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At least 271 records · Page 15

All sources NASA NTRS DOE OSTI

NASA NTRS1996

A Framework for Performing V&V within Reuse-Based Software Engineering

Verification and validation (V&V) is performed during application development for many systems, especially safety-critical and mission-critical systems. The V&V process is intended to discover errors, especially errors related to critical processing, as early as possible during the development process. Early discovery is important in order to minimize the cost and other impacts of correcting these errors. In order to provide early detection of errors, V&V is conducted in parallel with system development, often beginning with the concept phase. In reuse-based software engineering, however, decisions on the requirements, design and even implementation of domain assets can be made prior to beginning development of a specific system. In this case, V&V must be performed during domain engineering in order to have an impact on system development. This paper describes a framework for performing V&V within architecture-centric, reuse-based software engineering. This framework includes the activities of traditional application-level V&V, and extends these activities into domain engineering and into the transition between domain engineering and application engineering. The framework includes descriptions of the types of activities to be performed during each of the life-cycle phases, and provides motivation for the activities.

Addy, Edward 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 NTRS2002

Analysis of Salinity Intrusion in the San Francisco Bay-Delta using a GA- Optimized Neural Net, and Application of the Model to Prediction in the Elkhorn Slough Habitat

The San Francisco Bay Delta is a large hydrodynamic complex that incorporates the Sacramento and San Joaquin Estuaries, the Burman Marsh, and the San Francisco Bay proper. Competition exists for the use of this extensive water system both from the fisheries industry, the agricultural industry, and from the marine and estuarine animal species within the Delta. As tidal fluctuations occur, more saline water pushes upstream allowing fish to migrate beyond the Burman Marsh for breeding and habitat occupation. However, the agriculture industry does not want extensive salinity intrusion to impact water quality for human and plant consumption. The balance is regulated by pumping stations located alone the estuaries and reservoirs whereby flushing of fresh water keeps the saline intrusion at bay. The pumping schedule is driven by data collected at various locations within the Bay Delta and by numerical models that predict the salinity intrusion as part of a larger model of the system. The Interagency Ecological Program (IEP) for the San Francisco Bay/Sacramento-San Joaquin Estuary collects, monitors, and archives the data, and the Department of Water Resources provides a numerical model simulation (DSM2) from which predictions are made that drive the pumping schedule. A problem with this procedure is that the numerical simulation takes roughly 16 hours to complete a C:~ prediction. We have created a neural net, optimized with a genetic algorithm, that takes as input the archived data from multiple stations and predicts stage, salinity, and flow at the Carquinez Straits (at the downstream end of the Burman Marsh). This model seems to be robust in its predictions and operates much faster than the current numerical DSM2 model. Because the system is strongly tidal driven, we used both Principal Component Analysis and Fast Fourier Transforms to discover dominant features within the IEP data. We then filtered out the dominant tidal forcing to discover non-primary tidal effects, and used this to enhance the neural network by mapping input-output relationships in a more efficient manner. Furthermore, the neural network implicitly incorporates both the hydrodynamic and water quality models into a single predictive system. Although our model has not yet been enhanced to demonstrate improve pumping schedules, it has the possibility to support better decision-making procedures that may then be implemented by State agencies if desired. Our intention is now to use this model in the smaller Elkhorn Slough complex near Monterey Bay where no such hydrodynamic model currently exists. At the Elkhorn Slough, we are fusing the neural net model of tidally-driven flow with in situ flow data and airborne and satellite remote sensation data. These further constrain the behavior of the model in predicting the longer-term health and future of this vital estuary.

Thompson, David E.↗

NASA NTRS2001

Development and Validation of the Controller Acceptance Rating Scale (CARS): Results of Empirical Research

The measurement of operational acceptability is important for the development, implementation, and evolution of air traffic management decision support tools. The Controller Acceptance Rating Scale was developed at NASA Ames Research Center for the development and evaluation of the Passive Final Approach Spacing Tool. CARS was modeled after a well-known pilot evaluation rating instrument, the Cooper-Harper Scale, and has since been used in the evaluation of the User Request Evaluation Tool, developed by MITRE's Center for Advanced Aviation System Development. In this paper, we provide a discussion of the development of CARS and an analysis of the empirical data collected with CARS to examine construct validity. Results of intraclass correlations indicated statistically significant reliability for the CARS. From the subjective workload data that were collected in conjunction with the CARS, it appears that the expected set of workload attributes was correlated with the CARS. As expected, the analysis also showed that CARS was a sensitive indicator of the impact of decision support tools on controller operations. Suggestions for future CARS development and its improvement are also provided.

Lee, Katharine K.↗

NASA NTRS1996

Asynchronous Message Passing in the JPL Flight System Testbed

The flight mission simulation software in the Jet Propulsion Laboratory's Flight System Testbed (FST) is a heterogeneous, distributed system that is built on an interprocess communication model of asynchronous message passing rather than remote procedure calls (RPCs). The reasoning behind this design decision is discussed; the mechanism used to implement it (.

message passing RPC interprocess communication dis↗

NASA NTRS2010

Autonomous Flight Safety System

The Autonomous Flight Safety System (AFSS) is an independent self-contained subsystem mounted onboard a launch vehicle. AFSS has been developed by and is owned by the US Government. Autonomously makes flight termination/destruct decisions using configurable software-based rules implemented on redundant flight processors using data from redundant GPS/IMU navigation sensors. AFSS implements rules determined by the appropriate Range Safety officials.

Simpson, James↗

NASA NTRS2014

Managing Research in a Risk World

The Office of Chief Medical Officer (OCHMO) owns all human health and performance risks managed by the Human System Risk Board (HSRB). While the HSRB manages the risks, the Human Research Program (HRP) manages the research portion of the overall risk mitigation strategy for these risks. The HSRB manages risks according to a process that identifies and analyzes risks, plans risk mitigation and tracks and reviews the implementation of these strategies according to its decisions pertaining to the OCHMO risk posture. HRP manages risk research work using an architecture that describes evidence-based risks, gaps in our knowledge about characterizing or mitigating the risk, and the tasks needed to produce deliverables to fill the gaps and reduce the risk. A planning schedule reflecting expected research milestones is developed, and as deliverables and new evidence are generated, research progress is tracked via the Path to Risk Reduction (PRR) that reflects a risk's research plan for a design reference mission. HRP's risk research process closely interfaces with the HSRB risk management process. As research progresses, new deliverables and evidence are used by the HSRB in conjunction with other operational and non-research evidence to inform decisions pertaining to the likelihood and consequence of the risk and risk posture. Those decisions in turn guide forward work for research as it contributes to overall risk mitigation strategies. As HRP tracks its research work, it aligns its priorities by assessing the effectiveness of its contributions and maintaining specific core competencies that would be invaluable for future work for exploration missions.

Anton, W.↗

NASA NTRS2015

Tropospheric Emissions: Monitoring of Pollution Overview

TEMPO is now well into its implementation phase, having passed both its Key Decision Point C and the Critical Design Review (CDR) for the instrument. The CDR for the ground systems will occur in March 2016 and the CDR for the Mission component at a later date, after the host spacecraft has been selected. TEMPO is on schedule to measure atmospheric pollution for greater North America from space using ultraviolet and visible spectroscopy. TEMPO measures from Mexico City to the Canadian oil sands, and from the Atlantic to the Pacific, hourly and at high spatial resolution. TEMPO provides a tropospheric measurement suite that includes the key elements of tropospheric air pollution chemistry. Measurements are from geostationary (GEO) orbit, to capture the inherent high variability in the diurnal cycle of emissions and chemistry. The small product spatial footprint resolves pollution sources at sub-urban scale. Together, this temporal and spatial resolution improves emission inventories, monitors population exposure, and enables effective emission-control strategies. TEMPO takes advantage of a GEO host spacecraft to provide a modest cost mission that measures the spectra required to retrieve O3, NO2, SO2, H2CO, C2H2O2, H2O, aerosols, cloud parameters, and UVB radiation. TEMPO thus measures the major elements, directly or by proxy, in the tropospheric O3 chemistry cycle. Multi-spectral observations provide sensitivity to O3 in the lowermost troposphere, substantially reducing uncertainty in air quality predictions by 50 percent. TEMPO quantifies and tracks the evolution of aerosol loading. It provides near-real-time air quality products that will be made widely, publicly available. TEMPO provides much of the atmospheric measurement capability recommended for GEO-CAPE in the 2007 National Research Council Decadal Survey, Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond. Instruments from Europe (Sentinel 4) and Asia (GEMS) will form parts of a global GEO constellation for pollution monitoring later this decade, with a major focus on intercontinental pollution transport. TEMPO will launch at a prime time to be a component of this constellation.

Chance, Kelly↗

NASA NTRS2019

An Initial Analysis of Automating Conjunction Assessment and Collision Avoidance Planning in Space Traffic Management

We introduce a framework that automates the process of assessing potential satellite conjunctions in space, and generating collision avoidance maneuvers to support mitigation efforts within a novel space traffic management (STM) architecture. A software implementation of the framework was developed in a MATLAB-STK integrated environment, however, the concept and framework is agnostic to the language or environment. The software pulls from existing catalogs of spaceborne objects and ingests user-defined parameters to produce conjunction data, which could potentially aid collision avoidance planning in the STM architecture. The utility of the software in maneuver planning and exploring a performance-based tradespace of actions is demonstrated using three example cases: one-to-one conjunction, one-versus-four conjunctions, and a near head-on collision. The framework also provides a test-bed for the use of application programming interfaces (APIs) to demonstrate machine-to-machine communication between entities in our proposed STM architecture. Results from this software implementation are expected to aid distributed decision-making among various stakeholders, and inform efficient, autonomous, structured but flexible concept of operations within STM.

Space Systems Engineering↗

NASA NTRS2018

Assessment of Potential Mars Relay Network Enhancements

In anticipation of increased demands on Mars relay services, including planned arrivals of NASA’s InSight Lander in November 2018, and of NASA’s Mars 2020 rover and ESA’s ExoMars Rover & Surface Platform mission in Feb-Mar.2021, we have assessed a number of potential modifications and upgrades to Mars relay orbiters and quantified their impacts in terms of key relay support metrics, to support NASA and ESA programmatic decisions. Specific areas of investigation include: 1) implementation of “split-pass” relay capability for support to collocated landers, 2) modifications of the extended mission orbit for the Mars Atmosphere and Volatile EvolutioN Mission (MAVEN), and 3) introduction of Low-Density Parity Check (LDPC) coding. We report here on each of these potential upgrades, quantify the performance implications each would have on future Mars relay services in the context of future mission support scenarios, and provide a status on implementation.

Wenkert, Daniel↗

NASA NTRSDate not supplied

Systems Health Management and Prognostics Approaches for Electric Aircrafts

As more and more electric vehicles emerge in our daily operation progressively, a very critical challenge lies in the prediction of remaining driving flying time/distance for the flying vehicles. This information is important, particularly in the case of auto vehicles, because such vehicles can become self-aware, autonomously compute its own capabilities, and identify how to best plan and successfully complete vehicular missions safely. In case of electric aircrafts, computing the remaining flying time is also safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Latest achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision-making. A systematic prediction framework is implemented to identify all possible sources of uncertainty, quantify each of them individually, and mathematically estimate their combined effect on the system-level quantity of interest, in this case, the remaining flying time/distance of the unmanned aircraft. Note - This presentation contains all previously published information.

Systems Health Managent↗

NASA NTRSDate not supplied

Health Monitoring and Prognostics for Electric Aircrafts

Systems Health Managent↗

NASA NTRS2023

Evaluation of a Regional Crop Model Implementation for Sub-National Yield Assessments in Kenya

CONTEXT: Cropping system models can be used to both assess regional food security and to monitor and predict agricultural drought. Agriculture in Kenya is extremely important to both the economy and food security of the country. OBJECTIVE: This study evaluated a regional implementation of a widely used crop model, the Decision Support System for Agrotechnology Transfer (DSSAT), within a coupled modeling framework, the Regional Hydrologic Extremes Assessment System (RHEAS), over Kenya. The goal of this study was to assess the ability of RHEAS to simulate the annual variability of maize yields at the county level and evaluate the uncertainty inherent in the model and inputs. METHODS: The RHEAS system implements a stochastic ensemble approach to account for field scale variabilities in crop management practices and underlying soil and weather conditions. Satellite-derived datasets were used to evaluate the land surface component of the system and seasonally disaggregated yield for 5 years was used to assess the performance of the cropping system model. RESULTS AND CONCLUSIONS: The median correlation between RHEAS and satellite-derived soil moisture and evapotranspiration estimates were 0.78, and 0.51, respectively, indicating that the model is able to capture the key drivers of the hydrological budget. Overall, RHEAS simulated yearly yield variations with a median correlation of 0.7 with reported yields, with the best performance in the short rains season. However, across both seasons, the RHEAS model was positively biased on the order of ~1.6 MT/ha. The overall median unbiased RMSE was 0.66 MT/ha. The RHEAS system shows skill at simulating extreme departures in anomalies, and a majority of the time (62.5%) the reported yields fall within the interquartile range of the simulations. SIGNIFICANCE: One of the most important areas of improvement for the next generation of agricultural data and models is to better understand and communicate the inherent uncertainties. This is especially critical in data-limited regions. Here we present a modeling system and its implementation that begins to address these concerns. We demonstrate the ability to simulate broad trends in yields at the county level for sub-annual yields with skills that commensurate previous national/annual level studies.

Crop model↗

NASA NTRS1973

Radar studies of arctic ice and development of a real-time Arctic ice type identification system

Studies were conducted to develop a real-time Arctic ice type identification system. Data obtained by NASA Mission 126, conducted at Pt. Barrow, Alaska (Site 93) in April 1970 was analyzed in detail to more clearly define the major mechanisms at work affecting the radar energy illuminating a terrain cell of sea ice. General techniques for reduction of the scatterometer data to a form suitable for application of ice type decision criteria were investigated, and the electronic circuit requirements for implementation of these techniques were determined. Also, consideration of circuit requirements are extended to include the electronics necessary for analog programming of ice type decision algorithms. After completing the basic circuit designs a laboratory model was constructed and a preliminary evaluation performed. Several system modifications for improved performance are suggested. (Modified author abstract)

Rouse, J. W., Jr.↗

NASA NTRS2010

MODIS Snow Cover Mapping Decision Tree Technique: Snow and Cloud Discrimination

Accurate mapping of snow cover continues to challenge cryospheric scientists and modelers. The Moderate-Resolution Imaging Spectroradiometer (MODIS) snow data products have been used since 2000 by many investigators to map and monitor snow cover extent for various applications. Users have reported on the utility of the products and also on problems encountered. Three problems or hindrances in the use of the MODIS snow data products that have been reported in the literature are: cloud obscuration, snow/cloud confusion, and snow omission errors in thin or sparse snow cover conditions. Implementation of the MODIS snow algorithm in a decision tree technique using surface reflectance input to mitigate those problems is being investigated. The objective of this work is to use a decision tree structure for the snow algorithm. This should alleviate snow/cloud confusion and omission errors and provide a snow map with classes that convey information on how snow was detected, e.g. snow under clear sky, snow tinder cloud, to enable users' flexibility in interpreting and deriving a snow map. Results of a snow cover decision tree algorithm are compared to the standard MODIS snow map and found to exhibit improved ability to alleviate snow/cloud confusion in some situations allowing up to about 5% increase in mapped snow cover extent, thus accuracy, in some scenes.

Riggs, George A.↗

DOE OSTI2026

Concise Guide on Hydrogen for Ports

This Concise Guide on Hydrogen for Ports provides port stakeholders with a comprehensive overview of hydrogen as an emerging energy solution for maritime and land-based operations. It explains hydrogen’s fundamental properties, production pathways, and emissions profiles, while highlighting its potential benefits and associated challenges. The document explores practical applications for hydrogen at ports alongside considerations for storage, delivery, and integration. It also outlines implementation frameworks, stakeholder engagement approaches, and risk assessment methodologies to support informed decision-making. The guide aims to provide a pathway forward for ports that choose to consider implementation of hydrogen technology at their facility.

08 HYDROGEN↗

DOE OSTI2022

Proposed Products to Support Shelter-Evacuation Decision Making in the Event of a Nuclear Detonation

Response strategies implemented in the first few hours to days after a nuclear detonation on the US homeland may save more than 100,000 lives. Effective planning and pre-event capability development can increase the response efficacy and so the number of lives saved. During such an event, the US Department of Defense, Joint Task Force Civil Support (DoD JTF-CS) provides command and control for the DoD forces supporting civil authority response operations. Among other activities, JTF-CS expects to support FEMA as well as State and local agencies in shelter and evacuation response activities. JTF-CS currently uses a manual method to generate evacuation decision making products. This method compares the dose that would be (a) acquired remaining at a given location to that (b) acquired during evacuation along a small number of routes. In these products, evacuation may be warranted when the projected “remain” dose is greater than the “evacuate” dose. This method only provides a limited consideration of the protection buildings provide their occupants. To inform the JTF-CS nuclear detonation response, the DoD Defense Threat Reduction Agency (DTRA) has tasked Lawrence Livermore National Laboratory (LLNL) to design a set of planning and response products to support shelter-evacuation activities. This report documents these products to facilitate DTRA and JTF-CS planning efforts. To provide context, we also provide appendices that summarize US planning guidance response zones, early (<72 h) response strategies, and other key topics.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2023

Development of a Technical, Economic, and Risk Assessment Tool for the Evaluation of Work Reduction Opportunities

Efficient and cost-effective operation of a nuclear power plant (NPP) is essential to ensuring long-term economical and safe operation. Multiple cost saving opportunities exist, referred to here as work reduction opportunities (WRO). These WROs reduce plant operating costs by employing various cost-effective strategies (e.g., implementation of modern technologies). Identifying and objectively screening WROs is an essential task to help reduce overall costs. However, there is no comprehensive framework for assessing WROs in the nuclear industry and evaluating their impact on plant operations. This report presents a novel framework for systematically evaluating WROs from a technical, economic, and risk perspective. As NPPs continue to add new technology and implement modernization strategies into their current processes, potential WROs are commonly identified. Although most WROs have the potential to reduce costs, not all opportunities will result in significant cost savings due to unforeseen risks, large implementation costs, or benefits that fall short of expectations. Examples of this can be the result of a technology that is not fully developed, uncertainty in the amount of cost reduction, or difficulties introducing a new process into an organization. These uncertainties can manifest several ways and can result in a WRO with limited cost savings or even a loss of investment. The framework developed emphasizes the importance of effectively screening the WROs from a holistic perspective to objectively identify inefficiencies and ensure a positive impact to the organization. This report presents the Technical, Economic, and Risk Assessment (TERA) as a key methodology for the screening and evaluation of potential WROs. The TERA framework begins with a screening phase where the process is examined through a hybrid combination of Lean Six Sigma and Integrated Operations for Nuclear (ION) guiding principles. This framework examines the current processes using the Lean Six Sigma SIPOC (Suppliers, Inputs, Process, Outputs, Consumers) methodology but retains the ION key elements of People, Technology, Process, and Governance as important factors to the nuclear decision-making process. By combining the principles of Lean Six Sigma and ION, the developed screening process is specific to the nuclear industry in that it systematically evaluates WROs in order to implement new technology that is comprehensively evaluated. The TERA begins by mapping current processes as they relate to WROs and examining the inefficiencies. Furthermore, the created process map can be used to identify and evaluate potential solutions. Using key performance indicators (KPIs), the TERA evaluates each area—technology, economics, and risk—for uncertainties and to perform cost-benefit analysis. The results of the TERA are important KPIs that allow for an evaluation of different processes and technology implementations. This assessment enables decision-makers to compare various WROs based on metrics and then make informed decisions for which opportunity to implement first. This research includes not only the creation of the TERA framework, but also the evaluation of its performance. A case study for screening potential WROs at Southern Nuclear Company is presented that utilizes the TERA methodology. Through the use of TERA, various WROs were screened, and the solutions evaluated for cost-benefit expectations. The report concludes by summarizing the overall effort and implications for utility modernization. The performance of the screening and TERA are discussed as well as the impact on the nuclear industry. The TERA process enables utilities to evaluate and inform investment decisions for WROs and mitigate any potential risks. Through this research, we provide utilities with a valuable framework to optimize operations, reduce costs, and drive continuous process improvement.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗