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At least 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Bayesian Analysis of the Power Spectrum of the Cosmic Microwave Background

There is a wealth of cosmological information encoded in the spatial power spectrum of temperature anisotropies of the cosmic microwave background. The sky, when viewed in the microwave, is very uniform, with a nearly perfect blackbody spectrum at 2.7 degrees. Very small amplitude brightness fluctuations (to one part in a million!!) trace small density perturbations in the early universe (roughly 300,000 years after the Big Bang), which later grow through gravitational instability to the large-scale structure seen in redshift surveys... In this talk, I will discuss a Bayesian formulation of this problem; discuss a Gibbs sampling approach to numerically sampling from the Bayesian posterior, and the application of this approach to the first-year data from the Wilkinson Microwave Anisotropy Probe. I will also comment on recent algorithmic developments for this approach to be tractable for the even more massive data set to be returned from the Planck satellite.

Bayesian inference↗
NASA NTRS2009

Lossless Astronomical Image Compression and the Effects of Random Noise

In this paper we compare a variety of modern image compression methods on a large sample of astronomical images. We begin by demonstrating from first principles how the amount of noise in the image pixel values sets a theoretical upper limit on the lossless compression ratio of the image. We derive simple procedures for measuring the amount of noise in an image and for quantitatively predicting how much compression will be possible. We then compare the traditional technique of using the GZIP utility to externally compress the image, with a newer technique of dividing the image into tiles, and then compressing and storing each tile in a FITS binary table structure. This tiled-image compression technique offers a choice of other compression algorithms besides GZIP, some of which are much better suited to compressing astronomical images. Our tests on a large sample of images show that the Rice algorithm provides the best combination of speed and compression efficiency. In particular, Rice typically produces 1.5 times greater compression and provides much faster compression speed than GZIP. Floating point images generally contain too much noise to be effectively compressed with any lossless algorithm. We have developed a compression technique which discards some of the useless noise bits by quantizing the pixel values as scaled integers. The integer images can then be compressed by a factor of 4 or more. Our image compression and uncompression utilities (called fpack and funpack) that were used in this study are publicly available from the HEASARC web site.Users may run these stand-alone programs to compress and uncompress their own images.

Pence, William↗
NASA NTRS2008

NASA Tech Briefs, August 2008

Customizable Digital Receivers for Radar Two-Camera Acquisition and Tracking of a Flying Target Visual Data Analysis for Satellites A Data Type for Efficient Representation of Other Data Types Hand-Held Ultrasonic Instrument for Reading Matrix Symbols Broadband Microstrip-to-Coplanar Strip Double-Y Balun A Topographical Lidar System for Terrain-Relative Navigation Programmable Low-Voltage Circuit Breaker and Tester Electronic Switch Arrays for Managing Microbattery Arrays Topics covered include: Lower-Dark-Current, Higher-Blue-Response CMOS Imagers; Fabricating Large-Area Sheets of Single-Layer Graphene by CVD; Support for Diagnosis of Custom Computer Hardware; Providing Goal-Based Autonomy for Commanding a Spacecraft; Dynamic Method for Identifying Collected Sample Mass; Optimal Planning and Problem-Solving; Attitude-Control Algorithm for Minimizing Maneuver Execution Errors; Grants Document-Generation System; Heat-Storage Modules Containing LiNO3 3H2O and Graphite Foam; Precipitation-Strengthened, High-Temperature, High-Force Shape Memory Alloys; Improved Relief Valve Would Be Less Susceptible to Failure; Safety Modification of Cam-and-Groove Hose Coupling; Using Composite Materials in a Cryogenic Pump; Using Electronic Noses to Detect Tumors During Neurosurgery; Producing Newborn Synchronous Mammalian Cells; Smaller, Lower-Power Fast-Neutron Scintillation Detectors; Rotationally Vibrating Electric-Field Mill; Estimating Hardness from the USDC Tool-Bit Temperature Rise; Particle-Charge Spectrometer; Automated Production of Movies on a Cluster of Computers; FIDO-Class Development Rover; and Tone-Based Command of Deep Space Probes Using Ground Antennas.

Source record↗
NASA NTRS2009

Distinguishing non-resonant four-wave-mixing noise in coherent stokes and anti-stokes Raman scattering

A method of examining a sample comprises exposing the sample to a pump pulse of electromagnetic radiation for a first period of time, exposing the sample to a stimulant pulse of electromagnetic radiation for a second period of time which overlaps in time with at least a portion of the first exposing, to produce a signal pulse of electromagnetic radiation for a third period of time, and interfering the signal pulse with a reference pulse of electromagnetic radiation, to determine which portions of the signal pulse were produced during the exposing of the sample to the stimulant pulse. The first and third periods of time are each greater than the second period of time.

Marks, Daniel L.↗
NASA NTRS2009

Nonlinear interferometric vibrational imaging

A method of examining a sample, which includes: exposing a reference to a first set of electromagnetic radiation, to form a second set of electromagnetic radiation scattered from the reference; exposing a sample to a third set of electromagnetic radiation to form a fourth set of electromagnetic radiation scattered from the sample; and interfering the second set of electromagnetic radiation and the fourth set of electromagnetic radiation. The first set and the third set of electromagnetic radiation are generated from a source; at least a portion of the second set of electromagnetic radiation is of a frequency different from that of the first set of electromagnetic radiation; and at least a portion of the fourth set of electromagnetic radiation is of a frequency different from that of the third set of electromagnetic radiation.

Boppart, Stephen A.↗
NASA NTRS2010

Measuring Crack Length in Coarse Grain Ceramics

Due to a coarse grain structure, crack lengths in precracked spinel specimens could not be measured optically, so the crack lengths and fracture toughness were estimated by strain gage measurements. An expression was developed via finite element analysis to correlate the measured strain with crack length in four-point flexure. The fracture toughness estimated by the strain gaged samples and another standardized method were in agreement.

Salem, Jonathan A.↗
NASA NTRS2010

Navier-Stokes Dynamics by a Discrete Boltzmann Model

This work investigates the possibility of particle-based algorithms for the Navier-Stokes equations and higher order continuum approximations of the Boltzmann equation; such algorithms would generalize the well-known Pullin scheme for the Euler equations. One such method is proposed in the context of a discrete velocity model of the Boltzmann equation. Preliminary results on shock structure are consistent with the expectation that the shock should be much broader than the near discontinuity predicted by the Pullin scheme, yet narrower than the prediction of the Boltzmann equation. We discuss the extension of this essentially deterministic method to a stochastic particle method that, like DSMC, samples the distribution function rather than resolving it completely.

Rubinstein, Robet↗
NASA NTRS2011

Methods for Radiometric Cross-Calibration of Imaging Sensors With and Without Overlapping Collections

This slide presentation reviews methods of cross calibration for imaging sensors. Cross calibration methods fall under two categories: (1) Relies on knowledge of a source that is common to both sensors, (2) Typically near-coincident views. Some work has used methods that do not require simultaneous data collections. This talk discusses the International System of Units (SI) -traceable approaches that permit cross-calibration. It describes on-orbit cross-calibration methods that are typically used, with and without overlapping views. It reviews sample results. It also describes a method without overlapping views and without on-site measurements.

Thome, K. J.↗
NASA NTRS2010

The Atacama Cosmology Telescope (ACT): Beam Profiles and First SZ Cluster Maps

The Atacama Cosmology Telescope (ACT) is currently observing the cosmic microwave background with arcminute resolution at 148 GHz, 218 GHz, and 277 GHz, In this paper, we present ACT's first results. Data have been analyzed using a maximum-likelihood map-making method which uses B-splines to model and remove the atmospheric signal. It has been used to make high-precision beam maps from which we determine the experiment's window functions, This beam information directly impacts all subsequent analyses of the data. We also used the method to map a sample of galaxy clusters via the Sunyaev-Ze1'dovich (SZ) effect, and show five clusters previously detected with X-ray or SZ observations, We provide integrated Compton-y measurements for each cluster. Of particular interest is our detection of the z = 0.44 component of A3128 and our current non-detection of the low-redshift part, providing strong evidence that the further cluster is more massive as suggested by X-ray measurements. This is a compelling example of the redshift-independent mass selection of the SZ effect.

Hincks, A. D.↗
NASA NTRS2004

Field Demonstration of DNAPL Dehalogenation Using Emulsified Zero-Valent Iron

This paper describes the results of the first field-scale demonstration conducted to evaluate the performance of nano-scale emulsified zero-valent iron (EZVI) injected into the saturated zone to enhance in situ dehalogenation of dense, non-aqueous phase liquids (DNAPLs) containing trichloroethene (TCE). EZVI is an innovative and emerging remediation technology. EZVI is a surfactant-stabilized, biodegradable emulsion that forms emulsion droplets consisting of an oil-liquid membrane surrounding zero-valent iron (ZVI) particles in water. EZVI was injected over a five day period into eight wells in a demonstration test area within a larger DNAPL source area at NASA's Launch Complex 34 (LC34) using a pressure pulse injection method. Soil and groundwater samples were collected before and after treatment and analyzed for volatile organic compounds (V005) to evaluate the changes in VOC mass, concentration and mass flux. Significant reductions in TCE soil concentrations (>80%) were observed at four of the six soil sampling locations within 90 days of EZVI injection. Somewhat lower reductions were observed at the other two soil sampling locations where visual observations suggest that most of the EZVI migrated up above the target treatment depth. Significant reductions in TCE groundwater concentrations (57 to 100%) were observed at all depths targeted with EZVI. Groundwater samples from the treatment area also showed significant increases in the concentrations of cis-1,2-dichloroethene (cDCE), vinyl chloride (VC) and ethene. The decrease in concentrations of TCE in soil and groundwater samples following treatment with EZVI is believed to be due to abiotic degradation associated with the ZVI as well as biodegradation enhanced by the presence of the oil and surfactant in the EZVI emulsion.

Quinn, Jacqueline↗
NASA NTRS2013

Estimated Probability of a Cervical Spine Injury During an ISS Mission

Introduction: The Integrated Medical Model (IMM) utilizes historical data, cohort data, and external simulations as input factors to provide estimates of crew health, resource utilization and mission outcomes. The Cervical Spine Injury Module (CSIM) is an external simulation designed to provide the IMM with parameter estimates for 1) a probability distribution function (PDF) of the incidence rate, 2) the mean incidence rate, and 3) the standard deviation associated with the mean resulting from injury/trauma of the neck. Methods: An injury mechanism based on an idealized low-velocity blunt impact to the superior posterior thorax of an ISS crewmember was used as the simulated mission environment. As a result of this impact, the cervical spine is inertially loaded from the mass of the head producing an extension-flexion motion deforming the soft tissues of the neck. A multibody biomechanical model was developed to estimate the kinematic and dynamic response of the head-neck system from a prescribed acceleration profile. Logistic regression was performed on a dataset containing AIS1 soft tissue neck injuries from rear-end automobile collisions with published Neck Injury Criterion values producing an injury transfer function (ITF). An injury event scenario (IES) was constructed such that crew 1 is moving through a primary or standard translation path transferring large volume equipment impacting stationary crew 2. The incidence rate for this IES was estimated from in-flight data and used to calculate the probability of occurrence. The uncertainty in the model input factors were estimated from representative datasets and expressed in terms of probability distributions. A Monte Carlo Method utilizing simple random sampling was employed to propagate both aleatory and epistemic uncertain factors. Scatterplots and partial correlation coefficients (PCC) were generated to determine input factor sensitivity. CSIM was developed in the SimMechanics/Simulink environment with a Monte Carlo wrapper (MATLAB) used to integrate the components of the module. Results: The probability of generating an AIS1 soft tissue neck injury from the extension/flexion motion induced by a low-velocity blunt impact to the superior posterior thorax was fitted with a lognormal PDF with mean 0.26409, standard deviation 0.11353, standard error of mean 0.00114, and 95% confidence interval [0.26186, 0.26631]. Combining the probability of an AIS1 injury with the probability of IES occurrence was fitted with a Johnson SI PDF with mean 0.02772, standard deviation 0.02012, standard error of mean 0.00020, and 95% confidence interval [0.02733, 0.02812]. The input factor sensitivity analysis in descending order was IES incidence rate, ITF regression coefficient 1, impactor initial velocity, ITF regression coefficient 2, and all others (equipment mass, crew 1 body mass, crew 2 body mass) insignificant. Verification and Validation (V&V): The IMM V&V, based upon NASA STD 7009, was implemented which included an assessment of the data sets used to build CSIM. The documentation maintained includes source code comments and a technical report. The software code and documentation is under Subversion configuration management. Kinematic validation was performed by comparing the biomechanical model output to established corridors.

Brooker, John E.↗
NASA NTRS2015

Asteroid Redirect Crewed Mission Space Suit and EVA System Maturation

The Asteroid Redirect Crewed Mission (ARCM) requires a Launch/Entry/Abort (LEA) suit capability and short duration Extra Vehicular Activity (EVA) capability from the Orion spacecraft. For this mission, the pressure garment that was selected, for both functions, is the Modified Advanced Crew Escape Suit (MACES) with EVA enhancements and the life support option that was selected is the Exploration Portable Life Support System (PLSS). The proposed architecture was found to meet the mission constraints, but much more work is required to determine the details of the required suit upgrades, the integration with the PLSS, and the rest of the tools and equipment required to accomplish the mission. This work has continued over the last year to better define the operations and hardware maturation of these systems. EVA simulations have been completed in the NBL and interfacing options have been prototyped and analyzed with testing planned for late 2014. For NBL EVA simulations, in 2013, components were procured to allow in-house build up for four new suits with mobility enhancements built into the arms. Boots outfitted with clips that fit into foot restraints have also been added to the suit and analyzed for possible loads. Major suit objectives accomplished this year in testing include: evaluation of mobility enhancements, ingress/egress of foot restraint, use of foot restraint for worksite stability, ingress/egress of Orion hatch with PLSS mockup, and testing with two crew members in the water at one time to evaluate the crew's ability to help one another. Major tool objectives accomplished this year include using various other methods for worksite stability, testing new methods for asteroid geologic sampling and improving the fidelity of the mockups and crew equipment. These tests were completed on a medium fidelity capsule mockup, asteroid vehicle mockup, and asteroid mockups that were more accurate for an asteroid type EVA than previous tests. Another focus was the design and fabrication of the interface between the MACES and the PLSS. The MACES was not designed to interface with a PLSS, hence an interface kit must accommodate the unique design qualities of the MACES and provide the necessary life support function connections to the PLSS. A prototype interface kit for MACES to PLSS has been designed and fabricated. Unmanned and manned testing of the interface will show the usability of the kit while wearing a MACES. The testing shows viability of the kit approach as well as the operations concept. The design will be vetted through suit and PLSS experts and, with the findings from the testing, the best path forward will be determined. As the Asteroid Redirect Mission matures, the suit/life support portion of the mission will mature along with it and EVA Tools & Equipment can be iterated to accommodate the overall mission objectives and compromises inherent in EVA Suit optimization. The goal of the EVA architecture for ARCM is to continue to build on the previously developed technologies and lessons learned, and accomplish the ARCM EVAs while providing a stepping stone to future missions and destinations.

Bowie, Jonathan T.↗
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 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 NTRS2015

Preparation System and Method

Systems and methods for preparing a sample for further analysis are provided. The system can include an enclosure. A membrane can be disposed within the enclosure. First and second reservoirs can be disposed within the enclosure, and at least one of the first and second reservoirs can be adapted to have a reagent disposed therein. A valve can be disposed within the enclosure and in fluid communication with the first or second reservoirs or both. The valve can also be in fluid communication with the membrane. The valve can be adapted to selectively regulate the flow of the reagent from the first reservoir, through the membrane, and into the second reservoir.

Zhang, Ye↗
NASA NTRS2018

Residual Stress Mapping of As-Built and Hot Isostatic Pressure Treated GRCop-84 as Fabricated by Selective Laser Melting

GRCop-84, a copper alloy developed by NASA Glenn Research Center (GRC) with the starting At% (atomic percent) Cu-8 Cr-4 Nb, has a copper matrix with a fine intermetallic dispersion of Cr2Nb (cubic Laves phase C15). The alloy is being developed for high-heat-flux applications and has excellent high temperature properties including retention of tensile strength at high temperatures, high thermal conductivity, and excellent creep resistance. GRCop-84 has shown higher survivability rates than other metal additive alloys, good surface finish, and requires less operator tweaking for builds, and this is not fully understood. Neutron diffraction provides an accurate, non-destructive method of measuring the thermal stresses accumulated during production; the primary source of failure before annealing. The unstressed lattice spacing (d (sub 0)), residual stress, and distribution have been characterized for simple shapes in HIP (Hot Isostatic Pressing,) and as-built conditions made with SLM (Selective Laser Melting), a powder bed fusion method, with the HIP samples showing significantly reduced stresses concentrations than the as-built.

Minnecci, Robert↗
NASA NTRS2018

Combined Error and Uncertainty Estimates for CFD Problems

Given input sources of uncertainty, non-intrusive uncertainty propagation methods quantify the uncertainty in output quantities of interest (QoI) by performing a nite number of CFD (Computational Fluid Dynamics) instance realizations needed in the calculation of output statistics. It is well known that this introduces multiple sources of error. CFD codes often utilize finite-dimensional approximation (grids, basis functions, etc.) thus incurring CFD numerical errors often approximately reinterpreted as a statistical bias. Uncertainty propagation methods calculate uncertainty statistics for output quantities of interest using a numerical method (e.g. deterministic quadrature, sampling, etc.) thus incurring UQ (Uncertainty Quantification) numerical errors. Importance of quantifying these errors in large scale scientific computing: How accurate is an output statistic?; How should additional computational resources be invested to further reduce the error in a statistic?

Posteriori↗
NASA NTRS2021

Amino Acid Abundances and Compositions in Iron and Stony-Iron Meteorites

The organic compositions of carbonaceous chondrite meteorites have been extensively studied; however, there have been fewer reports of other meteorite classes, and almost none from iron meteorites, which contain much less carbon than carbonaceous chondrites but make up ~4% of observed meteorite falls. Here, we report the bulk amino acid content of three iron meteorites (Campo del Cielo, IAB; Canyon Diablo, IAB; and Cape York, IIIAB) and both the metal and silicate portions of a pallasite (Imilac). We developed a novel method to prepare the samples for analysis, followed by hot water extraction and analysis via liquid chromatography‐mass spectrometry. Free amino acid abundances ranging from 301 to 1216 pmol/g were observed in the meteorites, with the highest abundance in the silicate portion of the pallasite. Although some of the amino acid content could be attributed to terrestrial contamination, evidence suggests that some compounds are indigenous. A suite of C(5) amino acids was observed with a distinct distribution favoring a straight chain (n‐pentanoic acid) structure; this straight chain dominance is suggestive of that observed in thermally altered stony meteorites. Amino acids were also observed in terrestrial iron granules that were milled and analyzed in the same way as the meteorites, although the distribution of detected amino acids was different. It is possible that similar formation mechanisms existed in both the meteorites and the terrestrial iron, or that observed amino acids resulted from reactions of precursors during sample preparation. This work suggests that iron meteorites should not be overlooked for contributions of amino acids and likely other soluble organic molecules to the early Earth. Future studies of iron–nickel meteorites and asteroids, such as Psyche, may provide further insights into their potential organic inventory.

Jamie E. Elsila↗