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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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168 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Study of turbulence-induced refraction of lower hybrid waves using synthetic scrape-off layer filaments

Here, turbulence-induced refraction effects to lower hybrid (LH) wave propagation and current drive are studied using synthetic scrape-off layer (SOL) blob/filament fields. A synthetic 3D, field-following, blob turbulence model is implemented in the ray-tracing/Fokker-Planck (RTFP) codes GENRAY/CQL3D. In Alcator C-Mod, the blob field is shown to significantly affect LH ray-trajectories, leading to increased on-axis damping and smoother current profiles. This effect depends on the average blob size and amplitude. In addition, the diffusion of ray-trajectories in phase-space caused by turbulence increases the robustness of the RTFP model. A modified $N_{||}$ launch spectrum, acting as a proxy for parametric decay instability (PDI) effects, is included in simulations with the blob model. A synergy between the modified launch spectrum and turbulence-induced refraction results in synthetic hard x-ray profiles that agree with experiment. Lastly, the blob model is used to predict the effect of SOL turbulence on DIII-D high-field side (HFS) LH launch. Assuming low turbulence amplitude in the HFS SOL (~5%), turbulence-induced refraction is predicted to have little effect on current drive efficiency.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Spin Hall effect of radiofrequency waves in magnetized plasmas

In inhomogeneous media, electromagnetic-wave rays deviate from the trajectories predicted by the leading-order geometrical optics. This effect, called the spin Hall effect of light, is typically neglected in ray-tracing codes used for modeling waves in plasmas. Here, we demonstrate that the spin Hall effect can be significant for radiofrequency waves in toroidal magnetized plasmas whose parameters are in the ballpark of those used in fusion experiments. For example, an electron-cyclotron wave beam can deviate by as large as 10 wavelengths (~ 0.1 m) relative to the lowest-order ray trajectory in the poloidal direction. Finally, we calculate this displacement using gauge-invariant ray equations of extended geometrical optics, and we also compare our theoretical predictions with full-wave simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

A ray-tracing algorithm for ab-initio calculation of thermal load in undulator-based synchrotron beamlines

The OASYS suite and its powerful integration features are used to implement a ray-tracing algorithm to accurately calculate the thermal load in any component of an undulator-based synchrotron beamline. This is achieved by sampling and converting the SRW source of a given energy into a Shadow source and using the latter code to ray trace the full beamline. The accuracy of the algorithm is proved by reconstructing the full undulator radiation distribution through an aperture and comparing the result with direct calculaton of the total power using SRW. The algorithm is particularly suited to analyze cases with complex beamline layouts and optical elements, such as crystals, multilayers, and compound refractive lenses. Examples of its use to calculate the power load on elements of two of the feature beamlines at the Advanced Photon Source Upgrade Project and a comparison of the results with analytical calculations are presented.

43 PARTICLE ACCELERATORS↗
NASA NTRS1990

Linearized ray-trace analysis

A new, coordinate-free version of the exact ray-trace equations for optical systems consisting of conic reflecting, refracting and reference surfaces is presented. These equations are differentiated to obtain closed-form optical sensitivity dyadics. For computation, the sensitivities are evaluated in a single global coordinate frame and combined in linearized ray-trace matrix difference equations that propagate the rays and the sensitivities from element to element. One purpose of this analysis is to create optical models that can be directly integrated with models of the instrument structure and control systems for dynamic simulation.

Redding, David C.↗
NASA NTRS2004

Gravity Waves and Mesospheric Clouds in the Summer Middle Atmosphere: A Comparison of Lidar Measurements and Ray Modeling of Gravity Waves Over Sondrestrom, Greenland

We conducted gravity wave ray-tracing experiments within an atmospheric region centered near the ARCLITE lidar system at Sondrestrom, Greenland (67N, 310 deg E), in efforts to understand lidar observations of both upper stratospheric gravity wave activity and mesospheric clouds during August 1996 and the summer of 2001. The ray model was used to trace gravity waves through realistic three-dimensional daily-varying background atmospheres in the region, based on forecasts and analyses in the troposphere and stratosphere and climatologies higher up. Reverse ray tracing based on upper stratospheric lidar observations at Sondrestrom was also used to try to objectively identify wave source regions in the troposphere. A source spectrum specified by reverse ray tracing experiments in early August 1996 (when atmospheric flow patterns produced enhanced transmission of waves into the upper stratosphere) yielded model results throughout the remainder of August 1996 that agreed best with the lidar observations. The model also simulated increased vertical group propagation of waves between 40 km and 80 km due to intensifying mean easterlies, which allowed many of the gravity waves observed at 40 km over Sondrestrom to propagate quasi-vertically from 40-80 km and then interact with any mesospheric clouds at 80 km near Sondrestrom, supporting earlier experimentally-inferred correlations between upper stratospheric gravity wave activity and mesospheric cloud backscatter from Sondrestrom lidar observations. A pilot experiment of real-time runs with the model in 2001 using weather forecast data as a low-level background produced less agreement with lidar observations. We believe this is due to limitations in our specified tropospheric source spectrum, the use of climatological winds and temperatures in the upper stratosphere and mesosphere, and missing lidar data from important time periods.

LIDAR (LIGHT DETECTION AND RANGING)↗