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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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Aeroacoustic research programs at the Army Aviation Research and Technology Activity

The Army rotorcraft aeroacoustic programs are reviewed, highlighting the theoretical and experimental progress made by Army researchers in the physical understanding of helicopter impulsive noise. The two impulsive noise sources addressed over this past decade are high-speed impulsive noise and blade-vortex interaction noise, both of which have had and will continue to have an increasing influence on Army rotorcraft design and operations. The advancements discussed are in the areas of in-flight data acquisition techniques, small-scale-model tests in wind tunnels, holographic interferometry/tomographic techniques, and the expanding capabilities of computational fluid dynamics in rotorcraft acoustic problems. Current theoretical prediction methods are compared with experimental data, and parameters that govern model scaling are established. The very successful cooperative efforts between the Army, NASA, and industry are also addressed

Yu, Yung H.↗
NASA NTRS1984

NTF Modeling Program

The National Transonic Facility presents a design for and assessment of a transonic wind tunnel. Among the topics covered in viewgraph format are: aerodynamic validation models, scale models of wind tunnel components, performance evaluations of various wind tunnel parameters, and drive systems.

McKinney, L. Wayne↗
NASA NTRS2001

X-38 Experimental Aeroheating at Mach 10

This report provides an update of the hypersonic aerothermodynamic wind tunnel test program conducted at the NASA Langley Research Center in support of the X-38 program. Global surface heat transfer distributions were measured on 0.0177 and 0.0236 scale models of the proposed X-38 configuration at Mach 10 in air. The parametrics that were investigated primarily include freestream unit Reynolds numbers of 0.6 to 2.2 million per foot and body flap deflections of 15, 20, and 25 deg for an angle-of-attack of 40 deg. The model-scale variance was tested to obtain laminar, transitional, and turbulent heating levels on the defected bodyflaps. In addition, a limited investigation of forced boundary layer transition through the use of discrete roughness elements was performed. Comparisons of the present experimental results to computational predictions and previous experimental data were conducted Laminar, transitional, and turbulent heating levels were observed on the deflected body flap, which compared favorably to the computational results and to the predicted heating based on the flight aerothermodynamic database.

Berry, Scott A.↗
NASA NTRS2002

Advanced Nacelle Acoustic Lining Concepts Development

The work reported in this document consisted of six distinct liner technology development subtasks: 1) Analysis of Model Scale ADP Fan Duct Lining Data (Boeing): An evaluation of an AST Milestone experiment to demonstrate 1995 liner technology superiority relative to that of 1992 was performed on 1:5.9 scale model fan rig (Advanced Ducted Propeller) test data acquired in the NASA Glenn 9 x 15 foot wind tunnel. The goal of 50% improvement was deemed satisfied. 2) Bias Flow Liner Investigation (Boeing, VCES): The ability to control liner impedance by low velocity bias flow through liner was demonstrated. An impedance prediction model to include bias flow was developed. 3) Grazing Flow Impedance Testing (Boeing): Grazing flow impedance tests were conducted for comparison with results achieved at four different laboratories. 4) Micro-Perforate Acoustic Liner Technology (BFG, HAE, NG): Proof of concept testing of a "linear liner." 5) Extended Reaction Liners (Boeing, NG): Bandwidth improvements for non-locally reacting liner were investigated with porous honeycomb core test liners. 6) Development of a Hybrid Active/Passive Lining Concept (HAE): Synergism between active and passive attenuation of noise radiated by a model inlet was demonstrated.

Bielak, G.↗
NASA NTRS2006

Flight Test Results for Uniquely Tailored Propulsion-Airframe Aeroacoustic Chevrons: Community Noise

The flow/acoustic environment around the jet exhaust of an engine when installed on an airplane, say, under the wing, is highly asymmetric due to the pylon, the wing and the high-lift devices. Recent scale model tests have shown that such Propulsion Airframe Aeroacoustic (PAA) interactions and the jet mixing noise can be reduced more than with conventional azimuthally uniform chevrons by uniquely tailoring the chevrons to produce enhanced mixing near the pylon. This paper describes the community noise results from a flight test on a large twin-engine airplane using this concept of azimuthally varying chevrons for engines installed under the wing. Results for two different nozzle configurations are described: azimuthally varying "PAA T-fan" chevrons on the fan nozzle with a baseline no-chevron core nozzle and a second with PAA T-fan chevrons with conventional azimuthally uniform chevrons on the core nozzle. We analyze these test results in comparison to the baseline no-chevron nozzle on both spectral and integrated power level bases. The study focuses on the peak jet noise reduction and the effects at high frequencies for typical take-off power settings. The noise reduction and the absolute noise levels are then compared to model scale results. The flight test results verify that the PAA T-fan nozzles in combination with standard core chevron nozzles can, indeed, give a reasonable amount of noise reduction at low frequencies without high-frequency lift during take-off conditions and hardly any impact on the cruise thrust coefficient.

Nesbitt, Eric↗
NASA NTRS1979

Experimental studies of radiative base heating of a Jovian entry model

A scale model of the Jovian entry vehicle of 6.4 cm diameter is tested in an electric-arc-driven shock tube while a sphere model of 5 cm diameter is tested in a combustion-driven shock tube and an electric-arc-driven shock tunnel. The radiative heat-transfer rate and pressure on the front and the base regions are measured in the absence of ablation with sensors imbedded in the models in a stream consisting of 10% hydrogen in a bath of either neon or argon. The measured radiative heat-transfer rates and pressures are up to about 22 kW/sq cm and 12 atm, respectively, at the front stagnation point. The ratio of the base-to-stagnation-point radiative heat-transfer rates is found to be about 1/4 for the sphere at Mach 1.8, about 1/30 for the sphere at Mach 4.8, and about 1/6 for the scale model at Mach 1.7. When the effects of model geometry and Mach number are accounted for, the present experimental results agree well with the theoretical prediction of Park.

Shirai, H.↗
DOE OSTI2023

Physics–Informed Neural Networks of the Saint–Venant Equations for Downscaling a Large–Scale River Model

Large-scale river models are being refined over coastal regions to improve the scientific understanding of coastal processes, hazards and responses to climate change. However, coarse mesh resolutions and approximations in physical representations of tidal rivers limit the performance of such models at resolving the complex flow dynamics near the river-ocean interface, resulting in inaccurate simulations of flood inundation. In this research, we propose a machine learning (ML) framework based on the state-of-the-art physics-informed neural network (PINN) to simulate the downscaled flow at the subgrid scale. First, we demonstrate that PINN is able to assimilate observations of various types and solve the one-dimensional (1-D) Saint-Venant equations (SVE) directly. We perform the flow simulations over a floodplain and along an open channel in several synthetic case studies. The PINN performance is evaluated against analytical solutions and numerical models. Our results indicate that the PINN solutions of water depth have satisfactory accuracy with limited observations assimilated. In the case of flood wave propagation induced by storm surge and tide, a new neural network architecture is proposed based on Fourier feature embeddings that seamlessly encodes the periodic tidal boundary condition in the PINN's formulation. Furthermore, we show that the PINN-based downscaling can produce more reasonable subgrid solutions of the along-channel water depth by assimilating observational data. The PINN solution outperforms the simple linear interpolation in resolving the topography and dynamic flow regimes at the subgrid scale. This study provides a promising path towards improving emulation capabilities in large-scale models to characterize fine-scale coastal processes.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1976

The global reference atmospheric model, mod 2 (with two scale perturbation model)

The Global Reference Atmospheric Model was improved to produce more realistic simulations of vertical profiles of atmospheric parameters. A revised two scale random perturbation model using perturbation magnitudes which are adjusted to conform to constraints imposed by the perfect gas law and the hydrostatic condition is described. The two scale perturbation model produces appropriately correlated (horizontally and vertically) small scale and large scale perturbations. These stochastically simulated perturbations are representative of the magnitudes and wavelengths of perturbations produced by tides and planetary scale waves (large scale) and turbulence and gravity waves (small scale). Other new features of the model are: (1) a second order geostrophic wind relation for use at low latitudes which does not "blow up" at low latitudes as the ordinary geostrophic relation does; and (2) revised quasi-biennial amplitudes and phases and revised stationary perturbations, based on data through 1972.

Justus, C. G.↗
DOE OSTI2019

Tree mortality submodels drive simulated long-term forest dynamics: assessing 15 models from the stand to global scale

Models are pivotal for assessing future forest dynamics under the impacts of changing climate and management practices, incorporating representations of tree growth, mortality, and regeneration. Quantitative studies on the importance of mortality submodels are scarce. We evaluated 15 dynamic vegetation models (DVMs) regarding their sensitivity to different formulations of tree mortality under different degrees of climate change. The set of models comprised eight DVMs at the stand scale, three at the landscape scale, and four typically applied at the continental to global scale. Some incorporate empirically derived mortality models, and others are based on experimental data, whereas still others are based on theoretical reasoning. Each DVM was run with at least two alternative mortality submodels. Model behavior was evaluated against empirical time series data, and then, the models were subjected to different scenarios of climate change. Most DVMs matched empirical data quite well, irrespective of the mortality submodel that was used. However, mortality submodels that performed in a very similar manner against past data often led to sharply different trajectories of forest dynamics under future climate change. Most DVMs featured high sensitivity to the mortality submodel, with deviations of basal area and stem numbers on the order of 10–40% per century under current climate and 20–170% under climate change. The sensitivity of a given DVM to scenarios of climate change, however, was typically lower by a factor of two to three. We conclude that (1) mortality is one of the most uncertain processes when it comes to assessing forest response to climate change, and (2) more data and a better process understanding of tree mortality are needed to improve the robustness of simulated future forest dynamics. Our study highlights that comparing several alternative mortality formulations in DVMs provides valuable insights into the effects of process uncertainties on simulated future forest dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Advanced modeling to accelerate the scale up of carbon capture technologies

In order to help meet the goals of the DOE carbon capture program, the Carbon Capture Simulation Initiative (CCSI) was launched in early 2011 to develop, demonstrate, and deploy advanced computational tools and validated multi-scale models to reduce the time required to develop and scale-up new carbon capture technologies. This article focuses on essential elements related to the development and validation of multi-scale models in order to help minimize risk and maximize learning as new technologies progress from pilot to demonstration scale.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2015

Calculations of inflaton decays and reheating: with applications to no-scale inflation models

We discuss inflaton decays and reheating in no-scale Starobinsky-like models of inflation, calculating the effective equation-of-state parameter, w, during the epoch of inflaton decay, the reheating temperature, T{sub reh}, and the number of inflationary e-folds, N{sub ∗}, comparing analytical approximations with numerical calculations. We then illustrate these results with applications to models based on no-scale supergravity and motivated by generic string compactifications, including scenarios where the inflaton is identified as an untwisted-sector matter field with direct Yukawa couplings to MSSM fields, and where the inflaton decays via gravitational-strength interactions. Finally, we use our results to discuss the constraints on these models imposed by present measurements of the scalar spectral index n{sub s} and the tensor-to-scalar perturbation ratio r, converting them into constraints on N{sub ∗}, the inflaton decay rate and other parameters of specific no-scale inflationary models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Using Advanced Modeling to Accelerate the Scale-Up of Carbon Capture Technologies

Carbon capture and storage (CCS) is one of many approaches that are critical for significantly reducing domestic and global CO2 emissions. The U.S. Department of Energy’s Clean Coal Technology Program Plan envisions 2nd generation CO2 capture technologies ready for demonstration-scale testing around 2020 with the goal of enabling commercial deployment by 2025 [1]. Third generation technologies have a similarly aggressive timeline. A major challenge is that the development and scale-up of new technologies in the energy sector historically takes up to 15 years to move from the laboratory to pre-deployment and another 20 to 30 years for widespread industrial scale deployment. In order to help meet the goals of the DOE carbon capture program, the Carbon Capture Simulation Initiative (CCSI) was launched in early 2011 to develop, demonstrate, and deploy advanced computational tools and validated multi-scale models to reduce the time required to develop and scale up new carbon capture technologies. The CCSI Toolset (1) enables promising concepts to be more quickly identified through rapid computational screening of processes and devices, (2) reduces the time to design and troubleshoot new devices and processes by using optimization techniques to focus development on the best overall process conditions and by using detailed device-scale models to better understand and improve the internal behavior of complex equipment, and (3) provides quantitative predictions of device and process performance during scale up based on rigorously validated smaller scale simulations that take into account model and parameter uncertainty[2]. This article focuses on essential elements related to the development and validation of multi-scale models in order to help minimize risk and maximize learning as new technologies progress from pilot to demonstration scale.

Miller, David↗
NASA NTRS1975

Revised Perturbation Statistics for the Global Scale Atmospheric Model

Magnitudes and scales of atmospheric perturbations about the monthly mean for the thermodynamic variables and wind components are presented by month at various latitudes. These perturbation statistics are a revision of the random perturbation data required for the global scale atmospheric model program and are from meteorological rocket network statistical summaries in the 22 to 65 km height range and NASA grenade and pitot tube data summaries in the region up to 90 km. The observed perturbations in the thermodynamic variables were adjusted to make them consistent with constraints required by the perfect gas law and the hydrostatic equation. Vertical scales were evaluated by Buell's depth of pressure system equation and from vertical structure function analysis. Tables of magnitudes and vertical scales are presented for each month at latitude 10, 30, 50, 70, and 90 degrees.

Justus, C. G.↗
DOE OSTI2014

Likelihood-based gene annotations for gap filling and quality assessment in genome-scale metabolic models

Genome-scale metabolic models provide a powerful means to harness information from genomes to deepen biological insights. With exponentially increasing sequencing capacity, there is an enormous need for automated reconstruction techniques that can provide more accurate models in a short time frame. Current methods for automated metabolic network reconstruction rely on gene and reaction annotations to build draft metabolic networks and algorithms to fill gaps in these networks. However, automated reconstruction is hampered by database inconsistencies, incorrect annotations, and gap filling largely without considering genomic information. Here we develop an approach for applying genomic information to predict alternative functions for genes and estimate their likelihoods from sequence homology. We show that computed likelihood values were significantly higher for annotations found in manually curated metabolic networks than those that were not. We then apply these alternative functional predictions to estimate reaction likelihoods, which are used in a new gap filling approach called likelihood-based gap filling to predict more genomically consistent solutions. To validate the likelihood-based gap filling approach, we applied it to models where essential pathways were removed, finding that likelihood-based gap filling identified more biologically relevant solutions than parsimony-based gap filling approaches. We also demonstrate that models gap filled using likelihood-based gap filling provide greater coverage and genomic consistency with metabolic gene functions compared to parsimony-based approaches. Interestingly, despite these findings, we found that likelihoods did not significantly affect consistency of gap filled models with Biolog and knockout lethality data. This indicates that the phenotype data alone cannot necessarily be used to discriminate between alternative solutions for gap filling and therefore, that the use of other information is necessary to obtain a more accurate network. All described workflows are implemented as part of the DOE Systems Biology Knowledgebase (KBase) and are publicly available via API or command-line web interface.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2017

Acoustic Model Testing Chronology

Scale models have been used for decades to replicate liftoff environments and in particular acoustics for launch vehicles. It is assumed, and analyses supports, that the key characteristics of noise generation, propagation, and measurement can be scaled. Over time significant insight was gained not just towards understanding the effects of thruster details, pad geometry, and sound mitigation but also to the physical processes involved. An overview of a selected set of scale model tests are compiled here to illustrate the variety of configurations that have been tested and the fundamental knowledge gained. The selected scale model tests are presented chronologically.

Nesman, Tom↗
DOE OSTI2015

Grain-Size Based Additivity Models for Scaling Multi-rate Uranyl Surface Complexation in Subsurface Sediments

This study statistically analyzed a grain-size based additivity model that has been proposed to scale reaction rates and parameters from laboratory to field. The additivity model assumed that reaction properties in a sediment including surface area, reactive site concentration, reaction rate, and extent can be predicted from field-scale grain size distribution by linearly adding reaction properties for individual grain size fractions. This study focused on the statistical analysis of the additivity model with respect to reaction rate constants using multi-rate uranyl (U(VI)) surface complexation reactions in a contaminated sediment as an example. Experimental data of rate-limited U(VI) desorption in a stirred flow-cell reactor were used to estimate the statistical properties of multi-rate parameters for individual grain size fractions. The statistical properties of the rate constants for the individual grain size fractions were then used to analyze the statistical properties of the additivity model to predict rate-limited U(VI) desorption in the composite sediment, and to evaluate the relative importance of individual grain size fractions to the overall U(VI) desorption. The result indicated that the additivity model provided a good prediction of the U(VI) desorption in the composite sediment. However, the rate constants were not directly scalable using the additivity model, and U(VI) desorption in individual grain size fractions have to be simulated in order to apply the additivity model. An approximate additivity model for directly scaling rate constants was subsequently proposed and evaluated. The result found that the approximate model provided a good prediction of the experimental results within statistical uncertainty. This study also found that a gravel size fraction (2-8mm), which is often ignored in modeling U(VI) sorption and desorption, is statistically significant to the U(VI) desorption in the sediment.

Zhang, Xiaoying↗