parameters for climate research. The time-varying nature of cloud cover requires a measurement system that obtains cloud radiance at sufficient time intervals for determining accurate values of cloudiness for the appropriate averaging period. Current plans for the ISCCP call for such day to be acquired every 3 hours during both data and night to ensure that the diurnal cycle of cloud cover is adequately sampled. The satellite system proposed is an array of geostationary and polar-orbiting satellites. The error in mean cloud cover estimates for observation systems which do not include geostationary satellites are quantified. Candidates for such a system include two NOAA Sun-synchronous satellites with daylight equatorial-crossing times of 0730 and 1430, and a USSR satellite in an 81 deg. inclination, 900-km altitude orbit.

Harrison, E. F.↗

NASA NTRS2013

Uncertainty Quantification of GEOS-5 L-band Radiative Transfer Model Parameters Using Bayesian Inference and SMOS Observations

Uncertainties in L-band (1.4 GHz) radiative transfer modeling (RTM) affect the simulation of brightness temperatures (Tb) over land and the inversion of satellite-observed Tb into soil moisture retrievals. In particular, accurate estimates of the microwave soil roughness, vegetation opacity and scattering albedo for large-scale applications are difficult to obtain from field studies and often lack an uncertainty estimate. Here, a Markov Chain Monte Carlo (MCMC) simulation method is used to determine satellite-scale estimates of RTM parameters and their posterior uncertainty by minimizing the misfit between long-term averages and standard deviations of simulated and observed Tb at a range of incidence angles, at horizontal and vertical polarization, and for morning and evening overpasses. Tb simulations are generated with the Goddard Earth Observing System (GEOS-5) and confronted with Tb observations from the Soil Moisture Ocean Salinity (SMOS) mission. The MCMC algorithm suggests that the relative uncertainty of the RTM parameter estimates is typically less than 25 of the maximum a posteriori density (MAP) parameter value. Furthermore, the actual root-mean-square-differences in long-term Tb averages and standard deviations are found consistent with the respective estimated total simulation and observation error standard deviations of m3.1K and s2.4K. It is also shown that the MAP parameter values estimated through MCMC simulation are in close agreement with those obtained with Particle Swarm Optimization (PSO).

MCMC↗

NASA NTRS2020

Automated Noise Calibration System (VT-1000)

This paper details an automated Noise Source calibration system in development at Jet Propulsion Laboratory, California Institute of Technology (JPL). The paper begins with a discussion on Noise Figure and Excess Noise Ratio (ENR) theory, fundamentals and governing equations. As part of the fundamentals is a discussion of the system’s use of the Y-factor method to obtain accurate measurements of the Unit Under Test (UUT), and how these measurements are compared against a known ENR standard to obtain the UUT’s ENR values. There is also an in-depth discussion on uncertainty quantification for Noise Source system calibrations. The architecture of the automated calibration system is provided, which includes both the system’s hardware and software configuration. The software is written in Python 3, and provides the user detailed instruction on how to proceed, including step-by-step connection requirements. This system automates much of the measurement process, including real-time uncertainty quantification and report generation, as well as real-time feedback to the user to allow intervention if necessary. The system takes advantage of a database of results from previous measurements to compare calibration history of the ENR measurements. The automated system presented here operates over a frequency range from 10 MHz to 50 GHz, and has shown substantial time savings over traditional manual methods of performing this calibration.

Timpe, Scott↗

NASA NTRS1975

Operational use of LANDSAT imagery for the estimation of snow areal extent

Quantification of the surface area of snow covering watersheds can be a useful parameter in estimating snow water content for inclusion in water runoff prediction equations. An operational manual interpretation technique is described, which allows fast and accurate estimates to be made of the areal extent of snow parameter using LANDSAT-1 imagery. The analysis procedures and the statistical results are presented.

Katibah, E. F.↗

NASA NTRS1975

Areal extent of snow estimation in the Northern Sierra Nevada Mountains using LANDSAT-1 imagery

Quantification of the surface area of snow covering watersheds is believed to be a useful parameter in estimating snow water content for inclusion in water runoff prediction equations. An operational manual interpretation technique which allows fast and accurate estimates to be made of the areal extent of snow parameter using LANDSAT-1 imagery is documented. The analysis procedures, the statistical results, and the associated costs of this research are presented.

Katibah, E. F.↗

NASA NTRSDate not supplied

H20 Phase Characterization and Icing Mitigation Through Quantum Sensing in Silicon Carbide Non-Metal Defects

The primary focus of aircraft icing research has been on ice accretion on wings for its serious adverse consequences. When icing occurs on a wing, the change in airfoil shape results in a decrease in lift and an increase in drag, leading to potentially fatal accidents. Although the issue was recognized in the 1920s, the icing problem is still an area of ongoing research due to the complexity of the icing phenomena. A much-improved understanding of how certain weather conditions produce different icing characteristics will lead to new mitigation methods and a better quantification of current methods. This can be done by better understanding of the molecular bonding energy produced by ice polytype combinations when interacting with different surface materials in various environments. This work is currently developing both models that more accurately describe the quantum signatures of H2O states (i.e. supercooled, ice, liquid, glass phase...) and chip-based detectors to evaluate these signatures. These sensors utilize ion defects in Silicon Carbide (SiC) as extremely sensitive atomic magnetic detectors. This effort leverages both the decades-long SiC development expertise and infrastructure at NASA Glenn and its growing capabilities in quantum metrology.

Daniel R. Hart↗

NASA NTRS1977

Quantification of soil mapping by digital analysis of LANDSAT data

Soil survey mapping units are designed such that the dominant soil represents the major proportion of the unit. At times, soil mapping delineations do not adequately represent conditions as stated in the mapping unit descriptions. Digital analysis of LANDSAT multispectral scanner (MSS) data provides a means of accurately describing and quantifying soil mapping unit composition. Digital analysis of LANDSAT MSS data collected on 9 June 1973 was used to prepare a spectral soil map for a 430-hectare area in Clinton County, Indiana. Fifteen spectral classes were defined, representing 12 soil and 3 vegetation classes. The 12 soil classes were grouped into 4 moisture regimes based upon their spectral responses; the 3 vegetation classes were grouped into one all-inclusive class.

Kirschner, F. R.↗