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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A Tidal Hydrodynamic Model for Cook Inlet, Alaska, to Support Tidal Energy Resource Characterization

Cook Inlet in Alaska has been identified as a prime site in the U.S. for potential tidal energy development, because of its enormous tidal power potential that accounts for nearly one-third of the national total. As one important step to facilitate tidal energy development, a tidal hydrodynamic model based on the unstructured-grid, finite-volume community ocean model (FVCOM) was developed for Cook Inlet to characterize the tidal stream energy resource. The model has a grid resolution that varies from about 1000 m at the open boundary to 100–300 m inside the Inlet. Extensive model validation was achieved by comparing model predictions with field observations for tidal elevation and velocity at various locations in Cook Inlet. The error statistics confirmed the model performs reasonably well in capturing the tidal dynamics in the system, e.g., R2 > 0.98 for tidal elevation and generally > 0.9 for velocity. Model results suggest that tides in Cook Inlet evolve from progressive waves at the entrance to standing waves at the upper Inlet, and that semi-diurnal tidal constituents are amplified more rapidly than diurnal constituents. The model output was used to identify hotspots that have high energy potential and warrant additional velocity and turbulence measurements such as East Foreland, where averaged power density exceeds 5 kw/m2. Lastly, a tidal energy extraction simulation was conducted for a hypothetical turbine farm configuration at the Forelands cross section to evaluate tidal energy extraction and resulting changes in far-field hydrodynamics.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Turbulent Parameters by airborne measurements over BNF in March 2025

The original data were collected during the AAF Engineering Flights (AEF2025) in the vicinity of the ARM Bankhead National Forest (BNF) Atmospheric Observatory (https://www.arm.gov/capabilities/observatories/bnf ) in northwestern Alabama in March 2025. The ARM Aerial Facility ArcticShark uncrewed aerial system (UAS, https://www.arm.gov/capabilities/observatories/aaf/uas) was based at the public-use airport of Posey Field, Alabama (FAA LID: 1M4, 34.28027778° N, 87.60055556° W, 283m MSL) from March 10 through March 24, 2025. The ArcticShark UAS performed nine flights, including eight research flights over the AMF3 (BNF Main Site) and Supplemental Facilities to measure atmospheric state, turbulence, surface IR temperature and imagery, and aerosol number concentration and size distribution. The current data set presents a collection of turbulent parameters in the atmospheric boundary layer or lower free troposphere based on airborne measurement throughout the field campaign. The primary instruments used to create the current data set were the Aircraft Integrated Meteorological Measurement System (AIMMS-30) and the fine-wire thermocouple probe.

Atmosphere↗
DOE OSTI2025

CHELAX-BNF: Turbulent Parameters by airborne measurements

The original data were collected on board the ARM Aerial Facility ArcticShark uncrewed aerial system (UAS; https://www.arm.gov/capabilities/observatories/aaf/uas ) during the “Characterizing HEterogeneous Land-Atmosphere eXchanges at BNF” field campaign (CHEAX-BNF; https://arm.gov/research/campaigns/aaf2025CHELAX-BNF ). The ARM Aerial Facility ArcticShark UAS was based at the public-use airport of Posey Field, AL (FAA LID: 1M4, 34.28027778° N, 87.60055556° W, 283m MSL) from May 28 through June 23, 2025. The ArcticShark UAS performed 5 flights, including 4 research flights over the BNF Main Site (ARM Mobile Facility 3, https://arm.gov/capabilities/observatories/amf ) and Supplemental Facilities to measure atmospheric state, turbulence, surface IR temperature and imagery, aerosol number concentration, and aerosol size distribution. The current data set presents a collection of turbulent parameters in the atmospheric boundary layer or lower free troposphere based on airborne measurement throughout the field campaign. The primary instruments used to create the current data set were the Aircraft Integrated Meteorological Measurement System (AIMMS-30) and the fine-wire thermocouple probe.

Aircraft Integrated Meteorological Measurement Sys↗
DOE OSTI2025

Tidal energy resource characterization measurements at Cook Inlet’s East Foreland: Velocity and turbulence

To characterize tidal current and turbulence at a top tidal energy site off the East Foreland in Cook Inlet, Alaska, United States, three moorings were deployed for two months between July and August 2021, and a transect survey was conducted over the course of two tidal cycles at the end of the deployment period. Measurements of velocity and turbulence were then analyzed to better understand the site's hydrodynamics and power potential. Analysis reveals that swift, north-flowing flood currents peak at 4~m/s, while south-flowing ebb currents reach just over 3~m/s. Turbulence intensity ranges from 23\% at the seafloor to 8\% near the surface, and the presence of the foreland creates more intense turbulence near-shore during ebb tide than flood. Power availability at the site could be as high as 720~MW, or 13~kW/m$^2$, though the energy available to a marine energy device will be smaller than this estimate because of water-to-wire efficiency and wake losses. The results from this measurement campaign will inform the validation of a high-resolution tidal hydrodynamic model, as well as early tidal energy projects that are beginning to move beyond the prototyping and demonstration stages to full-scale deployments.

McVey, James R.↗
DOE OSTI2020

Internal measurement of magnetic turbulence in ELMy H-mode tokamak plasmas

Magnetic turbulence is directly observed internally in the pedestal of ELMy H-mode tokamak plasmas using a newly developed Faraday-effect polarimetry measurement. Fluctuation amplitude is δb r ≥ 15 G (150–500 kHz), with a ratio of magnetic to density fluctuation |δb r /B|/|δn/n|≥0.15. Here, magnetic turbulence is identified as resulting from micro-tearing-instability and mode growth accompanied by degraded plasma confinement is observed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

NPFTURBULENCE: Turbulent Parameters by airborne measurements

The original data were collected during the field campaign of “Turbulent layers promoting New Particle Formation” experiment (NPFTURBULENCE; https://www.arm.gov/research/campaigns/aaf2024npfturbulence) over the Atmospheric Radiation Measurement (ARM) user facility's Southern Great Plains (SGP) atmospheric observatory (https://www.arm.gov/capabilities/observatories/sgp ) in north-central Oklahoma. The ARM Aerial Facility ArcticShark uncrewed aerial system (UAS, https://www.arm.gov/capabilities/observatories/aaf/uas) was based at Blackwell–Tonkawa Municipal Airport (IATA: BWL, ICAO: KBKN, FAA LID: BKN, 36.74475° N, 97.34918° W, 313.9 m MSL), for the field campaign from May 5 through May 29, 2024. The ArcticShark UAS performed 11 flights, including 10 research flights over the Central Facility of the ARM SGP to measure atmospheric state, turbulence, surface IR temperature and imagery, and aerosol number concentration and size distribution. The current data set presents a comprehensive collection of turbulent parameters in the atmospheric boundary layer or lower free troposphere based on airborne measurement throughout the field campaign. The primary instruments used to create the current data set were the Aircraft Integrated Meteorological Measurement System (AIMMS-30) and the fine-wire thermocouple probe. For user convenience, the current data set includes several parameters commonly used in turbulent research for normalization and/or scaling: atmospheric boundary-layer height, surface conditions, convective scales for temperature, and velocity, etc.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Time-resolved particle image velocimetry measurements of the turbulent Richtmyer–Meshkov instability

Experiments are presented on the Richtmyer–Meshkov instability (RMI) with a three-dimensional, multi-mode initial perturbation. The experiments use a vertical shock tube, where a stably stratified interface is formed between air and sulphur hexafluoride (SF 6 ) via counterflow. A perturbation is imposed at the interface by vertical oscillation of the gas column, forming Faraday waves. The interface is accelerated by a Mach 1.17 (in air) shock wave, and the development of the mixing region between the gases is investigated using particle image velocimetry. Following shock acceleration, a reflected shock wave from the bottom of the shock tube interacts with the mixing layer a second time (reshock). The experiment is initialized with both high and low amplitude perturbations to examine the effect of the perturbation amplitude on measured quantities. The instability growth exponent (θ) is determined from the kinetic energy field using the width of the mixing layer and the decay of kinetic energy, which are found to be in agreement when the flow is most strongly excited. A growth exponent of θ ≈ 0.5 is found for all cases except the high-amplitude reshocked regime (where θ ≈ 0.33). High-amplitude experiments exhibit the transitional outer Reynolds number (Re ≡ hh˙/ν >10 4 ) required for mixing transition following the incident shock, and both experiments are elevated well above this threshold following reshock. However, neither set of experiments meet the more stringent requirements proposed by Zhou et al. (Phys. Rev.E, vol. 67, issue 5, 2003) which include the time dependent aspect of the RMI, an observation which is also made when examining the spectra.

42 ENGINEERING↗
DOE OSTI2022

Dynamic attenuation scheme in measurement-device-independent quantum key distribution over turbulent channels

Measurement-device-independent quantum key distribution (MDI QKD) offers great security in practice because it removes all detector side channels. However, conducting MDI QKD over free-space channels is challenging. One of the largest culprits is the mismatched transmittance of the two independent turbulent channels causing a reduced Hong-Ou-Mandel visibility and thus a lower secret key rate. Here we introduce a dynamic attenuation scheme, where the transmittance of each of the two channels is monitored in real time by transmitting bright light pulses from each users to the measurement device. Based on the measured channel transmittance, a suitable amount of attenuation is introduced to the low-loss channel at the measurement device. Our simulation results show a significant improvement of QKD performance, especially when using short raw keys.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

The driving mode of shock-driven turbulence

Turbulence in the interstellar medium (ISM) is crucial in the process of star formation. Shocks produced by supernova explosions, jets, radiation from massive stars, or galactic spiral-arm dynamics are amongst the most common drivers of turbulence in the ISM. However, it is not fully understood how shocks drive turbulence, in particular whether shock driving is a more solenoidal (rotational, divergence-free) or a more compressive (potential, curl-free) mode of driving turbulence. The mode of turbulence driving has profound consequences for star formation, with compressive driving producing three times larger density dispersion, and an order of magnitude higher star formation rate than solenoidal driving. Here, we use hydrodynamical simulations of a shock inducing turbulent motions in a structured, multiphase medium. This is done in the context of a laser-induced shock, propagating into a foam material, in preparation for an experiment to be performed at the National Ignition Facility (NIF). Specifically, we analyse the density and velocity distributions in the shocked turbulent medium, and measure the turbulence driving parameter $b=(\sigma _{\rho /\langle \rho \rangle }^{2\Gamma }-1)^{1/2}(1-\sigma _{\rho /\langle \rho \rangle }^{-2})^{-1/2}\mathcal {M}^{-1}\Gamma ^{-1/2}$, with the density dispersion σρ/<ρ>, the turbulent Mach number $\mathcal {M}$, and the polytropic exponent Γ. Purely solenoidal and purely compressive driving correspond to b ~ 1/3 and b ~ 1, respectively. As a result, using simulations in which a shock is driven into a multiphase medium with structures of different sizes and Γ < 1, we find b ~ 1 for all cases, showing that shock-driven turbulence is consistent with strongly compressive driving.

79 ASTRONOMY AND ASTROPHYSICS↗