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NASA NTRS2011

Validating LES for Jet Aeroacoustics

Engineers charged with making jet aircraft quieter have long dreamed of being able to see exactly how turbulent eddies produce sound and this dream is now coming true with the advent of large eddy simulation (LES). Two obvious challenges remain: validating the LES codes at the resolution required to see the fluid-acoustic coupling, and the interpretation of the massive datasets that are produced. This paper addresses the former, the use of advanced experimental techniques such as particle image velocimetry (PIV) and Raman and Rayleigh scattering, to validate the computer codes and procedures used to create LES solutions. This paper argues that the issue of accuracy of the experimental measurements be addressed by cross-facility and cross-disciplinary examination of modern datasets along with increased reporting of internal quality checks in PIV analysis. Further, it argues that the appropriate validation metrics for aeroacoustic applications are increasingly complicated statistics that have been shown in aeroacoustic theory to be critical to flow-generated sound, such as two-point space-time velocity correlations. A brief review of data sources available is presented along with examples illustrating cross-facility and internal quality checks required of the data before it should be accepted for validation of LES.

Bridges, James↗

NASA NTRS2021

Estimation of Snow Mass Information via Assimilation of C-Band Synthetic Aperture Radar Backscatter Observations Into an Advanced and Surface Model

This study assimilated Sentinel-1 C-band backscatter observations over snow-covered terrain into the Noah-Multiparameterization land surface model using support vector machine (SVM) regression and an ensemble Kalman filter to improve the modeled terrestrial snow mass estimates. The data assimilation (DA) experiment was conducted across Western Colorado from September 2016 to August 2017. As part of the DA experiments, the impact of a rule-based update was evaluated by comparing snow water equivalent (SWE) estimates via DA (with [ DAv1 ] and without [ DAv2 ] the rule-based update) against SNOTEL SWE measurements. Results confirmed that rule-based update helped minimize SVM controllability issues, and in turn, improved the accuracy of SWE estimates relative to both open loop (OL) and DAv2 . Comparison of SWE estimates from Sentinel-1 DAv1 against SNOTEL SWE revealed that 75% of stations showed improvements in bias and correlation coefficient relative to the OL. Assimilated SWE estimates also showed statistical improvements during both the snow accumulation and snow ablation periods. However, unbiased root mean square error showed a slight increase during the snow ablation period due to the large variability in the electromagnetic response of C-band backscatter over deep and/or wet snow. Improvement of the SWE estimates also resulted in improving river discharge estimates compared to in situ measurements. River discharge using Sentinel-1 DAv1 improved the Nash–Sutcliffe efficiency at all available stations. These results suggest that physically constrained SVM can serve as an efficient observation operator for snow mass DA through explicit consideration of the first-order C-band scattering mechanisms over different terrestrial snow conditions.

Jongmin Park↗

NASA NTRS1998

On Geomagnetism and Paleomagnetism

A statistical description of Earth's broad scale, core-source magnetic field has been developed and tested. The description features an expected, or mean, spatial magnetic power spectrum that is neither "flat" nor "while" at any depth, but is akin to spectra advanced by Stevenson and McLeod. This multipole spectrum describes the magnetic energy range; it is not steep enough for Gubbins' magnetic dissipation range. Natural variations of core multipole powers about their mean values are to be expected over geologic time and are described via trial probability distribution functions that neither require nor prohibit magnetic isotropy. The description is thus applicable to core-source dipole and low degree non-dipole fields despite axial dipole anisotropy. The description is combined with main field models of modem satellite and surface geomagnetic measurements to make testable predictions of: (1) the radius of Earth's core, (2) mean paleomagnetic field intensity, and (3) the mean rates and durations of both dipole power excursions and durable axial dipole reversals. The predicted core radius is 0.7% above the 3480 km seismologic value. The predicted root mean square paleointensity (35.6 mu T) and mean Virtual Axial Dipole Moment (about 6.2 lx 1022 Am(exp 2)) are within the range of various mean paleointensity estimates. The predicted mean rate of dipole power excursions, as defined by an absolute dipole moment <20% of the 1980 value, is 9.04/Myr and 14% less than obtained by analysis of a 4 Myr paleointensity record. The predicted mean rate of durable axial dipole reversals (2.26/Myr) is 2.3% more than established by the polarity time-scale for the past 84 Myr. The predicted mean duration of axial dipole reversals (5533 yr) is indistinguishable from an observational value. The accuracy of these predictions demonstrates the power and utility of the description, which is thought to merit further development and testing. It is suggested that strong stable stratification of Earth's uppermost outer core leads to a geologically long interval of no dipole reversals and a very nearly axisymmetric field outside the core. Statistical descriptions of other planetary magnetic fields are outlined.

Voorhies, Coerte V.↗

NASA NTRS1985

The Use of AIS Data for Identifying and Mapping Calcareous Soils in Western Nebraska

The identification of calcareous soils, through unique spectral responses of the vegetation to the chemical nature of calcareous soils, can improve the accuracy of delineating the boundaries of soil mapping units over conventional field techniques. The objective of this experiment is to evaluate the use of the Airborne Imaging Spectrometer (AIS) in the identification and delineation of calcareous soils in the western Sandhills of Nebraska. Based upon statistical differences found in separating the spectral curves below 1.3 microns, calcareous and non-calcareous soils may be identified by differences in species of vegetation. Additional work is needed to identify biogeochemical differences between the two soils.

Samson, S. A.↗

NASA NTRS2007

Overview of Aircraft Noise Prediction Tools Assessment

The acoustic assessment task for both the Subsonic Fixed Wing and the Supersonic projects under NASA s Fundamental Aeronautics Program was designed to assess the current state-of-the-art in noise prediction capability and to establish baselines for gauging future progress. The documentation of our current capabilities included quantifying the differences between predictions of noise from computer codes and measurements of noise from experimental tests. Quantifying the accuracy of both the computed and experimental results further enhanced the credibility of the assessment. This presentation gives sample results from codes representative of NASA s capabilities in aircraft noise prediction at the system level and at the component level. These include semi-empirical, statistical, analytical, and numerical codes. An example of system level results is shown for an aircraft. Component level results are shown for airframe flaps and landing gear, for jet noise from a variety of nozzles, and for broadband fan noise. Additional results are shown for modeling of the acoustic behavior of duct acoustic lining and the attenuation of sound in lined ducts with flow.

Dahl, Milo D.↗

NASA NTRS2022

Solar Temperature Variations Computed from SORCE SIM Irradiances Observed During 2003-2020

NASA’s Solar Radiation and Climate Experiment (SORCE) Spectral Irradiance Monitor (SIM) instrument produced about 17 years of daily average Spectral Solar Irradiance ( SSI ) data for wavelengths 240 nm – 2416 nm. We choose a day of minimal solar activity, 2008-08-24, during the 2008 − 2009 minimum between cycles 23 and 24, and compute the brightness temperature (𝑇 o ) from that day’s solar spectral irradiance (𝑆𝑆𝐼 o ). We consider small variations of T and SSI about these reference values, and derive linear and quadratic analytic approximations by Taylor expansion about the reference day values. To determine approximation accuracy, we compare to exact brightness temperatures T computed from the Planck spectrum, by solving analytically for T , or equivalent root-finding in Wolfram Mathematica. We find that the linear analytic approximation overestimates, while the quadratic underestimates the exact result. This motivates search for statistical “fit” models “in between” the two analytic models, with minimum root-mean-square-error RMSE. We make this search using open-source statistical R software, determine coefficients for linear and quadratic fit models, and compare statistical with analytic RMSE’s. When only linear analytic and fit models are compared, the fit model is superior at ultraviolet, visible, and near infrared wavelengths. This again holds true when comparing only quadratic models. Quadratic is superior to linear for both analytic and statistical models, and statistical fits give smallest RMSE’s. Lastly, we use linear analytic and fit models to find an interpolating function in wavelength, useful in case the SIM results need adjustment to another choices of wavelengths, to compare or extend to any other instrument.

SORCE↗

NASA NTRS1972

Star scanner attitude determination for the OSO-7 spacecraft.

Calculation of the inertial orientation of the OSO-7 spacecraft from the times at which known stars or planets transit planes fixed in the spacecraft. Both the reference planes and the timing information are provided by the star scanner instrument aboard the spacecraft, while the star identification and the statistical estimation of a set of parameters describing the spacecraft attitude are accomplished in a ground station computer facility. A recursive least-squares determination is made of a vector of first-order differential corrections to the attitude state vector. Preliminary analysis indicates the system accuracy to be 3 arc min in each attitude Euler angle.

Mackison, D. L.↗

NASA NTRS1972

Estimating trajectory correction requirements for multiple outer planet missions.

General approach to the problem of estimating trajectory correction requirements for multiple outer planet flyby missions when the navigation system uses onboard optical measurements made during approach to each target planet to complement the ground-based radio measurements. The accuracy and reliability of the onboard measurement system plays a critical role in sizing the trajectory correction capability required. An illustration of the combined use of radio and optical measurements is provided for the particular case of a Jupiter-Uranus-Neptune mission. Use of the statistical technique developed for computing the trajectory correction margin required to account for uncertainties in subsystem performance, permits trajectory correction savings of 100 to 20 m/sec over 'worst case' designs. This represents weight savings of about 50% of the science payload. For the example case trajectory correction requirements are estimated for two candidate optical systems and the radio alone case. The use of onboard measurements allows a trajectory correction savings of approximately 140 m/sec.

Friedman, L. D.↗

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 NTRS1981

Analysis of soil moisture extraction algorithm using data from aircraft experiments

A soil moisture extraction algorithm is developed using a statistical parameter inversion method. Data sets from two aircraft experiments are utilized for the test. Multifrequency microwave radiometric data surface temperature, and soil moisture information are contained in the data sets. The surface and near surface ( or = 5 cm) soil moisture content can be extracted with accuracy of approximately 5% to 6% for bare fields and fields with grass cover by using L, C, and X band radiometer data. This technique is used for handling large amounts of remote sensing data from space.

Burke, H. H. K.↗

NASA NTRS1999

Cross-Sensor Validation of the Optical Transient Detector (OTD)

Lightning data from the U.S. National Lightning Detection Network (NLDN) is used to perform preliminary validation of the satellite-based Optical Transient Detector (OTD). Sensor precision, accuracy, detection efficiency and biases of the deployed instrument are considered. We estimate the sensor to have, on average, better than 30 km spatial and 100 ms temporal accuracy. The detection efficiency for cloud-to-ground lightning is about 45-70%, slightly higher for intracloud lightning. There are only marginal day/night biases in the dataset, although 55 day averaging is required to remove sampling-based diurnal lightning cycle biases. The sensor detects statistically significant differences in the optical characteristics of intracloud, negative cloud-to-ground and positive cloud-to-ground lightning, although it cannot a priori determine flash types.

Boccippio, D. J.↗

NASA NTRS2003

Estimation of Model Error Variances During Data Assimilation

Data assimilation is all about understanding the error characteristics of the data and models that are used in the assimilation process. Reliable error estimates are needed to implement observational quality control, bias correction of observations and model fields, and intelligent data selection. Meaningful covariance specifications are obviously required for the analysis as well, since the impact of any single observation strongly depends on the assumed structure of the background errors. Operational atmospheric data assimilation systems still rely primarily on climatological background error covariances. To obtain error estimates that reflect both the character of the flow and the current state of the observing system, it is necessary to solve three problems: (1) how to account for the short-term evolution of errors in the initial conditions; (2) how to estimate the additional component of error caused by model defects; and (3) how to compute the error reduction in the analysis due to observational information. Various approaches are now available that provide approximate solutions to the first and third of these problems. However, the useful accuracy of these solutions very much depends on the size and character of the model errors and the ability to account for them. Model errors represent the real-world forcing of the error evolution in a data assimilation system. Clearly, meaningful model error estimates and/or statistics must be based on information external to the model itself. The most obvious information source is observational, and since the volume of available geophysical data is growing rapidly, there is some hope that a purely statistical approach to model error estimation can be viable. This requires that the observation errors themselves are well understood and quantifiable. We will discuss some of these challenges and present a new sequential scheme for estimating model error variances from observations in the context of an atmospheric data assimilation system.

Dee, Dick↗

NASA NTRSDate not supplied

Analysis of Hypervelocity-Impacted Thin Films for Space Applications

Exposure to the harsh space environment and hypervelocity impacts from micrometeoroids and small orbital debris can affect space operations through long-term degradation of spacecraft materials, surfaces, or systems. Multi-layer insulation (MLI) and coated, polyimide films are spacecraft materials commonly found on the external surfaces of spacecraft for thermal control and protection. Characterizing the damage to these exposed materials with in situ and laboratory measurements can better inform spacecraft designers and operators in understanding and mitigating surface or system degradation. In this paper, we examine flown Hubble Space Telescope (HST) Equipment Bay 5 MLI and coated, polyimide ground test articles to characterize hypervelocity impact damage. Impact feature cavities are inspected to identify damage, which can validate long-term degradation models, improve thermal management systems, or improve accuracy of damage predictions. An overview of the impact characterization using optical microscopy, narrowband spectroscopy, and Scanning Election Microscopy/Energy Dispersive X- ray (SEM/EDX) of the two materials is presented. Observations of robustness in the space environment, as well as a detailed assessment of cratering and penetration statistics for the space-exposed sample, also are discussed.

Melissa A. Ward↗

NASA NTRS1972

Mars gravitational field estimation error

The error covariance matrices associated with a weighted least-squares differential correction process have been analyzed for accuracy in determining the gravitational coefficients through degree and order five in the Mars gravitational potential junction. The results are presented in terms of standard deviations for the assumed estimated parameters. The covariance matrices were calculated by assuming Doppler tracking data from a Mars orbiter, a priori statistics for the estimated parameters, and model error uncertainties for tracking-station locations, the Mars ephemeris, the astronomical unit, the Mars gravitational constant (G sub M), and the gravitational coefficients of degrees six and seven. Model errors were treated by using the concept of consider parameters.

Compton, H. R.↗

NASA NTRS1975

Study of on-board compression of earth resources data

The current literature on image bandwidth compression was surveyed and those methods relevant to compression of multispectral imagery were selected. Typical satellite multispectral data was then analyzed statistically and the results used to select a smaller set of candidate bandwidth compression techniques particularly relevant to earth resources data. These were compared using both theoretical analysis and simulation, under various criteria of optimality such as mean square error (MSE), signal-to-noise ratio, classification accuracy, and computational complexity. By concatenating some of the most promising techniques, three multispectral data compression systems were synthesized which appear well suited to current and future NASA earth resources applications. The performance of these three recommended systems was then examined in detail by all of the above criteria. Finally, merits and deficiencies were summarized and a number of recommendations for future NASA activities in data compression proposed.

Habibi, A.↗

NASA NTRS1982

Crop classification using airborne radar and Landsat data

NASA 13.3 GHz airborne radar data from a soil moisture measurement analysis is used to investigate the statistical nature of the radar backscattering coefficient for bare ground and three different crop types, and to evaluate the crop classification rates using Landsat data alone or combined with the airborne survey. The scatterometer was a fan-beam Doppler system, VV polarized, and is considered only for 50 deg angles of incidence. A total of 36 fields were covered a week apart by the aircraft and Landsat, and Rayleigh statistics were used in the frequency averaging to eliminate fluctuations due to random fluctuations. Within-field variances were calculated for the Landsat and the radar data and used to design optimum crop classification procedures. The Landsat Band 4 readings were 67% accurate, and an increase in accuracy of 10% was achieved by the addition of the radar data.

Ulaby, F. T.↗

NASA NTRS1987

Fine-scale motion in the central Orion nebula

The inner region of M42 has been mapped in the O III N1 forbidden line at an unprecedented combination of velocity and spatial resolution and photometric accuracy. Three separate velocity systems along the line of sight are identified. Differential mass flow is present in two of these systems. All three systems show random fluctuations in velocity well above their measurement errors. The point-by-point velocities are used to determine the diagnostic statistical parameter, the structure function. The random motions show correlation with spatial separation, as expected for turbulence; but comparison with the predictions of classical theory for nebular turbulence shows poor agreement. If Kolmogorov (1941, 1942) theory applies, then the energy must be input at many scales.

Castaneda, Hector O.↗

NASA NTRS1993

Coherent lidar design and performance verification

The verification of LAWS beam alignment in space can be achieved by a measurement of heterodyne efficiency using the surface return. The crucial element is a direct detection signal that can be identified for each surface return. This should be satisfied for LAWS but will not be satisfied for descoped LAWS. The performance of algorithms for velocity estimation can be described with two basic parameters: the number of coherently detected photo-electrons per estimate and the number of independent signal samples per estimate. The average error of spectral domain velocity estimation algorithms are bounded by a new periodogram Cramer-Rao Bound. Comparison of the periodogram CRB with the exact CRB indicates a factor of two improvement in velocity accuracy is possible using non-spectral domain estimators. This improvement has been demonstrated with a maximum-likelihood estimator. The comparison of velocity estimation algorithms for 2 and 10 micron coherent lidar was performed by assuming all the system design parameters are fixed and the signal statistics are dominated by a 1 m/s rms wind fluctuation over the range gate. The beam alignment requirements for 2 micron are much more severe than for a 10 micron lidar. The effects of the random backscattered field on estimating the alignment error is a major problem for space based lidar operation, especially if the heterodyne efficiency cannot be estimated. For LAWS, the biggest science payoff would result from a short transmitted pulse, on the order of 0.5 microseconds instead of 3 microseconds. The numerically errors for simulation of laser propagation in the atmosphere have been determined as a joint project with the University of California, San Diego. Useful scaling laws were obtained for Kolmogorov atmospheric refractive turbulence and an atmospheric refractive turbulence characterized with an inner scale. This permits verification of the simulation procedure which is essential for the evaluation of the effects of refractive turbulence on coherent Doppler lidar systems. The analysis of 2 micron Doppler lidar data from Coherent Technologies, Inc. (CTI) has demonstrated many of the advantages of doppler lidar measurements of boundary layer winds. The effects of wind shear and wind turbulence over the pulse volume are probably the dominant source of the reduced performance. The effects of wind shear and wind turbulence on the statistical description of doppler lidar data has been derived and calculated.

Frehlich, Rod↗