SEARCH · Search NASA

Results for “high accelerating gradient”

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 289 records · Page 16

All sources NASA NTRS DOE OSTI

DOE OSTI2024

Reducing field emission in superconducting cavities with ozone

Contaminations on the active surface of high-power microwave resonators, such as radio-frequency accelerator cavities, can greatly enlarge electron field emission and reduce their performance. In this work, we demonstrate the use of ozone to clean the surface of niobium superconducting radio-frequency cavities resulting in reduced field emission and enhanced accelerating gradient before onset of field emission. We report results from processing four cavities.

43 PARTICLE ACCELERATORS↗

NASA NTRS1992

STS-40 orbital acceleration research experiment flight results during a typical sleep period

The Orbital Acceleration Research Experiment (OARE), an electrostatic accelerometer package with complete on-orbit calibration capabilities, was flown for the first time aboard the Space Shuttle on STS-40. This is also the first time an accelerometer package with nano-g sensitivity and a calibration facility has flown aboard the Space Shuttle. The instrument is designed to measure and record the Space Shuttle aerodynamic acceleration environment from the free molecule flow regime through the rarified flow transition into the hypersonic continuum regime. Because of its sensitivity, the OARE instrument defects aerodynamic behavior of the Space Shuttle while in low-earth orbit. A 2-hour orbital time period on day seven of the mission, when the crew was asleep and other spacecraft activities were at a minimum, was examined. During the flight, a 'trimmed-mean' filter was used to produce high quality, low frequency data which was successfully stored aboard the Space Shuttle in the OARE data storage system. Initial review of the data indicated that, although the expected precision was achieved, some equipment problems occurred resulting in uncertain accuracy. An acceleration model which includes aerodynamic, gravity-gradient, and rotational effects was constructed and compared with flight data. Examination of the model with the flight data shows the instrument to be sensitive to all major expected low frequency acceleration phenomena; however, some erratic instrument bias behavior persists in two axes. In these axes, the OARE data can be made to match a comprehensive atmospheric-aerodynamic model by making bias adjustments and slight linear corrections for drift. The other axis does not exhibit these difficulties and gives good agreement with the acceleration model.

Blanchard, R. C.↗

DOE OSTI2025

Progress and challenges in traveling-wave (TW) SRF cavity

Traveling-wave (TW) technology can push the accelerator field gradient of niobium SRF cavity to 70MV/m or higher beyond the limit of 50~60MV/m in Standing-wave (SW) technology. The early stages of TW SRF cavity developments had been funded by several SBIR grants to Euclid Techlabs and completed in collaboration with Fermilab through a 1-cell prototype and a proof-of-principle 3-cell TW cavity. The TW resonance excitation in the 3-cell TW cavity at 2K was demonstrated through the low power RF test in early 2024. A high-power test of the 3-cell in TW mode being prepared. To advance a design and technology to fabricate a novel high gradient TW SRF cavity, FNAL proposed a half-meter TW RF design and R&Ds to realize that are in progress. Here we will report the recent progress in the 3-cell TW cavity and the challenges towards a half-meter scale TW cavity.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Validating methods for modeling composition gradients in planar shock experiments

An interface is Rayleigh–Taylor (RT) unstable when acceleration pushes a less dense material into a more dense one, and the growth of the instability is governed partly by the Atwood number gradient. Double-shell inertial confinement fusion capsules have a foam spacer layer pushing on an inner capsule composed of a beryllium tamper and high-Z inner shell, and so have RT unstable interfaces that require benchmarking. To this end, the results of a planar shock experiment with beryllium/tungsten targets are presented. One target had the normal bilayer construction of beryllium and tungsten in two distinct layers; the second target had the beryllium grading into tungsten with a quasi-exponential profile, motivated by the potential for reduced RT growth with the gradient profile. Simulations mimic the shock profiles for both targets and match the shock velocity to within 5%. These results validate the ability of our simulations to model double-shell capsules with bilayer or graded layer Be/W inner shells, which are needed to design future experiments at the National Ignition Facility.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

HD-Bind: Encoding of Molecular Structure with Low Precision, Hyperdimensional Binary Representations

Publicly available collections of drug-like molecules have grown to comprise tens of billions of compounds due to advances in combinatorial chemistry. Traditional methods for identifying "hit" molecules from a large collection of potential drug-like candidates have relied on biophysical theory to compute approximations to the Gibbs free energy of the binding interaction between the drug and its protein target. These approaches have the major drawback that they require exceptional computing capabilities for even relatively small collections of molecules. Hyperdimensional Computing (HDC) is a recently-proposed learning paradigm that represents data with high-dimension binary vectors; this allows the use of low-precision binary vector arithmetic to create models of the data that can be learned without the need for the gradient-based optimization required in many conventional machine learning and deep learning methods. This algorithmic simplicity allows for acceleration in hardware that has been previously demonstrated in a range of application areas. We consider existing HDC approaches for molecular property classification and introduce two novel encodings of a commonly-used molecular representation, the extended connectivity fingerprint (ECFP). We show that HDC-based inference methods are as much as 91 times more efficient than traditional machine learning methods, and achieve an acceleration of nearly nine orders of magnitude compared to molecular docking. Our results show that HDC accelerated methods retain competitive accuracy on a number of well-studied tasks such as molecular property predictions using the MoleculeNet dataset, and bind/no-bind activity classification using the DUD-E and LIT-PCBA datasets. Our work thus motivates further investigation into molecular representation learning to develop ultraefficient pre-screening tools.

Jones, William↗

NASA NTRS2005

A Parallel Particle Swarm Optimization Algorithm Accelerated by Asynchronous Evaluations

A parallel Particle Swarm Optimization (PSO) algorithm is presented. Particle swarm optimization is a fairly recent addition to the family of non-gradient based, probabilistic search algorithms that is based on a simplified social model and is closely tied to swarming theory. Although PSO algorithms present several attractive properties to the designer, they are plagued by high computational cost as measured by elapsed time. One approach to reduce the elapsed time is to make use of coarse-grained parallelization to evaluate the design points. Previous parallel PSO algorithms were mostly implemented in a synchronous manner, where all design points within a design iteration are evaluated before the next iteration is started. This approach leads to poor parallel speedup in cases where a heterogeneous parallel environment is used and/or where the analysis time depends on the design point being analyzed. This paper introduces an asynchronous parallel PSO algorithm that greatly improves the parallel e ciency. The asynchronous algorithm is benchmarked on a cluster assembled of Apple Macintosh G5 desktop computers, using the multi-disciplinary optimization of a typical transport aircraft wing as an example.

Venter, Gerhard↗

NASA NTRS1995

Effects of gravity on sheared and nonsheared turbulent nonpremixed flames

The present numerical study is concerned with the fundamental physics of the multiway interaction between turbulence, chemical reaction, and buoyancy in a nonpremixed flame. The method of direct numerical simulation (DNS) is used to solve the instantaneous, three-dimensional governing equations. Because of the present supercomputer limitations, we consider two simple flow geometries, namely an initially uniform flow without shear (equivalent to grid-generated turbulence) and an initially uniform shear flow. In each flow, the fuel and oxidant initially exist as two separate streams. As the reactants mix, chemical reaction takes place and exothermic energy is released causing variations in density. In the presence of a gravity field, the spatial and temporal distributions of the induced buoyancy forces depend on the local density gradients and the direction of the gravitational acceleration. The effects of buoyancy include the generation of local shear, baroclinic production or destruction of vorticity, and countergradient heat and mass transport. Increased vorticity and small-scale turbulence promote further mixing and reaction. However, if the strain-rates become too high, local flame extinction can occur. Our objective is to gain an understanding of the complex interactions between the physical phenomena involved, with particular attention to the effects of buoyancy on the turbulence structure, flame behavior, and factors influencing flame extinction.

Elghobashi, Said↗

NASA NTRS1946

An Estimation of the Flying Qualities of the Kaiser Fleetwing All-Wing Airplane from Tests of a 1/7-Scale Model, TED No. NACA 2340

An investigation of a 1/7-scale powered model of the Kaiser Fleetwing all-wing airplane was made in the Langley full-scale tunnel to provide data for an estimation of the flying qualities of the airplane. The analysis of the stability and control characteristics of the airplane has been made as closely as possible in accordance with the requirements of the Bureau of Aeronautics, Navy Department's specifications, and a summary of the more significant conclusions is presented as follows. With the normal center of gravity located at 20 percent of the mean aerodynamic chord, the airplane will have adequate static longitudinal stability, elevator fixed, for all flight conditions except for low-power operation at low speeds where the stability will be about neutral. There will not be sufficient down-elevator deflection available for trim above speeds of about 130 miles per hour. It is probable that the reduction in the up-elevator deflections required for trim will be accompanied by reduced elevator hinge moments for low-power operation at low flight speeds. The static directional stability for this airplane will be low for all rudder-fixed or rudder-free flight conditions. The maximum rudder deflection of 30 deg will trim only about 15 deg yaw for most flight conditions and only 10 deg yaw for the condition with low power at low speeds. Also, at low powers and low speeds, it is estimated that the rudders will not trim the total adverse yaw resulting from an abrupt aileron roll using maximum aileron deflection. The airplane will meet the requirements for stability and control for asymmetric power operation with one outboard engine inoperative. The airplane would have no tendency for directional divergence but would probably be spirally unstable, with rudders fixed. The static lateral stability of the airplane will probably be about neutral for the high-speed flight conditions and will be only slightly increased for the low-power operation in low-speed flight. The airplane will not roll against the ailerons in a side-slip maneuver. Although the airplane would probably meet the minimum requirements of pb/2V of 0.07 at all speeds, there will be a loss in rolling ability of the airplane at high aileron deflections and at low flight speeds. It is estimated that the wing stall will be a gradual movement forward from the trailing edge and will be accompanied by no sudden pitching or rolling accelerations. Some stall warning may be indicated by reduction in the elevator and aileron force gradients and by the shaking of the controls caused by unsteady flow over the surfaces near the stall.

Brewer, Gerald W.↗

DOE OSTI2024

Optimization using pathwise algorithmic derivatives of electromagnetic shower simulations

Among the well-known methods to approximate derivatives of expectancies computed by Monte-Carlo simulations, averages of pathwise derivatives are often the easiest one to apply. Computing them via algorithmic differentiation typically does not require major manual analysis and rewriting of the code, even for very complex programs like simulations of particle-detector interactions in high-energy physics. However, the pathwise derivative estimator can be biased if there are discontinuities in the program, which may diminish its value for applications. This work integrates algorithmic differentiation into the electromagnetic shower simulation code HepEmShow based on G4HepEm, allowing us to study how well pathwise derivatives approximate derivatives of energy depositions in a sampling calorimeter with respect to parameters of the beam and geometry. We found that when multiple scattering is disabled in the simulation, means of pathwise derivatives converge quickly to their expected values, and these are close to the actual derivatives of the energy deposition. Additionally, we demonstrate the applicability of this novel gradient estimator for stochastic gradient-based optimization in a model example.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

Progress in the Development of the Nb 3 Sn MQXFB Quadrupole for the HiLumi Upgrade of the LHC

The high-luminosity upgrade of the Large Hadron Collider (HL-LHC) requires new high field and large-aperture quadrupole magnets for the low-beta inner triplets (MQXF). With a nominal operating gradient of 132.2 T/m in a 150 mm aperture and a conductor peak field of 11.3 T, the new quadrupole magnets are based on Nb 3 Sn superconducting technology. After a series of short models constructed in close collaboration by LARP (LHC Accelerator Research Program) and CERN, the development program is entering in the series production phase with CERN on one side and the US Accelerator Upgrade Project (US-AUP) on the other side assembling and testing full-length magnets. This paper describes the status of the development activities at CERN, in particular on the cold powering test of the first MQFXB prototype and on the construction of the second full scale prototype. Critical operations such as reaction heat treatment, coil impregnation and magnet assembly are discussed. Finally, the plan towards the series production is described.

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

A modeling study of ocean thermal energy conversion resource and potential environmental effects around Kailua-Kona, Hawaii

Ocean Thermal Energy Conversion (OTEC) offers a promising renewable energy solution through a heat exchange process using the temperature difference between warm surface seawater and cold deep seawater. Because accurate resource characterization is critical for the optimal design and implementation of OTEC systems, a high-resolution numerical model is employed to better characterize the OTEC resource at Kona, Hawaii. Our model provides detailed spatial and temporal variability of the thermal gradient, which is essential for assessing the viability and efficiency of OTEC systems. The model results reveal distinct patterns and dynamics not captured by existing observations or models (e.g., lower-resolution information). These findings highlight the importance of using high-resolution models for accurate predictions of thermal gradient variability, ultimately supporting more efficient and sustainable OTEC deployment. Additionally, the study investigates the impacts of mixed water discharge from OTEC plants that can cause shock to organisms living in the surface water and potentially destabilize the water column. Understanding these effects is vital for minimizing any potential negative environmental consequences and ensuring the long-term viability of OTEC operations. Further, our model improves OTEC resource characterization, which can lead to optimal design and deployment of OTEC systems. The analysis of OTEC water discharge impacts can accelerate the development of OTEC technologies, overcoming permitting/consenting challenges. These findings contribute to the broader adoption of high-resolution modeling in ocean energy resource characterization, particularly for OTEC applications.

30 DIRECT ENERGY CONVERSION↗

NASA NTRS2001

Flux Compression Magnetic Nozzle

In pulsed fusion propulsion schemes in which the fusion energy creates a radially expanding plasma, a magnetic nozzle is required to redirect the radially diverging flow of the expanding fusion plasma into a rearward axial flow, thereby producing a forward axial impulse to the vehicle. In a highly electrically conducting plasma, the presence of a magnetic field B in the plasma creates a pressure B(exp 2)/2(mu) in the plasma, the magnetic pressure. A gradient in the magnetic pressure can be used to decelerate the plasma traveling in the direction of increasing magnetic field, or to accelerate a plasma from rest in the direction of decreasing magnetic pressure. In principle, ignoring dissipative processes, it is possible to design magnetic configurations to produce an 'elastic' deflection of a plasma beam. In particular, it is conceivable that, by an appropriate arrangement of a set of coils, a good approximation to a parabolic 'magnetic mirror' may be formed, such that a beam of charged particles emanating from the focal point of the parabolic mirror would be reflected by the mirror to travel axially away from the mirror. The degree to which this may be accomplished depends on the degree of control one has over the flux surface of the magnetic field, which changes as a result of its interaction with a moving plasma.

Thio, Y. C. Francis↗

DOE OSTI2022

Multi-variance replica exchange SGMCMC for inverse and forward problems via Bayesian PINN

Physics-informed neural network (PINN) has been successfully applied in solving a variety of nonlinear non-convex forward and inverse problems. However, the training is challenging because of the non-convex loss functions and the multiple optima in the Bayesian inverse problem. In this work, we propose a multi-variance replica exchange stochastic gradient Langevin dynamics method to tackle the challenge of the multiple local optima in the optimization and the challenge of the multiple modal posterior distribution in the inverse problem. Replica exchange methods are capable of escaping from the local traps and accelerating the convergence; two chains with different temperatures are designed where the low temperature chain aims for the local convergence, and the target of the high temperature chain is to travel globally and explore the whole loss function entropy landscape. However, it may not be efficient to solve mathematical inversion problems by using the vanilla replica method directly since the method doubles the computational cost in evaluating the forward solvers (likelihood functions) in the two chains. To address this issue, we propose to make different assumptions on the energy function estimation and this facilities one to use solvers of different fidelities in the likelihood function evaluation. More precisely, one can use a solver with low fidelity in the high temperature chain while using a solver with high fidelity in the low temperature chain. Our proposed method significantly lowers the computational cost in the high temperature chain, meanwhile preserving the accuracy and converging very fast. Here we give an unbiased estimate of the swapping rate and give an estimation of the discretization error of the scheme. To verify our idea, we design and solve four inverse problems which have multiple modes. The proposed method is also employed to train the Bayesian PINN to solve the forward and inverse problems; faster and more accurate convergence has been observed when compared to the stochastic gradient Langevin dynamics (SGLD) method and vanilla replica exchange methods.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

CO 2 storage site characterization using ensemble-based approaches with deep generative models

Estimating spatially distributed properties such as permeability from available sparse measurements is a great challenge in efficient subsurface CO 2 storage operations. In this paper, a deep generative model that can accurately capture complex subsurface structure is tested with an ensemble-based inversion method for accurate and accelerated characterization of CO 2 storage sites. We chose Wasserstein Generative Adversarial Network with Gradient Penalty (WGAN-GP) for its realistic reservoir property representation and Ensemble Smoother with Multiple Data Assimilation (ES-MDA) for its robust data fitting and uncertainty quantification capability. WGAN-GP are trained to generate high-dimensional permeability fields from a low-dimensional latent space and ES-MDA then updates the latent variables by assimilating available measurements. Several subsurface site characterization examples including Gaussian, channelized, and fractured reservoirs are used to evaluate the accuracy and computational efficiency of the proposed method and the main features of the unknown permeability fields are characterized accurately with reliable uncertainty quantification. Furthermore, the estimation performance is compared with a widely-used variational, i.e., optimization-based, inversion approach, and the proposed approach outperforms the variational inversion method in several benchmark cases. We explain such superior performance by visualizing the objective function in the latent space: because of nonlinear and aggressive dimension reduction via generative modeling, the objective function surface becomes extremely complex while the ensemble approximation can smooth out the multi-modal surface during the minimization. This suggests that the ensemble-based approach works well over the variational approach when combined with deep generative models at the cost of forward model runs unless convergence-ensuring modifications are implemented in the variational inversion.

42 ENGINEERING↗

DOE OSTI2020

Adaptive Activation Functions Accelerate Convergence in Deep and Physics-informed Neural Networks

We employ adaptive activation functions for regression in deep and physics-informed neural networks (PINNs) to approximate smooth and discontinuous functions as well as solutions of linear and nonlinear partial differential equations. In particular, we solve the nonlinear Klein-Gordon equation, which has smooth solutions, the nonlinear Burgers equation, which can admit high gradient solutions, and the Helmholtz equation. We introduce a scalable hyper-parameter in the activation function, which can be optimized to achieve best performance of the network as it changes dynamically the topology of the loss function involved in the optimization process. The adaptive activation function has better learning capabilities than the traditional one (fixed activation) as it improves greatly the convergence rate, especially at early training, as well as the solution accuracy. To better understand the learning process, we plot the neural network solution in the frequency domain to examine how the network captures successively different frequency bands present in the solution. We consider both forward problems, where the approximate solutions are obtained, as well as inverse problems, where parameters involved in the governing equation are identified. Our simulation results show that the proposed method is a very simple and effective approach to increase the efficiency, robustness and accuracy of the neural network approximation of nonlinear functions as well as solutions of partial differential equations, especially for forward problems. We theoretically prove that in the proposed method, gradient descent algorithms are not attracted to suboptimal critical points or local minima.

machine leaning, Bad minima, Inverse problems, Phy↗

DOE OSTI2021

High gradient C-band research at Los Alamos [Slides]

The Los Alamos C-band Test stand (CERF-NM) is operational. We are about to start testing and fabricating cavities using various materials and various fabrication methods for both ours and collaborators’ cavities.

42 ENGINEERING↗

DOE OSTI2020

Tune compensation in nearly scaling fixed field alternating gradient accelerators

In this paper, we investigate the stability of the particle trajectories in fixed field alternating gradient accelerators (FFAs) in the presence of field errors. The emphasis is on the scaling radial sector FFA type: A collaboration work is ongoing in view of better understanding the properties of the 150 MeV scaling FFA at Kyoto University Institute for Integrated Radiation and Nuclear Science in Japan and progress toward high-intensity operation. Analysis of certain types of field imperfections revealed some interesting features that required the development of an analytical model based on the scalloping angle of the orbits. This helped explain some of the experimental results as well as generalize the concept of a scaling FFA to a nonscaling one for which the tune variations obey a well-defined law. Based on this, a compensation scheme of tune variations in imperfect scaling FFAs is presented. This is the cornerstone of a novel concept of a fixed tune FFA in which the scaling is not achieved at every azimuthal position of the ring but rather in an average sense.

43 PARTICLE ACCELERATORS↗

NASA NTRS1992

Upwind scheme for solving the Euler equations on unstructured tetrahedral meshes

An upwind scheme is presented for solving the three-dimensional Euler equations on unstructured tetrahedral meshes. Spatial discretization is accomplished by a cell-centered finite-volume formulation using flux-difference splitting. Higher-order differences are formed by a multidimensional linear reconstruction process. The solution gradients required for the higher-order differenes are computed by a novel approach that yields highly resolved solutions in regions of smooth flow while avoiding oscillations across shocks without explicitly applying a limiter. Solutions are advanced in time by a three-stage Runge-Kutta time-stepping scheme with convergence accelerated to steady state by local time stepping and implicit residual smoothing. Transonic solutions are presented for two meshes around the ONERA M6 wing and demonstrate substantial accuracy and insensitivity to mesh size.

Frink, Neal T.↗