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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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297 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Prediction of Acoustic Environments from Horizontal Rocket Firings

In recent years, advances in research and engineering have led to more powerful launch vehicles which can reach areas of space not yet explored. These more powerful vehicles yield acoustic environments potentially destructive to the vehicle or surrounding structures. Therefore, it has become increasingly important to be able to predict the acoustic environments created by these vehicles in order to avoid structural and/or competent failure. The current industry standard technique for predicting launch-induced acoustic environments was developed by Eldred in the early 1970's and is published in NASA SP-80721. Recent work2 has shown Eldred's technique to be inaccurate for current state-of-the-art launch vehicles. Due to the high cost of full-scale and even sub-scale rocket experiments, very little rocket noise data is available. Furthermore, much of the work thought to be applicable to rocket noise has been done with heated jets. Tam3,4 has done an extensive amount of research on jets of different nozzle exit shape, diameter, velocity, and temperature. Though the values of these parameters, especially exit velocity and temperature, are often very low compared to these values in rockets, a lot can be learned about rocket noise from jet noise literature. The turbulent nature of jet and rocket exhausts is quite similar. Both exhausts contain turbulent structures of varying scale-termed the fine and large scale turbulence by Tam. The finescale turbulence is due to small eddies from the jet plume interacting with the ambient atmosphere. According to Tam et al., the noise radiated by this envelope of small-scale turbulence is statistically isotropic. Hence, one would expect the noise from the small scale turbulence of the jet to be nearly omni-directional. The coherent nature of the large-scale turbulence results in interference of the noise radiated from different spatial locations within the jet. This interference-whether it is constructive or destructive-results in highly directional noise radiation. Tam3 has proposed a model to predict the acoustic environment due to jets and while it works extremely well for jets, it was found to be inappropriate for rockets8. A model to predict the acoustic environment due to a launch vehicle in the far-field which incorporates concepts from both Eldred and Tam was created. This was done using five sets of horizontally fired rocket data, obtained between 2008 and 2012. Three of these rockets use solid propellant and two use liquid propellant. Through scaling analysis, it is shown that liquid and solid rocket motors exhibit similar spectra at similar amplitudes. This model is accurate for these five data sets within 5 dB of the measured data for receiver angles of 30deg to 160deg (with respect to the downstream exhaust centerline). The model uses the following vehicle parameters: nozzle exit diameter and velocity, radial distance from source to receiver, receiver angle, mass flow rate, and acoustic efficiency.

Giacomoni, Clothilde↗
NASA NTRS2013

The Atacama Cosmology Telescope: Likelihood for Small-Scale CMB Data

The Atacama Cosmology Telescope has measured the angular power spectra of microwave fluctuations to arcminute scales at frequencies of 148 and 218 GHz, from three seasons of data. At small scales the fluctuations in the primordial Cosmic Microwave Background (CMB) become increasingly obscured by extragalactic foregounds and secondary CMB signals. We present results from a nine-parameter model describing these secondary effects, including the thermal and kinematic Sunyaev-Zel'dovich (tSZ and kSZ) power; the clustered and Poisson-like power from Cosmic Infrared Background (CIB) sources, and their frequency scaling; the tSZ-CIB correlation coefficient; the extragalactic radio source power; and thermal dust emission from Galactic cirrus in two different regions of the sky. In order to extract cosmological parameters, we describe a likelihood function for the ACT data, fitting this model to the multi-frequency spectra in the multipole range 500 < l < 10000. We extend the likelihood to include spectra from the South Pole Telescope at frequencies of 95, 150, and 220 GHz. Accounting for different radio source levels and Galactic cirrus emission, the same model provides an excellent fit to both datasets simultaneously, with χ2/dof= 675/697 for ACT, and 96/107 for SPT. We then use the multi-frequency likelihood to estimate the CMB power spectrum from ACT in bandpowers, marginalizing over the secondary parameters. This provides a simplified 'CMB-only' likelihood in the range 500 < l < 3500 for use in cosmological parameter estimation

Cosmology↗
NASA NTRS2018

Measurements to Understand the Flow Mechanisms Contributing to Tandem-Rotor Outwash

Downwash and outwash characteristics of a model-scale tandem-rotor system in the presence of the ground were analyzed by identifying and understanding the physical mechanisms contributing to the observed flow field behavior. A building block approach was followed in simplifying the problem, separating the effects of the fuselage, effects of one rotor on the other, etc. Flow field velocities were acquired in a vertical plane at four aircraft azimuths of a small-scale tandem rotor system using the particle image velocimetry (PIV) technique for radial distances up to 4 times the rotor diameter. Results were compared against full-scale CH-47D measurements. Excellent correlation was found between the small- and full-scale mean flow fields (after appropriate normalization using rotor and wall jet parameters). Following the scalability analysis, the effect of rotor height on the outwash was also studied. Close to the aircraft, an increase in rotor height above ground decreased the outwash velocity at all aircraft azimuths. However, farther away, the longitudinal and lateral axes of the aircraft showed increasing and decreasing outwash velocities, respectively, with increasing rotor height. Measurements also indicated the presence of large-scale (of the size of the rotor height) shear-layer vortical structures along the ground that could be the source of low-frequency (approximately 1 Hz) flow variation observed in the full-scale measurements. Flow visualization studies and PIV measurements were also made on jets of different sizes to complement the observations made on rotors wherever possible. Baseline rotor measurements were made out-of-ground effect to understand the nature of inflow distribution for realistic rotor configurations and their modified characteristics in the presence of ground. Lastly, a feasibility study on applying high-fidelity CFD simulations for outwash study was conducted using Helios to model an isolated rotor configuration IGE at full scale Reynolds number. The results were encouraging and demonstrated the practical challenges associated with predicting rotor outwash.

Measurements↗
NASA NTRS2015

Measurements to Understand the Flow Mechanisms Contributing to Tandem-Rotor Outwash

Downwash and outwash characteristics of a model-scale tandem-rotor system in the presence of the ground were analyzed by identifying and understanding the physical mechanisms contributing to the observed flow field behavior. A building block approach was followed in simplifying the problem, separating the effects of the fuselage, effects of one rotor on the other, etc. Flow field velocities were acquired in a vertical plane at four aircraft azimuths of a small-scale tandem rotor system using the particle image velocimetry (PIV) technique for radial distances up to 4 times the rotor diameter. Results were compared against full-scale CH-47D measurements. Excellent correlation was found between the small- and full-scale mean flow fields (after appropriate normalization using rotor and wall jet parameters). Following the scalability analysis, the effect of rotor height on the outwash was also studied. Close to the aircraft, an increase in rotor height above ground decreased the outwash velocity at all aircraft azimuths. However, farther away, the longitudinal and lateral axes of the aircraft showed increasing and decreasing outwash velocities, respectively, with increasing rotor height. Measurements also indicated the presence of large-scale (of the size of the rotor height) shear-layer vortical structures along the ground that could be the source of low-frequency (approximately 1 Hz) flow variation observed in the full-scale measurements. Flow visualization studies and PIV measurements were also made on jets of different sizes to complement the observations made on rotors wherever possible. Baseline rotor measurements were made out-of-ground effect to understand the nature of inflow distribution for realistic rotor configurations and their modified characteristics in the presence of ground. Lastly, a feasibility study on applying high-fidelity CFD simulations for outwash study was conducted using Helios to model an isolated rotor configuration IGE at full-scale Reynolds number. The results were encouraging and demonstrated the practical challenges associated with predicting rotor outwash.

Ramasamy, Manikandan↗
NASA NTRS2021

Accuracy Assessment of Global Internal-Tide Models Using Satellite Altimetry Models Using Satellite Altimetry

Altimeter measurements are corrected for several geophysical parameters in order to access ocean signals of interest, like mesoscale or sub-mesoscale variability. The ocean tide is one of the most critical corrections due to the amplitude of the tidal elevations and to the aliasing phenomena of high-frequency signals into the lower-frequency band, but the internal-tide signatures at the ocean surface are not yet corrected globally. Internal tides can have a signature of several centimeters at the surface with wavelengths of about 50–250 km for the first mode and even smaller scales for higher-order modes. The goals of the upcoming Surface Water Ocean Topography (SWOT) mission and other high-resolution ocean measurements make the correction of these small-scale signals a challenge, as the correction of all tidal variability becomes mandatory to access accurate measurements of other oceanic signals. In this context, several scientific teams are working on the development of new internal-tide models, taking advantage of the very long altimeter time series now available, which represent an unprecedented and valuable global ocean database. The internal-tide models presented here focus on the coherent internal-tide signal and they are of three types: empirical models based upon analysis of existing altimeter missions, an assimilative model and a three-dimensional hydrodynamic model. A detailed comparison and validation of these internal-tide models is proposed using existing satellite altimeter databases. The analysis focuses on the four main tidal constituents: M2, K1, O1 and S2. The validation process is based on a statistical analysis of multi-mission altimetry including Jason-2 and Cryosphere Satellite-2 data. The results show a significant altimeter variance reduction when using internal-tide corrections in all ocean regions where internal tides are generating or propagating. A complementary spectral analysis also gives some estimation of the performance of each model as a function of wavelength and some insight into the residual non-stationary part of internal tides in the different regions of interest. This work led to the implementation of a new internal-tide correction (ZARON'one) in the next geophysical data records version-F (GDR-F) standards.

Loren Carrere↗
NASA NTRS2022

Magnetic Field Intermittency in the Solar Wind: Parker Solar Probe and SolO Observations Ranging from the Alfvén Region up to 1AU

Parker Solar Probe (PSP) and SolO data are utilized to investigate magnetic field intermittency in the solar wind (SW). Small-scale intermittency (20−100 di) is observed to radially strengthen when methods relying on higher-order moments are considered (SFq; SDK), but no clear trend is observed at larger scales. However, lower-order moment-based methods (e.g., partial variance of increments; PVI) are deemed more appropriate for examining the evolution of the bulk of coherent structures (CSs), PVI ≥ 3. Using PVI, we observe a scale-dependent evolution in the fraction of the data set occupied by CSs, fPVI≥3. Specifically, regardless of the SW speed, a subtle increase is found in fPVI≥3 for ℓ = 20 di, in contrast to a more pronounced radial increase in CSs observed at larger scales. Intermittency is investigated in relation to plasma parameters. Though, slower SW speed intervals exhibit higher fPVI≥6 and higher kurtosis maxima, no statistical differences are observed for fPVI≥3. Highly Alfvénic intervals display lower levels of intermittency. The anisotropy with respect to the angle between the magnetic field and SW flow, ΘVB is investigated. Intermittency is weaker at ΘVB ≈ 0° and is strengthened at larger angles. Considering the evolution at a constant alignment angle, a weakening of intermittency is observed with increasing advection time of the SW. Our results indicate that the strengthening of intermittency in the inner heliosphere is driven by the increase in comparatively highly intermittent perpendicular intervals sampled by the probes with increasing distance, an effect related directly to the evolution of the Parker spiral.

Nikos Sioulas↗
NASA NTRSDate not supplied

Using NASA Earth Observations to Identify Trends in Harmful Algal Blooms in Narragansett Bay

Narragansett Bay in Rhode Island is known for its quahog, or hard-shell clam, shellfisheries. However, increased levels in harmful algal blooms (HABs) have posed threats to quahog populations and raised public health concerns due to shellfishery closures resulting from contamination with neurotoxins released by phytoplankton. NASA DEVELOP partnered with the Environmental Protection Agency’s National Health and Environmental Effects Research Laboratory and Rhode Island’s Department of Environmental Management to use Earth observations and the partners’ in-situ data to visualize phytoplankton bloom events within the bay. The team used Sentinel-3 Ocean and Land Color Instrument (OLCI), Landsat 8 Operational Land Imager (OLI), and Landsat 9 OLI-2 to track proposed proxies for phytoplankton from June 2016 to October 2023. Multiple sensors and datasets were employed for more accurate results due to the small spatial extent of Narragansett Bay. Chlorophyll-a and total suspended solids were determined to be accurate parameters to monitor HAB events. Although complications could arise due to the relatively small size of the bay and small-scale of the bloom events, which may be difficult to visualize via remote sensing, Earth observations have proven to help strengthen HAB research, monitoring, and prediction and will complement the extensive in-situ data in Narragansett Bay.

Isabella Giordano↗
DOE OSTI2021

Dark Energy Survey Year 3 Results: Constraints on cosmological parameters and galaxy bias models from galaxy clustering and galaxy-galaxy lensing using the redMaGiC sample

We constrain cosmological parameters and galaxy-bias parameters using the combination of galaxy clustering and galaxy-galaxy lensing measurements from the Dark Energy Survey Year-3 data. We describe our modeling framework and choice of scales analyzed, validating their robustness to theoretical uncertainties in small-scale clustering by analyzing simulated data. Using a linear galaxy bias model and redMaGiC galaxy sample, we obtain constraints on the matter content of the universe to be $\Omega_{\rm m} = 0.325^{+0.033}_{-0.034}$. We also implement a non-linear galaxy bias model to probe smaller scales that includes parameterizations based on hybrid perturbation theory, and find that it leads to a 17% gain in cosmological constraining power. Using the redMaGiC galaxy sample as foreground lens galaxies, we find the galaxy clustering and galaxy-galaxy lensing measurements to exhibit significant signals akin to decorrelation between galaxies and mass on large scales, which is not expected in any current models. This likely systematic measurement error biases our constraints on galaxy bias and the $S_8$ parameter. We find that a scale-, redshift- and sky-area-independent phenomenological decorrelation parameter can effectively capture this inconsistency between the galaxy clustering and galaxy-galaxy lensing. We perform robustness tests of our methodology pipeline and demonstrate stability of the constraints to changes in the theory model. After accounting for this decorrelation, we infer the constraints on the mean host halo mass of the redMaGiC galaxies from the large-scale bias constraints, finding the galaxies occupy halos of mass approximately $1.5 \times 10^{13} M_{\odot}/h$.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Invertible Temper Modeling using Normalizing Flows and the Effects of Structure Preserving Loss

Advanced manufacturing research and development is typically small-scale, owing to costly experiments associated with these novel processes. Deep learning techniques could help accelerate this development cycle but frequently struggle in small-data regimes like the advanced manufacturing space. While prior work has applied deep learning to modeling visually plausible advanced manufacturing microstructures, little work has been done on data-driven modeling of how microstructures are affected by heat treatment, or assessing the degree to which synthetic microstructures are able to support existing workflows. We propose to address this gap by using invertible neural networks (normalizing flows) to model the effects of heat treatment, e.g., tempering. The model is developed using scanning electron microscope imagery from samples produced using shear-assisted processing and extrusion (ShAPE) manufacturing. This approach not only produces visually and topologically plausible samples, but also captures information related to a sample’s material properties or experimental process parameters. We also demonstrate that topological data analysis, used in prior work to characterize microstructures, can also be used to stabilize model training, preserve structure, and improve downstream results. We assess directions for future work and identify our approach as an important step towards end-to-end deep learning system for accelerating advanced manufacturing research and development.

Howland, Sylvia↗