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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Cellular Decomposition Based Hybrid-Hierarchical Control Systems with Applications to Flight Management Systems

The work in this research project has been focused on the construction of a hierarchical hybrid control theory which is applicable to flight management systems. The motivation and underlying philosophical position for this work has been that the scale, inherent complexity and the large number of agents (aircraft) involved in an air traffic system imply that a hierarchical modelling and control methodology is required for its management and real time control. In the current work the complex discrete or continuous state space of a system with a small number of agents is aggregated in such a way that discrete (finite state machine or supervisory automaton) controlled dynamics are abstracted from the system's behaviour. High level control may then be either directly applied at this abstracted level, or, if this is in itself of significant complexity, further layers of abstractions may be created to produce a system with an acceptable degree of complexity at each level. By the nature of this construction, high level commands are necessarily realizable at lower levels in the system.

Caines, P. E.↗
NASA NTRSDate not supplied

Trajectory Based Operations (TBO)

Today, the FAA is fully engaged in the development and deployment of TBO for the NAS. To realize TBO, the FAA and NAS user community recognize the importance of systems-of-systems thinking and of greater integration across systems, programs, teams, and between research and the field. The ATD-1 Operational Integration Assessment (OIA), helped blaze the trail for this important transition while moving TBFM Terminal Sequencing and Spacing (TSAS) down the path to deployment. Only a few years later, a comprehensive flight test of Flight Deck Interval Management (FIM) capabilities was executed, complementary and interoperable with traffic flow capabilities that were then emerging for TBO. Together, the ATD-1 tech transfers helped pave the way for the highly integrated systems-of-systems development and acquisition being undertaken for TBO. This session will chart that path to where we are today, and where we are going in the future.

ATD-1, TSAS, FIM, trajectory based operations↗
NASA NTRS2006

Technology Developments Integrating a Space Network Communications Testbed

As future manned and robotic space explorations missions involve more complex systems, it is essential to verify, validate, and optimize such systems through simulation and emulation in a low cost testbed environment. The goal of such a testbed is to perform detailed testing of advanced space and ground communications networks, technologies, and client applications that are essential for future space exploration missions. We describe the development of new technologies enhancing our Multi-mission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE) that enable its integration in a distributed space communications testbed. MACHETE combines orbital modeling, link analysis, and protocol and service modeling to quantify system performance based on comprehensive considerations of different aspects of space missions. It can simulate entire networks and can interface with external (testbed) systems. The key technology developments enabling the integration of MACHETE into a distributed testbed are the Monitor and Control module and the QualNet IP Network Emulator module. Specifically, the Monitor and Control module establishes a standard interface mechanism to centralize the management of each testbed component. The QualNet IP Network Emulator module allows externally generated network traffic to be passed through MACHETE to experience simulated network behaviors such as propagation delay, data loss, orbital effects and other communications characteristics, including entire network behaviors. We report a successful integration of MACHETE with a space communication testbed modeling a lunar exploration scenario. This document is the viewgraph slides of the presentation.

hybrid simulation↗
NASA NTRS2016

ASTAR Flight Test: Overview and Spacing Results

The purpose of the NASA Langley Airborne Spacing for Terminal Arrival Routes (ASTAR) research aboard the Boeing ecoDemonstrator aircraft was to demonstrate the use of NASA's ASTAR algorithm using contemporary tools of the Federal Aviation Administration's Next Generation Air Transportation System (NEXTGEN). EcoDemonstrator is a Boeing test program which utilizes advanced experimental equipment to accelerate the science of aerospace and environmentally friendly technologies. The ASTAR Flight Test provided a proof-of-concept flight demonstration that exercised an algorithmic-based application in an actual aircraft. The test aircraft conducted Interval Management operations to provide time-based spacing off a target aircraft in non-simulator wind conditions. Work was conducted as a joint effort between NASA and Boeing to integrate ASTAR in a Boeing supplied B787 test aircraft while using a T-38 aircraft as the target. This demonstration was also used to identify operational risks to future flight trials for the NASA Air Traffic Management Technology Demonstration expected in 2017.

Roper, Roy D.↗
NASA NTRSDate not supplied

Coordination between Federated Scheduling and Conflict Resolution in UAM Operations

This work proposes a federated scheduling algorithm and explores two mechanisms for coordinating federated scheduling and conflict resolution functions - two core traffic management functions in urban air mobility operations. A federated scheduling algorithm is first developed, together with data that needs to be shared among schedulers. Two mechanisms for coordinating scheduling and conflict resolution functions are then introduced and studied as conflicts in high-density operations may not be completely resolved by conflict resolution function alone. The first coordination mechanism is constructed based on the arrival scheduler at the destination and another one utilizes the departure scheduler at the origin. Experiments and trade space studies are conducted to compare these two mechanisms using fast-time traffic simulations. Results show that both mechanisms perform well in coordinating scheduling and conflict resolution functions and helping resolve all potential conflicts. Experiments also show that with proper parameter selection, both mechanisms can achieve better efficiency (less delay) while maintaining zero losses of separation.

Federated scheduling↗
NASA NTRS2021

Coordination between Federated Scheduling and Conflict Resolution in UAM Operations

This work proposes a federated scheduling algorithm and explores two mechanisms for coordinating federated scheduling and conflict resolution functions - two core traffic management functions in urban air mobility operations. A federated scheduling algorithm is first developed, together with data that needs to be shared among schedulers. Two mechanisms for coordinating scheduling and conflict resolution functions are then introduced and studied as conflicts in high-density operations may not be completely resolved by conflict resolution function alone. The first coordination mechanism is constructed based on the arrival scheduler at the destination and another one utilizes the departure scheduler at the origin. Experiments and trade space studies are conducted to compare these two mechanisms using fast-time traffic simulations. Results show that both mechanisms perform well in coordinating scheduling and conflict resolution functions and helping resolve all potential conflicts. Experiments also show that with proper parameter selection, both mechanisms can achieve better efficiency (less delay) while maintaining zero losses of separation.

Federated scheduling↗
NASA NTRS2015

Scheduling and Delivering Aircraft to Departure Fixes in the NY Metroplex with Controller-Managed Spacing Tools

In this paper, successful Time-Based Flow Management (TBFM) scheduling systems for arrivals are considered and adapted to apply to departures. We present a concept of operations that integrates Controller-Managed Spacing tools for departures (CMS-D) with existing tactical departure scheduling tools to coordinate demand at departure fixes in a metroplex environment. We tested our concept in a Human-in-the-Loop simulation and compared the effect of two scheduling conditions: 1) "Departure Scheduling" consisting of an emulation of the Integrated Departure and Arrival Capability (IDAC) where Towers and a Planner (Traffic Management Coordinator at the appropriate facility) coordinate aircraft scheduled takeoff times to departure fixes; and 2) "Arrival Sensitive Departure Scheduling" where, in addition, the Tower and Planner also consider arrival Scheduled Time of Arrivals (STAs) at the airport's dependent runway. Results indicate little difference between the two scheduling conditions, but a large difference between the No Tools and the two scheduling conditions with CMS-D tools. The scheduling/CMS-D tools conditions markedly reduced heading, speed clearances, and workload for controllers who were merging flows at the departure fixes. In the tool conditions, departure controllers conditioned departures earlier rather than later when aircraft were tied near the departure fixes. In the scheduling/CMS-D tools conditions, departures crossed the departure fixes 50 seconds earlier and with an 8% error rate (consisting of time ahead or behind desired time of arrival) compared to a 19% error rate in the No Tool condition. Two exploratory runs showed that similar beneficial effects can be obtained only with the CMS-D tools without scheduling takeoff times, but at the cost of a somewhat higher workload for controllers, indicating the benefits of pre-departure scheduling of aircraft with minimal delays. Hence, we found that CMS-D tools were very beneficial in the metroplex environment we tested but that further research is needed to clarify the benefits of the various scheduling approaches.

terminal airspace↗
NASA NTRS1996

Decision-Aiding and Optimization for Vertical Navigation of Long-Haul Aircraft

Most decisions made in the cockpit are related to safety, and have therefore been proceduralized in order to reduce risk. There are very few which are made on the basis of a value metric such as economic cost. One which can be shown to be value based, however, is the selection of a flight profile. Fuel consumption and flight time both have a substantial effect on aircraft operating cost, but they cannot be minimized simultaneously. In addition, winds, turbulence, and performance vary widely with altitude and time. These factors make it important and difficult for pilots to (a) evaluate the outcomes associated with a particular trajectory before it is flown and (b) decide among possible trajectories. The two elements of this problem considered here are: (1) determining what constitutes optimality, and (2) finding optimal trajectories. Pilots and dispatchers from major u.s. airlines were surveyed to determine which attributes of the outcome of a flight they considered the most important. Avoiding turbulence-for passenger comfort-topped the list of items which were not safety related. Pilots' decision making about the selection of flight profile on the basis of flight time, fuel burn, and exposure to turbulence was then observed. Of the several behavioral and prescriptive decision models invoked to explain the pilots' choices, utility maximization is shown to best reproduce the pilots' decisions. After considering more traditional methods for optimizing trajectories, a novel method is developed using a genetic algorithm (GA) operating on a discrete representation of the trajectory search space. The representation is a sequence of command altitudes, and was chosen to be compatible with the constraints imposed by Air Traffic Control, and with the training given to pilots. Since trajectory evaluation for the GA is performed holistically, a wide class of objective functions can be optimized easily. Also, using the GA it is possible to compare the costs associated with different airspace design and air traffic management policies. A decision aid is proposed which would combine the pilot's notion of optimality with the GA-based optimization, provide the pilot with a number of alternative pareto-optimal trajectories, and allow him to consider unmodelled attributes and constraints in choosing among them. A solution to the problem of displaying alternatives in a multi-attribute decision space is also presented.

Patrick, Nicholas J. M.↗
NASA NTRS1998

A Method for Making Cross-Comparable Estimates of the Benefits of Decision Support Technologies for Air Traffic Management

We present a general method for making cross comparable estimates of the benefits of NASA-developed decision support technologies for air traffic management, and we apply a specific implementation of the method to estimate benefits of three decision support tools (DSTs) under development in NASA's advanced Air Transportation Technologies Program: Active Final Approach Spacing Tool (A-FAST), Expedite Departure Path (EDP), and Conflict Probe and Trial Planning Tool (CPTP). The report also reviews data about the present operation of the national airspace system (NAS) to identify opportunities for DST's to reduce delays and inefficiencies.

Lee, David↗
NASA NTRS2001

Phased-Array Satcom Antennas Developed for Aeronautical Applications

The Advanced Communications (AC) for Aeronautics research at the NASA Glenn Research Center integrates both aeronautics and space communications technologies to achieve the national objective of upgrading the present National Airspace System infrastructure by responding to the agency's aviation capacity and safety goals. One concept for future air traffic management, free flight, presents a significantly increased demand for communications systems capacity and performance in comparison to current air traffic management practices. Current aeronautical communications systems are incapable of supporting the anticipated demands, and the new digital data communications links that are being developed, or are in the early stages of implementation, are not primarily designed to carry the data-intensive free flight air traffic management (ATM) communications loads. Emerging satellite communications technologies are the best potential long-term solution to provide the capacity and performance necessary to enable a mature free flight concept to be deployed. NASA AC/ATM funded the development of a Boeing-designed Ku-band transmit phased-array antenna, a combined in-house and contract effort. Glenn designed and integrated an Aeronautical Mobile Satellite Communications terminal based on the transmit phased-array antenna and a companion receive phased-array antenna previously developed by Boeing.

Kerczewski, Robert J.↗
NASA NTRS2013

Validating an Air Traffic Management Concept of Operation Using Statistical Modeling

Validating a concept of operation for a complex, safety-critical system (like the National Airspace System) is challenging because of the high dimensionality of the controllable parameters and the infinite number of states of the system. In this paper, we use statistical modeling techniques to explore the behavior of a conflict detection and resolution algorithm designed for the terminal airspace. These techniques predict the robustness of the system simulation to both nominal and off-nominal behaviors within the overall airspace. They also can be used to evaluate the output of the simulation against recorded airspace data. Additionally, the techniques carry with them a mathematical value of the worth of each prediction-a statistical uncertainty for any robustness estimate. Uncertainty Quantification (UQ) is the process of quantitative characterization and ultimately a reduction of uncertainties in complex systems. UQ is important for understanding the influence of uncertainties on the behavior of a system and therefore is valuable for design, analysis, and verification and validation. In this paper, we apply advanced statistical modeling methodologies and techniques on an advanced air traffic management system, namely the Terminal Tactical Separation Assured Flight Environment (T-TSAFE). We show initial results for a parameter analysis and safety boundary (envelope) detection in the high-dimensional parameter space. For our boundary analysis, we developed a new sequential approach based upon the design of computer experiments, allowing us to incorporate knowledge from domain experts into our modeling and to determine the most likely boundary shapes and its parameters. We carried out the analysis on system parameters and describe an initial approach that will allow us to include time-series inputs, such as the radar track data, into the analysis

Statistical emulation↗
NASA NTRS2015

Flight Deck Interval Management Avionics: Eye-Tracking Analysis

Interval Management (IM) is one NexGen method for achieving airspace efficiencies. In order to initiate IM procedures, Air Traffic Control provides an IM clearance to the IM aircraft's pilots that indicates an intended spacing from another aircraft (the target to follow - or TTF) and the point at which this should be achieved. Pilots enter the clearance in the flight deck IM (FIM) system; and once the TTF's Automatic Dependent Surveillance-Broadcast signal is available, the FIM algorithm generates target speeds to meet that IM goal. This study examined four Avionics Conditions (defined by the instrumentation and location presenting FIM information) and three Notification Methods (defined by the visual and aural alerts that notified pilots to IM-related events). Current commercial pilots flew descents into Dallas/Fort-Worth in a high-fidelity commercial flight deck simulation environment with realistic traffic and communications. All 12 crews experienced each Avionics Condition, where order was counterbalanced over crews. Each crew used only one of the three Notification Methods. This paper presents results from eye tracking data collected from both pilots, including: normalized number of samples falling within FIM displays, normalized heads-up time, noticing time, dwell time on first FIM display look after a new speed, a workload-related metric, and a measure comparing the scan paths of pilot flying and pilot monitoring; and discusses these in the context of other objective (vertical and speed profile deviations, response time to dial in commanded speeds, out-of-speed-conformance and reminder indications) and subjective measures (workload, situation awareness, usability, and operational acceptability).

Latorella, Kara↗
NASA NTRS2016

Feasibility of Varying Geo-Fence Around an Unmanned Aircraft Operation Based on Vehicle Performance and Wind

Managing trajectory separation is critical to ensuring accessibility, efficiency, and safety in the unmanned airspace. The notion of geo-fences is an emerging concept, where distance buffers enclose individual trajectories and areas of operation in order to manage the airspace. Currently, the Air Traffic Management system for commercial travel defines static distance buffers around the aircraft; however, commercial UASs are envisioned to operate in significantly closer proximity to other UAS requiring a geo-fence for spacing operations. The geo-fence size can be determined based on vehicle performance characteristics, state of the airspace, weather, and other unforeseen events such as emergency or disaster response. Calculation of the geo-fence size could be determined as part of pre-flight planning and during real-time operations. A largely non-homogeneous fleet of UASs will be operating in low altitude and will likely be commercially developed. Due to intellectual property concerns, the operators may not provide detailed specifications of the control system to UTM. In addition, the huge variety of UAS makes modeling each control system prohibitive and flight data for these vehicles may not exist. Therefore, a generalized, simple geo-fence sizing algorithm must be developed such that it does not rely on detailed knowledge of the vehicle control system, accounts for the presence of urban winds, and is sufficiently accurate. In this work, two simple models are investigated to determine its feasibility as an adequate means for calculating the geo-fence size. The vehicle data used in this work are provided by UAS manufactures who have partnered with NASA's UTM project and some publicly available websites. The first model utilizes wind data processed from the NOAA HRRR (Hourly Rapid Refresh) product and Sonar Annemometer data provided by San Jose State. The second model utilizes OpenFOAM which is a CFD code used to generate a wind field for flow around a single building. The key vehicle performance parameters can include UAS response time to disturbances, command to actuation latency, control system rate limits, time to recovery to desired path, and aerodynamics. It was found that the first model provides an initial understanding of geo-fence sizing, but does not provide enough accuracy to provide UTM with an efficient means of scheduling vehicles. The results of the second model reveal that modeling UAS controls systems with a linearized plant and gain scheduled PID controller does not allow capture the UAS flight dynamics within a significant envelope of the wind disturbances.

uncertainty↗
NASA NTRS1996

Decision-Aiding and Optimization for Vertical Navigation of Long-Haul Aircraft

Most decisions made in the cockpit are related to safety, and have therefore been proceduralized in order to reduce risk. There are very few which are made on the basis of a value metric such as economic cost. One which can be shown to be value based, however, is the selection of a flight profile. Fuel consumption and flight time both have a substantial effect on aircraft operating cost, but they cannot be minimized simultaneously. In addition, winds, turbulence, and performance x,ary widely with altitude and time. These factors make it important and difficult for pilots to (a) evaluate the outcomes associated with a particular trajectory before it is flown and (b) decide among possible trajectories. The two elements of this problem considered here are (1) determining, what constitutes optimality, and (2) finding optimal trajectories. Pilots and dispatchers from major U.S. airlines were surveyed to determine which attributes of the outcome of a flight they considered the most important. Avoiding turbulence-for passenger comfort topped the list of items which were not safety related. Pilots' decision making about the selection of flight profile on the basis of flight time, fuel burn, and exposure to turbulence was then observed. Of the several behavioral and prescriptive decision models invoked to explain the pilots' choices, utility maximization is shown to best reproduce the pilots' decisions. After considering more traditional methods for optimizing trajectories, a novel method is developed using a genetic algorithm (GA) operating on a discrete representation of the trajectory search space. The representation is a sequence of command altitudes, and was chosen to be compatible with the constraints imposed by Air Traffic Control, and with the training given to pilots. Since trajectory evaluation for the GA is performed holistically, a wide class of objective functions can be optimized easily. Also, using the GA it is possible to compare the costs associated with different airspace design and air traffic management policies. A decision aid is proposed which would combine the pilot's notion of optimility with the GA-based optimization, provide the pilot with a number of alternative pareto-optimal trajectories, and allow him to consider un-modelled attributes and constraints in choosing among them. A solution to the problem of displaying alternatives in a multi-attribute decision space is also presented.

Patrick, Nicholas J. M.↗
NASA NTRSDate not supplied

Integrating Upper Class E Traffic Management (ETM) Operations into the National Airspace System: Use Cases and Research Questions

As new categories of vehicles are introduced in the National Airspace System, so too are novel concepts for a cooperative approach to traffic management environments. One of these new environments, Upper Class E Traffic Management (ETM), is expected to include a variety of high altitude, long endurance vehicles with a range of performance capabilities and mission profiles that operate in cooperative areas above 60,000 feet. In addition to developing the rules, architecture, and systems for operations within the ETM environment itself, it is also important to consider how ETM vehicles will integrate with traditional Air Traffic Management and interact with Air Traffic Control (ATC) as they traverse ATC-controlled airspace and transition in and out of cooperative ETM operating areas. As a first step toward future ETM demonstrations at the National Aeronautics and Space Administration (NASA) Ames Research Center’s Airspace Operations Laboratory, use cases with step-by-step procedures were developed to identify both nominal and off-nominal scenarios in which ETM operations will interact with ATC. As NASA prepares to develop a simulation platform to demonstrate ETM cooperative practices and ETM-ATC interactions, the procedures, ATC roles and responsibilities, data exchange requirements, and research questions that were identified as part of use case development will inform scenario and system architecture design. The upcoming simulation work will include initial prototype ETM-ATC coordination tools to support ATC controllers’ interactions with ETM operations. This paper will briefly discuss NASA’s upcoming ETM development work and then provide background on ETM-ATC interactions, describe each ETM-ATC interaction use case, and discuss open questions on concept, procedures, and assumptions.

ATC↗
NASA NTRSDate not supplied

Integrating Upper Class E Traffic Management (ETM) Operations into the National Airspace System: Use Cases and Research Questions

As new categories of vehicles are introduced in the National Airspace System, so too are novel concepts for a cooperative approach to traffic management environments. One of these new environments, Upper Class E Traffic Management (ETM), is expected to include a variety of high altitude, long endurance vehicles with a range of performance capabilities and mission profiles that operate in cooperative areas above 60,000 feet. In addition to developing the rules, architecture, and systems for operations within the ETM environment itself, it is also important to consider how ETM vehicles will integrate with traditional Air Traffic Management and interact with Air Traffic Control (ATC) as they traverse ATC-controlled airspace and transition in and out of cooperative ETM operating areas. As a first step toward future ETM demonstrations at the National Aeronautics and Space Administration (NASA) Ames Research Center’s Airspace Operations Laboratory, use cases with step-by-step procedures were developed to identify both nominal and off-nominal scenarios in which ETM operations will interact with ATC. As NASA prepares to develop a simulation platform to demonstrate ETM cooperative practices and ETM-ATC interactions, the procedures, ATC roles and responsibilities, data exchange requirements, and research questions that were identified as part of use case development will inform scenario and system architecture design. The upcoming simulation work will include initial prototype ETM-ATC coordination tools to support ATC controllers’ interactions with ETM operations. This paper will briefly discuss NASA’s upcoming ETM development work and then provide background on ETM-ATC interactions, describe each ETM-ATC interaction use case, and discuss open questions on concept, procedures, and assumptions.

ATC↗
NASA NTRS2014

A Frequency Analysis Approach for Categorizing Air Traffic Behavior

A method of analyzing National Air Space (NAS) air traffic that uses the Discrete Fourier Transform (DFT) is presented. The DFT is used to transform time domain traffic count data into the frequency domain where the sources of traffic in air spaces can be identified and characterized more easily. It is shown in simulation that individual traffic flows within Air Route Traffic Control Centers can be distinguished by their periodicity in the DFT plot. Next, three Traffic Management Initiatives (playbook rerouting, metered flows, and Ground Delay Programs) are implemented in simulations and their signature effects on the traffic are identified using the DFT. Finally, historical flight data is studied and the DFT is applied to sector traffic count data. It is found that in many cases, variations in traffic due to rerouting and convective weather disturbances are better highlighted in the frequency domain than in the original time domain data. Initial results of the DFT show it has potential as a tool for measuring and/or predicting NAS behavior for daily tactical planning and control purposes.

fourier transform↗
NASA NTRSDate not supplied

Uncertainty Propagation in Pre-Flight Prediction of Unmanned Aerial Vehicle Separation Violation

Current forecasts on the future of aeronautics suggest an in- creasing number of unmanned aerial vehicles entering the low- altitude airspace in the next decades (FAA, 2018; Kopardekar et al., 2016). Small vehicles for package delivery as well as larger vehicles for urban air mobility will change the airspace drastically, increasing density of operations both in time, i.e. high number of take-off and landings per unit time, and in space, operating in dense urban environment. This scenario poses challenges to the current approach to air traffic control, and large efforts from academia, industry and regulatory bodies are dedicated to the development of new traffic management strategies that leverage higher computing and simulating capabilities available today. In this paper, we propose a simple look-ahead approach to predict potential minimum separation violations at the strategic level, that is before vehicles start flying, depending on the predefined 4D trajectories and uncertainty affecting the wind acting along those routes. The wind field is extracted from the NOAA North America Mesoscale Forecast System and interpolated using Gaussian process regression, while uncertainty affecting the expected cruise airspeed is propagated through error intervals. The approach allows the prediction of aircraft separation as a function of time, highlighting potential safety violations that would go undetected if uncertainty affecting the expected 4D trajectories is not considered. The paper will also discuss issues related to accuracy and scalability of the approach to multiple vehicle operations.

Trajectory Prediction↗