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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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At least 1,477 records · Page 82

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NASA NTRS1975

Two self-test methods applied to an inertial system problem

The paper describes two self-test procedures applied to the problem of estimating the biases in accelerometers and gyroscopes on an inertial platform. The first technique is the weighted sum-squared residual (WSSR) test, with which accelerator bias jumps are easily isolated, but gyro bias jumps are difficult to isolate. The WSSR method does not take full advantage of the knowledge of system dynamics. The other technique is a multiple hypothesis method developed by Buxbaum and Haddad (1969). It has the advantage of directly providing jump isolation information, but suffers from computational problems. It might be possible to use the WSSR to detect state jumps and then switch to the BH system for jump isolation and estimate compensation.

Willsky, A. S.↗

DOE OSTI2022

Neural network accelerator for quantum control

Efficient quantum control is necessary for practical quantum computing implementations with current technologies. Conventional algorithms for determining optimal control parameters are computationally expensive, largely excluding them from use outside of the simulation. Existing hardware solutions structured as lookup tables are imprecise and costly. By designing a machine learning model to approximate the results of traditional tools, a more efficient method can be produced. Such a model can then be synthesized into a hardware accelerator for use in quantum systems. In this study, we demonstrate a machine learning algorithm for predicting optimal pulse parameters. This algorithm is lightweight enough to fit on a low-resource FPGA and perform inference with a latency of 175 ns and pipeline interval of 5 ns with > 0.99 gate fidelity. In the long term, such an accelerator could be used near quantum computing hardware where traditional computers cannot operate, enabling quantum control at a reasonable cost at low latencies without incurring large data bandwidths outside of the cryogenic environment.

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

Mitigation of Pitting on Nitrogen-Doped Niobium Surfaces through Two-Step Electropolishing

Surface processing of niobium superconducting RF cavities used in particle accelerators is crucial for determining their performance. The nitrogen (N)-doping method, developed at Fermilab, enhances the cavities’ quality factor by doping the cavity’s interior surface with N atoms at 800 °C. After N-doping, electropolishing (EP) is employed to remove the niobium nitride phases and attain the desired concentration of interstitial N atoms. This study explores the effects of EP conditions on N-doped niobium samples. The samples were electropolished at 5 to 40 °C and voltages between 3 and 22 V. Different EP voltage ranges produced two types of pits, classified based on their sizes. Larger pits, linked to higher voltages, are also affected by the reaction rate. Pitting could be reduced at a lower temperature and adequate EP voltage. However, to effectively minimize gas evolution forming large-sized pitting, peeling off the top nitride layer before EP might be beneficial. This was achieved through precise low-voltage etching, forming a two-step EP process. The process involves removing the top 100–200 nm layer at a low voltage, followed by standard EP to remove the required material. This two-step EP process effectively mitigated the pitting risk associated with gas evolution on N-doped surfaces.

43 PARTICLE ACCELERATORS↗

NASA NTRS1982

A computational design method for transonic turbomachinery cascades

This paper describes a systematical computational procedure to find configuration changes necessary to modify the resulting flow past turbomachinery cascades, channels and nozzles, to be shock-free at prescribed transonic operating conditions. The method is based on a finite area transonic analysis technique and the fictitious gas approach. This design scheme has two major areas of application. First, it can be used for design of supercritical cascades, with applications mainly in compressor blade design. Second, it provides subsonic inlet shapes including sonic surfaces with suitable initial data for the design of supersonic (accelerated) exits, like nozzles and turbine cascade shapes. This fast, accurate and economical method with a proven potential for applications to three-dimensional flows is illustrated by some design examples.

Sobieczky, H.↗

NASA NTRS1994

Stiffness-generated rigid-body mode shapes for Lanczos eigensolution with SUPORT DOF by way of a MSC/NASTRAN DMAP alter

When using all MSC/NASTRAN eigensolution methods except Lanczos, the analyst can replace the coupled system rigid-body modes calculated within DMAP module READ with mass orthogonalized and normalized rigid-body modes generated from the system stiffness. This option is invoked by defining MSC/NASTRAN r-set degrees of freedom via the SUPORT bulk data card. The newly calculated modes are required if the rigid-body modes calculated by the eigensolver are not 'clean' due to numerical roundoffs in the solution. When performing transient structural dynamic load analysis, the numerical roundoffs can result in inaccurate rigid-body accelerations which affect steady-state responses. Unfortunately, when using the Lanczos method and defining r-set degrees of freedom, the rigid-body modes calculated within DMAP module REIGL are retained. To overcome this limitation and to allow MSC/NASTRAN to handle SUPORT degrees of freedom identically for all eigensolvers, a DMAP Alter has been written which replaces Lanczos-calculated rigid-body modes with stiffness-generated rigid-body modes. The newly generated rigid-body modes are normalized with respect to the system mass and orthogonalized using the Gram-Schmidt technique. This algorithm has been implemented as an enhancement to an existing coupled loads methodology.

Abdallah, Ayman A.↗

DOE OSTI2023

Accelerating discrete dislocation dynamics simulations with graph neural networks

Discrete dislocation dynamics (DDD) is a widely employed computational method to study plasticity at the mesoscale that connects the motion of dislocation lines to the macroscopic response of crystalline materials. However, the computational cost of DDD simulations remains a bottleneck that limits its range of applicability. Here, we introduce a new DDD-GNN framework in which the expensive time-integration of dislocation motion is entirely substituted by a graph neural network (GNN) model trained on DDD trajectories. As a first application, we demonstrate the feasibility and potential of our method on a simple yet relevant model of a dislocation line gliding through an array of obstacles. We show that the DDD-GNN model is stable and reproduces very well unseen ground-truth DDD simulation responses for a range of straining rates and obstacle densities, without the need to explicitly compute nodal forces or dislocation mobilities during time-integration. Our approach opens new promising avenues to accelerate DDD simulations and to incorporate more complex dislocation motion behaviors.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Reinforcement Learning-Based Approach for EMT Automation of Large-Scale PV Plants

In the pursuit of efficient and precise modeling of large-scale power systems, particularly utility-scale photovoltaic (PV) plants, Electromagnetic Transient (EMT) simulations play a crucial role. As utility-scale PV plants increase in size and complexity, traditional computational methods become inadequate, necessitating more advanced techniques. This paper highlights the progressive efforts made to accelerate EMT simulations. A novel continuous reinforcement learning (RL) strategy is explored to automate the differentiation and categorization of stiff and non-stiff differential algebraic equations (DAEs). The use of stiff and non-stiff integration methods applied to relevant parts of the DAEs assists with the speed-up of the simulations. The paper details the data acquisition, development and offline training of the RL model, leading to its validation that demonstrates a high precision in optimizing simulation methods. The proposed RL promises to significantly enhance the efficacy of EMT simulations, offering a robust framework for the future of power system analysis.

Xia, Qianxue↗

NASA NTRS2011

Accelerated Adaptive MGS Phase Retrieval

The Modified Gerchberg-Saxton (MGS) algorithm is an image-based wavefront-sensing method that can turn any science instrument focal plane into a wavefront sensor. MGS characterizes optical systems by estimating the wavefront errors in the exit pupil using only intensity images of a star or other point source of light. This innovative implementation of MGS significantly accelerates the MGS phase retrieval algorithm by using stream-processing hardware on conventional graphics cards. Stream processing is a relatively new, yet powerful, paradigm to allow parallel processing of certain applications that apply single instructions to multiple data (SIMD). These stream processors are designed specifically to support large-scale parallel computing on a single graphics chip. Computationally intensive algorithms, such as the Fast Fourier Transform (FFT), are particularly well suited for this computing environment. This high-speed version of MGS exploits commercially available hardware to accomplish the same objective in a fraction of the original time. The exploit involves performing matrix calculations in nVidia graphic cards. The graphical processor unit (GPU) is hardware that is specialized for computationally intensive, highly parallel computation. From the software perspective, a parallel programming model is used, called CUDA, to transparently scale multicore parallelism in hardware. This technology gives computationally intensive applications access to the processing power of the nVidia GPUs through a C/C++ programming interface. The AAMGS (Accelerated Adaptive MGS) software takes advantage of these advanced technologies, to accelerate the optical phase error characterization. With a single PC that contains four nVidia GTX-280 graphic cards, the new implementation can process four images simultaneously to produce a JWST (James Webb Space Telescope) wavefront measurement 60 times faster than the previous code.

Lam, Raymond K.↗

NASA NTRS1995

Computational Study of Flow Establishment in a Ram Accelerator

The temporal evolution of the combustion process established during projectile transition from the launch tube into the ram accelerator section containing an explosive hydrogen-oxygen-argon gas mixture is studied. The Navier-Stokes equations for chemically reacting flow are solved in a fully coupled manner, using an implicit, time accurate algorithm. The solution procedure is based on a spatially second order total variation diminishing scheme and a temporally second order, variable-step, backward differentiation formula method. The hydrogen-oxygen chemistry is modeled with a 9-species, 19-step mechanism. The accuracy of the solution method is first demonstrated by several benchmark calculations. Numerical simulations of two ram accelerator configurations are then presented. In particular, the temporal developments of shock-induced combustion and thrust forces are followed. Positive thrust is established in both cases; however, in one of the ram accelerator configurations studied, combustion in the boundary layer enhances its separation, ultimately resulting in unstart.

Yungster, S.↗

NASA NTRS1991

A numerical algorithm for optimal feedback gains in high dimensional linear quadratic regulator problems

A hybrid method for computing the feedback gains in linear quadratic regulator problem is proposed. The method, which combines use of a Chandrasekhar type system with an iteration of the Newton-Kleinman form with variable acceleration parameter Smith schemes, is formulated to efficiently compute directly the feedback gains rather than solutions of an associated Riccati equation. The hybrid method is particularly appropriate when used with large dimensional systems such as those arising in approximating infinite-dimensional (distributed parameter) control systems (e.g., those governed by delay-differential and partial differential equations). Computational advantages of the proposed algorithm over the standard eigenvector (Potter, Laub-Schur) based techniques are discussed, and numerical evidence of the efficacy of these ideas is presented.

Banks, H. T.↗

DOE OSTI2019

Advances in global optimization of high brightness beams

High brightness electron beams play an important role in accelerator-based applications such as driving X-ray free electron laser (FEL) radiation.Here in this paper, we report on advances in global beam dynamics optimization of an accelerator design using start-to-end simulations and a new parallel multi-objective differential evolution optimization method. The global optimization results in significant improvement of the final electron beam brightness.

43 PARTICLE ACCELERATORS↗

NASA NTRS2008

High-Performance Polyimide Powder Coatings

Much of the infrastructure at Kennedy Space Center and other NASA sites has been subjected to outside weathering effects for more than 40 years. Because much of this infrastructure has metallic surfaces, considerable effort is continually devoted to developing methods to minimize the effects of corrosion on these surfaces. These efforts are especially intense at KSC, where offshore salt spray and exhaust from Solid Rocket Boosters accelerate corrosion. Coatings of various types have traditionally been the choice for minimizing corrosion, and improved corrosion control methods are constantly being researched. Recent work at KSC on developing an improved method for repairing Kapton (polyimide)-based electrical wire insulation has identified polyimides with much lower melting points than traditional polyimides used for insulation. These lower melting points and the many other outstanding physical properties of polyimides (thermal stability, chemical resistance, and electrical properties) led us to investigate whether they could be used in powder coatings.

Source record↗

DOE OSTI2021

Insight into SEI Growth in Li-Ion Batteries using Molecular Dynamics and Accelerated Chemical Reactions

The performance of lithium-ion batteries (LIB) using organic electrolytes strongly depends on the formation of a stable solid electrolyte interphase (SEI) film. Elucidating the dynamic evolution and spatial composition of the SEI can be very useful to study the stability of SEI components and help optimize the formation cycles of LIB. We propose a classical molecular dynamics simulation protocol for predicting the first stages of SEI formation using a reaction method involving the decomposition of EC and LiPF 6 molecules in the electrolyte. We accelerate the formation of SEI components near the anode surface by increasing the probability of reactions, implemented through a geometry matching scheme, followed by a force-field reconfiguration. We observe the formation of gases (C 2 H 4 ), inorganic (Li 2 CO 3 and LiF) and organic (LEDC) components. Finally, this protocol shows promise to be able to evaluate the effects of varying electrolyte compositions and additives on SEI layer structure and composition.

25 ENERGY STORAGE↗

DOE OSTI2021

Inverse Biot–Savart Optimization for Superconducting Accelerator Magnets

Superconducting (SC) magnets for accelerator concepts are often synthesized by numerically optimizing magnetic field waveforms, a process that requires a subsequent solution of a constrained inverse problem to identify suitable SC magnet windings. When the desired field distribution is intuitive, the inverse process is facilitated by seeding preconceived coil distributions into design optimization methods for refinement. With more complex magnetic field distributions, an initial design may be unknown, and topology optimization tools are required to synthesize current distributions without a priori guidance from a subject matter expert. In this work, we develop a constrained inverse Biot-Savart topology optimization methodology that synthesizes optimal distributions of current density in racetrack-like SC coils. The problem structure is exploited through a computationally efficient quadratic programming formulation, and the method is applied to recently published magnetic field waveforms for a recirculating proton phase shifter, a proton therapy gantry, and dipole magnets with sharp field transitions. The method and results herein identify novel winding configurations that can help magnet designers bring accelerator concepts to fruition.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRS1988

An explicit Runge-Kutta method for 3D turbulent incompressible flows

A computer code has been developed to solve for the steady-state solution of the 3D incompressible Reynolds-averaged Navier-Stokes equations. The approach is based on the cell-center, central-difference, finite-volume formulation and an explicit one-step, multistage Runge-Kutta time-stepping scheme. The Baldwin-Lomax turbulence model is used. Techniques to accelerate the rate of convergence to a steady-state solution include the preconditioned method, the local time stepping, and the implicit residual smoothing. Improvements in computational efficiency have been demonstrated in several areas. This numerical procedure has been used to simulate the turbulent horseshoe vortex flow around an airfoil/flat-plate juncture.

Sung, Chao-Ho↗

NASA NTRS2007

Implementation of Leak Test Methods for the International Space Station (ISS) Elements, Systems and Components

The International Space Station (ISS has Qualification and Acceptance Environmental Test Requirements document, SSP 41172 that includes many environmental tests such as Thermal vacuum & Cycling, Depress/Repress, Sinusoidal, Random, and Acoustic Vibration, Pyro Shock, Acceleration, Humidity, Pressure, Electromatic Interference (EMI)/Electromagnetic Compatibility (EMCO), etc. This document also includes (13) leak test methods for Pressure Integrity Verification of the ISS Elements, Systems, and Components. These leak test methods are well known, however, the test procedure for specific leak test method shall be written and implemented paying attention to the important procedural steps/details that, if omitted or deviated, could impact the quality of the final product and affect the crew safety. Such procedural steps/details for different methods include, but not limited to: - Sequence of testing, f or example, pressurization and submersion steps for Method I (Immersion); - Stabilization of the mass spectrometer leak detector outputs fo r Method II (vacuum Chamber or Bell jar); - Proper data processing an d taking a conservative approach while making predictions for on-orbit leakage rate for Method III(Pressure Change); - Proper Calibration o f the mass spectrometer leak detector for all the tracer gas (mostly Helium) Methods such as Method V (Detector Probe), Method VI (Hood), Method VII (Tracer Probe), Method VIII(Accumulation); - Usage of visibl ility aides for Method I (Immersion), Method IV (Chemical Indicator), Method XII (Foam/Liquid Application), and Method XIII (Hydrostatic/Visual Inspection); While some methods could be used for the total leaka ge (either internal-to-external or external-to-internal) rate requirement verification (Vacuum Chamber, Pressure Decay, Hood, Accumulation), other methods shall be used only as a pass/fail test for individual joints (e.g., welds, fittings, and plugs) or for troubleshooting purposes (Chemical Indicator, Detector Probe, Tracer Probe, Local Vacuum Chamber, Foam/Liquid Application, and Hydrostatic/Visual Inspection). Any isolation of SSP 41172 requirements have led to either retesting of hardware or accepting a risk associated with the potential system or component pressure integrity problem during flight.

Underwood, Steve↗

NASA NTRS1929

Corrosion Embrittlement of Duralumin V : Results of Weather-Exposure Tests

In a series of weather exposure tests of sheet duralumin, upon which accelerated corrosion tests in the laboratory by the wet-and-dry corrosion method in a sodium chloride solution has already been carried out, a close parallelism between the results of the two kinds of tests was found to exist. The exposure tests showed that the lack of permanence of sheet duralumin is largely, if not entirely, due to corrosion. A corrosion attack of an intercrystalline nature is very largely responsible for the degree of embrittlement produced. The rate of embrittlement was greatly accelerated by a marine atmosphere and by the tropical climate. Variations in corrosion and embrittlement are noted in relation to heat treatment, cold working, and types of protective coatings.

Rawdon, Henry S↗

DOE OSTI2025

Virtual to Physical: Reinforcement Learning to Optimize SNS Particle Accelerator Controls

Complex accelerators must have control systems that can handle dynamic nonlinear environments. This makes traditional control methods unsuitable as they can struggle to adapt to these uncertainties. This provides an ideal environment for reinforcement learning algorithms as they are adaptable and generalizable. We present a reinforcement learning pipeline that can effectively handle the dynamics of a complex accelerator. We test and prove our pipelines capabilities on multiple environments including the Spallation Neutron Source (SNS) and the Beam Test Facility (BTF) at Oakridge National Lab (ORNL). Due to the limited time available to train an online algorithm like reinforcement learning on a real accelerator, we utilize a virtual twin accelerator (VIRAC) developed by ORNL to pretrain the policy and show its ability to converge in the virtual environment. We then test the adaptability of the pretrained RL model by applying it on the real accelerator and comparing the results. Utilizing our Scientific Optimization and Controls Toolkit (SOCT) and open-source standards such as Gymnasium we create and solve for a MEBT orbit correction problem in the SNS and an emittance maximization problem in the BTF. We show how Twin Delayed Deep Deterministic Policy Gradient (TD3) can solve this optimization environment in the virtual accelerator and transfer this policy onto the real accelerator for inference and model retraining. We show how reinforcement learning can be utilized as a control system for complex accelerators and provide a model pipeline for how an implementation performs and can be adapted to new accelerator control problems.

Kasparian, Armen [Thomas Jefferson National Accele↗