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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Computational Workbench for Multibody Dynamics

PyCraft is a computer program that provides an interactive, workbenchlike computing environment for developing and testing algorithms for multibody dynamics. Examples of multibody dynamic systems amenable to analysis with the help of PyCraft include land vehicles, spacecraft, robots, and molecular models. PyCraft is based on the Spatial-Operator- Algebra (SOA) formulation for multibody dynamics. The SOA operators enable construction of simple and compact representations of complex multibody dynamical equations. Within the Py-Craft computational workbench, users can, essentially, use the high-level SOA operator notation to represent the variety of dynamical quantities and algorithms and to perform computations interactively. PyCraft provides a Python-language interface to underlying C++ code. Working with SOA concepts, a user can create and manipulate Python-level operator classes in order to implement and evaluate new dynamical quantities and algorithms. During use of PyCraft, virtually all SOA-based algorithms are available for computational experiments.

Edmonds, Karina↗
DOE OSTI2023

A framework for multirate time integration of interface-coupled problems

The research described here was performed as part of the DOE SciDAC project Coupling Approaches for Next Generation Architectures (CANGA). A framework was developed for the derivation of novel algorithms for the multirate time integration of two-component systems coupled across an interface between spatial domains. The multirate aspect means that different time steps are allowed by each component integrator. The framework provides a way to construct multirate integrators with desirable properties related to stability, accuracy and preservation of system invariants. This report describes the framework and summarizes the major results, examples and research products.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1991

Use of non-spherical gravity harmonics for relative motion GN/C (category 2)

Detailed analysis of the Automatic Rendezvous and Capture problem indicate a need for three different regions of mathematical description for the GN&C algorithms: (1) multi-vehicle orbital mechanics to the rendezvous interface point, i.e., within 100 nm; (2) relative motion solutions (such as Clohessy-Wiltshire type) from the far-field to the near-field interface, i.e., within 1 nm and; (3) close proximity motion - the near-field motion where the relative differences in the gravitational and orbit inertial accelerations can be neglected from the equations of motion. Limit boundaries to these regions can be precisely defined by further analysis and will be functions of the tracking measurement accuracies and the computer resources available for the solution of the algorithms. This paper analyzes the relative motion in Regions 2 and 3 above and present the derivation and discussion of the general case of non-spherical gravitational perturbed relative motion. Mathematical deviations from the numerically integrated spherical gravity case and solutions from the Clohessy-Wiltshire equations are presented in the analysis. Based upon this preliminary analysis, it is recommended that further efforts be used to assess the relative position and velocity differences in Region 2 due to non-spherical gravity harmonics and that viable GN&C algorithms be developed to include these gravity perturbations (especially the effects of the first gravity harmonic, J2).

Henderson, David M.↗
NASA NTRS2005

The Optimization of Trained and Untrained Image Classification Algorithms for Use on Large Spatial Datasets

The HARVIST project seeks to automatically provide an accurate, interactive interface to predict crop yield over the entire United States. In order to accomplish this goal, large images must be quickly and automatically classified by crop type. Current trained and untrained classification algorithms, while accurate, are highly inefficient when operating on large datasets. This project sought to develop new variants of two standard trained and untrained classification algorithms that are optimized to take advantage of the spatial nature of image data. The first algorithm, harvist-cluster, utilizes divide-and-conquer techniques to precluster an image in the hopes of increasing overall clustering speed. The second algorithm, harvistSVM, utilizes support vector machines (SVMs), a type of trained classifier. It seeks to increase classification speed by applying a "meta-SVM" to a quick (but inaccurate) SVM to approximate a slower, yet more accurate, SVM. Speedups were achieved by tuning the algorithm to quickly identify when the quick SVM was incorrect, and then reclassifying low-confidence pixels as necessary. Comparing the classification speeds of both algorithms to known baselines showed a slight speedup for large values of k (the number of clusters) for harvist-cluster, and a significant speedup for harvistSVM. Future work aims to automate the parameter tuning process required for harvistSVM, and further improve classification accuracy and speed. Additionally, this research will move documents created in Canvas into ArcGIS. The launch of the Mars Reconnaissance Orbiter (MRO) will provide a wealth of image data such as global maps of Martian weather and high resolution global images of Mars. The ability to store this new data in a georeferenced format will support future Mars missions by providing data for landing site selection and the search for water on Mars.

Kocurek, Michael J.↗
NASA NTRS2003

Multimodal neuroelectric interface development

We are developing electromyographic and electroencephalographic methods, which draw control signals for human-computer interfaces from the human nervous system. We have made progress in four areas: 1) real-time pattern recognition algorithms for decoding sequences of forearm muscle activity associated with control gestures; 2) signal-processing strategies for computer interfaces using electroencephalogram (EEG) signals; 3) a flexible computation framework for neuroelectric interface research; and d) noncontact sensors, which measure electromyogram or EEG signals without resistive contact to the body.

Evaluation Studies↗
NASA NTRS2008

G-Guidance Interface Design for Small Body Mission Simulation

The G-Guidance software implements a guidance and control (G and C) algorithm for small-body, autonomous proximity operations, developed under the Small Body GN and C task at JPL. The software is written in Matlab and interfaces with G-OPT, a JPL-developed optimization package written in C that provides G-Guidance with guaranteed convergence to a solution in a finite computation time with a prescribed accuracy. The resulting program is computationally efficient and is a prototype of an onboard, real-time algorithm for autonomous guidance and control. Two thruster firing schemes are available in G-Guidance, allowing tailoring of the software for specific mission maneuvers. For example, descent, landing, or rendezvous benefit from a thruster firing at the maneuver termination to mitigate velocity errors. Conversely, ascent or separation maneuvers benefit from an immediate firing to avoid potential drift toward a second body. The guidance portion of this software explicitly enforces user-defined control constraints and thruster silence times while minimizing total fuel usage. This program is currently specialized to small-body proximity operations, but the underlying method can be generalized to other applications.

Acikmese, Behcet↗
DOE OSTI2025

Comparison of Sequence Component-Based Fault Detection and Relay Coordination Algorithms in Inverter-Based Networks

Protection of inverter-based microgrids using sequence component-based relaying schemes is a promising solution. These methods offer several advantages, including lower computational requirements, compatibility with commercial relay systems, and cost-effectiveness compared to communication-based approaches. This article investigate the performance of various sequence component based schemes with the objective of identifying the algorithms that provide the best fault detection and relay coordination, solely relying on local voltages and current at relay terminals. Positive, negative and zero sequence impedance, admittance and power detection algorithms were tested on modified IEEE 13 bus test network for various shunt faults (LG, LL, LLG, LLL). Hardware-in-the-loop validation was achieved using the Typhoon real-time simulator, interfacing with a SEL 751 relay. This research demonstrates that while several algorithms are capable of detecting faults with sufficient accuracy, only a few are effective in achieving proper coordination. Validation results indicate that the negative sequence power approach provides the best performance in both fault detection and coordination.

Patel, Deepika [ORNL] (ORCID:0000000341099994)↗
DOE OSTI2021

Chapter 18: Learning and Tracking Ad Hoc Fiducial Markers in Spatial Augmented Reality

We describe a spatial augmented reality system with a tangible user interface used to control computer simulations of complex systems. In spatial augmented reality, the user’s physical space is augmented with projected imagery, blending real objects with projected information, and a tangible user interface enables users to manipulate physical objects as controllers for interactive visualizations. Our system learns ad hoc objects in the user’s environment as fiducial markers (i.e., objects that are visually recognized and tracked). When combined with simulation and visualization tools, these interfaces allow the user to control simulations or ensembles of simulations via physical objects using apt metaphors. While other research has leveraged the use of depth cameras, our system enables the use of standard cameras in readily available smartphones and webcams and has an implementation that runs completely in JavaScript in the web browser. We discuss the prerequisite object-recognition requirements for such tangible user interfaces and describe computer-vision and machine-learning algorithms meeting those requirements. We conclude by presenting example applications, which are also available online.

energy distribution↗
DOE OSTI2023

A publicly available PyTorch-$\mathrm{ABAQUS}$ $\mathrm{UMAT}$ deep-learning framework for level-set plasticity

Here this paper introduces a publicly available PyTorch-ABAQUS deep-learning framework of a family of plasticity models where the yield surface is implicitly represented by a scalar-valued function. In particular, our focus is to introduce a practical framework that can be deployed for engineering analysis that employs a user-defined material subroutine (UMAT/VUMAT) for ABAQUS, which is written in FORTRAN. To accomplish this task while leveraging the back-propagation learning algorithm to speed up the neural-network training, we introduce an interface code where the weights and biases of the trained neural networks obtained via the PyTorch library can be automatically converted into a generic FORTRAN code that can be a part of the UMAT/VUMAT algorithm. To enable third-party validation, we purposely make all the data sets, source code used to train the neural-network-based constitutive models, and the trained models available in a public repository. Furthermore, the practicality of the workflow is then further tested on a dataset for anisotropic yield function to showcase the extensibility of the proposed framework. A number of representative numerical experiments are used to examine the accuracy, robustness and reproducibility of the results generated by the neural network models.

36 MATERIALS SCIENCE↗
NASA NTRS1979

Low-level processing for real-time image analysis

A system that detects object outlines in television images in real time is described. A high-speed pipeline processor transforms the raw image into an edge map and a microprocessor, which is integrated into the system, clusters the edges, and represents them as chain codes. Image statistics, useful for higher level tasks such as pattern recognition, are computed by the microprocessor. Peak intensity and peak gradient values are extracted within a programmable window and are used for iris and focus control. The algorithms implemented in hardware and the pipeline processor architecture are described. The strategy for partitioning functions in the pipeline was chosen to make the implementation modular. The microprocessor interface allows flexible and adaptive control of the feature extraction process. The software algorithms for clustering edge segments, creating chain codes, and computing image statistics are also discussed. A strategy for real time image analysis that uses this system is given.

Eskenazi, R.↗
NASA NTRS2020

Entropy Stable h/p-Nonconforming Discretization with the Summation-by-Parts Property for the Compressible Euler and Navier–Stokes Equations

In this paper, we extend the entropy conservative/stable algorithms presented by Del Rey Fernandez and coauthors for the compressible Euler and Navier-Stokes equations on nonconforming p-refined/coarsened curvilinear grids to h/p refinement/coarsening. The main difficulty in developing nonconforming algorithms is the construction of appropriate coupling procedures across nonconforming interfaces. Here, we utilize a computationally simple and efficient approach based upon using decoupled interpolation operators. The resulting scheme is entropy conservative/stable and elementwise conservative. Numerical simulations of the isentropic vortex and viscous shock propagation con firm the entropy conservation/stability and accuracy properties of the method (achieving ~ p + 1 convergence), which are comparable to those of the original conforming scheme. Simulations of the Taylor{Green vortex at R(e) = 1,600 and turbulent flow past a sphere at R(e(infinity)) = 2,000 show the robustness and stability properties of the overall spatial discretization for unstructured grids. Finally, to demonstrate the entropy conservation property of a fully-discrete explicit entropy stable algorithm with h=p refinement/coarsening, we present the time evolution of the entropy function obtained by simulating the propagation of the isentropic vortex using a relaxation Runge-Kutta scheme.

Nonconforming interfaces↗
NASA NTRS1992

Analysis and applications of a general boresight algorithm for the DSS-13 beam waveguide antenna

A general antenna beam boresight algorithm is presented. Equations for axial pointing error, peak received signal level, and antenna half-power beamwidth are given. A pointing error variance equation is derived that illustrates the dependence of the measurement estimation performance on the various algorithm inputs, including RF signal level uncertainty. Plots showing pointing error uncertainty as function of algorithm inputs are presented. Insight gained from the performance analysis is discussed in terms of its application to the areas of antenna controller and receiver interfacing, pointing error compensation, and antenna calibrations. Current and planned applications of the boresight algorithm, including its role in the upcoming Ka-band downlink experiment (KABLE), are highlighted.

Alvarez, L. S.↗
DOE OSTI2019

Software Requirements Document: Benchmarking Algorithm for RadioNuclide Identification (BARNI)

This document provides the requirements for the Benchmark Algorithm for Radio-Nuclide Identification (BARNI) software, an open-source tool for comparing radionuclide identification algorithm performance. It specifies the requirements for the user interface, maintainability, documentation and testing. In addition, this document outlines the core functionality of the product, which will align with the needs of the Office of Nuclear Smuggling Detection and Deterrence (NSDD). Specifically, these include interoperability with RASE, and compatibility with the FLIR R400.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Preliminary Enhanced LAW Glass Formulation Algorithm

This report summarizes the Preliminary Enhanced Low-Activity Waste Glass Formulation Algorithm (GFA), its background information, and the calculations it performs. The Preliminary Enhanced Low-Activity Waste GFA is a tool developed in MATLAB to formulate glass for a given waste composition while attempting to maximize waste loading. It is intended for use at the Waste Treatment and Immobilization Plant, where nuclear waste will be vitrified into glass. The formulated glass is required to satisfy several processing and product quality constraints. In addition, calculations must account for associated uncertainties in constraint prediction and measurement. The GFA adheres to Pacific Northwest National Laboratory nuclear quality assurance procedures and has been validated and verified. In this second revision to the report, two constraints: the lithium and zirconia target constraints were amended to Table 3.1 and programmed into the algorithm. Additionally, three sections were added. Section 3.2.1 includes the Enhanced LAW Correlation Rules, an addition to the glass optimality criteria. Section 4.0 discusses a stepped process approach taken to ensure the algorithm can adequately react to differences between its recommended output and the actual measurements and transfers made during plant operation, and calculation of specific radionuclide concentrations. Section 5.2 describes changes to the user interaction with the algorithm program including the addition of a graphical user interface and compilation of the software.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Deep Learning for Fish Identification from Sonar Data (CRADA 481 Final Report)

In eastern regions of the United States, the American eel is a species of management and regulatory concern because of significant population declines, despite the species’ previous abundance in all tributaries of rivers flowing into the Atlantic Ocean. The American eel is also a candidate for listing under the U.S. Endangered Species Act. While hydropower construction and operation are only one of several factors contributing to this population decline, such a listing could impose additional regulatory challenges for a large number of hydropower projects. In this CRADA project, we improved technologies for identifying migrating eels with the goal of reducing the cost and time required for future American eel hydropower impact assessment and mitigation studies, while maintaining accuracy. We built on results from a previous FOA project (FOA# DE-FOA-0001662), led by the Electric Power Research Institute (EPRI), which developed a highly accurate, deep-learning method for identifying migrating eels from imaging sonar data. The current study aimed to further optimize this deep-learning model, originally designed for image classification, and to develop an object detection software capable of identifying fish from sonar videos in real time, enabling the detection of events like fish migrations and specific species, such as the American eel, at hydropower dams. The data conversion algorithms were packaged as software with a graphical user interface, and the software is evaluated by external collaborators. We focused on the American eel in this project and explored the transferability of the developed deep learning models to the sea lamprey, given the similar body shape and swimming behavior between the two species.

13 HYDRO ENERGY↗
DOE OSTI2025

OEDI—Solar Grid Integration Data and Analytics Library

As a part of the Open Energy Data Initiative, this effort aims to develop and demonstrate novel distribution state estimation, control optimization, and transient analysis as well as provide access to data, data integration, and mapping information. More specifically, the focus of the effort will be on physics-based distribution system state estimation, hybrid (physics-based and machine learning) distribution optimal power flow, and event detection/analysis for solar integration and analytics. This work will enable reproducible, robust, replicable, and generalizable R&D in simulation and emulation of solar system integration. These test models and datasets will provide an integrated library for developing and testing power system operation technologies. To make the library user-friendly, this project will provide data curation tools such as data translators, mapping scripts and APIs, database schemas and metadata, interfaces and user dashboard, source code for the reference algorithms, description of the use-cases/scenarios, and comprehensive information on all the assumptions.

14 SOLAR ENERGY↗
NASA NTRS1989

Investigation of the applicability of a functional programming model to fault-tolerant parallel processing for knowledge-based systems

In a fault-tolerant parallel computer, a functional programming model can facilitate distributed checkpointing, error recovery, load balancing, and graceful degradation. Such a model has been implemented on the Draper Fault-Tolerant Parallel Processor (FTPP). When used in conjunction with the FTPP's fault detection and masking capabilities, this implementation results in a graceful degradation of system performance after faults. Three graceful degradation algorithms have been implemented and are presented. A user interface has been implemented which requires minimal cognitive overhead by the application programmer, masking such complexities as the system's redundancy, distributed nature, variable complement of processing resources, load balancing, fault occurrence and recovery. This user interface is described and its use demonstrated. The applicability of the functional programming style to the Activation Framework, a paradigm for intelligent systems, is then briefly described.

Harper, Richard↗
NASA NTRS1990

Computer implementation of analysis and optimization procedures for control-structure interaction problems

Implementation aspects of control-structure interaction analysis and optimization by the staggered use of single-discipline analysis modules are discussed. The single-discipline modules include structural analysis, controller synthesis and optimization. The software modularity is maintained by employing a partitioned control-structure interaction analysis procedure, thus avoiding the need for embedding the single-discipline modules into a monolithic program. A software testbed has been constructed as a stand-alone analysis and optimization program and tested for its versatility and software modularity by applying it to the dynamic analysis and preliminary design of a prototype Earth Pointing Satellite. Experience with the in-core testbed program so far demonstrates that the testbed is efficient, preserves software modularity, and enables the analyst to choose a different set of algorithms, control strategies and design parameters via user software interfaces. Thus, the present software architecture is recommended for adoption by control-structure interaction analysts as a preliminary analysis and design tool.

Belvin, W. Keith↗