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At least 289 records · Page 16

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NASA NTRS2005

Java-based Graphical User Interface for MAVERIC-II

A computer program entitled "Marshall Aerospace Vehicle Representation in C II, (MAVERIC-II)" is a vehicle flight simulation program written primarily in the C programming language. It is written by James W. McCarter at NASA/Marshall Space Flight Center. The goal of the MAVERIC-II development effort is to provide a simulation tool that facilitates the rapid development of high-fidelity flight simulations for launch, orbital, and reentry vehicles of any user-defined configuration for all phases of flight. MAVERIC-II has been found invaluable in performing flight simulations for various Space Transportation Systems. The flexibility provided by MAVERIC-II has allowed several different launch vehicles, including the Saturn V, a Space Launch Initiative Two-Stage-to-Orbit concept and a Shuttle-derived launch vehicle, to be simulated during ascent and portions of on-orbit flight in an extremely efficient manner. It was found that MAVERIC-II provided the high fidelity vehicle and flight environment models as well as the program modularity to allow efficient integration, modification and testing of advanced guidance and control algorithms. In addition to serving as an analysis tool for techno logy development, many researchers have found MAVERIC-II to be an efficient, powerful analysis tool that evaluates guidance, navigation, and control designs, vehicle robustness, and requirements. MAVERIC-II is currently designed to execute in a UNIX environment. The input to the program is composed of three segments: 1) the vehicle models such as propulsion, aerodynamics, and guidance, navigation, and control 2) the environment models such as atmosphere and gravity, and 3) a simulation framework which is responsible for executing the vehicle and environment models and propagating the vehicle s states forward in time and handling user input/output. MAVERIC users prepare data files for the above models and run the simulation program. They can see the output on screen and/or store in files and examine the output data later. Users can also view the output stored in output files by calling a plotting program such as gnuplot. A typical scenario of the use of MAVERIC consists of three-steps; editing existing input data files, running MAVERIC, and plotting output results.

Seo, Suk Jai↗

NASA NTRS2006

Ion Thruster Discharge Performance Per Magnetic Field Topography

DC-ION is a detailed computational model for predicting the plasma characteristics of rain-cusp ion thrusters. The advanced magnetic field meshing algorithm used by DC-ION allows precise treatment of the secondary electron flow. This capability allows self-consistent estimates of plasma potential that improves the overall consistency of the results of the discharge model described in Reference [refJPC05mod1]. Plasma potential estimates allow the model to predict the onset of plasma instabilities, and important shortcoming of the previous model for optimizing the design of discharge chambers. A magnetic field mesh simplifies the plasma flow calculations, for both the ions and the secondary electrons, and significantly reduces numerical diffusion that can occur with meshes not aligned with the magnetic field. Comparing the results of this model to experimental data shows that the behavior of the primary electrons, and the precise manner of their confinement, dictates the fundamental efficiency of ring-cusp. This correlation is evident in simulations of the conventionally sized NSTAR thruster (30 cm diameter) and the miniature MiXI thruster (3 cm diameter).

plasma processes↗

NASA NTRS2006

PixelLearn

PixelLearn is an integrated user-interface computer program for classifying pixels in scientific images. Heretofore, training a machine-learning algorithm to classify pixels in images has been tedious and difficult. PixelLearn provides a graphical user interface that makes it faster and more intuitive, leading to more interactive exploration of image data sets. PixelLearn also provides image-enhancement controls to make it easier to see subtle details in images. PixelLearn opens images or sets of images in a variety of common scientific file formats and enables the user to interact with several supervised or unsupervised machine-learning pixel-classifying algorithms while the user continues to browse through the images. The machinelearning algorithms in PixelLearn use advanced clustering and classification methods that enable accuracy much higher than is achievable by most other software previously available for this purpose. PixelLearn is written in portable C++ and runs natively on computers running Linux, Windows, or Mac OS X.

Mazzoni, Dominic↗

NASA NTRS2012

Physics of Acoustic Radiation from Jet Engine Inlets

Numerical simulations of acoustic radiation from a jet engine inlet are performed using advanced computational aeroacoustics (CAA) algorithms and high-quality numerical boundary treatments. As a model of modern commercial jet engine inlets, the inlet geometry of the NASA Source Diagnostic Test (SDT) is used. Fan noise consists of tones and broadband sound. This investigation considers the radiation of tones associated with upstream propagating duct modes. The primary objective is to identify the dominant physical processes that determine the directivity of the radiated sound. Two such processes have been identified. They are acoustic diffraction and refraction. Diffraction is the natural tendency for an acoustic wave to follow a curved solid surface as it propagates. Refraction is the turning of the direction of propagation of sound waves by mean flow gradients. Parametric studies on the changes in the directivity of radiated sound due to variations in forward flight Mach number and duct mode frequency, azimuthal mode number, and radial mode number are carried out. It is found there is a significant difference in directivity for the radiation of the same duct mode from an engine inlet when operating in static condition and in forward flight. It will be shown that the large change in directivity is the result of the combined effects of diffraction and refraction.

Tam, Christopher K. W.↗

NASA NTRS2008

Addition of Electrostatic Forces to EDEM with Applications to Triboelectrically Charged Particles

Tribocharging of particles is common in many processes including fine powder handling and mixing, printer toner transport and dust extraction. In a lunar environment with its high vacuum and lack of water, electrostatic forces are an important factor to consider when designing and operating equipment. Dust mitigation and management is critical to safe and predictable performance of people and equipment. The extreme nature of lunar conditions makes it difficult and costly to carryout experiments on earth which are necessary to better understand how particles gather and transfer charge between each other and with equipment surfaces. DEM (Discrete Element Modeling) provides an excellent virtual laboratory for studying tribocharging of particles as well as for design of devices for dust mitigation and for other purposes related to handling and processing of lunar regolith. Theoretical and experimental work has been performed pursuant to incorporating screened Coulombic electrostatic forces into EDEM Tm, a commercial DEM software package. The DEM software is used to model the trajectories of large numbers of particles for industrial particulate handling and processing applications and can be coupled with other solvers and numerical models to calculate particle interaction with surrounding media and force fields. In this paper we will present overview of the theoretical calculations and experimental data and their comparison to the results of the DEM simulations. We will also discuss current plans to revise the DEM software with advanced electrodynamic and mechanical algorithms.

Hogue, Michael D.↗

NASA NTRS2013

NASA Tech Briefs, April 2013

Topics covered include: Fully Integrated, Miniature, High-Frequency Flow Probe Utilizing MEMS Leadless SOI Technology; Nanoscale Surface Plasmonics Sensor With Nanofluidic Control; Advanced Dispersed Fringe Sensing Algorithm for Coarse Phasing Segmented Mirror Telescopes; Neural Network Back-Propagation Algorithm for Sensing Hypergols; Bulk Moisture and Salinity Sensor; Change-Based Satellite Monitoring Using Broad Coverage and Targetable Sensing; Circularly Polarized Microwave Antenna Element with Very Low Off-Axis Cross-Polarization; Ultra-Low Heat-Leak, High-Temperature Superconducting Current Leads for Space Applications; Flash Cracking Reactor for Waste Plastic Processing; An Automated Safe-to-Mate (ASTM) Tester; Wireless Chalcogenide Nanoionic-Based Radio-Frequency Switch; Compute Element and Interface Box for the Hazard Detection System; DOT Transmit Module; Composite Aerogel Multifoil Protective Shielding; Li-Ion Electrolytes with Improved Safety and Tolerance to High-Voltage Systems; Polymer-Reinforced, Non-Brittle, Lightweight Cryogenic Insulation; Controlled, Site-Specific Functionalization of Carbon Nanotubes with Diazonium Salts; Regenerable Sorbent for CO2 Removal; Sprayable Aerogel Bead Compositions With High Shear Flow Resistance and High Thermal Insulation Value; Lexan Linear Shaped Charge Holder with Magnets and Backing Plate; Robotic Ankle for Omnidirectional Rock Anchors; Wind, Wave, and Tidal Energy Without Power Conditioning; An Active Heater Control Concept to Meet IXO Type Mirror Module Thermal-Structural Distortion Requirement; Waterless Clothes-Cleaning Machine; Integrated Electrical Wire Insulation Repair System; LVGEMS Time-of-Flight Mass Spectrometry on Satellites; Surface Inspection Tool for Optical Detection of Surface Defects; Per-Pixel, Dual-Counter Scheme for Optical Communications; Certification-Based Process Analysis; Surface Navigation Using Optimized Waypoints and Particle Swarm Optimization; Smart-Divert Powered Descent Guidance to Avoid the Backshell Landing Dispersion Ellipse; Estimating Foreign-Object-Debris Density from Photogrammetry Data; Adaptive Sampling of Spatiotemporal Phenomena with Optimization Criteria; Building a 2.5D Digital Elevation Model From 2D Imagery; Eyes on the Earth 3D; Target Trailing With Safe Navigation for Maritime Autonomous Surface Vehicles; Adams-Based Rover Terramechanics and Mobility Simulator - ARTEMIS; ISTP CDF Skeleton Editor; Uplink Summary Generator (ULSGEN) Version 1.0; Robotics On-Board Trainer (ROBoT); Software Engineering Tools for Scientific Models; Automatic Data Filter Customization Using a Genetic Algorithm; Tracker Toolkit; Towards Efficient Scientific Data Management Using Cloud Storage; On a Formal Tool for Reasoning About Flight Software Cost Analysis; A Nanostructured Composites Thermal Switch Controls Internal and External Short Circuit in Lithium Ion Batteries; Spacecraft Crew Cabin Condensation Control; and Functional Near-Infrared Spectroscopy Signals Measure Neuronal Activity in the Cortex.

Source record↗

NASA NTRS2016

Towards Autonomous Operations of the Robonaut 2 Humanoid Robotic Testbed

The Robonaut project has been conducting research in robotics technology on board the International Space Station (ISS) since 2012. Recently, the original upper body humanoid robot was upgraded by the addition of two climbing manipulators ("legs"), more capable processors, and new sensors, as shown in Figure 1. While Robonaut 2 (R2) has been working through checkout exercises on orbit following the upgrade, technology development on the ground has continued to advance. Through the Active Reduced Gravity Offload System (ARGOS), the Robonaut team has been able to develop technologies that will enable full operation of the robotic testbed on orbit using similar robots located at the Johnson Space Center. Once these technologies have been vetted in this way, they will be implemented and tested on the R2 unit on board the ISS. The goal of this work is to create a fully-featured robotics research platform on board the ISS to increase the technology readiness level of technologies that will aid in future exploration missions. Technology development has thus far followed two main paths, autonomous climbing and efficient tool manipulation. Central to both technologies has been the incorporation of a human robotic interaction paradigm that involves the visualization of sensory and pre-planned command data with models of the robot and its environment. Figure 2 shows screenshots of these interactive tools, built in rviz, that are used to develop and implement these technologies on R2. Robonaut 2 is designed to move along the handrails and seat track around the US lab inside the ISS. This is difficult for many reasons, namely the environment is cluttered and constrained, the robot has many degrees of freedom (DOF) it can utilize for climbing, and remote commanding for precision tasks such as grasping handrails is time-consuming and difficult. Because of this, it is important to develop the technologies needed to allow the robot to reach operator-specified positions as autonomously as possible. The most important progress in this area has been the work towards efficient path planning for high DOF, highly constrained systems. Other advances include machine vision algorithms for localizing and automatically docking with handrails, the ability of the operator to place obstacles in the robot's virtual environment, autonomous obstacle avoidance techniques, and constraint management.

Badger, Julia↗

NASA NTRS2016

Lenslet Array to Further Suppress Star Light for Direct Exoplanet Detection

Direct imaging plays a key role in the detection and characterization of exoplanets orbiting within its host star's habitable zone. Many innovative ideas for starlight suppression and wavefront control have been proposed and developed over the past decade. However, several technological challenges still lie ahead to achieve the required contrast, including controlling the observatory pointing performance, fabricating occulting masks with tight optical tolerances, developing wavefront control algorithms, controlling stray light, advancing single photon detecting detectors, and integrated system-level issues. This paper explores how a lenslet array and pinhole mask may be implemented to further suppress uncorrected starlight that leaks through the occulting mask. An external occulter, or star shade, is simulated to demonstrate this concept, although this approach can be implemented for internal coronagraphs as well. We describe how to use simple relay optics to control the scene near the inner working angle and the level of the suppression expected. Furthermore, if the lenslet array is the input to an integral field spectrograph, as planned for the WFIRST mission, the spectral content of the exoplanet atmospheres can be obtained to determine if the observed planet is habitable and ultimately, if it is inhabited.

Integral Field spectrograph↗

NASA NTRS2018

Advanced Symbolic Analysis Tools for Fault-Tolerant Integrated Distributed Systems

The project aims to develop advanced model-checking algorithms and tools to automate the verification of fault-tolerant distributed systems for avionics. We present a new method called Property-Directed K-Induction (PD-KIND) for synthesizing K-inductive invariants of state-transition systems. PD-KIND builds upon Satifiability Modulo Theories (SMT) to generalize Bradley's IC3 method and its variants. This method is implemented in a new tool called SALLY. Case studies show that PD-KIND can automatically verify fault-tolerant algorithms under a variety of fault models and that SALLY is competitive with other SMT-based model checkers.

Dutertre, Bruno↗

NASA NTRS2018

A Comprehensive Model of Earth's Magnetic Field Determined from 4 Years of Swarm Satellite Observations

The European Space Agency's three-satellite constellation Swarm, launched in November 2013, has provided unprecedented monitoring of Earth's magnetic field via a unique set of gradiometric and multi-satellite measurements from low Earth orbit. In order to exploit these measurements, an advanced "Comprehensive Inversion" (CI) algorithm has been developed to optimally separate the various major magnetic field sources in the near-Earth regime. The CI algorithm is used to determine Swarm Level-2 (L2) magnetic field data products that include the core, lithospheric, ionospheric, magnetospheric, and associated induced sources. In addition, it has become apparent that the CI is capable of extracting the magnetic signal associated with the oceanic principal lunar semi-diurnal tidal constituent M(sub 2) to such an extent that it has been added to the L2 data product line. This paper presents the parent model of the Swarm L2 CI products derived with measurements from the first four years of the Swarm mission and from ground observatories, denoted as "CIY4", including the new product describing the magnetic signal of the M(sub 2) oceanic tide.

Swarm Satellites↗

NASA NTRS2016

Time Series Explorer: Bayesian Blocks with Generalized Profiles and in Higher Dimensions

The Time Series Explorer (TSE) is a project aimed at provided new and advanced time series analysis algorithms in two forms: a tool kit and an automated pipeline applying selected tools in machine learning settings. I will present a sketch of TSE with emphasis on time-domain modeling in general and recent improvements of the Bayesian Block (BB) algorithm in particular. This includes generalizing the shape of the elementary blocks from the current constant-rate model to general shapes, such as two-sided exponentials. Related topics will include extension of BB to higher dimensions and a novel way to detect and characterize short time-scale bursts in time-tagged event data. The Fermi Gamma Ray Space Telescope light curve for the Crab Nebula will be used as an example for all of the algorithms discussed. This work is in collaboration with Tom Loredo.

Bayesian Block (BB) algorithm↗

NASA NTRS2019

Advanced Electronics for the SONTRAC Neutron Spectrometer

Solar neutrons are the tell-tale of highly energetic processes (e.g. solar flares) at the Sun in which particle acceleration is taking place over a broad range in energy. Unlike charged radiation, neutrons escape unscathed from the ambient magnetic fields, providing a view of particle acceleration unhindered by the effects of transport. High-energy neutrons are challenging to measure with the traditional double scatter technique based on time-of-flight (ToF). This technique is limited by the finite flight path and active scintillator sizes required by small satellite platforms. The new SOlar Neutron TRACking (SONTRAC) concept, based on scintillating-fiber bundles, will provide high resolution imaging of fast neutrons at energies where the bulk of solar and magnetospheric neutrons resides. Recent development of the new SONTRAC instrument concept's advanced electronics and processing algorithms are presented.

SiPM readout↗

NASA NTRSDate not supplied

A Flexible Multibody Approach to Space Launch System Liftoff Pad Separation with Umbilical Disconnect

A flexible multibody dynamic framework is applied to the Space Launch System (SLS) liftoff Coupled Loads Analysis (CLA), enabling computational efficiencies and systematic inclusion of components and various nonlinearities. The objective of this work is to simulate the SLS liftoff transient pad separation event inclusive of umbilical disconnects. The vehicle stacking preloads and cryogenically induced preloads, due to the fueling of the Core Stage (CS), are integrated via specialized deformed coupling procedure to ensure full capture of the liftoff transient event. The Vehicle Stabilizer System (VSS) hydraulic struts are nonlinear and provide amplitude dependent damping, significantly contributing to the liftoff transient event. Ground Extensible Columns (EC) provide additional stiffness and preloads on the Mobile Launcher (ML), also significantly contributing to the liftoff transient. An advanced Henkel-Mar algorithm, with separation and re-contact, thus tracking the potential post separation re-contact between the booster aft skirt and ML, the umbilicals and vehicle, and ground EC separation. For this system level nonlinear dynamic simulation, the flexible multibody framework provides a systematic approach for the addition of component specific algorithms to enforce nonlinearities. This multibody framework is similar to an object-oriented programming language integrating classes of associated subroutines. As such, the complexities associated with the nonlinear CLA are greatly reduced, facilitating simplified bookkeeping as well as accelerating the execution of the nonlinear time-domain simulations.

Joel W Sills Jr.↗

NASA NTRS1996

Scalable Solutions to Integral Equation and Finite Element Simulations

The application of advanced computer architecture and software to a broad range of electromagnetic problems had allowed more accurate simulations of electrically larger and more complex components and systems...This paper overviews solutions to Maxwell's equations implicitly defined through systems of linear equations.

parallel↗

NASA NTRSDate not supplied

Quantum-Compatible Variational Segmentation for Image-to-Image Wildfire Detection Using Satellite Data

Wildfire occurrences have been increasing for the past decade, leaving devastating traces across the world. In the recent efforts, remote sensing and airborne missions have been utilized to better understand and manage wildfires. This has resulted in an exponential increase in volume of remote sensing data, which has pushed the need for intelligent automation of data extraction for wildfire studies. Machine learning offers accurate automation in detecting such natural anomalies and enable decision-makers to take actions in a timely manner. Recent advances in machine learning algorithms, namely probabilistic generative methods, allow researchers and decisionmakers to step beyond detection and study “what-if” scenarios for wildfire occurrences. Additionally, they offer better imitations to the stochastic behavior of nature, and wildfire events. However, optimizing the performance of these probabilistic generative models is a computationally expensive process, specially using digital computers. On the other hand, quantum computers have recently shown a promise to reduce computationally costly training of such models and provide performance improvements. There is a body of research investigating the potential for improved machine learning methods in which key operations are performed on a quantum computer. In this study, we propose a probabilistic image-toimage segmentation approach combining a very well-known segmentation method, U-NET, with a Conditional Variational Auto-Encoder (CVAE) to not only detect wildfires but also describe the stochasticity of the phenomenon and be capable of running “what-if” scenarios. Our proposed model is compatible with training on quantum computers, which results in a quantum-assisted image-to-image segmentation approach and can be used to benchmark the potential benefit of quantum computing over the classical one.

quantum↗

NASA NTRS1988

Computer sciences

The Computer Science Program provides advanced concepts, techniques, system architectures, algorithms, and software for both space and aeronautics information sciences and computer systems. The overall goal is to provide the technical foundation within NASA for the advancement of computing technology in aerospace applications. The research program is improving the state of knowledge of fundamental aerospace computing principles and advancing computing technology in space applications such as software engineering and information extraction from data collected by scientific instruments in space. The program includes the development of special algorithms and techniques to exploit the computing power provided by high performance parallel processors and special purpose architectures. Research is being conducted in the fundamentals of data base logic and improvement techniques for producing reliable computing systems.

Smith, Paul H.↗

NASA NTRS2021

Light-Robust Pole-from-Silhouette Algorithm and Visual-Hull Estimation for Autonomous Optical Navigation to an Unknown Small Body

We present an advanced Pole-from-Silhouette (PFS) algorithm, which is robust to illumination conditions and non-zero sun phase. PFS is an important step in the optical navigation pipeline for an autonomous small spacecraft to approach an unknown small body. The algo- rithm estimates the rotation pole and 3D shape (visual hull) of the small body using only the lit pixels within the silhouette of the small body, the body’s rotation rate, the spacecraft attitude, and the spacecraft-target relative distance, which is estimated from orbit determination. We present detailed numerical simulations and multiple sensitivity analyses to demonstrate the effectiveness of our proposed PFS algorithm in different scenarios and target bodies.

Nesnas, Issa A.↗

NASA NTRS1972

Application of advanced filtering methods to the determination of the interplanetary orbit of Mariner '71.

This paper presents the results of the applications of advanced filtering methods to the determination of the interplanetary orbit of the Mariner '71 spacecraft. The advanced techniques are specific extensions of the Kalman filter. The special problems associated with applying these techniques are discussed and the particular algorithmic implementations are outlined. The advanced methods are compared against the weighted least squares filters of conventional application. The results reveal that relatively simple advanced filter configurations yield solutions superior to those of the conventional methods when applied to the Mariner '71 radio measurements.

Rourke, K. H.↗