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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Space Radiation Cancer Risks and Uncertainities for Different Mission Time Periods

Space radiation consists of solar particle events (SPEs), comprised largely of medium energy protons (less than several hundred MeV); and galactic cosmic ray (GCR), which includes high energy protons and high charge and energy (HZE) nuclei. For long duration missions, space radiation presents significant health risks including cancer mortality. Probabilistic risk assessment (PRA) is essential for radiation protection of crews on long term space missions outside of the protection of the Earth s magnetic field and for optimization of mission planning and costs. For the assessment of organ dosimetric quantities and cancer risks, the particle spectra at each critical body organs must be characterized. In implementing a PRA approach, a statistical model of SPE fluence was developed, because the individual SPE occurrences themselves are random in nature while the frequency distribution of SPEs depends strongly upon the phase within the solar activity cycle. Spectral variability of SPEs was also examined, because the detailed energy spectra of protons are important especially at high energy levels for assessing the cancer risk associated with energetic particles for large events. An overall cumulative probability of a GCR environment for a specified mission period was estimated for the temporal characterization of the GCR environment represented by the deceleration potential (theta). Finally, this probabilistic approach to space radiation cancer risk was coupled with a model of the radiobiological factors and uncertainties in projecting cancer risks. Probabilities of fatal cancer risk and 95% confidence intervals will be reported for various periods of space missions.

Kim,Myung-Hee Y.↗
NASA NTRS2013

Adaptive Sensing of Time Series with Application to Remote Exploration

We address the problem of adaptive informationoptimal data collection in time series. Here a remote sensor or explorer agent throttles its sampling rate in order to track anomalous events while obeying constraints on time and power. This problem is challenging because the agent has limited visibility -- all collected datapoints lie in the past, but its resource allocation decisions require predicting far into the future. Our solution is to continually fit a Gaussian process model to the latest data and optimize the sampling plan on line to maximize information gain. We compare the performance characteristics of stationary and nonstationary Gaussian process models. We also describe an application based on geologic analysis during planetary rover exploration. Here adaptive sampling can improve coverage of localized anomalies and potentially benefit mission science yield of long autonomous traverses.

artificial intelligence↗
NASA NTRS2017

Minerva: User-Centered Science Operations Software Capability for Future Human Exploration

In June of 2016, the Biologic Analog Science Associated with Lava Terrains (BASALT) research project conducted its first field deployment, which we call BASALT-1. BASALT-1 consisted of a science-driven field campaign in a volcanic field in Idaho as a simulated human mission to Mars. Scientists and mission operators were provided a suite of ground software tools that we refer to collectively as Minerva to carry out their work. Minerva provides capabilities for traverse planning and route optimization, timeline generation and display, procedure management, execution monitoring, data archiving, visualization, and search. This paper describes the Minerva architecture, constituent components, use cases, and some preliminary findings from the BASALT-1 campaign.

Deans, Matthew↗
NASA NTRS2017

Minerva: User-Centered Science Operations Software Capability for Future Human Exploration

In June of 2016, the Biologic Analog Science Associated with Lava Terrains (BASALT) research project conducted its first field deployment, which we call BASALT-1. BASALT-1 consisted of a science-driven field campaign in a volcanic field in Idaho as a simulated human mission to Mars. Scientists and mission operators were provided a suite of ground software tools that we refer to collectively as Minerva to carry out their work. Minerva provides capabilities for traverse planning and route optimization, timeline generation and display, procedure management, execution monitoring, data archiving, visualization, and search. This paper describes the Minerva architecture, constituent components, use cases, and some preliminary findings from the BASALT-1 campaign.

Deans, Matthew↗
NASA NTRS2019

Developing a Community of Practice for Applied Uses of Future PACE Data to Address Marine Food Security Challenges

External interaction:The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission will include a hyperspectral imaging radiometer to advance ecosystem monitoring beyond heritage retrievals of the concentration of surface chlorophyll and other traditional ocean color variables, offering potential for novel science and applications. PACE is the first NASA ocean color mission to occur under the agency's new and evolving effort to directly engage practical end users prior to satellite launch to increase adoption of this freely available data toward societal challenges. Here we describe early efforts to engage a community of practice around marine food-related resource management, business decisions, and policy analysis. Obviously one satellite cannot meet diverse end user needs at all scales and locations, but understanding downstream needs helps in the assessment of information gaps and planning how to optimize the unique strengths of PACE data in combination with the strengths of other satellite retrievals, in situ measurements, and models. Higher spectral resolution data from PACE can be fused with information from satellites with higher spatial or temporal resolution, plus other information, to enable identification and tracking of new marine biological indicators to guide sustainable management. Accounting for the needs of applied researchers as well as non-traditional users of satellite data early in the PACE mission process will ultimately serve to broaden the base of informed users and facilitate faster adoption of the most advanced science and technology toward the challenge of mitigating food insecurity.

Schollaert Uz, Stephanie↗
NASA NTRS2022

The Scientific Importance of Returning Airfall Dust as a Part of Mars Sample Return (MSR)

Dust transported in the martian atmosphere is of intrinsic scientific interest and has relevance for the planning of human missions in the future. The MSR Campaign, as currently designed, presents an important opportunity to return serendipitous, airfall dust. The tubes containing samples collected by the Perseverance rover would be placed in cache depots on the martian surface perhaps as early as 2023–24 for recovery by a subsequent mission no earlier than 2028–29, and possibly as late as 2030–31. Thus, the sample tube surfaces could passively collect dust for multiple years. This dust is deemed to be exceptionally valuable as it would inform our knowledge and understanding of Mars' global mineralogy, surface processes, surface-atmosphere interactions, and atmospheric circulation. Preliminary calculations suggest that the total mass of such dust on a full set of tubes could be as much as 100 mg and, therefore, sufficient for many types of laboratory analyses. Two planning steps would optimize our ability to take advantage of this opportunity: (1) the dust-covered sample tubes should be loaded into the Orbiting Sample container (OS) with minimal cleaning and (2) the capability to recover this dust early in the workflow within an MSR Sample Receiving Facility (SRF) would need to be established. A further opportunity to advance dust/atmospheric science using MSR, depending upon the design of the MSR Campaign elements, may lie with direct sampling and the return of airborne dust.

Monica M. Grady↗
NASA NTRS2024

Optimizing Air Traffic - Integrating Artificial Intelligence and Machine Learning in Flight Path Planning and 3D Airspace Visualization for Air Traffic Control

Air Traffic Control (ATC) systems are vital components of the National Airspace System (NAS). ATC, Airport Traffic Control Towers (ATCT), and Terminal Radar Approach Control (TRACON) are responsible for directing all flights departing from and arriving at airports, managing our nation’s airspace, preventing potential accidents, and ensuring that every flight is accounted for. However, these systems often face challenges in effectively monitoring the skies. Issues such as poor communication between operators, difficulty in performing operations, and the constant need for vigilance frequently burden ATC operators. Additionally, the projected increase in air traffic in the coming years will only exacerbate the stress associated with this role. To address these issues, we propose a system that assists ATC operators in situations such as handovers, emergencies, and routing aircraft to avoid weather hazards. Our solution includes an Artificial Intelligence (AI) and Machine Learning (ML)-based Flight Pathways Planning System (FPPS) designed to find the fastest and most optimal routes for aircraft, taking into account weather conditions, restricted terrain, and Extended-Range Twin-Engine Operational Performance Standards (ETOPS) ratings. The proposed Predictive Weather Planning Model, included in FPPS, adjusts routes based on real-time and forecasted weather conditions. Additionally, our NVIDIA Omniverse 3D Visualization System offers a highly interactive environment for better visualization and a clear view of the airspace. By incorporating these systems, the roles of ATC, ATCT, and TRACON operators will become more manageable and less stressful, equipping them to efficiently handle the growing density of airspace.

Regina Ayoubi↗
NASA NTRS2009

Probabilistic Risk Model for Organ Doses and Acute Health Effects of Astronauts on Lunar Missions

Exposure to large solar particle events (SPEs) is a major concern during EVAs on the lunar surface and in Earth-to-Lunar transit. 15% of crew times may be on EVA with minimal radiation shielding. Therefore, an accurate assessment of SPE occurrence probability is required for the mission planning by NASA. We apply probabilistic risk assessment (PRA) for radiation protection of crews and optimization of lunar mission planning.

Kim, Myung-Hee Y.↗
NASA NTRS1991

Autonomous space processor for orbital debris

The development of an Autonomous Space Processor for Orbital Debris (ASPOD) was the goal. The nature of this craft, which will process, in situ, orbital debris using resources available in low Earth orbit (LEO) is explained. The serious problem of orbital debris is briefly described and the nature of the large debris population is outlined. The focus was on the development of a versatile robotic manipulator to augment an existing robotic arm, the incorporation of remote operation of the robotic arms, and the formulation of optimal (time and energy) trajectory planning algorithms for coordinated robotic arms. The mechanical design of the new arm is described in detail. The work envelope is explained showing the flexibility of the new design. Several telemetry communication systems are described which will enable the remote operation of the robotic arms. The trajectory planning algorithms are fully developed for both the time optimal and energy optimal problems. The time optimal problem is solved using phase plane techniques while the energy optimal problem is solved using dynamic programming.

Ramohalli, Kumar↗
NASA NTRS2002

A survey of spacecraft formation flying guidance

This paper is the first comprehensive spacecraft formation flying guidance (FFG) survey. Here by the term guidance we mean both path planning (i. e., reference trajectory generation) and optimal, open loop control design. FFG naturally divides into two areas: Deep Space (DS), in which relative spacecraft dynamics reduce to double integrator form, and Planetary Orbital Environments (POE), in which they do not (e.9. libration point formations). Both areas consider optimal formation reconfigurations. In addition, DS FFG addresses optimal u, v-coverages for multiple spacecraft interferometers and rest-to-rest rotations. The main focus of the POE literature, however, is 'assive apertures.' These are periodic and fuel-eficient relative spacecraft trajectories that accomplish scientific objectives (e.9. synthesizing an aperture).

formation flying guidance optimal control path pla↗
NASA NTRS1975

Optimizing airport runway improvement program - A dynamic programming approach

In order to reduce the air traffic delay in the terminal area, an immediate remedy is to increase airport capacity by an expansion of the existing runway system. The runway expansion program is often limited by budgetary constraints; the expensive facilities for a long-term improvement cannot be built at once. When a runway improvement strategy is being considered for a longer planning horizon, the investiment decision depends upon the interrelations of its composite periods. The problem, therefore, is to determine how time factor and investment decisions interact to yield an optimal improvement scheme that meets demand at a minimum cost. With this objective in mind, a dynamic programming methodology is employed to determine the optimal planning scheme. Also, an example runway improvement problem is tested to illustrate how a dynamic programming model is practical in actual application.

Yu, J. C.↗
NASA NTRS1991

Advanced design for orbital debris removal in support of solar system exploration

The development of an Autonomous Space Processor for Orbital Debris (ASPOD) is the ultimate goal. The craft will process, in situ, orbital debris using resources available in low Earth orbit (LEO). The serious problem of orbital debris is briefly described and the nature of the large debris population is outlined. This year, focus was on development of a versatile robotic manipulator to augment an existing robotic arm; incorporation of remote operation of robotic arms; and formulation of optimal (time and energy) trajectory planning algorithms for coordinating robotic arms. The mechanical design of the new arm is described in detail. The versatile work envelope is explained showing the flexibility of the new design. Several telemetry communication systems are described which will enable the remote operation of the robotic arms. The trajectory planning algorithms are fully developed for both the time-optimal and energy-optimal problem. The optimal problem is solved using phase plane techniques while the energy optimal problem is solved using dynamics programming.

Source record↗
NASA NTRS2011

TPSAS-NF1676L-12441-DND

The increasing presence of airport surface surveillance technologies has spawned a strong interest in airport surface traffic management research; the vast majority has assumed that the airport’s runway configuration is known and constant. Tactical Runway Configuration Management (TRCM), one component of NASA’s System Oriented Runway Management concept, plans the airport configuration to optimize traffic efficiency for the forecast weather, traffic, and other factors. While planning runway configuration can provide benefit and is required by other automation concepts, larger benefits are possible by planning other airport configuration decisions, such as runway assignment policies, that are currently made manually by controllers. A laboratory prototype of the TRCM algorithm which selects optimal airport configuration schedules has been implemented and studied within a simulation environment. The presentation will describe simulation results for several airports, under various weather and traffic conditions. The sequence of airport configurations recommended by TRCM result in significantly less delay than the airport configurations that were actually used by controllers, illustrating both the potential benefit from airport configuration optimization and the ability of TRCM to provide effective airport configuration schedules. The application to several, distinct airports demonstrates the approach is capable of handling the differences between airports with a common algorithm, while providing decision support that respects the current procedures at those airports. Consequently, TRCM is able to be deployed to any airport within the current National Airspace System. The TRCM algorithmic approach is also extensible to future operational scenarios. NASA is in the process of transferring the initial TRCM technology to the FAA. Future research will extend the concept and algorithm to provide coordinated plans for metroplex airports and study NextGen applications.

Stephen Atkins↗
NASA NTRS2011

TPSAS-NF1676L-12263-DND

The increasing presence of airport surface surveillance technologies has spawned a strong interest in airport surface traffic management research; the vast majority has assumed that the airport’s runway configuration is known and constant. Tactical Runway Configuration Management (TRCM), one component of NASA’s System Oriented Runway Management concept, plans the airport configuration to optimize traffic efficiency for the forecast weather, traffic, and other factors. While planning runway configuration can provide benefit and is required by other automation concepts, larger benefits are possible by planning other airport configuration decisions, such as runway assignment policies, that are currently made manually by controllers. A laboratory prototype of the TRCM algorithm which selects optimal airport configuration schedules has been implemented and studied within a simulation environment. The presentation will describe simulation results for several airports, under various weather and traffic conditions. The sequence of airport configurations recommended by TRCM result in significantly less delay than the airport configurations that were actually used by controllers, illustrating both the potential benefit from airport configuration optimization and the ability of TRCM to provide effective airport configuration schedules. The application to several, distinct airports demonstrates the approach is capable of handling the differences between airports with a common algorithm, while providing decision support that respects the current procedures at those airports. Consequently, TRCM is able to be deployed to any airport within the current National Airspace System. The TRCM algorithmic approach is also extensible to future operational scenarios. NASA is in the process of transferring the initial TRCM technology to the FAA. Future research will extend the concept and algorithm to provide coordinated plans for metroplex airports and study NextGen applications.

Stephen Atkins↗
NASA NTRS1994

Design of a cooperative problem-solving system for en-route flight planning: An empirical evaluation

Both optimization techniques and expert systems technologies are popular approaches for developing tools to assist in complex problem-solving tasks. Because of the underlying complexity of many such tasks, however, the models of the world implicitly or explicitly embedded in such tools are often incomplete and the problem-solving methods fallible. The result can be 'brittleness' in situations that were not anticipated by the system designers. To deal with this weakness, it has been suggested that 'cooperative' rather than 'automated' problem-solving systems be designed. Such cooperative systems are proposed to explicitly enhance the collaboration of the person (or a group of people) and the computer system. This study evaluates the impact of alternative design concepts on the performance of 30 airline pilots interacting with such a cooperative system designed to support enroute flight planning. The results clearly demonstrate that different system design concepts can strongly influence the cognitive processes and resultant performances of users. Based on think-aloud protocols, cognitive models are proposed to account for how features of the computer system interacted with specific types of scenarios to influence exploration and decision making by the pilots. The results are then used to develop recommendations for guiding the design of cooperative systems.

Layton, Charles↗
NASA NTRS1994

Design of a cooperative problem-solving system for en-route flight planning: An empirical evaluation

Both optimization techniques and expert systems technologies are popular approaches for developing tools to assist in complex problem-solving tasks. Because of the underlying complexity of many such tasks, however, the models of the world implicitly or explicitly embedded in such tools are often incomplete and the problem-solving methods fallible. The result can be 'brittleness' in situations that were not anticipated by the system designers. To deal with this weakness, it has been suggested that 'cooperative' rather than 'automated' problem-solving systems be designed. Such cooperative systems are proposed to explicitly enhance the collaboration of the person (or a group of people) and the computer system. This study evaluates the impact of alternative design concepts on the performance of 30 airline pilots interacting with such a cooperative system designed to support en-route flight planning. The results clearly demonstrate that different system design concepts can strongly influence the cognitive processes and resultant performances of users. Based on think-aloud protocols, cognitive models are proposed to account for how features of the computer system interacted with specific types of scenarios to influence exploration and decision making by the pilots. The results are then used to develop recommendations for guiding the design of cooperative systems.

Layton, Charles↗