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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 1,729 records · Page 96
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Algorithm for in-flight gyroscope calibration

An optimal algorithm for the in-flight calibration of spacecraft gyroscope systems is presented. Special consideration is given to the selection of the loss function weight matrix in situations in which the spacecraft attitude sensors provide significantly more accurate information in pitch and yaw than in roll, such as will be the case in the Hubble Space Telescope mission. The results of numerical tests that verify the accuracy of the algorithm are discussed.

Davenport, P. B.↗
NASA NTRS1993

MeV Gamma Ray Detection Algorithms for Stacked Silicon Detectors

By making use of the signature of a gamma ray event as it appears in N = 5 to 20 lithium-drifted silicon detectors and applying smart selection algorithms, gamma rays in the energy range of 1 to 8 MeV can be detected with good efficiency and selectivity. Examples of the types of algorithms used for different energy regions include the simple sum mode, the sum-coincidence mode used in segmented detectors, unique variations on sum-coincidence for an N-dimensional vector event, and a new and extremely useful mode for double escape peak spectroscopy at pair-production energies. The latter algorithm yields a spectrum similar to that of the pair spectrometer, but without the need of the dual external segments for double escape coincidence, and without the large loss in efficiency of double escape events. Background events due to Compton scattering are largely suppressed. Monte Carlo calculations were used to model the gamma ray interactions in the silicon, in order to enable testing of a wide array of different algorithms on the event N-vectors for a large-N stack.

McMurray, Robert E. Jr.↗
NASA NTRS1983

An algorithm for the empirical optimization of antenna arrays

A numerical technique is presented to optimize the performance of arbitrary antenna arrays under realistic conditions. An experimental-computational algorithm is formulated in which n-dimensional minimization methods are applied to measured data obtained from the antenna array. A numerical update formula is used to induce partial derivative information without requiring special perturbations of the array parameters. The algorithm provides a new design for the antenna array, and the method proceeds in an iterative fashion. Test case results are presented showing the effectiveness of the algorithm.

Blank, S.↗
NASA NTRS2023

On-Board Deployment Event Verification for GOES-R Spacecraft

As is common with many spacecraft designs, the GOES-R vehicles require a series of deployment events to transition from the launch configuration to the operational configuration. Rather than implementing additional sensors to verify various deployments, the GOES-R program developed an alternate approach that uses existing gyro rate sensing. The approach includes two pieces: the first is a new onboard shock detection capability to confirm initiation of individual deployment events, and the second is a ground-based dynamics verification step to confirm completion of deployment events. We first present the algorithm that detects shock events for various deployment devices along with the parameter tuning performed during ground tests. We then show inflight performance of the shock detection algorithm. While shock detection is useful for observing initiation of deployment events, completion of some deployment events cannot be determined by shock detection alone. For these events, such as solar panel latch-up and deployable boom extension, the program developed dynamics models for the deployment transient responses. High-rate gyro data were recorded for these events, which allow the ground team to verify that the appendages were fully deployed. We show the predictive models for these events and corresponding flight results.

GeoXO↗
DOE OSTI2018

Optimization of stepwise clustering algorithm in backward trajectory analysis

In recent years, the backward trajectory model has been widely used in the research of meteorological and atmospheric environmental quality. This paper presents a comprehensive study on a stepwise clustering analysis algorithm in the clustering process of backward trajectory model and an application of the clustering analysis of single-particle backward trajectory in 2016 in Changchun City. This study starts with an analysis of the original stepwise clustering algorithm and its application to a clustering process of 8784 backward trajectories during 48 h in Changchun City as a benchmark test case. Then, two improvements are made in the algorithm: First, in the process of finding the optimal classification, the algorithm complexity is improved from original O(n 3 ) to O(log(n)*n 2 ) through algorithm improvement. The algorithm performance is enhanced by log(n) times. Next, in the process of re-establishing the classification, the algorithm complexity is improved from the original O(m*n 2 ) to O(m*log(n)*n), that is another algorithm performance improvement by a factor of log(n). Therefore, the accumulative execution efficiency improvement through the algorithm optimization is 2*log(n) times, which has been further verified in the practical application in Changchun City.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Active meta-learning for predicting and selecting perovskite crystallization experiments

Autonomous experimentation systems use algorithms and data from prior experiments to select and perform new experiments in order to meet a specified objective. In most experimental chemistry situations, there is a limited set of prior historical data available, and acquiring new data may be expensive and time consuming, which places constraints on machine learning methods. Active learning methods prioritize new experiment selection by using machine learning model uncertainty and predicted outcomes. Meta-learning methods attempt to construct models that can learn quickly with a limited set of data for a new task. Here in this paper, we applied the model-agnostic meta-learning (MAML) model and the Probabilistic LATent model for Incorporating Priors and Uncertainty in few-Shot learning (PLATIPUS) approach, which extends MAML to active learning, to the problem of halide perovskite growth by inverse temperature crystallization. Using a dataset of 1870 reactions conducted using 19 different organoammonium lead iodide systems, we determined the optimal strategies for incorporating historical data into active and meta-learning models to predict reaction compositions that result in crystals. We then evaluated the best three algorithms (PLATIPUS and active-learning k-nearest neighbor and decision tree algorithms) with four new chemical systems in experimental laboratory tests. With a fixed budget of 20 experiments, PLATIPUS makes superior predictions of reaction outcomes compared to other active-learning algorithms and a random baseline.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Testing redMaPPer centring probabilities using galaxy clustering and galaxy–galaxy lensing

Here, galaxy cluster centring is a key issue for precision cosmology studies using galaxy surveys. Mis-identification of central galaxies causes systematics in various studies such as cluster lensing, satellite kinematics, and galaxy clustering. The red-sequence Matched-filter Probabilistic Percolation (redMaPPer) estimates the probability that each member galaxy is central from photometric information rather than specifying one central galaxy. The redMaPPer estimates can be used for calibrating the off-centring effect, however, the centring algorithm has not previously been well-tested. We test the centring probabilities of redMaPPer cluster catalogue using the projected cross-correlation between redMaPPer clusters with photometric red galaxies and galaxy–galaxy lensing. We focus on the subsample of redMaPPer clusters in which the redMaPPer central galaxies (RMCGs) are not the brightest member galaxies (BMEM) and both of them have spectroscopic redshift.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2002

On the Numerical Convergence to Steady State of Hypersonic Flows Over Bodies with Concavities

Two recent numerical studies of hypersonic flows over bodies with concavities revealed problems with convergence to a steady state with an oft-used application of local-time-stepping. Both simulated flows showed a time-like, periodic shedding of vortices in a subsonic domain bounded by supersonic external flow although the simulations, using local-time-stepping, were not time accurate. Simple modifications to the numerical algorithm were implemented to enable implicit, first-order accurate in time simulations. Subsequent time-accurate simulations of the two test problems converged to a steady state. The baseline algorithm and modifications for temporal accuracy are described. The requirement for sub-iterations to achieve convergence is demonstrated. Failure to achieve convergence without time accuracy is conjectured to arise from temporal errors being continuously refocused into a subsonic domain.

Gnoffo, Peter A.↗
NASA NTRS2020

Characterization and Commissioning of a Ka-Band Ground Station for Cognitive Algorithm Development

In 2018, the Cognitive Communications and Propagation projects completed installation and checkout testing of a new Ka-Band ground station at the NASA Glenn Research Center in Cleveland, Ohio. The Cognitive Algorithms Demonstration Testbed (CADeT) was developed to provide a fully characterized and controllable dynamic link environment to researchers looking to demonstrate hardware and software aligned with atmospheric sensing and cognitive algorithms. CADeT integrates a host of precision control and measurement systems in addition to repurposing a 5.5 meter beam-waveguide dish platform previously used with the Advanced Communications Technology Satellite (ACTS). This paper will discuss the laboratory testing of ground station components with a emphasis on elements vital to achieving link budget requirements including characterization of the new Gallium Nitride (GaN) Solid State Power Amplifier (SSPA) and far-field measurements of the new antenna feed. Finally, the paper discusses in-situ tests conducted with CADeT and the Tracking and Data Relay Satellite System (TDRSS) to validate laboratory results and make necessary link budget adjustments before reviewing the lessons learned.

Cameron M Seidl↗
NASA NTRS1982

Development of flying qualities criteria for single pilot instrument flight operations

Flying qualities criteria for Single Pilot Instrument Flight Rule (SPIFR) operations were investigated. The ARA aircraft was modified and adapted for SPIFR operations. Aircraft configurations to be flight-tested were chosen and matched on the ARA in-flight simulator, implementing modern control theory algorithms. Mission planning and experimental matrix design were completed. Microprocessor software for the onboard data acquisition system was debugged and flight-tested. Flight-path reconstruction procedure and the associated FORTRAN program were developed. Algorithms associated with the statistical analysis of flight test results and the SPIFR flying qualities criteria deduction are discussed.

Bar-Gill, A.↗
DOE OSTI2021

Real-Time Lossless Compression for Ultra-High-Density Synchrophasor and Point on Wave Data

Modern advanced Phasor Measurement Units (PMUs) are developed with ultra-high reporting rates to meet the demand for monitoring the power systems dynamics in detail. Due to the large volume of data, the communication and storage systems are seriously challenged with the presence of Ultra-High-Density (UHD) synchrophasor and Point on Wave (POW) data. Therefore, it is an urgent task to compress the UHD data for more efficient communication and data storage. This paper proposes several methods to compress the synchrophasor and POW data in a lossless manner. First, an Improved-Time-Series-Special Compression (ITSSC) method is proposed to compress the UHD frequency data. Second, a Delta-difference Huffman method is combined with the TSSC algorithm to compress the UHD phase angle data. Finally, a cyclical high-order delta modulation method is proposed to compress the UHD POW data. The proposed models are extensively tested and compared with different existing lossless compression algorithms using the field-collected synchrophasor and POW data at different reporting rates. The results indicate that the proposed algorithms are efficient in performing lossless compression for the UHD synchrophasor and POW data in real time.

42 ENGINEERING↗
DOE OSTI2021

Retro-Commissioning Sensor Suitcase for Energy Efficiency

This project will enable Pacific Northwest National Laboratory (PNNL) and Lawrence Berkeley National Laboratory (LBNL) to work with industry partner, GreenPath Energy Solutions, joint developers of the Suitcase, to enhance the capabilities and usability of the Retro-Commissioning Sensor Suitcase (hereinafter the Sensor Suitcase or Suitcase), assisting GreenPath to take the Suitcase to market and rapidly expand their market share. The proposed project will specifically focus on 1) adding sensors types to extend the data collection capability and support more building and equipment performance metrics and identification of even more energy saving opportunities, 2) developing algorithms to identify recommendations for the new energy savings opportunities from item 1 and to prototype software modifications implementing them, 3) validating the use of vibration sensors to detect the operating state of a broader set of packaged HVAC equipment (additional capacities, different numbers of stages, etc.) than tested in initial development and modifying the state algorithm and software code, as needed, 4) improving cost-effectiveness in manufacturing the Sensor Suitcase, and 5) additional field testing of the technology in real buildings to more comprehensively validate Suitcase performance and to guide refinement of its capabilities. Project results will position GreenPath, and potential future licensees, to implement the new capabilities developed in this project in GreenPath’s RCx Building Suitcase, increasing its functionality and the savings resulting from its use. These enhancements will increase the value of the Suitcase to users and increase the potential market for its use and impacts in that impact.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1990

Constructing second-order structural models with specified mass submatrix condition numbers

This paper presents a simple new algorithm for constructing second-order models for any given flexible structure, with these models satisfying the constraint that each leading principal submatrix of the mass matrix must have a specified condition number. Now, the effects of rounding errors in practical computation generally increase with increasing condition number, i.e. as the matrix considered approaches singularity. Thus, the new models should prove useful for the systematic testing of the numerical properties of many algorithms in the dynamics and control of flexible structures.

Williams, T.↗
NASA NTRS2015

Flight Testing of Guidance, Navigation and Control Systems on the Mighty Eagle Robotic Lander Testbed

During 2011 a series of progressively more challenging flight tests of the Mighty Eagle autonomous terrestrial lander testbed were conducted primarily to validate the GNC system for a proposed lunar lander. With the successful completion of this GNC validation objective the opportunity existed to utilize the Mighty Eagle as a flying testbed for a variety of technologies. In 2012 an Autonomous Rendezvous and Capture (AR&C) algorithm was implemented in flight software and demonstrated in a series of flight tests. In 2012 a hazard avoidance system was developed and flight tested on the Mighty Eagle. Additionally, GNC algorithms from Moon Express and a MEMs IMU were tested in 2012. All of the testing described herein was above and beyond the original charter for the Mighty Eagle. In addition to being an excellent testbed for a wide variety of systems the Mighty Eagle also provided a great learning opportunity for many engineers and technicians to work a flight program.

Hannan, Mike↗
DOE OSTI2020

Multidimensional Tests of a Finite-Volume Solver for MHD With a Real-Gas Equation of State

This work considers two algorithms of a finite-volume solver for the MHD equations with a real-gas equation of state (EOS). Both algorithms use a multistate form of Harten-Lax-Van Leer approximate Riemann solver as formulated for MHD discontinuities. This solver is modified to use the generalized sound speed from the real-gas EOS. Two methods are tested: EOS evaluation at cell centers and at flux interfaces where the former is more computationally efficient. A battery of 1D and 2D tests are employed: convergence of 1D and 2D linearized waves, shock tube Riemann problems, a 2D nonlinear circularly polarized Alfvén wave, and a 2D magneto-Rayleigh-Taylor instability test. The cell-centered EOS evaluation algorithm produces unresolvable thermodynamic inconsistencies in the intermediate states leading to spurious solutions while the flux-interface EOS evaluation algorithm robustly produces the correct solution. The linearized wave tests show this inconsistency is associated with the magnetosonic waves and the magneto-Rayleigh-Taylor instability test demonstrates simulation findings where the spurious solution leads to an unphysical simulation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Total variation-based neutron computed tomography

We perform the neutron computed tomography reconstruction problem via an inverse problem formulation with a total variation penalty. In the case of highly under-resolved angular measurements, the total variation penalty suppresses high-frequency artifacts which appear in filtered back projections. Here, in order to efficiently compute solutions for this problem, we implement a variation of the split Bregman algorithm; due to the error-forgetting nature of the algorithm, the computational cost of updating can be significantly reduced via very inexact approximate linear solvers. We present the effectiveness of the algorithm in the significantly low-angular sampling case using synthetic test problems as well as data obtained from a high flux neutron source. Finally, the algorithm removes artifacts and can even roughly capture small features when an extremely low number of angles are used.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2009

Lossless Astronomical Image Compression and the Effects of Random Noise

In this paper we compare a variety of modern image compression methods on a large sample of astronomical images. We begin by demonstrating from first principles how the amount of noise in the image pixel values sets a theoretical upper limit on the lossless compression ratio of the image. We derive simple procedures for measuring the amount of noise in an image and for quantitatively predicting how much compression will be possible. We then compare the traditional technique of using the GZIP utility to externally compress the image, with a newer technique of dividing the image into tiles, and then compressing and storing each tile in a FITS binary table structure. This tiled-image compression technique offers a choice of other compression algorithms besides GZIP, some of which are much better suited to compressing astronomical images. Our tests on a large sample of images show that the Rice algorithm provides the best combination of speed and compression efficiency. In particular, Rice typically produces 1.5 times greater compression and provides much faster compression speed than GZIP. Floating point images generally contain too much noise to be effectively compressed with any lossless algorithm. We have developed a compression technique which discards some of the useless noise bits by quantizing the pixel values as scaled integers. The integer images can then be compressed by a factor of 4 or more. Our image compression and uncompression utilities (called fpack and funpack) that were used in this study are publicly available from the HEASARC web site.Users may run these stand-alone programs to compress and uncompress their own images.

Pence, William↗
DOE OSTI2020

Simulating the Autonomous Future: A Look at Virtual Vehicle Environments and How to Validate Simulation Using Public Data Sets

The rapid evolution of autonomous vehicles (AVs) has exposed the need for fast-paced development and testing processes of a variety of perception, planning, and control algorithms. To expedite development, the AV industry and researchers leverage virtual vehicle environments to simulate a range of test scenarios that may otherwise be costly or difficult to conduct on a real test track. However, the various virtual environments may have different results depending on the fidelity of various simulation features, such as vehicle dynamics, sensor simulation, and environment recreation. Herein, this tutorial article examines a proposed framework for constructing, parameterizing, and validating a virtual vehicle environment using an existing AV data set. First, an overview of several open source and commercially available simulation tools, including their associated workflows, for scene and scenario creation is presented. Next, various open AV data sets are examined to inform the data set selection for the validation framework. Then, an example workflow of recreating a real-world scene from the selected data set in a simulation tool with various emulated sensors parameterized to match the data set is demonstrated. Finally, an example AV-perception algorithm is subjected to data streams from virtual and real-world environments and suggested metrics for analyzing the results are discussed.

42 ENGINEERING↗