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NASA NTRS1991

Systematic methods for knowledge acquisition and expert system development

Nine cooperating rule-based systems, collectively called AUTOCREW which were designed to automate functions and decisions associated with a combat aircraft's subsystems, are discussed. The organization of tasks within each system is described; performance metrics were developed to evaluate the workload of each rule base and to assess the cooperation between the rule bases. Simulation and comparative workload results for two mission scenarios are given. The scenarios are inbound surface-to-air-missile attack on the aircraft and pilot incapacitation. The methodology used to develop the AUTOCREW knowledge bases is summarized. Issues involved in designing the navigation sensor selection expert in AUTOCREW's NAVIGATOR knowledge base are discussed in detail. The performance of seven navigation systems aiding a medium-accuracy INS was investigated using Kalman filter covariance analyses. A navigation sensor management (NSM) expert system was formulated from covariance simulation data using the analysis of variance (ANOVA) method and the ID3 algorithm. ANOVA results show that statistically different position accuracies are obtained when different navaids are used, the number of navaids aiding the INS is varied, the aircraft's trajectory is varied, and the performance history is varied. The ID3 algorithm determines the NSM expert's classification rules in the form of decision trees. The performance of these decision trees was assessed on two arbitrary trajectories, and the results demonstrate that the NSM expert adapts to new situations and provides reasonable estimates of the expected hybrid performance.

Belkin, Brenda L.↗

NASA NTRS2009

Benefits Assessment of Algorithmically Combining Generic High Altitude Airspace Sectors

In today's air traffic control operations, sectors that have traffic demand below capacity are combined so that fewer controller teams are required to manage air traffic. Controllers in current operations are certified to control a group of six to eight sectors, known as an area of specialization. Sector combinations are restricted to occur within areas of specialization. Since there are few sector combination possibilities in each area of specialization, human supervisors can effectively make sector combination decisions. In the future, automation and procedures will allow any appropriately trained controller to control any of a large set of generic sectors. The primary benefit of this will be increased controller staffing flexibility. Generic sectors will also allow more options for combining sectors, making sector combination decisions difficult for human supervisors. A sector-combining algorithm can assist supervisors as they make generic sector combination decisions. A heuristic algorithm for combining under-utilized air space sectors to conserve air traffic control resources has been described and analyzed. Analysis of the algorithm and comparisons with operational sector combinations indicate that this algorithm could more efficiently utilize air traffic control resources than current sector combinations. This paper investigates the benefits of using the sector-combining algorithm proposed in previous research to combine high altitude generic airspace sectors. Simulations are conducted in which all the high altitude sectors in a center are allowed to combine, as will be possible in generic high altitude airspace. Furthermore, the algorithm is adjusted to use a version of the simplified dynamic density (SDD) workload metric that has been modified to account for workload reductions due to automatic handoffs and Automatic Dependent Surveillance Broadcast (ADS-B). This modified metric is referred to here as future simplified dynamic density (FSDD). Finally, traffic demand sets with increased air traffic demand are used in the simulations to capture the expected growth in air traffic demand by the mid-term.

Bloem, Michael↗

NASA NTRS2005

Analysis of Aircraft Clusters to Measure Sector-Independent Airspace Congestion

The Distributed Air/Ground Traffic Management (DAG-TM) concept of operations* permits appropriately equipped aircraft to conduct Free Maneuvering operations. These independent aircraft have the freedom to optimize their trajectories in real time according to user preferences; however, they also take on the responsibility to separate themselves from other aircraft while conforming to any local Traffic Flow Management (TFM) constraints imposed by the air traffic service provider (ATSP). Examples of local-TFM constraints include temporal constraints such as a required time of arrival (RTA), as well as spatial constraints such as regions of convective weather, special use airspace, and congested airspace. Under current operations, congested airspace typically refers to a sector(s) that cannot accept additional aircraft due to controller workload limitations; hence Dynamic Density (a metric that is indicative of controller workload) can be used to quantify airspace congestion. However, for Free Maneuvering operations under DAG-TM, an additional metric is needed to quantify the airspace congestion problem from the perspective of independent aircraft. Such a metric would enable the ATSP to prevent independent aircraft from entering any local areas of congestion in which the flight deck based systems and procedures may not be able to ensure separation. This new metric, called Gaggle Density, offers the ATSP a mode of control to regulate normal operations and to ensure safety and stability during rare-normal or off-normal situations (e.g., system failures). It may be difficult to certify Free Maneuvering systems for unrestricted operations, but it may be easier to certify systems and procedures for specified levels of Gaggle Density that could be monitored by the ATSP, and maintained through relatively minor flow-rate (RTA type) restrictions. Since flight deck based separation assurance is airspace independent, the challenge is to measure congestion independent of sector boundaries. Figure 1 , reproduced from Ref. 1, depicts an example traffic situation. When the situation is analyzed by sector boundaries (left side of figure), a Dynamic Density metric would identify excessive congestion in the central sector. When the same traffic situation is analyzed independent of sector boundaries (right side of figure), a Gaggle Density metric would identify congestion in two dynamically defined areas covering portions of several sectors. The first step towards measuring airspace-independent congestion is to identify aircraft clusters, i.e., groups of closely spaced aircraft. The objective of this work is to develop techniques to detect and classify clusters of aircraft.

Bilimoria, Karl D.↗

DOE OSTI2025

Improving Cyber Situational Understanding

Effective cybersecurity operations require the ability to analyze large amounts of information to assess security risks and formulate defensive strategies against adversaries. This has become more complex in recent years as the sprawl and interconnectivity of devices grows through implementation of virtualization, cloud computing, and Internet of Things (IoT). The amount of data and analysis required for effective cybersecurity command and control decisions far exceeds humans’ capacity to perform manually. We characterize the analysis problem as cyber situational understanding. The research presented to improve cyber situational understanding focuses on vulnerability analysis and threat intelligence. Regarding vulnerabilities, entities must analyze and plan work for between thousands and tens of thousands of software vulnerabilities annually. Entities heavily use network firewalls to limit vulnerability exposure. As a result, some of these vulnerabilities permit exposure to adversarial exploitation, whereas others are inaccessible and therefore present negligible risk of exploitation. Distinguishing between high and low risk software vulnerabilities requires a deep understanding of the vulnerability, network firewall protection, and characteristics of the targeted device. This problem is solved by extracting network service features from vulnerability data features using both machine-learning and natural language processing. Then, the network firewall topology is parsed to determine which vulnerabilities are reachable by adversaries. Ultimately, a state-based safety analysis ascertains which vulnerabilities are unsafe. A related vulnerability analysis problem occurs in cybersecurity operations when associating an entity’s hardware and software assets to public vulnerability databases. Assets often reveal hardware and software through installation artifacts and network service identification, and entities store these artifacts in inventory databases. However, software and hardware vendors apply a standard Common Platform Enumeration (CPE) naming convention when publicly reporting vulnerabilities. Associating these two datasets often requires many hours to days of manual inspection. The proposed solution automates the mapping approach of human analysts using fuzzy matching techniques, natural language processing, and, ultimately, machine learning to present a small set of recommendations for mapping the two datasets. The result significantly reduces human analysis time and reduces the occurrence of false positives in vulnerability notifications. Finally, cyber threat intelligence (CTI) requires associating cyber observable artifacts, such as IP addresses, URIs, and file hashes, with cyber threat tactics, techniques, and procedures. Unfortunately, most CTI data is compartmentalized across multiple organizations and cannot be shared due to the legal and reputational risk with cyber threat being associated with the entity. The approach to solving this problem inovlves using a distributed ledger with anonymous token spending and authentication. This allows a consortium of semi-trusted entities to share the workload of curating CTI for a threat sharing community’s cooperative benefit.

Huff, Philip↗

NASA NTRSDate not supplied

Evaluation of Aerobic Standards for Lunar Surface Extravehicular Activities

Introduction: As NASA prepares to return to the Moon, astronauts will need to be physically primed to successfully execute Extravehicular Activities (EVA) on the Lunar surface. Compared to past Apollo missions, Artemis missions will include EVAs of increased physical demand, frequency, intensity, and duration, thus requiring adequate fitness to successfully and safely complete mission objectives. The physical demand associated with partial gravity (g) EVAs on the Moon is expected to be greater compared to microgravity EVAs based on initial workload estimation. Currently, aerobic fitness standards for partial g EVAs are not well supported by high-fidelity data and require further research for establishing standards to protect crew health and performance during Lunar surface missions. Therefore, the aim of this investigation is to characterize metabolic data from Lunar analog simulations and in-flight crew population aerobic capacity data to validate the current NASA 3001 standard for celestial partial g aerobic fitness (aerobic capacity (VO_2pk) ≥36.5ml/kg/min). Methods: In order to evaluate aerobic fitness requirements for Lunar EVAs, the following were performed: 1) preliminary analysis of long-duration (6 hr) EVA analog simulations in the Neutral Buoyancy Laboratory (NBL) and the Active Response Gravity Offload System (ARGOS) to evaluate expected metabolic rates for 1/6 g EVAs (NBL: n=1 female; ARGOS: n=1 male) and 2) assessment of the current NASA 3001 celestial surface EVA aerobic standard (aerobic capacity (VO_2pk) ≥36.5ml/kg/min) with data from an ISS astronaut population (n=30 male + 13 female) captured before and during space flight (flight day 15). Preliminary Results: Average fractional aerobic capacity during simulated EVAs were 33%±7% VO_2pk and 23.3±7% VO_2pk in the NBL and ARGOS, respectively. This was within a previously predicted 30–40% sustainable work rate. Average metabolic rates for some tasks performed in the NBL, such as traverse (40.4% VO_2pk) and ingress (47.1% VO_2pk) were higher than the predicted sustainable work range. In ARGOS, the tasks with the greatest metabolic rates were object relocation (34.2% VO_2pk) and incapacitated crew rescue (27.0% VO_2pk). Characterization of ISS crewmember aerobic capacity determined that the average preflight VO_2pk was 42.1±5.4 ml/kg/min for females and 37.5±5.4 ml/kg/min for males. At preflight, 21.5% of crewmembers were below the 36.5 ml/kg/min in-mission aerobic standard for celestial surface EVA as outlined in NASA-STD-3001. In-flight, both female and male crewmembers experienced reductions in VO_2pk (11.7% and 10.9%, respectively), such that, during the mission, 62% of crewmembers were below the standard aerobic capacity level for celestial surface EVAs. Conclusions: Our preliminary data suggest that while average metabolic rates for simulated Lunar EVA fall within the 30–40% sustainable work range, task specific metabolic rates exceed this range and may indicate that greater fitness is necessary for more strenuous tasks expected to be performed on the Lunar surface. Additionally, deconditioning due to space flight results in most crewmembers falling below the current celestial partial g EVA standard, which may increase risk to crew health and performance and completing mission objectives for surface missions. Further research is necessary in Artemis-specific analog environments to validate the current NASA-3001 aerobic standard for celestial EVAs. Additionally, work is ongoing to validate the current NASA-3001 strength standard for celestial EVAs.

N.C. Strock↗

DOE OSTI2026

A GPU-based compressible combustion solver for applications exhibiting disparate space and time scales

High-speed chemically active flows pose significant computational challenges due to their disparate space and time scales, with stiff chemistry often dominating simulation time. While modern scientific computing programs achieve exascale performance by leveraging graphics processing units (GPUs), existing GPU-based compressible combustion solvers face critical limitations in memory management, load balancing, and handling the highly localized nature of chemical reactions. To this end, we present a high-performance compressible reacting flow solver built on the AMReX framework and optimized for multi-GPU settings. Here, our approach addresses three GPU performance bottlenecks: memory access patterns through column-major storage optimization, computational workload variability via a bulk-sparse integration strategy for chemical kinetics, and multi-GPU load distribution for adaptive mesh refinement applications. The solver adapts existing matrix-based chemical kinetics formulations to multi-grid contexts. Using representative combustion applications, including 2D and 3D detonations and a 3D jet-in-crossflow configuration, we demonstrate 1.4–5× performance improvements over initial implementations on an in-house cluster of NVIDIA H100 GPUs, and near-ideal weak scaling on the Frontier supercomputer (Oak Ridge Leadership Computing Facility) with up to 1024 AMD Instinct MI250X GPUs. Roofline analysis reveals substantial improvements in arithmetic intensity for both convection (∼ 10 ×) and chemistry (∼ 4 ×) routines, confirming efficient utilization of GPU memory bandwidth and computational resources.

42 ENGINEERING↗

NASA NTRS2002

Workload-Matched Adaptive Automation Support of Air Traffic Controller Information Processing Stages

Adaptive automation (AA) has been explored as a solution to the problems associated with human-automation interaction in supervisory control environments. However, research has focused on the performance effects of dynamic control allocations of early stage sensory and information acquisition functions. The present research compares the effects of AA to the entire range of information processing stages of human operators, such as air traffic controllers. The results provide evidence that the effectiveness of AA is dependent on the stage of task performance (human-machine system information processing) that is flexibly automated. The results suggest that humans are better able to adapt to AA when applied to lower-level sensory and psychomotor functions, such as information acquisition and action implementation, as compared to AA applied to cognitive (analysis and decision-making) tasks. The results also provide support for the use of AA, as compared to completely manual control. These results are discussed in terms of implications for AA design for aviation.

Kaber, David B.↗

NASA NTRS2016

Improving Operational Acceptability of Dynamic Weather Routes Through Analysis of Commonly Use Routings

The Dynamic Weather Routes (DWR) tool is a ground-based trajectory automation system that continuously and automatically analyzes active in-flight aircraft in en route airspace to find simple modifications to flight plan routes that can save significant flying time, while avoiding weather and considering traffic conflicts, airspace sector congestion, special use airspace, and FAA routing restrictions. Trials of the DWR system have shown that significant delay savings are possible. However, some DWR advised routes are also rejected by dispatchers or modified before being accepted. Similarly, of those sent by dispatchers to flight crews as proposed route change requests, many are not accepted by air traffic control, or are modified before implementation as Center route amendments. Such actions suggest that the operational acceptability of DWR advised route corrections could be improved, which may reduce workload and increase delay savings. This paper analyzes the historical usage of different flight routings, varying from simple waypoint pairs to lengthy strings of waypoints incorporating jet routes, in order to improve DWR route acceptability. An approach is developed that can be incorporated into DWR, advising routings with high historical usage and savings potential similar to that of the nominal DWR advisory. It is hypothesized that modifying a nominal DWR routing to one that is commonly used, and nearby, will result in more actual savings since common routings are generally familiar and operationally acceptable to air traffic control. The approach allows routing segments with high historical usage to be concatenated to form routes that meet all DWR constraints. The relevance of a route's historical usage to its acceptance by dispatchers and air traffic control is quantified by analyzing historical DWR data. Results indicate that while historical usage may be less of a concern to flight dispatchers accepting or rejecting DWR advised route corrections, it may be important to air traffic control acceptance of DWR routes.

dynamic weather routes↗

NASA NTRS2016

Improving Operational Acceptability of Dynamic Weather Routes (DWR) Through Analysis of Commonly Used Routings

The Dynamic Weather Routes (DWR) tool is a ground-based trajectory automation system that continuously and automatically analyzes active in-flight aircraft in en route airspace to find simple modifications to flight plan routes that can save significant flying time, while avoiding weather and considering traffic conflicts, airspace sector congestion, special use airspace, and FAA routing restrictions. Trials of the DWR system have shown that significant delay savings are possible. However, some DWR advised routes are also rejected by dispatchers or modified before being accepted. Similarly, of those sent by dispatchers to flight crews as proposed route change requests, many are not accepted by air traffic control, or are modified before implementation as Center route amendments. Such actions suggest that the operational acceptability of DWR advised route corrections could be improved, which may reduce workload and increase delay savings. This paper analyzes the historical usage of different flight routings, varying from simple waypoint pairs to lengthy strings of waypoints incorporating jet routes, in order to improve DWR route acceptability. An approach is developed that can be incorporated into DWR, advising routings with high historical usage and savings potential similar to that of the nominal DWR advisory. It is hypothesized that modifying a nominal DWR routing to one that is commonly used, and nearby, will result in more actual savings since common routings are generally familiar and operationally acceptable to air traffic control. The approach allows routing segments with high historical usage to be concatenated to form routes that meet all DWR constraints. The relevance of a routes historical usage to its acceptance by dispatchers and air traffic control is quantified by analyzing historical DWR data. Results indicate that while historical usage may be less of a concern to flight dispatchers accepting or rejecting DWR advised route corrections, it may be important to air traffic control acceptance of DWR routes.

Operational Acceptability↗

DOE OSTI2024

Exploring Architectural-Aware Affinity Policies in Modern HPC Runtimes

Modern commodity and High-Performance Computing (HPC) systems are evolving with complex CPU architectures. These architectures now feature higher core and NUMA domain counts and implement features such as hyperthreading. When considering significant differences in hardware configurations, library availability, and hardware-tailored system/software stacks, which could substantially vary from one system to another, performance portability is hard to achieve. Throughout the years, this trend resulted in an increasingly high burden on application developers to fine-tune their workloads for each architecture. This work explores how hardware-dependent aspects such as locality/process/thread affinity affect performance in modern CPU architectures. We focus our study on the Global Memory and Threading (GMT) distributed runtime system as a representative of Partitioned Global Address Space (PGAS) software stacks commonly adopted for productivity. In particular, to appreciate performance implications, we evaluate GMT’s thread affinity policies, and, introduce two new ones which exploit architectural awareness. Finally, we explore alternative NUMA configurations via different process bindings and perform a scalability study on three HPC clusters with varying CPU architectures and NUMA layouts. Our analysis indicates that more complex architectures are more affected by affinity and binding policies and highlights the importance of setting proper runtime configurations to achieve superior performance.

Di Dio Lavore, Ian↗

NASA NTRS2013

Investigating the Complexity of Transitioning Separation Assurance Tools into NextGen Air Traffic Control

In a study, that introduced ground-based separation assurance automation through a series of envisioned transitional phases of concept maturity, it was found that subjective responses to scales of workload, situation awareness, and acceptability in a post run questionnaire revealed as-predicted results for three of the four study conditions but not for the third, Moderate condition. The trend continued for losses of separation (LOS) where the number of LOS events were far greater than expected in the Moderate condition. To offer an account of why the Moderate condition was perceived to be more difficult to manage than predicted, researchers examined the increase in amount and complexity of traffic, increase in communication load, and increased complexities as a result of the simulation's mix of aircraft equipage. Further analysis compared the tools presented through the phases, finding that controllers took advantage of the informational properties of the tools presented but shied away from using their decision support capabilities. Taking into account similar findings from other studies, it is suggested that the Moderate condition represented the first step into a "shared control" environment, which requires the controller to use the automation as a decision making partner rather than just a provider of information. Viewed in this light, the combination of tools offered in the Moderate condition was reviewed and some tradeoffs that may offset the identified complexities were suggested.

separation assurance↗

NASA NTRS2017

Evaluation of Early Ground Control Station Configurations for Interacting with a UAS Traffic Management (UTM) System

The purpose of this paper is to report on a human factors evaluation of ground control station design concepts for interacting with an unmanned traffic management system. The data collected for this paper comes from recent field tests for NASA's Unmanned Traffic Management (UTM) project, and covers the following topics; workload, situation awareness, as well as flight crew communication, coordination, and procedures. The goal of this evaluation was to determine if the various software implementations for interacting with the UTM system can be described and classified into design concepts to provide guidance for the development of future UTM interfaces. We begin with a brief description of NASA's UTM project, followed by a description of the test range configuration related to a second development phase. We identified (post hoc) two classes in which the ground control stations could be grouped. This grouping was based on level of display integration. The analysis was exploratory and informal. It was conducted to compare ground stations across those two classes and against the aforementioned topics. Herein, we discuss the results.

unmanned traffic management↗

DOE OSTI2025

Scalable Multi-Facility Workflows for Artificial Intelligence Applications in Climate Research

Earth observation satellites and earth system models are sources of vast, multi-modal datasets that are invaluable for advancing climate and environmental research. However, their scale and complexity pose significant challenges for processing and analysis. In this paper we discuss our experiences in developing and using a scientific research application using an automated multi-facility workflow that orchestrates data collection, preprocessing, artificial intelligence (AI) inferencing, and data movement across diverse computational resources, leveraging the Advanced Computing Ecosystem Testbed at the Oak Ridge Leadership Computing Facility (OLCF). We demonstrate that our workflow can be seamlessly integrated and orchestrated across research facilities managed by different federal agencies, thus allowing users to extract new scientific insights from climate datasets. The experimental results indicate that the multi-facility workflow significantly reduces processing time, enhances scalability, and maintains high efficiency across varying workloads. Notably, our workflow processes 12,000 high-resolution satellite images in just 44 seconds using 80 workers distributed across 10 nodes on the OLCF systems. Such high throughput is essential for dynamic tokenization and sharding of petascale satellite data for distributed AI model training and inferencing at scale across thousands of GPUs.

Kurihana, Takuya [ORNL] (ORCID:0000000156698565)↗

NASA NTRS1985

Analysis of adaptive algorithms for an integrated communication network

Techniques were examined that trade communication bandwidth for decreased transmission delays. When the network is lightly used, these schemes attempt to use additional network resources to decrease communication delays. As the network utilization rises, the schemes degrade gracefully, still providing service but with minimal use of the network. Because the schemes use a combination of circuit and packet switching, they should respond to variations in the types and amounts of network traffic. Also, a combination of circuit and packet switching to support the widely varying traffic demands imposed on an integrated network was investigated. The packet switched component is best suited to bursty traffic where some delays in delivery are acceptable. The circuit switched component is reserved for traffic that must meet real time constraints. Selected packet routing algorithms that might be used in an integrated network were simulated. An integrated traffic places widely varying workload demands on a network. Adaptive algorithms were identified, ones that respond to both the transient and evolutionary changes that arise in integrated networks. A new algorithm was developed, hybrid weighted routing, that adapts to workload changes.

Reed, Daniel A.↗

NASA NTRS1984

Subjective Workload Assessment and Voluntary Control of Effort in a Tracking Task

A manual control tracking task was manipulated along two dimensions: (1) control order and (2) forcing function bandwidth. In the first phase of the experiment subjective workload assessments were collected. It was found that subjective assessments of workload were closely associated with performance in the case of increasing control order, but not in the case of increasing bandwidth. This was interpreted as indicating that subjective workload assessments are most appropriate for the study of increasing difficulty centered in response selection processes as opposed to response execution processes. In the second phase of the experiment the subjects were asked to voluntarily limit the effort they applied in the performance of the tracking task. The results indicate that the subjects were quite facile in doing this. However, comparison of these data to the findings of other studies that manipulated effort via dual-task biasing indicate that effort manipulation is much more potent in a single-task configuration. This finding is discussed in terms of multiple resource theories of attentional capacity. The utility of an analysis of covariance procedure in studying the relationships between subjective ratings and performance is highlighted.

Vidulich, M. A.↗

NASA NTRS2007

Did Vertigo Kill America's Forgotten Astronaut?

On November 15, 1967, U.S. Air Force test pilot Major Michael J. Adams was killed while flying the X-15 rocket-propelled research vehicle in a parabolic spaceflight profile. This flight was part of a joint effort with NASA. An electrical short in one of the experiments aboard the vehicle caused electrical transients, resulting in excessive workload by the pilot. At altitude Major Adams inappropriately initiated a flat spin that led to a series of unusual aircraft attitudes upon atmospheric re-entry, ultimately causing structural failure of the airframe. Major Adams was known to experience vertigo (i.e. spatial disorientation) while flying the X-15, but all X-15 pilots most likely experienced vertigo (i.e. somatogravic, or "Pitch-Up", illusion) as a normal physiologic response to the accelerative forces involved. Major Adams probably experienced vertigo to a greater degree than did others, since prior aeromedical testing for astronaut selection at Brooks AFB revealed that he had an unusually high degree of labyrinthine sensitivity. Subsequent analysis reveals that after engine burnout, and through the zenith of the flight profile, he likely experienced the oculoagravic ("Elevator") illusion. Nonetheless, painstaking investigation after the mishap revealed that spatial disorientation (Type II, Recognized) was NOT the cause, but rather, a contributing factor. The cause was in fact the misinterpretation of a dual-use flight instrument (i.e. Loss of Mode Awareness), resulting in confusion between yaw and roll indications, with subsequent flight control input that was inappropriate. Because of the altitude achieved on this flight, Major Adams was awarded Astronaut wings posthumously. Understanding the potential for spatial disorientation, particularly the oculoagravic illusion, associated with parabolic spaceflight profiles, and understanding the importance of maintaining mode awareness in the context of automated cockpit design, are two lessons that have direct application to the commercial space industry today.

Bendrick, Gregg A.↗

NASA NTRS1991

Systematic methods for knowledge acquisition and expert system development

Nine cooperating rule-based systems, collectively called AUTOCREW, were designed to automate functions and decisions associated with a combat aircraft's subsystem. The organization of tasks within each system is described; performance metrics were developed to evaluate the workload of each rule base, and to assess the cooperation between the rule-bases. Each AUTOCREW subsystem is composed of several expert systems that perform specific tasks. AUTOCREW's NAVIGATOR was analyzed in detail to understand the difficulties involved in designing the system and to identify tools and methodologies that ease development. The NAVIGATOR determines optimal navigation strategies from a set of available sensors. A Navigation Sensor Management (NSM) expert system was systematically designed from Kalman filter covariance data; four ground-based, a satellite-based, and two on-board INS-aiding sensors were modeled and simulated to aid an INS. The NSM Expert was developed using the Analysis of Variance (ANOVA) and the ID3 algorithm. Navigation strategy selection is based on an RSS position error decision metric, which is computed from the covariance data. Results show that the NSM Expert predicts position error correctly between 45 and 100 percent of the time for a specified navaid configuration and aircraft trajectory. The NSM Expert adapts to new situations, and provides reasonable estimates of hybrid performance. The systematic nature of the ANOVA/ID3 method makes it broadly applicable to expert system design when experimental or simulation data is available.

Belkin, Brenda L.↗

NASA NTRS2006

Comanche Helmet-Mounted Display Symbology Simulation

The Aeroflightdynamics Directorate (AMRDEC) conducted a simulation to examine the performance of the Comanche Contact Analog world-referenced symbology displayed on the Comanche HIDSS when compared with a compressed symbology design similar to that specified by the former MIL-STD 1295. Six experimental test pilots flew one modified ADS-33 maneuver (hover turn, bob-up), an unusual attitude recovery, and two terrain flight tactical tasks in the NASA Vertical Motion Simulator (VMS). Analysis of the pilot objective performance data and subjective data showed the following results. Objective test results showed that 1295 symbology yielded more rapid maneuvering in the hover turn bob-up than Contact Analog symbology. The average margin of difference in the time to complete the maneuver was approximately two seconds, which was statistically significant. There were no significant differences measured between symbology sets with respect to altitude or position performance measures for all other maneuvers. The NOE target ID task data showed improved accuracy in determining heading to target when using Contact Analog over MIL-STD-1295. Subjective test results, including handling qualities ratings (HQRs) and NASA-TLX workload ratings, showed small but consistent advantages of 1295 symbology over Contact Analog for most parameters. For the bob-up maneuver, 1295 symbology handling qualities were rated Desired for lateral position error and time to complete whereas Contact Analog was rated adequate. The average HQRs for all other maneuvers were rated the same for both symbology sets. Pilot comments and the results of an online questionnaire more strongly favored 1295 over Contact Analog. Repeated comments from all six pilots led to a focus on design issues with six Contact Analog symbols. Those symbols were the heading tape, horizon line, radar altitude six-second predictor, the position of the torque symbol, the absence of a hover position cue, and the widespread positioning of the symbology to the outer edges of the display field-of-view. Pilots rated the present design of three of the six symbols as having safety-of-flight implications. Those symbols were the heading tape, horizon line, and six-second predictor. To summarize, test results showed no objective data that would warrant restricting experimental test pilots from flying constrained tasks. Small but consistent advantages were recorded for the MILSTD-1295 symbology design when executing ADS-33 constrained tasks. No general performance differences were recorded for the operational maneuvers (NOE, contour flight modes) except for the azimuth-to-target task, which favored the Contact Analog heading tape design. There were consistent and strong pilot comments supporting the MIL-STD-1295 design over Contact Analog in both this current simulation and in Comanche Sim I. Three Contact Analog symbols warrant modification and further evaluation to mitigate safety-of-flight implications noted by participating test pilots. A plan for symbology redesign and testing was developed. However, the Comanche program was cancelled by Department of Army in February 2004.

Turpin, Terry S.↗