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NASA NTRS1981

Spacecraft computer resource margin management

The conduction of the Project Galileo Orbiter, with 18 microcomputers and the equivalent of 360K 8-bit bytes of memory contained within two major engineering subsystems and eight science instruments, requires that the key onboard computer system resources be managed in a very rigorous manner. Attention is given to the rationale behind the project policy, the development stage, the preliminary design stage, the design/implementation stage, and the optimization or 'scrubbing' stage. The implementation of the policy is discussed, taking into account the development of the Attitude and Articulation Control Subsystem (AACS) and the Command and Data Subsystem (CDS), the reporting of margin status, and the response to allocation oversubscription.

Larman, B. T.↗

NASA NTRS2022

Scheduling For Urban Air Mobility Using Safe Learning

This work considers the scheduling problem for Urban Air Mobility (UAM) vehicles travelling between origin-destination pairs with both hard and soft trip deadlines. Each route is described by a discrete probability distribution over trip completion times (or delay) and over interarrival times of requests (or demand) for the route along with a fixed hard or soft deadline. Soft deadlines carry a cost that is incurred when the deadline is missed. An online, safe scheduler is developed that ensures that hard deadlines are never missed and that average cost of missing soft deadlines is minimized. The system is modelled as a Markov Decision Process (MDP) and safe model based learning is used to find the probabilistic distributions over route delays and demand. Monte Carlo Tree Search (MCTS) Earliest Deadline First (EDF) is used to safely explore the learned models in an online fashion and develop a near-optimal non-preemptive scheduling policy. These results are compared with Value Iteration (VI) and MCTS (Random) scheduling solutions.

Urban Air Mobility↗

NASA NTRSDate not supplied

Scheduling for Urban Air Mobility using Safe Learning

Urban Air Mobility↗

NASA NTRS2005

Cognitive Functioning in Space Exploration Missions: A Human Requirement

Solving cognitive issues in the exploration missions will require implementing results from both Human Behavior and Performance, and Space Human Factors Engineering. Operational and research cognitive requirements need to reflect a coordinated management approach with appropriate oversight and guidance from NASA headquarters. First, this paper will discuss one proposed management method that would combine the resources of Space Medicine and Space Human Factors Engineering at JSC, other NASA agencies, the National Space Biomedical Research Institute, Wyle Labs, and other academic or industrial partners. The proposed management is based on a Human Centered Design that advocates full acceptance of the human as a system equal to other systems. Like other systems, the human is a system with many subsystems, each of which has strengths and limitations. Second, this paper will suggest ways to inform exploration policy about what is needed for optimal cognitive functioning of the astronaut crew, as well as requirements to ensure necessary assessment and intervention strategies for the human system if human limitations are reached. Assessment strategies will include clinical evaluation and fitness-to-perform evaluations. Clinical intervention tools and procedures will be available to the astronaut and space flight physician. Cognitive performance will be supported through systematic function allocation, task design, training, and scheduling. Human factors requirements and guidelines will lead to well-designed information displays and retrieval systems that reduce crew time and errors. Means of capturing process, design, and operational requirements to ensure crew performance will be discussed. Third, this paper will describe the current plan of action, and future challenges to be resolved before a lunar or Mars expedition. The presentation will include a proposed management plan for research, involvement of various organizations, and a timetable of deliverables.

Fiedler, Edan↗

NASA NTRS2013

It's the Heat AND the Humidity -- Assessment of Extreme Heat Scenarios to Enable the Assessment of Climate Impacts on Public Health

In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. In a NASA-funded project supporting the National Climate Assessment, we are providing historical and future measures of extreme heat to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The project s emphasis is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM output, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons, 2040 and 2090, are the focus of future assessments; these are compared to the recent past period of 1981-2000. We are characterizing regional-scale temperature and humidity conditions using GCM output for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM output have been analyzed to develop a heat stress climatology based on statistics of extreme heat indicators. Differences between the two future and past periods have been used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes, combined with hourly historical meteorological data at a spatial scale (12 km) much finer than that of GCMs, enable us to create future climate realizations, from which we compute the daily heat stress measures and related spatially-specific climatological fields. These include the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices and a new heat stress variable that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. All output is being provided at the 12 km spatial scale and will also be aggregated to the county level, which is a popular scale of analysis for public health researchers. County-level statistics will be made available by our collaborators at the Centers for Disease Control and Prevention (CDC) via the Wide-ranging Online Data for Epidemiologic Research (WONDER) system. CDC WONDER makes the information resources of the CDC available to public health professionals and the general public. This addition of heat stress measures to CDC WONDER will allow decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. It will also allow public health researchers and policy makers to better include such heat stress measures in the context of national health data available in the CDC WONDER system. The users will be able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S.

Crosson, William L↗

NASA NTRS1994

A knowledge-based system for controlling automobile traffic

Transportation network capacity variations arising from accidents, roadway maintenance activity, and special events as well as fluctuations in commuters' travel demands complicate traffic management. Artificial intelligence concepts and expert systems can be useful in framing policies for incident detection, congestion anticipation, and optimal traffic management. This paper examines the applicability of intelligent route guidance and control as decision aids for traffic management. Basic requirements for managing traffic are reviewed, concepts for studying traffic flow are introduced, and mathematical models for modeling traffic flow are examined. Measures for quantifying transportation network performance levels are chosen, and surveillance and control strategies are evaluated. It can be concluded that automated decision support holds great promise for aiding the efficient flow of automobile traffic over limited-access roadways, bridges, and tunnels.

Maravas, Alexander↗

NASA NTRS1998

Airport Financing and User Charge Systems in the USA

This paper examines the financing of U.S. public airports in a turbulent era of change, and projects toward the future. It begins by briefly outlining historical patterns that have changed the industry, and airport facilities in particular. It then develops basic principles of public finance as applied to public infrastructure, followed by the applicable principles of management. Following that, the current airport financing system is analyzed and contrasted with a socially optimal financing system. A concluding section suggests policy reforms and their likely benefits. The principles of finance and management discussed here are elementary. However, their implications are radical for U.S. airport policy. There is a great deal of room to improve the allocation of aviation infrastructure resources. The application of these basic principles makes it evident that in many cases, current practice is wasteful, environmentally unsound, overly costly, and inequitable. Future investments in public aviation capital will continue to be wasteful until more efficient pricing systems are instituted. Thus, problem in the U.S. is not one of insufficient investment in airport infrastructure, but investment in the wrong types of infrastructure. In the U.S., the vast majority of publically-owned airports are owned by local governments. Thus, while the federal government bad a great deal of influence in financing airports, ultimately these are local decisions. The same is true with many other public infrastructure issues. Katz and Herman (1997) report that in 1995, U.S. net public capital stock equaled almost $4.6 trillion, 72% of which ($3.9 trillion) was owned by state and local governments, most of it in buildings, highways, Streets, sewer systems, and water supply facilities. Thus, public infrastructure finance is fundamentally a local government issue, with implications for federal and state governments in the design of their aid programs.

Bartle, John R.↗

NASA NTRS2014

Agent Based Modeling of Air Carrier Behavior for Evaluation of Technology Equipage and Adoption

As part of ongoing research, the National Aeronautics and Space Administration (NASA) and LMI developed a research framework to assist policymakers in identifying impacts on the U.S. air transportation system (ATS) of potential policies and technology related to the implementation of the Next Generation Air Transportation System (NextGen). This framework, called the Air Transportation System Evolutionary Simulation (ATS-EVOS), integrates multiple models into a single process flow to best simulate responses by U.S. commercial airlines and other ATS stakeholders to NextGen-related policies, and in turn, how those responses impact the ATS. Development of this framework required NASA and LMI to create an agent-based model of airline and passenger behavior. This Airline Evolutionary Simulation (AIRLINE-EVOS) models airline decisions about tactical airfare and schedule adjustments, and strategic decisions related to fleet assignments, market prices, and equipage. AIRLINE-EVOS models its own heterogeneous population of passenger agents that interact with airlines; this interaction allows the model to simulate the cycle of action-reaction as airlines compete with each other and engage passengers. We validated a baseline configuration of AIRLINE-EVOS against Airline Origin and Destination Survey (DB1B) data and subject matter expert opinion, and we verified the ATS-EVOS framework and agent behavior logic through scenario-based experiments. These experiments demonstrated AIRLINE-EVOS's capabilities in responding to an input price shock in fuel prices, and to equipage challenges in a series of analyses based on potential incentive policies for best equipped best served, optimal-wind routing, and traffic management initiative exemption concepts..

Horio, Brant M.↗

NASA NTRS1979

Flexible space structure model reduction by modal cost analysis

It is noted that reduced models and reduced controllers for flexible space structures are obtained by retaining those modes which make the greatest contribution to quadratic control objectives. Attention is given to the relative importance of damping, frequency and mode shapes in the mode truncation decisions for the following control objectives: attitude control, vibration suppression and figure control. It is also shown that using Modal Cost Analysis (MCA) on the closed loop modes of the optimally controlled system allows the construction of reduced control policies which feedback only those closed loop coordinates which are most critical to the quadratic control performance criterion. In this manner, the modes which need to be controlled are deduced from truncations of the optimal controller.

Skelton, R. E.↗

NASA NTRS1980

Modal cost analysis for linear matrix-second-order systems

Reduced models and reduced controllers for systems governed by matrix-second-order differential equations are obtained by retaining those modes which make the largest contributions to quadratic control objectives. Such contributions, expressed in terms of modal data, used as mode truncation criteria, allow the statement of the specific control objectives to influence the early model reduction from very high order models which are available, for example, from finite element methods. The relative importance of damping, frequency, and eigenvector in the mode truncation decisions are made explicit for each of these control objectives: attitude control, vibration suppression and figure control. The paper also shows that using modal cost analysis (MCA) on the closed loop modes of the optimally controlled system allows the construction of reduced control policies which feedback only those closed loop modal coordinates which are most critical to the quadratic control performance criterion. In this way, the modes which should be controlled (and hence the modes which must be observable by choice of measurements), are deduced from truncations of the optimal controller.

Skelton, R. E.↗

NASA NTRS2024

Development of A Composite Drought Indicator for Operational Drought Monitoring in the MENA Region

This paper presents the composite drought indicator (CDI) that Jordanian, Lebanese, Moroccan, and Tunisian government agencies now produce monthly to support operational drought management decision making, and it describes their iterative co-development processes. The CDI is primarily intended to monitor agricultural and ecological drought on a seasonal time scale. It uses remote sensing and modelled data inputs, and it reflects anomalies in precipitation, vegetation, soil moisture, and evapotranspiration. Following quantitative and qualitative validation assessments, engagements with policymakers, and consideration of agencies’ technical and institutional capabilities and constraints, we made changes to CDI input data, modelling procedures, and integration to tailor the system for each national context. We summarize validation results, drought modelling challenges and how we overcame them through CDI improvements, and we describe the monthly CDI production process and outputs. Finally, we synthesize procedural and technical aspects of CDI development and reflect on the constraints we faced as well as trade-offs made to optimize the CDI for operational monitoring to support policy decision-making—including aspects of salience, credibility, and legitimacy—within each national context.

Karim Bergaoui↗

NASA NTRS2024

Cost and Benefit Analysis of Mitigating, Tracking, and Remediating Orbital Debris

Orbital debris may collide with crewed and robotic spacecraft, placing them at risk. The wide range of debris, from 9,000-kilogram rocket bodies to millions of millimeter-size debris, has led to a similarly wide range of proposed actions for addressing the risks posed by debris. However, the costs and benefits of these actions have historically been unknown. This is a challenge for decision makers who are choosing which actions to support through technology development or policy changes. NASA’s Office of Technology, Policy, and Strategy is addressing these technical and economic uncertainties by building a capability to (1) complete rigorous calculations of the net present value of each action, (2) identify an optimal portfolio of actions to reduce risk, and (3) quantitatively analyze policies related to space sustainability. This report describes our progress toward that capability and to solicit feedback from the space and economic communities. Our previous work, referred to here as Phase 1, assessed the costs and benefits of performing debris remediation on operationally relevant timescales. The current analysis contains major updates to the risk model used in Phase 1 and expands the breadth of actions considered to include mitigating the creation of debris, improving the ability to track debris, and more methods for cleaning up existing debris. We demonstrate that our approach of measuring risks in dollars allows for the effectiveness of seemingly incommensurate actions to be compared and generates insights that other approaches to measuring risk have missed.

Jericho Locke↗

NASA NTRS2024

Cost and Benefit Analysis of Mitigating, Tracking, and Remediating Orbital Debris

Presentation accompanying the technical report with the same name. The abstract for the report and the full study is repeated below. Orbital debris may collide with crewed and robotic spacecraft, placing them at risk. The wide range of debris, from 9,000-kilogram rocket bodies to millions of millimeter-size debris, has led to a similarly wide range of proposed actions for addressing the risks posed by debris. However, the costs and benefits of these actions have historically been unknown. This is a challenge for decision makers who are choosing which actions to support through technology development or policy changes. NASA’s Office of Technology, Policy, and Strategy is addressing these technical and economic uncertainties by building a capability to (1) complete rigorous calculations of the net present value of each action, (2) identify an optimal portfolio of actions to reduce risk, and (3) quantitatively analyze policies related to space sustainability. This report describes our progress toward that capability and to solicit feedback from the space and economic communities. Our previous work, referred to here as Phase 1, assessed the costs and benefits of performing debris remediation on operationally relevant timescales. The current analysis contains major updates to the risk model used in Phase 1 and expands the breadth of actions considered to include mitigating the creation of debris, improving the ability to track debris, and more methods for cleaning up existing debris. We demonstrate that our approach of measuring risks in dollars allows for the effectiveness of seemingly incommensurate actions to be compared and generates insights that other approaches to measuring risk have missed.

Jericho Locke↗

NASA NTRSDate not supplied

A Cost and Benefit Analysis of Orbital Debris Remediation, Mitigation,Tracking, and Characterization

Orbital debris may collide with crewed and robotic spacecraft, placing them at risk. The wide range of debris, from 9,000-kilogram rocket bodies to millions of millimeter-size debris, has led to a similarly wide range of proposed actions for addressing the risks posed by debris. However, the costs and benefits of these actions have historically been unknown. This is a challenge for decision makers who are choosing which actions to support through technology development or policy changes. NASA’s Office of Technology, Policy, and Strategy is addressing these technical and economic uncertainties by building a capability to (1) complete rigorous calculations of the net present value of each action, (2) identify an optimal portfolio of actions to reduce risk, and (3) quantitatively analyze policies related to space sustainability. This report describes our progress toward that capability and to solicit feedback from the space and economic communities. Our previous work(Colvin, Karcz, and Wusk. 2023), referred to here as Phase 1, assessed the costs and benefits of performing debris remediation on operationally relevant timescales. The current paper summarizes the work of Locke and Colvin (2024), which contains major updates to the risk model used in Phase 1 and expands the breadth of actions considered to include mitigating the creation of debris, improving the ability to track debris, and more methods for cleaning up existing debris. We demonstrate that our approach of measuring risks in dollars allows for the effectiveness of seemingly incommensurate actions to be compared and generates insights that other approaches to measuring risk have missed.

Orbital Debris↗

NASA NTRS2011

Achieving the Proper Balance Between Crew and Public Safety

A paramount objective of all human-rated launch and reentry vehicle developers is to ensure that the risks to both the crew onboard and the public are minimized within reasonable cost, schedule, and technical constraints. Past experience has shown that proper attention to range safety requirements necessary to ensure public safety must be given early in the design phase to avoid additional operational complexities or threats to the safety of people onboard, and the design engineers must give these requirements the same consideration as crew safety requirements. For human spaceflight, the primary purpose and operational concept for any flight safety system is to protect the public while maximizing the likelihood of crew survival. This paper will outline the policy considerations, technical issues, and operational impacts regarding launch and reentry vehicle failure scenarios where crew and public safety are intertwined and thus addressed optimally in an integrated manner. An overview of existing range and crew safety policy requirements will be presented. Application of these requirements and lessons learned from both the Space Shuttle and Constellation Programs will also be discussed. Using these past programs as examples, the paper will detail operational, design, and analysis approaches to mitigate and balance the risks to people onboard and in the public. Manned vehicle perspectives from the Federal Aviation Administration (FAA) and Air Force organizations that oversee public safety will be summarized as well. Finally, the paper will emphasize the need to factor policy, operational, and analysis considerations into the early design trades of new vehicles to help ensure that both crew and public safety are maximized to the greatest extent possible.

Gowan, John↗

NASA NTRS2010

Aircraft Trajectory Optimization and Contrails Avoidance in the Presence of Winds

There are indications that persistent contrails can lead to adverse climate change, although the complete effect on climate forcing is still uncertain. A flight trajectory optimization algorithm with fuel and contrails models, which develops alternative flight paths, provides policy makers the necessary data to make tradeoffs between persistent contrails mitigation and aircraft fuel consumption. This study develops an algorithm that calculates wind-optimal trajectories for cruising aircraft while avoiding the regions of airspace prone to persistent contrails formation. The optimal trajectories are developed by solving a non-linear optimal control problem with path constraints. The regions of airspace favorable to persistent contrails formation are modeled as penalty areas that aircraft should avoid and are adjustable. The tradeoff between persistent contrails formation and additional fuel consumption is investigated, with and without altitude optimization, for 12 city-pairs in the continental United States. Without altitude optimization, the reduction in contrail travel times is gradual with increase in total fuel consumption. When altitude is optimized, a two percent increase in total fuel consumption can reduce the total travel times through contrail regions by more than six times. Allowing further increase in fuel consumption does not seem to result in proportionate decrease in contrail travel times.

Ng, Hok K.↗

NASA NTRS2010

Concepts and Challenges for Environmentally Friendly En Route Operations

A flight trajectory optimization algorithm with fuel and contrails models, which develops alternative flight paths, provides policy makers the necessary data to make tradeoffs between persistent contrails mitigation and aircraft fuel consumption. This study develops an algorithm that calculates wind-optimal trajectories for cruising aircraft while avoiding the regions of airspace prone to persistent contrails formation. The optimal trajectory is derived using Singular Perturbation Method. The regions of airspace favorable to persistent contrails formation are modeled as high-risk areas that aircraft should avoid and are adjustable. The tradeoffs between persistent contrails formation and additional travel time are investigated for wind-optimal trajectories and various contrails-avoidance trajectories at 10 different cruising altitudes for flights departing from Chicago and San Diego to New York. The additional travel times required for avoiding 100% persistent contrails formation at various flight altitudes ranged from approximately 0% to 4.3% for flights from Chicago to New York. For flights between San Diego and New York, additional traveling times vary between 1.3% and 5% depending on the cruise altitude and the percentage of contrail avoidance. Talk will present the results of aircraft fuel consumptions that are proportional to the travel time for cruising aircraft.

Sridhar, Banavar↗

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.↗