Search NASA⌕ Search

SEARCH · Search NASA

Results for “ring model”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Simulation of the High Temperature Test Facility (HTTF) Core Using the 2D Ring Model with SAM

A two-dimensional ring model is developed with SAM to model the core of the High Temperature Test Facility (HTTF) at the system level. The ring model simplifies the complex structure of the HTTF core by converting the hexagonal rows of heaters and flow channels into layers of concentric annular rings. The ring model is first compared against a 3D-1D model where the solid structures are fully resolved in three dimensions while the fluid structures are modeled as one-dimensional flows. Comparison between the 3D-1D and the ring models shows that the latter can predict major parameters reasonably well under steady-state normal operating condition, but the heater temperatures are underpredicted. Adjustment is made to the effective thermal conductivity of the ceramic core of the ring model to improve the heater temperature predictions. Furthermore, the ring model is also used to simulate a transient Pressurized Conduction Cooldown (PCC) condition and is benchmarked with the experimental data from the HTTF Test PG-27. Good agreement is obtained between the experimental data and the predictions by the ring model.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1991

An overview of the neuron ring model

The Neuron Ring model employs an avalanche structure with two important distinctions at the neuron level. Each neuron has two memory latches; one traps maximum neuronal activation during pattern presentation, and the other records the time of latch content change. The latches filter short term memory. In the process, they preserve length 1 snapshots of activation theory history. The model finds utility in pattern classification. Its synaptic weights are first conditioned with sample spectra. The model then receives a test or unknown signal. The objective is to identify the sample closest to the test signal. Class decision follows complete presentation of the test data. The decision maker relies exclusively on the latch contents. Presented here is an overview of the Neuron Ring at the seminar level.

Taber, Rod↗
NASA NTRS1988

A multiple-vortex-ring model of the DFW microburst

A multiple-vortex-ring model of the winds associated with a microburst is verified by matching the model-generated winds to those encountered at the Dallas-Ft. Worth (DFW) microburst. The basis of the model consists of time-invariant vortex ring filaments embedded in irrotational flow. Each ring's viscous core is modeled by distributing the vorticity over a small distance (relative to the ring diameter) radially from the filaments. Parameters such as the size and strength of the vortex rings are identified using a modified Newton-Raphson technique. The parameters identified from the analysis of the DFW microburst encounter indicate a large ring with a radius of 8500 ft and a smaller ring with a radius of 1700 ft.

Schultz, Thomas A.↗
NASA NTRS1989

Multiple-Vortex-Ring Model Of A Microburst

Data from wind-shear incident support two-ring model. Report discusses multiple-vortex-ring mathematical model of microburst, which is strong downdraft that induces outflow of strong winds near ground. This low-altitude wind-shear phenomenon is topic of continuing study because of its effect on safety of flight.

Schultz, Thomas A.↗
DOE OSTI2023

Diabatic quantum annealing for the frustrated ring model

Abstract Quantum annealing (QA) is a continuous-time heuristic quantum algorithm for solving or approximately solving classical optimization problems. The algorithm uses a schedule to interpolate between a driver Hamiltonian with an easy-to-prepare ground state and a problem Hamiltonian whose ground state encodes solutions to an optimization problem. The standard implementation relies on the evolution being adiabatic: keeping the system in the instantaneous ground state with high probability and requiring a time scale inversely related to the minimum energy gap between the instantaneous ground and excited states. However, adiabatic evolution can lead to evolution times that scale exponentially with the system size, even for computationally simple problems. Here, we study whether non-adiabatic evolutions with optimized annealing schedules can bypass this exponential slowdown for one such class of problems called the frustrated ring model. For sufficiently optimized annealing schedules and system sizes of up to 39 qubits, we provide numerical evidence that we can avoid the exponential slowdown. Our work highlights the potential of highly-controllable QA to circumvent bottlenecks associated with the standard implementation of QA.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1987

Revised NASA axially symmetric ring model for coupled-cavity traveling-wave tubes

A versatile large-signal, two-dimensional computer program is used by NASA to model coupled-cavity travelling-wave tubes (TWTs). In this model, the electron beam is divided into a series of disks, each of which is further divided into axially symmetric rings which can expand and contract. The trajectories of the electron rings and the radiofrequency (RF) fields are determined from the calculated axial and radial space-charge, RF, and magnetic forces as the rings pass through a sequence of cavities. By varying electrical and geometric properties of individual cavities, the model is capable of simulating severs, velocity tapers, and voltage jumps. The calculated electron ring trajectories can be used in designing magnetic focusing and multidepressed collectors. The details of using the program are presented, and results are compared with experimental data.

Wilson, Jeffrey D.↗
DOE OSTI2023

Modeling Ring Current Proton Fluxes Using Artificial Neural Network and Van Allen Probe Measurements

Abstract Terrestrial ring current dynamics are a critical part of the near‐space environment, in that they directly drive geomagnetic field variations that control particle drifts, and define geomagnetic storms. The present study aims to specify a global and time‐varying distribution of ring current proton using geomagnetic indices and solar wind parameters with their history as input. We train an artificial neural network (ANN) model to reproduce proton fluxes measured by the Radiation Belt Storm Probes Ion Composition Experiment instrument onboard Van Allen Probes. By choosing optimal feature parameters and their history length, the model results show a high correlation and a small error between model specifications and satellite measurements. The modeled results well capture energy‐dependent proton dynamics in association with geomagnetic storms, including inward radial diffusion, acceleration and decay. Our ANN model produces proton fluxes with their corresponding 3D spatiotemporal variations, capturing the latitudinal distribution and local time asymmetry that are consistent with observations and that can further inform theory.

Li, Jinxing↗
NASA NTRS1988

Tilted-ring models of the prolate spiral galaxies NGC 5033 and 5055

Observations of the kinematics of H I in the disks of spiral galaxies have shown that isovelocity contours often exhibit a twisted pattern. The shape of a galaxy's gravitational potential well (whether due to luminous matter or dark matter) can be determined from the direction of the twist. If this twist is a manifestation of the precession of a nonsteady-state disk, it is shown that the twists of NGC 5033 and 5055 imply an overall prolate shape, with the major axis of the potential well aligned along the rotation axis of the disk. Therefore, the luminous disks of these galaxies must be embedded in dark halos that are prolate spheroids or prolatelike triaxial figures.

Christodoulou, Dimitris M.↗
NASA NTRS2003

Photometric Analysis of the Jovian Ring System and Modeling of Ring Origin and Evolution

We have successfully completed the work described in our proposal. The work supported by this grant resulted in the publication of the following paper: Brooks, S. M., L. W. Esposito, M. R. Showalter, and H. B. Throop. 2002. The size distribution of Jupiter's main ring from Galileo imaging and spectroscopy. Icarus, in press. This was also the major part of Dr. Shawn Brooks PhD dissertation. Dr. Brooks gave oral presentations on this work at the Lunar and Planetary Conference, the annual meetings of the Division for Planetary Sciences of the American Astronomical Society, the annual meetings of the European Geophysical Society, the international Jupiter Conference in Boulder, the Jupiter after Galileo and Cassini Conference in Lisbon and to the Working Group in Non-Linear Dynamics in Potsdam, Germany. This work was reviewed in: Esposito, L. W. 2002. Planetary rings. Rep. hog. Phys. 65, 1741-1783. Planetary rings. LASP reprint 874. Online at http://stacks.iop.org/RoPP/65/1741. Dr. Esposito gave presentations at schools and over the internet on the results of this work. Dr. Brooks lectured in undergraduate and graduate classes on Jupiter's rings, and on the meaning of his research. In August 2003, Dr. Shawn Brooks received the Phd degree from the University of Colorado in Astrophysical and Planetary Sciences.

Esposito, L. W.↗
NASA NTRS1990

Models of Neptune's arc rings

Models proposed to explain the dynamical confinement of such structures as incomplete arc rings in orbit about the planet Neptune are reviewed and tested against the currently available observational data. It is shown that satellites can confine arc rings to very limited radial and azimuthal extents via a combination of corotation and Lindblad resonances. The resonances can be produced by the same moon or by different moons.

Lissauer, Jack J.↗
DOE OSTI2024

Reduced‐Order Probabilistic Emulation of Physics‐Based Ring Current Models: Application to RAM‐SCB Particle Flux

Abstract In this work, we address the computational challenge of large‐scale physics‐based simulation models for the ring current. Reduced computational cost allows for significantly faster than real‐time forecasting, enhancing our ability to predict and respond to dynamic changes in the ring current, valuable for space weather monitoring and mitigation efforts. Additionally, it can also be used for a comprehensive investigation of the system. Thus, we aim to create an emulator for the Ring current‐Atmosphere interactions Model with Self‐Consistent magnetic field (RAM‐SCB) particle flux that not only improves efficiency but also facilitates forecasting with reliable estimates of prediction uncertainties. The probabilistic emulator is built upon the methodology developed by Licata and Mehta (2023), https://doi.org/10.1029/2022sw003345 . A novel discrete sampling is used to identify 30 simulation periods over 20 years of solar and geomagnetic activity. Focusing on a subset of particle flux, we use Principal Component Analysis for dimensionality reduction and Long Short‐Term Memory (LSTM) neural networks to perform dynamic modeling. Hyperparameter space was explored extensively resulting in about 5% median symmetric accuracy across all data sets for one‐step dynamic prediction. Using a hierarchical ensemble of LSTMs, we have developed a reduced‐order probabilistic emulator (ROPE) tailored for time‐series forecasting of particle flux in the ring current. This ROPE offers accurate predictions of omnidirectional flux at a single energy with no pitch angle information, providing robust predictions on the test set with an error score below 11% and calibration scores under 8% with bias under 2% providing a significant speed up as compared to the full RAM‐SCB run.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2010

Ring Current Dynamics in Moderate and Strong Storms: Comparative Analysis of TWINS and IMAGE/HENA Data with the Comprehensive Ring Current Model

We present a comparative study of ring current dynamics during strong and moderate storms. The ring current during the strong storm is studied with IMAGE/HENA data near the solar cycle maximum in 2000. The ring current during the moderate storm is studied using energetic neutral atom (ENA) data from the Two Wide-Angle Imaging Neutral- Atom Spectrometers (TWINS) mission during the solar minimum in 2008. For both storms, the local time distributions of ENA emissions show signatures of postmidnight enhancement (PME) during the main phases. To model the ring current and ENA emissions, we use the Comprehensive Ring Current Model (CRCM). CRCM results show that the main-phase ring current pressure peaks in the premidnight-dusk sector, while the most intense CRCM-simulated ENA emissions show PME signatures. We analyze two factors to explain this difference: the dependence of charge-exchange cross section on energy and pitch angle distributions of ring current. We find that the IMF By effect (twisting of the convection pattern due to By) is not needed to form the PME. Additionally, the PME is more pronounced for the strong storm, although relative shielding and hence electric field skewing is well developed for both events.

Buzulukova, N.↗
DOE OSTI2026

Surrogate model for third-integer resonance extraction at the Fermilab Delivery Ring

We present an ongoing work in which a surrogate model is being developed to reproduce the response dynamics of the third-integer resonant extraction process in the Delivery Ring (DR) at Fermilab. This is in pursuit of smoothly extracting circulating beam to the Mu2e Experiment’s production target, whereby the goal is to extract a uniform slice of the circulating 1e12 protons in the DR over 25,000 turns (43 ms). The DR contains 3 harmonic sextupoles that excite a third-integer resonance and three fast, tune-ramping quadrupole magnets that drive the horizontal tune towards the 29/3 resonance. In our initial work, the surrogate model trains on a semi-analytical simulation provided in the same format as live data. Using Reinforcement Learning (and other potential ML methods), the trained surrogate acts as the “environment” in which a simple ML control agent could learn to dynamically adjust the quadrupole ramp at 430 break points within the 43 microsecond spill window. The controller will be hosted on a dedicated Arria 10 FPGA. In this work, we report the accuracy and fidelity of the surrogate model in comparison to the response dynamics of the physics simulator.

Narayanan, Aakaash [Fermilab]↗