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At least 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Post-Shuttle EVA Operations on ISS

The EVA hardware used to assemble and maintain the ISS was designed with the assumption that it would be returned to Earth on the Space Shuttle for ground processing, refurbishment, or failure investigation (if necessary). With the retirement of the Space Shuttle, a new concept of operations was developed to enable EVA hardware (EMU, Airlock Systems, EVA tools, and associated support equipment and consumables) to perform ISS EVAs until 2016 and possibly beyond to 2020. Shortly after the decision to retire the Space Shuttle was announced, NASA and the One EVA contractor team jointly initiated the EVA 2010 Project. Challenges were addressed to extend the operating life and certification of EVA hardware, secure the capability to launch EVA hardware safely on alternate launch vehicles, and protect EMU hardware operability on orbit for long durations.

West, Bill↗
NASA NTRS2017

Survey of Constellation-Era LOX/Methane Development Activities and Future Development Needs

NASA formed the Constellation Program in 2005 to achieve the objectives of maintaining American presence in low-Earth orbit, returning to the moon for purposes of establishing an outpost, and laying the foundation to explore Mars and beyond in the first half of the 21st century. The Exploration Technology Development Program (ETDP) was formulated to address the technology needs to address Constellation architecture decisions. The Propellants and Cryogenic Advanced Development (PCAD) project was tasked with risk mitigation of specific propulsion related technologies to support ETDP. Propulsion systems were identified as critical technologies owing to the high gear-ratio of lunar Mars landers Cryogenic propellants offer performance advantage over storables (NTOMMH) Mass savings translate to greater payload capacity In-situ production of propellant an attractive feature; methane and oxygen identified as possible Martian in-situ propellants New technologies were required to meet more difficult missions High performance LOX/LH2 deep throttle descent engines High performance LOX/LCH4 ascent main and reaction control system (RCS) engines The PCAD project sought to provide those technologies through Reliable ignition pulse RCS Fast start High efficiency engines Stable deep throttling.

Propulsion system components↗
NASA NTRSDate not supplied

The Future of NASA Earth Science in the Commercial Cloud: Challenges and Opportunities

NASA produces a large volume and variety of data products that are used every day to support research, decision making, and education. The widespread use of NASA’s Earth Science data is enabled by NASA’s Earth Science Data System (ESDS) program, which oversees the archiving and distribution of these data and invests in the development of new data systems and tools. However, NASA’s current approach to Earth Science data distribution — based on distributed institutional archives with individual on-premises high-performance computing capabilities — faces some significant challenges, including massive increases in data volume from upcoming missions, a greater need for transdisciplinary science that synthesizes many different kinds of observations, and a push to make science more open, inclusive, and accessible. To address these challenges, NASA is aggressively migrating its Earth Science data and related tools and services into the commercial cloud. Migration of data into the commercial cloud can significantly improve NASA’s existing data system capabilities by (1) providing more flexible options for storage and compute (including rapid, as-needed access to state-of-the-art capabilities); (2) by centralizing and standardizing data access, which gives all of NASA’s institutional data centers access to all of each other’s datasets; and (3) by facilitating “analysis-in-place”, whereby users can bring their own computational workflows and tools to the data rather than having to maintain their own copies of NASA datasets. However, migration to the commercial cloud also poses some significant challenges, including (1) managing costs under a “pay-as-you-go” model; (2) incompatibility with existing tools and data formats with object-based storage and network access; (3) vendor lock-in; (4) challenges with data access for workflows that mix on-premise and cloud computing; and (5) standardization for highly diverse data as is present in NASA’s data archive. I conclude with two examples of recent NASA activities showcasing capabilities enabled by the commercial cloud: An interactive analysis and development platform for analyzing airborne imaging spectroscopy data, and a new collection of tools and services for data discovery, analysis, publication, and data-driven storytelling (Visualization, Exploration, and Data Analysis, VEDA).

Alexey N Shiklomanov↗
NASA NTRS2016

System Performance of an Integrated Airborne Spacing Algorithm with Ground Automation

The National Aeronautics and Space Administration's (NASA's) first Air Traffic Management (ATM) Technology Demonstration (ATD-1) was created to facilitate the transition of mature ATM technologies from the laboratory to operational use. The technologies selected for demonstration are the Traffic Management Advisor with Terminal Metering (TMA-TM), which provides precise time-based scheduling in the Terminal airspace; Controller Managed Spacing (CMS), which provides controllers with decision support tools to enable precise schedule conformance; and Interval Management (IM), which consists of flight deck automation that enables aircraft to achieve or maintain precise spacing behind another aircraft. Recent simulations and IM algorithm development at NASA have focused on trajectory-based IM operations where aircraft equipped with IM avionics are expected to achieve a spacing goal, assigned by air traffic controllers, at the final approach fix. The recently published IM Minimum Operational Performance Standards describe five types of IM operations. This paper discusses the results and conclusions of a human-in-the-loop simulation that investigated three of those IM operations. The results presented in this paper focus on system performance and integration metrics. Overall, the IM operations conducted in this simulation integrated well with ground-based decisions support tools and certain types of IM operational were able to provide improved spacing precision at the final approach fix; however, some issues were identified that should be addressed prior to implementing IM procedures into real-world operations.

Swieringa, Kurt A.↗
NASA NTRS1991

Search for supporting methodologies - Or how to support SEI for 35 years

Concepts relevant to the development of an evolvable information management system are examined in terms of support for the Space Exploration Initiative. The issues of interoperability within NASA and industry initiatives are studied including the Open Systems Interconnection standard and the operating system of the Open Software Foundation. The requirements of partitioning functionality into separate areas are determined with attention given to the infrastructure required to ensure system-wide compliance. The need for a decision-making context is a key to the distributed implementation of the program, and this environment is concluded to be next step in developing an evolvable, interoperable, and securable support network.

Handley, Thomas H., Jr.↗
NASA NTRS2010

Cost/Effort Drivers and Decision Analysis

Engineering trade study analyses demand consideration of performance, cost and schedule impacts across the spectrum of alternative concepts and in direct reference to product requirements. Prior to detailed design, requirements are too often ill-defined (only goals ) and prone to creep, extending well beyond the Systems Requirements Review. Though lack of engineering design and definitive requirements inhibit the ability to perform detailed cost analyses, affordability trades still comprise the foundation of these future product decisions and must evolve in concert. This presentation excerpts results of the recent NASA subsonic Engine Concept Study for an Advanced Single Aisle Transport to demonstrate an affordability evaluation of performance characteristics and the subsequent impacts on engine architecture decisions. Applying the Process Based Economic Analysis Tool (PBEAT), development cost, production cost, as well as operation and support costs were considered in a traditional weighted ranking of the following system-level figures of merit: mission fuel burn, take-off noise, NOx emissions, and cruise speed. Weighting factors were varied to ascertain the architecture ranking sensitivities to these performance figures of merit with companion cost considerations. A more detailed examination of supersonic variable cycle engine cost is also briefly presented, with observations and recommendations for further refinements.

Seidel, Jonathan↗
NASA NTRS2011

Adding Remote Sensing Data Products to the Nutrient Management Decision Support Toolbox

Some of the primary issues that manifest from nutrient enrichment and eutrophication (Figure 1) may be observed from satellites. For example, remotely sensed estimates of chlorophyll a (chla), total suspended solids (TSS), and light attenuation (Kd) or water clarity, which are often associated with elevated nutrient inputs, are data products collected daily and globally for coastal systems from satellites such as NASA s MODIS (Figure 2). The objective of this project is to inform water quality decision making activities using remotely sensed water quality data. In particular, we seek to inform the development of numeric nutrient criteria. In this poster we demonstrate an approach for developing nutrient criteria based on remotely sensed chla.

Lehrter, John↗
NASA NTRSDate not supplied

Predicting Airport Runway Configurations for Decision-Support Using Supervised Learning

One of the most challenging tasks for air traffic controllers is runway configuration management (RCM). It deals with the optimal selection of runways to operate on (for arrivals and departures) based on traffic, surface wind speed, wind direction, other environmental variables, noise constraints, and several other airport-specific factors. It affects the efficiency of the National Airspace System (NAS) and both surface and airspace operations can benefit from better understanding future runway configurations. In this paper, we present a comprehensive implementation of predictive models for runway configuration estimation from large volumes of historical data. Specifically, operational data from two full years (2018 and 2019) is collected, analyzed, and fused together to build the data product used in this work. The data set differs from prior work in the field in terms of its scope, resolution, and variety of factors collected and considered. Meteorological data is collected from two different sources – current weather conditions from METAR (Meteorological Terminal Aviation Routine Weather Report) and forecast weather conditions from Localized Aviation MOS Program (LAMP). Operational data from the Federal Aviation Administration (FAA) Aviation System Performance Metrics (ASPM) related to scheduled and actual number of arrivals and departures, average taxi times, etc. are collected. NASA’s Sherlock Data Warehouse is used to identify critical information such as go-arounds, and other events that might impact RCM decision-making. All data is collected and aggregated over 15-minute intervals throughout the two years. This provides a resolution like the timescales that might be necessary for runway configuration management decision-making. A variety of supervised learning algorithms are tested including Support Vector Machine, Random Forest, Gradient Boosting, etc. including tuning of the model hyperparameters. The modeling process is applied and presented on two representative U.S. airports – Charlotte Douglas International Airport (KCLT) and Denver International Airport (KDEN). The two airports present different levels of complexity in terms of the total number of configurations used and provide a balanced perspective on the generalizability of the developed approach to other airports in the NAS. Initial results are promising (F1 score of 0.91 at KCLT and 0.83 at KDEN) for data in the test set. The final paper will contain a comprehensive comparison between different models and model building strategies as well as further refined results. Most important predictors for each airport will be identified along with a discussion and recommendations on adapting the framework to other scenarios.

Tejas G Puranik↗
NASA NTRS2005

Intelligent Information Fusion in the Aviation Domain: A Semantic-Web based Approach

Information fusion from multiple sources is a critical requirement for System Wide Information Management in the National Airspace (NAS). NASA and the FAA envision creating an "integrated pool" of information originally coming from different sources, which users, intelligent agents and NAS decision support tools can tap into. In this paper we present the results of our initial investigations into the requirements and prototype development of such an integrated information pool for the NAS. We have attempted to ascertain key requirements for such an integrated pool based on a survey of DSS tools that will benefit from this integrated pool. We then advocate key technologies from computer science research areas such as the semantic web, information integration, and intelligent agents that we believe are well suited to achieving the envisioned system wide information management capabilities.

Ashish, Naveen↗
NASA NTRS1989

Automation of orbit determination functions for National Aeronautics and Space Administration (NASA)-supported satellite missions

The Flight Dynamics Facility (FDF) at Goddard Space Flight Center (GSFC) provides spacecraft trajectory determination for a wide variety of National Aeronautics and Space Administration (NASA)-supported satellite missions, using the Tracking Data Relay Satellite System (TDRSS) and Ground Spaceflight and Tracking Data Network (GSTDN). To take advantage of computerized decision making processes that can be used in spacecraft navigation, the Orbit Determination Automation System (ODAS) was designed, developed, and implemented as a prototype system to automate orbit determination (OD) and orbit quality assurance (QA) functions performed by orbit operations. Based on a machine-resident generic schedule and predetermined mission-dependent QA criteria, ODAS autonomously activates an interface with the existing trajectory determination system using a batch least-squares differential correction algorithm to perform the basic OD functions. The computational parameters determined during the OD are processed to make computerized decisions regarding QA, and a controlled recovery process isactivated when the criteria are not satisfied. The complete cycle is autonomous and continuous. ODAS was extensively tested for performance under conditions resembling actual operational conditions and found to be effective and reliable for extended autonomous OD. Details of the system structure and function are discussed, and test results are presented.

Mardirossian, H.↗
NASA NTRS1990

Automation of orbit determination functions for National Aeronautics and Space Administration (NASA)-supported satellite missions

The Flight Dynamics Facility (FDF) at Goddard Space Flight Center (GSFC) provides spacecraft trajectory determination for a wide variety of National Aeronautics and Space Administration (NASA)-supported satellite missions, using the Tracking Data Relay Satellite System (TDRSS) and Ground Spaceflight and Tracking Data Network (GSTDN). To take advantage of computerized decision making processes that can be used in spacecraft navigation, the Orbit Determination Automation System (ODAS) was designed, developed, and implemented as a prototype system to automate orbit determination (OD) and orbit quality assurance (QA) functions performed by orbit operations. Based on a machine-resident generic schedule and predetermined mission-dependent QA criteria, ODAS autonomously activates an interface with the existing trajectory determination system using a batch least-squares differential correction algorithm to perform the basic OD functions. The computational parameters determined during the OD are processed to make computerized decisions regarding QA, and a controlled recovery process is activated when the criteria are not satisfied. The complete cycle is autonomous and continuous. ODAS was extensively tested for performance under conditions resembling actual operational conditions and found to be effective and reliable for extended autonomous OD. Details of the system structure and function are discussed, and test results are presented.

Mardirossian, H.↗
NASA NTRS1990

Human factors in spacecraft design

This paper describes some of the salient implications of evolving mission parameters for spacecraft design. Among the requirements for future spacecraft are new, higher standards of living, increased support of human productivity, and greater accommodation of physical and cultural variability. Design issues include volumetric allowances, architecture and layouts, closed life support systems, health maintenance systems, recreational facilities, automation, privacy, and decor. An understanding of behavioral responses to design elements is a precondition for critical design decisions. Human factors research results must be taken into account early in the course of the design process.

Harrison, Albert A.↗
NASA NTRS1999

Gulf of Mexico Helicopter Offshore System Technologies Engineering Needs Assessment

The National Aeronautics and Space Administration (NASA), in partnership with the Federal Aviation Administration (FAA), is conducting a research and development program to modernize the National Airspace System (NAS). The mission of NASA's Advanced Air Transportation Technologies (AATT) project is to develop advanced Air Traffic Management (ATM) concepts and decision support tools for eventual deployment and implementation by the FAA and the private sector. One major objective of the NASA AATT project is to understand and promote the needs of all user classes. The Gulf of Mexico (GoMex) airspace has unique needs. A large number of helicopters operate in this area with only limited surveillance and sometimes-severe environmental conditions. Thunderstorms are the most frequent weather hazard during the spring, summer, and fall. In winter, reduced hours of daylight, low ceilings, strong winds, and icing conditions may restrict operations. Hurricanes impose the most severe weather hazard. The hurricane season, from June through October, normally requires at least one mass evacuation of all offshore platforms.

Edmund J. Koenke↗
NASA NTRS2001

Noise Mitigation Controller Tools

During the past decade, the National Aeronautics and Space Administration (NASA) has been developing and evaluating a suite of decision support tools (DSTs) to aid the air traffic controller in the management of traffic. These tools are known collectively as the Center/TRACON Automation System (CTAS). The primary focus of CTAS is increased capacity. As part of a new NASA program called Quiet Aircraft Technology (QAT), the following question is being addressed: Can CTAS technology also support the noise mitigation requirements imposed by the community? Controllers currently support a variety of low noise procedures in low traffic densities but, as traffic increases, these must be abandoned due to excessive spacing requirements for vectoring or inter-arrival spacing requirements needed to handle a spectrum of low noise procedures. NASA is currently investigating how to provide controllers with noise-mitigation-based advisories which address these issues without negatively impacting capacity. These issues are of global concern which must be addressed as the demand for air travel continues to increase.

Tobias, Leonard↗
NASA NTRS2009

Integration of Dust Prediction Systems and Vegetation Phenology to Track Pollen for Asthma Alerts in Public Health

Initial efforts to develop a deterministic model for predicting and simulating pollen release and downwind concentration to study dependencies of phenology on meteorology will be discussed. The development of a real-time, rapid response pollen release and transport system as a component of the New Mexico Environmental Public Health Tracking System (EPHTS), is based on meteorological models, NASA Earth science results (ESR), and an in-situ network of phenology cameras. The plan is to detect pollen release verified using ground based atmospheric pollen sampling within a few hours using daily MODIS daa in nearly real-time from Direct Broadcast, similar to the MODIS Rapid Response System for fire detection. As MODIS winds down, the NPOESS-VIIRS sensor will assume daily vegetation monitoring tasks. Also, advancements in geostationary satellites will allow 1km vegetation indices at 15-30 minute intervals. The pollen module in EPHTS will be used to: (1) support public health decisions for asthma and allergy alerts in New Mexico, Texas and Oklahoma; (2) augment the Centers for Disease Control and Prevention (CDC)'s Environmental Public Health Tracking Network (EPHTN); and (3) extend surveillance services to local healthcare providers subscribing to the Syndrome Reporting Information System (SYRIS). Previous studies in NASA's public health applications portfolios provide the infrastructure for this effort. The team is confident that NASA and NOAA ESR data, combined into a verified and validated dust model will yield groundbreaking results using the modified dust model to transport pollen. The growing ESR/health infrastructure is based on results from a rapid prototype scoping effort for pollen detection and simulation carried out by the principal investigators.

Luvall, Jeffrey↗
NASA NTRS2015

Data Applicability of Heritage and New Hardware for Launch Vehicle System Reliability Models

Many launch vehicle systems are designed and developed using heritage and new hardware. In most cases, the heritage hardware undergoes modifications to fit new functional system requirements, impacting the failure rates and, ultimately, the reliability data. New hardware, which lacks historical data, is often compared to like systems when estimating failure rates. Some qualification of applicability for the data source to the current system should be made. Accurately characterizing the reliability data applicability and quality under these circumstances is crucial to developing model estimations that support confident decisions on design changes and trade studies. This presentation will demonstrate a data-source classification method that ranks reliability data according to applicability and quality criteria to a new launch vehicle. This method accounts for similarities/dissimilarities in source and applicability, as well as operating environments like vibrations, acoustic regime, and shock. This classification approach will be followed by uncertainty-importance routines to assess the need for additional data to reduce uncertainty.

Al Hassan Mohammad↗
NASA NTRS2010

TPSAS-NF1676L-9990-DND

PVS (Prototype Veri cation System)1 is an interactive environment for the specification and verification of systems. PVS provides a strongly typed specification language, which is based on Higher-Order Logic. The type system of PVS supports: sub-typing, dependent-types, abstract data types, parametric types, records, unions, and tuples. The PVS theorem prover includes decision procedures for a variety of theories such as linear arithmetic, propositional logic, and temporal logic. This seminar will provide a gentle introduction to the basic and advanced features of PVS, including: theory interpretations, real number proving, batch proving, rapid prototyping, and strategy development. All these features are illustrated with simple examples and exercises.

César Muñoz↗
NASA NTRS2013

Integrating Wind Profiling Radars and Radiosonde Observations with Model Point Data to Develop a Decision Support Tool to Assess Upper-Level Winds for Space Launch

On the day-of-launch, the 45th Weather Squadron (45 WS) Launch Weather Officers (LWOs) monitor the upper-level winds for their launch customers to include NASA's Launch Services Program and NASA's Ground Systems Development and Operations Program. They currently do not have the capability to display and overlay profiles of upper-level observations and numerical weather prediction model forecasts. The LWOs requested the Applied Meteorology Unit (AMU) develop a tool in the form of a graphical user interface (GUI) that will allow them to plot upper-level wind speed and direction observations from the Kennedy Space Center (KSC) 50 MHz tropospheric wind profiling radar, KSC Shuttle Landing Facility 915 MHz boundary layer wind profiling radar and Cape Canaveral Air Force Station (CCAFS) Automated Meteorological Processing System (AMPS) radiosondes, and then overlay forecast wind profiles from the model point data including the North American Mesoscale (NAM) model, Rapid Refresh (RAP) model and Global Forecast System (GFS) model to assess the performance of these models. The AMU developed an Excel-based tool that provides an objective method for the LWOs to compare the model-forecast upper-level winds to the KSC wind profiling radars and CCAFS AMPS observations to assess the model potential to accurately forecast changes in the upperlevel profile through the launch count. The AMU wrote Excel Visual Basic for Applications (VBA) scripts to automatically retrieve model point data for CCAFS (XMR) from the Iowa State University Archive Data Server (http://mtarchive.qeol.iastate.edu) and the 50 MHz, 915 MHz and AMPS observations from the NASA/KSC Spaceport Weather Data Archive web site (http://trmm.ksc.nasa.gov). The AMU then developed code in Excel VBA to automatically ingest and format the observations and model point data in Excel to ready the data for generating Excel charts for the LWO's. The resulting charts allow the LWOs to independently initialize the three models 0-hour forecasts against the observations to determine which is the best performing model and then overlay the model forecasts on time-matched observations during the launch countdown to further assess the model performance and forecasts. This paper will demonstrate integration of observed and predicted atmospheric conditions into a decision support tool and demonstrate how the GUI is implemented in operations.

Bauman, William H., III↗