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At least 469 records · Page 26

Rotation histories of the natural satellites

Recent advances in the theory of rotation are combined with traditional approaches to study the rotational evolution of the 33 known natural satellites. A calculation similar to that reported by Burns and Safronov (1973) is applied to each satellite to obtain the characteristic time of decay of any wobble motion to smooth rotation about the principal axis of maximum moment of inertia. Stability criteria and capture probabilities are calculated for the 3/2 spin resonance. Results show that only the regular satellites and Iapetus, Hyperion, Triton, and the moon are tidally evolved. Of these, 13 have confirmed synchronous rotation periods; capture probabilities into the 3/2 resonance indicate that none of the remaining 10 should be captured in nonsynchronous, commensurate spin states. For the most part, the irregular satellites retain their original spins except for a relaxation to principal axis rotation. Tidal evolution of the obliquities of the satellites is evaluated in the framework of the generalization of Cassini's laws for the moon. Nearly resonant, forced librations in longitude of 4.8 and 0.5 deg are calculated on the basis of the observed shapes of Phobos and Deimos, respectively.

Peale, S. J.↗

Evaluation of wavelength groups for discrimination of agricultural cover types

Multispectral scanner data in twelve spectral channels, in the wavelength range 0.46 to 11.7 mm, acquired in July 1971 for three flightlines, were analyzed by applying automatic pattern recognition techniques. These twelve spectral channels were divided into four wavelength groups (W1, W2, W3 and W4), each consisting of three wavelength channels -- with respect to their estimated probability of correct classification (P sub c) in discriminating agricultural cover types. The same analysis was also done for the data acquired in August, to investigate the effect of time on these results. The effect of deletion of each of the wavelength groups on P sub C in the subsets of one to nine channels, is given. Values of P sub C for all possible combinations of wavelength groups, in the subsets of one to eleven channels are also given.

Kumar, R.↗

Evaluation of wavelength groups for discrimination of agricultural cover types

Multispectral scanner data in twelve spectral channels, in the wavelength range 0.46 to 11.7 microns, acquired in July, 1971, for three flightlines, were analyzed by applying automatic pattern recognition techniques. These twelve spectral channels were divided into four wavelength groups (W1, W2, W3 and W4), each consisting of three wavelength groups - with respect to their estimated probability of correct classification (Pc) - in discriminating agricultural cover types. The same analysis was also done for the data acquired in August, to investigate the effect of time on these results. The effect of deletion of each of the wavelength groups on Pc, in the subsets of one to nine channels, is given. Values of Pc for all possible combinations of wavelength groups, in the subsets of one to eleven channels, are also given.

Kumar, R.↗

Diagrammatic theory of transition of pendulum like systems

Orbit-orbit and spin-orbit gravitational resonances are analyzed using the model of a rigid pendulum subject to both a time-dependent periodic torque and a constant applied torque. First, a descriptive model of passage through resonance is developed from an examination of the polynomial equation that determines the extremes of the momentum variable. From this study, a probability estimate for capture into libration is derived. Second, a lowest order solution is constructed and compared with the solution obtained from numerical integration. The steps necessary to systematically improve this solution are also discussed. Finally, the effect of a dissipative term in the pendulum equation is analyzed.

Yoder, C. F.↗

Multiclass Bayes error estimation by a feature space sampling technique

A general Gaussian M-class N-feature classification problem is defined. An algorithm is developed that requires the class statistics as its only input and computes the minimum probability of error through use of a combined analytical and numerical integration over a sequence simplifying transformations of the feature space. The results are compared with those obtained by conventional techniques applied to a 2-class 4-feature discrimination problem with results previously reported and 4-class 4-feature multispectral scanner Landsat data classified by training and testing of the available data.

Mobasseri, B. G.↗

Interactions between large space power systems and low-Earth-orbit plasmas

There is a growing tendency to plan space missions that will incorporate very large space power systems. These space power systems must function in the space plasma environment, which can impose operational limitations. As the power output increases, the operating voltage also must increase and this voltage, exposed at solar array interconnects, interacts with the local plasma. The implications of such interactions are considered. The available laboratory data for biased array segment tests are reviewed to demonstrate the basic interactions considered. A data set for a floating high voltage array test was used to generate approximate relationships for positive and negative current collection from plasmas. These relationships were applied to a hypothetical 100 kW power system operating in a 400 km, near equatorial orbit. It was found that discharges from the negative regions of the array are the most probable limiting factor in array operation.

Stevens, N. J.↗

Magnetic confinement of cosmic clouds

The role of the magnetic field in the confinement or compression of interstellar gas clouds is reconsidered. The virial theorem for an isolated magnetized cloud in the presence of distant magnetic sources is reformulated in terms of moments of the internal and external currents, and an equilibrium condition is derived. This condition is applied to the interaction between isolated clouds for the simple- and artificial-case in which the field of each cloud is a dipole. With the simplest of statistical assumptions, the probability of any given cloud being compressed is calculated as about 10 percent, the magnetic field acting as a medium which transmits the kinetic pressure between clouds. Even when compression occurs the magnetic pressure 1/2 B-squared may decrease on leaving the cloud surface.

Azar, Michel↗

Asteroid orbital error analysis: Theory and application

We present a rigorous Bayesian theory for asteroid orbital error estimation in which the probability density of the orbital elements is derived from the noise statistics of the observations. For Gaussian noise in a linearized approximation the probability density is also Gaussian, and the errors of the orbital elements at a given epoch are fully described by the covariance matrix. The law of error propagation can then be applied to calculate past and future positional uncertainty ellipsoids (Cappellari et al. 1976, Yeomans et al. 1987, Whipple et al. 1991). To our knowledge, this is the first time a Bayesian approach has been formulated for orbital element estimation. In contrast to the classical Fisherian school of statistics, the Bayesian school allows a priori information to be formally present in the final estimation. However, Bayesian estimation does give the same results as Fisherian estimation when no priori information is assumed (Lehtinen 1988, and reference therein).

Muinonen, K.↗

The Behavior of Filters and Smoothers for Strongly Nonlinear Dynamics

The Kalman filter is the optimal filter in the presence of known Gaussian error statistics and linear dynamics. Filter extension to nonlinear dynamics is non trivial in the sense of appropriately representing high order moments of the statistics. Monte Carlo, ensemble-based, methods have been advocated as the methodology for representing high order moments without any questionable closure assumptions (e.g., Miller 1994). Investigation along these lines has been conducted for highly idealized dynamics such as the strongly nonlinear Lorenz (1963) model as well as more realistic models of the oceans (Evensen and van Leeuwen 1996) and atmosphere (Houtekamer and Mitchell 1998). A few relevant issues in this context are related to the necessary number of ensemble members to properly represent the error statistics and, the necessary modifications in the usual filter equations to allow for correct update of the ensemble members (Burgers 1998). The ensemble technique has also been applied to the problem of smoothing for which similar questions apply. Ensemble smoother examples, however, seem to quite puzzling in that results of state estimate are worse than for their filter analogue (Evensen 1997). In this study, we use concepts in probability theory to revisit the ensemble methodology for filtering and smoothing in data assimilation. We use Lorenz (1963) model to test and compare the behavior of a variety implementations of ensemble filters. We also implement ensemble smoothers that are able to perform better than their filter counterparts. A discussion of feasibility of these techniques to large data assimilation problems will be given at the time of the conference.

Zhu, Yanqiu↗

Uncertainty Estimates for Sonic-Boom Pressure Signatures and Loudness Carpets

A non-intrusive uncertainty quantification method is applied to computational analysis of supersonic, low-boom aircraft. The mean and standard deviation statistics of the pressure waveforms and loudness metrics are evaluated through use of numerical quadrature. The probability density function (p.d.f.) of these outputs is evaluated via kernel density estimation. The simulations use an inviscid, embedded-boundary Cartesian-mesh flow solver in the nearfield combined with an augmented Burgers’ equation solver for propagation in the farfield. The results show that the p.d.f. of the waveform is bimodal at shocks, which makes the mean and standard deviation statistics inappropriate. Despite this limitation, we show that the moment statistics can provide effective assessment of discrepancies when comparing with experimental data. This is demonstrated by presenting uncertainty analysis of a wind-tunnel test and showing that we significantly improve the predictions when we include the test uncertainties in the simulation. Normal distributions are obtained for the ground signature and loudness metrics, which is primarily due to the careful shaping of the low-boom waveform. Separation of variables and error control are used to reduce computational cost. We demonstrate that this is an efficient approach in the sense of balancing numerical errors in the statistics quadrature with discretization errors in the solvers.

ARMD↗

Potentially Underestimated Gas Flaring Activities—A New Approach to Detect Combustion Using Machine Learning and NASA’s Black Marble Product Suite

Monitoring changes in greenhouse gas (GHG) emission is critical for assessing climate mitigation efforts towards the Paris Agreement goal. A crucial aspect of science-based GHG monitoring is to provide objective information for quality assurance and uncertainty assessment of the reported emissions. Emission estimates from combustion events (gas flaring and biomass burning) are often calculated based on activity data (AD) from satellite observations, such as those detected from the visible infrared imaging radiometer suite (VIIRS) onboard the Suomi-NPP and NOAA-20 satellites. These estimates are often incorporated into carbon models for calculating emissions and removals. Consequently, errors and uncertainties associated with AD propagate into these models and impact emission estimates. Deriving uncertainty of AD is therefore crucial for transparency of emission estimates but remains a challenge due to the lack of evaluation data or alternate estimates. This work proposes a new approach using machine learning (ML) for combustion detection from NASA's Black Marble product suite and explores the assessment of potential uncertainties through comparison with existing detections. We jointly characterize combustion using thermal and light emission signals, with the latter improving detection of probable weaker combustion with less distinct thermal signatures. Being methodologically independent, the differences in ML-derived estimates with existing approaches can indicate the potential uncertainties in detection. The approach was applied to detect gas flares over the Eagle Ford Shale, Texas. We analyzed the spatio-temporal variations in detections and found that approximately 79.04% and 72.14% of the light emission-based detections are missed by ML-derived detections from VIIRS thermal bands and existing datasets, respectively. This improvement in combustion detection and scope for uncertainty assessment is essential for comprehensive monitoring of resulting emissions and we discuss the steps for extending this globally.

gas flaring↗

Modeling Measurement Error in Dose-Response Models of Community Annoyance to Low-Noise Supersonic Flight

The primary research goal of the forthcoming NASA Quesst mission community test campaign is to collect representative community response data in support of the development of supersonic overflight noise certification standards. Beginning in 2026, NASA will fly the novel X-59 demonstrator aircraft over select communities in United States in order to demonstrate the possibility of low-noise supersonic flight over land and to collect objective measurements and subjective data on the perceptual experience of this new noise source. It is believed that a regression of a binary perceptual response (‘highly annoyed’ or ‘not’) on estimated noise levels (doses, measured in decibels) will provide a useful dose-response relationship for regulators. However, as these estimated doses will be subject to measurement error, naïve estimators of regression coefficients are inconsistent and slopes may be subject to attenuation bias. In this presentation, I contrast functional modeling of measurement error via simulation extrapolation (SIMEX) with structural Bayesian measurement error models. These methods are applied to available data collected during two NASA risk reduction studies in California in 2011 and Texas in 2018. I’ll conclude noting that in the presence of nonnegligible measurement errors, probabilities of annoyance may be overpredicted for low noise levels and underpredicted for high noise levels, therefore, methods of correcting for measurement error will be necessary to improve the utility of the dose-response relationship for policy-making purposes.

simulation↗

Automated Monitoring with a BCP Fault-Decision Test

The Bayesian conditional probability (BCP) technique is a statistical fault-decision technique that is suitable as the mathematical basis of the fault-manager module in the automated-monitoring system and method described in the immediately preceding article. Within the automated-monitoring system, the fault-manager module operates in conjunction with the fault-detector module, which can be based on any one of several fault-detection techniques; examples include a threshold-limit-comparison technique or the BSP or SPRT technique mentioned in the preceding article. The present BCP technique is used to evaluate a series of one or more fault-detection events for the purpose of filtering out occasional false alarms produced by many types of statistical fault-detection procedures. The BCP technique increases the probability that an automated monitoring system produces a correct decision regarding the presence or absence of a fault. Because occasional false alarms are an inevitable consequence of the SPRT, BSP, or any other statistically based fault-detection test, there is a need for a logical procedure to distinguish between true and false alarms. Heretofore, it has been common practice to make a fault decision on an ad hoc basis for example by following a multiple-observation voting strategy in which a signal is declared to be indicative of a fault if m of the last n observations produced a fault-detection alarm. The BCP technique was developed to obtain results more reliable than those afforded by a voting strategy. The BCP technique involves a test in which one applies Bayesian inference techniques to a series of one or more single-observation alarms produced by a fault-detection test. One considers the last n decisions generated by a fault-detection test in order to evaluate the conditional probability that a failure is indicated (see figure). Each new decision reached by a fault-detection test is treated as a new piece of evidence about the state of the monitored asset, and the conditional probability of failure for the system is updated on the basis of this new evidence. The conditional probability of failure is compared with a predefined limit. For a probability below the limit, the asset is declared to be healthy. For a probability above the limit, the asset is declared to be faulty.

Bickford, Randall L.↗

Random walk theory applied to electron avalanche formation

Use of microscopic detail in random walk theory describing the initial formations of a large number of avalanches shows that concomitant electron transport coefficients quickly relax to equilibrium values. This enables the use of random walks having step sizes and probabilities based only on local electric field strengths and densities. A self-consistent avalanche solution which accounts for collective long range Coulomb interactions as well as short range elastic and inelastic collisions between electrons and background atoms is demonstrated for helium. Avalanche growth retardation followed by an abrupt growth augmentation as time proceeds is shown to be associated with the formation of regions of charge density extrema near the avalanche axis and within the axial distance covered by the electron swarm.

Englert, G. W.↗

Accelerated 133 Xe Quantification in Samples Containing Significant 133 mXe

The quantification of 133 Xe in the presence of its mother radionuclide 133 mXe requires the full quantification of both to perform the ingrowth correction for 133 Xe. Due to the nature of both of these radionuclides, the 133 mXe requires significantly more time to quantify by High Purity Germanium (HPGe) detectors due to lower production yields, lower gamma emission probabilities, and lower detection efficiencies. This work shows that 133 Xe and 133 mXe quantification can be accelerated by measuring the 133m:133 activity ratio for a large batch of material and applying this activity ratio to assays of lower activity subsamples of the same batch of material. Included in this report are derivations of the required decay correction equations, and experiments using actual samples to validate the performance of these equations. A detector calibration method is also shown that leverages this method as an alternative to existing calibration methods for 133 mXe quantification.

133mXe↗

NASA research programs responding to workshop recommendations

The atmospheric electricity and lightning committee forecasts lightning and dissemination of information on the probability of occurrence. A data source with the F-106 flight program was established. The objective is to improve the detectability of lightning and severe storms and help develop operational avoidance procedures and to study the use of satellite and Doppler radar to detect thunderstorms and forecast the probability of lightning. Three recommendations are made: (1) to establish a national flying lightning laboratory; (2) strike models are considered and to gather strike data; (3) to find the best way to apply electrical field data to operations.

Tobiason, A. R.↗

A parameterization for longwave surface radiation from sun-synchronous satellite data

A parameterization is presented for computing downward, upward, and net longwave radiation at the earth's surface using data from NOAA sun-synchronous satellites. The parameterization is applied to satellite soundings for April, 1982 over a large region of the tropical Pacific Ocean. Sensitivity studies were used to estimate the random and systematic errors in computed fluxes due to probable errors in TOVS-derived parameters. It is suggested that large biases in the results due to errors in TOVS-derived parameters may be corrected with data from the International Satellite Cloud Climatology Project.

Gupta, Shashi K.↗

Does the Bushveld-Vredefort system (South Africa) record the largest known terrestrial impact catastrophe?

The unique 2.05-Ga Bushveld and Vredefort complexes cover 100,000 sq km (diameter 400 km) on the otherwise stable Kaapvaal craton. Since the 1920's, workers have recognized that they are bracketed by the same units and were probably formed by related processes. Modern field studies and radiometric dates have provided no compelling evidence for different ages. Previous researchers invoked magmatic upthrust. Daly later attributed Vredefort to impact, but never applied his concept to the Bushveld. Subsequently, Vredefort yielded shatter cones, coesite and stishovite, and planar features; pseudotachylite (indistinguishable from Sudbury) was long known to be present. Other research concluded that at least four simultaneous impacts caused the Bushveld-Vredefort system. Three impacts formed overlapping Bushveld basins; the fourth made the Vredefort dome. The nature of intra-Bushveld 'fragments' and the properties of Rooiberg Felsite offer clues.

Elston, W. E.↗