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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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NASA NTRS2011

NASA Scope and Subject Category Guide

This guide provides a simple, effective tool to assist aerospace information analysts and database builders in the high-level subject classification of technical materials. Each of the 76 subject categories comprising the classification scheme is presented with a description of category scope, a listing of subtopics, cross references, and an indication of particular areas of NASA interest. The guide also includes an index of nearly 3,000 specific research topics cross referenced to the subject categories. The portable document format (PDF) version of the guide contains links in the index from each input subject to its corresponding categories. In addition to subject classification, the guide can serve as an aid to searching databases that use the classification scheme, and is also an excellent selection guide for those involved in the acquisition of aerospace literature. The CD-ROM contains both HTML and PDF versions.

Source record↗

NASA NTRS2002

Digital Distortion Caused by Traveling- Wave-Tube Amplifiers Simulated

Future NASA missions demand increased data rates in satellite communications for near real-time transmission of large volumes of remote data. Increased data rates necessitate higher order digital modulation schemes and larger system bandwidth, which place stricter requirements on the allowable distortion caused by the high-power amplifier, or the traveling-wave-tube amplifier (TWTA). In particular, intersymbol interference caused by the TWTA becomes a major consideration for accurate data detection at the receiver. Experimentally investigating the effects of the physical TWTA on intersymbol interference would be prohibitively expensive, as it would require manufacturing numerous amplifiers in addition to acquiring the required digital hardware. Thus, an accurate computational model is essential to predict the effects of the TWTA on system-level performance when a communication system is being designed with adequate digital integrity for high data rates. A fully three-dimensional, time-dependent, TWT interaction model has been developed using the electromagnetic particle-in-cell code MAFIA (Solution of Maxwell's equations by the Finite-Integration-Algorithm). It comprehensively takes into account the effects of frequency-dependent AM (amplitude modulation)/AM and AM/PM (phase modulation) conversion, gain and phase ripple due to reflections, drive-induced oscillations, harmonic generation, intermodulation products, and backward waves. This physics-based TWT model can be used to give a direct description of the effects of the nonlinear TWT on the operational signal as a function of the physical device. Users can define arbitrary excitation functions so that higher order modulated digital signals can be used as input and that computations can directly correlate intersymbol interference with TWT parameters. Standard practice involves using communication-system-level software packages, such as SPW, to predict if adequate signal detection will be achieved. These models use a nonlinear, black-box model to represent the TWTA. The models vary in complexity, but most make several assumptions regarding the operation of the high-power amplifier. When the MAFIA TWT interaction model was used, these assumptions were found to be in significant error. In addition, digital signal performance, including intersymbol interference, was compared using direct data input into the MAFIA model and using the system-level analysis tool SPW for several higher order modulation schemes. Results show significant differences in predicted degradation between SPW and MAFIA simulations, demonstrating the significance of the TWTA approximations made in the SPW model on digital signal performance. For example, a comparison of the SPW and MAFIA output constellation diagrams for a 16-ary quadrature amplitude modulation (16-QAM) signal (data shown only for second and fourth quadrants) is shown. The upper-bound degradation was calculated from the corresponding eye diagrams. In comparison to SPW simulations, the MAFIA data resulted in a 3.6-dB larger degradation.

Kory, Carol L.↗

DOE OSTI2021

Fast GPU-Based Generation of Large Graph Networks From Degree Distributions

Synthetically generated, large graph networks serve as useful proxies to real-world networks for many graph-based applications. The ability to generate such networks helps overcome several limitations of real-world networks regarding their number, availability, and access. Here, we present the design, implementation, and performance study of a novel network generator that can produce very large graph networks conforming to any desired degree distribution. The generator is designed and implemented for efficient execution on modern graphics processing units (GPUs). Given an array of desired vertex degrees and number of vertices for each desired degree, our algorithm generates the edges of a random graph that satisfies the input degree distribution. Multiple runtime variants are implemented and tested: 1) a uniform static work assignment using a fixed thread launch scheme, 2) a load-balanced static work assignment also with fixed thread launch but with cost-aware task-to-thread mapping, and 3) a dynamic scheme with multiple GPU kernels asynchronously launched from the CPU. The generation is tested on a range of popular networks such as Twitter and Facebook, representing different scales and skews in degree distributions. Results show that, using our algorithm on a single modern GPU (NVIDIA Volta V100), it is possible to generate large-scale graph networks at rates exceeding 50 billion edges per second for a 69 billion-edge network. GPU profiling confirms high utilization and low branching divergence of our implementation from small to large network sizes. For networks with scattered distributions, we provide a coarsening method that further increases the GPU-based generation speed by up to a factor of 4 on tested input networks with over 45 billion edges.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Overview of the EUROfusion Tokamak Exploitation programme in support of ITER and DEMO

Within the 9th European Framework programme, since 2021 EUROfusion is operating five tokamaks under the auspices of a single Task Force called ‘Tokamak Exploitation’. The goal is to benefit from the complementary capabilities of each machine in a coordinated way and help in developing a scientific output scalable to future largre machines. The programme of this Task Force ensures that ASDEX Upgrade, MAST-U, TCV, WEST and JET (since 2022) work together to achieve the objectives of Missions 1 and 2 of the EUROfusion Roadmap: i) demonstrate plasma scenarios that increase the success margin of ITER and satisfy the requirements of DEMO and, ii) demonstrate an integrated approach that can handle the large power leaving ITER and DEMO plasmas. The Tokamak Exploitation task force has therefore organized experiments on these two missions with the goal to strengthen the physics and operational basis for the ITER baseline scenario and for exploiting the recent plasma exhaust enhancements in all four devices (PEX: Plasma EXhaust) for exploring the solution for handling heat and particle exhaust in ITER and develop the conceptual solutions for DEMO. The ITER Baseline scenario has been developed in a similar way in ASDEX Upgrade, TCV and JET. Key risks for ITER such as disruptions and run-aways have been also investigated in TCV, ASDEX Upgrade and JET. Experiments have explored successfully different divertor configurations (standard, super-X, snowflakes) in MAST-U and TCV and studied tungsten melting in WEST and ASDEX Upgrade. The input from the smaller devices to JET has also been proven successful to set-up novel control schemes on disruption avoidance and detachment.

ASDEX upgrade↗

NASA NTRS2010

A Modified Lunar Reconnaissance Orbiter (LRO) High Gain Antenna (HGA) Controller Based on Flight Performance

The National Aeronautics and Space Administration's (NASA) Lunar Reconnaissance Orbiter (LRO) was launched on June 18, 2009 and is currently in a 50 km mean altitude polar orbit around the Moon. LRO was designed and built by the NASA Goddard Space Flight Center in Greenbelt, MD. The spacecraft is three-axis stabilized via the attitude control system (ACS), which is composed of various control modes using different sets of sensors and actuators. In addition to pointing the spacecraft, the ACS is responsible for pointing LRO s two appendages, the Solar Array (SA) and the High Gain Antenna (HGA). This study reviews LRO s HGA control system. Starting with an overview of the HGA system, the paper delves into the single input single output (SISO) linear analysis followed by the controller design. Based on flight results, an alternate control scheme is devised to address inherent features in the flight control system. The modified control scheme couples the HGA loop with the spacecraft pointing control loop, and through analysis is shown to be stable and improve transient performance. Although proposed, the LRO project decided against implementing this modification.

Shah, Neerav↗

DOE OSTI2021

Ripple-Type Control for Enhancing Resilience of Networked Physical Systems

Distributed control agents have been advocated as an effective means for improving the resiliency of our physical infrastructures under unexpected events. Purely local control has been shown to be insufficient, centralized optimal resource allocation approaches can be slow. In this context, we put forth a hybrid low-communication saturation-driven protocol for the coordination of control agents that are distributed over a physical system and are allowed to communicate with peers over a “hotline” communication network. According to this protocol, agents act on local readings unless their control resources have been depleted, in which case they send a beacon for assistance to peer agents. Our ripple-type scheme triggers communication locally only for the agents with saturated resources and it is proved to converge. Moreover, under a monotonicity assumption on the underlying physical law coupling control outputs to inputs, the devised control is proved to converge to a configuration satisfying safe operational constraints. The assumption is shown to hold for voltage control in electric power systems and pressure control in water distribution networks. Numerical tests corroborate the efficacy of the novel scheme.

distributed control↗

NASA NTRS1994

An Adaptively-Refined, Cartesian, Cell-Based Scheme for the Euler and Navier-Stokes Equations

A Cartesian, cell-based scheme for solving the Euler and Navier-Stokes equations in two dimensions is developed and tested. Grids about geometrically complicated bodies are generated automatically, by recursive subdivision of a single Cartesian cell encompassing the entire flow domain. Where the resulting cells intersect bodies, polygonal 'cut' cells are created. The geometry of the cut cells is computed using polygon-clipping algorithms. The grid is stored in a binary-tree data structure which provides a natural means of obtaining cell-to-cell connectivity and of carrying out solution-adaptive refinement. The Euler and Navier-Stokes equations are solved on the resulting grids using a finite-volume formulation. The convective terms are upwinded, with a limited linear reconstruction of the primitive variables used to provide input states to an approximate Riemann solver for computing the fluxes between neighboring cells. A multi-stage time-stepping scheme is used to reach a steady-state solution. Validation of the Euler solver with benchmark numerical and exact solutions is presented. An assessment of the accuracy of the approach is made by uniform and adaptive grid refinements for a steady, transonic, exact solution to the Euler equations. The error of the approach is directly compared to a structured solver formulation. A non smooth flow is also assessed for grid convergence, comparing uniform and adaptively refined results. Several formulations of the viscous terms are assessed analytically, both for accuracy and positivity. The two best formulations are used to compute adaptively refined solutions of the Navier-Stokes equations. These solutions are compared to each other, to experimental results and/or theory for a series of low and moderate Reynolds numbers flow fields. The most suitable viscous discretization is demonstrated for geometrically-complicated internal flows. For flows at high Reynolds numbers, both an altered grid-generation procedure and a different formulation of the viscous terms are shown to be necessary. A hybrid Cartesian/body-fitted grid generation approach is demonstrated. In addition, a grid-generation procedure based on body-aligned cell cutting coupled with a viscous stensil-construction procedure based on quadratic programming is presented.

Coirier, William John↗

DOE OSTI2021

Ripple-Type Control for Enhancing Resilience of Networked Physical Systems: Preprint

Distributed control agents have been advocated as an effective means for improving the resiliency of our physical in-frastructures under unexpected events. While purely local control has been shown to be insufficient, centralized optimal resource allocation approaches can be slow. In this context, we put forth a hybrid low-communication saturation-driven protocol for the coordination of control agents that are distributed over a physicalsystem and are allowed to communicate with peers over a 'hot-line' communication network. According to this protocol, agents act upon on local readings unless their control resources have been depleted, in which case they send a beacon for assistance to peer agents. Our ripple-type scheme triggers communication locally only for the agents with saturated resources, and is proved to converge. Moreover, under a monotonicity assumption on the underlying physical law coupling control outputs to inputs, the devised control is proved to converge to a configuration satisfying safe operational constraints. The assumption is shown to hold for voltage control in electric power systems and pressure control in water distribution networks. Numerical tests on both networks corroborate the efficacy of the novel scheme.

distributed control↗

DOE OSTI2023

Orthogonal spatial coding with stimulated parametric down-conversion

Orthogonal optical coding is widely used in classical multi-user communication networks. Using the phase conjugation property of stimulated parametric down-conversion, we extend the current time-domain orthogonal optical coding scheme to the spatial domain to encode and decode image information. In this process, the idler beam inherits the complex conjugate of the field information encoded in the seed beam. An encoding phase mask introduced onto the input seed beam blurs the image transferred to the idler. The original image is restored by passing the coded transferred image through a corrective phase mask placed in the momentum space of the idler beam. We expect that this scheme can also inspire new techniques in secure image transmission, aberration cancellation, and frequency conversion imaging.

Xu, Yang↗

DOE OSTI2021

Defect detection in atomic-resolution images via unsupervised learning with translational invariance

Abstract Crystallographic defects can now be routinely imaged at atomic resolution with aberration-corrected scanning transmission electron microscopy (STEM) at high speed, with the potential for vast volumes of data to be acquired in relatively short times or through autonomous experiments that can continue over very long periods. Automatic detection and classification of defects in the STEM images are needed in order to handle the data in an efficient way. However, like many other tasks related to object detection and identification in artificial intelligence, it is challenging to detect and identify defects from STEM images. Furthermore, it is difficult to deal with crystal structures that have many atoms and low symmetries. Previous methods used for defect detection and classification were based on supervised learning, which requires human-labeled data. In this work, we develop an approach for defect detection with unsupervised machine learning based on a one-class support vector machine (OCSVM). We introduce two schemes of image segmentation and data preprocessing, both of which involve taking the Patterson function of each segment as inputs. We demonstrate that this method can be applied to various defects, such as point and line defects in 2D materials and twin boundaries in 3D nanocrystals.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Constant Overhead Entanglement Distillation via Scrambling

High-fidelity quantum entanglement enables key quantum networking capabilities such as secure communication and distributed quantum computing, but long-distance entanglement distribution is limited by noise and loss. Entanglement distillation protocols address this problem by extracting high-fidelity Bell pairs from multiple noisy ones. The primary objective is minimizing the resource overhead: the number of noisy input pairs needed to distill each high-fidelity output pair. While protocols achieving optimal overhead are known in theory, they often require complex decoding operations that make practical implementation challenging. We circumvent this challenge by introducing protocols that use quantum scrambling—the spreading of quantum information under chaotic dynamics—through random Clifford operations. Based on this scrambling mechanism, our protocol maintains asymptotically constant overhead, independent of the desired output error rate $\bar{𝜖}$ , and can be implemented with shallow quantum circuits of depth 𝑂⁡(poly log log⁡ $\bar{𝜖}$ −1 ) and memory 𝑂⁡(poly log⁡ $\bar{𝜖}$ −1 ). Our protocol remains effective even with noisy quantum gates. By incorporating error correction, our protocol achieves state-of-the-art performance: starting with pairs of 10% initial infidelity, we require only seven noisy inputs per output pair to distill a single Bell pair with infidelity $\bar{𝜖}$ =10 −12 , substantially outperforming existing schemes. We demonstrate the utility of our protocols for quantum repeater networks.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

DC Link Capacitor Reduction with Feedforward Control in Series-Series Compensated Wireless Power Transfer Systems

This paper presents the use of feedforward control to reduce the input side DC link capacitance of series-series compensated wireless power transfer (WPT) systems. Compared to conventional control schemes for WPT systems, the proposed feedforward-based approach achieves significant reduction in the DC link capacitor without any complicated voltage or current sensing requirements from the secondary side. This results in more compact hardware architecture. The proposed method shows minimal increase in the turn-on switching loss of the inverter. The switching loss is analyzed, and detailed results are presented relating the switching loss to the DC link capacitance and voltage ripple for proper tradeoff between losses and capacitor size. Simulation and experimental results presented validate the proposed scheme.

Mukherjee, Subho↗

DOE OSTI2023

HopPyBar

HopPyBar is a python program to import, analyze, and export split-Hopkinson pressure bar (SHPB, also known as Kolsky bar) data. Traditional analysis offers a black box approach, where input data is converted to analyzed output by performing a series of calculations without user involvement. This program serves as a developmental platform to "white box" the data analysis process. Data streams can be captured (in-situ) to enable advanced or unconventional analyses, statistics, and comparisons. Additionally, the program is geared towards the standardized forms of input and output used at LANL to streamline analysis, but the open nature of the program makes additional input/output schemes straightforward to add. General workflow will import SHPB data in one of a number of formats, identify relevant portions of data signals, and convert to stress-strain-strain rate to show material behavior as a function of dynamic testing.

Morrow, Benjamin↗

NASA NTRS1992

Spatially-varying IIR filter banks for image coding

This paper reports on the application of spatially variant infinite impulse response (IIR) filter banks to subband image coding. The new filter bank is based on computationally efficient recursive polyphase decompositions that dynamically change in response to the input signal. In the absence of quantization, reconstruction can be made exact. However, by proper choice of an adaptation scheme, we show that subband image coding based on time varying filter banks can yield improvement over the use of conventional filter banks.

Chung, Wilson C.↗

NASA NTRSDate not supplied

Control and Scaling Approach for the Emulation of Dynamic Subscale Torque Loads

Research and development of electrified aircraft propulsion powertrains is moving toward the use electro-mechanical systems to emulate the loads a system imparts on another. Replacing a prime mover with a model driving an electro-mechanical system capable of emulating loads that regulate the system to produce a desired response is a lower risk, lower cost alternative to using the traditional prime mover for control system verification. This paper outlines a control and scaling approach for emulating scaled dynamic torque loads using electric machine (EM) hardware for electrified aircraft propulsion research and development purposes. The approach, known as the Sliding Mode Impedance Controller with Scaling (SMICS), drives a mechanically coupled two-EM system that provides a scaled hardware representation of an electrified turbomachinery shaft. One EM reflects inertial dynamics and load of the shaft under steady-state and transient operation while the second EM represents a motor/generator connected to the shaft. This closed loop system applies impedance and sliding mode control schemes to match desired dynamics in real-time along with parameter scaling to effectively scale full scale torque inputs, a full-scale desired inertia, and sub-scale speed feedback. The result is a sub-scale hardware implementation of a coupled EM system that is command-able by a model and control system designed for a full-scale electrified aircraft propulsion powertrain. The paper elaborates on the need for closed loop control and scaling as well as impedance and sliding mode control theory, shows a derivation of the controller and scaling, its implementation, and presents a comparison of theoretical and actual simulation results acquired during hardware-in-the-loop testing of a partial turboelectric propulsion concept at the NASA Electric Aircraft Testbed (NEAT).

Santino J Bianco↗

DOE OSTI2025

Dynamic Low-Rank Training with Spectral Regularization: Achieving Robustness in Compressed Representations

Deployment of neural networks on resource-constrained devices demands models that are both compact and robust to adversarial inputs. However, compression and adversarial robustness often conflict. In this work, we introduce a dynamical low-rank training scheme enhanced with a novel spectral regularizer that controls the condition number of the low-rank core in each layer. This approach mitigates the sensitivity of compressed models to adversarial perturbations without sacrificing clean accuracy. The method is model- and data-agnostic, computationally efficient, and supports rank adaptivity to automatically compress the network at hand. Extensive experiments across standard architectures, datasets, and adversarial attacks show the regularized networks can achieve over 94\% compression while recovering or improving adversarial accuracy relative to uncompressed baselines.

Schotthoefer, Steffen [ORNL] (ORCID:00000002156965↗

DOE OSTI2025

Dynamical Low-Rank Compression of Neural Networks with Robustness under Adversarial Attacks

Deployment of neural networks on resource-constrained devices demands models that are both compact and robust to adversarial inputs. However, compression and adversarial robustness often conflict. In this work, we introduce a dynamical low-rank training scheme enhanced with a novel spectral regularizer that controls the condition number of the low-rank core in each layer. This approach mitigates the sensitivity of compressed models to adversarial perturbations without sacrificing clean accuracy. The method is model- and data-agnostic, computationally efficient, and supports rank adaptivity to automatically compress the network at hand. Extensive experiments across standard architectures, datasets, and adversarial attacks show the regularized networks can achieve over 94 compression while recovering or improving adversarial accuracy relative to uncompressed baselines.

Schotthoefer, Steffen [ORNL] (ORCID:00000002156965↗

NASA NTRS1986

A robust adaptive flightpath reconstruction technique

Computational schemes are presented that allow accurate reconstruction of an aircraft's flightpath in real-time. The reconstruction of the flightpath is formulated as a linear state reconstruction problem, which can be solved via Kalman filtering (KF) techniques. This imposes some conditions upon the flight-test equipment. A reliable square root covariance KF (SRCF) implementation is chosen and further developed into a fully adaptive flightpath reconstruction scheme. Therefore, the basic SRCF is modified in order to cope with several practical problems such as: the automatic control of the convergence of the recursive KF calculations, time varying zero-bias errors on the input signal of the system model used in the KF, and the changing aircraft dynamics owing to a change in reference flight condition. The developed solutions for these problems are all implemented in a numerically stable way, which guarantees the overall flightpath reconstruction scheme to be robust. Furthermore, some special features of the used system model are exploited to make the algorithmic implementation very efficient. An experimental simulation study using simulated flight test data demonstrated these different capabilities.

Verhaegen, M. H.↗