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NASA NTRSDate not supplied

Confidence-Based Buffer for Strategic Deconfliction with Probabilistic Operational Intent

This paper presents a methodology to expand the 95% confidence level of the elliptical geometry given by Unmanned Aircraft System (UAS) operators planning to fly Beyond Visual Line of Sight (BVLOS) to any confidence level before being fed to the strategic deconfliction (SD) module, effectively increasing the separation buffer between Operational Intents (OIs). To assess the performance of this approach, it is integrated within an adaptation of the Rolling Horizon with K-Position Search volume-based strategic deconfliction approach, previously developed at NASA Ames, preventing the 4D overlapping of OIs shaped by ellipses instead of traditional blocks. Safety and efficiency metrics are evaluated through the deconfliction of four simulated package delivery route network structures across the San Francisco Metropolitan Area with increasing numbers of crossing waypoints (network complexity). Safety assessment entails the in-house creation of a metric to quantify collision occurrences per flight hour based on the frequency at which the probabilistic operational volume segments are sampled, whereas efficiency is measured using ground delay. Results indicate that the largest buffer growth occurs when increasing the confidence level beyond 99.9% and demonstrate the negative impact of network complexity on both metrics, regardless of the OI geometry. Further, the ellipse-based SD adaptation more accurately estimates temporal separation at crossings, allowing deconflicted vehicles to be closer together. It is concluded that the proposed methodology enables the desired confidence level to serve as an effective controller of buffer size.

safety↗

NASA NTRS1996

Reporter Concerns in 300 Mode-Related Incident Reports from NASA's Aviation Safety Reporting System

A model has been developed which represents prominent reporter concerns expressed in the narratives of 300 mode-related incident reports from NASA's Aviation Safety Reporting System (ASRS). The model objectively quantifies the structure of concerns which persist across situations and reporters. These concerns are described and illustrated using verbatim sentences from the original narratives. Report accession numbers are included with each sentence so that concerns can be traced back to the original reports. The results also include an inventory of mode names mentioned in the narratives, and a comparison of individual and joint concerns. The method is based on a proximity-weighted co-occurrence metric and object-oriented complexity reduction.

McGreevy, Michael W.↗

NASA NTRSDate not supplied

Improving Quantification of Medical Evacuation Risk for Human Spaceflight in the IMPACT Model

Traditionally, mission planners have used a heuristic and qualitative approach to design medical systems based on prior experience however this approach may result in high variability and implicit bias to design and could put missions and crewmembers at risk. The Informing Mission Planning through Analysis of Complex Tradespaces (IMPACT) tool is a probabilistic risk assessment tool designed by NASA to model medical risk in long duration missions outside of low earth orbit (LEO). This tool can quantify risk metrics such as risk of crewmember death, loss of crew task time, and the need for medical evacuation to better inform and augment the more traditional approach to medical system design. The risk metric of Return to Definitive Care (RTDC) represents the likelihood of requiring medical evacuation and has been difficult to quantify in a reliable and standardized manner. Initial development of the RTDC metric was constrained due to the complexity of a medical evacuation decision and the lack of prior spaceflight data and this presentation will discuss the review and improvement process used to increase model accuracy and fidelity.

Prashant Parmar↗

NASA NTRS1993

Intelligent Agent Architectures: Reactive Planning Testbed

An Integrated Agent Architecture (IAA) is a framework or paradigm for constructing intelligent agents. Intelligent agents are collections of sensors, computers, and effectors that interact with their environments in real time in goal-directed ways. Because of the complexity involved in designing intelligent agents, it has been found useful to approach the construction of agents with some organizing principle, theory, or paradigm that gives shape to the agent's components and structures their relationships. Given the wide variety of approaches being taken in the field, the question naturally arises: Is there a way to compare and evaluate these approaches? The purpose of the present work is to develop common benchmark tasks and evaluation metrics to which intelligent agents, including complex robotic agents, constructed using various architectural approaches can be subjected.

Rosenschein, Stanley J.↗

NASA NTRS1986

Properties of metre-wavelength solar bursts associated with coronal mass ejections

An investigation is made to determine the relationship between a coronal mass ejection (CME) and the characteristics of associated metre-wave activity. It is found that (1) the CME width and leading edge velocity can be highly influential in determining the intensity, spectral complexity and frequency coverage of both type II and continuum burst; (2) the presence of a CME is possibly a necessary condition for the production of a metric continuum event and (3) metric continuum bursts as well as intense, complex type II events are preferentially associated with strong, long lasting soft X-ray events.

Robinson, R. D.↗

NASA NTRS2011

Frame Synchronization Without Attached Sync Markers

We describe a method to synchronize codeword frames without making use of attached synchronization markers (ASMs). Instead, the synchronizer identifies the code structure present in the received symbols, by operating the decoder for a handful of iterations at each possible symbol offset and forming an appropriate metric. This method is computationally more complex and doesn't perform as well as frame synchronizers that utilize an ASM; nevertheless, the new synchronizer acquires frame synchronization in about two seconds when using a 600 kbps software decoder, and would take about 15 milliseconds on prototype hardware. It also eliminates the need for the ASMs, which is an attractive feature for short uplink codes whose coding gain would be diminished by the overheard of ASM bits. The lack of ASMs also would simplify clock distribution for the AR4JA low-density parity-check (LDPC) codes and adds a small amount to the coding gain as well (up to 0.2 dB).

Hamkins, Jon↗

NASA NTRS2011

Climate Change Impact Uncertainties for Maize in Panama: Farm Information, Climate Projections, and Yield Sensitivities

We present results from a pilot project to characterize and bound multi-disciplinary uncertainties around the assessment of maize (Zea mays) production impacts using the CERES-Maize crop model in a climate-sensitive region with a variety of farming systems (Panama). Segunda coa (autumn) maize yield in Panama currently suffers occasionally from high water stress at the end of the growing season, however under future climate conditions warmer temperatures accelerate crop maturation and elevated CO (sub 2) concentrations improve water retention. This combination reduces end-of-season water stresses and eventually leads to small mean yield gains according to median projections, although accelerated maturation reduces yields in seasons with low water stresses. Calibrations of cultivar traits, soil profile, and fertilizer amounts are most important for representing baseline yields, however sensitivity to all management factors is reduced in an assessment of future yield changes (most dramatically for fertilizers), suggesting that yield changes may be more generalizable than absolute yields. Uncertainty around General Circulation Model (GCM)s' projected changes in rainfall gain in importance throughout the century, with yield changes strongly correlated with growing season rainfall totals. Climate changes are expected to be obscured by the large inter-annual variations in Panamanian climate that will continue to be the dominant influence on seasonal maize yield into the coming decades. The relatively high (A2) and low (B1) emissions scenarios show little difference in their impact on future maize yields until the end of the century. Uncertainties related to the sensitivity of CERES-Maize to carbon dioxide concentrations have a substantial influence on projected changes, and remain a significant obstacle to climate change impacts assessment. Finally, an investigation into the potential of simple statistical yield emulators based upon key climate variables characterizes the important uncertainties behind the selection of climate change metrics and their performance against more complex process-based crop model simulations, revealing a danger in relying only on long-term mean quantities for crop impact assessment.

Maize↗

NASA NTRS1987

A task-based metric for telerobotic performance assessment

A methodology is described for developing a task complexity index based on combining the six basic motion primitives (three translation, three orientation) with force control and accuracy requirements. The result of this development is a set of complexity values that can be assigned to the high-level task primitives derived from a relatively shallow top-down mission analysis. These values are then averaged to arrive at total average mission complexities, such as for the mission of exchanging the Hubble Space Telescope (HST) battery modules. Application of this metric to a candidate set of NASA Flight Telerobotic Servicer evaluation tasks is discussed using the HST battery module mission for an in-depth example.

Barnes, J. F.↗

NASA NTRS2008

Trajectory Planning by Preserving Flexibility: Metrics and Analysis

In order to support traffic management functions, such as mitigating traffic complexity, ground and airborne systems may benefit from preserving or optimizing trajectory flexibility. To help support this hypothesis trajectory flexibility metrics have been defined in previous work to represent the trajectory robustness and adaptability to the risk of violating safety and traffic management constraints. In this paper these metrics are instantiated in the case of planning a trajectory with the heading degree of freedom. A metric estimation method is presented based on simplifying assumptions, namely discrete time and heading maneuvers. A case is analyzed to demonstrate the estimation method and its use in trajectory planning in a situation involving meeting a time constraint and avoiding loss of separation with nearby traffic. The case involves comparing path-stretch trajectories, in terms of adaptability and robustness along each, deduced from a map of estimated flexibility metrics over the solution space. The case demonstrated anecdotally that preserving flexibility may result in enhancing certain factors that contribute to traffic complexity, namely reducing proximity and confrontation.

Idris, Husni R.↗

NASA NTRSDate not supplied

Applying Machine Learning Tools for Runway Configuration Decision Support

Determining optimal runway configurations at airports, a responsibility assigned to air traffic controllers, is a challenging task. The decision-making process is intricate and involves consideration of many factors such as prevailing wind condition, convective weather, visibility, cloud ceilings, departure and arrival demand, traffic flow, equipment status, and other airport constraints. In a previous work, we developed a Runway Configuration Assistance tool using an offline reinforcement learning method called conservative Q-learning. In this paper, we evaluate and validate our Runway Configuration Assistance tool as a decision support for air traffic controllers. We validated our tool using three airports with differing levels of complexity: Charlotte Douglas International Airport, Denver International Airport, and Dallas Fort Worth International Airport. We quantified the performance of the Runway Configuration Assistance tool based on (1) agreement with historical air traffic controller decisions and (2) violation of decisions that would be obvious to subject-matter experts. Our tool showed promising results in both performance metrics for the three airports, despite the complexities in the runway configuration decision-making process. We also discuss challenges in using machine learning in general to aid air traffic management and identify deployment considerations for the Runway Configuration Assistance tool.

Runway Configuration Management↗

NASA NTRSDate not supplied

Machine Learning Tools for Runway Configuration Decision Support

Runway Configuration Management↗

NASA NTRS1998

Dynamic Density: An Air Traffic Management Metric

The definition of a metric of air traffic controller workload based on air traffic characteristics is essential to the development of both air traffic management automation and air traffic procedures. Dynamic density is a proposed concept for a metric that includes both traffic density (a count of aircraft in a volume of airspace) and traffic complexity (a measure of the complexity of the air traffic in a volume of airspace). It was hypothesized that a metric that includes terms that capture air traffic complexity will be a better measure of air traffic controller workload than current measures based only on traffic density. A weighted linear dynamic density function was developed and validated operationally. The proposed dynamic density function includes a traffic density term and eight traffic complexity terms. A unit-weighted dynamic density function was able to account for an average of 22% of the variance in observed controller activity not accounted for by traffic density alone. A comparative analysis of unit weights, subjective weights, and regression weights for the terms in the dynamic density equation was conducted. The best predictor of controller activity was the dynamic density equation with regression-weighted complexity terms.

Laudeman, I. V.↗

NASA NTRSDate not supplied

Tracking Critical Thermal Metrics throughout the Life Cycle of a Large Observatory Thermal Model

Observatory thermal models for large, complex missions, such as the Wide Field InfraRed Survey Telescope (WFIRST) mission, produce an immense amount of data to be processed. Configuration management of the model throughout the project life cycle has mainly focused on which versions of the subsystem models form the current observatory level configuration. However, the results produced by the model are not nearly as well tracked and traceable. Given the various states of design maturity for each of the components in the WFIRST design, an updated component model is nearly ready to be integrated at the next higher level of assembly about every month or two. With each subsystem model delivery, the observatory model needs to remove the old component, integrate the new one, execute the model, and inspect the results. Usually, this inspection focuses primarily on the newly integrated component. Recently, a Metric Tracking Spreadsheet was developed to help provide a “big picture” view of the entire observatory highlighting key parameters critical to mission performance. This spreadsheet helps track impacts on subsystems by updates of other subsystems that were not intuitively obvious. Metrics tracked include: absorbed environmental loading (to determine effectiveness of sunshield), temperatures of critical avionics, electrical dissipations, heater power predictions, stability of critical optics, parasitic heat leaks in cryogenic region, high level heat flows between elements, and model run time. Producing this data for the same operational configuration with each model update has helped produce a trail of data to evaluate the impact of model updates. While the metrics selected are specific for WFIRST, other large, complex observatories could be well served to establish their own metrics early in the project life cycle to track to quickly assess the impact of any subsystem on other subsystems or the overall system itself.

Thermal Desktop↗

NASA NTRSDate not supplied

Nearfield Anisotropic Mesh Adaptation for the Third AIAA Sonic Boom Workshop

Sonic boom prediction is critical for the development of low-boom supersonic aircraft and encouraging a replacement of the overland commercial supersonic ban with a certification standard. The Third AIAA Sonic Boom Workshop nearfield test cases provide a unique opportunity to review anisotropic adaptive-mesh strategies for complex geometries with important propulsion interaction effects. Anisotropic metrics formulated to control estimated Mach interpolation and integrated nearfield pressure signature (goal-oriented) errors are compared with the results obtained on workshop-provided meshes. Detailed flow solutions and mesh renderings are combined with computational schlieren images to reveal the complex interactions present in a shock-plume interaction wind tunnel model and a prototype of the Low-Boom Flight Demonstrator. A favorable comparison of independent implementations of the entire simulation process provides evidence that each process is implemented correctly and sets a solid foundation for confidence in the nearfield prediction of each method.

sonic boom↗

NASA NTRS2005

Safety and Mission Assurance Performance Metric

The safety and mission assurance (S&MA) performance metric is a method that provides a process through which the managers of a large, complex program can readily understand and assess the accepted risk, the problems, and the associated reliability of the program. Conceived for original use in helping to assure the safety and success of the International Space Station (ISS) program, the S&MA performance metric also can be applied to other large and complex programs and projects. The S&MA-performance-metric data products comprise one or more tables (possibly also one or more graphs) that succinctly display all of the information relevant (and no information that is irrelevant) to management decisions that must be made to assure the safety and success of a program or project, thereby facilitating such decisions.

Holsomback, Jerry↗

NASA NTRS1991

A generalized scheme for three-dimensional hyperbolic grid generation

A hyperbolic grid generation scheme formulated from grid orthogonality and cell volume specification is generalized such that high quality three-dimensional grids can be obtained for a wide variety of geometries. The speed of the scheme is one to two orders of magnitude faster than typical elliptic grid generation methods. The robustness of the scheme is significantly enhanced by several new techniques. By using a spatially variable smoothing coefficient, orthogonality and smoothness of the grid are maintained around complex concave and convex surface topologies. A metric correction procedure is employed to guarantee that the grid marches out of a corner by bisecting the angles subtended by the neighboring points. Extra robustness at severe convex corners is achieved by special local treatments. Different extrapolation methods are used to provide smoothness at floating edges and axis regions. The versatility of the new hyperbolic grid generation scheme is demonstrated by three-dimensional grids generated for external components of the intergrated Space Shuttle vehicle and the SOFIA telescope.

Chan, William M.↗

NASA NTRS1994

Software Process Assessment (SPA)

NASA's environment mirrors the changes taking place in the nation at large, i.e. workers are being asked to do more work with fewer resources. For software developers at NASA's Goddard Space Flight Center (GSFC), the effects of this change are that we must continue to produce quality code that is maintainable and reusable, but we must learn to produce it more efficiently and less expensively. To accomplish this goal, the Data Systems Technology Division (DSTD) at GSFC is trying a variety of both proven and state-of-the-art techniques for software development (e.g., object-oriented design, prototyping, designing for reuse, etc.). In order to evaluate the effectiveness of these techniques, the Software Process Assessment (SPA) program was initiated. SPA was begun under the assumption that the effects of different software development processes, techniques, and tools, on the resulting product must be evaluated in an objective manner in order to assess any benefits that may have accrued. SPA involves the collection and analysis of software product and process data. These data include metrics such as effort, code changes, size, complexity, and code readability. This paper describes the SPA data collection and analysis methodology and presents examples of benefits realized thus far by DSTD's software developers and managers.

Rosenberg, Linda H.↗

NASA NTRSDate not supplied

On the Notional Impact of Background Noise on the Human Response to UAVs

Proponents of UAV-based industries would like to think that their aircraft will be incapable of causing annoyance (among other negative responses) in the communities that they serve due to the noise of their vehicles simply not being heard over the existing soundscape. No measures of noise that are in wide use today for aviation take background sound into consideration, and thus would not predict this outcome. This work is an attempt to bridge this gap by looking at past results from psychoacoustic research in which background sounds appear to play a significant role (not just for aviation sources). It includes information on the problem of human auditory detection in general – what is the transductive mechanism of the ear, how does one quantify detectability, etc., and it attempts to make the connection between detectability and annoyance. A notional schematic version of how measures/predictions of these two aspects may be incorporated into a single assessment of noise is given. Overall, detectability is shown to be very complex to predict relative to conventional noise metrics that are used to correlate with human response. Given this, the outlook for the use of measures of detectability in scientific, industrial, and regulatory applications is discussed.

UAV↗