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NASA NTRS1982

Low-latitude cloudiness and climate feedback - Comparative estimates from satellite data

Three studies of the relative albedo to the IR components of cloud amount feedback are reviewed, and an approach to the seasonal variability in low-level cloud numbers is presented. Comparisons are made and uncertainties calculated for the predictions of cloud amounts from satellite data sets for outgoing IR flux. IR data is used directly for a linear regression analysis and seasonal and latitudinal variations are considered in terms of monthly-annual means for particular latitude zones. Investigations of NOAA-NESS satellite data revealed that cirrus clouds are transparent in the 10.5-12.5 microns range and cloud albedos decrease at wavelengths greater than 0.7 micron, which suggests a possibility of cloud-sky and clear-sky albedo comparisons at 0.5-0.7 micron. The inclusion of Rayleigh scattering and atmospheric water vapor absorption of sunlight is recommended to test the effects on observed contracts.

Cess, R. D.↗

NASA NTRS1984

Aeromechanical stability of a full-scale hingeless rotor in hover

The aeroelastic stability in hover of a 9.8-m-diam, hingeless helicopter rotor system is evaluated. Rotor inplane damping data were obtained for rotor operation between 350 and 425 rpm for thrust coefficients between 0.0 and 0.12. At constant rotor rotational speed, a minimum inplane damping level was obtained at a thrust coefficient of approximately 0.02. At constant rotor thrust, a minimum in rotor inplane damping was measured at 400 rpm. Correlation with a comprehensive aeroelastic stability program is found to be good. The influence of different aerodynamic inflow models on predicted damping levels is shown. Best correlation with experimental data is obtained using a dynamic inflow model rather than static or quasi-static inflow models. Comparison with other full-scale, hingeless rotor stability data in hover is presented. Also, direct comparisons are made with data from a full-scale bearingless main rotor test performed on the same general-purpose test apparatus. Although the bearingless rotor is more highly damped at design tip speed and 1-g thrust operation, greater sensitivity to operating conditions is shown.

Peterson, R. L.↗

NASA NTRS1988

The integrated analysis capability (IAC Level 2.0)

The critical data management issues involved in the development of the integral analysis capability (IAC), Level 2, to support the design analysis and performance evaluation of large space structures, are examined. In particular, attention is given to the advantages and disadvantages of the formalized data base; merging of the matrix and relational data concepts; data types, query operators, and data handling; sequential versus direct-access files; local versus global data access; programming languages and host machines; and data flow techniques. The discussion also covers system architecture, recent system level enhancements, executive/user interface capabilities, and technology applications.

Frisch, Harold P.↗

NASA NTRS1992

Distribution of space-gathered data

A Data Distribution Satellite (DDS) concept for directly distributing space-gathered data to users on the ground and allowing users access to their experiments for real-time control is described. The DDS would operate in conjunction with the Tracking and Data Relay Satellite System; high-capacity, optical intersatellite links would be used to establish connectivity with other satellites for international data relay or data gathering. The requirements, scenarios, and satellite communications payload are examined along with the benefits of the concept and the payload technologies that must be developed.

Price, Kent M.↗

NASA NTRS1993

Optimal gains for a single polar orbiting satellite

Gains are the spatial weighting of an observation in its neighborhood versus the local values of a model prediction. They are the key to data assimilation, as they are the direct measure of how the data are used to guide the model. As derived in the broad context of data assimilation by Kalman and in the context of meteorology, for example, by Rutherford, the optimal gains are functions of the prediction error covariances between the observation and analysis points. Kalman introduced a very powerful technique that allows one to calculate these optimal gains at the time of each observation. Unfortunately, this technique is both computationally expensive and often numerically unstable for dynamical systems of the magnitude of meteorological models, and thus is unsuited for use in PMIRR data assimilation. However, the optimal gains as calculated by a Kalman filter do reach a steady state for regular observing patterns like that of a satellite. In this steady state, the gains are constants in time, and thus could conceivably be computed off-line. These steady-state Kalman gains (i.e., Wiener gains) would yield optimal performance without the computational burden of true Kalman filtering. We proposed to use this type of constant-in-time Wiener gain for the assimilation of data from PMIRR and Mars Observer.

Banfield, Don↗

NASA NTRS1996

Grant Proposal for the Continuation of the Voyager Interstellar Mission: LECP Investigation

This proposal documents the plans of the Low Energy Charged Particle (LECP) investigation team for participation in NASA's Voyager Interstellar Mission (VIM) as the Voyager 1 and 2 spacecraft explore the outer reaches of the heliosphere and search for the termination shock and the heliopause. The proposal covers the four year period from 1 January 1997 to 31 December 2000. The LECP instruments on Voyager 1 and 2 measure in situ intensities of charged particles with energies from about 30 keV to 100 MeV for ions, and about 20 keV to greater than 10 MeV for electrons. The instruments provide detailed spectral, angular, and compositional information about the particles. Composition is available for greater than 200 keV/nuc using multi-parameter measurements. Angular information is obtained by a mechanically scanned platform that rotates at various commanded rates. Measurements of low energy ion and electron intensities versus time and spatial location within the heliosphere contain an abundance of information regarding various transport and acceleration processes on both local (approx. 1 hr, approx. 0.01 AU) and global (approx. 11 yrs, approx. 100 AU) scales. The LECP instruments provide unique observations of such dynamical processes, and we anticipate that it will return critical information regarding the boundaries of the heliosphere. Several recent and exciting discoveries based on LECP measurements emphasize the important role that low energy charged particle distributions play in physical processes in the interplanetary medium. Yet, at the same time, these discoveries also underscore the fact that our understanding of processes in the outer heliosphere is, in most cases, incomplete, and in others, only rudimentary at best. Among the discoveries referred to above are the following: (1) Shocks: Examination of greater than 30 keV ion intensities have revealed: (a) a total absence of acceleration beyond only -100-200 keV at a strong transient shock in May 1991 at 35 AU, despite an enhanced level of seed particles; (b) a large transient shock in September 1991 of global scale, with intensities of shock-accelerated ions greater than or equal to 30 keV to approx. 30 MeV showing complex, highly energy-dependent spatial evolution, and small-scale (approx. few gyroradii), often anisotropic, micro-structures; (c) recurrent intensity increases in greater than or equal to 30 keV to -few MeV ions, with structures that, in some cases, show no correlation with the associated corotating shock. (2) Superthermal ion pressure: A global merged interaction region with a leading shock, downstream of which the superthermal ion (greater than or equal to 30 keV to approx. 4 MeV) pressure is comparable to that of the thermal plasma, and the total particle pressure yields a plasma beta of order unity. (3) Pickup ions: Measurements of the C/O ratio within transient structures at 35-45 AU showing the first clear evidence that transient shocks can pre-accelerate interstellar pickup ions from approx. 1 keV/nuc to at least 1 MeV/nuc. (4) Seed particles: Injection of ions for acceleration to high energies at the termination shock is unlikely to be a problem, since interplanetary transient and recurrent shocks are continually accelerating ions, of solar wind or interstellar origin, to highly superthermal energies. (5) Precursor electrons: Ambient solar electrons (greater than or equal to few tens of keV) that exist in the outer heliosphere ca form a broad precursor, several days wide, that is upstream of the termination shock and potentially observable a few months prior to the shock crossing. (6) Solar wind velocity at Voyager 1: We can use LECP ion data to obtain the solar wind velocity at Voyager 1, enabling us to provide critical measurement of the plasma flow as we approach and encounter the termination shock and other regions (necessary due to the partial failure of the Voyager 1 PLS experiment). The work of the LECP investigator team during the VIM will include: (1) Continuing operations with regard to the receipt, processing, verification, cataloging, display, and distribution of the data from the LECP instruments on Voyager 1 and 2, (2) Monitoring the health and performance of the LECP instruments, and evaluating and characterizing the response of the LECP instruments to various energetic particle and plasma environments, (3) Participating in, and supporting Voyager Project planning exercises and other coordinated activities relevant to exploration of the outer heliosphere, (4) Developing analysis techniques and operational procedures suitable for searching for and characterizing the boundaries and unique regions of the outher heliosphere, (5) Continuing the preparation of data sets appropriate for submission to the National Space Sciences Data Center (NSSDC) and, where appropriate, the Planetary Data System (PDS), (6) Maintaining direct Web access to online LECP data through the JHU/APL Voyager LECP home page, (7) Performing scientific evaluations of the Voyager 1 and 2 LECP data sets in conjunction with other data sets and other investigators, with particular focus on the outer regions of the heliosphere, and (8) Publishing the results of these evaluations in the scientific literature and presenting the results in scientific conferences.

Krimigis, Stamatios M.↗

NASA NTRS2022

Sustainable Aviation Operations and the Role of Information Technology and Data Science: Background, Current Status and Future Directions

This paper reviews the achievements of the international community towards environmentally friendly aviation operations, also referred to as Sustainable Aviation Operations in the last 25 years and the aspirations and goals to limit the impact of aviation and climate in the future. The framework for achieving global progress is provided by the International Civil Aviation Organization. NASA and FAA supported research and development to advance ATM concepts, and implemented the technology, concepts, and procedures that were responsible for creating fuel efficient flights. Historically aviation operations have been analyzed using physics-based models and provide information for making operational decisions. Future developments in aviation operations require new concepts, procedure, modeling, and analysis techniques. There is an increasing interest in applying methods based on Machine Learning Techniques to problems in Air Traffic Management. Aviation operations involving many decision makers, multiple objectives, poor or unavailable physics-based models and the availability of a rich historical database provide opportunities to exploit the richness of data-driven methods. The promises and challenges in applying Machine Learning Techniques to Air Traffic Management are discussed in the paper along with the testing and trustworthiness required for adoption of the techniques in operations.

Sustainable Aviation, Data Science, Machine Learni↗

NASA NTRS2022

Sustainable Aviation Operations and the Role of Information Technology and Data Science: Background, Current Status and Future Directions

Sustainable Aviation, Data Science, Machine Learni↗

DOE OSTI2025

Machine Learned Empirical Numerical Integrator from Simulated Data

Recently, a number of state-of-the-art surrogate machine learning (ML) models have been designed for global weather and climate prediction, which have been trained using reanalysis data products. Reanalysis data products are constructed using numerical model simulations that combine numerical integration of partial differential equations and parameterization schemes. These products are typically only archived and made available using coarsened spatial and temporal resolutions. This study explores the impact of the numerical generation methods used to produce the training datasets and the temporal resolution of those datasets on machine learning surrogate models. Using the nonlinear vector autoregression (NVAR) machine as an explainable ML technique, simple dynamical systems are emulated with ML models trained on data produced by three classical numerical integration schemes. NVAR is validated as a skillful ML method, capable of producing accurate predictions and, more importantly, reconstructing both the underlying dynamics and the numerical integration scheme used to generate the training data. However, the machine fails to generalize predictions on unseen test data generated by different numerical integration schemes, despite the underlying dynamical system being the same. This result provides a word of caution for the growing field of machine learning emulation of weather and climate dynamics. Furthermore, we illustrate using NVAR that training on temporally coarsened data may increase the required complexity of ML models and potentially introduce new numerical challenges. Finally, we discover that empirical integration schemes with arbitrary time-stepping sizes can be constructed directly from the data, which implies a potential for the development of empirical numerical integration schemes.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1973

S-band transponder experiment

The purpose of this experiment was to measure the variations in the lunar gravitational field near the trajectory of orbiting space vehicles (the command and service module (CSM) and the small particles and fields subsatellites ejected from the Apollo 15 and 16 spacecraft). New information has been obtained from all Apollo orbiting spacecraft; however, this report shall be limited to the results from the Apollo 17 CSM and the Apollo 16 subsatellite. The data acquired are precise speed measurements of the orbiting spacecraft from which accelerations or gravity profiles may be inferred. Feature resolution is controlled by the spacecraft altitude and is almost a direct relationship (i.e., data taken from a 50-km altitude will resolve approximately a 50-km feature). Therefore, revolutions 3 to 12, when the CSM was in the low-altitude orbits, provided the clearest information.

Sjogren, W. L.↗

NASA NTRS1978

Genetic code correlations - Amino acids and their anticodon nucleotides

The data here show direct correlations between both the hydrophobicity and the hydrophilicity of the homocodonic amino acids and their anticodon nucleotides. While the differences between properties of uracil and cytosine derivatives are small, further data show that uracil has an affinity for charged species. Although these data suggest that molecular relationships between amino acids and anticodons were responsible for the origin of the code, it is not clear what the mechanism of the origin might have been.

Weber, A. L.↗

NASA NTRS1980

Simultaneous far-infrared, near-infrared, and radio observations of OH/IR stars

Simultaneous far-infrared, near-infrared, and radio observations have been made of five infrared stars which show OH maser emission at 1612 MHz. These stars have very thick circumstellar dust shells and are not seen optically. The data permit a direct comparison of the far-infrared and maser emission from these sources, which strongly supports the hypothesis that the maser emission is pumped by 35 micron photons. A comparison with data obtained at earlier epochs suggests that the maser emission is saturated. The infrared and radio data are used together with estimates of the source distances to determine the luminosities and mass loss rates for these objects. The luminosities lie in the range 2000-30,000 solar luminosities and are consistent with either Mira variable or M supergiant classifications for the underlying stars. The estimated mass loss rates lie between 0.000005-0.00007 solar mass/year.

Werner, M. W.↗

NASA NTRS1981

Short interval testing of solar cells

A drawback of conventional electrical evaluation procedures regarding solar cells is related to time consuming operations required in the determination of specific parameters, such as the maximum power point, from the plotted curves, and to the transfer of data to a large digital computer for analysis and manipulation. This is especially true when large numbers of cells must be measured. To overcome such drawbacks, a digital short interval tester was designed and constructed. The new tester provides rapid and accurate measurements at constant temperature. The utilization of a light shutter makes it possible to measure up to 200 data points along the I-V curve in less than a second, thus avoiding thermal effects. Because the system is digital, parameters such as the maximum power may be calculated directly from the data.

Saylor, C. R.↗

NASA NTRS1995

Application of advanced computing techniques to the analysis and display of space science measurements

A prototype system has been developed to aid the experimental space scientist in the display and analysis of spaceborne data acquired from direct measurement sensors in orbit. We explored the implementation of a rule-based environment for semi-automatic generation of visualizations that assist the domain scientist in exploring one's data. The goal has been to enable rapid generation of visualizations which enhance the scientist's ability to thoroughly mine his data. Transferring the task of visualization generation from the human programmer to the computer produced a rapid prototyping environment for visualizations. The visualization and analysis environment has been tested against a set of data obtained from the Hot Plasma Composition Experiment on the AMPTE/CCE satellite creating new visualizations which provided new insight into the data.

Klumpar, D. M.↗

NASA NTRSDate not supplied

Goniometric and Polarized Imaging Spectroscopic Lab Measurements of Spacecraft Materials

To better characterize the spectral response of common spacecraft materials, the following laboratory measurements are presented to support the Space Situational Awareness community in the analysis of remotely sensed observational data. Of interest is classifying material reflective properties using directional reflectance spectroscopy and spatially resolved polarized imaging spectroscopy, allowing laboratory data to be applicable to ground-based optical telescope observations. The team acquired a typical CubeSat solar panel and a sample of multi-layer insulation (MLI) commonly used on spacecraft for initial measurements. The directional spectral data were collected at the Goniometer of the Rochester Institute of Technology (GRIT) laboratory with a lab and field goniometer incorporating two AnalyticalSpectral Device (ASD) spectrometers, a small Lab sphere integrating sphere also paired with an ASD spectrometer, and a Headwall micro-Hyperspec E-Series imaging spectrometer with an adjustable linear polarizer. The goniometer measures spectral bi-directional reflectance factor (BRF) data over a broad range from 350−2500 nm at 1 nm spacing with 3 nm spectral resolution in the visible and near infrared and 8 nm in the shortwave infrared. With the same spectral capabilities, the integrating sphere measures hemispherical-directional reflectance (HDR) in a 45◦-nadir configuration. The Headwall imager covers a spectral range from 400−1000 nm with 1.6 nm spectral resolution.Our initial BRF measurements show interference effects for both materials typically observed with thin films and high infrared reflectivity. In contrast, the interference effects are not present in the HDR measurements of the MLI likely due to the interference effects being averaged out over the reflecting hemisphere. Spatially resolved polarization ratio maps show variability across the materials due to the varying surface structure. We outline a plan for expanding our analysis to a broader range of materials to characterize their directional reflectance spectroscopy.

Chris H. Lee↗

DOE OSTI2024

Deep probabilistic direction prediction in 3D with applications to directional dark matter detectors

Abstract We present the first method to probabilistically predict 3D direction in a deep neural network model. The probabilistic predictions are modeled as a heteroscedastic von Mises-Fisher distribution on the sphere S 2 , giving a simple way to quantify aleatoric uncertainty. This approach generalizes the cosine distance loss which is a special case of our loss function when the uncertainty is assumed to be uniform across samples. We develop approximations required to make the likelihood function and gradient calculations stable. The method is applied to the task of predicting the 3D directions of electrons, the most complex signal in a class of experimental particle physics detectors designed to demonstrate the particle nature of dark matter and study solar neutrinos. Using simulated Monte Carlo data, the initial direction of recoiling electrons is inferred from their tortuous trajectories, as captured by the 3D detectors. For 40 keV electrons in a 70% He 30% CO 2 gas mixture at STP, the new approach achieves a mean cosine distance of 0.104 (26 ∘ ) compared to 0.556 (64 ∘ ) achieved by a non-machine learning algorithm. We show that the model is well-calibrated and accuracy can be increased further by removing samples with high predicted uncertainty. This advancement in probabilistic 3D directional learning could increase the sensitivity of directional dark matter detectors.

Computer Science↗

NASA NTRS2012

The Use of the North Alabama Lightning Mapping Array (NALMA) in the Real-Time Operational Warning Environment During the March 2nd, 2012 Severe Weather Outbreak in Northern Alabama

The North Alabama Lightning Mapping Array (NALMA) is a three-dimensional very high frequency (VHF) detection network consisting of 11 sensors spread across north central Alabama and two sensors located in the Atlanta, Georgia region. The primary advantage of this network is that it detects total lightning, or the combination of both cloud-to-ground and intra-cloud lightning, instead of cloud-to-ground lightning alone. This helps to build a complete picture of storm evolution and development, and can serve as a proxy for storm updraft strength, particularly since intra-cloud lightning makes up the majority of all lightning in a typical thunderstorm. While the NALMA data do not directly indicate severe weather, they can indirectly indicate when a storm is strengthening (weakening) due to increases (decreases) in updraft strength, as the updraft is responsible for charging mechanisms within the storm. Data output are VHF radiation sources, which are produced during lightning breakdown processes. These sources are made into 2x2 km source density grids and are ported into the Advanced Weather Interactive Processing System (AWIPS) for National Weather Service (NWS) offices in Huntsville, AL, Nashville, TN, Morristown, TN, and Birmingham, AL, in near real-time. An increase in sources, or source densities, correlates to increased lightning activity and trends in updraft magnitude as long as the storm is within about 125 km of the center of the LMA network. Operationally, these data have been used at the Huntsville NWS office since early 2003 through a collaborative effort with NASA s Short-term Prediction Research and Transition (SPoRT) Center. Since then, total lightning observations have become an essential tool for forecasters during real-time warning operations. One of the operational advantages of the NALMA is the two-minute temporal resolution of the data. This provides forecasters with two to three updates during a typical volume scan of the WSR-88D radar.

White, Kristopher↗

NASA NTRS2020

Amino Acid Encoding for Deep Learning Applications

Background: The number of applications of deep learning algorithms in bioinformatics is increasing as they usually achieve superior performance over classical approaches, especially, when bigger training datasets are available. In deep learning applications, discrete data, e.g. words or n-grams in language, or amino acids or nucleotides in bioinformatics, are generally represented as a continuous vector through an embedding matrix. Recently, learning this embedding matrix directly from the data as part of the continuous iteration of the model to optimize the target prediction – a process called ‘end-to-end learning’ – has led to state-of-the-art results in many fields. Although usage of embeddings is well described in the bioinformatics literature, the potential of end-to-end learning for single amino acids, as compared to more classical manually-curated encoding strategies, has not been systematically addressed. To this end, we compared classical encoding matrices, namely one-hot, VHSE8 and BLOSUM62, to end-to-end learning of amino acid embeddings for two different prediction tasks using three widely used architectures, namely recurrent neural networks (RNN), convolutional neural networks (CNN), and the hybrid CNN-RNN. Results: By using different deep learning architectures, we show that end-to-end learning is on par with classical encodings for embeddings of the same dimension even when limited training data is available, and might allow for a reduction in the embedding dimension without performance loss, which is critical when deploying the models to devices with limited computational capacities. We found that the embedding dimension is a major factor in controlling the model performance. Surprisingly, we observed that deep learning models are capable of learning from random vectors of appropriate dimension. Conclusion: Our study shows that end-to-end learning is a flexible and powerful method for amino acid encoding. Further, due to the flexibility of deep learning systems, amino acid encoding schemes should be benchmarked against random vectors of the same dimension to disentangle the information content provided by the encoding scheme from the distinguishability effect provided by the scheme.

Deep-learning↗