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NASA NTRS2004

Performance Evaluation of Fiber Bragg Gratings at Elevated Temperatures

The development of integrated fiber optic sensors for smart propulsion systems demands that the sensors be able to perform in extreme environments. In order to use fiber optic sensors effectively in an extreme environment one must have a thorough understanding of the sensor s limits and how it responds under various environmental conditions. The sensor evaluation currently involves examining the performance of fiber Bragg gratings at elevated temperatures. Fiber Bragg gratings (FBG) are periodic variations of the refractive index of an optical fiber. These periodic variations allow the FBG to act as an embedded optical filter passing the majority of light propagating through a fiber while reflecting back a narrow band of the incident light. The peak reflected wavelength of the FBG is known as the Bragg wavelength. Since the period and width of the refractive index variation in the fiber determines the wavelengths that are transmitted and reflected by the grating, any force acting on the fiber that alters the physical structure of the grating will change what wavelengths are transmitted and what wavelengths are reflected by the grating. Both thermal and mechanical forces acting on the grating will alter its physical characteristics allowing the FBG sensor to detect both temperature variations and physical stresses, strain, placed upon it. This ability to sense multiple physical forces makes the FBG a versatile sensor. This paper reports on test results of the performance of FBGs at elevated temperatures. The gratings looked at thus far have been either embedded in polymer matrix materials or freestanding with the primary focus of this paper being on the freestanding FBGs. Throughout the evaluation process, various parameters of the FBGs performance were monitored and recorded. These parameters include the peak Bragg wavelength, the power of the Bragg wavelength, and total power returned by the FBG. Several test samples were subjected to identical test conditions to allow for statistical analysis of the data. Test procedures, calibrations, and referencing techniques are presented in the paper along with directions for future research.

Juergens, Jeffrey↗

NASA NTRS1997

Analysis of myosin heavy chain mRNA expression by RT-PCR

An assay was developed for rapid and sensitive analysis of myosin heavy chain (MHC) mRNA expression in rodent skeletal muscle. Only 2 microg of total RNA were necessary for the simultaneous analysis of relative mRNA expression of six different MHC genes. We designed synthetic DNA fragments as internal standards, which contained the relevant primer sequences for the adult MHC mRNAs type I, IIa, IIx, IIb as well as the embryonic and neonatal MHC mRNAs. A known amount of the synthetic fragment was added to each polymerase chain reaction (PCR) and yielded a product of different size than the amplified MHC mRNA fragment. The ratio of amplified MHC fragment to synthetic fragment allowed us to calculate percentages of the gene expression of the different MHC genes in a given muscle sample. Comparison with the traditional Northern blot analysis demonstrated that our reverse transcriptase-PCR-based assay was reliable, fast, and quantitative over a wide range of relative MHC mRNA expression in a spectrum of adult and neonatal rat skeletal muscles. Furthermore, the high sensitivity of the assay made it very useful when only small quantities of tissue were available. Statistical analysis of the signals for each MHC isoform across the analyzed samples showed a highly significant correlation between the PCR and the Northern signals as Pearson correlation coefficients ranged between 0.77 and 0.96 (P < 0.005). This assay has potential use in analyzing small muscle samples such as biopsies and samples from pre- and/or neonatal stages of development.

Non-NASA Center↗

NASA NTRS2005

Thermal Evaluation of Fiber Bragg Gratings at Extreme Temperatures

The development of integrated fiber optic sensors for use in aerospace health monitoring systems demands that the sensors be able to perform in extreme environments. In order to use fiber optic sensors effectively in an extreme environment one must have a thorough understanding of the sensor's capabilities, limitations, and performance under extreme environmental conditions. This paper reports on our current sensor evaluation examining the performance of freestanding fiber Bragg gratings (FBG) at extreme temperatures. While the ability of FBGs to survive at extreme temperatures has been established, their performance and long term survivability is not well documented. At extreme temperatures the grating structure would be expected to dissipate, degrading the sensors performance and eventually ceasing to return a detectable signal. The fiber jacket will dissipate leaving a brittle, unprotected fiber. For FBGs to be used in aerospace systems their performance and limitations need to be thoroughly understood at extreme temperatures. As the limits of the FBGs performance are pushed the long term survivability and performance of the sensor comes into question. We will not only examine the ability of FBGs to survive extreme temperatures but also look at their performance during many thermal cycles. This paper reports on test results of the performance of thermal cycling commercially available FBGs, at temperatures up to 1000 C, seen in aerospace applications. Additionally this paper will report on the performance of commercially available FBGs held at 1000 C for hundreds of hours. Throughout the evaluation process, various parameters of the FBGs performance were monitored and recorded. Several test samples were subjected to identical test conditions to allow for statistical analysis of the data. Test procedures, calibrations, referencing techniques, performance data, and interpretations and explanations of results are presented in the paper along with directions for future research.

Juergens, Jeffrey↗

NASA NTRS2005

Tools for Basic Statistical Analysis

Statistical Analysis Toolset is a collection of eight Microsoft Excel spreadsheet programs, each of which performs calculations pertaining to an aspect of statistical analysis. These programs present input and output data in user-friendly, menu-driven formats, with automatic execution. The following types of calculations are performed: Descriptive statistics are computed for a set of data x(i) (i = 1, 2, 3 . . . ) entered by the user. Normal Distribution Estimates will calculate the statistical value that corresponds to cumulative probability values, given a sample mean and standard deviation of the normal distribution. Normal Distribution from two Data Points will extend and generate a cumulative normal distribution for the user, given two data points and their associated probability values. Two programs perform two-way analysis of variance (ANOVA) with no replication or generalized ANOVA for two factors with four levels and three repetitions. Linear Regression-ANOVA will curvefit data to the linear equation y=f(x) and will do an ANOVA to check its significance.

Luz, Paul L.↗

NASA NTRS2014

Background Error Covariance Estimation Using Information from a Single Model Trajectory with Application to Ocean Data Assimilation

An attractive property of ensemble data assimilation methods is that they provide flow dependent background error covariance estimates which can be used to update fields of observed variables as well as fields of unobserved model variables. Two methods to estimate background error covariances are introduced which share the above property with ensemble data assimilation methods but do not involve the integration of multiple model trajectories. Instead, all the necessary covariance information is obtained from a single model integration. The Space Adaptive Forecast error Estimation (SAFE) algorithm estimates error covariances from the spatial distribution of model variables within a single state vector. The Flow Adaptive error Statistics from a Time series (FAST) method constructs an ensemble sampled from a moving window along a model trajectory.SAFE and FAST are applied to the assimilation of Argo temperature profiles into version 4.1 of the Modular Ocean Model (MOM4.1) coupled to the GEOS-5 atmospheric model and to the CICE sea ice model. The results are validated against unassimilated Argo salinity data. They show that SAFE and FAST are competitive with the ensemble optimal interpolation (EnOI) used by the Global Modeling and Assimilation Office (GMAO) to produce its ocean analysis. Because of their reduced cost, SAFE and FAST hold promise for high-resolution data assimilation applications.

Error Covariance↗

NASA NTRS2013

First Cloud-to-Ground Lightning Timing Study

NASA's LSP, GSDO and other programs use the probability of cloud-to-ground (CG) lightning occurrence issued by the 45th Weather Squadron (45 WS) in their daily and weekly lightning probability forecasts. These organizations use this information when planning potentially hazardous outdoor activities, such as working with fuels, or rolling a vehicle to a launch pad, or whenever personnel will work outside and would be at-risk from lightning. These organizations would benefit greatly if the 45 WS could provide more accurate timing of the first CG lightning strike of the day. The Applied Meteorology Unit (AMU) has made significant improvements in forecasting the probability of lightning for the day, but forecasting the time of the first CG lightning with confidence has remained a challenge. To address this issue, the 45 WS requested the AMU to determine if flow regimes, wind speed categories, or a combination of the two could be used to forecast the timing of the first strike of the day in the Kennedy Space Center (KSC)/Cape Canaveral Air Force Station (CCAFS) lightning warning circles. The data was stratified by various sea breeze flow regimes and speed categories in the surface to 5,000-ft layer. The surface to 5,000-ft layer was selected since that is the layer the 45 WS uses to predict the behavior of sea breeze fronts, which are the dominant influence on the occurrence of first lightning in Florida during the warm season. Due to small data sample sizes after stratification, the AMU could not determine a statistical relationship between flow regimes or speed categories and the time of the first CG strike.. As expected, although the amount and timing of lightning activity varies by time of day based on the flow regimes and speed categories, there are extended tails of low lightning activity making it difficult to specify times when the threat of the first lightning flash can be avoided. However, the AMU developed a graphical user interface with input from the 45 WS that allows forecasters to visualize the climatological frequencies of the timing of the first lightning strike. This tool should contribute directly to the 45 WS goal of improving lightning timing capability for its NASA, US Air Force and commercial customers.

statistical analysis↗

NASA NTRS2014

Background Error Covariance Estimation using Information from a Single Model Trajectory with Application to Ocean Data Assimilation into the GEOS-5 Coupled Model

An attractive property of ensemble data assimilation methods is that they provide flow dependent background error covariance estimates which can be used to update fields of observed variables as well as fields of unobserved model variables. Two methods to estimate background error covariances are introduced which share the above property with ensemble data assimilation methods but do not involve the integration of multiple model trajectories. Instead, all the necessary covariance information is obtained from a single model integration. The Space Adaptive Forecast error Estimation (SAFE) algorithm estimates error covariances from the spatial distribution of model variables within a single state vector. The Flow Adaptive error Statistics from a Time series (FAST) method constructs an ensemble sampled from a moving window along a model trajectory. SAFE and FAST are applied to the assimilation of Argo temperature profiles into version 4.1 of the Modular Ocean Model (MOM4.1) coupled to the GEOS-5 atmospheric model and to the CICE sea ice model. The results are validated against unassimilated Argo salinity data. They show that SAFE and FAST are competitive with the ensemble optimal interpolation (EnOI) used by the Global Modeling and Assimilation Office (GMAO) to produce its ocean analysis. Because of their reduced cost, SAFE and FAST hold promise for high-resolution data assimilation applications.

Data Assimilation↗

NASA NTRS2020

Recommendations for Using Noise Monitors to Estimate Noise Exposure During X-59 Community Tests

A low fidelity simulation approach is used to explore how to place and use noise monitors during X-59 QueSST community tests, where people’s annoyance to the noise produced by the X-59 aircraft will be gathered. Several recommendations are provided including: 1) the desired number of sparsely spaced noise monitor sites within the survey area, 2) whether to group and average measurements across multiple noise monitors located at a site, 3) what spacing should be used if grouped noise monitors are used, 4) an approach to mitigate ambient noise contamination at the measurement sites, 5) a method to combine empirical and predicted dose estimates to provide a single dose estimate for respondents, and 6) assessing how changes in turbulence intensity and array configuration affect dose uncertainty. To make these recommendations, the error that is expected when fitting contrived, smoothly varying sonic boom “reference exposure surfaces” is studied when a spatially sparse and scattered set of samples is used as responses for the fit. The reference exposure surfaces mimic the sonic boom exposure at ground level that might be expected in the X-59 survey area in the absence of atmospheric turbulence, ambient noise, and other localized effects. The spatial extent of these surfaces varies and is representative of the different survey area sizes that might be expected during future X-59 community overflight tests. These contrived reference surfaces are sampled, and those reference samples are then perturbed to mimic atmospheric turbulence, ambient noise and other localized effects that might affect noise monitor measurements within overflown communities. Two different surface fitting methods are investigated when fitting these perturbed samples to approximate the reference surface. The first method uses interpolation between the perturbed data at the scattered sites to compute the fit. The second method fits a polynomial surface model to the perturbed data using ordinary least squares regression analysis. For both fitting methods, the root mean square fit error is computed from the pointwise difference between the fit surface and the reference surface as the count and configuration of the sites is varied while also averaging the error across many different realizations of both the smooth variation of the reference exposure surface and the random, localized perturbations at the sample sites. Different site configurations are compared using this error statistic to make the recommendations noted above. Additionally, the two fitting approaches (interpolation vs linear regression) are compared based on the fit error observed in these simulations. These analyses, comparisons, and recommendations should inform future decisions on the noise monitor placement and the methods used to analyze the noise monitor data that is collected during X-59 community overflights.

sonic boom↗

DOE OSTI2012

SRF Cavity Surface Topography Characterization Using Replica Techniques

To better understand the roll of topography on SRF cavity performance, we seek to obtain detailed topographic information from the curved practical cavity surfaces. Replicas taken from a cavity interior surface provide internal surface molds for fine Atomic Force Microscopy (AFM) and stylus profilometry. In this study, we confirm the replica resolution both on surface local defects such as grain boundary and etching pits and compare the surface uniform roughness with the aid of Power Spectral Density (PSD) where we can statistically obtain roughness parameters at different scales. A series of sampling locations are at the same magnetic field chosen at the same latitude on a single cell cavity to confirm the uniformity. Another series of sampling locations at different magnetic field amplitudes are chosen for this replica on the same cavity for later power loss calculation. We also show that application of the replica followed by rinsing does not adversely affect the cavity performance.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2012

Small Angle Neutron Scattering

Small Angle Neutron Scattering (SANS) probes structural details at the nanometer scale in a non-destructive way. This article gives an introduction to scientists who have no prior small-angle scattering knowledge, but who seek a technique that allows elucidating structural information in challenging situations that thwart approaches by other methods. SANS is applicable to a wide variety of materials including metals and alloys, ceramics, concrete, glasses, polymers, composites and biological materials. Isotope and magnetic interactions provide unique methods for labeling and contrast variation to highlight specific structural features of interest. In situ studies of a material s responses to temperature, pressure, shear, magnetic and electric fields, etc., are feasible as a result of the high penetrating power of neutrons. SANS provides statistical information on significant structural features averaged over the probed sample volume, and one can use SANS to quantify with high precision the structural details that are observed, for example, in electron microscopy. Neutron scattering is non-destructive; there is no need to cut specimens into thin sections, and neutrons penetrate deeply, providing information on the bulk material, free from surface effects. The basic principles of a SANS experiment are fairly simple, but the measurement, analysis and interpretation of small angle scattering data involves theoretical concepts that are unique to the technique and that are not widely known. This article includes a concise description of the basics, as well as practical know-how that is essential for a successful SANS experiment.

biomaterials↗

DOE OSTI2014

Helioseismology of pre-emerging active regions. III. Statistical analysis

The subsurface properties of active regions (ARs) prior to their appearance at the solar surface may shed light on the process of AR formation. Helioseismic holography has been applied to samples taken from two populations of regions on the Sun (pre-emergence and without emergence), each sample having over 100 members, that were selected to minimize systematic bias, as described in Paper I. Paper II showed that there are statistically significant signatures in the average helioseismic properties that precede the formation of an AR. This paper describes a more detailed analysis of the samples of pre-emergence regions and regions without emergence based on discriminant analysis. The property that is best able to distinguish the populations is found to be the surface magnetic field, even a day before the emergence time. However, after accounting for the correlations between the surface field and the quantities derived from helioseismology, there is still evidence of a helioseismic precursor to AR emergence that is present for at least a day prior to emergence, although the analysis presented cannot definitively determine the subsurface properties prior to emergence due to the small sample sizes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2015

Mechanical environmental transport of actinides and ¹³⁷Cs from an arid radioactive waste disposal site

Particulate transport represents an important mechanism for actinides and fission products at the Earth's surface; soil samples taken in the early 1970's near the Subsurface Disposal Area (SDA) at Idaho National Laboratory (INL) provide a case study for examining the mechanisms and characteristics of actinide transport under arid conditions. Transuranic waste was disposed via shallow land burial at the SDA until shortly after a flooding event that occurred in 1969. In this study we analyze soils collected in the early 1970's for ¹³⁷Cs, ²⁴¹Am, and Pu using a combination of radiometric and mass spectrometric techniques. Two distinct ²⁴⁰Pu/²³⁹Pu isotopic ratios are observed for contamination from the SDA, with values ranging from at least 0.059 to 0.069. ²⁴¹Am concentrations are observed to increase only slightly in 0-4 cm soils over the ~40 year period since soil sampling, contrary to Markham's previous hypothesis that ²⁴¹Pu is principally associated with the 0-4 cm soil fractions (Markham 1978). The lack of statistical difference in ²⁴¹Am/²³⁹⁺²⁴⁰Pu ratios with depth suggests mechanical transport and mixing discrete contaminated particles under arid conditions. Occasional samples beyond the northeastern corner are observed to contain anomalously high Pu concentrations with corresponding low ²⁴⁰Pu/²³⁹Pu atoms ratios, suggesting the occurrence of "hot particles;" application of a background Pu subtraction results in calculated Pu atom ratios for the "hot particles" which are statistically similar to those observed in the northeastern corner. Taken together, our data suggests that flooding resulted in mechanical transport of contaminated particles into the area between the SDA and the flood containment dike in the northeastern corner, following which subsequent contamination spreading resulted from wind transport of discrete particles.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1987

Spectral characteristics and the extent of paleosols of the Palouse formation

Thematic mapping data was analyzed and verified by comparison to previously gathered transect samples and to aerial photographs. A bare-soil field with exposed paleosols characterized by slight enrichment of iron was investigated. Spectral relationships were first investigated statistically by creating a data set with DN values spatially matched as nearly as possible to field sample points. Chemical data for each point included organic carbon, free iron oxide, and amorphous iron content. The chemical data, DN values, and various band ratios were examined with the program package Statistix in order to find the combinations of reflectance data most likely to show a relationship which would dependably separate the exposed paleosols from the other soils. Cluster analysis and Fastclas classification procedures were applied to the most promising of the band ratio combinations.

Frazier, B. E.↗

DOE OSTI2022

Translation and rotation equivariant normalizing flow (TRENF) for optimal cosmological analysis

ABSTRACT Our Universe is homogeneous and isotropic, and its perturbations obey translation and rotation symmetry. In this work, we develop translation and rotation equivariant normalizing flow (TRENF), a generative normalizing flow (NF) model which explicitly incorporates these symmetries, defining the data likelihood via a sequence of Fourier space-based convolutions and pixel-wise non-linear transforms. TRENF gives direct access to the high dimensional data likelihood p(x|y) as a function of the labels y, such as cosmological parameters. In contrast to traditional analyses based on summary statistics, the NF approach has no loss of information since it preserves the full dimensionality of the data. On Gaussian random fields, the TRENF likelihood agrees well with the analytical expression and saturates the Fisher information content in the labels y. On non-linear cosmological overdensity fields from N-body simulations, TRENF leads to significant improvements in constraining power over the standard power spectrum summary statistic. TRENF is also a generative model of the data, and we show that TRENF samples agree well with the N-body simulations it trained on, and that the inverse mapping of the data agrees well with a Gaussian white noise both visually and on various summary statistics: when this is perfectly achieved the resulting p(x|y) likelihood analysis becomes optimal. Finally, we develop a generalization of this model that can handle effects that break the symmetry of the data, such as the survey mask, which enables likelihood analysis on data without periodic boundaries.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2013

SPECTROSCOPY OF THE LARGEST EVER {gamma}-RAY-SELECTED BL LAC SAMPLE

We report on spectroscopic observations covering most of the 475 BL Lacs in the second Fermi Large Area Telescope (LAT) catalog of active galactic nuclei (AGNs). Including archival measurements (correcting several erroneous literature values) we now have spectroscopic redshifts for 44% of the BL Lacs. We establish firm lower redshift limits via intervening absorption systems and statistical lower limits via searches for host galaxies for an additional 51% of the sample leaving only 5% of the BL Lacs unconstrained. The new redshifts raise the median spectroscopic z-tilde from 0.23 to 0.33 and include redshifts as large as z = 2.471. Spectroscopic redshift minima from intervening absorbers have z-tilde = 0.70, showing a substantial fraction at large z and arguing against strong negative evolution. We find that detected BL Lac hosts are bright ellipticals with black hole masses M {sub .} {approx} 10{sup 8.5} - 10{sup 9}, substantially larger than the mean of optical AGNs and LAT Flat Spectrum Radio Quasar samples. A slow increase in M {sub .} with z may be due to selection bias. We find that the power-law dominance of the optical spectrum extends to extreme values, but this does not strongly correlate with the {gamma}-ray properties, suggesting that strong beaming is the primary cause of the range in continuum dominance.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1977

Crop identification and area estimation over large geographic areas using LANDSAT MSS data

The author has identified the following significant results. LANDSAT MSS data was adequate to accurately identify wheat in Kansas; corn and soybean estimates in Indiana were less accurate. Computer-aided analysis techniques were effectively used to extract crop identification information from LANDSAT data. Systematic sampling of entire counties made possible by computer classification methods resulted in very precise area estimates at county, district, and state levels. Training statistics were successfully extended from one county to other counties having similar crops and soils if the training areas sampled the total variation of the area to be classified.

Bauer, M. E.↗

DOE OSTI2016

Characterization of microbial associations with methanotrophic archaea and sulfate-reducing bacteria through statistical comparison of nested Magneto-FISH enrichments

Methane seep systems along continental margins host diverse and dynamic microbial assemblages, sustained in large part through the microbially mediated process of sulfate-coupled Anaerobic Oxidation of Methane (AOM). This methanotrophic metabolism has been linked to consortia of anaerobic methane-oxidizing archaea (ANME) and sulfate-reducing bacteria (SRB). These two groups are the focus of numerous studies; however, less is known about the wide diversity of other seep associated microorganisms. We selected a hierarchical set of FISH probes targeting a range of Deltaproteobacteria diversity. Using the Magneto-FISH enrichment technique, we then magnetically captured CARD-FISH hybridized cells and their physically associated microorganisms from a methane seep sediment incubation. DNA from nested Magneto-FISH experiments was analyzed using Illumina tag 16S rRNA gene sequencing (iTag). Enrichment success and potential bias with iTag was evaluated in the context of full-length 16S rRNA gene clone libraries, CARD-FISH, functional gene clone libraries, and iTag mock communities. We determined commonly used Earth Microbiome Project (EMP) iTAG primers introduced bias in some common methane seep microbial taxa that reduced the ability to directly compare OTU relative abundances within a sample, but comparison of relative abundances between samples (in nearly all cases) and whole community-based analyses were robust. The iTag dataset was subjected to statistical co-occurrence measures of the most abundant OTUs to determine which taxa in this dataset were most correlated across all samples. In addition, many non-canonical microbial partnerships were statistically significant in our co-occurrence network analysis, most of which were not recovered with conventional clone library sequencing, demonstrating the utility of combining Magneto-FISH and iTag sequencing methods for hypothesis generation of associations within complex microbial communities. Network analysis pointed to many co-occurrences containing putatively heterotrophic, candidate phyla such as OD1, Atribacteria , MBG-B, and Hyd24-12 and the potential for complex sulfur cycling involving Epsilon -, Delta -, and Gammaproteobacteria in methane seep ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2014

The AstraLux multiplicity survey: Extension to late M-dwarfs

The distribution of multiplicity among low-mass stars is a key issue to understanding the formation of stars and brown dwarfs, and recent surveys have yielded large enough samples of nearby low-mass stars to study this issue statistically to good accuracy. Previously, we have presented a multiplicity study of ∼700 early/mid M-type stars observed with the AstraLux high-resolution Lucky Imaging cameras. Here, we extend the study of multiplicity in M-type stars through studying 286 nearby mid/late M-type stars, bridging the gap between our previous study and multiplicity studies of brown dwarfs. Most of the targets have been observed more than once, allowing us to assess common proper motion to confirm companionship. We detect 68 confirmed or probable companions in 66 systems, of which 41 were previously undiscovered. Detections are made down to the resolution limit of ∼100 mas of the instrument. The raw multiplicity in the AstraLux sensitivity range is 17.9%, leading to a total multiplicity fraction of 21%-27% depending on the mass ratio distribution, which is consistent with being flat down to mass ratios of ∼0.4, but cannot be stringently constrained below this value. The semi-major axis distribution is well represented by a log-normal function with μ{sub a} = 0.78 and σ{sub a} = 0.47, which is narrower and peaked at smaller separations than for a Sun-like sample. This is consistent with a steady decrease in average semi-major axis from the highest-mass binary stars to the brown dwarf binaries.

79 ASTRONOMY AND ASTROPHYSICS↗