Yuri Gawdiak

Air Transportation Strategic Trade Space Modeling and Assessment Through Analysis of On-Demand Air Mobility with Electric Aircraft

1 Manager of Strategic Analysis, Aeronautics Research Mission Directorate, NASA HQ, Washington DC 20546 2 Chief Executive Office, 205 Skimino Landing Dr., Williamsburg, VA 23188, AIAA Fellow 3 Chief Science Officer, 508 Olive St., Santa Cruz, CA 95076, AIAA Member 4 Chief Technology Officer, 784 Rosewood Dr., Palo Alto, CA 94303, AIAA Member 5 Senior Economist, GRA, Inc., 115 West Av, Suite 201, Jenkintown, PA 19046 6 Senior Consultant, LMI, 2000 Corporate Ridge, McLean, VA 22102, AIAA Senior Member 7 Senior Fellow, LMI, 2000 Corporate Ridge, McLean, VA 22102 8 Senior Fellow, LMI, 2000 Corporate Ridge, McLean, VA 22102 9 Director of Transportation Research, Old Dominion University, 5115 Hampton Blvd, Norfolk, VA 23529, AIAA Fellow 10 Metron Aviation, 45300 Catalina Court, Suite 101, Dulles, VA 20166 11 Metron Aviation, 45300 Catalina Court, Suite 101, Dulles, VA 20166 12 IAI, Inc., 15400 Calhoun Drive, Suite 400, Rockville MD 20855 13 NASA Langley Research Center, Hampton, VA 23681 14 NASA Langley Research Center, Hampton, VA 23681, AIAA Senior Member 15 Associate Technical Fellow, Boeing Commercial Airplanes, Seattle, WA 12th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference and 14th AIAA/ISSM 17 19 September 2012, Indianapolis, Indiana AIAA 2012-5594

On Space Exploration And Human Error - A Paper on Reliability and Safety

NASA space exploration should largely address a problem class in reliability and risk management stemming primarily from human error, system risk and multi-objective trade-off analysis, by conducting research into system complexity, risk characterization and modeling, and system reasoning. In general, in every mission we can distinguish risk in three possible ways: a) known-known, b) known-unknown, and c) unknown-unknown. It is probable almost certain that space exploration will partially experience similar known or unknown risks embedded in the Apollo missions, Shuttle or Station unless something alters how NASA will perceive and manage safety and reliability.

The personal satellite assistant: an internal spacecraft autonomous mobile monitor

This paper presents an overview of the research and development effort at the NASA Ames Research Center to create an internal spacecraft autonomous mobile monitor capable of performing intra-vehicular sensing activities by autonomously navigating onboard the International Space Station. We describe the capabilities, mission roles, rationale, high-level functional requirements, and design challenges for an autonomous mobile monitor. The rapid prototyping design methodology used, in which five prototypes of increasing fidelity are designed, is described as well as the status of these prototypes, of which two are operational and being tested, and one is actively being designed. The physical test facilities used to perform ground testing are briefly described, including a micro-gravity test facility that permits a prototype to propel itself in 3 dimensions with 6 degrees-of-freedom as if it were in a micro-gravity environment. We also describe an overview of the autonomy framework and its components including the software simulators used in the development process. Sample mission test scenarios are also described. The paper concludes with a discussion of future and related work followed by the summary.

JPDO Case Study of NextGen High Density Operations

The Joint Planning and Development Office has organized an Interagency Portfolio and Systems Analysis Division in order to provide an analytical basis to formulate and assess the capabilities of the Next Generation Air Transportation System. In the past analysis products have been developed based on targets of opportunity and dynamic requests from the other divisions within the JPDO. The High Density Case Study was formulated as an integrated, top-down, test case to strategically align the JPDO divisions and agency partners with their respective outputs for the NextGen plan into an integrated portfolio. This case study documents the capacity-related benefits and environmental impacts of a subset of the capabilities comprising the Next Generation Air Transportation System. The analysis focused on determining the benefits of the NextGen capabilities related to the High Density or Super-Density Operations. High Density Operations are a component of the OEP Solution Set while Super Density Operations are corresponding capabilities described in the NextGen Concept of Operations. For the sake of simplicity and consistency we refer to the analysis performed as the HD Case Study.

Context based configuration management

The commercial state-of-the-art tools for configuration managements (CM) systems are very mature for asset, hardware and software development systems. These tools are very good for tactical management for daily issues. However, strategic management and decisions also have a requirement for configuration management but unfortunately the traditional commercial off the shelf (COTS) tools are not adequate for those requirements. Using shortcomings as requirements drives our team has developed a hybrid tool-suite that directly supports the dynamic, distributed strategic planning and decision making environments. The context based configuration management (CBCM) system marries decision map technology with COTS configuration management work flow (Xerox Docushare), embedded component models (events models, configuration item models, and feedback models) all on top of a web based online collaboration technology (NASA/Xerox Netmark (Maluf, 2004) middleware engine). This paper documents the rapid prototype that has been developed to meet those requirements using this design and highlight the initial pilot results at NASA Headquarters with the Aeronautics Research Mission Directorate

Evaluation of NextGen Operational Benefits

The Next Generation Air Transportation System (NextGen) represents the transformation of the National Airspace System (NAS). It includes our national system of airports and uses 21 st century technologies to ensure future safety, capacity and environmental needs are met. NextGen will be realized through investments in research and development, new technologies, operational changes, and coordinated efforts of private industry and federal NextGen Partner Agencies. In FY2009, the Joint Planning and Development Office (JPDO) completed an analysis of an initial NextGen alternative, or path to implementing the full range of capabilities that have been proposed/envisioned for NextGen in 2025. The results of this analysis indicate that such a complete transformation to NextGen by 2025, based on this alternative, may not be feasible due to the associated costs and risks. In FY2010, the JPDO began to formulate and evaluate additional alternative implementation paths to achieve the long-term NextGen architecture. The JPDO’s Integrated Portfolio and Systems Analysis (IPSA) Division used NAS-wide modeling and simulation to evaluate these alternatives and estimate the corresponding stakeholder benefits under future scenarios. This paper describes the formulation and evaluation of the NextGen alternatives and provides a discussion of the operational performance benefits of the alternatives in terms of NAS throughput and delays. Results indicate that significant operational benefits can be realized through the implementation of additional ground and airborne technologies that extend those currently envisioned at the current rate of progress for the 2025 timeframe. In addition, NextGen implementation alternatives that include approaches such as greater use of regional airports show potential operational benefits compared with technology-focused implementations. The achievement of this more aggressive 2025 implementation of NextGen would require greater interagency cooperation,

Secure Large-Scale Airport Simulations Using Distributed Computational Resources

To fully conduct research that will support the far-term concepts, technologies and methods required to improve the safety of Air Transportation a simulation environment of the requisite degree of fidelity must first be in place. The Virtual National Airspace Simulation (VNAS) will provide the underlying infrastructure necessary for such a simulation system. Aerospacespecific knowledge management services such as intelligent data-integration middleware will support the management of information associated with this complex and critically important operational environment. This simulation environment, in conjunction with a distributed network of super-computers, and high-speed network connections to aircraft, and to Federal Aviation Administration (FAA), airline and other data-sources will provide the capability to continuously monitor and measure operational performance against expected performance. The VNAS will also provide the tools to use this performance baseline to obtain a perspective of what is happening today and of the potential impact of proposed changes before they are introduced into the system.

Airport Remote Tower Sensor Systems

Networks of video cameras, meteorological sensors, and ancillary electronic equipment are under development in collaboration among NASA Ames Research Center, the Federal Aviation Administration (FAA), and the National Oceanic Atmospheric Administration (NOAA). These networks are to be established at and near airports to provide real-time information on local weather conditions that affect aircraft approaches and landings. The prototype network is an airport-approach-zone camera system (AAZCS), which has been deployed at San Francisco International Airport (SFO) and San Carlos Airport (SQL). The AAZCS includes remotely controlled color video cameras located on top of SFO and SQL air-traffic control towers. The cameras are controlled by the NOAA Center Weather Service Unit located at the Oakland Air Route Traffic Control Center and are accessible via a secure Web site. The AAZCS cameras can be zoomed and can be panned and tilted to cover a field of view 220 wide. The NOAA observer can see the sky condition as it is changing, thereby making possible a real-time evaluation of the conditions along the approach zones of SFO and SQL. The next-generation network, denoted a remote tower sensor system (RTSS), will soon be deployed at the Half Moon Bay Airport and a version of it will eventually be deployed at Los Angeles International Airport. In addition to remote control of video cameras via secure Web links, the RTSS offers realtime weather observations, remote sensing, portability, and a capability for deployment at remote and uninhabited sites. The RTSS can be used at airports that lack control towers, as well as at major airport hubs, to provide synthetic augmentation of vision for both local and remote operations under what would otherwise be conditions of low or even zero visibility.

Modal Preference Modeling of Transportation Demand and Supply for Strategy Portfolio Analyses - Results and Future Plans

Future demand for transportation is and will continue to be shaped by forces that have not been well accommodated in past strategic analyses; further, regression-based analytical methods are less well suited than generative methods for projecting demands for modal options that have little historical data on which to base regressions. New transportation modes, business models, consumer behaviors and vehicle capabilities are the primary factors not well managed in regressive demand projection methods. An example is the ability to study co-evolutionary effects such as a “virtual” mode or modes (i.e., interacting by telepresence as a modal option) on population dynamics or urbanization trends. The risk is that current national transportation strategies in air mobility tend to be constrained by “business as usual” considerations of a rear-view-facing nature. In addition, air transportation demand projections are frequently made in modal isolation; that is, projections for air travel demand have not typically accounted for the full context of all other existing and prospective new modal options and their improvements. Further, if the strategy development processes do not consider the prospect of vastly different characteristics of external context, including new consumer behaviors and modal options then the strategies carry inherent risks. The plausible ranges and combinations in trends or vectors in technologies, energy, environmental, and prosperity considerations comprise a wide range of future conditions s in which strategies must be evaluated. Because 1 Chief Executive Office, 205 Skimino Landing Dr., Williamsburg, VA 23188, AIAA Fellow 2 Chief Science Officer, 508 Olive St., Santa Cruz, CA 95076, AIAA Member 3 Chief Technology Officer, 784 Rosewood Dr., Palo Alto, CA 94303, AIAA Member 4 Director, Transportation Research, Old Dominion University, 5115 Hampton Blvd, Norfolk, VA 23529, AIAA 2 Chief Science Officer, 508 Olive St., Santa Cruz, CA 95076, AIAA Member 3 Chief Technology Officer, 784 Rosewood Dr., Palo Alto, CA 94303, AIAA Member 4 Director, Transportation Research, Old Dominion University, 5115 Hampton Blvd, Norfolk, VA 23529, AIAA Fellow 5 Senior Consultant, LMI, 2000 Corporate Ridge, McLean, VA 22102, AIAA Senior Member 6 Senior Fellow, LMI, 2000 Corporate Ridge, McLean, VA 22102 7 Senior Economist, GRA, Inc., 115 West Av, Suite 201, Jenkintown, PA 19046 8 Manager of Strategic Analysis, Aeronautics Research Mission Directorate, NASA HQ, Washington DC 20546

NextGen Metrics for the Joint Planning and Development Office

The Interagency Portfolio and System Analysis Division of the Joint Planning and Development Office has developed a number of metrics to assess the projected performance of the Next Generation Air Transportation System (NextGen). Metrics are currently being calculated for capacity and environment, two of the six goals established in the Department of Transportation’s 2004 Integrated National Plan for the Next Generation Air Transportation System. Metrics have also been posited but are not currently assessed for the four other goals: global leadership, safety, national defense, and security. The metrics for capacity and environment are based on projected performance of the National Airspace System (NAS), as evaluated by a suite of models and simulations that replicate operation of the NAS and its effects on the environment in terms of noise, local air quality, and climate. The NextGen goals and associated metrics show a high degree of correspondence with the 11 Key Performance Areas formulated by the International Civil Aeronautics Organization. The JPDO has also identified a set of stakeholder metrics, intended to reflect the impact of NextGen on its stakeholders and facilitate communication with them. These metrics include both monetized metrics, expressed in terms of the dollar value of benefits and costs, and nonmonetized metrics, as indicators of system performance. Issues that the JPDO metrics activity has addressed include selection of a representative point from the continuum of combinations of throughput and delay. The JPDO is also considering the value of calculating system efficiency metrics, and plans to continue to enhance alignment of its metrics with those of member agencies, develop target values, enhance stakeholder metrics, and support continued development of modeling and analysis tools. Challenges that remain include improved metrics for delay and predictability of system performance, as well as metrics for fundamental attributes such as robustness and flexibility.