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At least 451 records · Page 25

All sources NASA NTRS DOE OSTI

DOE OSTI2019

IR spectroscopic quantification of small molecule transport and desorption phenomena in polymers

The application, continued performance, and degradation behavior of polymers often depends on their interaction with small organic or gaseous volatiles. Understanding the underlying permeation and diffusion properties of materials is crucial for predicting their barrier properties (permeant flux), drying behavior, solvent loss or tendency to trap small molecules, as well as their interaction with materials in the vicinity due to off-gassing phenomena, perhaps leading to compatibility concerns. Further, the diffusion of low Mw organics is also important for mechanistic aspects of degradation processes. Based on our need for improved characterization methods, a FTIR-based spectroscopic gas/volatile quantification setup was designed and evaluated for determination of the diffusion, desorption and transport behavior of small IR-active molecules in polymers. At the core of the method, a modified, commercially available IR transmission gas cell monitors time-dependent gas concentration. Appropriate experimental conditions, e.g. desorption or permeation under continuous flow or static gas conditions, are achieved using easily adaptable external components such as flow controllers and sample ampoules. This study presents overview approaches using the same IR detection methodology to determine diffusivity (desorption into a static gas environment, continuous gas flow, or intermittent desorption) and permeability (static and dynamic flow detection). Further, the challenges encountered for design and setup of IR gas quantification experiments, related to calibration and gas interaction, are presented. These methods establish desorption and permeation behavior of solvents (water and methanol), CO 2 off-gassing from foam, and offer simultaneous measurements of the permeation of several gases in a gas mixture (CO 2 , CO and CH 4 ) through polymer films such as epoxy and Kapton. They offer complementary guidance for material diagnostics and understanding of basic properties in sorption and transport behavior often of relevance to polymer degradation or materials reliability phenomena.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Melting temperature measurement of refractory oxide ceramics as a function of oxygen fugacity using containerless methods

An aerodynamic conical nozzle levitator (CNL) has been used to measure the melting temperatures of refractory ceramics. The well-established method of cooling traces has been adapted to allow measurements for air-sensitive samples using a controlled atmosphere, where the oxygen partial pressure can be adjusted and monitored in real time. In this study, we explain the details of a system that we developed for use at the Spallation Neutron Source (Oak Ridge National Laboratory). Measurements of the melting behavior of (Fe,Cr,Al) 3 O 4 spinels were made between log (PO 2 (atm)) of -0.7 and -5. The melting temperature of hercynite is found to be oxygen potential dependent, ranging between 1692 and 1767°C at log (PO 2 ) values from -4.42 to -0.70.

36 MATERIALS SCIENCE↗

DOE OSTI2019

An Efficient, Globally Convergent Method for Optimization Under Uncertainty Using Adaptive Model Reduction and Sparse Grids

We present a new approach to efficiently solve optimization problems constrained by partial differential equations (PDEs) with uncertain coefficients. The method leverages two sources of inexactness that trade accuracy for speed: (1) stochastic collocation based on dimension-adaptive sparse grids (SGs), which approximates the stochastic objective function with a limited number of quadrature nodes, and (2) projection-based reduced-order models (ROMs), which generate efficient approximations to PDE solutions. These two sources of inexactness lead to inexact objective function and gradient evaluations, which are managed by a trust-region method that guarantees global convergence by adaptively refining the SG and ROM until a proposed error indicator drops below a tolerance specified by trust-region convergence theory. A key feature of the proposed method is that the error indicator---which accounts for errors incurred by both the SG and ROM---must be only an asymptotic error bound, i.e., a bound that holds up to an arbitrary constant that need not be computed. This allows the approach to be applicable to a wide range of problems, including those where sharp, computable error bounds are not available; this distinguishes the proposed method from previous works. Numerical experiments performed on a model problem from optimal flow control under uncertainty verify global convergence of the method and demonstrate the method's ability to outperform previously proposed alternatives.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Exploring the Mass-loss Histories of the Red Supergiants

We report mid- to far-infrared imaging and photometry from 7 to 37 μm with SOFIA/FORCAST and 2 μm adaptive optics imaging with LBTI/LMIRCam of a large sample of red supergiants (RSGs) in four Galactic clusters: RSGC1, RSGC2 = Stephenson 2, RSGC3, and NGC 7419. The RSGs in these clusters cover their expected range in luminosity and initial mass from ≈9 to more than 25 M {sub ⊙}. The population includes examples of very late-type RSGs such as MY Cep, which may be near the end of the RSG stage, high-mass-losing maser sources, yellow hypergiants, and post-RSG candidates. Many of the stars and almost all of the most luminous have spectral energy distributions (SEDs) with extended infrared excess radiation at the longest wavelengths. To best model their SEDs, we use the DUSTY code with a variable radial density distribution function to estimate their mass-loss rates. Our M-dot –luminosity relation for 42 RSGs basically follows the classical de Jager curve, but at luminosities below 10{sup 5} L{sub ⊙}, we find a significant population of RSGs with M-dot below the de Jager relation. At luminosities above 10{sup 5} L {sub ⊙}, there is a rapid transition to higher mass-loss rates that approximates and overlaps the de Jager curve. We recommend that instead of using a linear relation or single curve, the empirical M-dot –luminosity relation is better represented by a broad band. Interestingly, the transition to much higher M-dot at about 10{sup 5} L {sub ⊙} corresponds approximately to an initial mass of 18–20 M {sub ⊙}, which is close to the upper limit for RSGs becoming Type II supernovae.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1970

Determination of hydroxyl content in impure magnesium oxide

Three-step thermal process quantitatively determines the hydroxyl content in samples of magnesium oxide. Analytical method can be adapted to large-scale production of hydroxyl-free magnesium oxide.

Blosser, E. R.↗

NASA NTRS1972

Analysis of the flow field generated near an aircraft engine operating in reverse thrust

A computer solution is developed to the exhaust gas reingestion problem for aircraft operating in the reverse thrust mode on a crosswind-free runway. The computer program determines the location of the inlet flow pattern, whether the exhaust efflux lies within the inlet flow pattern or not, and if so, the approximate time before the reversed flow reaches the engine inlet. The program is written so that the user is free to select discrete runway speeds or to study the entire aircraft deceleration process for both the far field and cross-ingestion problems. While developed with STOL applications in mind, the solution is equally applicable to conventional designs. The inlet and reversed jet flow fields involved in the problem are assumed to be noninteracting. The nacelle model used in determining the inlet flow field is generated using an iterative solution to the Neuman problem from potential flow theory while the reversed jet flow field is adapted using an empirical correlation from the literature. Sample results obtained using the program are included.

Ledwith, W. A., Jr.↗

NASA NTRS1978

Application of higher harmonic blade feathering for helicopter vibration reduction

Higher harmonic blade feathering for helicopter vibration reduction is considered. Recent wind tunnel tests confirmed the effectiveness of higher harmonic control in reducing articulated rotor vibratory hub loads. Several predictive analyses developed in support of the NASA program were shown to be capable of calculating single harmonic control inputs required to minimize a single 4P hub response. In addition, a multiple-input, multiple-output harmonic control predictive analysis was developed. All techniques developed thus far obtain a solution by extracting empirical transfer functions from sampled data. Algorithm data sampling and processing requirements are minimal to encourage adaptive control system application of such techniques in a flight environment.

Powers, R. W.↗

NASA NTRS1986

Adaptive finite element methods for compressible flow problems

Some recent work on adaptive FEMs for solving transient Euler equations in two-dimensional domains is summarized. The formulation of an FEM model of the Euler equations is shown, and the application of the adaptive strategies to data management schemes is addressed. Sample numerical results from the application of the model and strategies to the flow over a step and to transient cases are given.

Oden, J. T.↗

NASA NTRS1990

Convergence of the SMI and the diagonally loaded SMI algorithms with weak interference

Approximations for the power levels at the output of an adaptive array that uses the diagonally loaded sample-matrix inversion (SMI) algorithm are derived. Diagonal loading is a technique where the diagonal of the covariance matrix is augmented with a positive or negative constant prior to inversion. This paper examines how the signal-to-interference-plus-noise ratio (SINR) and signal-to-interference ratio (SIR) at the array output vary with the number of samples taken when the input signals are CW. It is shown that positive loading produces more rapid convergence with a reduction in output SIR. Negative loading provides an improved SIR level, but positive loading produces more rapid convergence. Negative loading provides an improved SIR level, but the output power levels are erratic and slow to converge. Simulation results which verify the theoretical procedure are given.

Ganz, Matthew W.↗

NASA NTRS1996

The effects of cloud inhomogeneities upon radiative fluxes, and the supply of a cloud truth validation dataset

The ASTER polar cloud mask algorithm is currently under development. Several classification techniques have been developed and implemented. The merits and accuracy of each are being examined. The classification techniques under investigation include fuzzy logic, hierarchical neural network, and a pairwise histogram comparison scheme based on sample histograms called the Paired Histogram Method. Scene adaptive methods also are being investigated as a means to improve classifier performance. The feature, arctan of Band 4 and Band 5, and the Band 2 vs. Band 4 feature space are key to separating frozen water (e.g., ice/snow, slush/wet ice, etc.) from cloud over frozen water, and land from cloud over land, respectively. A total of 82 Landsat TM circumpolar scenes are being used as a basis for algorithm development and testing. Numerous spectral features are being tested and include the 7 basic Landsat TM bands, in addition to ratios, differences, arctans, and normalized differences of each combination of bands. A technique for deriving cloud base and top height is developed. It uses 2-D cross correlation between a cloud edge and its corresponding shadow to determine the displacement of the cloud from its shadow. The height is then determined from this displacement, the solar zenith angle, and the sensor viewing angle.

Welch, Ronald M.↗

NASA NTRS2024

Flow Cytometry Methods to Monitor Immune System Dysregulation in Astronauts

Persistent immune system dysregulation has been documented to occur in astronauts participating in orbital spaceflight onboard the International Space Station. The phenomenon consists of reductions in T and NK cell function, altered cytokine profiles, persistent inflammation, and the subclinical reactivation of latent herpesviruses. In select crewmembers the dysregulation does actually lead to clinical symptoms, primarily atypical allergy or atopic dermatitis/zoster. Flow cytometry has served a central role defining the ‘immune assessment’ panel of assays that allow monitoring of astronauts. The cytometry assays which have been utilized include: 1. Peripheral leukocyte subsets 2. T cell function 3. Monocyte function 4. NK cell function 5. Intracellular cytokine analysis 6. Virus-specific T cell number (tetramer assay) 7. Virus-specific T cell function (peptide stimulation) 8. Leukocyte-bacterial challenge cytometry 9. Cytometric bead/multiplex array (soluble proteins) The use of these assays has been validated through various ISS flight investigations to define, to varying degrees, both in-flight, and post-flight immune system alterations. The kinetics of the dysregulation through the various phases of spaceflight, as well as post-flight recovery, have also been documented. To allow the science to occur within the orbital constraints of a spaceflight investigation, particular sample collection and processing techniques were developed compatible with the delays associated with terrestrial processing of in-flight samples. A subset of the assays has been adapted to routine monitoring of astronauts via a NASA ‘ISS Standard Measures’ activity, with the data from a specific crew then provided to all science investigators for that particular mission. This battery of cytometry assays has also been applied, through ground investigations, to several terrestrial ‘spaceflight analog’ populations. The purpose was to validate the analog which most closely replicates the in-flight observed pattern of alterations, generally believed to be winterover at an Antarctica station. To assist in determination of clinical risk, the assay panel has also been applied to investigations of various terrestrial patient populations, particularly zoster patients. As NASA is initiating crewed lunar missions via the ‘Artemis’ program, deployment of a miniaturized, microgravity-compatible flow cytometer, would be extremely beneficial to allow real time monitoring of crewmembers. Real time medical data could influence use of several countermeasures options during deep space missions. Several such instruments have been developed and validated to varying degrees of success. Assay details and summary findings across the various flight and ground platforms will be presented, as will current status in developing such technology for in-flight use.

Brian Crucian↗

DOE OSTI2017

Galaxy Merger Candidates in High-redshift Cluster Environments

We compile a sample of spectroscopically and photometrically selected cluster galaxies from four high-redshift galaxy clusters (1.59<z<1.71) from the Spitzer Adaptation of the Red-Sequence Cluster Survey (SpARCS), and a comparison field sample selected from the UKIDSS Deep Survey. Using near-infrared imaging from the Hubble Space Telescope, we classify potential mergers involving massive (M{sub ∗}⩾3×10{sup 10} M{sub ⊙}) cluster members by eye, based on morphological properties such as tidal distortions, double nuclei, and projected near neighbors within 20 kpc. With a catalog of 23 spectroscopic and 32 photometric massive cluster members across the four clusters and 65 spectroscopic and 26 photometric comparable field galaxies, we find that after taking into account contamination from interlopers, 11.0{sub −5.6}{sup +7.0}% of the cluster members are involved in potential mergers, compared to 24.7{sub −4.6}{sup +5.3}% of the field galaxies. We see no evidence of merger enhancement in the central cluster environment with respect to the field, suggesting that galaxy–galaxy merging is not a stronger source of galaxy evolution in cluster environments compared to the field at these redshifts.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Autonomous elemental characterization enabled by a low cost robotic platform built upon a generalized software architecture

Despite the rapidly growing applications of robots in industry, the use of robots to automate tasks in scientific laboratories is less prolific due to the lack of generalized methodologies and the high cost of hardware. This paper focuses on the automation of characterization tasks necessary for reducing cost while maintaining generalization and proposes a software architecture for building robotic systems in scientific laboratory environments. A dual-layer (Socket.IO and ROS) action server design is the basic building block, which facilitates the implementation of a web-based front end for user-friendly operation and the use of ROS Behavior Trees for convenient task planning and execution. A robotic platform for automating mineral and material sample characterization is built upon the architecture, with an open-source, low-cost three-axis computer numerical control gantry system serving as the main robot. A handheld laser induced breakdown spectroscopy (LIBS) analyzer is integrated with a 3D printed adapter, enabling (1) automated 2D chemical mapping and (2) autonomous sample measurement (with the support of an RGB-Depth camera). We demonstrate the utility of automated chemical mapping by scanning the surface of a spodumene-bearing pegmatite core sample with a 1071-point dense hyperspectral map acquired at a rate of 1520 bits per second. Furthermore, we showcase the autonomy of the platform in terms of perception, dynamic decision-making, and execution, through a case study of LIBS measurement of multiple mineral samples. The platform enables controlled and autonomous chemical quantification in the laboratory that complements field-based measurements acquired with the same handheld device, linking resource exploration and processing steps in the supply chain for lithium-based battery materials.

Cao, Xuan [Lawrence Berkeley National Laboratory (↗

DOE OSTI2022

Aerosol Inlets for a Mid-Sized Uncrewed Aerial System (UAS)

The purpose of this technical report is to document the efforts to design and test two inlet systems for aerosol sampling suitable for deployment on a medium-sized fixed-wing Uncrewed Aerial System (UAS). This work, which was supported by the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) user facility, was conducted at the Pacific Northwest National Laboratory (PNNL) for the ARM Aircraft Facility (AAF) starting in November 2017. The current work is a part of AAF efforts to instrument the ArcticShark (a mid-sized UAS owned and operated by the AAF) for atmospheric research and develop a scientific payload for deployment on a similar-sized UAS with minimal adaptation and integration. An aerosol inlet system is necessary to sample and transport ambient air sample to the scientific instrumentation with minimal distortions to the aerosols. Two isokinetic aerosol inlets were designed: the first is a simple passive system for a single instrument suitable to be installed in a wing pylon; the second is a system with active control designed to sample and distribute air among several heterogeneous instruments and to provide basic humidity control of the air sample so that the measured aerosol parameters should correspond to “dry” conditions (a common requirement). Both systems could be easily adapted for deployment on another platform and/or with a different set of instrumentation. Several conducted flight tests showed that the inlets’ performance met our design goals.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Aerosol Inlets for a Mid-Sized Uncrewed Aerial System (UAS)

42 ENGINEERING↗

DOE OSTI2022

Quantifying Subsurface Biogeochemical Variability in a High Altitude Watershed During Winter Isolation

Shallow subsurface microbial and geochemical processes in watersheds are dynamic and responsive to seasonal and long-term environmental change. At high elevation or latitude, such changes may occur during winter months when normal sampling is impossible, impractical, unsafe, or may actually alter the processes being studied. Yet accurate modeling of biogeochemical parameters in these environments requires sampling that can capture events and persistent cold climate trends. Gaps in current models exist where data have not been collected during extended snow- or ice-covered periods. The goals of our exploratory study were to examine the biogeochemical processes occurring in a well-studied high altitude watershed during winter when the system is largely inaccessible. We tested the hypothesis that during snow cover in the East River (ER) watershed, episodic excursions of microbial community structure and biogeochemical processes and concentrations fluctuated from values extrapolated from pre- and post-snow time periods. Through our research we identified previously unresolved subsurface-surface transport phenomena and a heretofore under-appreciated methane cycle occurring during wintertime months, thus providing valuable insight into watershed processes. Our research showed that autonomous sampling techniques, first used in marine systems, is extremely versatile and can be adapted for use in harsh continental settings to examine temporal changes in freshwater chemistry and microbial community assemblage. Further, we found that by sampling during periods when systems are hard to access, will lend insight and better accountability for global budgets for methane, an important greenhouse gas. By strengthening our knowledge of wintertime biogeochemical relationships in high altitude watersheds our research leads to more complete descriptions of cryptic processes and ultimately will inform and improve the reactive transport models that simulate processes in these systems.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Genomic Signatures of a Major Adaptive Event in the Pathogenic Fungus Melampsora larici-populina

The recent availability of genome-wide sequencing techniques has allowed systematic screening for molecular signatures of adaptation, including in nonmodel organisms. Host–pathogen interactions constitute good models due to the strong selective pressures that they entail. We focused on an adaptive event which affected the poplar rust fungus Melampsora larici-populina when it overcame a resistance gene borne by its host, cultivated poplar. Based on 76 virulent and avirulent isolates framing narrowly the estimated date of the adaptive event, we examined the molecular signatures of selection. Using an array of genome scan methods based on different features of nucleotide diversity, we detected a single locus exhibiting a consistent pattern suggestive of a selective sweep in virulent individuals (excess of differentiation between virulent and avirulent samples, linkage disequilibrium, genotype–phenotype statistical association, and long-range haplotypes). Our study pinpoints a single gene and further a single amino acid replacement which may have allowed the adaptive event. Although our samples are nearly contemporary to the selective sweep, it does not seem to have affected genome diversity further than the immediate vicinity of the causal locus, which can be explained by a soft selective sweep (where selection acts on standing variation) and by the impact of recombination in mitigating the impact of selection. Therefore, it seems that properties of the life cycle of M. larici-populina, which entails both high genetic diversity and outbreeding, has facilitated its adaptation.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2016

Comparison of Surrogate Models with Physical Models for Dynamic Probabilistic Risk Analysis Using the RAVEN Code

Dynamic probabilistic risk analysis (DPRA) has emerged in the nuclear industry as an effective tool to identify points of weakness in nuclear reactors and create a comprehensive approach to quantifying risk. While DPRA allows for detailed analysis, it usually requires thousands of runs due to the necessity of exploring low probability, high consequence events, which can be computationally prohibitively difficult to assess. Risk Analysis Virtual Environment (RAVEN) is a software package being developed under the Nuclear Energy Advanced Modeling and Simulation program at the Idaho National Laboratory. It is able to manage complex control logic to drive a RELAP-7 simulation and to handle sampling strategies including Monte Carlo, Latin Hypercube, Grid and Adaptive samplers. By performing a thorough investigation of the possibility space of an accident scenario with RELAP-7, RAVEN is able to identify consequences of accident scenarios that have not been encountered. The most computational resource intensive step of a RAVEN analysis is running the RELAP-7 code modeling the physical system behavior. Using surrogate models to represent the outcomes of more complex simulations rather than the full model can greatly reduce the computation effort required. In situations where the uncertainty distributions of a model are unknown, or when there are multiple sets of uncertainty distributions, DPRA generally requires rerunning the physical model for each set of uncertainty distributions used. By taking an unbiased sample of the physical model and creating a surrogate model from the results, the surrogate model can be sampled under a different set of uncertainty distributions to provide equivalent results. This paper presents an example of this approach. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗