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At least 973 records · Page 54

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NASA NTRS2010

Radio-Frequency Tank Eigenmode Sensor for Propellant Quantity Gauging

Although there are several methods for determining liquid level in a tank, there are no proven methods to quickly gauge the amount of propellant in a tank while it is in low gravity or under low-settling thrust conditions where propellant sloshing is an issue. Having the ability to quickly and accurately gauge propellant tanks in low-gravity is an enabling technology that would allow a spacecraft crew or mission control to always know the amount of propellant onboard, thus increasing the chances for a successful mission. The Radio Frequency Mass Gauge (RFMG) technique measures the electromagnetic eigenmodes, or natural resonant frequencies, of a tank containing a dielectric fluid. The essential hardware components consist of an RF network analyzer that measures the reflected power from an antenna probe mounted internal to the tank. At a resonant frequency, there is a drop in the reflected power, and these inverted peaks in the reflected power spectrum are identified as the tank eigenmode frequencies using a peak-detection software algorithm. This information is passed to a pattern-matching algorithm, which compares the measured eigenmode frequencies with a database of simulated eigenmode frequencies at various fill levels. A best match between the simulated and measured frequency values occurs at some fill level, which is then reported as the gauged fill level. The database of simulated eigenmode frequencies is created by using RF simulation software to calculate the tank eigenmodes at various fill levels. The input to the simulations consists of a fairly high-fidelity tank model with proper dimensions and including internal tank hardware, the dielectric properties of the fluid, and a defined liquid/vapor interface. Because of small discrepancies between the model and actual hardware, the measured empty tank spectra and simulations are used to create a set of correction factors for each mode (typically in the range of 0.999 1.001), which effectively accounts for the small discrepancies. These correction factors are multiplied to the modes at all fill levels. By comparing several measured modes with the simulations, it is possible to accurately gauge the amount of propellant in the tank. An advantage of the RFMG approach of applying computer simulations and a pattern-matching algorithm is that the Although there are several methods for determining liquid level in a tank, there are no proven methods to quickly gauge the amount of propellant in a tank while it is in low gravity or under low-settling thrust conditions where propellant sloshing is an issue. Having the ability to quickly and accurately gauge propellant tanks in low-gravity is an enabling technology that would allow a spacecraft crew or mission control to always know the amount of propellant onboard, thus increasing the chances for a successful mission. The Radio Frequency Mass Gauge (RFMG) technique measures the electromagnetic eigenmodes, or natural resonant frequencies, of a tank containing a dielectric fluid. The essential hardware components consist of an RF network analyzer that measures the reflected power from an antenna probe mounted internal to the tank. At a resonant frequency, there is a drop in the reflected power, and these inverted peaks in the reflected power spectrum are identified as the tank eigenmode frequencies using a peak-detection software algorithm. This information is passed to a pattern-matching algorithm, which compares the measured eigenmode frequencies with a database of simulated eigenmode frequencies at various fill levels. A best match between the simulated and measured frequency values occurs at some fill level, which is then reported as the gauged fill level. The database of simulated eigenmode frequencies is created by using RF simulation software to calculate the tank eigenmodes at various fill levels. The input to the simulations consists of a fairly high-fidelity tank model with proper dimensions and including internal tank harare, the dielectric properties of the fluid, and a defined liquid/vapor interface. Because of small discrepancies between the model and actual hardware, the measured empty tank spectra and simulations are used to create a set of correction factors for each mode (typically in the range of 0.999 1.001), which effectively accounts for the small discrepancies. These correction factors are multiplied to the modes at all fill levels. By comparing several measured modes with the simulations, it is possible to accurately gauge the amount of propellant in the tank. An advantage of the RFMG approach of applying computer simulations and a pattern-matching algorithm is that the

Zimmerli, Gregory A.↗

DOE OSTI2021

Continuum gyrokinetic simulations of edge plasmas in single-null geometries

The first continuum gyrokinetic calculations of electrostatic ion scale turbulence are presented for the case of a diverted tokamak geometry. The simulation model solves the long-wavelength limit of the full-F gyrokinetic equation for ion species coupled to the quasi-neutrality equation for electrostatic potential variations, where a fluid model is used for an electron response. Furthermore, in order to facilitate simulations of highly-anisotropic microturbulence in the presence of strong magnetic shear and a magnetic X-point, a numerical algorithm utilizing a locally field-aligned multiblock coordinate system has been developed and implemented in the 5D finite-volume code COGENT. In this approach, the toroidal direction is divided into blocks, such that within each block, the cells are field-aligned and a non-matching grid interface is allowed at block boundaries. The toroidal angle corresponds to the “coarse” field-aligned coordinate, whereas the poloidal cross section, comprised of the radial and poloidal directions, is finely gridded to resolve short-scale perpendicular turbulence structures and to support accurate re-mapping (interpolation) at block boundaries. The 5D simulations explore cross-separatrix ion scale turbulence in the presence of a self-consistent radial electric field and address the effects of magnetic-shear stabilization in the X-point region.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2010

Implementation of an Autonomous Multi-Maneuver Targeting Sequence for Lunar Trans-Earth Injection

Using a fully analytic initial guess estimate as a first iterate, a targeting procedure that constructs a flyable burn maneuver sequence to transfer a spacecraft from any closed Moon orbit to a desired Earth entry state is developed and implemented. The algorithm is built to support the need for an anytime abort capability for Orion. Based on project requirements, the Orion spacecraft must be able to autonomously calculate the translational maneuver targets for an entire Lunar mission. Translational maneuver target sequences for the Orion spacecraft include Lunar Orbit Insertion (LOI), Trans-Earth Injection (TEI), and Trajectory Correction Maneuvers (TCMs). This onboard capability is generally assumed to be supplemental to redundant ground computation in nominal mission operations and considered as a viable alternative primarily in loss of communications contingencies. Of these maneuvers, the ability to accurately and consistently establish a flyable 3-burn TEI target sequence is especially critical. The TEI is the sole means by which the crew can successfully return from the Moon to a narrowly banded Earth Entry Interface (EI) state. This is made even more critical by the desire for global access on the lunar surface. Currently, the designed propellant load is based on fully optimized TEI solutions for the worst case geometries associated with the accepted range of epochs and landing sites. This presents two challenges for an autonomous algorithm: in addition to being feasible, the targets must include burn sequences that do not exceed the anticipated propellant load.

Whitley, Ryan J.↗

NASA NTRS1998

[MODIS Investigation]

The objectives of the last six months were: (1) Revise the algorithms for the Fluorescence Line Height (FLH) and Chlorophyll Fluorescence Efficiency (CFE) products, especially the data quality flags; (2) Revise the MOCEAN validation plan; (3) Deploy and recover bio-optical instrumentation at the Hawaii Ocean Time-series (HOT) site as part of the Joint Global Ocean Flux Study (JGOFS); (4) Prepare for field work in the Antarctic Polar Frontal Zone as part of JGOFS; (5) Submit manuscript on bio-optical time scales as estimated from Lagrangian drifters; (6) Conduct chemostat experiments on fluorescence; (7) Interface with the Global Imager (GLI) science team; and (8) Continue development of advanced data system browser. We are responsible for the delivery of two at-launch products for AM-1: Fluorescence line height (FLH) and chlorophyll fluorescence efficiency (CFE). We also considered revising the input chlorophyll, which is used to determine the degree of binning. We have refined the quality flags for the Version 2 algorithms. We have acquired and installed a Silicon Graphics Origin 200. We are working with the University of Miami team to develop documentation that will describe how the MODIS ocean components are linked together.

Abbott, Mark R.↗

DOE OSTI2024

The Pixel Anomaly Detection Tool : a user-friendly GUI for classifying detector frames using machine-learning approaches

Data collection at X-ray free electron lasers has particular experimental challenges, such as continuous sample delivery or the use of novel ultrafast high-dynamic-range gain-switching X-ray detectors. This can result in a multitude of data artefacts, which can be detrimental to accurately determining structure-factor amplitudes for serial crystallography or single-particle imaging experiments. Here, a new data-classification tool is reported that offers a variety of machine-learning algorithms to sort data trained either on manual data sorting by the user or by profile fitting the intensity distribution on the detector based on the experiment. This is integrated into an easy-to-use graphical user interface, specifically designed to support the detectors, file formats and software available at most X-ray free electron laser facilities. The highly modular design makes the tool easily expandable to comply with other X-ray sources and detectors, and the supervised learning approach enables even the novice user to sort data containing unwanted artefacts or perform routine data-analysis tasks such as hit finding during an experiment, without needing to write code.

47 OTHER INSTRUMENTATION↗

DOE OSTI2018

Simulation and Experimental Studies of Illumination Effects on the Current Transport of Nitridated GaAs Schottky Diode

In this paper, we studied the electrical characteristic of Schottky diodes based on gold contact on nitridated GaAs substrates. The used (100) GaAs substrate is n-type with concentration of N{sub d} = 4.9 × 10{sup 15} cm{sup –3}. Nitridation process was performed using a N2 glow discharge source (GDS) creating N atomic species. A ultra-thin film with a thickness of 2.2 nm GaN is performed on GaAs surface. In order to study the electric characteristics under illumination, we use of a He–Ne laser of 1 mW power and 632.8 nm wavelength. The current–voltage (I–V) of the Au/GaN/GaAs structures was investigated at room temperature. The saturation current I{sub S}, the series resistance R{sub S} and the mean ideality factor n are, respectively, equal to 4.46 × 10{sup –07} A, 172 Ohm, 1.4 in the dark and to 5.64 × 10{sup –07} A, 148 Ohm, 1.21 under illumination. To analyze these results, a 1D-simulation code of forward and reverse current–voltage characteristics versus the critical parameters of a nitridated GaAs Schottky diode is implemented. The algorithm is based on the solution of the system composed by Poisson’s and continuities equations. In this calculation, we take into account the existence of the GaN layer and the localization of traps states in the perturbed interface. We have considered the W-shaped and U-shaped distribution of traps states in the band gap. The effects of the doping concentration of GaAs, the traps states density, light intensities and the work function of gold ϕ{sub m} are investigated. By fitting the experimental curve, we can deduce the values of the traps states and the exact value of the work function of gold, and consequently we validate the developed model.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

The ArborX Library: Version 2.0

This article provides an overview of the 2.0 release of the ArborX library, a performance portable geometric search library based on Kokkos. We describe the major changes in ArborX 2.0 including a new interface for the library to support a wider range of user problems, new search data structures (brute force and distributed), support for user functions to be executed on the results (callbacks), and an expanded set of the supported algorithms (ray tracing and clustering).

GPU↗

DOE OSTI2019

Extremum Seeking Library (ESL) v1.0

The software developed is a library for the Modelica language. The library includes different extremum seeking control algorithms and examples of possible usecases. It is also intended to export the models as so called Functional Mock-up Units, which are models supported by any kind of software which supports the Functional Mock-up Interface standard.

Mueller, Joscha↗

NASA NTRS1979

Radar image processing of real aperture SLAR data for the detection and identification of iceberg and ship targets

An iceberg detection and identification system consisting of a moderate resolution Side Looking Airborne Radar (SLAR) interfaced with a Radar Image Processor (RIP) based on a ROLM 1664 computer with a 32K core memory updatable to 64K is described. The system can be operated in high- or low-resolution sampling modes. Specifically designed algorithms are applied to digitized signal returns to provide automatic target detection and location, geometrically correct video image display and data recording. The real aperture Motorola AN/APS-94D SLAR operates in the X-band and is tunable between 9.10 and 9.40 GHz; its output power is 45 kW peak with a pulse repetition rate of 750 pulses per hour. Schematic diagrams of the system are provided, together with preliminary test data.

Marthaler, J. G.↗

NASA NTRS1988

Highly automated transmission-edge mapping

Instrumentation and software are described, which are used to determine maps of properties of materials based on optical transmission spectra. In addition to a Fourier transform spectrometer, the hardware includes an xy-stage containing a small stationary aperture and two computer controlled stepper motors for positioning the sample. This idea has been used for years but this implementation is highly automated compared to those previously described. All mapping has been in the 2-15 micron wavelength range but this is not an inherent limitation of the technique. In this spectral range, useful results may be obtained with apertures as small as 25 microns in diameter. The software is described including the algorithm for obtaining the cut-on wavelength from a semiconductor spectrum. Data from both transverse slices and longitudinal slabs of narrow bandgap alloy semiconductors are shown including composition maps for materials solidified with convex and concave growth interfaces.

Szofran, F. R.↗

NASA NTRS1992

Advanced techniques in reliability model representation and solution

The current tendency of flight control system designs is towards increased integration of applications and increased distribution of computational elements. The reliability analysis of such systems is difficult because subsystem interactions are increasingly interdependent. Researchers at NASA Langley Research Center have been working for several years to extend the capability of Markov modeling techniques to address these problems. This effort has been focused in the areas of increased model abstraction and increased computational capability. The reliability model generator (RMG) is a software tool that uses as input a graphical object-oriented block diagram of the system. RMG uses a failure-effects algorithm to produce the reliability model from the graphical description. The ASSURE software tool is a parallel processing program that uses the semi-Markov unreliability range evaluator (SURE) solution technique and the abstract semi-Markov specification interface to the SURE tool (ASSIST) modeling language. A failure modes-effects simulation is used by ASSURE. These tools were used to analyze a significant portion of a complex flight control system. The successful combination of the power of graphical representation, automated model generation, and parallel computation leads to the conclusion that distributed fault-tolerant system architectures can now be analyzed.

Palumbo, Daniel L.↗

NASA NTRS1992

Modal Test/Analysis Correlation of Space Station Structures Using Nonlinear Sensitivity

The modal correlation problem is formulated as a constrained optimization problem for validation of finite element models (FEM's). For large-scale structural applications, a pragmatic procedure for substructuring, model verification, and system integration is described to achieve effective modal correlation. The space station substructure FEM's are reduced using Lanczos vectors and integrated into a system FEM using Craig-Bampton component modal synthesis. The optimization code is interfaced with MSC/NASTRAN to solve the problem of modal test/analysis correlation; that is, the problem of validating FEM's for launch and on-orbit coupled loads analysis against experimentally observed frequencies and mode shapes. An iterative perturbation algorithm is derived and implemented to update nonlinear sensitivity (derivatives of eigenvalues and eigenvectors) during optimizer iterations, which reduced the number of finite element analyses.

Gupta, Viney K.↗

NASA NTRS1992

Modal test/analysis correlation of Space Station structures using nonlinear sensitivity

The modal correlation problem is formulated as a constrained optimization problem for validation of finite element models (FEM's). For large-scale structural applications, a pragmatic procedure for substructuring, model verification, and system integration is described to achieve effective modal correlations. The space station substructure FEM's are reduced using Lanczos vectors and integrated into a system FEM using Craig-Bampton component modal synthesis. The optimization code is interfaced with MSC/NASTRAN to solve the problem of modal test/analysis correlation; that is, the problem of validating FEM's for launch and on-orbit coupled loads analysis against experimentally observed frequencies and mode shapes. An iterative perturbation algorithm is derived and implemented to update nonlinear sensitivity (derivatives of eigenvalues and eigenvectors) during optimizer iterations, which reduced the number of finite element analyses.

Gupta, Viney K.↗

NASA NTRS2012

VESGEN Software for Mapping and Quantification of Vascular Regulators

VESsel GENeration (VESGEN) Analysis is an automated software that maps and quantifies effects of vascular regulators on vascular morphology by analyzing important vessel parameters. Quantification parameters include vessel diameter, length, branch points, density, and fractal dimension. For vascular trees, measurements are reported as dependent functions of vessel branching generation. VESGEN maps and quantifies vascular morphological events according to fractal-based vascular branching generation. It also relies on careful imaging of branching and networked vascular form. It was developed as a plug-in for ImageJ (National Institutes of Health, USA). VESGEN uses image-processing concepts of 8-neighbor pixel connectivity, skeleton, and distance map to analyze 2D, black-and-white (binary) images of vascular trees, networks, and tree-network composites. VESGEN maps typically 5 to 12 (or more) generations of vascular branching, starting from a single parent vessel. These generations are tracked and measured for critical vascular parameters that include vessel diameter, length, density and number, and tortuosity per branching generation. The effects of vascular therapeutics and regulators on vascular morphology and branching tested in human clinical or laboratory animal experimental studies are quantified by comparing vascular parameters with control groups. VESGEN provides a user interface to both guide and allow control over the users vascular analysis process. An option is provided to select a morphological tissue type of vascular trees, network or tree-network composites, which determines the general collections of algorithms, intermediate images, and output images and measurements that will be produced.

Parsons-Wingerter, Patricia A.↗

NASA NTRS2019

Simplifying NASA Earth Science Data and Information Access Through Natural Language Processing Based Data Analysis and Visualization

NASA Earth science data collected from satellites, model assimilation, airborne missions, and field campaigns, are large, complex and evolving. Such characteristics pose great challenges for end users (e.g., Earth science and applied science users, students, citizen scientists), particularly for those who are unfamiliar with NASA's EOSDIS and thus unable to access and utilize datasets effectively. For example, a novice user may simply ask: what is the total rainfall for a flooding event in my county yesterday? For an experienced user (e.g., algorithm developer), a question can be: how did my rainfall product perform, compared to ground observations, during a flooding event? Nonetheless, with rapid information technology development such as natural language processing, it is possible to develop simplified Web interfaces and back-end processing components to handle such questions and deliver answers in terms of text, data, or graphic results directly to users.In this presentation, we describe the main challenges for end users with different levels of expertise in accessing and utilizing NASA Earth science data. Surveys reveal that most non-professional users normally do not want to download and handle raw data as well as conduct heavy-duty data processing tasks. Often they just want some simple graphics or data for various purposes. To them, simple and intuitive user interfaces are sufficient because complicated ones can be difficult and time-consuming to learn. Professionals also want such interfaces to answer many questions from datasets. One solution is to develop a natural language based search box like Google and the search results can be text, data, graphics and more. Now the challenge is, with natural language processing, can we design a system to process a scientific question typed in by a user? In this presentation, we describe our plan for such a prototype. The workflow is: 1) extract needed information (e.g., variables, spatial and temporal information, processing methods, etc.) from the input, 2) process the data in the backend, and 3) deliver the results (data or graphics) to the user.

Liu, Zhong↗

DOE OSTI2021

TEQUILA: a platform for rapid development of quantum algorithms

Variational quantum algorithms are currently the most promising class of algorithms for deployment on near-term quantum computers. In contrast to classical algorithms, there are almost no standardized methods in quantum algorithmic development yet, and the field continues to evolve rapidly. As in classical computing, heuristics play a crucial role in the development of new quantum algorithms, resulting in a high demand for flexible and reliable ways to implement, test, and share new ideas. In this paper, inspired by this demand, we introduce TEQUILA, a development package for quantum algorithms in PYTHON, designed for fast and flexible implementation, prototyping and deployment of novel quantum algorithms in electronic structure and other fields. TEQUILA operates with abstract expectation values which can be combined, transformed, differentiated, and optimized. On evaluation, the abstract data structures are compiled to run on state of the art quantum simulators or interfaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Reinforcement Learning for Intentional Islanding in Resilient Power Transmission Systems

Intentional islanding is the process of identifying and deliberately decomposing the transmission network to form self-sustained islands from an endangered network during disruptions to improve resilience and security. Most existing intentional islanding models are offline resilience decision tools and hence do not provide outage responses in a timely manner. In this paper, a reinforcement learning (RL) based model for intentional islanding is developed, which offers real-time switching control, online deployability, and adaptability to varying system conditions. The intentional islanding process is formulated as a Markov decision process, where the optimal transmission switching policy is learned using the RL approach. The control policy is learned over an environment that encompasses a Power System Simulator for Engineering (PSS/E) model of the transmission network, facilitated by an interface to the standard openAI Gym framework. The proposed RL-based methodology aims to form stable and self-sustainable islands by ensuring voltage stability while reducing the power mismatch in the formed islands. A proximal policy optimization algorithm is designed, which is suitable for controlling the on/off status of the switches with multi-layer perceptron as value and actor networks. The effectiveness of the proposed framework in the self-recovery of the grid by island formation is applied on the modified IEEE 39-bus test network and validated by dynamic simulations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Neuromorphic ionic computing in droplet interface synapses

Ionic devices with memory capabilities can emulate neural functionality, enabling neuromorphic computing and biomedical applications. In this study, we report an ionic spiking synapse based on aqueous droplet interface bilayer assembly. Under stepwise triangular voltages, the device displays coupled memcapacitive-memristive behavior, showing noncrossing pinched hysteretic I-V loops. This hysteretic ion dynamics can be regulated by modifying bilayer components, reconstituting protein channels, or adjusting droplet assembly configuration. Droplet interface synapses (DIS) exhibit fundamental neuromorphic behaviors such as paired-pulse facilitation/depression, spike rate–dependent plasticity, Hebbian learning, and short-term associative learning under classical conditioning. We also used reservoir computing with DIS to implement two learning algorithms: a classification algorithm that recognizes handwritten digits and a reinforcement learning algorithm that learns to play a board game of tic-tac-toe.

Li, Zhongwu [Lawrence Livermore National Laborator↗