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NASA NTRS2016

Benefit Opportunities for Integrated Surface and Airspace Departure Scheduling: A Study of Operations at Charlotte-Douglas International Airport

NASA is collaborating with the FAA and aviation industry to develop and demonstrate new capabilities that integrate arrival, departure, and surface air-traffic operations. The concept relies on trajectory-based departure scheduling and collaborative decision making to reduce delays and uncertainties in taxi and climb operations. The paper describes the concept and benefit mechanisms aimed at improving flight efficiency and predictability while maintaining or improving operational throughput. The potential impact of the technology is studied and discussed through a quantitative analysis of relevant shortfalls at the site identified for initial deployment and demonstration in 2017: Charlotte-Douglas International Airport. Results from trajectory analysis indicate substantial opportunity to reduce taxi delays for both departures and arrivals by metering departures at the gate in a manner that maximizes throughput while adhering to takeoff restrictions due mostly to airspace constraints. Substantial taxi-out delay reduction is shown for flights subject to departure restrictions stemming from traffic flow management initiatives. Opportunities to improve the predictability of taxi, takeoff, and climb operations are examined and their potential impact on airline scheduling decisions and air-traffic forecasting is discussed. In addition, the potential to improve throughput with departure scheduling that maximizes use of available runway and airspace capacity is analyzed.

air traffic management↗

NASA NTRS2020

Intelligent Contingency Management for Urban Air Mobility

The third aviation revolution is seeking to enable transportation where users have access to immediate and flexible air travel; the users dictate trip origin, destination and timing. One of the major components of this vision is urban air mobility (UAM) for the masses. UAM means a safe and efficient system for vehicles to move passengers and cargo within a city. In order to reach UAM’s full market potential the vehicle will have to be autonomous. One of the primary challenges of autonomous flight is dealing with off-nominal events, both common and unforeseen; thus, intelligent contingency management (ICM) is one of the enabling technologies. In this context, the vehicle has to be aware of its internal state and external environment at all times, ascertain its capability and make decisions about mission completion or modification. All of these functions require data to model and assess the environment and then take actions based on these models. Necessarily, there is uncertainty associated with the data and the models generated from it. Since we are dealing with safety-critical systems, one of the main challenges of ICM is to generate sufficient data and to minimize its uncertainty to enable practical and safe decision making. We propose an overall architecture that incorporates deterministic and learning algorithms together to assess vehicle capabilities, project these into the future and make decisions on mission management level. A layered approach allows for mature parts and technologies to be integrated into early highly automated vehicles before the final state of autonomy is reached.

data-driven systems↗

NASA NTRS1994

A method for the probabilistic design assessment of composite structures

A formal procedure for the probabilistic design assessment of a composite structure is described. The uncertainties in all aspects of a composite structure (constituent material properties, fabrication variables, structural geometry, service environments, etc.), which result in the uncertain behavior in the composite structural responses, are included in the assessment. The probabilistic assessment consists of design criteria, modeling of composite structures and uncertainties, simulation methods, and the decision making process. A sample case is presented to illustrate the formal procedure and to demonstrate that composite structural designs can be probabilistically assessed with accuracy and efficiency.

Shiao, Michael C.↗

NASA NTRS2009

A Study on Advanced Lithium-Based Battery Cell Chemistries to Enhance Lunar Exploration Missions

NASA's Exploration Technology Development Program (ETDP) Energy Storage Project conducted an advanced lithium-based battery chemistry feasibility study to determine the best advanced chemistry to develop for the Altair lunar lander and the Extravehicular Activities (EVA) advanced lunar surface spacesuit. These customers require safe, reliable energy storage systems with extremely high specific energy as compared to today's state-of-the-art batteries. Based on customer requirements, the specific energy goals for the development project are 220 watt-hours per kilogram (Wh/kg) delivered at the battery level at 0 degrees Celsius (degrees Celcius) at a C/10 discharge rate. Continuous discharge rates between C/5 and C/2, operation over 0 to 30 degrees C, and 200 cycles are targeted. The team, consisting of members from NASA Glenn Research Center, Johnson Space Center, and Jet Propulsion laboratory, surveyed the literature, compiled information on recent materials developments, and consulted with other battery experts in the community to identify advanced battery materials that might be capable of achieving the desired results with further development. A variety of electrode materials were considered, including layered metal oxides, spinel oxides, and olivine-type cathode materials, and lithium metal, lithium alloy, and silicon-based composite anode materials. lithium-sulfur systems were also considered. Hypothetical cell constructs that combined compatible anode and cathode materials with suitable electrolytes, separators, current collectors, headers, and cell enclosures were modeled. While some of these advanced materials are projected to obtain the desired electrical performance, there are risks that also factored into the decision making process. The risks include uncertainties due to issues such as safety of a system containing some of these materials, ease of scaling-up of large batches of raw materials, adaptability of the materials to processing using established or reasonable cost manufacturing techniques, manufacturability of the materials in dimensions required for integration into battery cells of practical capacities, low Technology Readiness levels (TRl), and the ability to achieve the desired performance by the customer need dates. The advanced cell chemistry options were evaluated with respect to multiple quantitative and qualitative attributes while considering their projected performance at the end of the available development timeframe. Following a rigorous ranking process, a chemistry that combines a lithiated nickel manganese cobalt oxide (lithium NMC) cathode with a silicon-based composite anode was selected as the technology that can offer the best combination of safety, specific energy, energy density, and likelihood of success. Tasks over the next three years will focus on development of electrode materials, compatible electrolytes, and separator materials, and integration of promising components to assess their combined performance in working cells. Cells of the chosen chemistry will be developed to TRl 6 by 2014 and will then be transferred to the customers for infusion into their mission paths.

Reid, Concha↗

NASA NTRSDate not supplied

Collision Avoidance Approach Using Deep Reinforcement Learning

A method to enable autonomous robots moving in a 2D space collision free motivates the purposed approach for collision avoidance for autonomous UAM vehicles. Challenges of autonomous collision free navigation for both problems are similar. Agents in each environment do not know the intent, or goal, of the other. Finding the time efficient paths require some level of anticipation with neighboring agents which is computationally expensive. In the original work, these obstacles were overcome with a novel application of deep reinforcement learning which offloads the online computation to an offline learning algorithm. A value network that encodes the estimated time to the goal given the agent’s state and the observable portion of the other agent’s state is trained on a baseline policy and further refined with reinforcement learning to promote time efficient collision free navigation. Online, the value network efficiently informs the agent’s decision making in the face of uncertainty of the other agent’s next move. In this paper, challenges extending this methodology to the 3D environment of autonomous UAM vehicles with kinematic constraints are discussed and initial results shown.

Collision Avoidance↗

NASA NTRSDate not supplied

Collision Avoidance Approach Using Deep Reinforcement Learning

Collision Avoidance↗

NASA NTRS1993

Certain and possible rules for decision making using rough set theory extended to fuzzy sets

Uncertainty may be caused by the ambiguity in the terms used to describe a specific situation. It may also be caused by skepticism of rules used to describe a course of action or by missing and/or erroneous data. To deal with uncertainty, techniques other than classical logic need to be developed. Although, statistics may be the best tool available for handling likelihood, it is not always adequate for dealing with knowledge acquisition under uncertainty. Inadequacies caused by estimating probabilities in statistical processes can be alleviated through use of the Dempster-Shafer theory of evidence. Fuzzy set theory is another tool used to deal with uncertainty where ambiguous terms are present. Other methods include rough sets, the theory of endorsements and nonmonotonic logic. J. Grzymala-Busse has defined the concept of lower and upper approximation of a (crisp) set and has used that concept to extract rules from a set of examples. We will define the fuzzy analogs of lower and upper approximations and use these to obtain certain and possible rules from a set of examples where the data is fuzzy. Central to these concepts will be the idea of the degree to which a fuzzy set A is contained in another fuzzy set B, and the degree of intersection of a set A with set B. These concepts will also give meaning to the statement; A implies B. The two meanings will be: (1) if x is certainly in A then it is certainly in B, and (2) if x is possibly in A then it is possibly in B. Next, classification will be looked at and it will be shown that if a classification will be looked at and it will be shown that if a classification is well externally definable then it is well internally definable, and if it is poorly externally definable then it is poorly internally definable, thus generalizing a result of Grzymala-Busse. Finally, some ideas of how to define consensus and group options to form clusters of rules will be given.

Dekorvin, Andre↗

NASA NTRS2010

NASA Risk-Informed Decision Making Handbook

This handbook provides guidance for conducting risk-informed decision making in the context of NASA risk management (RM), with a focus on the types of direction-setting key decisions that are characteristic of the NASA program and project life cycles, and which produce derived requirements in accordance with existing systems engineering practices that flow down through the NASA organizational hierarchy. The guidance in this handbook is not meant to be prescriptive. Instead, it is meant to be general enough, and contain a sufficient diversity of examples, to enable the reader to adapt the methods as needed to the particular decision problems that he or she faces. The handbook highlights major issues to consider when making decisions in the presence of potentially significant uncertainty, so that the user is better able to recognize and avoid pitfalls that might otherwise be experienced.

Dezfuli, Homayoon↗

NASA NTRS2017

Effects of Acute Exposures to Carbon Dioxide upon Cognitive Functions

Carbon dioxide (CO2) originates from human metabolism and typically remains about 10-fold higher in concentration on the International Space Station (ISS) than at the earth's surface. There have been recurring complaints by crew members of episodes of "mental viscosity" adversely affecting their performance, and there is evidence from the ISS that associates CO2 levels with reports of headaches by crewmembers. Consequently, flight rules have been employed to control CO2 below 3 mm Hg, which is well below the existing Spacecraft Maximum Allowable Concentration (SMAC) of 10 mm Hg for 24-hour exposures, and 5.3 mm Hg for exposures of 7 to 180 days. Headaches, while sometime debilitating themselves, are also symptoms that can provide evidence that physiological defense mechanisms have been breached, and there is evidence that CO2 has effects at levels below the threshold for headaches. This concern appears to be substantiated in reports that CO2 at concentrations below 2 mm Hg substantially reduced some cognitive functions that are associated with the ability to make complex decisions in conditions that are characterized by volatility, uncertainty, complexity, ambiguity, and delayed feedback. These are conditions that could be encountered by crews in off-nominal situations or during the first missions beyond low earth orbit. Therefore, we set out to determine if decision-making under volatile, uncertain, confusing and ambiguous circumstances, where feedback is delayed or absent, is correlated with low levels of CO2 during acute exposures (several hours) in crew-like subjects and to determine if additional cognitive domains are sensitive to concentrations of CO2 at, or below, current ISS levels by using a test battery that is currently available onboard ISS. We enrolled 22 volunteers (8 females, 14 males) between the ages of 30-55 (38.8 +/- 7.0) years whose training and professional experience reflect that of the astronaut corps. Subjects were divided among 4 study groups. Exposures occurred in the 20-foot environmental chamber in Bldg 7 at JSC. Each group was exposed to each of four concentrations of CO2 (600, 1200, 2500, and 5000 ppm), and the exposure order was balanced across the groups which were randomly assigned to 4 possible complete exposure orders. Study participants and investigators were blinded to the exposure order. Each exposure lasted 4 hours and occurred on the same day each week for 4 consecutive weeks. Testing included the Strategic Management Simulation (SMS) methodology and the Cognition battery of psychometric measures that are being utilized aboard the ISS. Subjects participated in a familiarization session one week prior to the start of exposure sessions. Each exposure session followed the schedule noted in Figure 1 below. On the morning of each exposure, subjects completed the Cognition battery in a conference room at indoor ambient CO2 levels. Subjects then entered the exposure chamber and were acclimated to the environment for 15 minutes before completing another round of the Cognition battery. After a 20 minute rest, subject completed the approx.80 minute SMS. Subjects were allowed another 20 minute rest period before completing the final Cognition test battery in the exposure chamber. Subjects then returned to the conference room where they completed one final round of Cognition. Data from both testing methodologies are currently being analyzed and will be presented. Study investigators have not yet been unblinded to the coded exposure concentrations, but preliminary results suggest differences.

Ryder, V. E.↗

NASA NTRS2016

Simulation Credibility: Advances in Verification, Validation, and Uncertainty Quantification

Decision makers and other users of simulations need to know quantified simulation credibility to make simulation-based critical decisions and effectively use simulations, respectively. The credibility of a simulation is quantified by its accuracy in terms of uncertainty, and the responsibility of establishing credibility lies with the creator of the simulation. In this volume, we present some state-of-the-art philosophies, principles, and frameworks. The contributing authors involved in this publication have been dedicated to advancing simulation credibility. They detail and provide examples of key advances over the last 10 years in the processes used to quantify simulation credibility: verification, validation, and uncertainty quantification. The philosophies and assessment methods presented here are anticipated to be useful to other technical communities conducting continuum physics-based simulations; for example, issues related to the establishment of simulation credibility in the discipline of propulsion are discussed. We envision that simulation creators will find this volume very useful to guide and assist them in quantitatively conveying the credibility of their simulations.

Simulation Credibility↗

NASA NTRS1993

Population-based learning of load balancing policies for a distributed computer system

Effective load-balancing policies use dynamic resource information to schedule tasks in a distributed computer system. We present a novel method for automatically learning such policies. At each site in our system, we use a comparator neural network to predict the relative speedup of an incoming task using only the resource-utilization patterns obtained prior to the task's arrival. Outputs of these comparator networks are broadcast periodically over the distributed system, and the resource schedulers at each site use these values to determine the best site for executing an incoming task. The delays incurred in propagating workload information and tasks from one site to another, as well as the dynamic and unpredictable nature of workloads in multiprogrammed multiprocessors, may cause the workload pattern at the time of execution to differ from patterns prevailing at the times of load-index computation and decision making. Our load-balancing policy accommodates this uncertainty by using certain tunable parameters. We present a population-based machine-learning algorithm that adjusts these parameters in order to achieve high average speedups with respect to local execution. Our results show that our load-balancing policy, when combined with the comparator neural network for workload characterization, is effective in exploiting idle resources in a distributed computer system.

Mehra, Pankaj↗

NASA NTRS2006

Probabilistic Design of Composite Structures

A formal procedure for the probabilistic design evaluation of a composite structure is described. The uncertainties in all aspects of a composite structure (constituent material properties, fabrication variables, structural geometry, and service environments, etc.), which result in the uncertain behavior in the composite structural responses, are included in the evaluation. The probabilistic evaluation consists of: (1) design criteria, (2) modeling of composite structures and uncertainties, (3) simulation methods, and (4) the decision-making process. A sample case is presented to illustrate the formal procedure and to demonstrate that composite structural designs can be probabilistically evaluated with accuracy and efficiency.

Chamis, Christos C.↗

NASA NTRS2007

Risk Assessment: Evidence Base

Human systems PRA (Probabilistic Risk Assessment: a) Provides quantitative measures of probability, consequence, and uncertainty; and b) Communicates risk and informs decision-making. Human health risks rated highest in ISS PRA are based on 1997 assessment of clinical events in analog operational settings. Much work remains to analyze remaining human health risks identified in Bioastronautics Roadmap.

Johnson-Throop, Kathy A.↗

NASA NTRS2017

The Epic Chronicle of Designing Cassini's Titan Flyby Altitudes

The selection and optimization of Titan flyby altitudes for NASA's Cassini mission at Saturn has traveled a long, fascinating, and often torturous sixteen-year path - starting in 2001, when pre-arrival trajectory design decisions had to be made, through April of 2017 when Cassini's last, and arguably most critical, low flyby takes place. The chronicle of designing and updating the Titan flyby altitudes have twists and turns enough to satisfy a full-length novel or feature film, including: critical design decision-making before arrival with multiple atmospheric models, high uncertainties, and limited data; early flybys that seemed to show trends that weren't there; use and misuse of statistical analysis; unexpected surprises with limited reaction time; navigation of a scientific, engineering, and management community with a wide array of inherent biases; and consideration of a variety of project risk postures in a high-scrutiny, high-impact, high-reward environment.

Bittner, Molly↗

NASA NTRS2020

Toward Comprehensive Uncertainty Predictions for Remote Imaging Spectroscopy

Remote imaging spectroscopy’s role in Earth science will grow in the coming decade as a series of globe-spanning spectroscopy missions launch from NASA, ESA, and other agencies. The nature of remote imaging spectroscopy will change, advancing from short regional studies to address global multi-year questions. The diversity of data will also grow with exposure to a wider range of biomes and atmospheric conditions. To execute these new investigations we must reconcile diverse observing conditions to derive consistent global maps. To this end, rig- orous uncertainty quantification and propagation enables an optimal synthesis of data accounting for observing conditions and data quality. Understanding data uncertainties is also important for principled hypothesis testing, information content assessment, and informed decision making by end users. We survey prior efforts in uncer- tainty quantification for imaging spectroscopy, and describe methods for validating the accuracy of uncertainty predictions. We conclude with a discussion of remaining challenges and promising avenues for future research.

Susiluoto, Jouni↗

NASA NTRS2016

Effects of Acute Exposures to Carbon Dioxide Upon Cognitive Functions

Large quantities of carbon dioxide (CO2) originate from human metabolism and typically, within spacecraft, remain about 10-fold higher in concentration than at the earth's surface. There have been recurring complaints by crew members of episodes of "mental viscosity" adversely affecting their performance, and there is evidence from the International Space Station (ISS) that associates CO2 levels with reports of headaches by crewmembers. Additionally, there is concern that CO2 may contribute to vision impairment and intracranial pressure that has been observed in some crewmembers. Consequently, flight rules have been employed to control the level of CO2 below 4 mm Hg, which is well below the existing Spacecraft Maximum Allowable Concentration (SMAC) of 10 mm Hg for 24-hour exposures, and 5.3 mm Hg for exposures of 7 to 180 days. However, the flight rule imposed limit, which places additional demands upon resources and current technology, still exceeds the lower bound of the threshold range for reportable headaches (2 - 5 mm Hg). Headaches, while sometime debilitating themselves, are also symptoms that can provide evidence that physiological defense mechanisms have been breached. The causes of the headaches may elicit other subtle adverse effects that occur at CO2 levels well below that for headaches. The concern that CO2 may have effects at levels below the threshold for headaches appears to be substantiated in unexpected findings that CO2 at concentrations below 2 mm Hg substantially reduced some cognitive functions that are associated with the ability to make complex decisions in conditions that are characterized by volatility, uncertainty, complexity, ambiguity, and delayed feedback. These are conditions that could be encountered by crews in off-nominal situations or during the first missions beyond low earth orbit. If findings of the earlier study are confirmed in crew-like subjects, our findings would provide additional evidence that CO2 may need to be controlled at levels that are well below current spacecraft limits. Our study will extend the earlier study to determine if crew-like subjects are similarly effected by CO2. In addition to employing the Strategic Management Simulation tool, we will use the Cognition battery of psychometric measures that are being utilized aboard the ISS. It will be important to learn, by using Cognition, if additional cognitive domains are sensitive to concentrations of CO2 at or below limits currently controlled by flight rules. While spaceflight Cognition data will greatly enhance the knowledge base related to inflight behavioral health and performance, some of the measures may be influenced by fatigue (related to sleep deprivation and or workload) and changes in circadian rhythms. Therefore our use of this battery of tests in a well-controlled, ground-based study that is free of these potential confounding influences will establish a baseline terrestrial data set against which Cognition data collected in flight may be assessed. The findings from this study will be useful to the NASA Toxicology Office and the National Research Council Committee on Toxicology, which assists NASA in setting environmental standards, for revision of the SMAC for CO2, and for designing further studies on effects of CO2 upon cognitive functions.

Scully, R. R.↗

NASA NTRSDate not supplied

Mod-Sim and Decision-Making in Aerospace Domain

Explore the source record for details and available documents.

modeling and simulation↗

NASA NTRS2005

Decomposition-Based Decision Making for Aerospace Vehicle Design

Most practical engineering systems design problems have multiple and conflicting objectives. Furthermore, the satisfactory attainment level for each objective ( requirement ) is likely uncertain early in the design process. Systems with long design cycle times will exhibit more of this uncertainty throughout the design process. This is further complicated if the system is expected to perform for a relatively long period of time, as now it will need to grow as new requirements are identified and new technologies are introduced. These points identify a need for a systems design technique that enables decision making amongst multiple objectives in the presence of uncertainty. Traditional design techniques deal with a single objective or a small number of objectives that are often aggregates of the overarching goals sought through the generation of a new system. Other requirements, although uncertain, are viewed as static constraints to this single or multiple objective optimization problem. With either of these formulations, enabling tradeoffs between the requirements, objectives, or combinations thereof is a slow, serial process that becomes increasingly complex as more criteria are added. This research proposal outlines a technique that attempts to address these and other idiosyncrasies associated with modern aerospace systems design. The proposed formulation first recasts systems design into a multiple criteria decision making problem. The now multiple objectives are decomposed to discover the critical characteristics of the objective space. Tradeoffs between the objectives are considered amongst these critical characteristics by comparison to a probabilistic ideal tradeoff solution. The proposed formulation represents a radical departure from traditional methods. A pitfall of this technique is in the validation of the solution: in a multi-objective sense, how can a decision maker justify a choice between non-dominated alternatives? A series of examples help the reader to observe how this technique can be applied to aerospace systems design and compare the results of this so-called Decomposition-Based Decision Making to more traditional design approaches.

Borer, Nicholas K.↗