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NASA NTRS2017

Modeling Solar Energetic Particle Events Using ENLIL Heliosphere Simulations

Solar energetic particle (SEP) event modeling (SEPMOD) has gained renewed attention in part because of the availability of a decade of multipoint measurements from STEREO (Solar TErrestrial RElations Observatory) and L1 (Lagrangian point 1) spacecraft at 1 AU (Astronomical Unit). These observations are coupled with improving simulations of the geometry and strength of heliospheric shocks obtained by using coronagraph images to send erupted material into realistic solar wind backgrounds. The STEREO and ACE (Aerosol, Cloud systems, ocean Ecosystems) measurements in particular have highlighted the sometimes surprisingly widespread nature of SEP events. It is thus an opportune time for testing SEP models, which typically focus on protons approximately 1-100 megaelectronvolts, toward both physical insight to these observations and potentially useful space radiation environment forecasting tools. Some approaches emphasize the concept of particle acceleration and propagation from close to the Sun, while others emphasize the local field line connection to a traveling, evolving shock source. Among the latter is the previously introduced SEPMOD treatment, based on the widely accessible and well-exercised WSA-ENLIL (Wang-Sheeley-Arge-ENLIL)-cone model. SEPMOD produces SEP proton time profiles at any location within the ENLIL domain. Here we demonstrate a SEPMOD version that accommodates multiple, concurrent shock sources occurring over periods of several weeks. The results illustrate the importance of considering longer-duration time periods and multiple CME (Coronal Mass Ejection) contributions in analyzing, modeling, and forecasting SEP events.

Luhmann, J. G.↗

NASA NTRS2009

Controlling Infrastructure Costs: Right-Sizing the Mission Control Facility

Johnson Space Center's Mission Control Center is a space vehicle, space program agnostic facility. The current operational design is essentially identical to the original facility architecture that was developed and deployed in the mid-90's. In an effort to streamline the support costs of the mission critical facility, the Mission Operations Division (MOD) of Johnson Space Center (JSC) has sponsored an exploratory project to evaluate and inject current state-of-the-practice Information Technology (IT) tools, processes and technology into legacy operations. The general push in the IT industry has been trending towards a data-centric computer infrastructure for the past several years. Organizations facing challenges with facility operations costs are turning to creative solutions combining hardware consolidation, virtualization and remote access to meet and exceed performance, security, and availability requirements. The Operations Technology Facility (OTF) organization at the Johnson Space Center has been chartered to build and evaluate a parallel Mission Control infrastructure, replacing the existing, thick-client distributed computing model and network architecture with a data center model utilizing virtualization to provide the MCC Infrastructure as a Service. The OTF will design a replacement architecture for the Mission Control Facility, leveraging hardware consolidation through the use of blade servers, increasing utilization rates for compute platforms through virtualization while expanding connectivity options through the deployment of secure remote access. The architecture demonstrates the maturity of the technologies generally available in industry today and the ability to successfully abstract the tightly coupled relationship between thick-client software and legacy hardware into a hardware agnostic "Infrastructure as a Service" capability that can scale to meet future requirements of new space programs and spacecraft. This paper discusses the benefits and difficulties that a migration to cloud-based computing philosophies has uncovered when compared to the legacy Mission Control Center architecture. The team consists of system and software engineers with extensive experience with the MCC infrastructure and software currently used to support the International Space Station (ISS) and Space Shuttle program (SSP).

Martin, Keith↗

NASA NTRS2013

Spinoff 2012

Topics covered include: Water Treatment Technologies Inspire Healthy Beverages; Dietary Formulas Fortify Antioxidant Supplements; Rovers Pave the Way for Hospital Robots; Dry Electrodes Facilitate Remote Health Monitoring; Telescope Innovations Improve Speed, Accuracy of Eye Surgery; Superconductors Enable Lower Cost MRI Systems; Anti-Icing Formulas Prevent Train Delays; Shuttle Repair Tools Automate Vehicle Maintenance; Pressure-Sensitive Paints Advance Rotorcraft Design Testing; Speech Recognition Interfaces Improve Flight Safety; Polymers Advance Heat Management Materials for Vehicles; Wireless Sensors Pinpoint Rotorcraft Troubles; Ultrasonic Detectors Safely Identify Dangerous, Costly Leaks; Detectors Ensure Function, Safety of Aircraft Wiring; Emergency Systems Save Tens of Thousands of Lives; Oxygen Assessments Ensure Safer Medical Devices; Collaborative Platforms Aid Emergency Decision Making; Space-Inspired Trailers Encourage Exploration on Earth; Ultra-Thin Coatings Beautify Art; Spacesuit Materials Add Comfort to Undergarments; Gigapixel Images Connect Sports Teams with Fans; Satellite Maps Deliver More Realistic Gaming; Elemental Scanning Devices Authenticate Works of Art; Microradiometers Reveal Ocean Health, Climate Change; Sensors Enable Plants to Text Message Farmers; Efficient Cells Cut the Cost of Solar Power; Shuttle Topography Data Inform Solar Power Analysis; Photocatalytic Solutions Create Self-Cleaning Surfaces; Concentrators Enhance Solar Power Systems; Innovative Coatings Potentially Lower Facility Maintenance Costs; Simulation Packages Expand Aircraft Design Options; Web Solutions Inspire Cloud Computing Software; Behavior Prediction Tools Strengthen Nanoelectronics; Power Converters Secure Electronics in Harsh Environments; Diagnostics Tools Identify Faults Prior to Failure; Archiving Innovations Preserve Essential Historical Records; Meter Designs Reduce Operation Costs for Industry; Commercial Platforms Allow Affordable Space Research; Fiber Optics Deliver Real-Time Structural Monitoring; Camera Systems Rapidly Scan Large Structures; Terahertz Lasers Reveal Information for 3D Images; Thin Films Protect Electronics from Heat and Radiation; Interferometers Sharpen Measurements for Better Telescopes; and Vision Systems Illuminate Industrial Processes.

Source record↗

NASA NTRS2005

Discrete X-Ray Source Populations and Star Formation History in Nearby Galaxies

This program aims in understanding the connection between the discrete X-ray source populations observed in nearby galaxies and the history of star-formation in these galaxies. The ultimate goal is to use this knowledge in order to constrain X-ray binary evolution channels. For this reason although the program is primarily observational it has a significant modeling component. During the second year of this study we focused on detailed studies of the Antennae galaxies and the Small Magellanic Cloud (SMC). We also performed the initial analysis of the 5 galaxies forming a starburst-age sequence.

Zezas, Andreas↗

NASA NTRS1977

Copernicus observations of distant unreddened stars. II - Line of sight to HD 50896

Copernicus UV data on interstellar lines toward HD 50896, a Wolf-Rayet star, are analyzed to study abundances and physical conditions in the line of sight. About 20% of the low-velocity neutral gas is contained in a dense cloud with 10% to 50% of its hydrogen in molecular form; the atomic abundances show typical interstellar depletions. The low-velocity H II gas may be associated with the high ionizing flux of the Wolf-Rayet star or with H II regions along the line of sight. Si III exhibits strong absorption shortward of the low-velocity H II gas, characteristic of a collisionally ionized component at 30,000 to 80,000 K; the possible connections with an unobserved supernova remnant or stellar mass loss are discussed. High-velocity features at 78 and -96 km/sec, in which Fe and Si are near their cosmic abundances, are also indicative of strong shocks.

Shull, J. M.↗

NASA NTRS2020

Electrodynamic Dust Shield Housing for RASSOR Redesign and Fabrication

Abstract—An Electrodynamic Dust Shield (EDS) was to be mounted over the cameras of the Regolith Advanced Surface Systems Operations Robot (RASSOR) to mitigate the clouding effects and abrasive properties of lunar dust. This report discusses the redesign process and physical fabrication of the housing unit planned to attach the EDS to the RASSOR camera. The two-piece 3D-Printed design consists of a holder and cover unit. The EDS Holder seats the EDS near two live copper contacts that are to be wired into the main electronics housing. The EDS Cover seats two metal leaf spring tabs to bridge the connections between the copper contacts and EDS electrodes, as well as a centralized O-ring that is pressed flush against the EDS to mitigate dust intrusion. All components were modeled, printed, and checked for proper electrical contact and mechanical fit. The built-up assembly was subsequently tested in the Electrostatics and Surface Physics Laboratory (ESPL) and demonstrated good dust clearing performance.

Alexander Lacerna↗

NASA NTRS2020

Air Traffic Management TestBed Data Exchange Model

The Air Traffic Management (ATM) TestBed is a Platform as a Service that is being developed by the National Aeronautics and Space Administration (NASA) to help design, configure, integrate, run, and monitor air traffic simulations. The platform is designed to provide cloud services including back-end, big-data analytics tools, on-demand computing resource management, data storage, and communication middleware. The ATM TestBed reduces the time to test concepts and technologies, supports interactions among various methods such as human-in-the-loop and automation-in-the-loop simulations, and enables collaborative simulations by sharing technologies and tools in the ATM community. In order to allow easier access to simulation components, TestBed provides a messaging support layer for connectivity using a consistent set of input/output interfaces. In addition, a standard data format is introduced to facilitate communication between the components. The data exchange model, supported in the messaging support layer, standardizes the format of the information to be exchanged among the components. This document describes the messaging data model currently developed in TestBed and provides data dictionaries for references to component developers as well as simulation engineers.

air traffic simulation↗

NASA NTRSDate not supplied

A 3D Simulation Platform for Decentralized Decision-Making in Advanced Air Mobility

This paper presents a general purpose, plug-and-play simulation platform for the use of future aviation stakeholders, such as urban airspace planners, air vehicle operators, ground operation managers, air traffic controllers and aviation researchers. The presented simulator platform is envisioned to serve as a toolkit to visualize, evaluate, and configure future advanced air mobility (AAM) operations. Highlighting features of this toolkit include a modular architecture that allows multiple smart unmanned aerial systems (UASs) to remotely connect to the simulation server and participate in decentralized decision-making scenario simulations. As an example of the decentralized decision-making scenario, an inter-agent negotiation-based conflict resolution use case is considered in this paper, where the UASs leverage the on-board/on-the-edge artificial intelligence (AI) capability to continually build situational awareness, and use this information to predict future conflicts and resolve them through machine-to-machine negotiation. As such operations are non-existent at scale currently, the presented simulation platform offers a viable and cost-effective alternative for assessing the efficacy of AAM research outcomes and challenges in future shared airspace usage. The simulation platform allows plug-n-play connectivity with AI and non-AI compute modules representing individual UAS’s flight control. Each module can interact with the simulation platform independently to communicate current and desired future states, situational awareness, and conflict resolution utilization costs for inter-agent negotiation. The simulation environment orchestrates realistic operational scenarios with spatiotemporal details, dynamic events, tactical conflict-resolution methods, interfaces for customizing air traffic control parameters, and information exchange uncertainties. In the future, this can serve as a community focused cloud simulation platform, incorporating multi-stakeholder airspace constraints from regulatory, government, city, and local agencies.

Aditya N Das↗

NASA NTRS2022

A 3D Simulation Platform for Decentralized Decision-Making in Advanced Air Mobility

Aditya Das↗

NASA NTRS1981

Spectral investigations of Mars from Viking

In connection with the Viking mission, spectral and photometric data of Mars were obtained with the aid of camera systems located either on the planetary surface (Lander I and II) or in Martian orbit (Orbiter I and II). Operations from Lander I are scheduled to continue through 1990. Comparisons made of the surface and atmospheric spectral and photometric properties at various times throughout the Mission were probably the most important studies conducted by the Lander cameras. The variations in atmospheric optical density due to clouds, dust storm activity (both local and global), and even a partial eclipse of the sun by the small satellite Phobos, were observed by the Lander imaging systems. Using Viking Orbiter II images, the surface materials of the equatorial region have been classified and mapped on the basis of spectral reflectance properties. Attention is also given to some details regarding the characteristics of the Viking imaging systems.

Evans, N.↗

NASA NTRS2003

Two-Dimensional Transport Studies for the Composition and Structure of the Io Plasma Torus

The overall objective of this project is to investigate the roles of local and spatially extended plasma sources created by Io, plasma torus chemistry, and plasma convective and diffusive transport in producing the long-lived S(+), S(++) and O(+) radial ribbon structures of the plasma torus, their System III longitude and local-time asymmetries, their energy sources and their possible time variability. To accomplish this objective, two-dimensional [radial (L) and System III longitude] plasma transport equations for the flux-tube plasma content and energy content will be solved that include the convective motions for both the east-west electric field and co-rotational velocity-lag profile near Io s orbit, radial diffusion, and the spacetime dependent flux-tube production and loss created by both neutral-plasma and plasma-ion reaction chemistry in the plasma torus. For neutral-plasma chemistry, the project will for the first time undertake the calculation of realistic three-dimensional, spatially-extended, and time-varying contributions to the flux-tube ion-production and loss that are produced by Io's corona and extended neutral clouds. The unknown two-dimensional spatial nature of diffusion in the plasma transport will be isolated and better defined in the investigation by the collective consideration of the foregoing different physical processes. For energy transport, the energy flow from hot pickup ions (and a new electron source) to thermal ions and electrons will be included in investigating the System III longitude and local-time temperature asymmetries in the plasma torus. The research is central to the scope of the NASA Sun-Earth Connection Roadmap in Quest II Campaign 4 "Comparative Planetary Space Environments" by addressing key questions for understanding the magnetosphere of planets with high rotation rates and large internal plasma sources and, in addition, is of considerable importance to the NASA Solar System Exploration Science Theme. In this regard, Jupiter is the most extreme example with its rapid rotation and with its inner Galilean satellite Io providing the dominant plasma source for the magnetosphere.

Smyth, William H.↗

NASA NTRS1982

On charge exchange and knock-on processes in the exosphere of Io

One direct consequence of magnetospheric interaction of Io is the strong dynamical coupling of its neutral atmosphere with the corotating plasma. The absorption of the thermal ions and the associated neutral injection is an improtant issue not yet explored. As far as nonthermal escape of the neutral atmosphere is concerned, three processes stand out. That is, apart from sputtering, exospheric interactions like atom-ion knock-on collision and charge exchange recombination could be a significant source of the neutral clouds in the Jovian system. Using a current electrodynamic model of Io, both the absorption rate of the corotating thermal plasma and the production rates of new exospheric ions and the fast neutrals are considered. It is found that the source strength of the neutral atoms and molecules with speeds of about 100 km/sec could amount to 10 to the 26th/sec whereas exospheric neutrals emitted at lower speed (of about 10 km/sec) amounts to 4 x 10 to the 25th/sec. The generation of the new ions in connection with the streaming of the magnetospheric plasma around Io could also produce an asymmetric sputtering with a neutral flux of about 10 to the 27th/sec emitted from the region of Io which faces Jupiter. These results may be related to a number of sodium observations.

Ip, W.-H.↗

NASA NTRSDate not supplied

Lessons learned from replicating services for flood prediction and monitoring in Asia to the assessment of hurricane impacts in Central America

In October and November 2020, two dangerous back-to-back hurricanes, Eta and Iota, made landfall in Central America. The SERVIR program - a joint effort of NASA and the U.S. Agency for International Development, and whose motto is “connecting space to village” was able to leverage two tools originally developed for use in other regions for predicting and assessing the flood impacts of the hurricanes. The GEOGLoWS Streamflow Prediction tool - originally implemented in the Hindu Kush Himalayan region - was used for predicting potential flooding ahead of landfall by Eta and Iota. In conjunction, the Hydrologic Remote Sensing Analysis for Floods (HYDRAFloods) framework - originally developed along with SERVIR-Mekong - was used for post-event flood mapping, leveraging its ability to map floods in cloud-covered areas using synthetic aperture radar (SAR) imagery from the Copernicus program. Both tools were used in support of disaster coordination efforts being led by the Central American Regional Disaster Prevention Center (CEPREDENAC), in conjunction with its sister agency, the Regional Water Resources Committee (CRRH). The support provided to regional entities - and to their stakeholder national governments - served as an example of rapid generation of Earth observation products for disaster response. Feedback on those products was also provided, especially in terms of the implications of (i) calibration of predicted river volumes, and (ii) the latency of the input Earth observation imagery and attempts to map the floods’ maximum extents. An upcoming NASA DEVELOP project will also seek to strengthen the capability of CEPREDENAC and CRRH to apply HYDRAFloods for future extreme events. The application of the tools also provides a useful case study on capacity building, in terms of how Earth observation data and models can be replicated across regions.

Capacity building↗

NASA NTRS1997

Virtual Instrument Simulator for CERES

A benchtop virtual instrument simulator for CERES (Clouds and the Earth's Radiant Energy System) has been built at NASA, Langley Research Center in Hampton, VA. The CERES instruments will fly on several earth orbiting platforms notably NASDA's Tropical Rainfall Measurement Mission (TRMM) and NASA's Earth Observing System (EOS) satellites. CERES measures top of the atmosphere radiative fluxes using microprocessor controlled scanning radiometers. The CERES Virtual Instrument Simulator consists of electronic circuitry identical to the flight unit's twin microprocessors and telemetry interface to the supporting spacecraft electronics and two personal computers (PC) connected to the I/O ports that control azimuth and elevation gimbals. Software consists of the unmodified TRW developed Flight Code and Ground Support Software which serves as the instrument monitor and NASA/TRW developed engineering models of the scanners. The CERES Instrument Simulator will serve as a testbed for testing of custom instrument commands intended to solve in-flight anomalies of the instruments which could arise during the CERES mission. One of the supporting computers supports the telemetry display which monitors the simulator microprocessors during the development and testing of custom instrument commands. The CERES engineering development software models have been modified to provide a virtual instrument running on a second supporting computer linked in real time to the instrument flight microprocessor control ports. The CERES Instrument Simulator will be used to verify memory uploads by the CERES Flight Operations TEAM at NASA. Plots of the virtual scanner models match the actual instrument scan plots. A high speed logic analyzer has been used to track the performance of the flight microprocessor. The concept of using an identical but non-flight qualified microprocessor and electronics ensemble linked to a virtual instrument with identical system software affords a relatively inexpensive simulation system capable of high fidelity.

Chapman, John J.↗

NASA NTRS2019

Using Deep Learning to Automate Inference of Meteoroid Pre-Entry Properties

Properly assessing the asteroid threat depends on the knowledge of asteroid pre-entry parameters, such as size, velocity, mass, density, and strength. Although a vast number of possible bodies to study exist, such characterization of asteroid populations is currently limited by substantial costs associated with space rendezvous missions and rare meteorite findings. As asteroids fragment, ablate, and decelerate in the atmosphere, they emit light detectable by ground-based and space-borne instruments. Earth’s atmosphere, thus, becomes an accessible laboratory that enables impactor risk assessments by facilitating inference of the pre-entry parameters. These asteroid pre-entry conditions are typically deduced by modeling the entry and breakup physics that best reproduce the observed light or energy deposition curve. However, this process requires extensive manual trial-and-error of uncertain modeling parameters. Automating meteor modeling and inference would improve property distributions used in risk assessments and enable population characterization as more light curves become more readily available through the presence of space assets and ground-based camera networks. We previously developed a genetic algorithm to automate meteor modeling by using the fragment-cloud model (FCM) to search for the values of the FCM input parameters (e.g., diameter) that generate energy deposition profiles that match the observed one. Now, we apply deep learning to infer asteroid diameter, velocity, and density from observed energy deposition curves. We trained and tested our neural network models with synthetic energy deposition curves modeled using the FCM rubble pile implementation. We present an application of a 1D convolutional neural network and compare its performance to other attempted regressors and machine learning techniques, such as a fully connected neural network and Random Forest regression, to demonstrate its capabilities. We validate our model weights and approach using the Chelyabinsk, Tagish Lake, Benešov, Košice, and Lost City meteors.

Tarano, Ana Maria↗

NASA NTRS1984

Radiometric correction of atmospheric path length fluctuations in interferometric experiments

To support very long baseline interferometric experiments, a system has been developed for estimating atmospheric water vapor path delay. The system consists of dual microwave radiometers, one operating at 20.7 GHz and the other at 31.4 GHz. The measured atmospheric brightness temperatures at these two frequencies yield the estimate of the precipitable water present in both vapor and droplets. To determine the accuracy of the system, a series of observations were undertaken, comparing the outputs of two water vapor radiometers with the phase variation observed with two connected elements of the very large array (VLA). The results show that: (1) water vapor fluctuations dominate the residual VLA phase and (2) the microwave radiometers can measure and correct these effects. The rms phase error after correction is typically 15 deg at a wavelength of 6 cm, corresponding to an uncertainty in the path delay of 0.25 cm. The residual uncertainty is consistent with the stability of the microwave radiometer but is still considerably larger than the stability of the VLA. The technique is less successful under conditions of heavy cloud.

Resch, G. M.↗

NASA NTRS1991

Fuzzy set methods for object recognition in space applications

Progress on the following tasks is reported: (1) fuzzy set-based decision making methodologies; (2) feature calculation; (3) clustering for curve and surface fitting; and (4) acquisition of images. The general structure for networks based on fuzzy set connectives which are being used for information fusion and decision making in space applications is described. The structure and training techniques for such networks consisting of generalized means and gamma-operators are described. The use of other hybrid operators in multicriteria decision making is currently being examined. Numerous classical features on image regions such as gray level statistics, edge and curve primitives, texture measures from cooccurrance matrix, and size and shape parameters were implemented. Several fractal geometric features which may have a considerable impact on characterizing cluttered background, such as clouds, dense star patterns, or some planetary surfaces, were used. A new approach to a fuzzy C-shell algorithm is addressed. NASA personnel are in the process of acquiring suitable simulation data and hopefully videotaped actual shuttle imagery. Photographs have been digitized to use in the algorithms. Also, a model of the shuttle was assembled and a mechanism to orient this model in 3-D to digitize for experiments on pose estimation is being constructed.

Keller, James M.↗

NASA NTRSDate not supplied

Transcribing Air Traffic Control System Command Center Planning Telecons Using Cloud-Based Automatic Speech Recognition

This paper addresses the challenge of using Automatic Speech Recognition (ASR) technology to transcribe regular teleconferences that happen between FAA Air Traffic Control System Command Center (ATCSCC) planners, stakeholders and air users. These planning teleconferences (aka telecons or planning webinars) are an integral part of managing air traffic in the U.S. National Airspace System (NAS). In particular, the meetings facilitate the creation and modification of various traffic management initiatives (TMIs), that are used to regulate the flow of air traffic. This is typically a human intensive process, requiring specialists to listen to the entire meeting audio (10-20 minutes duration) and inferring the state of the NAS (e.g., weather phenomenon) that was discussed. It would be advantageous to have digital transcripts of the audio and have useful information (e.g., related to TMIs) automatically extracted from the transcripts. In this regard, we are exploring the adoption of state-of-the-art speech to text and Natural Language Processing (NLP) tools that will achieve our objective of digitizing the webinar audio. Unfortunately, the highly technical phraseology present in the audio and limited data availability for model building make ASR difficult. To overcome this challenge, we have taken the critical first step in creating a human transcription dataset from ~20 hours of speech in the ATCSCC audio with the help of subject matter experts. A novelty of our work is the creation of a ground truth transcription dataset for ATCSCC teleconference webinars, which is particularly important for Aviation domain-specific NLP tasks. Using Microsoft Speech Studio, a cloud-based ASR platform, we have fine-tuned the English pre-trained ASR models (available in speech studio) and achieved an average word error rate (WER) of 6.81%. The baseline ASR also provides a digital version of each planning webinar, making it accessible and text-searchable for future references. Additionally, the transcriptions can serve as a bridge between raw audio data and a range of text-based NLP tasks, such as named entity recognition (NER) and intent classification, potentially enhancing the digital footprint of the webinars and other connected data sources. Our work has several potential applications. Firstly, the transcriptions can be analyzed to understand the complex decision process of creating, implementing and modifying TMIs and may also contribute to TMI prediction services. Secondly, our dataset and model can be used to develop more accurate ASR systems for aviation-specific language, which can bring about digital communication in the aviation industry (and aid current “voice only” communications, which are inherently error-prone). Lastly, the transcriptions themselves can be used as a valuable resource for training other NLP models.

Stephen S. B. Clarke↗