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At least 1,495 records · Page 83
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

LOG-NORMAL DISTRIBUTION OF COSMIC VOIDS IN SIMULATIONS AND MOCKS

Following up on previous studies, we complete here a full analysis of the void size distributions of the Cosmic Void Catalog based on three different simulation and mock catalogs: dark matter (DM), haloes, and galaxies. Based on this analysis, we attempt to answer two questions: Is a three-parameter log-normal distribution a good candidate to satisfy the void size distributions obtained from different types of environments? Is there a direct relation between the shape parameters of the void size distribution and the environmental effects? In an attempt to answer these questions, we find here that all void size distributions of these data samples satisfy the three-parameter log-normal distribution whether the environment is dominated by DM, haloes, or galaxies. In addition, the shape parameters of the three-parameter log-normal void size distribution seem highly affected by environment, particularly existing substructures. Therefore, we show two quantitative relations given by linear equations between the skewness and the maximum tree depth, and between the variance of the void size distribution and the maximum tree depth, directly from the simulated data. In addition to this, we find that the percentage of voids with nonzero central density in the data sets has a critical importance. If the number of voids with nonzero central density reaches ≥3.84% in a simulation/mock sample, then a second population is observed in the void size distributions. This second population emerges as a second peak in the log-normal void size distribution at larger radius.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

A machine learning approach to emulation and biophysical parameter estimation with the Community Land Model, version 5

Abstract. Land models are essential tools for understanding and predicting terrestrial processes and climate–carbon feedbacks in the Earth system, but uncertainties in their future projections are poorly understood. Improvements in physical process realism and the representation of human influence arguably make models more comparable to reality but also increase the degrees of freedom in model configuration, leading to increased parametric uncertainty in projections. In this work we design and implement a machine learning approach to globally calibrate a subset of the parameters of the Community Land Model, version 5 (CLM5) to observations of carbon and water fluxes. We focus on parameters controlling biophysical features such as surface energy balance, hydrology, and carbon uptake. We first use parameter sensitivity simulations and a combination of objective metrics including ranked global mean sensitivity to multiple output variables and non-overlapping spatial pattern responses between parameters to narrow the parameter space and determine a subset of important CLM5 biophysical parameters for further analysis. Using a perturbed parameter ensemble, we then train a series of artificial feed-forward neural networks to emulate CLM5 output given parameter values as input. We use annual mean globally aggregated spatial variability in carbon and water fluxes as our emulation and calibration targets. Validation and out-of-sample tests are used to assess the predictive skill of the networks, and we utilize permutation feature importance and partial dependence methods to better interpret the results. The trained networks are then used to estimate global optimal parameter values with greater computational efficiency than achieved by hand tuning efforts and increased spatial scale relative to previous studies optimizing at a single site. By developing this methodology, our framework can help quantify the contribution of parameter uncertainty to overall uncertainty in land model projections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Small scatter and nearly isothermal mass profiles to four half-light radii from two-dimensional stellar dynamics of early-type galaxies

We study the total mass–density profile for a sample of 14 fast-rotator early-type galaxies (stellar masses 10.2≲logM{sub ∗}/M{sub ⊙}≲11.7). We combine observations from the SLUGGS and ATLAS{sup 3D} surveys to map out the stellar kinematics in two dimensions, out to a median radius for the sample of four half-light radii R{sub e} (or 10 kpc) and a maximum radius of 2.0–6.2 R{sub e} (or 4–21 kpc). We use axisymmetric dynamical models based on the Jeans equations, which allow for a spatially varying anisotropy; employ quite general profiles for the dark halos; and, in particular, do not place any restrictions on the profile slope. This is made possible by the availability of spatially extended two-dimensional kinematics. We find that our relatively simple models provide a remarkably good description of the observed kinematics. The resulting total density profiles are well described by a nearly isothermal power law ρ{sub tot}(r)∝r{sup −γ} from R{sub e}/10 to at least 4R{sub e}, the largest average deviation being 11%. The average logarithmic slope is 〈γ〉=2.19±0.03 with observed rms scatter of just σ{sub γ}=0.11. This scatter out to large radii, where dark matter dominates, is as small as previously reported by lensing studies around r ≈ R{sub e}/2, where the stars dominate. Our bulge–halo conspiracy places much tighter constraints on galaxy formation models. It illustrates the power of two-dimensional stellar kinematics observations at large radii. It is now important to test the generality of our results for different galaxy types and larger samples.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Self-consistent drift-diffusion-reaction model for the electron beam interaction with dielectric samples

The charging of insulating samples degrades the quality and complicates the interpretation of images in scanning electron microscopy and is important in other applications, such as particle detectors. In this paper, we analyze this nontrivial phenomenon on different time scales employing the drift-diffusion-reaction approach augmented with the trapping rate equations and a realistic semi-empirical source function describing the pulsed nature of the electron beam. We consider both the fast processes following the impact of a single primary electron, the slower dynamics resulting from the continuous bombardment of a sample, and the eventual approach to the steady-state regime.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Efficient Probabilistic Prediction and Uncertainty Quantification of Tropical Cyclone–Driven Storm Tides and Inundation

Abstract This study proposes and assesses a methodology to obtain high-quality probabilistic predictions and uncertainty information of near-landfall tropical cyclone–driven (TC-driven) storm tide and inundation with limited time and resources. Forecasts of TC track, intensity, and size are perturbed according to quasi-random Korobov sequences of historical forecast errors with assumed Gaussian and uniform statistical distributions. These perturbations are run in an ensemble of hydrodynamic storm tide model simulations. The resulting set of maximum water surface elevations are dimensionality reduced using Karhunen–Loève expansions and then used as a training set to develop a polynomial chaos (PC) surrogate model from which global sensitivities and probabilistic predictions can be extracted. The maximum water surface elevation is extrapolated over dry points incorporating energy head loss with distance to properly train the surrogate for predicting inundation. We find that the surrogate constructed with third-order PCs using elastic net penalized regression with leave-one-out cross validation provides the most robust fit across training and test sets. Probabilistic predictions of maximum water surface elevation and inundation area by the surrogate model at 48-h lead time for three past U.S. landfalling hurricanes (Irma in 2017, Florence in 2018, and Laura in 2020) are found to be reliable when compared to best track hindcast simulation results, even when trained with as few as 19 samples. The maximum water surface elevation is most sensitive to perpendicular track-offset errors for all three storms. Laura is also highly sensitive to storm size and has the least reliable prediction. Significance Statement The purpose of this study is to develop and evaluate a methodology that can be used to provide high-quality probabilistic predictions of hurricane-induced storm tide and inundation with limited time and resources. This is important for emergency management purposes during or after the landfall of hurricanes. Our results show that sampling forecast errors using quasi-random sequences combined with machine learning techniques that fit polynomial functions to the data are well suited to this task. The polynomial functions also have the benefit of producing exact sensitivity indices of storm tide and inundation to the forecasted hurricane properties such as path, intensity, and size, which can be used for uncertainty estimation. The code implementing the presented methodology is publicly available on GitHub.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2019

Microarcsecond VLBI Pulsar Astrometry with PSRπ II. Parallax Distances for 57 Pulsars

We present the results of PSRπ, a large astrometric project targeting radio pulsars using the Very Long Baseline Array (VLBA). From our astrometric database of 60 pulsars, we have obtained parallax-based distance measurements for all but 3, with a parallax precision that is typically ∼45 μas and approaches 10 μas in the best cases. Our full sample doubles the number of radio pulsars with a reliable (≳5σ) model-independent distance constraint. Importantly, many of the newly measured pulsars are well outside the solar neighborhood, and so PSRπ brings a near-tenfold increase in the number of pulsars with a reliable model-independent distance at d > 2 kpc. Our results show that both widely used Galactic electron density distribution models contain significant shortcomings, particularly at high Galactic latitudes. When comparing our results to pulsar timing, two of the four millisecond pulsars in our sample exhibit significant discrepancies in their proper motion estimates. With additional VLBI observations that extend our sample and improve the absolute positional accuracy of our reference sources, we will be able to additionally compare pulsar absolute reference positions between VLBI and timing, which will provide a much more sensitive test of the correctness of the solar system ephemerides used for pulsar timing. Finally, we use our large sample to estimate the typical accuracy attainable for differential VLBA astrometry of pulsars, showing that for sufficiently bright targets observed eight times over 18 months, a parallax uncertainty of 4 μas per arcminute of separation between the pulsar and calibrator can be expected.

A. T. Deller↗
NASA NTRS2020

Designing an Optimal Ensemble Strategy for GMAO S2S Forecast System

GMAO Sub/Seasonal prediction system (S2S) is being readied for a major upgrade to GEOS-S2S Version 3. An important factor in successful extended range forecast is the definition of an ensemble For initialization of the ensemble we propose a combination of lagged and burst initial conditions. We plan to run a relatively large ensemble of 40 members for sub-seasonal forecast (up to 3 months), at which point we sub-sample the ensemble, and continue the forecast with 10 members (up to 12 months). Here we present the results of the extensive testing of various ways to generate the perturbations to the initial conditions and the validation of the stratified sampling strategy we chose.To generate perturbations for the burst ensemble members we used scaled differences of pairs of analysis states separated by 1-10 days, randomly chosen from a corresponding season. We considered perturbing separately only the atmospheric fields or only the ocean or both of the forecast initial conditions. Considering varying separation times between the analysis states, we were able to produce perturbations sampling various modes of variability. Focusing on the ENSO SST indices, we found that all types of perturbations are important for the ensemble spread.Our ensemble size for sub-seasonal forecasts was determined as to maximize the skill of predicting some of the leading modes of boreal winter atmospheric modes, NAO, PNA and AO. It is not feasible to run equally large ensemble for seasonal forecasts. Using a stratified sampling procedure we can identify the emerging directions of error growth. By comparing the stratified ensemble with randomly sampled ensemble of the same size, we were able to show that the former better estimates the mean of the original large ensemble.

Borovikov, Anna↗
DOE OSTI2023

Predicting rare events using neural networks and short-trajectory data

Estimating the likelihood, timing, and nature of events is a major goal of modeling stochastic dynamical systems. When the event is rare in comparison with the timescales of simulation and/or measurement needed to resolve the elemental dynamics, accurate prediction from direct observations becomes challenging. In such cases a more effective approach is to cast statistics of interest as solutions to Feynman-Kac equations (partial differential equations). Here, we develop an approach to solve Feynman-Kac equations by training neural networks on short-trajectory data. Our approach is based on a Markov approximation but otherwise avoids assumptions about the underlying model and dynamics. This makes it applicable to treating complex computational models and observational data. Additionally, we illustrate the advantages of our method using a low-dimensional model that facilitates visualization, and this analysis motivates an adaptive sampling strategy that allows on-the-fly identification of and addition of data to regions important for predicting the statistics of interest. Finally, we demonstrate that we can compute accurate statistics for a 75-dimensional model of sudden stratospheric warming. This system provides a stringent test bed for our method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Provenance information as a tool for addressing engineered nanoparticle reproducibility challenges

Nanoparticles of various types are of increasing research and technological importance in biological and other applications. Difficulties in the production and delivery of nanoparticles with consistent and well defined properties appear in many forms and have a variety of causes. Among several issues are those associated with incomplete information about the history of particles involved in research studies including the synthesis method, sample history after synthesis including time and nature of storage and the detailed nature of any sample processing or modification. In addition, the tendency of particles to change with time or environmental condition suggests that the time between analysis and application is important and some type of consistency or verification process can be important. The essential history of a set of particles can be identified as provenance information tells the origin or source of a batch of nano-objects along with information related to handling and any changes that may have taken place since it was originated. A record of sample provenance information for a set of particles can play a useful role in identifying some of the sources and decreasing the extent of particle variability and the observed lack of reproducibility observed by many researchers.

Environmental Molecular Sciences Laboratory↗
NASA NTRS2002

Assessment of Air Quality in the International Space Station (ISS) and Space Shuttle Based on Samples Returned Aboard STS-110 (ISS-8A) in April 2002

The toxicological assessment of grab sample canisters (GSCs) returned aboard STS-110 is reported. Analytical methods have not changed from earlier reports, and surrogate standard recoveries from the GSCs were 77-121%, with one exception. Pressure tracking indicated no leaks in the canisters. Recoveries from lab and trip controls for formaldehyde analyses ranged from 87 to 96%. The two general criteria used to assess air quality are the total-non-methane-volatile organic hydrocarbons (NMVOCs) and the total T-value (minus the CO2 and formaldehyde contributions). Because of the inertness of Freon 218 (octafluoropropane, OFP), its contribution to the NMVOC is subtracted and tabulated separately. Control of atmospheric alcohols is important to the water recovery system engineers, hence total alcohols are also shown for each sample. Because formaldehyde is quantified from sorbent badges, its concentration is listed separately. These five indices of air quality are summarized.

James, John T.↗
DOE OSTI2018

Eco-friendly and effective strategy to synthesize ZnO/Ag{sub 2}O heterostructures and its excellent photocatalytic property under visible light

Highlights: • ZnO/Ag{sub 2}O photocatalysts with heterostructures were synthesized via a facile mechanochemical method. • The synthetic process does not involve any organic solvents and the reaction matrix can be recycled easily. • The synthetic method is gram-scale, and we can easily and routinely scale up this process to produce grams of the heterostructure nanomaterials. • The as-prepared samples without post-calcination show a high degree of crystallinity. - Abstract: ZnO/Ag{sub 2}O photocatalysts with heterostructure were synthesized by a green and effective mechanochemical method. The preparation process was taken in solid state at room temperature with a short grinding time. The as-made products showed a high degree of crystallinity without post-calcination treatment. Such synthetic method does not involve any organic solvents and the reaction matrix can be recycled. The as-prepared ZnO/Ag{sub 2}O samples show excellent photocatalytic activity and photostability for degradation of different organic dyes under visible light. The content of Ag{sub 2}O plays an important role in the photocatalytic activity, which can be tuned by the precursor AgNO{sub 3}. The photodegradation rate constant (k) of the optimal ZnO/Ag{sub 2}O sample under visible light is nearly 0.1004 min{sup −1} for methylene blue (MB), 0.063 min{sup −1} for rhodamine B (RHB) and 0.07 min{sup −1} for methyl orange (MO), which are much better than the pure ZnO (0.0075 min{sup −1}). The enhancement of the visible light photocatalytic activity could be attributed to the heterojunction interfaces induced by the match of crystal lattice and energy band between the Ag{sub 2}O and ZnO. The Ag{sub 2}O generates the excited-state electrons under visible light irradiation. The excited electrons on Ag{sub 2}O could directly transfer to the conduction band (CB) of ZnO, making ZnO/Ag{sub 2}O present remarkable visible light photocatalytic activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRSDate not supplied

Large Scale Transcriptional Analysis of Legacy Spaceflight Tissues from the NASA Institutional Scientific Collection

The NASA Institutional Scientific Collection (ISC) has amassed a collection of valuable space biology samples spanning from early Space Shuttle missions to recent missions on the International Space Station (ISS). However, the full potential of this archive has not been realized, with many samples having been stored for decades without being re-accessed. Given the pace of analytical advancement since the ISC began accumulating samples, we undertook a systematic transcriptional analysis of these samples to reveal additional patterns that may have been missed during the original investigations. We selected 93 mouse and rat samples from 5 separate Space Shuttle, ISS and ground-analogue studies with a focus on muscle, spleen and thymus tissues to allow identification of important changes related to musculoskeletal unloading and immune function. RNA extracted from these tissues was consistently of a quality and we are now generating transcriptional profiling data from sample set. This resulting data will be immediately released through the GeneLab data systems for open analysis by the space biology community. While this study will stand on its own, it will also serve as a model for future, comprehensive, analyses of the ISC.

Rodent↗
DOE OSTI2016

The Two-Column Aerosol Project: Phase I-Overview and impact of elevated aerosol layers on aerosol optical depth

The Two-Column Aerosol Project (TCAP), conducted from June 2012 through June 2013, was a unique study designed to provide a comprehensive data set that can be used to investigate a number of important climate science questions, including those related to aerosol mixing state and aerosol radiative forcing. The study was designed to sample the atmosphere between and within two atmospheric columns; one fixed near the coast of North America (over Cape Cod, MA) and a second moveable column over the Atlantic Ocean several hundred kilometers from the coast. The U.S. Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF) was deployed at the base of the Cape Cod column, and the ARM Aerial Facility was utilized for the summer and winter intensive observation periods. One important finding from TCAP is that four of six nearly cloud-free flight days had aerosol layers aloft in both the Cape Cod and maritime columns that were detected using the nadir pointing second-generation NASA high-spectral resolution lidar (HSRL-2). In addition, these layers contributed up to 60% of the total observed aerosol optical depth (AOD). Many of these layers were also intercepted by the aircraft configured for in situ sampling, and the aerosol in the layers was found to have increased amounts of biomass burning material and nitrate compared to aerosol found near the surface. Lastly, while there was a great deal of spatial and day-to-day variability in the aerosol chemical composition and optical properties, no systematic differences between the two columns were observed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Quantum advantages for Pauli channel estimation

We show that entangled measurements provide an exponential advantage in sample complexity for Pauli channel estimation, which is both a fundamental problem and a practically important subroutine for benchmarking near-term quantum devices. The specific task we consider is to simultaneously learn all the eigenvalues of an n-qubit Pauli channel to ±ε precision. We give an estimation protocol with an n-qubit ancilla that succeeds with high probability using only O(n/ε 2 ) copies of the Pauli channel, while proving that any ancilla-free protocol (possibly with adaptive control and channel concatenation) would need at least Ω(2 n/3 ) rounds of measurement. We further study the advantages provided by a small number of ancillas. For the case that a k-qubit ancilla (k≤n) is available, we obtain a sample complexity lower bound of Ω(2 (n-k)/3 ) for any nonconcatenating protocol, and a stronger lower bound of Ω(n 2n-k ) for any nonadaptive, nonconcatenating protocol, which is shown to be tight. We also show how to apply the ancilla-assisted estimation protocol to a practical quantum benchmarking task in a noise-resilient and sample-efficient manner, given reasonable noise assumptions. Our results provide a practically interesting example for quantum advantages in learning and also bring insights for quantum benchmarking.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2017

NASA-STD-6001B Test 1 Upward Flame Propagation; Sample Length Impact on MOC Investigation

Understanding the combustion behavior of materials in the elevated oxygen environments of habitable spacecraft is of utmost importance to crew safety and mission success. Currently, certification for unrestricted flight usage of a material with respect to flammability involves passing the Upward Flame Propagation Test of NASA-STD-6001B (Test 1). This test evaluates materials in a standardized test configuration for two failure criteria: self-extinguishment within 15 cm (6 in.) and the propensity of flame propagation by means of flaming material transfer. By the NASA standard, full-length samples are 30 cm (12 in.) in length; however, factors independent of the test method such as limited material availability or various nonstandard test configurations limit the full pretest sample lengths available for test. This paper characterizes the dependence, if any, of pretest sample length on NASA-STD-6001B Test 1 results. Testing was performed using the Maximum Oxygen Concentration (MOC) Threshold Method to obtain a data set for each sample length tested. In addition, various material types, including cloth (Nomex), foam (TA-301) and solids (Ultem), were tested to investigate potential effects of test specimen types. Though additional data needs to be generated to provide statistical confidence, preliminary findings are that use of variable sample lengths has minimal impact on NASA-STD-6001B flammability performance and MOC determination.

Harper, Susana Tapia↗
NASA NTRS1976

Small Particle Pollutants

NASA and the EPA are cooperating to measure particle size of all elements in aerosols from airports, coal-fired power stations, municipal waste incinerators, and other combustion aerosol sources. Langley intends to sample the air using its proton-induced x-ray emission technique initially developed to determine aerosols in jet-engine exhaust. Proton technique is important because no other rapid, nondestructive method now exists for measuring trace element compositions of massive amounts of air. Method can also analyze human tissue and hair samples to determine exposure to toxic elements.

Source record↗
NASA NTRS1989

Non-Contact Temperature Requirements (NCTM) for drop and bubble physics

Many of the materials research experiments to be conducted in the Space Processing program require a non-contaminating method of manipulating and controlling weightless molten materials. In these experiments, the melt is positioned and formed within a container without physically contacting the container's wall. An acoustic method, which was developed by Professor Taylor G. Wang before coming to Vanderbilt University from the Jet Propulsion Laboratory, has demonstrated the capability of positioning and manipulating room temperature samples. This was accomplished in an earth-based laboratory with a zero-gravity environment of short duration. However, many important facets of high temperature containerless processing technology have not been established yet, nor can they be established from the room temperature studies, because the details of the interaction between an acoustic field an a molten sample are largely unknown. Drop dynamics, bubble dynamics, coalescence behavior of drops and bubbles, electromagnetic and acoustic levitation methods applied to molten metals, and thermal streaming are among the topics discussed.

Hmelo, Anthony B.↗
NASA NTRS1989

Chemistry and petrology of Apollo 17 highland coarse fines - Plutonic and melt rocks

A suite of 21 fragments from the Apollo 17 coarse-fines consists of ferroan anorthosites, anorthositic gabbros, granulitic and regolith breccias, and impact melts. These samples belong to known petrographic and chemical groups. Three ferroan anorthosites were found, including one which appears to be the lowest in REE (La = 0.60X) and probably the purest of the Apollo 17 anorthosites identified thus far. The ferroan suite is a more important component at the Apollo 17 site than previously recognized. The Apollo 17 melt rocks are similar to other samples with LKFM and low-K KREEP compositions and show less diversity in trace elements (REE) than the Apollo 15 melt rocks. Apollo 17 melt rocks consist of aphanitic and poikilitic types that show some compositional variability with identical Ni/Ir, suggesting that either two distinct melt sheets formed by similar projectiles, or compositional heterogeneity within one melt sheet is possible.

Laul, J. C.↗