SEARCH · Search NASA

Results for “Acceleration methods”

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.

SourceResearch connectionFrom yearThrough year

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

At least 721 records · Page 40

All sources NASA NTRS DOE OSTI

NASA NTRS2011

Variable Depth Bragg Peak Method for Single Event Effects Testing

Traditionally, accelerator SEE testing is accomplished by removing the tops of packages so that the IC chips are accessible to heavy ions. However, ICs in some advanced packages cannot be de-lidded so a different approach is used that involves grinding and/or chemically etching away part of the package and the chip from the back side. The parts are then tested from the back side with ions having sufficient range to reach the sensitive volume. More recently, the entire silicon substrate in an SOI/SRAM was removed, making it possible to use low-energy ions with shorter ranges. Where removal of part of the package is not possible, facilities at Michigan State, NASA Space Radiation Laboratory, GANIL (France) and GSI (Germany) offer high-energy heavy ions with long ranges so that the ions can reach the devices' sensitive volumes without much change in the LET. Unfortunately, a run will typically involve only one ion species having a single energy and LET due to the long time it takes to tune a new energy. The Variable Depth Bragg Peak (VDBP) method is similar to the above method in that it involves the use of high-energy heavy ions that are able to pass through the packaging material and reach the device, obviating the need to remove the package. However, the method provides a broad range of LETs from a single ion by inserting degraders in the beam that modify the ion energy and, therefore, the LET. The crux of the method involves establishing a fiduciary point for degrader thickness, i.e., where the Bragg peak is located precisely at the sensitive volume in the device, for which the measured SEU cross-section and the ion LET are both also maxima and can be calculated using a Monte-Carlo program, TRIM. Once the fiduciary point has been established, calibrated high density polyethylene (HDPE) degraders are inserted into or removed from the beam to vary the ion LET at the device in a known manner. After each change of degrader thickness, the SEU cross-section is measured and the corresponding LET calculated from the change in degrader thickness. That information is used to generate a plot of cross-section as a function of ion LET. The advantages of this approach are that the part does not have to be de-lidded and a broad range of LETs is available from a single heavy ion without having to go to non-normal angles of incidence to change the "effective" LET. As we will show, it is possible to obtain an entire curve of cross-section versus LET using just two or three ions. Fig. 1 shows curves of cross-section vs LET for a Freescale 4 Mbit SOI/SRAM measured at the 88" Cyclotron at Berkeley and at NSRL. The open symbols are the data obtained from Berkeley for top-side and back-side irradiation. The solid data points are for the data obtained at NSRL using a device for which the package was intact. The data are for Iron and Gold and cover a range of LETs from 4 MeV.cm2/mg to 84 MeV.cm2/mg. The agreement between the data obtained from Berkeley and from NSRL is excellent, demonstrating that the VDBP method is capable of providing accurate values of cross-section versus LET, at least for the 4 Mbit SRAM. Details of the technique will be included in the final presentation.

Buchner, S.↗

NASA NTRS2022

Spectral Power-law Formation by Sequential Particle Acceleration in Multiple Flare Magnetic Islands

We present a first-principles model of pitch-angle and energy distribution function evolution as particles are sequentially accelerated by multiple flare magnetic islands. Data from magnetohydrodynamic (MHD) simulations of an eruptive flare/coronal mass ejection provide ambient conditions for the evolving particle distributions. Magnetic islands, which are created by sporadic reconnection at the self-consistently formed flare current sheet, contract and accelerate the particles. The particle distributions are evolved using rules derived in our previous work. In this investigation, we assume that a prescribed fraction of particles sequentially "hops" to another accelerator and receives an additional boost in energy and anisotropy. This sequential process generates particle number spectra that obey an approximate power law at mid-range energies and presents low- and high-energy breaks. We analyze these spectral regions as functions of the model parameters. We also present a fully analytic method for forming and interpreting such spectra, independent of the sequential acceleration model. The method requires only a few constrained physical parameters, such as the percentage of particles transferred between accelerators, the energy gain in each accelerator, and the number of accelerators visited. Our investigation seeks to bridge the gap between MHD and kinetic regimes by combining global simulations and analytic kinetic theory. The model reproduces and explains key characteristics of observed flare hard X-ray spectra as well as the underlying properties of the accelerated particles. Our analytic model provides tools to interpret high-energy observations for missions and telescopes, such as RHESSI, FOXSI, NuSTAR, Solar Orbiter, EOVSA, and future high-energy missions.

magnetic reconnection↗

NASA NTRS2017

Damage Based Analysis (DBA) - Theory, Derivation and Practical Application Using Both an Acceleration and Pseudo Velocity Approach

The objective of this presentation is to give a brief overview of the theory behind the (DBA) method, an overview of the derivation and a practical application of the theory using the Python computer language. The Theory and Derivation will use both Acceleration and Pseudo Velocity methods to derive a series of equations for processing by Python. We will take the results and compare both Acceleration and Pseudo Velocity methods and discuss implementation of the Python functions. Also, we will discuss the efficiency of the methods and the amount of computer time required for the solution. In conclusion, (DBA) offers a powerful method to evaluate the amount of energy imparted into a system in the form of both Amplitude and Duration during qualification testing and flight environments. Many forms of steady state and transient vibratory motion can be characterized using this technique. (DBA) provides a more robust alternative to traditional methods such Power Spectral Density (PSD) using a maximax approach.

Structural Dynamics↗

DOE OSTI2021

BraggNN : fast X-ray Bragg peak analysis using deep learning

X-ray diffraction based microscopy techniques such as high-energy diffraction microscopy (HEDM) rely on knowledge of the position of diffraction peaks with high precision. These positions are typically computed by fitting the observed intensities in detector data to a theoretical peak shape such as pseudo-Voigt. As experiments become more complex and detector technologies evolve, the computational cost of such peak-shape fitting becomes the biggest hurdle to the rapid analysis required for real-time feedback in experiments. To this end, we propose BraggNN, a deep-learning based method that can determine peak positions much more rapidly than conventional pseudo-Voigt peak fitting. When applied to a test dataset, peak center-of-mass positions obtained from BraggNN deviate less than 0.29 and 0.57 pixels for 75 and 95% of the peaks, respectively, from positions obtained using conventional pseudo-Voigt fitting (Euclidean distance). When applied to a real experimental dataset and using grain positions from near-field HEDM reconstruction as ground-truth, grain positions using BraggNN result in 15% smaller errors compared with those calculated using pseudo-Voigt. Recent advances in deep-learning method implementations and special-purpose model inference accelerators allow BraggNN to deliver enormous performance improvements relative to the conventional method, running, for example, more than 200 times faster on a consumer-class GPU card with out-of-the-box software.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Accelerating Phase-field Predictions Via Surrogate Models Trained By Machine Learning Methods .

Abstract not provided.

Hu, Chongze↗

NASA NTRS2019

Coilgun Acceleration Model Containing Multiple Interacting Coils

A coilgun operates by pulsing current through an axially-arranged series of independently-controlled coils inductively interacting with a small, electrically-conductive, azimuthally-symmetric projectile to accelerate it to high velocities. The electrical circuits are programmed to pulse current through the coils in such a way so as to impart further electromagnetic acceleration in each stage. A method is developed to calculate the mutual inductance between the coils and between each coil and the projectile. These terms are used to write a system of first-order ordinary differential equations governing the projectile velocity and the current flow in each coil. While the inclusion of the electromagnetic interactions between coils significantly complicates the equation set as more coil sets are included in the problem, casting the problem symbolically in mass matrix form permits solution using standard numerical Runge-Kutta techniques. Comparing a projectile with a single-turn to that comprised of nine-turns, the inductance of the former is much smaller, but this leads to a greater induced projectile current. The lower inductance and greater current appear to offset each other with little difference in the acceleration profile for the two cases. For the limited cases studied, coils with a discharge half-cycle equal to the time for a projectile to transit from one coil to the next yield increased efficiency.

Polzin, Kurt A.↗

DOE OSTI2025

Explainable and Differentiable Reinforcement Learning for Multi-objective Optimization in Particle Accelerators

Operating particle accelerators involves optimizing multiple goals simultaneously, which can be challenging due to trade-offs among objectives. While evolutionary algorithms like the genetic algorithm (GA) have been used for various Multi-Objective Optimization (MOO) tasks, they are not inherently suited for complex control problems. This talk highlights two variations of Reinforcement Learning (RL) for concurrently optimizing heat load and trip rates at the Continuous Electron Beam Accelerator Facility (CEBAF). The problem involves strict constraints on individual states, actions, and overall energy requirements of the beam. First, this talk highlights how differentiability can be harnessed through a Deep Differentiable Reinforcement Learning (DDRL) approach to address MOO issues within particle accelerators. We examine the DDRL method alongside Model Free Reinforcement Learning (MFRL), GA, and Bayesian Optimization (BO). The performance of these methods is assessed by generating a Pareto-front for two objectives. Our findings indicate that DDRL excels in handling high-dimensional problems more effectively than MFRL, BO, and GA. Next, we will show integration of explainable physics-based constraints into RL algorithms to enhance trans- parency and trust in decision-making processes by enabling users to verify that agents adhere to established physical principles. This surrogate function can be modeled using neural networks or sparse dictionary mod- els. By examining the mathematical form of the learned constraint function, we are able to confirm the agent has learned to use the established physics of each environment provided but the surrogate model. In addi- tion, we find that the introduction of a mathematical functional dictionary based surrogate model enables our reinforcement learning algorithms to reliably converge for difficult high-dimensional accelerator controls environments.

Rajput, Kishansingh [Thomas Jefferson National Acc↗

DOE OSTI2019

Automation of particulate characterization

Foreign particles residing on the field carrying surface of accelerator cavities are a known mechanism for field emission. Developing the methods and tools for collecting and characterizing particles found in an accelerator enables process development towards field emission free SRF cavities. Methods are presented for sampling assemblies, components, processes, and environmental conditions utilizing forensic techniques with specialized tooling. Sampling activities to date have produced an inventory of over 850 GSR spindles. Traditional SEM + EDS analysis of this volume of spindles is challenged by labor investment, spindle sampling methods, and the subsequent data pipeline which ultimately results in a statically inadequate dataset for any particulate distribution characterization. A complete systematic analysis of the spindles is enabled by third party software controlling SEM automation for EDS data acquisition. Details of spindle creation, collection equipment, component sampling, automating particle assessment, and data analysis used to characterize samples from beamline elements in CEBAF are presented.

Spradlin, Josh↗

DOE OSTI2023

Improved measurements of nonlinear integrable optics at IOTA

Nonlinear integrable optics (NIO) are a promising novel approach at improving the stability of high intensity beams. Implementations of NIO based on specialized magnetic elements are being tested at the Integrable Optics Test Accelerator (IOTA) at Fermilab. One method of verifying proper implementation of these solutions is by measuring the analytic invariants predicted by theory. The initial measurements of nonlinear invariants were performed during IOTA run in 2019/20, however the covid-19 pandemic prevented the full-scale experimental program from being completed. Several important improvements were implemented in IOTA for the 2022/23 run, including the operation at higher beam energy of 150 MeV, improved optics control, and chromaticity correction. This report presents on the improved calibrations of the NIO for nonlinear invariant measurements.

43 PARTICLE ACCELERATORS↗

DOE OSTI2023

Improved Measurements of Nonlinear Integrable Optics Invariants at IOTA

Nonlinear integrable optics (NIO) are a promising novel approach at improving the stability of high intensity beams. Implementations of NIO based on specialized magnetic elements are being tested at the Integrable Optics Test Accelerator (IOTA) at Fermilab. One method of verifying proper implementation of these solutions is by measuring the analytic invariants predicted by theory. The initial measurements of nonlinear invariants were performed during IOTA run in 2019/20, however the covid-19 pandemic prevented the full-scale experimental program from being completed. Several important improvements were implemented in IOTA for the 2022/23 run, including the operation at higher beam energy of 150 MeV, improved optics control, and chromaticity correction. This report presents the results of improved measurements of nonlinear invariants.

43 PARTICLE ACCELERATORS↗

NASA NTRS2016

Damage Based Analysis (DBA): Theory, Derivation and Practical Application - Using Both an Acceleration and Pseudo-Velocity Approach

Pseudo Velocity↗

DOE OSTI2025

Surrogate optimization of variational quantum circuits

Variational quantum eigensolvers are touted as a near-term algorithm capable of impacting many applications. However, the potential has not yet been realized, with few claims of quantum advantage and high resource estimates, especially due to the need for optimization in the presence of noise. Finding algorithms and methods to improve convergence is important to accelerate the capabilities of near-term hardware for VQE or more broad applications of hybrid methods in which optimization is required. To this goal, we look to use modern approaches developed in circuit simulations and stochastic classical optimization, which can be combined to form a surrogate optimization approach to quantum circuits. Using an approximate (classical CPU/GPU) state vector simulator as a surrogate model, we efficiently calculate an approximate Hessian, passed as an input for a quantum processing unit or exact circuit simulator. This method will lend itself well to parallelization across quantum processing units. We demonstrate the capabilities of such an approach with and without sampling noise and a proof-of-principle demonstration on a quantum processing unit utilizing 40 qubits.

Gustafson, Erik J. [RIACS, Mtn. View] (ORCID:00000↗

NASA NTRS1984

Lifting surface theory for a helicopter rotor in forward flight

A lifting surface theory was developed for a helicopter rotor in forward flight for compressible and incompressible flow. The method utilizes the concept of the linearized acceleration potential and makes use of the vortex lattice procedure. Calculations demonstrating the application of the method are given in terms of the lift distribution on a single rotor, a two-bladed rotor, and a rotor with swept-forward and swept-back tips. In addition, the lift on a rotor which is vibrating in a pitching mode at 4/rev is given. Compressibility effects and interference effects for a two-bladed rotor are discussed.

Tai, H.↗

NASA NTRS1985

Lifting surface theory for a helicopter rotor in forward flight

Tai, H.↗

NASA NTRS1985

Compressible, unsteady lifting-surface theory for a helicopter rotor in forward flight

A lifting-surface theory has been developed for a helicopter rotor in forward flight for compressible and incompressible flow. The method utilizes the concept of the linearized acceleration potential and makes use of the doublet lattice procedure. Calculations demonstrating the application of the method are given in terms of the lift distribution on a one-bladed rotor, a two-bladed rotor, and a rotor with swept-forward and swept-back tips. Also, the lift on a rotor vibrating in a pitching mode at 4 per revolution is given. Compressibility effects and interference effects for a two-bladed rotor are discussed.

Runyan, H. L.↗

NASA NTRS1984

Lifting surface theory for a helicopter rotor in forward flight

Tai, H.↗

NASA NTRS1985

Application of a lifting surface theory for a helicopter in forward flight

A lifting-surface theory has been developed for a helicopter rotor in forward flight for compressible and incompressible flow. The method utilizes the concept of the linearized acceleration potential and makes use of the doublet lattice procedure. Calculations demonstrating the application of the method are given in terms of the lift distribution on a single rotor, a two-bladed rotor, and a rotor with swept-forward and swept-back tips. In addition, the lift on a rotor which is vibrating in a pitching mode at 4/rev is given. Compressibility effects and interference effects for a two-bladed rotor are discussed.

Runyan, Harry L.↗

DOE OSTI2021

Methods for Precision Studies of Neutrino Interactions

Accelerator neutrino oscillation experiments provide a sensitive way to investigatea number of major open questions in neutrino physics. To achieve precision neutrinooscillation measurements, we need a good understanding of key aspects of the experiments,such as the detection technologies used and neutrino interactions at few-GeV energies.The MicroBooNE experiment has advanced the development of technologies for LArTPCs.An ultra-violet laser system was introduced to MicroBooNE in order to measure theelectric field in situ, which plays a central role in the formation of charge and lightsignals in LArTPCs. This thesis describes the setup and operation of the laser system. Ideveloped a general methodology to measure the electric field and the consequent spatialdistortion in LArTPCs, which supports precision measurements in accelerator neutrinooscillation experiments. In MicroBooNE, the measured electric field distortions are upto 15 ± 3 % with respect to the nominal value, and the measured spatial distortions areup to 15 ± 3 cm. The result of the electric field measurement is applied to the detectorsimulation and the event reconstruction, which leads to a better detector characterizationfor neutrino analyses. A significant concern for measurements of neutrino interactions ismodel dependence, as the currently available models are not sufficient for describing thepicture of neutrino interacting at few-GeV energies. In this thesis, I developed a detailedstrategy for a model-independent cross-section measurement at low energy transfers,where the available model predictions do not agree with the inclusive measurementsfrom multiple experiments. A likelihood fit technique for cross-section extraction isrealized in an accelerator neutrino experiment using a LArTPC for the first time. Thetreatment of systematic uncertainties developed in this thesis is generally applicable foranalyses using similar fitting techniques. This neutrino interaction study at low energytransfers provides a probe to the poorly understood region of neutrino cross sections. Themeasurement scheme developed here aims to guide future model-independent cross-sectionmeasurements, particularly for neutrino experiments using LArTPCs.

Chen, Yifan↗