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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

Large Grooves in the South Polar Layered Deposits: Insights from Spacecraft Data and Terrestrial Analogs

The Martian polar layered deposits (PLD) are probably the best source of information about the recent climate history of Mars, but their origin and the mechanisms of accumulation are still a mystery. The polar layers are sedimentary deposits that most planetary scientists believe are composed of water ice and varying amounts of wind-blown dust, although their composition is poorly constrained. Interpretation of the observed polar stratigraphy in terms of global climate changes is complicated by the significant difference in surface ages between the north and south PLD inferred from crater statistics. The study reported here was undertaken as part of the landing site selection effort for the Mars Polar Lander (MPL) and Deep Space 2 (DS2) missions that made use of all available data. We used Mariner 9, Viking, and Mars Global Surveyor images of the south PLD in the area accessible to MPL and DS2 to evaluate the topography and morphology of grooves, terraced layers, and other features. Here we report on results from grooves that appear to have been carved by strong winds. Because these features are found throughout the interior of the PLD, where MPL and DS2 were targeted to land, their topographic characteristics were judged as important input for landing site safety assessment. The characteristics of the grooves also provide constraints and insights into aeolian processes in the polar regions and the effects these have on PLD ablation. Our results indicate that these grooves do not represent landing hazards at the scale of the images (approx. 80 m/pixel). Their topography and shape do not seem correlated with south PLD layering. No Earth analog of suitable scale exists, although the grooves bear some resemblance to smaller terrestrial deflation hollows found in soft sediment and ice. Additional information is contained in original extended abstract.

Bridges, N. T.↗
NASA NTRS2017

Results of the First Continuous Meteor Head Echo Survey at Polar Latitudes

We present the first quasi continuous meteor head echo measurements obtained during a period of over two years using the Middle Atmosphere ALOMAR Radar System (MAARSY). The measurements yield information on the altitude, trajectory, vector velocity, radar cross section, deceleration and dynamical mass of every single event. The large statistical amount of nearly one million meteor head detections provide an excellent overview of the elevation, altitude, velocity and daily count rate distributions during different times of the year at polar latitudes. Only 40 percent of the meteors were detected within the full width half maximum of the specific sporadic meteor sources. Our observation of the sporadic meteors are compared to the observations with other radar systems and a meteor input function (MIF). The best way to compare different radar systems is by comparing the radar cross section (RCS), which is the main detection criterion for each system. In this study we aim to compare our observations with a MIF, which provides information only about the meteoroid mass. Thus, we are using a statistical approach for the elevation and velocity dependent visibility and a specific mass selection. The predicted absolute count rates from the MIF are in a good agreement with the observation when it is assumed that the radar system is only sensitive to meteoroids with masses higher than one microgram. The analysis of the dynamic masses seems to be consistent with this assumption since the count rate of events with smaller masses are low and decrease even more by using events with relatively small errors.

Interplanetary dust↗
NASA NTRS1984

A general scientific information system to support the study of climate-related data

The development and use of NASA's Pilot Climate Data System (PCDS) are discussed. The PCDS is used as a focal point for managing and providing access to a large collection of actively used data for the Earth, ocean and atmospheric sciences. The PCDS provides uniform data catalogs, inventories, and access methods for selected NASA and non-NASA data sets. Scientific users can preview the data sets using graphical and statistical methods. The system has evolved from its original purpose as a climate data base management system in response to a national climate program, into an extensive package of capabilities to support many types of data sets from both spaceborne and surface based measurements with flexible data selection and analysis functions.

Treinish, L. A.↗
NASA NTRS1985

Statistics of Aeolian Surface of Mars

Aeolian control of large scale surface texture is apparent in orbiter images from selected regions of Mars -- the polar areas, equatorial canyons, and some craters. At other locations on Mars there is evidence suggesting aeolian control on meter scales within a context provided by larger landforms.

Simpson, R. A.↗
NASA NTRS1993

Discussion on selected symbiotic stars

Because of its large variety of aspects, the symbiotic phenomenon is not very suitable for a statistical treatment. It is also not clear whether symbiotic stars really represent a homogeneous group of astrophysical objects or a collection of objects of different natures but showing similar phenomena. However we are especially interested in the symbiotic phenomenon, i.e., in those physical processes occurring in the atmosphere of each individual object and in their time dependence. Such a research can be performed through the detailed analysis of individual objects. This study should be done for a time long enough to cover all the different phases of their activity, in all the spectral ranges. Since the typical time scale of the symbiotic phenomena is up to several years and decades, this represents a problem since, for instance, making astronomy outside the visual region is a quite new field of research. It was a fortunate case that a few symbiotic stars (Z And, AG Dra, CH Cyg, AX Per, and PU Vul) had undergone remarkable light variations (or 'outbursts') in recent years, which could have been followed in the space ultraviolet with IUE, and simultaneously in the optical and IR with ground-based telescopes. But, in general, the time coverage of most of the symbiotic objects is too short to have a complete picture of their behavior. In this regard, one should recall Mayall's remark about the light curve of Z And: 'Z Andromedae is another variable that shows it will require several hundred years of observations before a good analysis can be made of its variations'. This pessimistic remark should be considered as a note of caution for those involved in the interpretation of the observations. We shall discuss a number of individual symbiotic stars for which the amount of observational data is large enough to draw a rather complete picture of their general behavior and to make consistent models. We shall especially illustrate the necessary steps toward an empirical model and take the discussion of the individual objects as a useful occasion to describe different techniques of diagnosis.

Viotti, Roberto↗
NASA NTRS2010

Regression Model Term Selection for the Analysis of Strain-Gage Balance Calibration Data

The paper discusses the selection of regression model terms for the analysis of wind tunnel strain-gage balance calibration data. Different function class combinations are presented that may be used to analyze calibration data using either a non-iterative or an iterative method. The role of the intercept term in a regression model of calibration data is reviewed. In addition, useful algorithms and metrics originating from linear algebra and statistics are recommended that will help an analyst (i) to identify and avoid both linear and near-linear dependencies between regression model terms and (ii) to make sure that the selected regression model of the calibration data uses only statistically significant terms. Three different tests are suggested that may be used to objectively assess the predictive capability of the final regression model of the calibration data. These tests use both the original data points and regression model independent confirmation points. Finally, data from a simplified manual calibration of the Ames MK40 balance is used to illustrate the application of some of the metrics and tests to a realistic calibration data set.

Ulbrich, Norbert Manfred↗
NASA NTRS2008

Landing Site Dispersion Analysis and Statistical Assessment for the Mars Phoenix Lander

The Mars Phoenix Lander launched on August 4, 2007 and successfully landed on Mars 10 months later on May 25, 2008. Landing ellipse predicts and hazard maps were key in selecting safe surface targets for Phoenix. Hazard maps were based on terrain slopes, geomorphology maps and automated rock counts of MRO's High Resolution Imaging Science Experiment (HiRISE) images. The expected landing dispersion which led to the selection of Phoenix's surface target is discussed as well as the actual landing dispersion predicts determined during operations in the weeks, days, and hours before landing. A statistical assessment of these dispersions is performed, comparing the actual landing-safety probabilities to criteria levied by the project. Also discussed are applications for this statistical analysis which were used by the Phoenix project. These include using the statistical analysis used to verify the effectiveness of a pre-planned maneuver menu and calculating the probability of future maneuvers.

Bonfiglio, Eugene P.↗
NASA NTRS2013

The NuSTAR Extragalactic Survey: A First Sensitive Look at the High-Energy Cosmic X-Ray Background Population

We report on the first 10 identifications of sources serendipitously detected by the Nuclear Spectroscopic Telescope Array (NuSTAR) to provide the first sensitive census of the cosmic X-ray background source population at approximately greater than 10 keV. We find that these NuSTAR-detected sources are approximately 100 times fainter than those previously detected at approximately greater than 10 keV and have a broad range in redshift and luminosity (z = 0.020-2.923 and L(sub 10-40 keV) approximately equals 4 × 10(exp 41) - 5 × 10(exp 45) erg per second; the median redshift and luminosity are z approximately equal to 0.7 and L(sub 10-40 keV) approximately equal to 3 × 10(exp 44) erg per second, respectively. We characterize these sources on the basis of broad-band approximately equal to 0.5 - 32 keV spectroscopy, optical spectroscopy, and broad-band ultraviolet-to-mid-infrared spectral energy distribution analyses. We find that the dominant source population is quasars with L(sub 10-40 keV) greater than 10(exp 44) erg per second, of which approximately 50% are obscured with N(sub H) approximately greater than 10(exp 22) per square centimeters. However, none of the 10 NuSTAR sources are Compton thick (N(sub H) approximately greater than 10(exp 24) per square centimeters) and we place a 90% confidence upper limit on the fraction of Compton-thick quasars (L(sub 10-40 keV) greater than 10(exp 44) erg per second) selected at approximately greater than 10 keV of approximately less than 33% over the redshift range z = 0.5 - 1.1. We jointly fitted the rest-frame approximately equal to 10-40 keV data for all of the non-beamed sources with L(sub 10-40 keV) greater than 10(exp 43) erg per second to constrain the average strength of reflection; we find R less than 1.4 for gamma = 1.8, broadly consistent with that found for local active galactic nuclei (AGNs) observed at approximately greater than 10 keV. We also constrain the host-galaxy masses and find a median stellar mass of approximately 10(exp 11) solar mass, a factor approximately 5 times higher than the median stellar mass of nearby high-energy selected AGNs, which may be at least partially driven by the order of magnitude higher X-ray luminosities of the NuSTAR sources. Within the low source-statistic limitations of our study, our results suggest that the overall properties of the NuSTAR sources are broadly similar to those of nearby high-energy selected AGNs but scaled up in luminosity and mass.

Spectroscopic↗
NASA NTRS1991

Psychiatric diagnoses in a group of astronaut applicants

Between 1959 and 1987, the psychiatric evaluation of astronaut candidates evolved from a 30-h intensive examination evaluating applicants for psychopathology, and studying their performance under stress, to a 2-h clinical interview whose structure and contents were determined by the individual examiner. Evaluations done during these years applied both psychiatric (or, 'select-out') criteria and psychological (or, 'select-in') criteria. In an attempt to more rigorously define the psychiatric, 'select-out' component, a standardized, semistructured clinical interview was developed to identify the presence or history of psychiatric disorders listed in the Diagnostic and Statistical Manual of Mental Disorders, 3rd Ed. ('DSM-III'). A total of 117 astronaut applicants underwent this clinical interview as part of a comprehensive medical evaluation during a recent astronaut selection. Of the 117 applicants, 9 (7.7 percent) met DSM-III criteria for a variety of Axis I and Axis II diagnoses, including V-code diagnoses.

Santy, Patricia A.↗
DOE OSTI2023

Automated identification and calculation of prompt effects in kinetic mechanisms using statistical models

The kinetics of prompt dissociation involves rovibrationally excited species (generally formed by exothermic reactions) which may dissociate or isomerize prior to thermalization via collisions with the bath gas. Treating such rovibrationally excited species (so-called "hot" species) with standard kinetic phenomenology may result in incorrect macroscopic representation of their reactivity. Here this work presents the first fully automated methodology for the calculation of prompt effects of a chosen species in a kinetic mechanism, including (i) reaction selection; (ii) theoretical calculation of rate constants and prompt branching fractions; and (iii) final rate constant fitting. The energy partition between hot fragments is estimated using a variety of statistical models, including a new physically sound microcanonical statistical model based on the rovibrational density of states of the fragments. The methodology is validated against literature data for the prompt dissociations of HCO and C 3 H 7 radicals. The microcanonical statistical model is in better agreement with trajectory simulations for larger species and is thus applicable for practical systems that typically involve large molecules, for which direct dynamics calculations are impractical. The automated workflow is applied to the evaluation of the effects of prompt dissociation for two isomeric radicals C 4 H 7 1-3 (1-methylallyl) and C 4 H 7 1-4 (3-buten-1-yl). Twelve H-atom abstraction reactions are selected and the corresponding rate constants are computed with first principles theory. The microcanonical statistical model predicts that prompt dissociations of C 4 H 7 1-3 and C 4 H 7 1-4 are already significant at 1000K, resulting in differences of up to an order of magnitude at 2000K with respect to the phenomenological thermal rate constants. To illustrate the effects of prompt dissociation on simulations of experimental data, the calculated prompt rate constants are implemented in both CRECK and C3MechV3.3 kinetic mechanisms. Simulations of experimental flame data illustrate the noticeable impact of prompt dissociation kinetics on the high-temperature combustion reactivity of C 4 H 8 -1 and C 4 H 8 -2.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1975

Computer-aided analysis of Landsat-1 MSS data - A comparison of three approaches, including a 'modified clustering' approach

Three approaches for analyzing Landsat-1 data from Ludwig Mountain in the San Juan Mountain range in Colorado are considered. In the 'supervised' approach the analyst selects areas of known spectral cover types and specifies these to the computer as training fields. Statistics are obtained for each cover type category and the data are classified. Such classifications are called 'supervised' because the analyst has defined specific areas of known cover types. The second approach uses a clustering algorithm which divides the entire training area into a number of spectrally distinct classes. Because the analyst need not define particular portions of the data for use but has only to specify the number of spectral classes into which the data is to be divided, this classification is called 'nonsupervised'. A hybrid method which selects training areas of known cover type but then uses the clustering algorithm to refine the data into a number of unimodal spectral classes is called the 'modified-supervised' approach.

Fleming, M. D.↗
DOE OSTI2025

Using Separation-Enhanced Isotope Ratio Mass Spectrometry to Enable Increased Renewable Carbon Content in Transportation Fuels (CRADA 525)

Stable isotope ratio measurements of carbon atoms using isotope ratio mass spectrometry (IRMS) can be an effective tool for quantifying biogenic carbon in co-processed fuels, with results approaching the precision and accuracy of accelerator mass spectrometry (AMS). The lower cost of an IRMS may enable deployment to refineries, improving access and analysis turnaround times (≤2 hours), and, by extension, provide data that can allow process optimization to maximize renewable carbon in desired refinery products. This project explored the integration of chemical separation with IRMS analyses to enable highly detailed tracking of biogenic carbon into fuel product streams separated by boiling point range, chemical class, or specific compound. Forty-nine fuels and fuel components of fossil and biogenic origin, spanning gasoline and diesel boiling point ranges, were received from three refiners and were analyzed for their δ 13 C values via IRMS. Results spanned a 13 C range from ca. 10‰ to 44‰ and reflect materials derived from sustainable sources (e.g., C4 or C3 plants, animal-based pathways, syngas) or from fossil-derived fuels. Common ranges are approximately 18‰ to 9‰ and approximately 30‰ to 20‰ for C4 and C3 plants, respectively, and approximately 34‰ to 24‰ and approximately 70‰ to 33‰ for petroleum-derived fuels and methane, respectively. Fuel-like standards were developed and tested using direct-injection elemental analyzer (EA) IRMS for liquid fuels. This method was compared with the published methods, yielding statistically similar results. Four blend curve sets were produced ranging from 0% to 100% of a fuel containing biogenic carbon, focusing on 0% to 10% biogenic carbon. Linear fits were the most applicable for two of the four blend curve sets; however, two sets were found to exhibit slightly quadratic behavior, which was more pronounced in low biogenic blend samples, necessitating second-order fits. The origin of the slight quadratic behavior remains unclear; however, the discussion points to possible interpretations. CanmetENERGY thoroughly characterized a majority of the samples using one- and two-dimensional gas chromatography (GC and GC×GC, respectively) and other analyses. Selected samples were subjected to solid phase extraction (SPE) for saturate, olefin, aromatic, and polar (SOAP) analysis, and the resulting solvent-diluted fractions containing saturates and aromatics were returned to Pacific Northwest National Laboratory (PNNL), where the solvent was removed via evaporation or physical separation using GC techniques. Characterization and separations provided an understanding of saturate and aromatic content, as well as boiling point ranges for each sample and sample fraction. Samples resulting from SPE were examined using EA-IRMS and gas chromatography combustion IRMS (GC-C-IRMS) analyses. Both approaches suggest that the range in values between end-members can be increased by selecting the paraffinic or aromatic fraction of the end-member or by selecting among individual compounds resulting from GC separation of the paraffinic fractions. Considerable work remains to put these approaches into practice and statistically validate the benefit for using a fraction or individual compound over bulk analysis of a sample. However, initial results suggest that separations provide advantages for samples having blend ratios of less than 10% biogenic blendstocks. 13 C results showed statistically similar biofuel blend results to those obtained at PNNL, although additional work is needed to obtain better reproducibility. Select samples were sent to Los Alamos National Laboratory (LANL) for IRMS measurements and Beta Analytics for AMS measurements. This work suggests that IRMS and AMS yield closely comparable results and in some circumstances, IRMS could serve as a surrogate for AMS. While additional work is needed to better resolve statistical advantages for separations and better show the comparable nature of IRMS and AMS in both the biogenic carbon analysis of bulk chemical classes, initial results from this study suggest that these should be pursued in order to proliferate this approach for quantifying biogenic carbon in transportation fuels to the refinery level, thereby potentially enabling process optimization in co-processing scenarios.

09 BIOMASS FUELS↗
DOE OSTI2023

Model validation and selection in metabolic flux analysis and flux balance analysis

13C-Metabolic Flux Analysis (13C-MFA) and Flux Balance Analysis (FBA) are widely used to investigate the operation of biochemical networks in both biological and biotechnological research. Both methods use metabolic reaction network models of metabolism operating at steady state so that reaction rates (fluxes) and the levels of metabolic intermediates are constrained to be invariant. They provide estimated (MFA) or predicted (FBA) values of the fluxes through the network in vivo, which cannot be measured directly. These fluxes can shed light on basic biology and have been successfully used to inform metabolic engineering strategies. Several approaches have been taken to test the reliability of estimates and predictions from constraint-based methods and to compare alternative model architectures. Despite advances in other areas of the statistical evaluation of metabolic models, such as the quantification of flux estimate uncertainty, validation and model selection methods have been underappreciated and underexplored. We review the history and state-of-the-art in constraint-based metabolic model validation and model selection. Applications and limitations of the χ 2 -test of goodness-of-fit, the most widely used quantitative validation and selection approach in 13C-MFA, are discussed, and complementary and alternative forms of validation and selection are proposed. A combined model validation and selection framework for 13C-MFA incorporating metabolite pool size information that leverages new developments in the field is presented and advocated for. Finally, we discuss how adopting robust validation and selection procedures can enhance confidence in constraint-based modeling as a whole and ultimately facilitate more widespread use of FBA in biotechnology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Machine Learning to Select Experiments Driven by Fundamental Science and Applications for Targeted Nuclear Data Improvement

This work describes a blueprint for a process that accelerates progress in science by quantitatively answering the following question: What is the optimal combination of fundamental-science and application-driven experiments to maximally reduce pertinent data uncertainties? Answering this question entails solving a high-dimensional and complex optimization problem that is best solved with advanced statistic techniques often classified as machine learning. We apply this process within the framework of nuclear data with the aim to select an experiment combination that will reduce uncertainties in 239 Pu nuclear data for neutron energies between 1 and 600 keV. In this field, fundamental-physics driven data, called differential, look at one nuclear physics observable at a time. They are contrasted to application-driven, integral, data where one or few resulting values inform a broad set of nuclear data across several nuclides and energies. The candidates for integral experiments are criticality measurements that were refined by a genetic algorithm to be maximally sensitive to 239 Pu fission cross sections in the desired energy range. Twenty-three candidate differential experiments were investigated and span multiple nuclear physics observables (e.g., total, capture cross sections) for isotopes appearing in the integral experiments. The optimal combination among these candidate experiments was investigated via generalized least squares fitting, augmented with Gaussian processes to ameliorate statistical irregularities in data, and the D-optimality criterion. The latter evaluates for each pair of candidates the joint reduction in uncertainties of all 12200 nuclear data appearing in the integral experiments compared to the knowledge we have from 168 past experiments, theory, and nuclear data. We chose as differential measurements those that investigate 63 Cu and 239 Pu total cross sections, based on D-optimality rank and feasibility constraints. Two integral (criticality) experiments were selected: An experiment with Al 2 ⁢O 3 and graphite interleaved with Pu and a thick Cu reflector explores 1–30 keV, while we target the 30–600 keV range with an experiment that swaps boron in place of graphite with a different geometry.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

A framework to measure the properties of intergalactic metal systems with two-point flux statistics

ABSTRACT The abundance, temperature, and clustering of metals in the intergalactic medium are important parameters for understanding their cosmic evolution and quantifying their impact on cosmological analysis with the Ly α forest. The properties of these systems are typically measured from individual quasar spectra redward of the quasar’s Ly α emission line, yet that approach may provide biased results due to selection effects. We present an alternative approach to measure these properties in an unbiased manner with the two-point statistics commonly employed to quantify large-scale structure. Our model treats the observed flux of a large sample of quasar spectra as a continuous field and describes the one-dimensional, two-point statistics of this field with three parameters per ion: the abundance (column density distribution), temperature (Doppler parameter), and clustering (cloud–cloud correlation function). We demonstrate this approach on multiple ions (e.g. ${\rm C\, \small {\rm IV}}$ , ${\rm Si\, \small {\rm IV}}$ , and ${\rm Mg\, \small {\rm II}}$ ) with early data from the Dark Energy Spectroscopic Instrument (DESI) and high-resolution spectra from the literature. Our initial results show some evidence that the ${\rm C\, \small {\rm IV}}$ abundance is higher than previous measurements and evidence for abundance evolution over time. The first full year of DESI observations will have over an order of magnitude more quasar spectra than this study. In a future paper, we will use those data to measure the growth of clustering and its impact on the Ly α forest, as well as test other DESI analysis infrastructure such as the pipeline noise estimates and the resolution matrix.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2010

Analysis of Sting Balance Calibration Data Using Optimized Regression Models

Calibration data of a wind tunnel sting balance was processed using a candidate math model search algorithm that recommends an optimized regression model for the data analysis. During the calibration the normal force and the moment at the balance moment center were selected as independent calibration variables. The sting balance itself had two moment gages. Therefore, after analyzing the connection between calibration loads and gage outputs, it was decided to choose the difference and the sum of the gage outputs as the two responses that best describe the behavior of the balance. The math model search algorithm was applied to these two responses. An optimized regression model was obtained for each response. Classical strain gage balance load transformations and the equations of the deflection of a cantilever beam under load are used to show that the search algorithm s two optimized regression models are supported by a theoretical analysis of the relationship between the applied calibration loads and the measured gage outputs. The analysis of the sting balance calibration data set is a rare example of a situation when terms of a regression model of a balance can directly be derived from first principles of physics. In addition, it is interesting to note that the search algorithm recommended the correct regression model term combinations using only a set of statistical quality metrics that were applied to the experimental data during the algorithm s term selection process.

Ulbrich, N.↗
NASA NTRS2002

The Soft X-Ray Emission in a Large Sample of Galaxy Clusters with ROSAT PSPC

The study of soft X-ray emission of 38 X-ray selected galaxy clusters observed by ROSAT PSPC indicates that the soft excess phenomenon may be a common occurrence in galaxy clusters. Excess soft X-ray radiation, above the contribution from the hot intra-cluster medium, is evident in a large fraction of sources, and is clearly detected with large statistical significance in the deepest observations. The investigation relies on new, high resolution 21 cm HI observations. The sample selection also features analysis of infrared images, to further ensure reliability of results with respect to the characteristics of Galactic absorption. The possibility of background or calibration effects as cause of the excess emission is likewise investigated; a detailed analysis of the distribution of the excess emission with respect to detector position and Galactic HI column density shows that the excess emission is a genuine celestial phenomenon. We find evidence for a preferential distribution of the soft excess emission at distances larger than approx. 150-200 kpc from the centers of clusters; this behavior may be naturally explained in the context of a non-thermal Inverse-Compton scenario. Alternatively, we propose that the phenomenon maybe caused by thermal emission of very large-scale 'warm' filaments seen in recent hydrodynamic simulations. This new interpretation relieves the very demanding requirements of either the traditional intra-cluster 'warm' gas and the non-thermal scenarios. We also investigate the possibility of the soft excess originating from unresolved, X-ray faint cluster galaxies.

Bonamente, Massimiliano↗