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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 145 records · Page 8

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NASA NTRS2012

Optimal Integration of Departure and Arrivals in Terminal Airspace

Coordination of operations with spatially and temporally shared resources such as route segments, fixes, and runways improves the efficiency of terminal airspace management. Problems in this category include scheduling and routing, thus they are normally difficult to solve compared with pure scheduling problems. In order to reduce the computational time, a fast time algorithm formulation using a non-dominated sorting genetic algorithm (NSGA) was introduced in this work and applied to a test case based on existing literature. The experiment showed that new method can solve the whole problem in fast time instead of solving sub-problems sequentially with a window technique. The results showed a 60% or 406 second delay reduction was achieved by sharing departure fixes (more details on the comparison with MILP results will be presented in the final paper). Furthermore, the NSGA algorithm was applied to a problem in LAX terminal airspace, where interactions between 28% of LAX arrivals and 10% of LAX departures are resolved by spatial segregation, which may introduce unnecessary delays. In this work, spatial segregation, temporal segregation, and hybrid segregation were formulated using the new algorithm. Results showed that spatial and temporal segregation approaches achieved similar delay. Hybrid segregation introduced much less delay than the other two approaches. For a total of 9 interacting departures and arrivals, delay reduction varied from 4 minutes to 6.4 minutes corresponding flight time uncertainty from 0 to 60 seconds. Considering the amount of flights that could be affected, total annual savings with hybrid segregation would be significant.

high density terminal↗

NASA NTRS1999

Avoiding Braess' Paradox Through Collective Intelligence

In an Ideal Shortest Path Algorithm (ISPA), at each moment each router in a network sends all of its traffic down the path that will incur the lowest cost to that traffic. In the limit of an infinitesimally small amount of traffic for a particular router, its routing that traffic via an ISPA is optimal, as far as cost incurred by that traffic is concerned. We demonstrate though that in many cases, due to the side-effects of one router's actions on another routers performance, having routers use ISPA's is suboptimal as far as global aggregate cost is concerned, even when only used to route infinitesimally small amounts of traffic. As a particular example of this we present an instance of Braess' paradox for ISPA'S, in which adding new links to a network decreases overall throughput. We also demonstrate that load-balancing, in which the routing decisions are made to optimize the global cost incurred by all traffic currently being routed, is suboptimal as far as global cost averaged across time is concerned. This is also due to "side-effects", in this case of current routing decision on future traffic. The theory of COllective INtelligence (COIN) is concerned precisely with the issue of avoiding such deleterious side-effects. We present key concepts from that theory and use them to derive an idealized algorithm whose performance is better than that of the ISPA, even in the infinitesimal limit. We present experiments verifying this, and also showing that a machine-learning-based version of this COIN algorithm in which costs are only imprecisely estimated (a version potentially applicable in the real world) also outperforms the ISPA, despite having access to less information than does the ISPA. In particular, this COIN algorithm avoids Braess' paradox.

Wolpert , David H.↗

NASA NTRS2011

Contact Graph Routing

Contact Graph Routing (CGR) is a dynamic routing system that computes routes through a time-varying topology of scheduled communication contacts in a network based on the DTN (Delay-Tolerant Networking) architecture. It is designed to enable dynamic selection of data transmission routes in a space network based on DTN. This dynamic responsiveness in route computation should be significantly more effective and less expensive than static routing, increasing total data return while at the same time reducing mission operations cost and risk. The basic strategy of CGR is to take advantage of the fact that, since flight mission communication operations are planned in detail, the communication routes between any pair of bundle agents in a population of nodes that have all been informed of one another's plans can be inferred from those plans rather than discovered via dialogue (which is impractical over long one-way-light-time space links). Messages that convey this planning information are used to construct contact graphs (time-varying models of network connectivity) from which CGR automatically computes efficient routes for bundles. Automatic route selection increases the flexibility and resilience of the space network, simplifying cross-support and reducing mission management costs. Note that there are no routing tables in Contact Graph Routing. The best route for a bundle destined for a given node may routinely be different from the best route for a different bundle destined for the same node, depending on bundle priority, bundle expiration time, and changes in the current lengths of transmission queues for neighboring nodes; routes must be computed individually for each bundle, from the Bundle Protocol agent's current network connectivity model for the bundle s destination node (the contact graph). Clearly this places a premium on optimizing the implementation of the route computation algorithm. The scalability of CGR to very large networks remains a research topic. The information carried by CGR contact plan messages is useful not only for dynamic route computation, but also for the implementation of rate control, congestion forecasting, transmission episode initiation and termination, timeout interval computation, and retransmission timer suspension and resumption.

Burleigh, Scott C.↗

NASA NTRSDate not supplied

Noise Impact Analysis for Urban Air Mobility in Dallas-Fort Worth Metroplex

This study supports re-design of airspace and procedures for management of Urban Air Mobility (UAM) fleet operations in a given metropolitan area. A goal of UAM is to maintain geographic separation of UAM flight tracks from densely populated areas in order to reduce the potential negative community impact of UAM and manage flight trajectory in anticipation of allowable noise levels and current land use. A UAM route inventory and a demographic-data-optimized topographic map are developed for the Dallas-Fort Worth metroplex to identify routes or baseline route segments for reduction of noise impact. Noise contours are computed for baseline route and alternative route design given the desired UAM demand level. The impact of UAM fleet noise is predicted based on predicted number of people and noise-sensitive facilities located inside the noise contours.

Urban Air Mobility↗

NASA NTRSDate not supplied

Noise Impact Analysis for Urban Air Mobility in Dallas-Fort Worth Metroplex

Urban Air Mobility↗

NASA NTRS2016

Application of Aviation Turbulence Information to Air-Traffic Management (ATM): Chapter - 24

Unexpected turbulence especially in the upper troposphere and lower stratosphere where cabin crews and passengers in cruising aircraft are likely to unbuckle causes in-flight injuries, structural damage, and flight delay. Therefore, turbulence information can be used to improve safety while pursuing efficiency in Air-Traffic Management (ATM). In this chapter, simple modeling of aircraft trajectories combined with wind and turbulence predictions can suggest the optimal solution of flight plans that minimizes both total flight time (e.g., fuel consumption) and potential encounters of turbulence from departure to arrival airports. Also, probabilistic ensemble turbulence forecasts are applied to suggest an optimal strategic and tactical ATM route planning in a given weather and turbulence condition in the United States which are evaluated against in situ Eddy Dissipation Rate observations from commercial aircraft. Finally, variations of long-haul trans-Oceanic flight routes and their turbulence potentials are investigated using a global reanalysis data to understand how the upper-level large-scale flow patterns can affect the long-term ATM planning through the changes of winds and turbulence conditions.

Wind Optimal↗

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↗

DOE OSTI2025

Integrated Routing and Traffic Signal Control for CAVs via Reinforcement Learning Approach

Incorporating Connected and Automated Vehicles (CAVs) into urban traffic networks presents opportunities and challenges for traffic management systems. This paper aims to develop an integrated routing and traffic signal control system designed explicitly for CAVs, utilizing a Reinforcement Learning (RL) approach. The objective is to enhance traffic flow and improve overall transportation efficiency in the controlled areas. We propose an innovative framework that employs the Deep Reinforcement Learning (DRL) algorithm, especially the Deep Q-network (DQN), to dynamically adjust the number of vehicles in the routes and the duration of traffic signals. Our simulation results demonstrate that a DQN agent successfully optimizes the number of vehicles in the routes and traffic signal timings of traffic signal controllers, eventually reducing total travel time. The study illustrates the potential usage of RL-based systems in managing routing and traffic signals for CAVs, offering a promising opportunity for future urban traffic management strategies.

Park, Jiho [New York University]↗

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 NTRS2009

Integration of Weather Data into Airspace and Traffic Operations Simulation (ATOS) for Trajectory- Based Operations Research

Explicit integration of aviation weather forecasts with the National Airspace System (NAS) structure is needed to improve the development and execution of operationally effective weather impact mitigation plans and has become increasingly important due to NAS congestion and associated increases in delay. This article considers several contemporary weather-air traffic management (ATM) integration applications: the use of probabilistic forecasts of visibility at San Francisco, the Route Availability Planning Tool to facilitate departures from the New York airports during thunderstorms, the estimation of en route capacity in convective weather, and the application of mixed-integer optimization techniques to air traffic management when the en route and terminal capacities are varying with time because of convective weather impacts. Our operational experience at San Francisco and New York coupled with very promising initial results of traffic flow optimizations suggests that weather-ATM integrated systems warrant significant research and development investment. However, they will need to be refined through rapid prototyping at facilities with supportive operational users We have discussed key elements of an emerging aviation weather research area: the explicit integration of aviation weather forecasts with NAS structure to improve the effectiveness and timeliness of weather impact mitigation plans. Our insights are based on operational experiences with Lincoln Laboratory-developed integrated weather sensing and processing systems, and derivative early prototypes of explicit ATM decision support tools such as the RAPT in New York City. The technical components of this effort involve improving meteorological forecast skill, tailoring the forecast outputs to the problem of estimating airspace impacts, developing models to quantify airspace impacts, and prototyping automated tools that assist in the development of objective broad-area ATM strategies, given probabilistic weather forecasts. Lincoln Laboratory studies and prototype demonstrations in this area are helping to define the weather-assimilated decision-making system that is envisioned as a key capability for the multi-agency Next Generation Air Transportation System [1]. The Laboratory's work in this area has involved continuing, operations-based evolution of both weather forecasts and models for weather impacts on the NAS. Our experience has been that the development of usable ATM technologies that address weather impacts must proceed via rapid prototyping at facilities whose users are highly motivated to participate in system evolution.

Peters, Mark↗

DOE OSTI2026

Gradient-informed Hamiltonian Monte Carlo for multicomponent CALPHAD model optimization and uncertainty quantification

CALPHAD model parameter optimization is inherently challenging due to non-smooth objective functions, high-dimensional parameter spaces, and the need for uncertainty quantification (UQ). Traditional weighted nonlinear least squares approaches are computationally efficient but local, whereas black-box global optimizers and ensemble Markov Chain Monte Carlo (MCMC) methods provide broader exploration at substantial computational cost. The objective of this work is to combine the global exploration capability of gradient-informed Hamiltonian Monte Carlo – specifically the No-U-Turn Sampler (NUTS) – with local deterministic refinement using BFGS to efficiently optimize multicomponent CALPHAD models with minimal manual intervention. Analytic gradients are computed via the Jansson derivative framework. The methodology is demonstrated on the Cr—Fe binary system and extended to the Cr—Fe—Ni ternary system with 32 degrees of freedom. For Cr—Fe, NUTS achieves comparable or superior optimality relative to ensemble MCMC while requiring over an order-of-magnitude fewer likelihood evaluations. Parameter uncertainties are quantified through NUTS sampling and propagated to thermodynamic observables using local expansion, demonstrating a novel modular approach that combines binary and ternary parameter subsets without requiring global relaxation. These results establish gradient-informed exploration as a scalable strategy for multicomponent CALPHAD optimization and provide a practical route towards efficient higher-order database development with quantified uncertainty.

36 MATERIALS SCIENCE↗

NASA NTRS2004

An Application of the Phosphorus Consistent Rule for Environmentally Acceptable Cost-Efficient Management of Broiler Litter in Crop Production

We calculated the profitability of using broiler litter as a source of plant nutrients using the phosphorus consistent litter application rule. The cost saving by using litter is 37% over the use of chemical fertilizer-only option to meet the nutrient needs of major crops grown in Alabama. In the optimal solution, only a few routes of all the possible routes developed were used for inter- and intra- county litter hauling. If litter is not adopted as the sole source of crop nutrients, the best environmental policy may be to pair the phosphorus consistent rule with taxes, marketable permits, and subsidies.flaws

Paudel, Krishna P.↗

NASA NTRS2014

802.11s Wireless Mesh Network Visualization Application

Results of past experimentation at NASA Johnson Space Center showed that the IEEE 802.11s standard has better performance than the widely implemented alternative protocol B.A.T.M.A.N (Better Approach to Mobile Ad hoc Networking). 802.11s is now formally incorporated into the Wi- Fi 802.11-2012 standard, which specifies a hybrid wireless mesh networking protocol (HWMP). In order to quickly analyze changes to the routing algorithm and to support optimizing the mesh network behavior for our intended application a visualization tool was developed by modifying and integrating open source tools.

Mauldin, James Alexander↗

NASA NTRS2016

Performance Evaluation of the Approaches and Algorithms for Hamburg Airport Operations

The German Aerospace Center (DLR) and the National Aeronautics and Space Administration (NASA) have been independently developing and testing their own concepts and tools for airport surface traffic management. Although these concepts and tools have been tested individually for European and US airports, they have never been compared or analyzed side-by-side. This paper presents the collaborative research devoted to the evaluation and analysis of two different surface management concepts. Hamburg Airport was used as a common test bed airport for the study. First, two independent simulations using the same traffic scenario were conducted: one by the DLR team using the Controller Assistance for Departure Optimization (CADEO) and the Taxi Routing for Aircraft: Creation and Controlling (TRACC) in a real-time simulation environment, and one by the NASA team based on the Spot and Runway Departure Advisor (SARDA) in a fast-time simulation environment. A set of common performance metrics was defined. The simulation results showed that both approaches produced operational benefits in efficiency, such as reducing taxi times, while maintaining runway throughput. Both approaches generated the gate pushback schedule to meet the runway schedule, such that the runway utilization was maximized. The conflict-free taxi guidance by TRACC helped avoid taxi conflicts and reduced taxiing stops, but the taxi benefit needed be assessed together with runway throughput to analyze the overall performance objective.

air traffic management↗

NASA NTRS2016

Performance Evaluation of the Approaches and Algorithms using Hamburg Airport Operations

The German Aerospace Center (DLR) and the National Aeronautics and Space Administration (NASA) have been independently developing and testing their own concepts and tools for airport surface traffic management. Although these concepts and tools have been tested individually for European and US airports, they have never been compared or analyzed side-by-side. This paper presents the collaborative research devoted to the evaluation and analysis of two different surface management concepts. Hamburg Airport was used as a common test bed airport for the study. First, two independent simulations using the same traffic scenario were conducted: one by the DLR team using the Controller Assistance for Departure Optimization (CADEO) and the Taxi Routing for Aircraft58; Creation and Controlling (TRACC) in a real-time simulation environment, and one by the NASA team based on the Spot and Runway Departure Advisor (SARDA) in a fast-time simulation environment. A set of common performance metrics was defined. The simulation results showed that both approaches produced operational benefits in efficiency, such as reducing taxi times, while maintaining runway throughput. Both approaches generated the gate pushback schedule to meet the runway schedule, such that the runway utilization was maximized. The conflict-free taxi guidance by TRACC helped avoid taxi conflicts and reduced taxiing stops, but the taxi benefit needed be assessed together with runway throughput to analyze the overall performance objective.

Airport surface operations↗

NASA NTRS2016

Performance Evaluation of the Approaches and Algorithms Using Hamburg Airport Operations

The German Aerospace Center (DLR) and the National Aeronautics and Space Administration (NASA) have been independently developing and testing their own concepts and tools for airport surface traffic management. Although these concepts and tools have been tested individually for European and US airports, they have never been compared or analyzed side-by-side. This paper presents the collaborative research devoted to the evaluation and analysis of two different surface management concepts. Hamburg Airport was used as a common test bed airport for the study. First, two independent simulations using the same traffic scenario were conducted; one by the DLR team using the Controller Assistance for Departure Optimization (CADEO) and the Taxi Routing for Aircraft: Creation and Controlling (TRACC) in a real-time simulation environment, and one by the NASA team based on the Spot and Runway Departure Advisor (SARDA) in a fast-time simulation environment. A set of common performance metrics was defined. The simulation results showed that both approaches produced operational benefits in efficiency, such as reducing taxi times, while maintaining runway throughput. Both approaches generated the gate pushback schedule to meet the runway schedule, such that the runway utilization was maximized. The conflict-free taxi guidance by TRACC helped avoid taxi conflicts and reduced taxiing stops, but the taxi benefit needed be assessed together with runway throughput to analyze the overall performance objective.

nasa-dlr research collaboration↗

NASA NTRS2019

Cognitive Communications for NASA Space Systems

The growing complexity of spacecraft constellations, communication relay offerings, and mission architectures drives the need for the development of autonomous communication systems. NASA has traditionally launched single spacecraft missions that are served by the Space Communication and Navigation (SCaN) program. Operations on SCaN networks are typically scheduled weeks in advance, and often each asset serves a single user spacecraft at a time. Recent movement towards swarm missions could make the current approach unsustainable. Additionally, the integration of commercial communication service providers will substantially increase the data transfer options available to new missions. NASA science missions have found benefit in launching swarms of spacecraft, allowing coordinated simultaneous observations from different perspectives. Inter-spacecraft communication (mesh networking) is an enabler for this architecture, as are CubeSats that allow cost-effective provisioning of distributed mission assets. As more complex swarm missions launch, one challenge is coordinating communication within the swarm and choosing the appropriate mechanism for telemetry, tracking, control, and data services to and from Earth. Cognitive communications research conducted by SCaN aims to mitigate the increasing communication complexity for mission users by increasing the autonomy of links, networks, and service scheduling. By considering automation techniques including recent advances in artificial intelligence and machine learning, cognitive algorithms and related approaches enable increased mission science return, improved resource utilization for service provider networks, and resiliency in unpredictable or unplanned environments. The Cognitive Communications Project at the NASA Glenn Research Center develops applications of data-driven, non-deterministic methods to improve the autonomy of space communication. The project emphasizes development of decentralized space networks with artificial intelligence agents optimizing communication link throughput, data routing, and system-wide asset management. This paper discusses the objectives, approaches, and opportunities of the research to address growing needs of the space communications community.

Chelmins, David↗

NASA NTRS2019

Cognitive Communications for NASA Space Systems

The Cognitive Communications Project at the NASA Glenn Research Center develops applications of data-driven, non-deterministic methods to improve the autonomy of space communication. The project emphasizes development of decentralized space networks with artificial intelligence agents optimizing communication link throughput, data routing, and system-wide asset scheduling. This paper discusses the objectives, approaches, and opportunities of the research to address growing needs of the space communications community.

Chelmins, David↗