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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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At least 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

5 Percent Ares I Scale Model Acoustic Test: Overpressure Characterization and Analysis

During the ignition of a ducted solid rocket motor (SRM), rapid expansion of injected hot gases from the motor into a confined volume causes the development of a steep fronted wave. This low frequency transient wave propagates outward from the exhaust duct, impinging the vehicle and ground structures. An unsuppressed overpressure wave can potentially cause modal excitation in the structures and vehicle, subsequently leading to damage. This presentation details the ignition transient f indings from the 5% Ares I Scale Model Acoustic Test (ASMAT). The primary events of the ignition transient environment induced by the SRM are the ignition overpressure (IOP), duct overpressure (DOP), and source overpressure (SOP). The resulting observations include successful knockdown of the IOP environment through use of a Space Shuttle derived IOP suppression system, a potential load applied to the vehicle stemming from instantaneous asymmetrical IOP and DOP wave impingement, and launch complex geometric influences on the environment. The results are scaled to a full-scale Ares I equivalent and compared with heritage data including Ares I-X and both suppressed and unsuppressed Space Shuttle IOP environments.

Alvord, David↗
DOE OSTI2017

Regulations, Codes, and Standards (RCS) for Large-Scale Hydrogen Systems

Hydrogen has potential applications that require larger-scale storage, use, and handling systems than currently are employed in emerging-market fuel cell applications. These potential applications include hydrogen generation and storage systems that would support electrical grid systems. There has been extensive work evaluating regulations, codes, and standards (RCS) for the emerging fuel cell market, such as the infrastructure required to support fuel cell electric vehicles. However, there has not been a similar RCS evaluation and development process for these larger systems. This paper presents an evaluation of the existing RCS in the United States for large-scale systems and identifies potential RCS gaps. This analysis considers large-scale hydrogen technologies that are currently being employed in limited use but may be more widely used as large-scale applications expand. The paper also identifies areas of potential safety research that would need to be conducted to fill the RCS gaps. U.S. codes define bulk hydrogen storage systems but do not define large-scale systems. This paper evaluates potential applications to define a large-scale hydrogen system relative to the systems employed in emerging technologies such as hydrogen fuelling stations. These large-scale systems would likely be of similar size to or larger than industrial hydrogen systems.

08 HYDROGEN↗
DOE OSTI2015

MULTIFRACTAL AND MONOFRACTAL SCALING IN A LABORATORY MAGNETOHYDRODYNAMIC TURBULENCE EXPERIMENT

Both multifractal and monofractal scaling of structure function exponents are observed in the turbulent magnetic fluctuations of the Swarthmore Spheromak Experiment plasma. Structure function and probability distribution function (PDF) analysis exhibits multifractal scaling exponents in low frequency, inertial range fluctuations of the turbulence but monofractal scaling in higher frequency, dissipation range fluctuations. The transition from multifractal to monofractal scaling occurs rapidly suggesting a dissipation mechanism that is insensitive to turbulent structure scale size. Structure functions and PDFs are presented for both temporal and spatial measurements. Variations in the magnetic helicity in the plasma are also shown to modify multifractal scaling characteristics of the inertial range, but do not affect the monofractal scaling of the dissipation range.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Automated Integration of Continental-Scale Observations in Near-Real Time for Simulation and Analysis of Biosphere–Atmosphere Interactions

The National Ecological Observatory Network (NEON) is a continental-scale observatory with sites across the US collecting standardized ecological observations that will operate for multiple decades. To maximize the utility of NEON data, we envision edge computing systems that gather, calibrate, aggregate, and ingest measurements in an integrated fashion. Edge systems will employ machine learning methods to cross-calibrate, gap-fill and provision data in near-real time to the NEON Data Portal and to High Performance Computing (HPC) systems, running ensembles of Earth system models (ESMs) that assimilate the data. For the first time gridded EC data products and response functions promise to offset pervasive observational biases through evaluating, benchmarking, optimizing parameters, and training new machine learning parameterizations within ESMs all at the same model-grid scale. Leveraging open-source software for EC data analysis, we are already building software infrastructure for integration of near-real time data streams into the International Land Model Benchmarking (ILAMB) package for use by the wider research community. We will present a perspective on the design and integration of end-to-end infrastructure for data acquisition, edge computing, HPC simulation, analysis, and validation, where Artificial Intelligence (AI) approaches are used throughout the distributed workflow to improve accuracy and computational performance.

Durden, David J.↗
DOE OSTI2015

Summary of BISON Development and Validation Activities - NEAMS FY15 Report

The objective of the NEAMS ToolKit is to develop a “pellet-to-plant” simulation capability useful for predicting performance and safety for a broad range of nuclear reactor power systems. The NEAMS ToolKit has been organized into a Fuels Product Line (FPL) and a Reactor Product Line (RPL) and is modular in design. Within the FPL, a multiscale approach has been adopted in which simulations of fuel performance at the engineering scale are informed by material property and irradiation performance models developed from mesoscale simulations of microstructural evolution. The focus in this report is on development and validation of the engineering-scale fuel performance analysis tool within the FPL, which is BISON. This summary report contains an overview of work performed under the work package enti- tled “FY2015 NEAMS INL-Engineering Scale Fuel Performance & Interface with RPL Tools.” A first chapter identifies the specific FY-15 milestones, providing a basic description of the asso- ciated work and references to related detailed documentation. Where applicable, a representative technical result is provided. A second chapter summarizes major additional accomplishments including 1) a BISON validation paper, 2) a multiphysics coupling paper, 3) application of BI- SON to Reactivity Insertion Accident analysis and 4) use of BISON for uncertainity analysis in fuel modeling. A final chapter outlines FY-16 future work.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Scaling and Complexity of Stress Fluctuations Associated with Smooth and Jerky Flow in FeCoNiTiAl High-Entropy Alloy

Recent observations of jerky flow in high-entropy alloys (HEA) revealed a high role of self-organization of dislocations in their plasticity. The present work reports the first results of the investigation of stress fluctuations during plastic deformation of an FeCoNiTiAl alloy, examined in a wide temperature range covering both smooth and jerky flow. These fluctuations, which accompany the overall deformation behavior representing an essentially slower stress evolution controlled by the work hardening, were processed using complementary approaches comprising Fourier spectral analysis, refined composite multiscale entropy, and multifractal formalisms. The joint analysis at distinct scales testified that even a macroscopically smooth plastic flow is accompanied by nonrandom fluctuations, disclosing the self-organized dynamics of dislocations. Qualitative changes in such a fine-scale “noise” were found with varying temperature. The observed diversity is significant for understanding the relationships between different scales of plasticity of HEAs and crystal materials in general.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Final Report Scalable Analysis Methods and In Situ Infrastructure for Extreme Scale Knowledge Discovery

The primary challenge motivating this project is the widening gap between the ability to compute information and to store it for subsequent analysis. This gap adversely impacts science code teams, who can perform analysis only on a small fraction of the data they calculate, resulting in the substantial likelihood of lost or missed science, when results are computed but not analyzed. Our approach is to perform as much analysis or visualization processing on data while it is still resident in memory, which is known as in situ processing. The idea in situ processing was not new at the time of the start of this effort in 2014, but efforts in that space were largely ad hoc, and there was no concerted effort within the research community that aimed to foster production-quality software tools suitable for use by Department of Energy (DOE) science projects. Our objective was to produce and enable the use of production-quality in situ methods and infrastructure, at scale, on DOE high-performance computing (HPC) facilities, though we expected to have an impact beyond DOE due to the widespread nature of the challenges, which affect virtually all large-scale computational science efforts. To achieve this objective, we engaged in software technology research and development (R&D), in close partnerships with DOE science code teams, to produce software technologies that were shown to run efficiently at scale on DOE HPC platforms.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2024

Airborne Measurements of Scale‐Dependent Latent Heat Flux Impacted by Water Vapor and Vertical Velocity Over Heterogeneous Land Surfaces During the CHEESEHEAD19 Campaign

Abstract The water vapor transport associated with latent heat flux (LE) in the planetary boundary layer (PBL) is critical for the atmospheric hydrological cycle, radiation balance, and cloud formation. The spatiotemporal variability of LE and water vapor mixing ratio ( r v ) are poorly understood due to the scale‐dependent and nonlinear atmospheric transport responses to land surface heterogeneity. Here, airborne in situ measurements with the wavelet technique are utilized to investigate scale‐dependent relationships among LE, vertical velocity ( w ) variance (), and r v variance () over a heterogeneous surface during the Chequamegon Heterogeneous Ecosystem Energy‐balance Study Enabled by a High‐density Extensive Array of Detectors 2019 (CHEESEHEAD19) field campaign. Our findings reveal distinct scale distributions of LE, , and at 100 m height, with a majority scale range of 120 m–4 km in LE, 32 m–2 km in , and 200 m–8 km in . The scales are classified into three scale ranges, the turbulent scale (8–200 m), large‐eddy scale (200 m–2 km), and mesoscale (2–8 km) to evaluate scale‐resolved LE contributed by and . The large‐eddy scale in PBL contributes over 70% of the monthly mean total LE with equal parts (50%) of contributions from and . The monthly temporal variations mainly come from the first two major contributing classified scales in LE, , and . These results confirm the dominant role of the large‐eddy scale in the PBL in the vertical moisture transport from the surface to the PBL, while the mesoscale is shown to contribute an additional ∼20%. This analysis complements published scale‐dependent LE variations, which lack detailed scale‐dependent vertical velocity and moisture information.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Modeling and Scaling up of Membrane Modules Leveraging Dimensional Analysis

In the current analysis, we study the separation performance using membrane modules through dimensional analysis (DA). We formulate the main process equations to identify relevant dimensionless numbers inherent in the physics. In particular, we identify that the critical step in the separation process is mass transfer through the selective layer. Remarkably, the dimensionless feed flow (DFfeed) emerges as a crucial factor in describing this process. Not only does DFfeed directly appear in the governing equations, but it also holds a physical significance associated with the time scales for the mass transfer across the feed side and through the selective layer. Regarding the output performance variables, we consider the recovery, stage cut, productivity and purity. In this context, we profit from experimental data and CFD simulations to evaluate the separation performance of the modules when varying the input flowrate, the scale of the module, and the CO2 permeance. These datasets enable us to establish correlations between performance metrics and the dimensionless feed flow. Using simple power functions of DFfeed, we obtain R2 coefficients exceeding 0.99, indicating the accuracy of the correlations built in the present work. In the future, we wish to use DA to understand key transport mechanisms, predict and control module performance, and challenge the universality of these findings by testing various gas separations across different membrane modules beyond our case study.

Pedrozo, Hector A.↗
DOE OSTI2014

Weighing 'El Gordo' with a precision scale: Hubble space telescope weak-lensing analysis of the merging galaxy cluster ACT-CL J0102–4915 at z = 0.87

We present a Hubble Space Telescope weak-lensing study of the merging galaxy cluster 'El Gordo' (ACT-CL J0102–4915) at z = 0.87 discovered by the Atacama Cosmology Telescope (ACT) collaboration as the strongest Sunyaev-Zel'dovich decrement in its ∼1000 deg{sup 2} survey. Our weak-lensing analysis confirms that ACT-CL J0102–4915 is indeed an extreme system consisting of two massive (≳ 10{sup 15} M {sub ☉} each) subclusters with a projected separation of ∼0.7 h{sub 70}{sup −1} Mpc. This binary mass structure revealed by our lensing study is consistent with the cluster galaxy distribution and the dynamical study carried out with 89 spectroscopic members. We estimate the mass of ACT-CL J0102–4915 by simultaneously fitting two axisymmetric Navarro-Frenk-White (NFW) profiles allowing their centers to vary. We use only a single parameter for the NFW mass profile by enforcing the mass-concentration relation from numerical simulations. Our Markov-Chain-Monte-Carlo analysis shows that the masses of the northwestern (NW) and the southeastern (SE) components are M{sub 200c}=(1.38±0.22)×10{sup 15} h{sub 70}{sup −1} M{sub ⊙} and (0.78±0.20)×10{sup 15} h{sub 70}{sup −1} M{sub ⊙}, respectively, where the quoted errors include only 1σ statistical uncertainties determined by the finite number of source galaxies. These mass estimates are subject to additional uncertainties (20%-30%) due to the possible presence of triaxiality, correlated/uncorrelated large scale structure, and departure of the cluster profile from the NFW model. The lensing-based velocity dispersions are 1133{sub −61}{sup +58} km s{sup −1} and 1064{sub −66}{sup +62} km s{sup −1} for the NW and SE components, respectively, which are consistent with their spectroscopic measurements (1290 ± 134 km s{sup –1} and 1089 ± 200 km s{sup –1}, respectively). The centroids of both components are tightly constrained (∼4'') and close to the optical luminosity centers. The X-ray and mass peaks are spatially offset by ∼8'' (∼62 h{sub 70}{sup −1} kpc), which is significant at the ∼2σ confidence level. The mass peak, however, does not lead the gas peak in the direction expected if we are viewing the cluster soon after first core passage during a high speed merger. Under the assumption that the merger is happening in the plane of the sky, extrapolation of the two NFW halos to a radius r{sub 200a}=2.4 h{sub 70}{sup −1} Mpc yields a combined mass of M{sub 200a}=(3.13±0.56)×10{sup 15} h{sub 70}{sup −1} M{sub ⊙}. This extrapolated total mass is consistent with our two-component-based dynamical analysis and previous X-ray measurements, projecting ACT-CL J0102–4915 to be the most massive cluster at z > 0.6 known to date.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Local-scale Arctic tundra heterogeneity affects regional-scale carbon dynamics

In northern Alaska nearly 65% of the terrestrial surface is composed of polygonal ground, where geomorphic tundra landforms disproportionately influence carbon and nutrient cycling over fine spatial scales. Process-based biogeochemical models used for local to Pan-Arctic projections of ecological responses to climate change typically operate at coarse-scales (1km 2 –0.5°) at which fine-scale (<1km 2 ) tundra heterogeneity is often aggregated to the dominant land cover unit. Here, we evaluate the importance of tundra heterogeneity for representing soil carbon dynamics at fine to coarse spatial scales. We leveraged the legacy of data collected near Utqiagvik, Alaska between 1973 and 2016 for model initiation, parameterization, and validation. Simulation uncertainty increased with a reduced representation of tundra heterogeneity and coarsening of spatial scale. Hierarchical cluster analysis of an ensemble of 21 st -century simulations reveals that a minimum of two tundra landforms (dry and wet) and a maximum of 4km 2 spatial scale is necessary for minimizing uncertainties (<10%) in regional to Pan-Arctic modeling applications.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1988

The composite blade structural analyzer (COBSTRAN)

The use and application of the COBSTRAN (COmposite Blade STRuctural ANalyzer) computer code is presented. COBSTRAN was developed at NASA-Lewis and is currently being used for the design and analysis of aircraft engine ducted and unducted fan blades. The features of COBSTRAN are demonstrated for the modeling and analysis of a scaled down wind tunnel model propfan blade made from fiber composites. Comparison of analytical and experimental mode shapes and frequencies are shown, verifying the model development and analysis techniques used. The methodologies and programs developed for this analysis are directly applicable to other propfan blades.

Aiello, Robert A.↗
DOE OSTI2018

Theory-based Scaling of Energy Confinement Time for Future Reactor Design

The scaling of thermal energy confinement time plays important roles in tokamak fusion research. A simple log-linear scaling from regression analysis of a large experimental database has been widely used in terms of the engineering or dimensionless parameters. A particularly important example is the IPB98(y,2) scaling for ELMy H-mode plasmas developed for the ITER project [1].

Park, J.M.↗
NASA NTRS2014

A One-Dimensional Global-Scaling Erosive Burning Model Informed by Blowing Wall Turbulence

A derivation of turbulent flow parameters, combined with data from erosive burning test motors and blowing wall tests results in erosive burning model candidates useful in one-dimensional internal ballistics analysis capable of scaling across wide ranges of motor size. The real-time burn rate data comes from three test campaigns of subscale segmented solid rocket motors tested at two facilities. The flow theory admits the important effect of the blowing wall on the turbulent friction coefficient by using blowing wall data to determine the blowing wall friction coefficient. The erosive burning behavior of full-scale motors is now predicted more closely than with other recent models.

Kibbey, Timothy P.↗
DOE OSTI2018

Nonlocal Analysis of Natural Vibrations of Carbon Nanotubes

When the atomic level is considered, the dynamic properties have a major influence on nanostructures behavior because of their ultrahigh or very high natural frequencies. Vibrations are essential in the analysis of resonators, oscillators, and sensors for carbon nanotube-based devices. The present paper is dedicated to the eigenfrequencies analysis of single-walled carbon nanotubes. In the analysis, the small-scale coefficient is introduced, and the nonlocal elasticity theory is applied in the modal analysis of the carbon nanotubes. The correlation between nonlocal small-scale parameter and the vibrational behavior of the carbon nanotubes is studied. The determination of nonlocal parameter is based on the structural finite element model of the nanotube. A detailed parametric study is realized to investigate the effects of the length-to-diameter ratio L/D, nonlocal coefficient, the influence of boundary conditions on eigenfrequencies of carbon nanotubes. The main contribution of this work is the evaluation of the nonlocal parameter for single-walled carbon nanotubes based on the finite element approximation in modeling the dynamic behavior instead of commonly used MD simulations. It was clearly displayed that the application of the nonlocal beam models involves analysis of the small-scale parameter, whose value determines the final eigenfrequencies. The highest values of eigenfrequencies were observed for the local beam model. It was presented that the eigenfrequencies for carbon nanotubes decrease when the nanotube length increases for all analyzed modes. On the other hand, when the diameter of carbon nanotubes increases, the eigenfrequency values rise. The numerical validation of the nonlocal parameter revealed the high dependence on the boundary conditions and the mode number. However, the influence of the mode number and the boundary conditions is vanishing for long single-walled carbon nanotubes.

36 MATERIALS SCIENCE↗
NASA NTRS1979

Ferrographic analysis of wear debris from full-scale bearing fatigue tests

The Ferrograph was used to determine the types and quantities of wear particles generated during full scale bearing fatigue tests. Deep-groove ball bearings made from steel were used. A tetraester lubricant was used in a recirculating lubricant system containing a 49 micrometers absolute filter. Test conditions include a maximum Hertz stress of 2.4 GPa, a shaft speed of 15,000 rpm, and a lubricant supply temperature of 74 C (165 F). Four fatigue failures were detected by accelerometers in this test set. In general, the Ferrograph was more sensitive (up to 23 hr) in detecting spall initiation than either accelerometers or the normal spectrographic oil analysis. Four particle types were observed: normal rubbing weather particles, spheres, nonferrous particles, and severe wear (spall) fragments.

Jones, W. R., Jr.↗
DOE OSTI2016

Scalable Analysis Methods and In Situ Infrastructure for Extreme Scale Knowledge Discovery

The primary challenge motivating this team’s work is the widening gap between the ability to compute information and to store it for subsequent analysis. This gap adversely impacts science code teams, who are able to perform analysis only on a small fraction of the data they compute, resulting in the very real likelihood of lost or missed science, when results are computed but not analyzed. Our approach is to perform as much analysis or visualization processing on data while it is still resident in memory, an approach that is known as in situ processing. The idea in situ processing was not new at the time of the start of this effort in 2014, but efforts in that space were largely ad hoc, and there was no concerted effort within the research community that aimed to foster production-quality software tools suitable for use by DOE science projects. In large, our objective was produce and enable use of production-quality in situ methods and infrastructure, at scale, on DOE HPC facilities, though we expected to have impact beyond DOE due to the widespread nature of the challenges, which affect virtually all large-scale computational science efforts. To achieve that objective, we assembled a unique team of researchers consisting of representatives from DOE national laboratories, academia, and industry, and engaged in software technology R&D, as well as engaged in close partnerships with DOE science code teams, to produce software technologies that were shown to run effectively at scale on DOE HPC platforms.

97 MATHEMATICS AND COMPUTING↗