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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 55 records · Page 3

AWAKEN Virtual Tower / Derived Data

Virtual tower data consist of profiles of wind speed and direction at a number of locations near the A1 site. These profiles were computed from dual-Doppler analysis of two Halo XR+ scanning Doppler lidars located at sites A5 and A7. Both lidars performed shallow RHI scans in the general direction of the A1 site. Scan azimuths were periodically adjusted to sample different locations. This resulted in a total of 14 unique tower locations over 5 periods between 12 November 2022 and 17 October 2023.

17 WIND ENERGY↗

AWAKEN Virtual Tower / Derived Data

Virtual tower data consist of profiles of wind speed and direction at a number of locations near the A1 site. These profiles were computed from dual-Doppler analysis of two Halo XR+ scanning Doppler lidars located at sites A5 and A7. Both lidars performed shallow RHI scans in the general direction of the A1 site. Scan azimuths were periodically adjusted to sample different locations. This resulted in a total of 14 unique tower locations over 5 periods between 12 November 2022 and 17 October 2023.

17 WIND ENERGY↗

AWAKEN Virtual Tower / Derived Data

Virtual tower data consist of profiles of wind speed and direction at a number of locations near the A1 site. These profiles were computed from dual-Doppler analysis of two Halo XR+ scanning Doppler lidars located at sites A5 and A7. Both lidars performed shallow RHI scans in the general direction of the A1 site. Scan azimuths were periodically adjusted to sample different locations. This resulted in a total of 14 unique tower locations over 5 periods between 12 November 2022 and 17 October 2023.

17 WIND ENERGY↗

AWAKEN Virtual Tower / Derived Data

Virtual tower data consist of profiles of wind speed and direction at a number of locations near the A1 sites. These profiles were computed from dual-Doppler analysis of two Halo XR+ scanning Doppler lidars located at sites A5 and A7. Both lidars performed shallow RHI scans in the general direction of the A1 site. Scan azimuths were periodically adjusted to sample different locations. This resulted in a total of 14 unique tower locations over 5 periods between 12 November 2022 and 17 October 2023.

17 WIND ENERGY↗

AWAKEN Virtual Tower / Derived Data

Virtual tower data consist of profiles of wind speed and direction at a number of locations near the A1 sites. These profiles were computed from dual-Doppler analysis of two Halo XR+ scanning Doppler lidars located at sites A5 and A7. Both lidars performed shallow RHI scans in the general direction of the A1 site. Scan azimuths were periodically adjusted to sample different locations. This resulted in a total of 14 unique tower locations over 5 periods between 12 November 2022 and 17 October 2023.

17 WIND ENERGY↗

AWAKEN Virtual Tower / Derived Data

Virtual tower data consist of profiles of wind speed and direction at a number of locations near the A1 sites. These profiles were computed from dual-Doppler analysis of two Halo XR+ scanning Doppler lidars located at sites A5 and A7. Both lidars performed shallow RHI scans in the general direction of the A1 site. Scan azimuths were periodically adjusted to sample different locations. This resulted in a total of 14 unique tower locations over 5 periods between 12 November 2022 and 17 October 2023.

17 WIND ENERGY↗

AWAKEN Virtual Tower / Derived Data

Virtual tower data consist of profiles of wind speed and direction at a number of locations near the A1 sites. These profiles were computed from dual-Doppler analysis of two Halo XR+ scanning Doppler lidars located at sites A5 and A7. Both lidars performed shallow RHI scans in the general direction of the A1 site. Scan azimuths were periodically adjusted to sample different locations. This resulted in a total of 14 unique tower locations over 5 periods between 12 November 2022 and 17 October 2023.

17 WIND ENERGY↗

AWAKEN Virtual Tower / Derived Data

Virtual tower data consist of profiles of wind speed and direction at a number of locations near the A1 sites. These profiles were computed from dual-Doppler analysis of two Halo XR+ scanning Doppler lidars located at sites A5 and A7. Both lidars performed shallow RHI scans in the general direction of the A1 site. Scan azimuths were periodically adjusted to sample different locations. This resulted in a total of 14 unique tower locations over 5 periods between 12 November 2022 and 17 October 2023.

17 WIND ENERGY↗

AWAKEN Virtual Tower / Derived Data

Virtual tower data consist of profiles of wind speed and direction at a number of locations near the A1 sites. These profiles were computed from dual-Doppler analysis of two Halo XR+ scanning Doppler lidars located at sites A5 and A7. Both lidars performed shallow RHI scans in the general direction of the A1 site. Scan azimuths were periodically adjusted to sample different locations. This resulted in a total of 14 unique tower locations over 5 periods between 12 November 2022 and 17 October 2023.

17 WIND ENERGY↗

AWAKEN Virtual Tower / Derived Data

Virtual tower data consist of profiles of wind speed and direction at a number of locations near the A1 sites. These profiles were computed from dual-Doppler analysis of two Halo XR+ scanning Doppler lidars located at sites A5 and A7. Both lidars performed shallow RHI scans in the general direction of the A1 site. Scan azimuths were periodically adjusted to sample different locations. This resulted in a total of 14 unique tower locations over 5 periods between 12 November 2022 and 17 October 2023.

17 WIND ENERGY↗

Experimental Investigation of Vapor Formation in Liquid CO2 Flow Through a Converging-Diverging Nozzle

Carbon dioxide is an attractive working fluid for many cycles, including for pumped thermal energy storage (PTES). A challenge with some proposed sCO2 PTES cycles is the operation of sCO2 machinery outside the typical bounds of experience, with local phase change from the liquid state being particularly unknown. Presently, there is insufficient data in the literature regarding multiphase CO2 to adequately design a multiphase-tolerant turbine, so generation of foundational data is required. This experimental study investigates the flow characteristics of sub-sonic liquid CO2 undergoing expansion and phase change in a converging-diverging nozzle. The nozzle is instrumented to measure static pressure, unsteady pressure, temperature, and density. The static pressure transducers are located at 27 axial locations to accurately characterize the pressure profile in the nozzle. High-accuracy RTDs are located at the entrance and exit of the nozzle, and three dynamic pressure transducers are strategically located to capture any unsteady phenomena. During testing, values of mass flow and nozzle inlet pressure are swept to vary the pressure drop and fluid properties. The measured total pressure drop in the nozzle is compared to a homogenous model and the Lockhart-Martinelli correlation method, with the latter predicting loss quite closely. The resulting data set is valuable for validating multiphase numerical models in a simple geometry before implementation of these models in turbomachinery design.

25 ENERGY STORAGE↗

Experimental demonstration of real-time electron temperature profile control in DIII-D

Future tokamak reactor operation will require the ability to maintain a given plasma scenario for extended periods of time. This will necessitate the capability to react to changes in the plasma state and return the plasma to the target scenario; the principal method to achieve this is through feedback control. Thus, it is necessary to develop and test feedback controllers for the plasma profiles that define a target scenario. In this work, a feedback controller for the electron temperature (Te) profile is tested experimentally in DIII-D. This experiment relied on the ability to ascertain the electron temperature profile in real time, which was achieved using an observer algorithm. The observer relies on both diagnostic data and a predictive model of the electron temperature profile evolution; this predictive model includes contributions from neural network surrogate models. Because of these dependencies, a number of capabilities needed to be added to the real-time PCS for DIII-D in order to support the Te profile control experiment. The neural network surrogates needed to be integrated into the PCS to be called in real time. An observer algorithm for the Te profile needed to be added and connected to the Thomson scattering system to allow access to the current state of the profile in real time. When tested, the observer was shown to produce Te profiles that are consistent with the shape of the Thomson scattering data while rejecting much of the noise in the diagnostic data. Finally, the controller itself was tested in real time. This experiment showed that the controller is capable of tracking the electron temperature target at locations across the spatial profile.

Morosohk, Shira [Oak Ridge Associated Universities↗

Challenges and approaches to interpretive modeling of boundary plasma and neutral transport in a closed, pumped divertor

An experimental discharge from the DIII-D tokamak is modeled using the SOLPS-ITER code suite and compared against measurements in the pumped and relatively closed upper divertor. Uncertainties of boundary plasma simulations are identified by attempting to match code inputs to experimental conditions, including iteratively solving transport coefficients to match upstream experimental profiles using varying quantities of core particle flux, different pumping models, and various assumptions of ion thermal transport. Simulated boundary conditions for particle injection at the core interface are shown to be relevant to the plasma solution at the divertor targets, even if upstream transport is modified so that plasma profiles are comparatively similar, although seperatrix density is not held constant. When upstream plasma profiles are matched to experimental measurements by varying diffusive transport coefficients, using either poloidally symmetric or ballooning structure, the model finds a majority of injected energy being transported radially off the computational domain, in conflict with experimental radiated power measurements and heat flux measurements at the divertor target. Imposing a maximum thermal diffusivity or radially shifting the experimental separatrix location of the fitted profiles to increase power conducted to the targets by increasing the upstream electron temperature does not significantly modify this result. Including a thermalizing plenum volume in the simulation domain is shown to maintain the experimental volumetric pumping rate without knowing the neutral energy distribution incident on the pump duct a priori. By modifying transport parameters to match different assumptions for ion temperature, downstream neutral pressure changes by more than a factor of two, suggesting that attention to ion thermal transport may be a critical parameter for simulations to accurately resolve recycling and neutral transport, particularly in a closed divertor geometry. In addition to quantifying various modeling uncertainties, this work motivates both further experimental study and modeling improvements to improve predictive capabilities.

divertor↗

exoALMA. V. Gaseous Emission Surfaces and Temperature Structures

An analysis of the gaseous component in protoplanetary disks can inform us about their thermal and physical structure, chemical composition, and kinematic properties, all of which are crucial for understanding various processes within the disks. By exploiting the asymmetry of the line emission, or via line profile analysis, we can locate the emitting surfaces. Here, we present the emission surfaces of the exoALMA sources in 12 CO J = 3–2, 13 CO J = 3–2, and CS J = 7–6. We find that 12 CO traces the upper disk atmosphere, with mean $\langle$ z/r $\rangle$ values of ≈0.28, while 13 CO and CS trace lower regions of the disk with mean $\langle$ z/r $\rangle$ values of ≈0.16 and ≈0.18, respectively. We find that 12 CO $\langle$ z/r $\rangle$ and the disk mass are positively correlated with each other; this relationship offers a straightforward way to infer the disk mass. We derive 2D r – z temperature distributions of the disks. Additionally, we search for substructure in the surfaces and radial intensity profiles; we find evidence of localized substructure in the emission surfaces and peak intensity profiles of nearly every disk, with this substructure often being coincident between molecular tracers, intensity profiles, and kinematic perturbations. Four disks display evidence of potential photodesorption, implying that this effect may be common even in low far-ultraviolet star-forming regions. For most disks, we find that the physical and thermal structure is more complex than analytical models can account for, highlighting a need for more theoretical work and a better understanding of the role of projection effects on our observations.

79 ASTRONOMY AND ASTROPHYSICS↗

The mass and galaxy distribution around SZ-selected clusters

ABSTRACT We present measurements of the radial profiles of the mass and galaxy number density around Sunyaev–Zel’dovich (SZ)-selected clusters using both weak lensing and galaxy counts. The clusters are selected from the Atacama Cosmology Telescope Data Release 5 and the galaxies from the Dark Energy Survey Year 3 data set. With signal-to-noise ratio of 62 (45) for galaxy (weak lensing) profiles over scales of about 0.2–20 h−1 Mpc, these are the highest precision measurements for SZ-selected clusters to date. Because SZ selection closely approximates mass selection, these measurements enable several tests of theoretical models of the mass and light distribution around clusters. Our main findings are: (1) The splashback feature is detected at a consistent location in both the mass and galaxy profiles and its location is consistent with predictions of cold dark matter N-body simulations. (2) The full mass profile is also consistent with the simulations. (3) The shapes of the galaxy and lensing profiles are remarkably similar for our sample over the entire range of scales, from well inside the cluster halo to the quasilinear regime. We measure the dependence of the profile shapes on the galaxy sample, redshift, and cluster mass. We extend the Diemer & Kravtsov model for the cluster profiles to the linear regime using perturbation theory and show that it provides a good match to the measured profiles. We also compare the measured profiles to predictions of the standard halo model and simulations that include hydrodynamics. Applications of these results to cluster mass estimation, cosmology, and astrophysics are discussed.

79 ASTRONOMY AND ASTROPHYSICS↗

Photonic Angular Momentum in Intense Light–Matter Interactions

Light contains both spin and orbital angular momentum. Despite contributing equally to the total photonic angular momentum, these components derive from quite different parts of the electromagnetic field profile, namely its polarization and spatial variation, respectively, and therefore do not always share equal influence in light–matter interactions. With the growing interest in utilizing light’s orbital angular momentum to practice added control in the study of atomic systems, it becomes increasingly important for students and researchers to understand the subtlety involved in these interactions. In this article, we present a review of the fundamental concepts and recent experiments related to the interaction of beams containing orbital angular momentum with atoms. An emphasis is placed on understanding light’s angular momentum from the perspective of both classical waves and individual photons. We then review the application of these beams in recent experiments, namely single- and few-photon transitions, strong-field ionization, and high-harmonic generation, highlighting the role of light’s orbital angular momentum and the atom’s location within the beam profile within each case.

Optics↗

Time-dependent experimental identification of inter-ELM microtearing modes in the tokamak edge on DIII-D

In a series of discharges on the DIII-D tokamak, fast vertical plasma jogs are used to induce current perturbations in the steep gradient region of the H-mode edge. These current perturbations directly influence the edge q profile, decoupling the resonant location and instability drive of pedestal-localized microtearing modes (MTMs.) By exploiting this effect, we develop and apply a new experimental technique to track the dynamical frequency evolution of MTMs in the pedestal region, providing a compelling validation of the MTM model. The frequency of potential MTMs is calculated as the Doppler-shifted electron diamagnetic frequency at rational q=m/n surfaces, showing remarkable agreement with chirped frequency behavior of n=3, 4 and 5 modes detected with fast magnetics. Data is collected throughout multiple ELM cycles in order to build robust statistics describing the time-dependent frequency evolution of MTMs, which can be explained by examining the recovery of pedestal gradients after an ELM event. MTMs have a dominant transport contribution in the electron thermal channel, so the presented results indicate that reduced models of pedestal transport must be electromagnetic in nature and constructed with accurate calculations of MTM stability; inclusion of this physics is essential for accurate predictions of the electron temperature pedestal profile. Supporting measurements of mode saturation, propagation direction and transport fingerprints are made to support the dynamic frequency determination, unambiguously and experimentally identifying MTMs in the pedestal region of DIII-D.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Grid Impact Analysis of Heavy-Duty Electric Vehicle Charging Stations

This paper presents a grid impact analysis of heavy-duty electric vehicle (EV) charging stations. In this work, heavy-duty EVs have battery capacities high enough to provide a range of 250-500 miles on a single charge, such as long-haul trucks. Heavy-duty EVs will require extremely fast charging rates to reduce charging time and will induce very high charging loads (at the multiple-megawatt scale) if several vehicles charge at the same time. Therefore, analysis is needed to understand the impact of charging station loads on the electric power grid and set the baseline for developing mitigation plans and necessary system upgrades. We develop a systematic procedure to analyze the potential impact of the placement of charging stations on the grid. Charging load is modeled using a DC fast-charging station model. A voltage load sensitivity matrix approach is leveraged to investigate the challenges of placing charging stations on the feeder. Given the charging load profiles and suggested charging station locations, time-series simulations are performed on various connection points on the feeder to understand the impact. The analysis is performed on both the IEEE 34-bus system and a realistic feeder from California. Initial mitigation solutions are developed based on insights from this analysis.

47 OTHER INSTRUMENTATION↗