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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Human-Interaction Challenges in UAV-Based Autonomous Surveillance

Autonomous UAVs provide a platform for intelligent surveillance in application domains ranging from security and military operations to scientific information gathering and land management. Surveillance tasks are often long duration, requiring that any approach be adaptive to changes in the environment or user needs. We describe a decision- theoretic model of surveillance, appropriate for use on our autonomous helicopter, that provides a basis for optimizing the value of information returned by the UAV. From this approach arise a range of challenges in making this framework practical for use by human operators lacking specialized knowledge of autonomy and mathematics. This paper describes our platform and approach, then describes human-interaction challenges arising from this approach that we have identified and begun to address.

Freed, Michael↗
NASA NTRS2017

A Machine Learning Concept for DTN Routing

This paper discusses the concept and architecture of a machine learning based router for delay tolerant space networks. The techniques of reinforcement learning and Bayesian learning are used to supplement the routing decisions of the popular Contact Graph Routing algorithm. An introduction to the concepts of Contact Graph Routing, Q-routing and Naive Bayes classification are given. The development of an architecture for a cross-layer feedback framework for DTN (Delay-Tolerant Networking) protocols is discussed. Finally, initial simulation setup and results are given.

Delay Tolerant Networks↗
NASA NTRS2017

Modelling the Risks Remotely Piloted Aircraft Pose to People on the Ground

Worldwide there is much e ort being directed towards the development of a framework of air- worthiness regulations for remotely piloted aircraft systems (RPAS). It is now broadly accepted that regulations should have a strong foundation in, and traceability to, the management of the safety risks. Existing risk models for RPAS operations do not provide a simple means for incorporating the wide range of technical and operational controls into the risk analysis and evaluation processes. This paper describes a new approach for modelling and evaluating the risks associated with RPAS operations near populous areas based on the barrier bow tie (BBT) model. A BBT model is used to structure the underlying risk management problem. The model focuses risk analysis, evaluation, and decision making activities on the devices, people, and processes that can be employed to reduce risk. The BBT model and a comprehensive set of example risk controls are presented. The general model can be applied to any RPAS operation. The foundations for quantitative and qualitative assessments using a BBT model are also presented. The modelling and evaluation framework is illustrated through its application to a case-study rotary wing RPAS for two operational scenarios. The model can be used as a basis for determining airworthiness certification requirements for RPAS.

Barrier bow tie model↗
NASA NTRS2012

Object-Oriented Bayesian Networks (OOBN) for Aviation Accident Modeling and Technology Portfolio Impact Assessment

The concern for reducing aviation safety risk is rising as the National Airspace System in the United States transforms to the Next Generation Air Transportation System (NextGen). The NASA Aviation Safety Program is committed to developing an effective aviation safety technology portfolio to meet the challenges of this transformation and to mitigate relevant safety risks. The paper focuses on the reasoning of selecting Object-Oriented Bayesian Networks (OOBN) as the technique and commercial software for the accident modeling and portfolio assessment. To illustrate the benefits of OOBN in a large and complex aviation accident model, the in-flight Loss-of-Control Accident Framework (LOCAF) constructed as an influence diagram is presented. An OOBN approach not only simplifies construction and maintenance of complex causal networks for the modelers, but also offers a well-organized hierarchical network that is easier for decision makers to exploit the model examining the effectiveness of risk mitigation strategies through technology insertions.

Shih, Ann T.↗
NASA NTRSDate not supplied

Informing Disaster Response: An Introduction to the NASA Disaster Response Coordination System

Satellite observations provide information about the Earth that can be critical to building situational awareness and filling in data gaps during disaster response. The National Aeronautics and Space Administration (NASA) Earth Science Division’s Disasters Program aims to advance Earth science data and information to support management decisions that prevent or mitigate the impacts of disasters. In support of this goal, NASA’s Disaster Response Coordination System (DRCS) manages a One-NASA approach to coordinate and mobilize the Agency’s assets and expertise to provide geospatial information during disasters. The purpose of the DRCS is to advance the utility of Earth observation information for supporting disaster response decision support, build skilled and effective response communities through improved coordination, engagement, and learning, and reduce impact to lives and livelihoods by empowering communities to respond to disasters more effectively. The DRCS employs a user-centered, activation framework that begins with direct requests from responders and ends with after-action assessments that feed lessons learned and process improvements. This poster will introduce the DRCS model and approach to expanding the use of Earth observations and geospatial information to support disaster response, share use cases for recent event activations, and highlight initial lessons learned.

Disaster Response↗
NASA NTRS2012

Cognitive Systems Modeling and Analysis of Command and Control Systems

Military operations, counter-terrorism operations and emergency response often oblige operators and commanders to operate within distributed organizations and systems for safe and effective mission accomplishment. Tactical commanders and operators frequently encounter violent threats and critical demands on cognitive capacity and reaction time. In the future they will make decisions in situations where operational and system characteristics are highly dynamic and non-linear, i.e. minor events, decisions or actions may have serious and irreversible consequences for the entire mission. Commanders and other decision makers must manage true real time properties at all levels; individual operators, stand-alone technical systems, higher-order integrated human-machine systems and joint operations forces alike. Coping with these conditions in performance assessment, system development and operational testing is a challenge for both practitioners and researchers. This paper reports on research from which the results led to a breakthrough: An integrated approach to information-centered systems analysis to support future command and control systems research development. This approach integrates several areas of research into a coherent framework, Action Control Theory (ACT). It comprises measurement techniques and methodological advances that facilitate a more accurate and deeper understanding of the operational environment, its agents, actors and effectors, generating new and updated models. This in turn generates theoretical advances. Some good examples of successful approaches are found in the research areas of cognitive systems engineering, systems theory, and psychophysiology, and in the fields of dynamic, distributed decision making and naturalistic decision making.

Norlander, Arne↗
NASA NTRS2006

Intertwining Risk Insights and Design Decisions

The state of systems engineering is such that a form of early and continued use of risk assessments is conducted (as evidenced by NASA's adoption and use of the 'Continuous Risk Management' paradigm developed by SEI). ... However, these practices fall short of theideal: (1) Integration between risk assessment techniques and other systems engineering tools is weak. (2) Risk assessment techniques and the insights they yield are only informally coupled to design decisions. (3) Individual riskassessment techniques lack the mix of breadth, fidelity and agility required to span the gamut of the design space. In this paper we present an approach that addresses these shortcomings. The hallmark of our approach is a simple representation comprising objectives (what the system is to do), risks (whose occurrence would detract from attainment of objectives) and activities (a.k.a. 'mitigations') that, if performed, will decrease those risks. These are linked to indicate by how much a risk would detract from attainment of an objective, and by how much an activity would reduce a risk. The simplicity of our representational framework gives it the breadth to encompass the gamut of the design space concerns, the agility to be utilized in even the earliest phases of designs, and the capability to connect to system engineering models and higher-fidelity risk tools. It is through this integration that we address the shortcomings listed above, and so achieve the intertwining between risk insights and design decisions needed to guide systems engineering towards superior final designs while avoiding costly rework to achieve them. The paper will use an example, constructed to be representative of space mission design, to illustrate our approach.

systems engineering↗
NASA NTRS2005

Automated Planning and Scheduling for Space Mission Operations

Research Trends: a) Finite-capacity scheduling under more complex constraints and increased problem dimensionality (subcontracting, overtime, lot splitting, inventory, etc.) b) Integrated planning and scheduling. c) Mixed-initiative frameworks. d) Management of uncertainty (proactive and reactive). e) Autonomous agent architectures and distributed production management. e) Integration of machine learning capabilities. f) Wider scope of applications: 1) analysis of supplier/buyer protocols & tradeoffs; 2) integration of strategic & tactical decision-making; and 3) enterprise integration.

scheduling↗
NASA NTRSDate not supplied

NASA ESTO Advanced Information Systems Technology (AIST)

"(Only Talk/No Publication) NASA’s Advanced Information Systems Technology (AIST) Program identifies, develops, and supports adoption of software and information systems, as well as novel computer science technologies expected to be needed by the Earth Science Division in the 5-10-year timeframe. This presentation gives an overview of the AIST Program. AIST’s previous thrusts have been New Observing Strategies (NOS) and Analytic Collaborative Frameworks (ACF). The current vision is to connect these two thrusts and integrate them into the larger concept of Earth System Digital Twins (ESDT). To implement this new vision, the AIST Program is focusing on technologies and innovative concepts with three main objectives: O1. Enable new observation measurements and new observing systems design and operations through intelligent, timely, dynamic, and coordinated distributed sensing; O2. Enable agile science investigations that fully utilize the large amount of diverse observations using advanced analytic tools, visualizations, and computing environments, and that interact seamlessly with relevant observing systems; O3. Enable the development of integrated Earth Science frameworks that mirror the Earth with state-of-the-art models (Earth system models and others), timely and relevant observations, and analytic tools. This thrust will provide technology for enabling near- and long-term science and policy decisions (“science decisions” including planning for the acquisition of new measurements; the development of new models or science analysis; the integration of Earth observations in novel ways; applications to inform choices, support decisions, and guide actions for societal benefit; etc.)."

Mathematical and Computer Sciences (General)↗
NASA NTRS2023

Advanced Information Systems Technology (AIST) Overview & Current and Recent Projects

"NASA's Advanced Information Systems Technology (AIST) Program identifies, develops, and supports adoption of software and information systems, as well as novel computer science technologies expected to be needed by the Earth Science Division in the 5-10-year timeframe. Overall, the AIST Program is focusing on advanced technologies and innovative concepts with three main objectives: O1. Enable new observation measurements and new observing systems design and operations through intelligent, timely, dynamic, and coordinated distributed sensing; O2. Enable agile science analyses that fully utilize the large amount of diverse observations using advanced analytic tools, visualizations, and computing environments, and that interact seamlessly with relevant observing systems; O3. Enable the development of integrated Earth Science frameworks that mirror the Earth with state-of-the-art models (Earth system models and others), timely and relevant observations, and analytic tools. This thrust will provide technology for enabling near- and long-term science and policy decisions (""""science decisions"""" including planning for the acquisition of new measurements; the development of new models or science analysis; the integration of Earth observations in novel ways; applications to inform choices, support decisions, and guide actions for societal benefit; etc.). AIST objectives aim at optimizing Earth Science mission return – NOS from an observation point of view and ACF/ESDT from an information analysis and utilization point of view. The assets and data accessed and utilized in these systems may come from NASA and non-NASA sources. "

Earth Science Remote Sensing; Information Systems↗
NASA NTRS2020

Prognostics for Systems Health Management - Model and Hybrid Based Approaches. Where are We Heading?

To facilitate and solve the prediction problem, awareness of the current state and health of the system is key, since it is necessary to perform condition-based system health predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditional. In case of next generation electric aircrafts, computing remaining flying time is safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. In order to tackle and solve the prediction problem, it is essential to have awareness of the current health state of the system, especially since it is necessary to perform condition-based predictions. To be able to predict the future state of the system, it is also required to possess knowledge of the current and future operational conditions and flight profiles for accurate estimation of end-of-discharge (EOD) for the batteries. Similar framework can be implemented to other complex systems and subsystems. Our research approach is to develop a system level health monitoring safety indicator which runs estimation and prediction algorithms to estimate remaining useful life predictions at system, subsystem swell as component levels. Given models of the current and future system behavior, a general approach of model-based prognostics is discussed as a solution to the prediction problem and further for decision making. Data driven prognostics approaches have been equally used with good results in the past, where respective approaches have their own challenges to tackle. This limits their applicability to complex real-world domains: (a) high complexity or incompleteness of physics-based models and (b) limited representativeness of the training dataset for data-driven models. With the advent of internet of things for data collection and increased use of ML algorithms, hybrid approaches are the next avenue to reduce the challenges and achieve better results. An hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety critical systems is presented. In this framework, we use physics-based performance models to infer unobservable model parameters related to the system's components health solving a calibration problem.

Prognostics↗
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 NTRS2023

A Multi-Satellite Framework to Rapidly Evaluate Extreme Biosphere Cascades: The Western US 2021 Drought and Heatwave

The increasing frequency and intensity of climate extremes and complex ecosystem responses motivate the need for integrated observational studies at low-latency to determine biosphere responses and carbon-climate feedbacks. Here, we develop a satellite-based rapid attribution workflow and demonstrate its use at a 1–2-month latency to attribute drivers of the carbon cycle feedbacks during the 2020-2021 Western US drought and heatwave. In the first half of 2021, concurrent negative photosynthesis anomalies and large positive column CO 2 anomalies were detected with satellites. Using a simple atmospheric mass balance approach, we estimate a surface carbon efflux anomaly of 132 TgC in June 2021, a magnitude corroborated 28 independently with a dynamic global vegetation model. Integrated satellite observations of hydrologic processes, representing the soil-plant-atmosphere continuum (SPAC), show that these surface carbon flux anomalies are largely due to substantial reductions in photosynthesis because of a spatially widespread moisture-deficit propagation through the SPAC between 2020 and 2021. A causal model indicates deep soil moisture stores partially drove photosynthesis, maintaining its values in 2020 and driving its declines throughout 2021. The causal model also suggests legacy effects may have amplified photosynthesis deficits in 2021 beyond the direct effects of environmental forcing. The integrated, observation framework presented here provides a valuable first assessment of a biosphere extreme response and an independent testbed for improving drought propagation and mechanisms in models. The rapid identification of extreme carbon anomalies and hotspots can also aid mitigation and adaptation decisions.

Causal model↗
NASA NTRS2023

Earth Observations into Action: Systemic Integration of Earth Observation Applications into National Risk Reduction Decision Structures

As stated in the United Nations Global Assessment Report 2022 Concept Note, decision makers everywhere need data and statistics that are accurate, timely, sufficiently disaggregated, relevant, accessible, and easy to use. The purpose of this paper is to demonstrate scalable and replicable methods to advance and integrate the use of Earth observation, specifically ongoing efforts within the Group on Earth Observations Work Programme and the Committee on Earth Observation Satellites Work Plan, to support risk-informed decision making, based on documented national and subnational needs and requirements.

earth observations↗
NASA NTRS2002

Structural Weight Estimation for Launch Vehicles

This paper describes some of the work in progress to develop automated structural weight estimation procedures within the Vehicle Analysis Branch (VAB) of the NASA Langley Research Center. One task of the VAB is to perform system studies at the conceptual and early preliminary design stages on launch vehicles and in-space transportation systems. Some examples of these studies for Earth to Orbit (ETO) systems are the Future Space Transportation System [1], Orbit On Demand Vehicle [2], Venture Star [3], and the Personnel Rescue Vehicle[4]. Structural weight calculation for launch vehicle studies can exist on several levels of fidelity. Typically historically based weight equations are used in a vehicle sizing program. Many of the studies in the vehicle analysis branch have been enhanced in terms of structural weight fraction prediction by utilizing some level of off-line structural analysis to incorporate material property, load intensity, and configuration effects which may not be captured by the historical weight equations. Modification of Mass Estimating Relationships (MER's) to assess design and technology impacts on vehicle performance are necessary to prioritize design and technology development decisions. Modern CAD/CAE software, ever increasing computational power and platform independent computer programming languages such as JAVA provide new means to create greater depth of analysis tools which can be included into the conceptual design phase of launch vehicle development. Commercial framework computing environments provide easy to program techniques which coordinate and implement the flow of data in a distributed heterogeneous computing environment. It is the intent of this paper to present a process in development at NASA LaRC for enhanced structural weight estimation using this state of the art computational power.

Cerro, Jeff↗
NASA NTRS1993

MARSNET: A European network of stations on the surface of Mars

Following an ESA preliminary study on the possible areas of European participation in the future international exploration of Mars and an ESA call for ideas of new missions, MARSNET, a network of small surface stations, was selected for further in-depth scientific and technical assessment studies as a potential European contribution to such exploration. Subsequently, the MARSNET phase A studies started in the autumn of 1991. The industrial kickoff took place in early January 1992, following the tender evaluation and the decision to select the Aerospatiale-led consortium including Dornier, Alcatel, Laben, and Etca to perform the industrial studies. The phase A studies ended in early 1993. However, critical items such as an instrument deployment device continue to be studied in the framework of ESA's Technology Research Program. The MARSNET mission consists of a network of three semihard landers to be placed on the Martian surface, several thousand kilometers apart, thus defining a regional/global seismological and meteorological network in the Tharsis region. The small stations would be targeted for landing at scientifically interesting sites in this region of Mars, which is the most likely area to still show tectonic activity; this would allow the seismometers to acquire data for the determination of the internal structure of the planet. Landing site geology and geochemistry will also be studied.

Chicarro, A. F.↗
NASA NTRS2018

Cooperative Automation Supporting Pilot-Dispatch Negotiation of Enroute Trajectory Change Requests

The advent of advanced technologies in communication, navigation, and surveillance is enabling more integration between the aircraft and the ground systems in managing air traffic operations. As a result, automation has evolved to provide the flight crew, air traffic controllers, and traffic flow managers with capabilities for collaborating on information access, analysis, and decision making. In this paper, we investigate different cooperative schemes between these agents, supported by automation, in managing dynamic trajectory changes while the flight is en route to improve flight and system performance. The analysis was conducted using an abstract cognitive tasking framework to identify trajectory change tasks independently from the agent performing them. Cooperation schemes were then derived by assessing different levels of cooperation on each task between the air and ground agents and their automation. The assessment was based on which automation-supported agent is more capable of performing the task and the expected benefit mechanisms that result from cooperating. The cooperation schemes were compared based on a qualitative, but objective, assessment of the benefits expected from cooperation.

air-ground integration↗
NASA NTRS2014

An Integrated Reliability and Physics-Based Risk Modeling Approach for Assessing Human Spaceflight Systems

This paper presents an integrated reliability and physics-based risk modeling approach for assessing human spaceflight systems. The approach is demonstrated using an example, end-to-end risk assessment of a generic-crewed space transportation system during a reference mission to the International Space Station. The behavior of the system is modeled using analysis techniques from multiple disciplines in order to properly capture the dynamic time- and state- dependent consequences of failures encountered in different mission phases. We discuss how to combine traditional reliability analyses with Monte Carlo simulation methods and physics-based engineering models to produce loss-of- mission and loss-of-crew risk estimates supporting risk-based decision-making and requirement verification. This approach facilitates risk-informed design by providing more realistic representation of system failures and interactions; identifying key risk-driving sensitivities, dependencies, and assumptions; and tracking multiple figures of merit within a single, responsive assessment framework that can readily incorporate evolving design information throughout system development.

Risk assessment↗