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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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Expanding the parameter space of the wide-pedestal QH-mode towards ITER conditions
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The geometry of the ICRF-induced wave–SOL interaction. A multi-machine experimental review in view of the ITER operation
As a part of ITPA-Integrated Operational Scenario activities, this contribution reviews recent experimental characterizations of radio-frequency (RF)-induced scrape-off layer (SOL) modifications of various tokamaks worldwide and of the LArge Plasma Device at UCLA. The phenomenology, as observed using a large variety of measurement techniques, is consistent with expectations from RF sheath rectification. Emphasis is then put on the complex three-dimensional (3D) spatial patterns of the RF–SOL interaction, in relation to the magnetic topology and the spatial distribution of RF currents over the metallic structures surrounding the RF wave launchers. Dependence on the local plasma parameters in the antenna vicinity is also briefly addressed. The final part discusses implications for future devices.
Numerical studies on saturated kink and sawtooth induced fast ion transport in JET ITER-like plasmas
Here, this presentation examines the energetic particle transport induced by saturated kink modes and sawtooth crashes in JET deuterium plasmas. It is known that kink mode-resonant transport and phase-space redistribution from sawtooth crashes can drive strong fast ion transport with dependencies on particle pitch and energy. Measurements with JET's Faraday cup fast ion loss detector array have shown that the internal kink growth phase preceding sawtooth crashes produces substantial fast ion losses. This report will numerically investigate the dominant energetic particle transport mechanism with a detailed examination of the fast ion phase-space dependencies, resonances, orbit topology changes, induced losses, and redistribution associated with the long-lived, resonant, kink mode and non-resonant sawtooth crash. The ORBIT-kick model forms the basis of the transport studies with realistic fast ion distributions produced from TRANSP. A recently created reduced model for sawtooth induced transport is used while the saturated kink modes are modeled with ideal MHD codes. The simulations were further validated against experiment with a newly developed synthetic Faraday cup fast ion loss detector in addition to scintillator probe and neutron measurements.
Optimization of lithium vapor box divertor evaporator location on NSTX-U using SOLPS-ITER
Commercial fusion reactors will be faced with extremely high divertor target heat fluxes that will require mitigation. Simulations of detachment in an NSTX-U scenario projected to have 92 MW/m 2 unmitigated peak target heat flux are presented, which reaches sub-10 MW/m 2 target heat flux using a highly dissipating lithium vapor box divertor design. The lithium vapor box is a detached divertor design which employs lithium vapor evaporation and condensation to contain lithium below the X-point. Previous SOLPS modeling has indicated a lithium vapor box can reduce the heat flux down to 10 MW/m 2 via simultaneous evaporation from the Private Flux Region (PFR) and the Common Flux Region (CFR) sides of the vapor box. It is found here that PFR evaporation has improved access to the separatrix leading to significantly more efficient power dissipation than CFR evaporation. Simulations of target evaporation with an evaporation distribution that is self-consistent with the temperature of a Capillary Porous System with Fast flowing liquid lithium (CPSF) could reach n Li / n e ~ 0.025-0.030 at the Last Closed Flux Surface (LCFS) depending on the liquid metal flow speeds and lithium sputtering yield, while PFR-side evaporation can reach acceptable heat fluxes with n Li / n e ~ 0.038 at the LCFS. However, PFR evaporator performance can be improved if the target is allowed to be hot enough such that it reflects lithium, reaching n Li / n e ~ 0.028 and reducing required lithium evaporation. Ultimately PFR evaporation and target evaporation are found to have similar ability to produce acceptable heat flux solutions with minimal upstream concentration.
Demonstration of improvement in 2D tomographic reconstructions of filtered cameras in the JET ITER-like wall divertor due to corrected interpretation of reflections
Improved localization of emission and reduction of artefacts have been achieved in tomographic reconstructions of the tangentially viewing spectroscopic divertor cameras in JET by introducing the contribution of reflections from the metallic wall surfaces in the geometry definition of the tomography process. The reconstructions thus describe the plasma emission only without features arising from misinterpreted reflected light. Benchmarks with synthetic emission distributions showed accurate reproduction within 10% and 1–2% of the reference emission distributions and camera images, respectively, when the reflection correction was applied. Without the correction, the reconstructed emission was observed to concentrate from the divertor volume towards the wall surfaces together with bright emission artefacts appearing in front of the surfaces to reproduce the reflections seen in the camera images.
Fatigue Cyclic Testing of the ITER CS Inlets
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Convolutional neural network based non-iterative reconstruction for accelerating neutron tomography *
Abstract Neutron computed tomography (NCT), a 3D non-destructive characterization technique, is carried out at nuclear reactor or spallation neutron source-based user facilities. Because neutrons are not severely attenuated by heavy elements and are sensitive to light elements like hydrogen, neutron radiography and computed tomography offer a complementary contrast to x-ray CT conducted at a synchrotron user facility. However, compared to synchrotron x-ray CT, the acquisition time for an NCT scan can be orders of magnitude higher due to lower source flux, low detector efficiency and the need to collect a large number of projection images for a high-quality reconstruction when using conventional algorithms. As a result of the long scan times for NCT, the number and type of experiments that can be conducted at a user facility is severely restricted. Recently, several deep convolutional neural network (DCNN) based algorithms have been introduced in the context of accelerating CT scans that can enable high quality reconstructions from sparse-view data. In this paper, we introduce DCNN algorithms to obtain high-quality reconstructions from sparse-view and low signal-to-noise ratio NCT data-sets thereby enabling accelerated scans. Our method is based on the supervised learning strategy of training a DCNN to map a low-quality reconstruction from sparse-view data to a higher quality reconstruction. Specifically, we evaluate the performance of two popular DCNN architectures—one based on using patches for training and the other on using the full images for training. We observe that both the DCNN architectures offer improvements in performance over classical multi-layer perceptron as well as conventional CT reconstruction algorithms. Our results illustrate that the DCNN can be a powerful tool to obtain high-quality NCT reconstructions from sparse-view data thereby enabling accelerated NCT scans for increasing user-facility throughput or enabling high-resolution time-resolved NCT scans.
Application of the iterative reconstruction to simulated galaxy fields
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Large-scale recoding of a bacterial genome by iterative recombineering of synthetic DNA
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An iterative CMB lensing estimator minimizing instrumental noise bias
Noise maps from cosmic microwave background (CMB) experiments are generally statistically anisotropic, due to scanning strategies, atmospheric conditions, or instrumental effects. Any mismodeling of this complex noise can bias the reconstruction of the lensing potential and the measurement of the lensing power spectrum from the observed CMB maps. We introduce a new CMB lensing estimator based on the maximum (MAP) reconstruction that is minimally sensitive to these instrumental noise biases. By modifying the likelihood to rely exclusively on correlations between CMB map splits with independent noise realizations, we minimize autocorrelations that contribute to biases. In the regime of many independent splits, this maximum closely approximates the optimal MAP reconstruction of the lensing potential. In simulations, we demonstrate that this method is able to determine lensing observables that are immune to any noise mismodeling with a negligible cost in signal-to-noise ratio. Our estimator enables unbiased and nearly optimal lensing reconstruction for next-generation CMB surveys.
Electron bunch profile reconstruction based on phase-constrained iterative algorithm
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Equilibrium of an arbitrary bunch train with cavity resonators and short range wake: Enhanced iterative solution with Anderson acceleration
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Implications of the Landau equations for iterated integrals
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Iteratively comparing gravitational-wave observations to the evolution of massive stellar binaries
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Elliptic polylogarithms and iterated integrals on elliptic curves. II. An application to the sunrise integral
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