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All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

Stellar Occultation Probe of Triton's Atmosphere

The goals of this research were (i) to better characterize Triton's atmospheric structure by probing a region not well investigated by Voyager and (ii) to begin acquiring baseline data for an investigation of the time evolution of the atmosphere which will set limits on the thermal conductivity of the surface and the total mass of N2 in the atmosphere. Our approach was to use observations (with the Kuiper Airborne Observatory) of a stellar occultation by Triton that was predicted to occur on 1993 July 10. As described in the attached reprint, we achieved these objectives through observation of this occultation and a subsequent one with the KAO in 1995. We found new results about Triton's atmospheric structure from the analysis of the two occultations observed with the KAO and ground-based data. These stellar occultation observations made both in the visible and infrared, have good spatial coverage of Triton including the first Triton central-flash observations, and are the first data to probe the 20-100 km altitude level on Triton. The small-planet light curve model of Elliot and Young (AJ 103, 991-1015) was generalized to include stellar flux refracted by the far limb, and then fitted to the data. Values of the pressure, derived from separate immersion and emersion chords, show no significant trends with latitude indicating that Triton's atmosphere is spherically symmetric at approximately 50 km altitude to within the error of the measurements. However, asymmetry observed in the central flash indicates the atmosphere is not homogeneous at the lowest levels probed (approximately 20 km altitude). From the average of the 1995 occultation data, the equivalent-isothermal temperature of the atmosphere is 47 +/- 1 K and the atmospheric pressure at 1400 km radius (approximately 50 km altitude) is 1.4 +/- 0.1 microbar. Both of these are not consistent with a model based on Voyager UVS and RSS observations in 1989 (Strobel et al, Icarus 120, 266-289). The atmospheric temperature from the occultation is 5 K colder than that predicted by the model and the observed pressure is a factor of 1.8 greater than the model.

Elliot, James L.↗
NASA NTRS1998

The Atmospheric Structure of Triton and Pluto

The goal of this research was to better determine the atmospheric structures of Triton and Pluto through further analysis of three occultation data sets obtained with the Kuiper Airborne Observatory (KAO.) As the research progressed, we concentrated our efforts on the Triton data, as this appeared to be the most fruitful. Three papers have been prepared as a result of this research. The first paper presents new results about Triton's atmospheric structure from the analysis of all ground-based stellar occultation data recorded to date, including one single-chord occultation recorded on 1993 July 10 and nine occultation lightcurves from the double-star event on 1995 August 14. These stellar occultation observations made both in the visible and in the infrared have good spatial coverage of Triton, including the first Triton central-flash observations, and are the first data to probe the altitude level 20-100 km on Triton. The small-planet lightcurve model of J. L. Elliot and L. A. Young was generalized to include stellar flux refracted by the far limb, and then fitted to the data. Values of the pressure, derived from separate immersion and emersion chords, show no significant trends with latitude, indicating that Triton's atmosphere is spherically symmetric at approximately 50 km altitude to within the error of the measurements; however, asymmetry observed in the central flash indicates the atmosphere is not homogenous at the lowest levels probed (approximately 20 km altitude). From the average of the 1995 occultation data, the equivalent isothermal temperature of the atmosphere is 47 plus or minus 1 K and the atmospheric pressure at 1400 km radius (approximately 50 km altitude) is 1.4 plus or minus 0.1 microbar. Both of these are not consistent with a model based on Voyager UVS and RSS observations in 1989. The atmospheric temperature from the occultation is 5 K colder than that predicted by the model and the observed pressure is a factor of 1.8 greater than the model. In our opinion, the disagreement in temperature and pressure is probably due to modeling problems at the microbar level, since measurements at this level have not previously been made. Alternatively, the difference could be due to seasonal change in Triton's atmospheric structure. The second paper reports observations of a recent stellar occultation by Triton which, when combined with earlier results, show that Triton has undergone a period of global warming since 1989. The most conservative estimates of the rate of temperature and surface-pressure increase during this period imply that the atmosphere is doubling in bulk every 10 years -- significantly faster than predicted by published frost model for Triton. Our results suggests that permanent polar caps on Triton play a dominant role in regulating seasonal atmospheric changes. Similar processes should also be active on Pluto. A third paper 'Global Warming on Triton' will appear in a the January 1999 issue of Sky and Telescope.

Elliot, James L.↗
NASA NTRS2011

IONAC-Lite

The Interplanetary Overlay Net - working Protocol Accelerator (IONAC) described previously in The Inter - planetary Overlay Networking Protocol Accelerator (NPO-45584), NASA Tech Briefs, Vol. 32, No. 10, (October 2008) p. 106 (http://www.techbriefs.com/component/ content/article/3317) provides functions that implement the Delay Tolerant Networking (DTN) bundle protocol. New missions that require high-speed downlink-only use of DTN can now be accommodated by the unidirectional IONAC-Lite to support high data rate downlink mission applications. Due to constrained energy resources, a conventional software implementation of the DTN protocol can provide only limited throughput for any given reasonable energy consumption rate. The IONAC-Lite DTN Protocol Accelerator is able to reduce this energy consumption by an order of magnitude and increase the throughput capability by two orders of magnitude. In addition, a conventional DTN implementation requires a bundle database with a considerable storage requirement. In very high downlink datarate missions such as near-Earth radar science missions, the storage space utilization needs to be maximized for science data and minimized for communications protocol-related storage needs. The IONAC-Lite DTN Protocol Accelerator is implemented in a reconfigurable hardware device to accomplish exactly what s needed for high-throughput DTN downlink-only scenarios. The following are salient features of the IONAC-Lite implementation: An implementation of the Bundle Protocol for an environment that requires a very high rate bundle egress data rate. The C&DH (command and data handling) subsystem is also expected to be very constrained so the interaction with the C&DH processor and the temporary storage are minimized. Fully pipelined design so that bundle processing database is not required. Implements a lookup table-based approach to eliminate multi-pass processing requirement imposed by the Bundle Protocol header s length field structure and the SDNV (self-delimiting numeric value) data field formatting. 8-bit parallel datapath to support high data-rate missions. Reduced resource utilization implementation for missions that do not require custody transfer features. There was no known implementation of the DTN protocol in a field programmable gate array (FPGA) device prior to the current implementation. The combination of energy and performance optimization that embodies this design makes the work novel.

Torgerson, Jordan L.↗
DOE OSTI2017

Gradient-based Optimization for Regression in the Functional Tensor-Train Format

We consider the task of low-multilinear-rank functional regression, i.e., learning a low-rank parametric representation of functions from scattered real-valued data. Our first contribution is the development and analysis of gradient-based optimization procedures, including stochastic gradient descent and quasi-Newton methods, for learning the parameters of a functional tensor-train (FT) that yields improved accuracy over standard alternating least squares methods. The functional tensor-train uses the tensor-train (TT) representation of low-rank arrays as an ansatz for a class of low-multilinear-rank functions. The FT is represented by a set of matrix-valued functions that contain a set of univariate functions, and the regression task is to learn the parameters of these univariate functions. Our second contribution demonstrates that using nonlinearly parameterized univariate functions, e.g., symmetric kernels with moving centers, within each core can outperform the standard approach of using a linear expansion of basis functions. Our final contributions are new rank adaptation and group-sparsity regularization procedures to minimize overfitting. We use several benchmark problems to demonstrate at least an order of magnitude lower accuracy with gradient-based optimization methods than ALS in the low-sample number regime. We also demonstrate an order of magnitude reduction in accuracy on a test problem resulting from nonlinear parameterizations over linear parameterizations. Finally we compare regression performance with 22 other nonparametric and parametric regression methods on 10 real-world data sets. We achieve top-five accuracy for seven of the data sets and best accuracy for two of the data sets. These rankings are the best amongst parametric models and competetive with the best non-parametric methods.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1998

A Size Effect on the Fatigue Crack Growth Rate Threshold of Alloy 718

Fatigue crack growth rate (FCGR) tests were conducted on Alloy 718 in the solution annealed and aged condition at room temperature. In each test, the FCGR threshold was measured using the decreasing (Delta)K method. Initial testing was at two facilities, one of which used C(T) specimens with W = 127 mm. Previous data at the other facility had been obtained with specimens with W = 50.8 mm. A comparison of test results at R = 0.1 showed that the threshold for the 127 mm specimen was considerably higher than that of the 50.8 mm specimen. A check showed that this difference was not due to a heat-to-heat or lab-to-lab variation. Additional tests were conducted on specimens with W = 25.4 mm and at other R values. Data for the various specimens is presented along with parameters usually used to describe threshold behavior.

Garr, K. R.↗
DOE OSTI2020

Deep anomaly detection for industrial systems: a case study

We explore the use of deep neural networks for anomaly detection of industrial systems where the data are multivariate time series measurements. We formulate the problem as a self-supervised learning where data under normal operation are used to train a deep neural network autoregressive model, i.e., use a window of time series data to predict future data values. The aim of such a model is to learn to represent the system dynamic behavior under normal conditions, while expect higher model vs. measurement discrepancies under faulty conditions. In real world applications, many control settings are discrete in nature. In this paper, vector embedding and joint losses are employed to deal with such situations. Both LSTM and CNN based deep neural network backbones are studied on the Secure Water Treatment (SWaT) testbed datasets. Also, Support Vector Data Description (SVDD) method is adapted to such anomaly detection settings with deep neural networks. Evaluation methods and results are discussed based on the SWaT dataset along with potential pitfalls.

anomaly detection, deep neural network↗
NASA NTRS1997

Gaseous abundances and methane supersaturation in Titan's troposphere

Various properties of Titan's troposphere are inferred from an analysis of Voyager I infrared spectrometer (IRIS) data between 200 and 600/ cm. Two homogeneous spectral averages acquired at widely separated emission angles are chosen for the analysis. Both data sets are associated with northern low latitudes very close to that of the radio science ingress occultation point. Solutions require simultaneous nonlinear least-squares fits to the two IRIS data sets, coupled with iteration of the radio occultation refractivity data. Values and associated 1-sigma uncertainties of several parameters are inferred from our analysis. These include mole fractions for molecular hydrogen (approx. 0.0011), argon (small), and methane near the surface ( approx. 0.057). Solutions are also obtained for the hydrogen parafraction (close to equilibrium, with considerable uncertainty), air temperature near the surface ( approx. 93 K), surface surface temperature discontinuity (approx. 1 K), and maximum degree of methane supersaturation in the upper troposphere (approx. 1.5). Actual values for the above-mentioned parameters depend on the amount of ethane cloud near the tropopause. There is no evidence for methane clouds in the upper troposphere, nor is their presence compatible with large degrees of supersaturation. A wave number dependence for the stratospheric haze opacity is inferred similar to that found for a polymeric residue created in laboratory discharge experiments. This haze appears to be uniformly distributed with latitude between altitudes of 40 and 160 km, provided those nighttime data at southern high latitudes that are discounted.

Samuelson, Robert E.↗
DOE OSTI2025

Quenching of single-particle strength inferred from nucleon-removal transfer reactions on 15 C

The difference in the proton and neutron separation energies (ΔS) of the weakly bound 15 C ground state is -19.86 MeV, an extreme value. Data from intermediate-energy heavy-ion induced (HI-induced) knockout reactions on nuclei spanning -20 ≲ ΔS ≲ +20 MeV, suggest that the degree to which single-particle strength is quenched, R s , has a negative correlation with ΔS, decreasing from unity around -20 MeV to around 0.2 at +20 MeV. For the 15 C ground state (R s = 0.96 (4) in HI-induced knockout), contrasting results have recently been obtained via the neutron-adding transfer reaction, which reveal a value of R s = 0.64 (15), similar to the value observed at modest and more extreme values of ΔS with reaction probes other than HI knockout. In order to explore the any potential differences between adding and removing processes in transfer reactions at extreme ΔS, single-neutron removal transfer reactions on 15 C were performed at 7.1 MeV/u in inverse kinematics. The removal of a valence neutron in 2s 1/2 orbit using both (p, d) and (d, t) reactions shows consistent quenching factors and agrees with those from the neutron-adding reaction. The present results, which can be compared with neutron knockout reaction, suggest that correlations, represented by the quenching factor, show limited dependence on neutron-proton asymmetry under the most extreme asymmetry conditions so far achieved in transfer reactions.

quenching factor↗
NASA NTRS1989

Inversion of imaging spectrometry data using singular value decomposition

The use of imaging spectrometers, which acquire data that are both spectrally contiguous images and spatially contiguous spectra, for quantitative remote sensing of the earth is addressed. Such data sets cannot be analyzed fully using either existing spectroscopic or image techniques. Singular value decomposition (SVD) is used here for spectral unmixing and determination of the spatial scales of mixing. It is shown that when it is used to invert the mixing endmember library, SVD allows more insight into library characteristics and more control of the inversion process than other commonly used matrix inversion techniques.

Boardman, Joe W.↗
NASA NTRS2003

Temporal Stability of the NDVI-LAI Relationship in a Napa Valley Vineyard

Remotely sensed normalized difference vegetation index (NDVI) values, derived from high-resolution satellite images, were compared with ground measurements of vineyard leaf area index (LAI) periodically during the 2001 growing season. The two variables were strongly related at six ground calibration sites on each of four occasions (r squared = 0.91 to 0.98). Linear regression equations relating the two variables did not significantly differ by observation date, and a single equation accounted for 92 percent of the variance in the combined dataset. Temporal stability of the relationship opens the possibility of transforming NDVI maps to LAI in the absence of repeated ground calibration fieldwork. In order to take advantage of this circumstance, however, steps should be taken to assure temporal consistency in spectral data values comprising the NDVI.

Johnson, L. F.↗
NASA NTRS2012

Automation and Process Improvement Enables a Small Team to Operate a Low Thrust Mission in Orbit Around the Asteroid Vesta

NASA's Dawn mission to the asteroid Vesta and dwarf planet Ceres launched September 27, 2007 and arrived at Vesta in July of 2011. This mission uses ion propulsion to achieve the necessary delta-V to reach and maneuver at Vesta and Ceres. This paper will show how the evolution of ground system automation and process improvement allowed a relatively small engineering team to transition from cruise operations to asteroid operations while maintaining robust processes. The cruise to Vesta phase lasted almost 4 years and consisted of activities that were built with software tools, but each tool was open loop and required engineers to review the output to ensure consistency. Additionally, this same time period was characterized by the evolution from manually retrieved and reviewed data products to automatically generated data products and data value checking. Furthermore, the team originally took about three to four weeks to design and build about four weeks of spacecraft activities, with spacecraft contacts only once a week. Operations around the asteroid Vesta increased the tempo dramatically by transitioning from one contact a week to three or four contacts a week, to fourteen contacts a week (every 12 hours). This was accompanied by a similar increase in activity complexity as well as very fast turn around activity design and build cycles. The design process became more automated and the tools became closed loop, allowing the team to build more activities without sacrificing rigor. Additionally, these activities were dependent on the results of flight system performance, so more automation was added to analyze the flight data and provide results in a timely fashion to feed the design cycle. All of this automation and process improvement enabled up the engineers to focus on other aspects of spacecraft operations, including spacecraft health monitoring and anomaly resolution.

ground system automation↗
NASA NTRS2011

Health Monitor for Multitasking, Safety-Critical, Real-Time Software

Health Manager can detect Bad Health prior to a failure occurring by periodically monitoring the application software by looking for code corruption errors, and sanity-checking each critical data value prior to use. A processor s memory can fail and corrupt the software, or the software can accidentally write to the wrong address and overwrite the executing software. This innovation will continuously calculate a checksum of the software load to detect corrupted code. This will allow a system to detect a failure before it happens. This innovation monitors each software task (thread) so that if any task reports "bad health," or does not report to the Health Manager, the system is declared bad. The Health Manager reports overall system health to the outside world by outputting a square wave signal. If the square wave stops, this indicates that system health is bad or hung and cannot report. Either way, "bad health" can be detected, whether caused by an error, corrupted data, or a hung processor. A separate Health Monitor Task is started and run periodically in a loop that starts and stops pending on a semaphore. Each monitored task registers with the Health Manager, which maintains a count for the task. The registering task must indicate if it will run more or less often than the Health Manager. If the task runs more often than the Health Manager, the monitored task calls a health function that increments the count and verifies it did not go over max-count. When the periodic Health Manager runs, it verifies that the count did not go over the max-count and zeroes it. If the task runs less often than the Health Manager, the periodic Health Manager will increment the count. The monitored task zeroes the count, and both the Health Manager and monitored task verify that the count did not go over the max-count.

Zoerner, Roger↗
DOE OSTI2020

A review of coal heating value correlations with application to coal char, tar, and other fuels

Accurately measuring a fuel’s heating value is one of the first steps in the classification of a new fuel. Heating values are widely used in coal combustion research and are becoming more useful in other fuel types as well. Many different empirical correlations to predict heating values based on primary organic (CHONS) elemental composition are found in the literature, many of which were originally created to predict heating values of parent coal, and some of which have been extended for biomass. However, no correlations exist for heating values of coal chars and tars. Thirteen literature heating value correlations (10 model forms with 13 unique sets of coefficients) were evaluated for their predictive accuracy of a wide variety of fuel types, including 353 coals. This comparative analysis showed that the predictive capabilities of many of these literature models are very similar for coal-based fuels, with good correlation of coal char heating values. Correlation of coal tar heating values was hampered by the lack of heating value data. The choice of which model to use becomes more important for biomass fuels as well as for more unique fuel types like propellants and explosives, municipal solid waste, etc. Finally, the best model forms for each fuel type are suggested based on several statistical measures of fit.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2026

Poisson Log-Normal Process for Count Data Prediction

Modeling count data is important in physics and other scientific disciplines, where measurements often involve discrete, non-negative quantities such as photon or neutrino detection events. Traditional parametric approaches can be trained to generate integer-count predictions but may struggle with capturing complex, non-linear dependencies often observed in the data. Gaussian process (GP) regression provides a robust non-parametric alternative to modeling continuous data; however, it cannot generate integer outputs. We propose the Poisson Log-Normal (PoLoN) process, a framework that employs GP to model Poisson log-rates. As in GP regression, our approach relies on the correlations between data points captured via GP kernel structure rather than explicit functional parameterizations. We demonstrate that the PoLoN predictive distribution is Poisson-LogNormal and provide an algorithm for optimizing kernel hyperparameters. Furthermore, we adapt the PoLoN approach to the problem of detecting weak localized signals superimposed on a smoothly varying background - a task of considerable interest in many areas of science and engineering. Our framework allows us to predict the strength, location and width of the detected signals. We evaluate PoLoN's performance using both synthetic and real-world datasets, including the open dataset from CERN which was used to detect the Higgs boson at the Large Hadron Collider. Our results indicate that the PoLoN process can be used as a non-parametric alternative for analyzing, predicting, and extracting signals from integer-valued data.

Saha, Anushka [Rutgers U., Piscataway]↗
DOE OSTI2017

Evaluation of performance indicators applied to a material recovery facility fed by mixed packaging waste

Highlights: • Material Flows assessment of a Material Recovery Facility has been realized. • Performance Indicators for a generic MRF have been proposed. • A Dashboard has been utilized to measure the facility performance. • Experimental values of incoming waste and output products composition are reported. - Abstract: Most of the integrated systems for municipal solid waste management aim to increase the recycling of secondary materials by means of physical processes including sorting, shredding and reprocessing. Several restrictions prevent from reaching a very high material recycling efficiency: the variability of the composition of new-marketed materials used for packaging production and its shape and complexity are critical issues. The packaging goods are in fact made of different materials (aluminium, polymers, paper, etc.), possibly assembled, having different shape (flat, cylindrical, one-dimensional, etc.), density, colours, optical properties and so on. These aspects limit the effectiveness and efficiency of the sorting and reprocessing plants. The scope of this study was to evaluate the performance of a large scale Material Recovery Facility (MRF) by utilizing data collected during a long period of monitoring. The database resulted from the measured data has been organized in four sections: (1) data related to the amount and type of inlet waste; (2) amount and composition of output products and waste; (3) operating data (such as worked hours for shift, planned and unscheduled maintenance time, setting parameters of the equipment, and energy consumption for shift); (4) economic data (value of each product, disposal price for the produced waste, penalty for non-compliance of products and waste, etc.). A part of this database has been utilized to build an executive dashboard composed by a set of performance indicators suitable to measure the effectiveness and the efficiency of the MRF operations. The dashboard revealed itself as a powerful tool to support managers and engineers in their decisions in respect to the market demand or compliance regulation variation as well as in the designing of the lay-out improvements. The results indicated that the 40% of the input waste was recovered as valuable products and that a large part of these (88%) complied with the standards of the recycling companies. The evaluation of the indicators led to the decision to modify the layout to improve the interception of some polymers for which the performance indicators were poor. In particular, two additional optical sorters have to be inserted to increase the yield indicator and to the overall performance of the facility. Definitely, the results of the work allowed to: increase the yield and purity of products’ flows; ensure the compliance of waste flows; increase the workability.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1979

VLSI system for synthetic aperture radar /SAR/ processing

The paper discusses an SAR problem based on actual requirements set forth by NASA for a spaceborne application. The requirements for high resolution and high quality necessitate a data sampling rate of 7.5 MHz. For each data value 1,025 4-bit complex multiply + add operations are needed, which is equivalent to 7.7 GHz complex multiply + add operation rate. Since this rate is much too high for general purpose systems, a special-purpose device was sought. This paper discusses two architectures based on parallel operation of 1,025 identical cells, each of which is capable of performing arithmetic, storage, and several control operations. The operation rate in each device is only 7.5 MHz, which is quite manageable, especially with the help of a substantial degree of pipelining. A computational-mathematical analysis is used as a primary tool for evaluating the design and some of its tradeoffs. Two different approaches are discussed and compared; both are based on having 1,025 identical cells working in parallel, but differ in their dual approaches to the flow of data.

Cohen, D.↗
DOE OSTI2019

Accelerating Relative-error Bounded Lossy Compression for HPC datasets with Precomputation-Based Mechanisms

Scientific simulations in high-performance computing (HPC) environments are producing vast volume of data, which may cause a severe I/O bottleneck at runtime and a huge burden on storage space for post-analysis. Unlike the traditional data reduction schemes (such as deduplication or lossless compression), not only can error-controlled lossy compression significantly reduce the data size but it can also hold the promise to satisfy user demand on error control. Point-wise relative error bounds (i.e., compression errors depends on the data values) are widely used by many scientific applications in the lossy compression, since error control can adapt to the precision in the dataset automatically. Point-wise relative error bounded compression is complicated and time consuming. In this work, we develop efficient precomputation-based mechanisms in the SZ lossy compression framework. Our mechanisms can avoid costly logarithmic transformation and identify quantization factor values via a fast table lookup, greatly accelerating the relative-error bounded compression with excellent compression ratios. In addition, our mechanisms also help reduce traversing operations for Huffman decoding, and thus significantly accelerate the decompression process in SZ. Experiments with four well-known real-world scientific simulation datasets show that our solution can improve the compression rate by about 30% and decompression rate by about 70% in most of cases, making our designed lossy compression strategy the best choice in class in most cases.

compression rate↗
NASA NTRS2012

Quantified Event Automata: Towards Expressive and Efficient Runtime Monitors

Runtime verification is the process of checking a property on a trace of events produced by the execution of a computational system. Runtime verification techniques have recently focused on parametric specifications where events take data values as parameters. These techniques exist on a spectrum inhabited by both efficient and expressive techniques. These characteristics are usually shown to be conflicting - in state-of-the-art solutions, efficiency is obtained at the cost of loss of expressiveness and vice-versa. To seek a solution to this conflict we explore a new point on the spectrum by defining an alternative runtime verification approach.We introduce a new formalism for concisely capturing expressive specifications with parameters. Our technique is more expressive than the currently most efficient techniques while at the same time allowing for optimizations.

state machines↗