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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 721 records · Page 40

On the Stability Analysis of Astrophysical Cooling Functions

To model the temperature evolution of optically thin astrophysical environments at MHD scales, radiative and collisional cooling rates are typically either pretabulated or fit into a functional form and then input into MHD codes as a radiative loss function. Thermal balance requires estimates of the analogous heating rates, which are harder to calculate, and due to uncertainties in the underlying dissipative heating processes these rates are often simply parameterized. The resulting net cooling function defines an equilibrium curve that varies with density and temperature. Such cooling functions can make the gas prone to thermal instability (TI), which will cause departures from equilibrium. There has been no systematic study of thermally unstable parameter space for nonequilibrium states. Motivated by our recent finding that there is a related linear instability, catastrophic cooling instability, that can dominate over TI, here we carry out such a study. We show that Balbus instability criteria for TI can be used to define a critical cooling rate, Λc, that permits a nonequilibrium analysis of cooling functions through the mapping of TI zones. We furthermore illustrate how thermal conduction modifies the shape of TI zones. Upon applying a Λc-based stability analysis to coronal loop simulations, we find that loops undergoing periodic episodes of coronal rain formation are linearly unstable to catastrophic cooling instability, while TI is stabilized by thermal conduction.

Amanda Stricklan↗

Elastic functional changepoint detection of climate impacts from localized sources

Detecting changepoints in functional data has become an important problem as interest in monitoring of climate phenomenon has increased, where the data is functional in nature. Here, the observed data often contains both amplitude (y-axis) and phase (x-axis) variability. If not accounted for properly, true changepoints may be undetected, and the estimated underlying mean change functions will be incorrect. In this article, an elastic functional changepoint method is developed which properly accounts for these types of variability. The method can detect amplitude and phase changepoints which current methods in the literature do not, as they focus solely on the amplitude changepoint. This method can easily be implemented using the functions directly or can be computed via functional principal component analysis to ease the computational burden. We apply the method and its nonelastic competitors to both simulated data and observed data to show its efficiency in handling data with phase variation with both amplitude and phase changepoints. We use the method to evaluate potential changes in stratospheric temperature due to the eruption of Mt. Pinatubo in the Philippines in June 1991. Using an epidemic changepoint model, we find evidence of a increase in stratospheric temperature during a period that contains the immediate aftermath of Mt. Pinatubo, with most detected changepoints occurring in the tropics as expected.

54 ENVIRONMENTAL SCIENCES↗

SIR-B ocean-wave enhancement with fast Fourier transform techniques

Shuttle Imaging Radar (SIR-B) imagery is Fourier filtered to remove the estimated system-transfer function, reduce speckle noise, and produce ocean scenes with a gray scale that is proportional to wave height. The SIR-B system response to speckled scenes of uniform surfaces yields an estimate of the stationary wavenumber response of the imaging radar, modeled by the 15 even terms of an eighth-order two-dimensional polynomial. Speckle can also be used to estimate the dynamic wavenumber response of the system due to surface motion during the aperture synthesis period, modeled with a single adaptive parameter describing an exponential correlation along track. A Fourier filter can then be devised to correct for the wavenumber response of the remote sensor and scene correlation, with subsequent subtraction of an estimate of the speckle noise component. A linearized velocity bunching model, combined with a surface tilt and hydrodynamic model, is incorporated in the Fourier filter to derive estimates of wave height from the radar intensities corresponding to individual picture elements.

Tilley, David G.↗

Mars surface radiation exposure for solar maximum conditions and 1989 solar proton events

The Langley heavy-ion/nucleon transport code, HZETRN, and the high-energy nucleon transport code, BRYNTRN, are used to predict the propagation of galactic cosmic rays (GCR's) and solar flare protons through the carbon dioxide atmosphere of Mars. Particle fluences and the resulting doses are estimated on the surface of Mars for GCR's during solar maximum conditions and the Aug., Sep., and Oct. 1989 solar proton events. These results extend previously calculated surface estimates for GCR's at solar minimum conditions and the Feb. 1956, Nov. 1960, and Aug. 1972 solar proton events. Surface doses are estimated with both a low-density and a high-density carbon dioxide model of the atmosphere for altitudes of 0, 4, 8, and 12 km above the surface. A solar modulation function is incorporated to estimate the GCR dose variation between solar minimum and maximum conditions over the 11-year solar cycle. By using current Mars mission scenarios, doses to the skin, eye, and blood-forming organs are predicted for short- and long-duration stay times on the Martian surface throughout the solar cycle.

Simonsen, Lisa C.↗

Enhancements to the SSME transfer function modeling code

This report details the results of a one year effort by Ohio University to apply the transfer function modeling and analysis tools developed under NASA Grant NAG8-167 (Irwin, 1992), (Bartholomew, 1992) to attempt the generation of Space Shuttle Main Engine High Pressure Turbopump transfer functions from time domain data. In addition, new enhancements to the transfer function modeling codes which enhance the code functionality are presented, along with some ideas for improved modeling methods and future work. Section 2 contains a review of the analytical background used to generate transfer functions with the SSME transfer function modeling software. Section 2.1 presents the 'ratio method' developed for obtaining models of systems that are subject to single unmeasured excitation sources and have two or more measured output signals. Since most of the models developed during the investigation use the Eigensystem Realization Algorithm (ERA) for model generation, Section 2.2 presents an introduction of ERA, and Section 2.3 describes how it can be used to model spectral quantities. Section 2.4 details the Residue Identification Algorithm (RID) including the use of Constrained Least Squares (CLS) and Total Least Squares (TLS). Most of this information can be found in the report (and is repeated for convenience). Section 3 chronicles the effort of applying the SSME transfer function modeling codes to the a51p394.dat and a51p1294.dat time data files to generate transfer functions from the unmeasured input to the 129.4 degree sensor output. Included are transfer function modeling attempts using five methods. The first method is a direct application of the SSME codes to the data files and the second method uses the underlying trends in the spectral density estimates to form transfer function models with less clustering of poles and zeros than the models obtained by the direct method. In the third approach, the time data is low pass filtered prior to the modeling process in an effort to filter out high frequency characteristics. The fourth method removes the presumed system excitation and its harmonics in order to investigate the effects of the excitation on the modeling process. The fifth method is an attempt to apply constrained RID to obtain better transfer functions through more accurate modeling over certain frequency ranges. Section 4 presents some new C main files which were created to round out the functionality of the existing SSME transfer function modeling code. It is now possible to go from time data to transfer function models using only the C codes; it is not necessary to rely on external software. The new C main files and instructions for their use are included. Section 5 presents current and future enhancements to the XPLOT graphics program which was delivered with the initial software. Several new features which have been added to the program are detailed in the first part of this section. The remainder of Section 5 then lists some possible features which may be added in the future. Section 6 contains the conclusion section of this report. Section 6.1 is an overview of the work including a summary and observations relating to finding transfer functions with the SSME code. Section 6.2 contains information relating to future work on the project.

Irwin, R. Dennis↗

Effects of exposure estimation errors on estimated exposure-response relations for PM2.5

Highlights: • Recent literature has identified associations between concentrations of fine particulate matter (PM2.5) in ambient air and adverse health effects at estimated exposure concentrations below current air ambient quality standards. • The models and analyses used do not usually quantify uncertainty about exposure estimates. • Realistic errors in exposure estimates can be estimated from available air quality monitoring stations by predicting concentrations at each station from concentrations at neighboring stations. • Exposure estimation errors are large enough to obscure low-dose nonlinearities or thresholds in the true concentration-response (C-R) function, artificially making them appear to be linear at low doses. • Better estimates of C-R functions will require modeling exposure distributions and estimation errors, rather than just estimating average exposure concentrations. Associations between fine particulate matter (PM2.5) exposure concentrations and a wide variety of undesirable outcomes, from autism and auto theft to elderly mortality, suicide, and violent crime, have been widely reported. Influential articles have argued that reducing National Ambient Air Quality Standards for PM2.5 is desirable to reduce these outcomes. Yet, other studies have found that reducing black smoke and other particulate matter by as much as 70% and dozens of micrograms per cubic meter has not detectably affected all-cause mortality rates even after decades, despite strong, statistically significant positive exposure concentration-response (C-R) associations between them. This paper examines whether this disconnect between association and causation might be explained in part by ignored estimation errors in estimated exposure concentrations. We use EPA air quality monitor data from the Los Angeles area of California to examine the shapes of estimated C-R functions for PM2.5 when the true C-R functions are assumed to be step functions with well-defined response thresholds. The estimated C-R functions mistakenly show risk as smoothly increasing with concentrations even well below the response thresholds, thus incorrectly predicting substantial risk reductions from reductions in concentrations that do not affect health risks. We conclude that ignored estimation errors obscure the shapes of true C-R functions, including possible thresholds, possibly leading to unrealistic predictions of the changes in risk caused by changing exposures. Instead of estimating improvements in public health per unit reduction (e.g., per 10 µg/m{sup 3} decrease) in average PM2.5 concentrations, it may be essential to consider how interventions change the distributions of exposure concentrations.

54 ENVIRONMENTAL SCIENCES↗

Quark Sivers Function at Small-$x$: Leading contribution from the Spin-Dependent Odderon

We present the calculation of the leading contribution to the quark Sivers function at small-Bjorken x as in [1]. This calculation uses the high energy scattering approximation and operator formalism developed in [2,3] to obtain a dominant contribution to the quark Sivers function coming from the spin-dependent odderon, in agreement with the results of [4]. We then calculate this dominant contribution in the diquark model of the proton to obtain a small-x estimate for the Sivers function.

Santiago, M. Gabriel↗

A Cross-Validation Approach to Approximate Basis Function Selection of the Stall Flutter Response of a Rectangular Wing in a Wind Tunnel

The stall flutter response of a rectangular wing in a low speed wind tunnel is modelled using a nonlinear difference equation description. Static and dynamic tests are used to select a suitable model structure and basis function. Bifurcation criteria such as the Hopf condition and vibration amplitude variation with airspeed were used to ensure the model was representative of experimentally measured stall flutter phenomena. Dynamic test data were used to estimate model parameters and estimate an approximate basis function.

Kukreja, Sunil L.↗

A Historical Overview of the NASA Orbital Debris Program Office’s Laboratory Optical Measurements

The NASA Orbital Debris Program Office (ODPO) has used laboratory measurements to help bring ground-based measurements together with models to ascertain Earth-orbiting target parameters of interest to support various orbital debris models. In 2005, the Optical Measurement Center (OMC) was established to simulate space-based illumination conditions using equipment and techniques that recreate telescopic observations, particularly source-target-sensor orientations. The intent was to recreate light curves using known aspect angles of known targets and phase angles (angle is defined by the vertex between illumination source-object-detector) to complement telescopic observations that could be used to update the current optical size estimation model (OSEM) – a model that converts object brightness into size for orbital debris models. To support the above goals, the laboratory has undergone several equipment upgrades to increase capabilities over almost 20 years of operation. The primary instrumentation acquires reflectance measurements and includes a solar-like light source, CCD camera with astrometric filters, and robotic arm. A rotary arm was added approximately five years after full operation to allow acquisition through a full 360° range of phase angles. Another part of the OMC instrumentation is a field spectrometer, predominately used for field operations to acquire pre- and post-flight spacecraft material spectral measurements. Additionally, reflectance spectroscopy of various materials is also of interest resulting from hypervelocity impact tests, pristine spacecraft materials, or samples of materials that are used in spacecraft design. These measurements are stored in NASA’s Spectral Material Database, a resource that is still being populated today. The study of spectral measurements also enabled the development of spectral unmixing routines to support the identification of spacecraft materials from spectral data gathered by ground based telescopes. Preliminary OMC investigations focused on feasibility studies to acquire 360° rotation light curves of simple shapes at a single-phase angle and extended to measurements of representative fragments from ground-based explosion tests. To correlate the light curves with ground-based optical measurements, a focused study on high area to mass materials was conducted in support of a newly identified population (at the time) in geosynchronous orbit (GEO) consisting of multi-layered insulation. To further characterize orbital debris, a larger selection of materials was analyzed using laboratory photometric measurements that included representative targets from pristine spacecraft materials and ground-based impact tests. Around 2012, an initiative was requested to understand the feasibility of active debris removal (ADR) of larger targets using grappling methods for spent rocket bodies. Using a priori information on selected targets, scaled-down versions of rocket bodies were generated thanks to improvements in 3D printing technology and machining. These targets were studied in the OMC to understand rotation characteristics. These were compared with telescopic data to determine if the tumble and rotation angles would allow ADR. In 2013, the OMC focused on combining spectral measurements with photometric data to characterize GEO orbital debris. Several years later, NASA acquired a Titan III Transtage test article from “The Boneyard” with a high-resemblance to on-orbit Titan III Transtage rocket bodies, allowing physical access to a representative rocket body that suffered fragmentations in GEO. This prompted the creation of 3D models using lidar technology and spectral measurements of the materials. Focused research also transitioned to specific materials (i.e., solar cells) when telescopic surveys requested characterization of specific GEO targets. In the different research products presented, the focus has been to understand the various parameters that influence optical size estimation, including albedo, phase functions, and brightness variations. Work in this area continues with newer sources of data, including DebriSat, a high-fidelity 56-kg spacecraft replica representative of a modern low Earth orbit (LEO) satellite subjected to a laboratory hypervelocity impact test to understand fragmentation events and to support updates to satellite breakup models and size estimation models. Utilizing the vast population of fragments from DebriSat and prior laboratory impact experiments, the ODPO has focused on acquiring bidirectional reflectance distribution function (BRDF) data to characterize targets in the laboratory, thus removing aspect angle dependencies. Additionally, the DebriSat project has provided improved processes for measuring size via image acquisition, such that a true fragment size can be directly compared to the derived size using the OSEM. The team continues to assess BRDFs and use spectral measurement data to investigate the parameters used in the OSEM, specifically magnitudes, albedo, and phase functions.

Heather Cowardin↗

The faintest stars - The luminosity and mass functions at the bottom of the main sequence

We present IR K-band photometry of complete samples of VLM candidates constructed from IIIaF and IVN plates in 10 fields taken as part of the POSSII and UKSRC surveys. Using the I-K colors constructed for these stars we estimate a bolometric luminosity function which extends to M(Bol) = 13.75. We find significant evidence for a luminosity function decreasing toward these luminosities. We also find that our results are consistent with those of studies based on the Nearby Star sample, when those data are presented as a bolometric luminosity function. We convert our observed luminosity function into a mass function, which extends with reasonable statistics to 0.08 solar masses - the H-burning minimum mass. We find significant evidence for features in the mass function at these masses. Specifically, the mass function 'turns over' at 0.25 solar mass, goes through a local minimum at about 0.15 solar mass, and may increase again below 0.1 solar mass - none of these features are predicted by any of the current theories of star formation. Lastly, the mass density we observe just above the H-burning minimum mass makes it difficult to envisage brown dwarfs contributing significant quantities of missing mass without invoking either a mass function in this region significantly steeper than that seen for main-sequence stars, or an extremely low cutoff mass to the mass function.

Tinney, Christopher G.↗

Fault-tolerant software for aircraft control systems

Concepts for software to implement real time aircraft control systems on a centralized digital computer were discussed. A fault tolerant software structure employing functionally redundant routines with concurrent error detection was proposed for critical control functions involving safety of flight and landing. A degraded recovery block concept was devised to allow collocation of critical and noncritical software modules within the same control structure. The additional computer resources required to implement the proposed software structure for a representative set of aircraft control functions were discussed. It was estimated that approximately 30 percent more memory space is required to implement the total set of control functions. A reliability model for the fault tolerant software was described and parametric estimates of failure rate were made.

Source record↗

A Monte Carlo comparison of the recovery of winds near upwind and downwind from the SASS-1 model function by means of the sum of squares algorithm and a maximum likelihood estimator

Backscatter measurements at upwind and crosswind are simulated for five incidence angles by means of the SASS-1 model function. The effects of communication noise and attitude errors are simulated by Monte Carlo methods, and the winds are recovered by both the Sum of Square (SOS) algorithm and a Maximum Likelihood Estimater (MLE). The SOS algorithm is shown to fail for light enough winds at all incidence angles and to fail to show areas of calm because backscatter estimates that were negative or that produced incorrect values of K sub p greater than one were discarded. The MLE performs well for all input backscatter estimates and returns calm when both are negative. The use of the SOS algorithm is shown to have introduced errors in the SASS-1 model function that, in part, cancel out the errors that result from using it, but that also cause disagreement with other data sources such as the AAFE circle flight data at light winds. Implications for future scatterometer systems are given.

Pierson, W. J., Jr.↗

Root traits as drivers of plant and ecosystem functioning: current understanding, pitfalls and future research needs

The effects of plants on the biosphere, atmosphere and geosphere are key determinants of terrestrial ecosystem functioning. However, despite substantial progress made regarding plant belowground components, we are still only beginning to explore the complex relationships between root traits and functions. Drawing on the literature in plant physiology, ecophysiology, ecology, agronomy and soil science, we reviewed 24 aspects of plant and ecosystem functioning and their relationships with a number of root system traits, including aspects of architecture, physiology, morphology, anatomy, chemistry, biomechanics and biotic interactions. Based on this assessment, we critically evaluated the current strengths and gaps in our knowledge, and identify future research challenges in the field of root ecology. Most importantly, we found that belowground traits with the broadest importance in plant and ecosystem functioning are not those most commonly measured. Also, the estimation of trait relative importance for functioning requires us to consider a more comprehensive range of functionally relevant traits from a diverse range of species, across environments and over time series. Finally, we also advocate that establishing causal hierarchical links among root traits will provide a hypothesis-based framework to identify the most parsimonious sets of traits with the strongest links on functions, and to link genotypes to plant and ecosystem functioning.

54 ENVIRONMENTAL SCIENCES↗

Likelihood Analysis for Mega Pixel Maps

The derivation of cosmological parameters from astrophysical data sets routinely involves operations counts which scale as O(N(exp 3) where N is the number of data points. Currently planned missions, including MAP and Planck, will generate sky maps with N(sub d) = 10(exp 6) or more pixels. Simple "brute force" analysis, applied to such mega-pixel data, would require years of computing even on the fastest computers. We describe an algorithm which allows estimation of the likelihood function in the direct pixel basis. The algorithm uses a conjugate gradient approach to evaluate X2 and a geometric approximation to evaluate the determinant. Monte Carlo simulations provide a correction to the determinant, yielding an unbiased estimate of the likelihood surface in an arbitrary region surrounding the likelihood peak. The algorithm requires O(N(sub d)(exp 3/2) operations and O(Nd) storage for each likelihood evaluation, and allows for significant parallel computation.

Kogut, Alan J.↗

Comparison of Response Surface Construction Methods for Derivative Estimation Using Moving Least Squares, Kriging and Radial Basis Functions

Response construction methods using Moving Least Squares (MLS), Kriging and Radial Basis Functions (RBF) are compared with the Global Least Squares (GLS) method in three numerical examples for derivative generation capability. Also, a new Interpolating Moving Least Squares (IMLS) method adopted from the meshless method is presented. It is found that the response surface construction methods using the Kriging and RBF interpolation yields more accurate results compared with MLS and GLS methods. Several computational aspects of the response surface construction methods also discussed.

Krishnamurthy, Thiagarajan↗