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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 307 records · Page 17

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NASA NTRS2012

A Peculiar Class of Debris Disks from Herschel/DUNES: A Steep Fall Off in the Far Infrared

Context. The existence of debris disks around old main sequence stars is usually explained by continuous replenishment of small dust grains through collisions from a reservoir of larger objects. Aims. We present photometric data of debris disks around HIP 103389 (HD199260), HIP 100350 (HN Peg, HD206860), and HIP 114948 (HD 219482), obtained in the context of our Herschel Open TIme Key Program DUNES (DUst around NEarby Stars). Methods. We used Herschel/PACS to detect the thermal emission of the three debris disks with a 30 sigma sensitivity of a few mJy at l00 micron and 160 micron. In addition, we obtained Herschel/PACS photometric data at 70 micron for HIP 103389. These observations are complemented by a large variety of optical to far-infrared photometric data. Two different approaches are applied to reduce the Herschel data to investigate the impact of data reduction on the photometry. We fit analytical models to the available spectral energy distribution (SED) data using the fitting method of simulated therma1 annealing as well as a classical grid search method. Results. The SEDs of the three disks potentially exhibit an unusually steep decrease at wavelengths >= 70 micron. We investigate the significance of the peculiar shape of these SEDs and the impact on models of the disks provided it is real. Using grain compositions that have been applied successfully for modeling of many other debris disks, our modeling reveals that such a steep decrease of the SEDs in the long wavelength regime is inconsistent with a power-law exponent of the grain size distribution -3.5 expected from a standard equilibrium collisional cascade. In contrast, a steep grain size distribution or, alternatively an upper grain size in the range of few tens of micrometers are implied. This suggests that a very distinct range of grain sizes would dominate the thermal. emission of such disks. However, we demonstrate that the understanding of the data of faint sources obtained with Herschel is still incomplete and that the significance of our results depends on the version of the data reduction pipeline used. Conclusions. A new mechanism to produce the dust in the presented debris disks, deviations from the conditions required for a standard equilibrium collisional cascade (grain size exponent of -3.5), and/or significantly different dust properties would be necessary to explain the potentially steep SED shape of the three debris disks presented.

Ertel, S.↗

NASA NTRS1949

Heat transfer from high-temperature surfaces to fluids II : correlation of heat-transfer and friction data for air flowing in inconel tube with rounded entrance

A heat transfer investigation, which was an extension of a previously reported NACA investigation, was conducted with air flowing through an electrically heated inconel tube with a rounded entrance,an inside diameter of 0.402 inch, and a length of 24 inches over a range of conditions, which included Reynolds numbers up to 500,000, average surface temperatures up to 2050 degrees R, and heat-flux densities up to 150,000 Btu per hour per square foot. Conventional methods of correlating heat-transfer data wherein properties of the air were evaluated at the average bulk, film, and surface temperatures resulted in reductions of Nusselt number of about 38, 46, and 53 percent, respectively, for an increase in surface temperature from 605 degrees to 2050 degrees R at constant Reynolds number. A modified correlation method in which the properties of air were based on the surface temperature and the Reynolds number was modified by substituting the product of the density at the inside tube wall and the bulk velocity for the conventional mass flow per unit cross-sectional area, resulted in a satisfactory correlation of the data for the extended ranges of conditions investigated.

Lowdermilk, Warren H↗

NASA NTRS1989

Monte Carlo simulation of an expanding gas

By application of simple computer graphics techniques, the statistical performance of two Monte Carlo methods used in the simulation of rarefied gas flows are assessed. Specifically, two direct simulation Monte Carlo (DSMC) methods developed by Bird and Nanbu are considered. The graphics techniques are found to be of great benefit in the reduction and interpretation of the large volume of data generated, thus enabling important conclusions to be drawn about the simulation results. Hence, it is discovered that the method of Nanbu suffers from increased statistical fluctuations, thereby prohibiting its use in the solution of practical problems.

Boyd, Iain D.↗

NASA NTRS1973

Study to demonstrate the feasibility of and determine the optimum method of remote haze monitoring by satellite

The author has identified the following significant results. Ground truth data has been obtained in order to determine the amount of haze present at the time of ERTS-1 passes over the Los Angeles area. October 21, 1972 was the haziest day, that was essentially cloud free, to date. At the time of the next pass, November 8, 1972 this area was quite clear. Changes in terrain features are minimized because these were consecutive passes. Digital tapes of the ERTS-1 data from these two days are being analyzed to determine the effects of haze on the data, in order to determine the optimum method for monitoring haze from a satellite. Preliminary results indicate that a slight reduction in contrast and some distortion of spectral signatures are caused by heavy haze. This effect is thought to be sufficient to determine the presence of moderate haze without the benefit of ground truth data. It is significant to note that there is very little degradation of ERTS-1 data caused be a rather heavy haze. For many purposes the data obtained on a hazy day are just as useful as that obtained on a clear day.

Rogers, E. H.↗

NASA NTRS2004

A Wall Correction Program Based on Classical Methods for the National Transonic Facility (Solid Wall or Slotted Wall) and the 14x22-Ft Subsonic Tunnel at NASA LaRC

A Fortran subroutine CMWALL is described, which is an implementation of the collective information from classical methods-based wall corrections. These methods use established closed-form expressions which were developed based on simple linear potential-based methods. This is a simple and rapid tool to calculate corrections due to wall interference in the National Transonic Facility (Solid Wall or Slotted Wall) or the 14x22-Ft Subsonic Tunnel at NASA LaRC. It is designed to be easily implemented in the existing tunnel data reduction programs, either as real-time or post-point. It is however important to realize that the method is based on the simplifying assumptions of linearity, small model and attached flow. The computed results are thus to be viewed as first-cut estimates, to be refined further using more complex methods based on measured wall pressures (known as wall signature methods).

Hemsch, Michael J.↗

NASA NTRS1926

The reduction of airplane flight test data to standard atmosphere conditions

This report was prepared for the National Advisory Committee for Aeronautics in order to supply the need of practical methods of reducing observed performance to standard conditions with a minimum of labor. The first part gives a very simple approximate method of reducing performance in climb, and is particularly adapted to work not requiring extreme accuracy. The second part gives a somewhat more elaborate and more accurate method which is well suited to general flight test reduction. The third part gives the conventional method of calibrating air-speed indicators and reducing the indicated speeds to true air speeds. An appendix gives working tables and charts for the standard atmosphere. (author)

Diehl, Walter S↗

NASA NTRS1985

Constitutive modeling for isotropic materials

The first year of progress on a NASA-Lewis contract with the General Electric Co is documented. The purpose of this contract (NAS3-23927) is to develop and evaluate unified constitutive equations for applications to hot-path components of aircraft gas turbine engines such as high pressure turbine blades and vanes. To accomplish this goal, uniaxial, notched, and multiaxial specimens made of conventionally cast Rene 80 are being tested under conditions that simulate engine operating conditions. To reduce the raw data, automated data reduction techniques are being developed that produce computer files containing the information needed to analyze proposed constitutive theories. Described are the analytical methods being developed to determine the parameters for these nonlinear unified theories by using the reduced data files. In another activity, a dedicated finite-element computer code is being developed to use unified theories in the structural analysis of hot-section components. This code was extensively verified for one such theory by successfully predicting the strain histories measured experimentally at the notch root of complex specimens taken from complex laboratory specimens.

Ramaswamy, V. G.↗

NASA NTRS2021

Trend Detection of Atmospheric Time Series: Incorporating Appropriate Uncertainty Estimates and Handling Extreme Events

This paper is aimed at atmospheric scientists without formal training in statistical theory. Its goal is to, 1) provide a critical review of the rationale for trend analysis of the time series typically encountered in the field of atmospheric chemistry; 2) describe a range of trend-detection methods; and 3) demonstrate effective means of conveying the results to a general audience. Trend detections in atmospheric chemical composition data are often challenged by a variety of sources of uncertainty, which often behave differently to other environmental phenomena such as temperature, precipitation rate, or stream flow, and may require specific methods depending on the science questions to be addressed. Some sources of uncertainty can be explicitly included in the model specification, such as autocorrelation and seasonality, but some inherent uncertainties are difficult to quantify, such as data heterogeneity and measurement uncertainty due to the combined effect of short- and long-term natural variability, instrumental stability, and aggregation of data from sparse sampling frequency. Failure to account for these uncertainties might result in an inappropriate inference of the trends and their estimation errors. On the other hand, the variation in extreme events might be interesting for different scientific questions, for example, the frequency of extremely high surface ozone events and their relevance to human health. In this study we aim to, 1) review trend detection methods for addressing different levels of data complexity in different chemical species; 2) demonstrate that the incorporation of scientifically interpretable covariates can outperform pure numerical curve fitting techniques in terms of uncertainty reduction and improved predictability; 3) illustrate the study of trends based on extreme quantiles that can provide insight beyond standard mean or median based trend estimates; and 4) present an advanced method of quantifying regional trends based on the inter-site correlations of multi-site data. All demonstrations are based on time series of observed trace gases relevant to atmospheric chemistry, but the methods can be applied to other environmental data sets.

Trace gas↗

NASA NTRS1980

Visual enhancement of images of natural resources: Applications in geology

The principal components technique for use in multispectral scanner LANDSAT data processing results in optimum dimensionality reduction. A powerful tool for MSS IMAGE enhancement, the method provides a maximum impression of terrain ruggedness; this fact makes the technique well suited for geological analysis.

Dejesusparada, N.↗

NASA NTRS1998

Assessment of Uncertainty in the Determination of Activation Energy for Polymeric Materials

An assessment of the experimental uncertainty in obtaining the kinetic activation energy from thermogravimetric analysis (TGA) data is presented. A neat phenolic resin, Borden SC1O08, was heated at three heating rates to obtain weight loss vs temperature data. Activation energy was calculated by two methods: the traditional Flynn and Wall method based on the slope of log(q) versus 1/T, and a modification of this method where the ordinate and abscissa are reversed in the linear regression. The modified method produced a more accurate curve fit of the data, was more sensitive to data nonlinearity, and gave a value of activation energy 75 percent greater than the original method. An uncertainty analysis using the modified method yielded a 60 percent uncertainty in the average activation energy. Based on this result, the activation energy for a carbon-phenolic material was doubled and used to calculate the ablation rate In a typical solid rocket environment. Doubling the activation energy increased surface recession by 3 percent. Current TGA data reduction techniques that use the traditional Flynn and Wall approach to calculate activation energy should be changed to the modified method.

Darby, Stephania P.↗

NASA NTRSDate not supplied

A Dynamic PCA and Machine Learning Tool for Automated Identification of Solar Wind Disturbances Impacting Earth’s Magnetosphere

Earth’s magnetosphere is continuously impacted by solar wind and interplanetary magnetic field (IMF) disturbances, such as shocks, discontinuities, magnetic clouds and more. Understanding how such disturbances propagate from the Sun and what is their impact on the different magnetospheric domains is key to understanding and forecasting energy transfer from the solar wind to Earth. The large number of overlapping solar wind and magnetospheric missions carrying magnetometers and the recent advances in communications and data storage technologies have enabled an unprecedented quantity of high-fidelity magnetic field data captured by in-situ spacecraft to be available at the click of a button. However, this massive quantity of available data can prove unwieldy for researchers, limiting the identification of interesting phenomena and disturbances to a relatively small percentage of the total dataset. Several techniques have been previously developed for automated identification of specific types of magnetic anomalies, but these methods are typically mission-specific and can be difficult to generalize. We present initial results for a generic method of automated anomaly detection in magnetic field measurements based on dimensionality reduction and unsupervised clustering via machine learning. The benefit of our technique is its high degree of generalizability and flexibility which make it a most useful data survey tool for a wide range of magnetic field datasets. This method can also be applied simultaneously to other observed time-series properties like plasma density, pressure, and velocity for more accurate event identification. Additionally, the application of this method to data captured by multiple spacecraft enables the simultaneous identification of disturbances and the determination of their propagation characteristics. Initial evaluation of this technique has been performed using data from Magnetospheric MultiScale (MMS) and THEMIS-ARTEMIS missions, providing a testbed scenario for the future Heliophysics Environmental and Radiation Measurement Experiment Suite (HERMES) platform instruments that will measure solar wind and IMF properties from lunar orbit onboard the Gateway station.

Miguel Martinez-Ledesma↗

NASA NTRSDate not supplied

A Dynamic PCA and Machine Learning Tool for Automated Identification of Solar Wind Disturbances Impacting Earth’s Magnetosphere

Miguel Martinez-Ledesma↗

NASA NTRS1999

An ecologic study of dietary links to prostate cancer

BACKGROUND: The etiology of prostate cancer has not been fully resolved in the scientific and medical literature, although the non-fat portion of milk and calcium are emerging as leading dietary risk factors, with lycopene (found in tomatoes) and vitamin D apparently being risk reduction factors. METHODS: The ecologic (multi-country statistical) approach is used to study dietary links to prostate cancer. Mortality data from 1986 for various age groups in 41 countries are compared with national consumer macronutrient supply values for 1983 and tomato supply values for 1985. RESULTS: For 28 countries with more than five Kcal/day of tomatoes in the consumer supply, a linear combination of non-fat milk (risk factor) and tomatoes (risk reduction factor) was found to have the highest statistical association with prostate cancer mortality rates for men over the age of 35, with the Pearson regression coefficient (R2) for those aged 65-74 years = 0.67 and p < 0.001. For the 13 countries with fewer than six Kcal/day of tomatoes, non-fat milk had the highest association (R2 = 0.92, p < 0.001 for men aged 65-74 years). For 41 countries combined, the non-fat portion of milk had the highest association with prostate cancer mortality rates (R2 = 0.73, p < 0.001 for men aged 65-74 years). CONCLUSIONS: These results support the results of several cohort studies which found the non-fat portion of milk to have the highest association with prostate cancer, likely due to the calcium, and tomatoes to reduce the risk of prostate cancer, most likely due to lycopene.

Diet/adverse effects↗

NASA NTRS1976

The profile of the helium 584 A solar line - Preliminary results from rocket-borne resonance absorption spectrometer

A measurement of the line profile of the He I 584 A line from the sun has been made on board a rocket on 20 January 1975. Wavelength resolution is obtained by the resonance absorption method. The instrument is described, and its performance in flight is analysed. The principles of data reduction are given, and preliminary results are presented and compared with available data from other sources. The width of the solar He I resonance line is found to be larger than 110 mA.

Delaboudiniere, J. P.↗

NASA NTRS1993

A survey for rapid variability among early main-sequence A stars

A survey of nonpeculiar early (A0-A5) main-sequence A stars for rapid, low-amplitude variability is presented. The survey is also an independent test of the main-sequence mass-loss theory proposed by Willson et al. (1986). All observations were gathered with the University of Wisconsin Two-Star Photometer. Several period-searching methods are used to analyze time series of differential-photometric data. This instrument coupled with a computerized high-speed data collection system was used with small telescopes at Pine Bluff Observatory and Table Mountain Observatory. Several period-search methods are used to analyze time series of differential-photometric data. This instrument and data-reduction technique allow millimagnitude light variations to be detected. The survey also discovered several low-amplitude Delta Sct stars, all of which are in or blueward of the recognized instability strip.

Schutt, Randy L.↗

NASA NTRS2003

Vector-Ordering Filter Procedure for Data Reduction

The vector-ordering filter (VOF) technique involves a procedure for sampling a large population of data vectors to select a subset of data vectors that fully characterize the state space of the large population. The VOF technique enables a large reduction of the volume of data that must be handled in the automated monitoring system and method discussed in the two immediately preceding articles. In so doing, the VOF technique enables the development of data-driven mathematical models of a monitored asset from sets of data that would otherwise exceed the memory capacities of conventional engineering computers. Data-driven mathematical models have been shown to offer high fidelity for purposes of control and monitoring of assets. In practice, a collection of asset-operating observations is acquired with the intention that the collection contain observations characteristic of the full dynamic range of operation of the asset. Often, such a collection contains an extremely large number of observations, many of which are redundant. The VOF technique fills the need for a means to extract, from the original collection of observational data, a reduced data matrix that excludes redundant data while maintaining the full statistical character and dynamic range of the original data. The reduced data matrix can then be used as the input data for development of a mathematical model of the monitored asset, or as training data for a neural-network substitute for an explicit mathematical model of the asset. Alternatively, the reduced data matrix can, itself, be used directly as a mathematical model of the monitored asset, as is commonly done in multivariate state-estimation techniques. The original data are collected from the asset over a range of operating states and are put in matrix form. Each column vector in the original data matrix represents the signal values acquired at a particular operational state of the asset. Thus, the number of columns of the original data matrix equals the number of observed states and the number of rows in this matrix equals the number of signals acquired at each observation. In the VOF technique, one extracts the reduced data matrix from the original data matrix through the selection of a representative subset of the column (state) vectors.

Bickford, Randall L.↗

NASA NTRS2019

Orion Capsule Parachute Assembly System (CPAS) Main and Drogue Canopy Instrumentation

Reefing systems are often used in parachute systems to control loading and inflation of the canopies. These systems typically use pyrotechnic cutters to sever lines to progress through the staging. Existing cutters have been used for more than 50 years and have been proven adequate through countless demands. These cutters must survive and operate through severe environments that include a large snatch load at deployment and random vibration through the stage. In lieu of extensive drop test campaigns, future cutters will need to be ground tested to environments which are representative of the flight environments. The Capsule Parachute Assembly System (CPAS) developed sensors that capture accelerations and rates in three axes at approximately 1500 Hertz (Hz) during parachute deployment and operation. These sensors have mass properties, size, and an attachment method similar to existing reefing line cutter assemblies, maximizing the usability of the data. Various risk reduction steps were taken to minimize any negative effects to the qualification parachute system and to increase the likelihood of collecting usable data. 24 sensors were flown on 12 qualification parachutes, successfully collecting sufficient data to characterize the deployment and operational environment of the reefing line cutters.

Daum, Jared S.↗

NASA NTRS1994

A Space and Atmospheric Visualization Science System

SAVS (a Space and Atmospheric Visualization Science system) is an integrated system with user-friendly functionality that employs a 'push-button' software environment that mimics the logical scientific processes in data acquisition, reduction, analysis, and visualization. All of this is accomplished without requiring a detailed understanding of the methods, networks, and modules that link the tools and effectively execute the functions. This report describes SAVS and its components, followed by several applications based on generic research interests in interplanetary and magnetospheric physics (IMP/ISTP), active experiments in space (CRRES), and mission planning focused on the earth's thermospheric, ionospheric, and mesospheric domains (TIMED). The final chapters provide a user-oriented description of interface functionalities, hands-on operations, and customized modules, with details of the primary modules presented in the appendices. The overall intent of the report is to reflect the accomplishments of the three-year development effort and to introduce potential users to the power and utility of the integrated data acquisition, analysis, and visualization system.

Szuszczewicz, E. P.↗