Search NASA⌕ Search

SEARCH · Search NASA

Results for “Accelerator Driven Systems”

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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

On the global circulation and the hurricane system of the Jovian atmosphere

An argument is made to support the proposal that Jupiter's red spot and the white and brown ovals are hurricanes or cyclones. Against the background of a convectively unstable troposphere, the general condition exists for the formation of hurricanes. The energy Jupiter emits must be transported upwards through the troposphere. If that transport is accelerated by the prevailing upward motions in the solar driven multicellular meridional circulation, eastward jets develop such as observed in the l region. But if that vertical transport is impeded by the prevailing downward motions in the meridional circulation, the atmosphere reacts and tends to maintain the process through the development of hurricanes. Dynamically induced by solar differential heating, an ordered latitudinal structure with alternating stability and instability is impressed on the troposphere to form alternating zonal strata where hurricanes are forbidden and permitted, respectively.

Mayr, H. G.↗
NASA NTRS2009

Coupled Particle Transport and Pattern Formation in a Nonlinear Leaky-Box Model

Effects of particle-particle coupling on particle characteristics in nonlinear leaky-box type descriptions of the acceleration and transport of energetic particles in space plasmas are examined in the framework of a simple two-particle model based on the Fokker-Planck equation in momentum space. In this model, the two particles are assumed coupled via a common nonlinear source term. In analogy with a prototypical mathematical system of diffusion-driven instability, this work demonstrates that steady-state patterns with strong dependence on the magnetic turbulence but a rather weak one on the coupled particles attributes can emerge in solutions of a nonlinearly coupled leaky-box model. The insight gained from this simple model may be of wider use and significance to nonlinearly coupled leaky-box type descriptions in general.

Barghouty, A. F.↗
NASA NTRS2016

Chip Scale Ultra-Stable Clocks: Miniaturized Phonon Trap Timing Units for PNT of CubeSats

The Chip Scale Ultra-Stable Clocks (CSUSC) project aims to provide a superior alternative to current solutions for low size, weight, and power timing devices. Currently available quartz-based clocks have problems adjusting to the high temperature and extreme acceleration found in space applications, especially when scaled down to match small spacecraft size, weight, and power requirements. The CSUSC project aims to utilize dual-mode resonators on an ovenized platform to achieve the exceptional temperature stability required for these systems. The dual-mode architecture utilizes a temperature sensitive and temperature stable mode simultaneously driven on the same device volume to eliminate ovenization error while maintaining extremely high performance. Using this technology it is possible to achieve parts-per-billion (ppb) levels of temperature stability with multiple orders of magnitude smaller size, weight, and power.

Dual-mode resonators↗
DOE OSTI2020

Toward fusion plasma scenario planning for NSTX-U using machine-learning-accelerated models

One of the most promising devices for realizing power production through nuclear fusion is the tokamak. To maximize performance, it is preferable that tokamak reactors achieve advanced operating scenarios characterized by good plasma confinement, improved magnetohydrodynamic (MHD) stability, and a largely non-inductively driven plasma current. Such scenarios could enable steady-state reactor operation with high \emph{fusion gain} --- the ratio of produced fusion power to the external power provided through the plasma boundary. Precise and robust control of the evolution of the plasma boundary shape as well as the spatial distribution of the plasma current, density, temperature, and rotation will be essential to achieving and maintaining such scenarios. The complexity of the evolution of tokamak plasmas, arising due to nonlinearities and coupling between various parameters, motivates the use of model-based control algorithms that can account for the system dynamics. In this work, a learning-based accelerated model trained on data from the National Spherical Torus Experiment Upgrade (NSTX-U) is employed to develop planning and control strategies for regulating the density and temperature profile evolution around desired trajectories. The proposed model combines empirical scaling laws developed across multiple devices with neural networks trained on empirical data from NSTX-U and a database of first-principles-based computationally intensive simulations. The reduced execution time of the accelerated model will enable practical application of optimization algorithms and reinforcement learning approaches for scenario planning and control development. An initial demonstration of applying optimization approaches to the learning-based model is presented, including a strategy for mitigating the effect of leaving the finite validity range of the accelerated model. The approach shows promise for actuator planning between experiments and in real-time.

machine learning↗
DOE OSTI2025

Acceleration of Power System Dynamic Simulations Using a Deep Equilibrium Layer and Neural ODE Surrogate

The dominant paradigm for power system dynamic simulation is to build system-level simulations by combining physics-based models of individual components. The sheer size of the system along with the rapid integration of inverter-based resources exacerbates the computational burden of running time domain simulations. Here, in this paper, we propose a data-driven surrogate model based on implicit machine learningspecifically deep equilibrium layers and neural ordinary differential equationsto learn a reduced order model of a portion of the full underlying system. The data-driven surrogate achieves similar accuracy and reduction in simulation time compared to a physics-based surrogate, without the constraint of requiring detailed knowledge of the underlying dynamic models. This work also establishes key requirements needed to integrate the surrogate into existing simulation workflows; the proposed surrogate is initialized to a steady state operating point that matches the power flow solution by design.

Neural ordinary differential equations↗
DOE OSTI2015

On the analysis of inhomogeneous magnetic field spectrometer for laser-driven ion acceleration

We present a detailed study of the use of a non-parallel, inhomogeneous magnetic field spectrometer for the investigation of laser-accelerated ion beams. Employing a wedged yoke design, we demonstrate the feasibility of an in-situ self-calibration technique of the non-uniform magnetic field and show that high-precision measurements of ion energies are possible in a wide-angle configuration. We also discuss the implications of a stacked detector system for unambiguous identification of different ion species present in the ion beam and explore the feasibility of detection of high energy particles beyond 100 MeV/amu in radiation harsh environments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Particle acceleration in laser-driven magnetic reconnection

Particle acceleration induced by magnetic reconnection is thought to be a promising candidate for producing the nonthermal emissions associated with explosive phenomena such as solar flares, pulsar wind nebulae, and jets from active galactic nuclei. Laboratory experiments can play an important role in the study of the detailed microphysics of magnetic reconnection and the dominant particle acceleration mechanisms. We have used two- and three-dimensional particle-in-cell simulations to study particle acceleration in high Lundquist number reconnection regimes associated with laser-driven plasma experiments. For current experimental conditions, we show that nonthermal electrons can be accelerated to energies more than an order of magnitude larger than the initial thermal energy. The nonthermal electrons gain their energy mainly from the reconnection electric field near the X points, and particle injection into the reconnection layer and escape from the finite system establish a distribution of energies that resembles a power-law spectrum. Energetic electrons can also become trapped inside the plasmoids that form in the current layer and gain additional energy from the electric field arising from the motion of the plasmoid. We compare simulations for finite and infinite periodic systems to demonstrate the importance of particle escape on the shape of the spectrum. Based on our findings, we provide an analytical estimate of the maximum electron energy and threshold condition for observing suprathermal electron acceleration in terms of experimentally tunable parameters. We also discuss experimental signatures, including the angular distribution of the accelerated particles, and construct synthetic detector spectra. Finally, these results open the way for novel experimental studies of particle acceleration induced by reconnection.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Extending SST vanadis to Add SIMT Functional Units

Sandia National Laboratories is currently investigating scalable architectural simulation capabilities, with a focus on simulating and evaluating highly scalable supercomputers for high-performance computing applications. This exploration is driven by the shift toward more specialized forms of compute and the need for a more diverse set of accurate models. This project will explore the use of General-Purpose Graphical Processing Units (GPGPUs) in high-performance computing using both physical systems and new simulator models – traditional GPUs as well as tightly-coupled SIMT accelerators.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1996

Variable-Speed Induction Motor Drives for Aircraft Environmental Control Compressors

New, more-efficient designs for aircraft jet engines are not capable of supplying the large quantities of bleed air necessary to provide pressurization and air conditioning for the environmental control systems (ECS) of the next generation of large passenger aircraft. System analysis and engineering have determined that electrically-driven ECS can help to maintain the improved fuel efficiencies; and electronic controllers and induction motors are now being developed in a NASA/NPD SBIR Program to drive both types of ECS compressors. Previous variable-speed induction motor/controller system developments and publications have primarily focused on field-oriented control, with large transient reserve power, for maximum acceleration and optimum response in actuator and robotics systems. The application area addressed herein is characterized by slowly-changing inputs and outputs, small reserve power capability for acceleration, and optimization for maximum efficiency. This paper therefore focuses on the differences between this case and the optimum response case, and shows the development of this new motor/controller approach. It starts with the creation of a new set of controller requirements. In response to those requirements, new control algorithms are being developed and implemented in an embedded computer, which is integrated into the motor controller closed loop. Buffered logic outputs are used to drive the power switches in a resonant-technology, power processor/motor-controller, at switching/resonant frequencies high enough to support efficient high-frequency induction motor operation at speeds up to 50,000-RPA

Mildice, J. W.↗
NASA NTRS2011

Consequences of the Breakout Model for Particle Acceleration in CMEs and Flares

The largest and most efficient particle accelerators in the solar system are the giant events consisting of a fast coronal mass ejection (CME) and an intense X-class solar flare. Both flares and CMEs can produce l0(exp 32) ergs or more in nonthermal particles. Two general processes are believed to be responsible: particle acceleration at the strong shock ahead of the CME, and reconnection-driven acceleration in the flare current sheet. Although shock acceleration is relatively well understood, the mechanism by which flare reconnection produces nonthermal particles is still an issue of great debate. We address the question of CME/flare particle acceleration in the context of the breakout model using 2.5D MHD simulations with adaptive mesh refinement (AMR). The AMR capability allows us to achieve ultra-high numerical resolution and, thereby, determine the detailed structure and dynamics of the flare reconnection region. Furthermore, we employ newly developed numerical analysis tools for identifying and characterizing magnetic nulls, so that we can quantify accurately the number and location of magnetic islands during reconnection. Our calculations show that flare reconnection is dominated by the formation of magnetic islands. In agreement with many other studies, we find that the number of islands scales with the effective Lundquist number. This result supports the recent work by Drake and co-workers that postulates particle acceleration by magnetic islands. On the other hand, our calculations also show that the flare reconnection region is populated by numerous shocks and other indicators of strong turbulence, which can also accelerate particles. We discuss the implications of our calculations for the flare particle acceleration mechanism and for observational tests of the models.

Antiochos, S. K.↗
NASA NTRS2022

Design of a Low-Cost, Submersible, Digital Holographic Microscope for in Situ Microbial Imaging

The methodologies for studying marine microbiology typically consist of utilizing instrumentation within a laboratory. This typically requires extracting a sample from its place of origin prior to examination, which may be days after collection. Oftentimes, the solution is to bring the lab to the ocean, which may be costly and provide further limitations for a sterile and stable laboratory environment. Here we present a low-cost, submersible, digital holographic microscope (DHM) designed to image marine microorganisms (such as bacteria and plankton) in their natural underwater environment. Our instrument eliminates the need to transport samples and allows for instantaneous data collection of microbes in-situ. The DHM achieves sub-micron spatial resolution and is paired with artificial intelligence for the detection and tracking of specimens to reduce the overall collected data. This instrument also aims to reduce the cost of manufacturing and field expenses relative to marine microbiological research. “Off the shelf” components were selected in the design process of this instrument which allows us to achieve precise results without sacrificing data quality. The DHM itself costs under one thousand dollars and features a low-cost high-resolution camera, the Arducam MT9J001. Included in the design were five main subsystems: optical, mechanical, electrical, power, and machine learning. Our on board computer and artificial intelligence consist of a Raspberry Pi 4 (8 Gb) and Google Coral USB Tensorflow accelerator. Instrument testing has successfully proven our abilities of data acquisition for at least two hours in depths of at least forty meters below sea level. Additionally, our artificial intelligence system is currently capable of tracking up to ten areas of interest in a fraction of a second with over ninety percent confidence via the neural net driven by the tensor cores on the Google Coral. Furthermore, we have demonstrated the versatility of our instrument by mounting it on an ocean-going ROV, the BlueRov2 by BlueRobotics. Our tests on the BlueRov2 exemplified the cost-effective nature of a submersible and reusable instrument that can be implemented in moderate environments and on most vessels.

Wallace, James Kent↗
DOE OSTI2024

Optimal Zeno Dragging for Quantum Control: A Shortcut to Zeno with Action-Based Scheduling Optimization

The quantum Zeno effect asserts that quantum measurements inhibit simultaneous unitary dynamics when the “collapse” events are sufficiently strong and frequent. This applies in the limit of strong continuous measurement or dissipation. It is possible to implement a dissipative control that is known as “Zeno dragging” by dynamically varying the monitored observable, and hence also the eigenstates, which are attractors under Zeno dynamics. This is similar to adiabatic processes, in that the Zeno-dragging fidelity is highest when the rate of eigenstate change is slow compared to the measurement rate. We demonstrate here two theoretical methods for using such dynamics to achieve control of quantum systems. The first, which we shall refer to as “shortcut to Zeno,” is analogous to the shortcuts to adiabaticity (counterdiabatic driving) that are frequently used to accelerate unitary adiabatic evolution. In the second approach, we apply the Chantasri-Dressel-Jordan stochastic action [PRA 88, 042110 (2013)], and demonstrate that the extremal-probability readout paths derived from this are well suited to setting up a Pontryagin-style optimization of the Zeno-dragging schedule. A fundamental contribution of the latter approach is to show that an action suitable for measurement-driven control optimization can be derived quite generally from statistical arguments. Implementing these methods on the Zeno dragging of a qubit, we find that both approaches yield the same solution, namely, that the optimal control is a unitary that matches the motion of the Zeno-monitored eigenstate. We then show that such a solution can be more robust than a unitary-only operation and we comment on solvable generalizations of our qubit example embedded in larger systems. These methods open up new pathways toward systematically developing dynamic control of Zeno subspaces to realize dissipatively stabilized quantum operations. Published by the American Physical Society 2024

Physics↗
NASA NTRS2001

Large-Scale Mini-Magnetosphere Plasma Propulsion (M2P2) Experiments

Mini-Magnetosphere Plasma Propulsion (M2P2) is an innovative plasma propulsion system that has the potential to propel spacecraft at unprecedented speeds of 50 to 80 km/s, with a low power requirement of approx. 1 kW per 100 kg of payload and -1 kg of neutral gas [fuel] consumption per day of acceleration. Acceleration periods from several days to a few months are envisioned. High specific impulse and efficiency are achieved through coupling of the spacecraft to the 400 km/s. solar wind through an artificial magnetosphere. The mini-magnetosphere or inflated magnetic bubble is produced by the injection of cold dense plasma into a spacecraft-generated magnetic field envelope. Magnetic bubble inflation is driven by electromagnetic processes thereby avoiding the material and deployment problems faced by mechanical solar sail designs. Here, we present the theoretical design of M2P2 as well as initial results from experimental testing of an M2P2 prototype demonstrating: 1) inflation of the dipole magnetic field geometry through the internal injection of cold plasma; and 2) deflection of and artificial solar wind by the prototype M2P2 system. In addition, we present plans for direct laboratory measurement of thrust imparted to a prototype M2P2 by an artificial solar wind during the summer of 2001.

Winglee, R. M.↗
DOE OSTI2026

High-Efficiency Solar-To-Fuel Photoelectrochemistry in Disordered Photonic Glass Electrodes (Final Technical Report)

This project investigated how photonic glass (PG) photoelectrodes—disordered arrangements of dielectric scatterers—can serve as scalable, tunable platforms for light trapping in photoelectrochemical (PEC) solar-to-fuel systems. By leveraging disorder-driven optical phenomena such as multiple scattering resonances and light localization, PG structures offer an alternative to conventional photonic crystals and inverse opals that require high structural precision. The scientific goals were to twofold: (1) develop approaches to predictive models for high performance PG electrodes based on light absorption simulations, and (2) fabricate, characterize, and optimize PG-based photoelectrodes for solar-to-hydrogen and solar-to-fuel photoelectrochemical applications. To overcome the complexity of ensemble optical simulations for disordered materials, the researchers developed a machine-learning-accelerated emulation of all configurations in the design space. With this approach, PG photoelectrodes based on a TiO2 semiconductor were designed to enhance PEC currents of up to one hundred times higher than the equivalent ultra-thin film photoanodes and several times higher than the equivalent photonic crystal. The research also explored integrated systems for electrochemical hydrogen production based on replacing water oxidation with the specific glycerol oxidation electrocatalysis. Overall, the project outlined an approach to a simple-to-fabricate photoelectrode system to drive photoelectrochemical reactions relevant to solar photochemical energy conversion.

14 SOLAR ENERGY↗
DOE OSTI2014

Linac4 low energy beam measurements with negative hydrogen ions

Linac4, a 160 MeV normal-conducting H{sup −} linear accelerator, is the first step in the upgrade of the beam intensity available from the LHC proton injectors at CERN. The Linac4 Low Energy Beam Transport (LEBT) line from the pulsed 2 MHz RF driven ion source, to the 352 MHz RFQ (Radiofrequency Quadrupole) has been built and installed at a test stand, and has been used to transport and match to the RFQ a pulsed 14 mA H{sup −} beam at 45 keV. A temporary slit-and-grid emittance measurement system has been put in place to characterize the beam delivered to the RFQ. In this paper a description of the LEBT and its beam diagnostics is given, and the results of beam emittance measurements and beam transmission measurements through the RFQ are compared with the expectation from simulations.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

From Rules to Reasoning: A Survey of Large Language Model-Based Approaches to Scientific Hypothesis and Idea Generation

Scientific hypothesis generation represents a fundamental challenge in contemporary research due to exponentially expanding literature volumes and increasing disciplinary specialization. Large language models (LLMs) have emerged as transformative tools for automated scientific discovery, moving beyond traditional rule-based and literature-mining approaches. Four paradigmatic approaches define current LLM-driven hypothesis generation: direct prompting and fine-tuning methods, knowledge-enhanced frameworks integrating retrieval-augmented generation (RAG), multi-agent collaborative systems simulating research teams, and reasoning-focused approaches implementing cognitive architectures. Domain-specific applications demonstrate statistical equivalence to human expert performance in social psychology, experimental validation in biomedical research, and near-expert quality in astronomy. Evaluation methodologies encompass human expert assessment, LLM-as-judge frameworks, and comprehensive benchmarking systems. Technical challenges include hallucination management, knowledge integration limitations, and balancing novelty with feasibility. Future directions emphasize hybrid neural-symbolic architectures and sophisticated human-AI collaboration models for responsible scientific discovery acceleration.

AI-driven discovery↗
DOE OSTI2013

Few-cycle optical probe-pulse for investigation of relativistic laser-plasma interactions

The development of a few-cycle optical probe-pulse for the investigation of laser-plasma interactions driven by a Ti:sapphire, 30 Terawatt (TW) laser system is described. The probe is seeded by a fraction of the driving laser's energy and is spectrally broadened via self-phase modulation in a hollow core fiber filled with a rare gas, then temporally compressed to a few optical cycles via chirped mirrors. Shadowgrams of the laser-driven plasma wave created in relativistic electron acceleration experiments are presented with few-fs temporal resolution, which is shown to be independent of post-interaction spectral filtering of the probe-beam.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Perspectives for neutron and gamma spectroscopy in high power laser driven experiments at ELI-NP

The measurement of energy spectra of neutrons and gamma rays emitted by nuclei, together with charge particles spectroscopy, are the main tools for understanding nuclear phenomena occurring also in high power laser driven experiments. However, the large number of particles emitted in a very short time, in particular the strong X-rays flash produced in laser-target interaction, impose adaptation of technique currently used in nuclear physics experiment at accelerator based facilities. These aspects are discussed (Section 1) in the context of proposed studies at high power laser system of ELI-NP. Preliminary results from two experiments performed at Titan (LLNL) and ELFIE (LULI) facilities using plastic scintillators for neutron detection (Section 2) and LaBr{sub 3}(Ce) scintillators for gamma detection (Section 3) are presented demonstrating the capabilities and the limitations of the employed methods. Possible improvements of these spectroscopic methods and their proposed implementation at ELI-NP will be discussed as well in the last section.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗