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At least 883 records · Page 49

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NASA NTRS2011

Variable X-Ray Absorption in the Mini-BAL QSO PG 1126-041

Context. X-ray studies of AGN with powerful nuclear winds are important to constrain the physics of the inner accretion/ejection flow around SMBH, and to understand the impact of such winds on the AGN environment. Aims. Our main scientific goal is to constrain the properties of a variable outflowing absorber that is thought to be launched near the SMBH of the mini-BAL QSO PG 1126-041 using a multi-epoch observational campaign performed with XMM-Newton. Methods. We performed temporally resolved X-ray spectroscopy and simultaneous UV and X-ray photometry on the most complete set of observations and on the deepest X-ray exposure of a mini-BAL QSO to date. Results. We found complex X-ray spectral variability on time scales of both months and hours, best reproduced by means of variable massive ionized absorbers along the line of sight. As a consequence, the observed optical-to-X-ray spectral index is found to be variable with time. In the highest signal-to-noise observation we detected highly ionized X-ray absorbing material outflowing much faster (u(sub X) approx. 16 500 km/s) than the UV absorbing one (u(sub uv) approx. 5,000 km/s). This highly ionized absorber is found to be variable on very short (a few kiloseconds) time scales. Conclusions. Our findings are qualitatively consistent with line driven accretion disk winds scenarios. Our observations have opened the time-resolved X-ray spectral analysis field for mini-BAL QSOs; only with future deep studies will we be able to map the dynamics of the inner flow and understand the physics of AGN winds and their impact on the environment.

Giustini, M.↗

NASA NTRS2013

Improved Understanding of the Modeled QBO Using MLS Observations and MERRA Reanalysis

The Quasi-Biennial Oscillation (QBO) dominates the variability of the tropical stratosphere on interannual time scales. The QBO has been shown to extend its influence into the chemical composition of this region through dynamical mechanisms. We have started our analysis using the realistic QBO internally generated by the Goddard Earth Observing System Version 5 (GEOS-5) general circulation model coupled to a comprehensive stratospheric and tropospheric chemical mechanism forced with observed sea surface temperatures over the past 33 years. We will show targeted comparisons with observations from NASAs Aura satellite Microwave Limb Sounder (MLS) and the Modern Era Retrospective-Analysis for Research and Applications (MERRA) reanalysis to provide insight into the simulation of the primary and secondary circulations associated with the QBO. Using frequency spectrum analysis and multiple linear regression we can illuminate the resulting circulations and deduce the strengths and weaknesses in their modeled representation. Inclusion of the QBO in our simulation improves the representation of the subtropical barriers and overall tropical variability. The QBO impact on tropical upwelling is important to quantify when calculating trends in sub-decadal scale datasets.

MERRA↗

NASA NTRS2015

Impact Testing and Simulation of a Sinusoid Foam Sandwich Energy Absorber

A sinusoidal-shaped foam sandwich energy absorber was developed and evaluated at NASA Langley Research Center through multi-level testing and simulation performed under the Transport Rotorcraft Airframe Crash Testbed (TRACT) research project. The energy absorber, designated the "sinusoid," consisted of hybrid carbon- Kevlar® plain weave fabric face sheets, two layers for each face sheet oriented at +/-45deg with respect to the vertical or crush direction, and a closed-cell ELFOAM(TradeMark) P200 polyisocyanurate (2.0-lb/ft3) foam core. The design goal for the energy absorber was to achieve an average floor-level acceleration of between 25- and 40-g during the full-scale crash test of a retrofitted CH-46E helicopter airframe, designated TRACT 2. Variations in the design were assessed through quasi-static and dynamic crush testing of component specimens. Once the design was finalized, a 5-ft-long subfloor beam was fabricated and retrofitted into a barrel section of a CH-46E helicopter. A vertical drop test of the barrel section was conducted onto concrete to evaluate the performance of the energy absorber prior to retrofit into TRACT 2. Finite element models were developed of all test articles and simulations were performed using LSDYNA ®, a commercial nonlinear explicit transient dynamic finite element code. Test analysis results are presented for the sinusoid foam sandwich energy absorber as comparisons of load-displacement and acceleration-time-history responses, as well as predicted and experimental structural deformations and progressive damage for each evaluation level (component testing through barrel section drop testing).

Jackson, Karen E.↗

NASA NTRS2016

Assessing Spontaneous Combustion Instability with Recurrence Quantification Analysis

Spontaneous instabilities can pose a significant challenge to verification of combustion stability, and characterizing its onset is an important avenue of improvement for stability assessments of liquid propellant rocket engines. Recurrence Quantification Analysis (RQA) is used here to explore nonlinear combustion dynamics that might give insight into instability. Multiple types of patterns representative of different dynamical states are identified within fluctuating chamber pressure data, and markers for impending instability are found. A class of metrics which describe these patterns is also calculated. RQA metrics are compared with and interpreted against another metric from nonlinear time series analysis, the Hurst exponent, to help better distinguish between stable and unstable operation.

Eberhart, Chad J.↗

NASA NTRS2019

Wind Tunnel Flow Field Visualizations of the Space Launch System Vehicle Ascent

A wind tunnel test was conducted to characterize the aeroacoustic environment of several configurations of the Space Launch System during ascent. The test was conducted in the 11-by-11 foot transonic and 9-by-7 foot supersonic test sections at NASA Ames research center. Throughout this experiment data was collected from several types of instrumentation including: dynamic and steady-state pressure sensors, unsteady and steady pressure sensitive paint, time-resolved shadowgraph and infrared imaging. The following details results and analysis from the time-resolved shadowgraph and infrared imaging data systems. The time-resolved shadowgraph provided a qualitative measurement of the near-field turbulent fluctuations. These results helped provide context to the relative magnitude and frequency content of the fluid-structure-interaction driving the surface pressure phenomena characterized by the discrete pressure transducers and unsteady pressure sensitive paint. The infrared imaging was used to verify boundary layer trip effectiveness and provide temperature correction for the unsteady pressure sensitive paint.

Shadowgraph↗

NASA NTRS2025

Airports as Energy Nodes Activity Summary

Advanced aircraft concepts that use non-traditional aviation energy storage methods such as batteries or cryogenic hydrogen are in development and expected to enter regular service at airports worldwide within the next decade. The energy needs for these aircraft may quickly overwhelm the existing energy infrastructure at airports, particularly at smaller and more remote facilities. Without energy upgrades, these airports will not be able to host these advanced vehicles, but without the advanced vehicle traffic, these airports will not have the rationale or funding to build up their energy infrastructure. The Airports as Energy Nodes (ÆNodes) activity, a collaboration between the National Aeronautics and Space Administration (NASA) and the National Renewable Energy Laboratory (NREL), was executed to understand and model the energy needs that advanced aircraft concepts may levy on these smaller airports, determine cost-effective approaches to enhance the airport energy infrastructure, and demonstrate the enhanced resilience of these energy infrastructure upgrades to the airport and surrounding community via “digital twin” simulation at relevant energy and dynamic time scales. The ÆNodes team also investigated future reference aircraft designs and materials to enable cryogenic hydrogen storage for aircraft. The ÆNodes team conducted analysis at two U.S. airport partner sites — Winchester Regional Airport in Winchester, Virginia, and Tweed/New Haven Airport in New Haven, Connecticut. The goal of this partnership was to develop data and reference infrastructure designs that could accommodate advanced aircraft in the future at these airports while also enhancing the resiliency of the energy supply to the surrounding airport community, which could be used to capture funding to enable the infrastructure upgrades. Over the course of the study, a method was developed to estimate air traffic requiring advanced energy services over the course of a year using a mix of historical data and companion studies on advanced aircraft transportation networks. The study has concluded at NASA but continues at NREL, who will develop a final report discussing the energy infrastructure upgrades and digital twin results. Preliminary results indicate that unrestricted adoption of advanced battery-electric aircraft may double traffic at these airports and increase peak daily power usage by an order of magnitude, while increase electricity energy needs by a factor of two to four. The infrastructure upgrades necessary to accommodate these increased energy needs could be used to provide enhanced energy services to the airport community to offset the cost and increase the utility of the upgrades, which will be described in the NREL final report.

Airports↗

DOE OSTI2022

Deciphering the influence of high-flux helium plasma exposure on tungsten nanostructure growth using real-time, in situ spectroscopic ellipsometry

In situ analysis of surfaces during high-flux plasma exposure represents a long-standing challenge in the study of plasma–material interactions. While post-mortem microscopy can provide a detailed picture of structural and compositional changes, in situ techniques can capture the dynamic evolution of the surface. In this study, we demonstrate how spectroscopic ellipsometry can be applied to the real-time characterization of W nanostructure (also known as “fuzz”) growth during exposure to low temperature, high-flux He plasmas. Strikingly, over a wide range of sample temperatures and helium fluences, the measured ellipsometric parameters (Ψ,Δ) collapse onto a single curve that can be directly correlated with surface morphologies characterized by ex situ helium ion microscopy. The initial variation in the (Ψ,Δ) parameters appears to be governed by small changes in surface roughness (<50 nm) produced by helium bubble nucleation and growth, followed by the emergence of 50 nm diameter W tendrils. This basic behavior appears to be reproducible over a wide parameter space, indicating that the spectroscopic ellipsometry may be of general practical use as a diagnostic to study surface morphologies produced by high-flux He implantation in refractory metals. An advantage of the methods outlined here is that they are applicable at low incident ion energies, even below the sputtering threshold. As an example of this application, we apply in situ ellipsometry to examine how W fuzz growth is affected both by varying ion energy and the temperature of the surface.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1992

The 3D inelastic analysis methods for hot section components

A two-year program to develop advanced 3D inelastic structural stress analysis methods and solution strategies for more accurate and cost effective analysis of combustors, turbine blades, and vanes is described. The approach was to develop a matrix of formulation elements and constitutive models. Three constitutive models were developed in conjunction with optimized iterating techniques, accelerators, and convergence criteria within a framework of dynamic time incrementing. Three formulation models were developed: an eight-noded midsurface shell element; a nine-noded midsurface shell element; and a twenty-noded isoparametric solid element. A separate computer program has been developed for each combination of constitutive model-formulation model. Each program provides a functional stand alone capability for performing cyclic nonlinear structural analysis. In addition, the analysis capabilities incorporated into each program can be abstracted in subroutine form for incorporation into other codes or to form new combinations.

Mcknight, R. L.↗

DOE OSTI2026

Polarized target nuclear magnetic resonance measurements with deep neural networks

Continuous-wave Nuclear Magnetic Resonance (CW-NMR) operated in constant-current mode has served as a foundational technique for polarization measurement in solid-state dynamically polarized targets within nuclear and high-energy physics experiments for several decades, and it remains an essential tool. Conventional Q-meter-based phase-sensitive detection is critical for precise real-time determination of target polarization during scattering runs. However, the accuracy and reliability of these measurements are frequently compromised by elevated noise levels, baseline drift, and systematic uncertainties arising from signal isolation and fitting, ultimately degrading the overall experimental figure of merit. In this work, we report the first successful application of neural network architectures to continuous-wave NMR polarization metrology. By leveraging advanced machine learning techniques for signal extraction and denoising, we achieve a substantial reduction of fitting uncertainties under a variety of realistic simulated and experimental conditions. These improvements translate directly into more robust real-time (online) polarization monitoring and higher precision in subsequent offline analysis. By reducing analysis-induced uncertainty, the resulting methodology can improve the effective figure of merit for scattering experiments employing dynamically polarized targets and provides a new toolset for NMR-based polarimetry in high-energy and nuclear physics.

Metrology↗

DOE OSTI2021

Solid-state NMR of unlabeled plant cell walls: high-resolution structural analysis without isotopic enrichment

Abstract Background Multidimensional solid-state nuclear magnetic resonance (ssNMR) spectroscopy has emerged as an indispensable technique for resolving polymer structure and intermolecular packing in primary and secondary plant cell walls. Isotope ( 13 C) enrichment provides feasible sensitivity for measuring 2D/3D correlation spectra, but this time-consuming procedure and its associated expenses have restricted the application of ssNMR in lignocellulose analysis. Results Here, we present a method that relies on the sensitivity-enhancing technique Dynamic Nuclear Polarization (DNP) to eliminate the need for 13 C-labeling. With a 26-fold sensitivity enhancement, a series of 2D 13 C– 13 C correlation spectra were successfully collected using the unlabeled stems of wild-type Oryza sativa (rice). The atomic resolution allows us to observe a large number of intramolecular cross peaks for fully revealing the polymorphic structure of cellulose and xylan. NMR relaxation and dipolar order parameters further suggest a sophisticated change of molecular motions in a ctl1 ctl2 double mutant: both cellulose and xylan have become more dynamic on the nanosecond and microsecond timescale, but the motional amplitudes are uniformly small for both polysaccharides. Conclusions By skipping isotopic labeling, the DNP strategy demonstrated here is universally extendable to all lignocellulose materials. This time-efficient method has landed the technical foundation for understanding polysaccharide structure and cell wall assembly in a large variety of plant tissues and species.

09 BIOMASS FUELS↗

DOE OSTI2022

Probing Electron Beam Induced Transformations on a Single-Defect Level via Automated Scanning Transmission Electron Microscopy

A robust approach for real-time analysis of the scanning transmission electron microscopy (STEM) data streams, based on ensemble learning and iterative training (ELIT) of deep convolutional neural networks, is implemented on an operational microscope, enabling the exploration of the dynamics of specific atomic configurations under electron beam irradiation via an automated experiment in STEM. Combined with beam control, this approach allows studying beam effects on selected atomic groups and chemical bonds in a fully automated mode. Here, in this study, we demonstrate atomically precise engineering of single vacancy lines in transition metal dichalcogenides and the creation and identification of topological defects in graphene. The ELIT-based approach facilitates direct on-the-fly analysis of the STEM data and engenders real-time feedback schemes for probing electron beam chemistry, atomic manipulation, and atom by atom assembly.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2007

High Fidelity Thermal Simulators for Non-Nuclear Testing: Analysis and Initial Results

Non-nuclear testing can be a valuable tool in the development of a space nuclear power system, providing system characterization data and allowing one to work through various fabrication, assembly and integration issues without the cost and time associated with a full ground nuclear test. In a non-nuclear test bed, electric heaters are used to simulate the heat from nuclear fuel. Testing with non-optimized heater elements allows one to assess thermal, heat transfer, and stress related attributes of a given system, but fails to demonstrate the dynamic response that would be present in an integrated, fueled reactor system. High fidelity thermal simulators that match both the static and the dynamic fuel pin performance that would be observed in an operating, fueled nuclear reactor can vastly increase the value of non-nuclear test results. With optimized simulators, the integration of thermal hydraulic hardware tests with simulated neutronie response provides a bridge between electrically heated testing and fueled nuclear testing, providing a better assessment of system integration issues, characterization of integrated system response times and response characteristics, and assessment of potential design improvements' at a relatively small fiscal investment. Initial conceptual thermal simulator designs are determined by simple one-dimensional analysis at a single axial location and at steady state conditions; feasible concepts are then input into a detailed three-dimensional model for comparison to expected fuel pin performance. Static and dynamic fuel pin performance for a proposed reactor design is determined using SINDA/FLUINT thermal analysis software, and comparison is made between the expected nuclear performance and the performance of conceptual thermal simulator designs. Through a series of iterative analyses, a conceptual high fidelity design can developed. Test results presented in this paper correspond to a "first cut" simulator design for a potential liquid metal (NaK) cooled reactor design that could be applied for Lunar surface power. Proposed refinements to this simulator design are also presented.

Bragg-Sitton, Shannon M.↗

DOE OSTI2023

Machine-learning-assisted analysis of transition metal dichalcogenide thin-film growth

In situ reflective high-energy electron diffraction (RHEED) is widely used to monitor the surface crystalline state during thin-film growth by molecular beam epitaxy (MBE) and pulsed laser deposition. With the recent development of machine learning (ML), ML-assisted analysis of RHEED videos aids in interpreting the complete RHEED data of oxide thin films. The quantitative analysis of RHEED data allows us to characterize and categorize the growth modes step by step, and extract hidden knowledge of the epitaxial film growth process. In this study, we employed the ML-assisted RHEED analysis method to investigate the growth of 2D thin films of transition metal dichalcogenides (ReSe2) on graphene substrates by MBE. Principal component analysis (PCA) and K-means clustering were used to separate statistically important patterns and visualize the trend of pattern evolution without any notable loss of information. Using the modified PCA, we could monitor the diffraction intensity of solely the ReSe2 layers by filtering out the substrate contribution. These findings demonstrate that ML analysis can be successfully employed to examine and understand the film-growth dynamics of 2D materials. Further, the ML-based method can pave the way for the development of advanced real-time monitoring and autonomous material synthesis techniques.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Diverse organic carbon dynamics captured by radiocarbon analysis of distinct compound classes in a grassland soil

Soil organic carbon (SOC) is a large, dynamic reservoir composed of a complex mixture of plant- and microbe-derived compounds with a wide distribution of cycling timescales and mechanisms. The distinct residence times of individual carbon components within this reservoir depend on a combination of factors, including compound reactivity, mineral association, and climate conditions. To better constrain SOC dynamics, bulk radiocarbon measurements are commonly used to trace biosphere inputs into soils and to estimate timescales of SOC cycling. However, understanding the mechanisms driving the persistence of organic compounds in bulk soil requires analyses of SOC pools that can be linked to plant sources and microbial transformation processes. Here, we adapt approaches, previously developed for marine sediments, to isolate organic compound classes from soils for radiocarbon ( 14 C) analysis. We apply these methods to a soil profile from an annual grassland in Hopland, California (USA), to assess changes in SOC persistence with depth (down to 1 m). We measured the radiocarbon values of water-extractable organic carbon (WEOC), total lipid extracts (TLEs), total hydrolyzable amino acids (AAs), and an acid-insoluble (AI) fraction from bulk and physically separated size fractions (< 2 mm, 2 mm–63 µm, and < 63 µm). Our results show that Δ 14 C values of bulk soil, size fractions, and extracted compound classes became more depleted with depth, and individual SOC components have distinct age–depth distributions that suggest distinguishable cycling rates. We found that AAs and TLEs cycle faster than the bulk soils and the AI fraction. The AI was the most 14 C-depleted fraction, indicating that it is the most chemically inert in this soil. Our approach enables the isolation and measurement of SOC fractions that separate functionally distinct SOC pools that can cycle relatively quickly (e.g., plant and microbial residues) from more passive or inert SOC pools (associated with minerals or petrogenic) from bulk soils and soil physical fractions. With the effort to move beyond SOC bulk analysis, we find that compound class 14 C analysis can improve our understanding of SOC cycling and disentangle the physical and chemical factors driving OC cycling rates and persistence.

58 GEOSCIENCES↗

NASA NTRS1996

Use of the Matching Pursuit Algorithm for Flight Flutter Test Data Analysis

The goal of flight flutter testing is to detect possibly destructive modes of aircraft vibration which may arise during flight from interaction of aerodynamic forces with structural dynamic properties of the airframe. This is typically accomplished by exciting the airframe with a time varying force and monitoring the response of the aircraft throughout its flight envelope. The data generated must be analyzed and presented so that the frequency and time of occurrence of excited modes are clearly and unambiguously displayed. Processing and display in near real time is also desirable. Display of data in the time-frequency plane is a natural choice because it is a familiar and intuitive framework. The Matching Pursuit algorithm provides a time-frequency analysis with good adaptability to signal structure and good signal representation in the time-frequency plane. Improvements in efficiency are needed before the algorithm can be used in real time, however.

Nelson, Ronald E.↗

DOE OSTI2020

The Effect of Intensity Fluctuations on Sequential X-ray Photon Correlation Spectroscopy at the X-ray Free Electron Laser Facilities

How materials evolve at thermal equilibrium and under external excitations at small length and time scales is crucial to the understanding and control of material properties. X-ray photon correlation spectroscopy (XPCS) at X-ray free electron laser (XFEL) facilities can in principle capture dynamics of materials that are substantially faster than a millisecond. However, the analysis and interpretation of XPCS data is hindered by the strongly fluctuating X-ray intensity from XFELs. Here we examine the impact of pulse-to-pulse intensity fluctuations on sequential XPCS analysis. We show that the conventional XPCS analysis can still faithfully capture the characteristic time scales, but with substantial decrease in the signal-to-noise ratio of the g2 function and increase in the uncertainties of the extracted time constants. We also demonstrate protocols for improving the signal-to-noise ratio and reducing the uncertainties.

36 MATERIALS SCIENCE↗

NASA NTRS1995

Rapid Airplane Parametric Input Design (RAPID)

RAPID is a methodology and software system to define a class of airplane configurations and directly evaluate surface grids, volume grids, and grid sensitivity on and about the configurations. A distinguishing characteristic which separates RAPID from other airplane surface modellers is that the output grids and grid sensitivity are directly applicable in CFD analysis. A small set of design parameters and grid control parameters govern the process which is incorporated into interactive software for 'real time' visual analysis and into batch software for the application of optimization technology. The computed surface grids and volume grids are suitable for a wide range of Computational Fluid Dynamics (CFD) simulation. The general airplane configuration has wing, fuselage, horizontal tail, and vertical tail components. The double-delta wing and tail components are manifested by solving a fourth order partial differential equation (PDE) subject to Dirichlet and Neumann boundary conditions. The design parameters are incorporated into the boundary conditions and therefore govern the shapes of the surfaces. The PDE solution yields a smooth transition between boundaries. Surface grids suitable for CFD calculation are created by establishing an H-type topology about the configuration and incorporating grid spacing functions in the PDE equation for the lifting components and the fuselage definition equations. User specified grid parameters govern the location and degree of grid concentration. A two-block volume grid about a configuration is calculated using the Control Point Form (CPF) technique. The interactive software, which runs on Silicon Graphics IRIS workstations, allows design parameters to be continuously varied and the resulting surface grid to be observed in real time. The batch software computes both the surface and volume grids and also computes the sensitivity of the output grid with respect to the input design parameters by applying the precompiler tool ADIFOR to the grid generation program. The output of ADIFOR is a new source code containing the old code plus expressions for derivatives of specified dependent variables (grid coordinates) with respect to specified independent variables (design parameters). The RAPID methodology and software provide a means of rapidly defining numerical prototypes, grids, and grid sensitivity of a class of airplane configurations. This technology and software is highly useful for CFD research for preliminary design and optimization processes.

Smith, Robert E.↗

NASA NTRS1989

DYSCO: A software system for modeling general dynamic systems

The DYSCO program has been under development since 1979. It has been funded by Army and Air Force laboratories and by the Kaman Aerospace Corporation. It is presently available at a number of government and nongovernment installations. It has been used to analyze a very broad range of dynamics problems. A principle feature of the software design of DYSCO is the separation of the executive from the technology. The executive, which controls all the operations, is intelligent in the sense that it knows that its function is to assemble differential equations and to prepare them for solution. The technology library contains FORTRAN routines which perform standard functions, such as, computing the equation coefficients of an element (or component) given the local state at any time. The technology library also contains algorithms and procedures for solving the coupled system equations. The system was designed to allow easy additional of technology to the library. Any linear or nonlinear structural entity, control system, or set of ordinary differential equations may be simply coded and added to the library, as well as algorithms for time or frequency domain solution. The program is described with emphasis on its usefulness in easily modeling unusual concepts and configurations, performing analysis of damage, evaluating new algorithms, and simulating dynamic tests.

Berman, Alex↗