Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “NaS”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

Unmanned Aircraft Systems Integration in the National Airspace System Project: Phase 2 Abstracts - FY2017 to FY2020

There is an increasing need to fly Unmanned Aircraft Systems (UAS) in the National Airspace System (NAS) to perform missions of vital importance to national security and defense, emergency management, science, and to enable commercial applications. However, routine access by UAS into the NAS remains unrealized. The UAS community needs routine access to the global airspace for all classes of UAS. Based upon that need, the National Aeronautics and Space Administration (NASA) Aeronautics Research Mission Directorate (ARMD) Integrated Aviation Systems Program (IASP) UAS Integration in the NAS Project identified the following goal: To Provide research findings, utilizing simulation and flight tests, to support the development and validation of Detect and Avoid (DAA) and Command and Control (C2) technologies necessary for integrating UAS into the NAS. Because this is such a broad reaching challenge facing the UAS community, the UAS-NAS Project recognizes the importance of working together with others in Industry and Other Government Agencies to overcome the technical, operational, and public perception barriers.

Jamie Marie Turner↗
NASA NTRSDate not supplied

Communication Demand in the National Airspace - A Federated Learning Approach

Within the national airspace system (NAS), efficient use of spectrum remains a challenge; as UAS and UAM missions evolve, the amount of mission-critical aircraft communications are expected to significantly grow. To accommodate the increased demand, NASA Glenn Research Center is investigating artificial intelligence approaches that could dynamically allocate spectrum; however, these solutions are driven by communication and aviation data items, many of which are not directly available. One such cornerstone data item is communication demand, parameterizing the needs within a sector in terms that may directly inform spectrum allocation, such as channel access duration, bandwidth, and modulation type. This paper considers the complexity of predicting communication demand as a function of NAS behaviors. Unlike prior prediction work in communications, this research must consider how the NAS may be impacted by external factors - such as convective weather and closures - rather than estimating demand from time-series forecasting alone. Much of this research considers a federated learning design to predict communication events in terms of the type of event occurring (sector coordination, conflict resolution, etc.). To do so, an investigation of products from Sherlock Data Warehouse is conducted, identifying the trends, sufficiency, and correlations of each product to identified events. Additionally, a preliminary discussion for inferring associations between these event types and their communication parameters (duration, bandwidth, modulation) is presented. By utilizing federated learning, imbalances in the types of events and data present throughout the NAS can inform local models without impairing global training. Furthermore, the two-stage approach proposed allows for robust and speculative communication modelling, as communication techniques continue to evolve. As a result, this model enables a generalized approach to understanding NAS communications which is able to inform long-term changes to aviation spectrum management.

Nathan Schimpf↗
NASA NTRSDate not supplied

A Federated Learning Approach to Predicting Communication Demand in the National Airspace

Within the national airspace system (NAS), efficient use of spectrum remains a challenge; as UAS and UAM missions evolve, the amount of mission-critical aircraft communications are expected to significantly grow. To accommodate the increased demand, NASA Glenn Research Center is investigating artificial intelligence approaches that could dynamically allocate spectrum; however, these solutions are driven by communication and aviation data items, many of which are not directly available. One such cornerstone data item is communication demand, parameterizing the needs within a sector in terms that may directly inform spectrum allocation, such as channel access duration, bandwidth, and modulation type. This paper considers the complexity of predicting communication demand as a function of NAS behaviors. Unlike prior prediction work in communications, this research must consider how the NAS may be impacted by external factors - such as convective weather and closures - rather than estimating demand from time-series forecasting alone. Much of this research considers a federated learning design to predict communication events in terms of the type of event occurring (sector coordination, conflict resolution, etc). To do so, an investigation of products from Sherlock Data Warehouse is conducted, identifying the trends, sufficiency, and correlations of each product to identified events. Additionally, a preliminary discussion for inferring associations between these event types and their communication parameters (duration, bandwidth, modulation) is presented. By utilizing federated learning, imbalances in the types of events and data present throughout the NAS can inform local models without impairing global training. Furthermore, the two-stage approach proposed allows for robust and speculative communication modelling, as communication techniques continue to evolve. As a result, this model enables a generalized approach to understanding NAS communications which is able to inform long-term changes to aviation spectrum management.

Nathan Schimpf↗
NASA NTRSDate not supplied

Impact of Near-Angle Scatter on Exo-Earth Coronagraphy

Near-Angle Scatter (NAS) of the host star’s light may limit the ability of a potential Habitable Worlds Observatory (HWO) to detect and characterize an Earth-like planet around a Sun-like star via coronagraphy. NAS from each optical surface produces an E-field across the dark hole that is coherent. These E-fields sum and could be as large or larger than the coronagraph mask leakage E-field. NAS E-fields contribute to the dark hole noise floor via both shot noise and heterodyne amplification of the wavefront instability. The amount of NAS is determined entirely by the statistical properties of the optical surface microroughness and the operating wavelength. Surface properties include not only the rms roughness, but also correlation length and the functional form of the distribution itself. This paper derives an expression that specifies the surface statistics required to achieve a given coronagraph error budget NAS throughput allocation. Analysis does not include scatter from coating columnar structure, edges, contamination, micrometeoroid impacts, or polarization.

H Philip Stahl↗
NASA NTRSDate not supplied

Intelligent Change Detection System: Autonomous Intelligent Machine Agent Model Development

NASA’s significant role in facilitating the harmonious integration of unmanned aircraft systems (UAS), with other aerial vehicles operating in the National Airspace System (NAS), has revealed a need for more advanced technological tools than are being utilized currently. This technology would lend itself to significantly assisting Direct-Action Aviation Personnel (DAAP) with the ingress and egress of UAS operations within the NAS. Providing research findings that would reduce technical barriers, associated with UAS-NAS integration, has been a persistent effort by both NASA and the FAA. One such research effort, pursued by NASA’s Transformative Tools and Technologies – Revolutionary Aviation Mobility (T3-RAM) project, is the development of an autonomous intelligent machine (AIM) agent that would aid DAAP functioning as implemented in remote ground control stations (RGCS). This evolution of the “human-machine” symbiosis, within the aviation environment, is necessary for many reasons. For example, there are projections of large increases to the 864,000 registered UAS and 45,000 aviation operations taking place in the NAS each day. With a data output range from 1 to 20 terabytes per flight or each aerial vehicle, which is projected to have proportional rate increase to that of registered UASs. It is evident, that due to the projected increase of UASs and their generated data, the human-agent’s data managing capabilities will be quickly overwhelmed by the enormous amounts of data emanating in the NAS. The research efforts presented in this paper puts forward results from the development, assessment, and verification of a previously conceptualized AIM-Agent that combats actionable-data (information) errors resulting from the visual perception phenomenon known as “change blindness” (CB). CB has been identified as one of the main culprits of information erroring encountered within the ground control station operator (GCSO) community.

Change Blindness↗
DOE OSTI2020

Ensembles of Networks Produced from Neural Architecture Search

Neural architecture search (NAS) is a popular topic at the intersection of deep learning and high performance computing. NAS focuses on optimizing the architecture of neural networks along with their hyperparameters in order to produce networks with superior performance. Much of the focus has been on how to produce a single best network to solve a machine learning problem, but as NAS methods produce many networks that work very well, this affords the opportunity to ensemble these networks to produce an improved result. Additionally, the diversity of network structures produced by NAS drives a natural bias towards diversity of predictions produced by the individual networks. This results in an improved ensemble over simply creating an ensemble that contains duplicates of the best network architecture retrained to have unique weights.

Herron, Emily↗
DOE OSTI2023

Online evolutionary neural architecture search for multivariate non-stationary time series forecasting

Time series forecasting (TSF) is one of the most important tasks in data science. TSF models are usually pre-trained with historical data and then applied on future unseen datapoints. However, real-world time series data is usually non-stationary and models trained offline usually face problems from data drift. Models trained and designed in an offline fashion can not quickly adapt to changes quickly or be deployed in real-time. To address these issues, this work presents the Online NeuroEvolution-based Neural Architecture Search (ONE-NAS) algorithm, which is a novel neural architecture search method capable of automatically designing and dynamically training recurrent neural networks (RNNs) for online forecasting tasks. Without any pre-training, ONE-NAS utilizes populations of RNNs that are continuously updated with new network structures and weights in response to new multivariate input data. ONE-NAS is tested on real-world, large-scale multivariate wind turbine data as well as the univariate Dow Jones Industrial Average (DJIA) dataset. These results demonstrate that ONE-NAS outperforms traditional statistical time series forecasting methods, including online linear regression, fixed long short-term memory (LSTM) and gated recurrent unit (GRU) models trained online, as well as state-of-the-art, online ARIMA strategies. Additionally, results show that utilizing multiple populations of RNNs which are periodically repopulated provide significant performance improvements, allowing this online neural network architecture design and training to be successful.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1994

Extended Operating Configuration 2 (EOC-2) Design Document

This document describes the design and plan of the Extended Operating Configuration 2 (EOC-2) for the Numerical Aerodynamic Simulation division (NAS). It covers the changes in the computing environment for the period of '93-'94. During this period the computation capability at NAS will have quadrupled. The first section summarizes this paper: the NAS mission is to provide, by the year 2000, a computing system capable of simulating an entire aerospace vehicle in a few hours. This will require 100 GigaFlops sustained performance. The second section contains information about the NAS user community and the computational model used for projecting future requirements. In the third section, the overall requirements are presented, followed by a summary of the target EOC-2 system. The following sections cover, in more detail, each major component that will have undergone change during EOC-2: the high speed processor, mass storage, workstations, and networks.

Barkai, David↗
NASA NTRS1993

Evaluation Metrics for the Paragon XP/S-15

On February 17th 1993, the Numerical Aerodynamic Simulation (NAS) facility located at the NASA Ames Research Center installed a 224 node Intel Paragon XP/S-15 system. After its installation, the Paragon was found to be in a very immature state and was unable to support a NAS users' workload, composed of a wide range of development and production activities. As a first step towards addressing this problem, we implemented a set of metrics to objectively monitor the system as operating system and hardware upgrades were installed. The metrics were designed to measure four aspects of the system that we consider essential to support our workload: availability, utilization, functionality, and performance. This report presents the metrics collected from February 1993 to August 1993. Since its installation, the Paragon availability has improved from a low of 15% uptime to a high of 80%, while its utilization has remained low. Functionality and performance have improved from merely running one of the NAS Parallel Benchmarks to running all of them faster (between 1 and 2 times) than on the iPSC/860. In spite of the progress accomplished, fundamental limitations of the Paragon operating system are restricting the Paragon from supporting the NAS workload. The maximum operating system message passing (NORMA IPC) bandwidth was measured at 11 Mbytes/s, well below the peak hardware bandwidth (175 Mbytes/s), limiting overall virtual memory and Unix services (i.e. Disk and HiPPI I/O) performance. The high NX application message passing latency (184 microns), three times than on the iPSC/860, was found to significantly degrade performance of applications relying on small message sizes. The amount of memory available for an application was found to be approximately 10 Mbytes per node, indicating that the OS is taking more space than anticipated (6 Mbytes per node).

Traversat, Bernard↗
NASA NTRS1998

Controller Strategies for Managing Air Traffic in High Altitude Arrival Sectors

Substantial increases in the volume of air traffic in the National Airspace System (NAS) are forecast for the next decade, with the number of passengers travelling on U.S. airlines expected to increase by as much as 60%. This increased demand on system capacity will be accompanied by increases in traffic complexity as air traffic service providers routinely accommodate user preferred routing requests. Changes to the NAS to meet these new demands are currently underway, including development of new decision support tools to aid controllers in monitoring and managing air traffic, and increased air-to-air and air-to-ground information exchange. Changes in roles and responsibilities of pilots and controllers in flight path management will accompany these changes in traffic patterns and information technology, however the ultimate responsibility for maintaining aircraft separation will remain with the air traffic controller. A thorough understanding of the methods controllers use to manage air traffic will help ensure that changes to the NAS are implemented in a way that maintains the controller's ability to separate aircraft as the system evolves. This presentation describes the strategies controllers use today to manage arrival traffic in its descent from cruise altitude to the Terminal Radar Approach Control (TRACON) boundary. Factors that increase the complexity of this task include the presence of overflight traffic, varying aircraft performance characteristics, winds aloft, ground speed variations with altitude, the need to merge arrival traffic into a single stream, and, when arrival traffic exceeds airport runway capacity, the added task of metering flow into the TRACON. Because of the limited information available to controllers to manage arrival traffic, their strategies are often driven by the need to reduce the task's complexity, which can result in de-optimized flight paths for individual aircraft (e.g., sub-optimal descent or speed profiles). Understanding these strategies and the cognitive demands that drive them will support a safe transition to a NAS that relies on enhanced technologies. In addition, it could enable system developers to identify opportunities for new automation-based procedures or information displays that could reduce the controller's workload and increase operational efficiency.

Smith, Nancy↗
NASA NTRS2001

Determining the amount of physical activity needed for long-term weight control

OBJECTIVE: To evaluate prospectively the influence of habitual physical activity on body weight of men and women and to develop a model that defines the role of physical activity on longitudinal weight change. DESIGN AND SETTING: Occupational cohort study conducted for a mean of 5.5 y. SUBJECTS: A total of 496 (341 male and 155 female) NASA/Johnson Space Center employees who completed the 3 month education component of the employee health-related fitness program and remained involved for a minimum of 2 y. MEASUREMENTS: Body weights were measured at baseline (T1) and follow-up (T2), and habitual physical activity was obtained from the mean of multiple ratings of the 11-point (0-10) NASA Activity Scale (NAS) recorded quarterly between T1 and T2. Other measures included age, gender, VO(2 max) obtained from maximal treadmill testing, body mass index (BMI), and body fat percentage. RESULTS: Multiple regression demonstrated that mean NAS, T1 weight, aging and gender all influence long-term T2 weight. T1 age was significant for the men only. Independently, each increase in mean NAS significantly (P<0.01) reduced T2 weight in men (b=-0.91 kg; 95% CI:-1.4 to-0.42 kg) and women (b=-2.14 kg; 95% CI:-2.93 to-1.35 kg). Mean NAS had a greater effect on T2 weight as T1 weight increased, and the relationship was dose-dependent. CONCLUSIONS: Habitual physical activity is a significant source of long-term weight change. The use of self-reported activity level is helpful in predicting long-term weight changes and may be used by health care professionals when counseling patients about the value of physical activity for weight control.

Exercise↗
NASA NTRS2005

Validation Of The Airspace Concept Evaluation System Using Real World Data

This paper discusses the process of performing a validation of the Airspace Concept Evaluation System (ACES) using real world historical flight operational data. ACES inputs are generated from select real world data and processed to create a realistic reproduction of a single day of operations within the National Airspace System (NAS). ACES outputs are then compared to real world operational metrics and delay statistics for the reproduced day. Preliminary results indicate that ACES produces delays and airport operational metrics similar to the real world with minor variations of delay by phase of flight. ACES is a nation-wide fast-time simulation tool developed at NASA Ames Research Center. ACES models and simulates the NAS using interacting agents representing center control, terminal flow management, airports, individual flights, and other NAS elements. These agents pass messages between one another similar to real world communications. This distributed agent based system is designed to emulate the highly unpredictable nature of the NAS, making it a suitable tool to evaluate current and envisioned airspace concepts. To ensure that ACES produces the most realistic results, the system must be validated. There is no way to validate future concepts scenarios using real world historical data, but current day scenario validations increase confidence in the validity of future scenario results. Each operational day has unique weather and traffic demand schedules. The more a simulation utilizes the unique characteristic of a specific day, the more realistic the results should be. ACES is able to simulate the full scale demand traffic necessary to perform a validation using real world data. Through direct comparison with the real world, models may continuee to be improved and unusual trends and biases may be filtered out of the system or used to normalize the results of future concept simulations.

Zelinski, Shannon↗
NASA NTRS2009

An Exploratory Study of Runway Arrival Procedures: Time Based Arrival and Self-Spacing

The ability of a flight crew to deliver their aircraft to its arrival runway on time is important to the overall efficiency of the National Airspace System (NAS). Over the past several years, the NAS has been stressed almost to its limits resulting in problems such as airport congestion, flight delay, and flight cancellation to reach levels that have never been seen before in the NAS. It is predicted that this situation will worsen by the year 2025, due to an anticipated increase in air traffic operations to one-and-a-half to three times its current level. Improved arrival efficiency, in terms of both capacity and environmental impact, is an important part of improving NAS operations. One way to improve the arrival performance of an aircraft is to enable the flight crew to precisely deliver their aircraft to a specified point at either a specified time or specified interval relative to another aircraft. This gives the flight crew more control to make the necessary adjustments to their aircraft s performance with less tactical control from the controller; it may also decrease the controller s workload. Two approaches to precise time navigation have been proposed: Time-Based Arrivals (e.g., required times of arrival) and Self-Spacing. Time-Based Arrivals make use of an aircraft s Flight Management System (FMS) to deliver the aircraft to the runway threshold at a given time. Self-Spacing enables the flight crew to achieve an ATC assigned spacing goals at the runway threshold relative to another aircraft. The Joint Planning and Development Office (JPDO), a multi-agency initiative established to plan and coordinate the development of the Next Generation Air Transportation System (NextGen), has asked for data for both of these concepts to facilitate future research and development. This paper provides a first look at the delivery performance of these two concepts under various initial and environmental conditions in an air traffic simulation environment.

Houston, Vincent E.↗
NASA NTRS2010

Airspace Systems Program: Next Generation Air Transportation System, NextGen Systems Analysis, Integration and Evaluation Project: Project Plan - Version 1.0

The key objectives of the NASA ASP are to: Improve mobility, capacity efficiency and access of the airspace system. Improve collaboration, predictability, and flexibility for the airspace users. Enable accurate modeling and simulation of air transportation systems. Accommodate operations of all classes of aircraft. Maintain system safety and environmental protection. In support of these program objectives, the major goal of the NextGen-SAIE Project is to enable the transition of key capacity and efficiency improvements to the NAS. Since many aspects of the NAS are unique to specific airport or airspace environments, demand on various parts of the NAS is not expected to increase equally as system demand grows. SAIE will provide systems level analysis of the NAS characteristics, constraints, and demands such that a suite of capacity-increasing concepts and technologies for system solutions are enabled and facilitated. The technical objectives in support of this goal are the following: Integration, evaluation, and transition of more mature concepts and technologies in an environment that faithfully emulates real-world complexities. Interoperability research and analysis of ASP technologies across ATM functions is performed to facilitate integration and take ASP concepts and technologies to higher Technology Readiness Level (TRL). Analyses are conducted on the program s concepts to identify the system benefits or impacts. System level analysis is conducted to increase understanding of the characteristics and constraints of airspace system and its domains.

Quon, Leighton↗
NASA NTRS2011

Flying Unmanned Aircraft: A Pilot's Perspective

The National Aeronautics and Space Administration (NASA) is pioneering various Unmanned Aircraft System (UAS) technologies and procedures which may enable routine access to the National Airspace System (NAS), with an aim for Next Gen NAS. These tools will aid in the development of technologies and integrated capabilities that will enable high value missions for science, security, and defense, and open the door to low-cost, extreme-duration, stratospheric flight. A century of aviation evolution has resulted in accepted standards and best practices in the design of human-machine interfaces, the displays and controls of which serve to optimize safe and efficient flight operations and situational awareness. The current proliferation of non-standard, aircraft-specific flight crew interfaces in UAS, coupled with the inherent limitations of operating UAS without in-situ sensory input and feedback (aural, visual, and vestibular cues), has increased the risk of mishaps associated with the design of the "cockpit." The examples of current non- or sub- standard design features range from "annoying" and "inefficient", to those that are difficult to manipulate or interpret in a timely manner, as well as to those that are "burdensome" and "unsafe." A concerted effort is required to establish best practices and standards for the human-machine interfaces, for the pilot as well as the air traffic controller. In addition, roles, responsibilities, knowledge, and skill sets are subject to redefining the terms, "pilot" and "air traffic controller", with respect to operating UAS, especially in the Next-Gen NAS. The knowledge, skill sets, training, and qualification standards for UAS operations must be established, and reflect the aircraft-specific human-machine interfaces and control methods. NASA s recent experiences flying its MQ-9 Ikhana in the NAS for extended duration, has enabled both NASA and the FAA to realize the full potential for UAS, as well as understand the implications of current limitations. Ikhana is a Predator-B/Reaper UAS, built by General Atomics, Aeronautical Systems, Inc., and modified for research. Since 2007, the aircraft has been flown seasonally with a wing-mounted pod containing an infrared scanner, utilized to provide real-time wildfire geo-location data to various fire-fighting agencies in the western U.S. The multi-agency effort included an extensive process to obtain flight clearance from the FAA to operate under special provisions, given that UAS in general do not fully comply with current airspace regulations (e.g. sense-and-avoid requirements).

Pestana, Mark E.↗
NASA NTRS2011

Progress Toward Future Runway Management

The runway is universally acknowledged as a constraining factor to capacity in the National Airspace System (NAS). It follows that investigation of the effective use of runways, both in terms of selection and assignment, is paramount to the efficiency of future NAS operations. The need to address runway management is not a new idea; however, as the complexities of factors affecting runway selection and usage increase, the need for effective research in this area correspondingly increases. Under the National Aeronautics and Space Administration s Airspace Systems Program, runway management is a key research area. To address a future NAS which promises to be a complex landscape of factors and competing interests among users and operators, effective runway management strategies and capabilities are required. This effort has evolved from an assessment of current practices, an understanding of research activities addressing surface and airspace operations, traffic flow management enhancements, among others. This work has yielded significant progress. Systems analysis work indicates that the value of System Oriented Runway Management tools is significantly increased in the metroplex environment over that of the single airport case. Algorithms have been developed to provide runway configuration recommendations for a single airport with multiple runways. A benefits analysis has been conducted that indicates the SORM benefits include supporting traffic growth, cost reduction as a result of system efficiency, NAS optimization from metroplex operations, fairness in aircraft operations, and rational decision making.

Lohr, Gary W.↗
NASA NTRS2011

UAS Modeling of the Communication Links Study Results

The Federal Aviation Administration (FAA) is the authority that grants access into, and operations within, the National Airspace System (NAS) for all aircraft, including Unmanned Aircraft Systems (UAS). The safe operation of UAS in the NAS must be assured if the full potential of UAS is to be realized and supported by the public and Congress. This report analyzed the communication systems that are needed for the safe operations of UAS in the NAS. Safe operations can be defined as the availability of the required links to carry the information to control the UAS and the return links to allow controllers to know where the UAS is at any given moment as well as how it is performing. This report is the end result of work performed jointly between the FAA and National Aeronautics and Space Administration (NASA)/Kennedy Space Center (NASA KSC). The work was done in support of the Radio Technical Commission for Aeronautics (RTCA) Special Committee 203 (SC-203) Control and Communications Working Group. The RTCA is a federal advisory committee to the FAA. Though the work was not under the direction of the working group, a large part of the specific values used in the simulations came from the working group. Specifically, all of the radio links were modeled based on the formulation completed by the working group. This report analyzed three scenarios from RTCA SC-203 that represent how a UAS would operate in the NAS. Each scenario was created using the Satellite Tool Kit (STK) modeling and simulation tool. The flight paths of the UAS were generated and the UAS dynamics were likewise modeled. Then each communication asset such as transmitters, receivers, and antennas were modeled and placed on the appropriate UAS, satellite, or Control Station (CS). After that, the radio links were analyzed for signal strength and antenna blockage, and the overall link performance was analyzed in detail. The goal was to obtain 99.9% availability on all of the radio communication links. In order to ensure the 99.9% availability, certain values for the telemetry transmitter will have to be increased slightly from I watt up to about 4 watts which is reasonable. The results of this analysis show that it is possible to send commands, during the airborne segment, to the Unmanned Aircraft (UA) and have the UA send back the system health and status with high availability of at least 99.9% of the time. This 99.9% availability included the condition of heavy rain at 90 mm/hr as well as interference from adjacent satellites. The link budget values used in this report were based on the work from the working group.

Birr, Richard B.↗
NASA NTRS2012

Projected Demand and Potential Impacts to the National Airspace System of Autonomous, Electric, On-Demand Small Aircraft

Electric propulsion and autonomy are technology frontiers that offer tremendous potential to achieve low operating costs for small-aircraft. Such technologies enable simple and safe to operate vehicles that could dramatically improve regional transportation accessibility and speed through point-to-point operations. This analysis develops an understanding of the potential traffic volume and National Airspace System (NAS) capacity for small on-demand aircraft operations. Future demand projections use the Transportation Systems Analysis Model (TSAM), a tool suite developed by NASA and the Transportation Laboratory of Virginia Polytechnic Institute. Demand projections from TSAM contain the mode of travel, number of trips and geographic distribution of trips. For this study, the mode of travel can be commercial aircraft, automobile and on-demand aircraft. NASA's Airspace Concept Evaluation System (ACES) is used to assess NAS impact. This simulation takes a schedule that includes all flights: commercial passenger and cargo; conventional General Aviation and on-demand small aircraft, and operates them in the simulated NAS. The results of this analysis projects very large trip numbers for an on-demand air transportation system competitive with automobiles in cost per passenger mile. The significance is this type of air transportation can enhance mobility for communities that currently lack access to commercial air transportation. Another significant finding is that the large numbers of operations can have an impact on the current NAS infrastructure used by commercial airlines and cargo operators, even if on-demand traffic does not use the 28 airports in the Continental U.S. designated as large hubs by the FAA. Some smaller airports will experience greater demand than their current capacity allows and will require upgrading. In addition, in future years as demand grows and vehicle performance improves other non-conventional facilities such as short runways incorporated into shopping mall or transportation hub parking areas could provide additional capacity and convenience.

Smith, Jeremy C.↗