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NASA NTRS2018

The InSAR Scientific Computing Environment 3.0: A Flexible Framework for NISAR Operational and User-Led Science Processing

The InSAR Scientific Computing Environment (ISCE) was first developed under the NASA Advanced Information Systems Technology as a flexible, extensible object-oriented framework for Interferometric Synthetic Aperture Radar (InSAR) processing. The ISCE framework uses Python 3 at the workflow level, controlling modules of compiled code for functional processing, and managing inputs, outputs, and other flow control services. The currently released version, called ISCE 2.1, is distributed to the research community through the Western North America InSAR Consortium under a research license. The ISCE team is working on the next generation of the code in order to prepare for the NASAISRO SAR (NISAR) mission operational processing. Innovations in this code include augmentation or conversion of the custom Python framework elements in ISCE with the Pyre framework, new workflows for interferometric and polarimetric stack processing, a more intuitive and graphically based user interface, and flow control for hybrid computing environments including CPU/GPU clusters, logging and error tracking facilities, and new more efficient computational modules that exploit graphical processor units (GPUs) when available. The ISCE 3.0 framework is designed to work in an operational environment as well as on a single user’s laptop or compute cluster, with services to discover capabilities and scale computations accordingly.

Buckley, Sean M.↗
NASA NTRSDate not supplied

Benefits of using Electronic Data Sheets (EDS) with coreFlight Systems (cFS) - A Project Example

Recently there has been interest in the incorporation of core Flight Systems (cFS) with Spacecraft Onboard Interface Services (SOIS) Electronic Data Sheets (EDS) in the spaceflight software community. The Regenerative Fuel Cell project at the Glenn Research Center is using cFS architecture with EDS support for its monitoring and control software. The presentation will outline the benefits to using cFS with EDS support: First, EDS establishes a single source of truth for the definitions of data structures used throughout an entire mission that may otherwise be programmed in different languages and designed with different processor architectures. Not only does this help with inter-application communication via the software bus, but it also greatly simplifies communication between systems. An EDS Application Programming Interface (API) library allows the conversion of EDS data structures to and from native data structures. Second, bindings for other programming languages (e.g. Lua, Python, JSON) have been written to allow the creation and manipulation of EDS data objects within those languages. The RFC project uses Lua scripts to automatically generate binary configuration files at build time to be loaded into our cFS programs. We also use Python bindings in a graphical user interface (GUI) to allow an operator to send commands and view telemetry messages sent from cFS instances. Finally, using Lua scripts we can set up specific simulation scenarios to perform automatic functional testing. During the development of the RFC software, the software team put together a generic python GUI called “cFS-EDS-GroundStation” that provides a basic interface to an instance of cFS with EDS support. The GUI includes a basic telecommand and telemetry system that reads directly from the generated EDS databases. In the telecommand system, dropdown menus are populated with all user commands that are defined in EDS. In the telemetry system, telemetry messages are automatically decoded, written to the screen, and saved to a binary file. Additional Python scripts have been written to convert the binary data files into a comma separated value (CSV) format for further processing. We will demonstrate the basic use of the cFS-EDS-GroundStation software including adding additional commands and telemetry payload values in EDS and see them appear automatically in the cFS-EDS-Groundstation software. About the RFC project: The Regenerative Fuel Cell project is tasked with developing and demonstrating a power system consisting of a fuel cell and electrolyzer to provide power during a lunar day/night cycle. During the night, the fuel cell takes Hydrogen and Oxygen gasses and converts them into electricity, water, and heat. During the day, the electrolyzer takes input power (e.g. from a photovoltaic array) and converts water back into Hydrogen and Oxygen gasses.

Mathew Mccaskey↗
NASA NTRS1994

Mission Operations Centers (MOCs): Integrating key spacecraft ground data system components

In an environment characterized by decreasing budgets, limited system development time, and user needs for increased capabilities, the Mission Operations Division (MOD) at the National Aeronautics and Space Administration Goddard Space Flight Center initiated a new, cost-effective concept in developing its spacecraft ground data systems: the Mission Operations Center (MOC). In the MOC approach, key components are integrated into a comprehensive and cohesive spacecraft planning, monitoring, command, and control system with a single, state-of-the-art graphical user interface. The MOD is currently implementing MOC's, which feature a common, reusable, and extendable system architecture, to support the X-Ray Timing Explorer (XTE), Tropical Rainfall Measuring Mission (TRMM), and Advanced Composition Explorer (ACE) missions. As a result of the MOC approach, mission operations are integrated, and users can, with a single system, perform real-time health and safety monitoring, real-time command and control, real-time attitude processing, real-time and predictive graphical spacecraft monitoring, trend analysis, mission planning and scheduling, command generation and management, network scheduling, guide star selection, and (using an expert system) spacecraft monitoring and fault isolation. The MOD is also implementing its test and training simulators under the new MOC management structure. This paper describes the MOC concept, the management approaches used in developing MOC systems, the technologies employed and the development process improvement initiatives applied in implementing MOC systems, and the expected benefits to both the user and the mission project in using the MOC approach.

Harbaugh, Randy↗
NASA NTRS1998

Six axis force feedback input device

The present invention is a low friction, low inertia, six-axis force feedback input device comprising an arm with double-jointed, tendon-driven revolute joints, a decoupled tendon-driven wrist, and a base with encoders and motors. The input device functions as a master robot manipulator of a microsurgical teleoperated robot system including a slave robot manipulator coupled to an amplifier chassis, which is coupled to a control chassis, which is coupled to a workstation with a graphical user interface. The amplifier chassis is coupled to the motors of the master robot manipulator and the control chassis is coupled to the encoders of the master robot manipulator. A force feedback can be applied to the input device and can be generated from the slave robot to enable a user to operate the slave robot via the input device without physically viewing the slave robot. Also, the force feedback can be generated from the workstation to represent fictitious forces to constrain the input device's control of the slave robot to be within imaginary predetermined boundaries.

Ohm, Timothy↗
NASA NTRS2012

The Mobile Chamber

A document discusses a simulation chamber that represents a shift from the thermal-vacuum chamber stereotype. This innovation, currently in development, combines the capabilities of space simulation chambers, the user-friendliness of modern-day electronics, and the modularity of plug-and-play computing. The Mobile Chamber is a customized test chamber that can be deployed with great ease, and is capable of bringing payloads at temperatures down to 20 K, in high vacuum, and with the desired metrology instruments integrated to the systems control. Flexure plans to lease Mobile Chambers, making them affordable for smaller budgets and available to a larger customer base. A key feature of this design will be an Apple iPad-like user interface that allows someone with minimal training to control the environment inside the chamber, and to simulate the required extreme environments. The feedback of thermal, pressure, and other measurements is delivered in a 3D CAD model of the chamber's payload and support hardware. This GUI will provide the user with a better understanding of the payload than any existing thermal-vacuum system.

Scharfstein, Gregory↗
NASA NTRS2015

Tactile Data Entry System

The patent-pending Glove-Enabled Computer Operations (GECO) design leverages extravehicular activity (EVA) glove design features as platforms for instrumentation and tactile feedback, enabling the gloves to function as human-computer interface devices. Flexible sensors in each finger enable control inputs that can be mapped to any number of functions (e.g., a mouse click, a keyboard strike, or a button press). Tracking of hand motion is interpreted alternatively as movement of a mouse (change in cursor position on a graphical user interface) or a change in hand position on a virtual keyboard. Programmable vibro-tactile actuators aligned with each finger enrich the interface by creating the haptic sensations associated with control inputs, such as recoil of a button press.

Adams, Richard J.↗
NASA NTRS2018

Miniature Exercise Device-2 (MED-2): Preliminary ISS Evaluation Results for a Compact Motorized Resistive and Aerobic Rowing Exercise Device

Future human missions beyond Low Earth Orbit (LEO) will require onboard equipment to provide exercise capabilities for the crew to counter the adverse physiological effects of long-duration microgravity. To accomplish this within the physical constraints of a space vehicle or transit module, a single miniature device that provides both resistive and aerobic exercise modalities is required. To meet this need, Johnson Space Center’s (JSC) Software, Robotics, and Simulation Division (ER) developed the Miniature Exercise Device-2 (MED-2). MED-2 integrates a torque-controlled servomotor and a series-elastic actuator to provide highly-controllable load profiles and a large magnitude output performance in a very small package. This innovative technology is derived from years of JSC/ER design, development and operational experience with cutting-edge robotics, motor controllers, software and actuator/sensor miniaturization, including Robonaut 2 and MED-1. MED-2 was presented at the 2016 ISS R&D Conference. This is an update now that the last of six crewmembers will have completed planned MED-2 sessions on the International Space Station (ISS) in May 2018.Current state-of-the-art ISS exercise equipment consists of two treadmills, a resistive exercise device and two cycle ergometers with a total mass of several thousand pounds and a total volume of several cubic yards. This equipment has proven vital to mitigate the musculoskeletal and cardiovascular degradation effects of microgravity. However, due to the large operational volume and mass of these ISS devices, tailoring them for smaller vehicles, such as Orion, is not possible. In addition, each of the current ISS devices targets a single specific modality. Compared to the existing spaceflight (and even terrestrial) exercise equipment, MED-2 is a new archetype altogether. The combined features of compact size, multi-modality and high-performance is attributable to its innovative series elastic actuator and motor controller. Following its arrival on ISS in 2016, MED-2 was evaluated in two parts. The first and shorter evaluation was an engineering functional checkout of the hardware. As this was a novel exercise device previously never used on ISS, the initial checkout assessed the operation of the hardware and ensured the motion and dynamic range of the crew did not present any collision or other hazards. The second portion of the study collected the heart rates, kinematics and utilized operational volumes of six astronauts to determine the quality of both the resistive and aerobic exercise modalities as delivered by MED-2. Investigators from JSC Biomedical Research and Environmental Science Division (SK) and Glenn Research Center are currently evaluating the data and preparing preliminary results. For the resistive exercise modality, MED-2 demonstrated a range of constant resistive loads from 10-150 lbf. With a displacement range of 84 inches, the MED-2 accommodates users from 5th percentile Japanese female through 95th percentile American male for all of its certified exercises. The displacement measurement accuracy has also been verified within 2.5 percent full range. The crew was able to successfully perform all prescribed resistive exercises, except Goblet Squats which were not feasible with a constant load profile. For the aerobic exercise modality, MED-2 simulated a rowing motion with prescribed and user-selected resistance levels. It has demonstrated rates up to 60 strokes per minute on the ground. MED-2 loads and displacements performance are the same as those cited for the resistive modality. Although each of the crew was able to perform the prescribed aerobic rowing sets, there was considerable variability in the rowing motion among different crewmembers. Also, as expected, the crew was unable to get the full benefits of a typical terrestrial rowing stroke because the current configuration does not allow the user to reach past their feet. These observations have already informed the requirements for other microgravity rowing devices currently in development. One of the unique features of the MED-2 device is the intuitive touch-screen control system. This One Portal graphical user interface (GUI) was developed based on JSC/ER’s heritage knowledge and experience of developing and sustaining the current ISS exercise equipment. Through this interface, the crew easily performed prepared prescriptions as well as had the ability to adjust exercise modality, load and other exercise details such as number of repetitions and number of sets. This touch-screen and GUI fulfilled the MED-2 project goal to simplify the interaction between the user and the device. Furthermore, the extent to which MED-2 utilizes a touchscreen and GUI to control exercise equipment is unmatched among the existing ISS exercise devices. As a motorized device, MED-2 technology can provide a customizable force profile that can be varied as a function of strap displacement, strap velocity or a combination of these and other variables. During 2017, JSC/ER developed and flight-certified a resistive exercise algorithm that mimics the 1-G inertial effects of free-weights and enables adjustable eccentric-to-concentric loading ratios. Subsequent development will explore varying the load profiles and incorporating additional exercises beyond the current list of certified movements.

Exercise↗
NASA NTRSDate not supplied

Aero-Engines AI - A Machine-Learning App for Aircraft Engine Concepts Assessment

Effective deployment of trained machine-learning models could drive a high level of efficiency in aircraft engine conceptual design. Aero-Engines AI is a Windows app that has been created to deploy trained machine-learning models to assess aircraft engine concepts. It was created using tkinter, a GUI (graphical user interface) module that is built into the standard Python library. Employing tkinter greatly facilitates the sharing of machine-learning application as an executable file which can be run on Windows machines (without the need to have Python or any library installed). Current version of the app focuses on the performance prediction of conventional turbofans. The app gets user input for a turbofan design, preprocesses the input data, and deploys trained machine-learning models to predict turbofan thrust specific fuel consumption (TSFC), engine weight, core size, and turbomachinery stage-counts. The machine-learning predictive models were built by employing supervised deep-learning algorithm to study patterns in an existing open-source database of production and research turbofan engines. They were trained, cross-validated, and tested in Keras, an open-source neural networks API (application programming interface) written in Python, with TensorFlow (Google open-source artificial intelligence library) serving as the backend engine. The smooth deployment of these machine-learning models using the app shows that Aero-Engines AI is an easy-to-use and a time-saving tool for aircraft engine design-space exploration during the conceptual design stage.

machine learning↗
DOE OSTI2020

Investigating Scientific Data Change with User Research Methods

Scientific datasets are continually expanding and changing due to fluctuations with instruments, quality assessment and quality control processes, and modifications to software pipelines. Datasets include minimal information about these changes or their effects requiring scientists manually assess modifications through a number of labor intensive and ad-hoc steps. The Deduce project is investigating data change to develop metrics, methods, and tools that will help scientists systematically identify and make decisions around data changes. Currently, there is a lack of understanding, and common practices, for identifying and evaluating changes in datasets since systematically measuring and managing data change is under explored in scientific work. We are conducting user research to address this need by exploring scientist's conceptualizations, behaviors, needs, and motivations when dealing with changing datasets. Our user research utilizes multiple methods to produce foundational, generative insights and evaluate research products produced by our team. In this paper, we detail our user research process and outline our findings about data change that emerge from our studies. Our work illustrates how scientific software teams can push beyond just usability testing user interfaces or tools to better probe the underlying ideas they are developing solutions to address.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
NASA NTRS2007

Imaging Sensor Flight and Test Equipment Software

The Lightning Imaging Sensor (LIS) is one of the components onboard the Tropical Rainfall Measuring Mission (TRMM) satellite, and was designed to detect and locate lightning over the tropics. The LIS flight code was developed to run on a single onboard digital signal processor, and has operated the LIS instrument since 1997 when the TRMM satellite was launched. The software provides controller functions to the LIS Real-Time Event Processor (RTEP) and onboard heaters, collects the lightning event data from the RTEP, compresses and formats the data for downlink to the satellite, collects housekeeping data and formats the data for downlink to the satellite, provides command processing and interface to the spacecraft communications and data bus, and provides watchdog functions for error detection. The Special Test Equipment (STE) software was designed to operate specific test equipment used to support the LIS hardware through development, calibration, qualification, and integration with the TRMM spacecraft. The STE software provides the capability to control instrument activation, commanding (including both data formatting and user interfacing), data collection, decompression, and display and image simulation. The LIS STE code was developed for the DOS operating system in the C programming language. Because of the many unique data formats implemented by the flight instrument, the STE software was required to comprehend the same formats, and translate them for the test operator. The hardware interfaces to the LIS instrument using both commercial and custom computer boards, requiring that the STE code integrate this variety into a working system. In addition, the requirement to provide RTEP test capability dictated the need to provide simulations of background image data with short-duration lightning transients superimposed. This led to the development of unique code used to control the location, intensity, and variation above background for simulated lightning strikes at user-selected locations.

Freestone, Kathleen↗
NASA NTRS2011

Multi-Mission Power Analysis Tool

Multi-Mission Power Analysis Tool (MMPAT) Version 2 simulates spacecraft power generation, use, and storage in order to support spacecraft design, mission planning, and spacecraft operations. It can simulate all major aspects of a spacecraft power subsystem. It is parametrically driven to reduce or eliminate the need for a programmer. A user-friendly GUI (graphical user interface) makes it easy to use. Multiple deployments allow use on the desktop, in batch mode, or as a callable library. It includes detailed models of solar arrays, radioisotope thermoelectric generators, nickel-hydrogen and lithium-ion batteries, and various load types. There is built-in flexibility through user-designed state models and table-driven parameters.

Broderick, Daniel↗
NASA NTRS2003

A Voice and Mouse Input Interface for 3D Virtual Environments

There have been many successful stories on how 3D input devices can be fully integrated into an immersive virtual environment. Electromagnetic trackers, optical trackers, gloves, and flying mice are just some of these input devices. Though we can use existing 3D input devices that are commonly used for VR applications, there are several factors that prevent us from choosing these input devices for our applications. One main factor is that most of these tracking devices are not suitable for prolonged use due to human fatigue associated with using them. A second factor is that many of them would occupy additional office space. Another factor is that many of the 3D input devices are expensive due to the unusual hardware that are required. For our VR applications, we want a user interface that would work naturally with standard equipment. In this paper, we demonstrate applications or our proposed muitimodal interface using a 3D dome display. We also show that effective data analysis can be achieved while the scientists view their data rendered inside the dome display and perform user interactions simply using the mouse and voice input. Though the sphere coordinate grid seems to be ideal for interaction using a 3D dome display, we can also use other non-spherical grids as well.

Kao, David L.↗
NASA NTRS1988

Issues on the use of meta-knowledge in expert systems

Meta knowledge is knowledge about knowledge; knowledge that is not domain specific but is concerned instead with its own internal structure. Several past systems have used meta-knowledge to improve the nature of the user interface, to maintain the knowledge base, and to control the inference engine. More extensive use of meta-knowledge is probable for the future as larger scale problems are considered. A proposed system architecture is presented and discussed in terms of meta-knowledge applications. The principle components of this system: the user support subsystem, the control structure, the knowledge base, the inference engine, and a learning facility are all outlined and discussed in light of the use of meta-knowledge. Problems with meta-constructs are also mentioned but it is concluded that the use of meta-knowledge is crucial for increasingly autonomous operations.

Facemire, Jon↗
NASA NTRS2005

System Developed for Real-Time Blade-Flutter Monitoring in the Wind Tunnel

A real-time system has been developed to monitor flutter vibrations in turbomachinery. The system is designed for continuous processing of blade tip timing data at a rate of 10 MB/sec. A USB 2.0 interface provides uninterrupted real-time processing of the data, and the blade-tip arrival times are measured with a 50-MHz oscillator and a 24-bit pipelined architecture counter. The input stage includes a glitch catcher, which reduces the probability of detecting a ghost blade to negligible levels. A graphical user interface provides online interrogation of any blade tip from any light probe sensor. Alternatively, data from all blades and all sensors can be superimposed into a single composite scatter plot displaying the vibration amplitude of each blade.

Kurkov, Anatole P.↗
NASA NTRS2006

Analytical Assessment of the Reciprocating Feed System

A preliminary analysis tool has been created in Microsoft Excel to determine deliverable payload mass, total system mass, and performance of spacecraft systems using various types of propellant feed systems. These mass estimates are conducted by inserting into the user interface the basic mission parameters (e.g., thrust, burn time, specific impulse, mixture ratio, etc.), system architecture (e.g., propulsion system type and characteristics, propellants, pressurization system type, etc.), and design properties (e.g., material properties, safety factors, etc.). Different propellant feed and pressurization systems are available for comparison in the program. This gives the user the ability to compare conventional pressure fed, reciprocating feed system (RFS), autogenous pressurization thrust augmentation (APTA RFS), and turbopump systems with the deliverable payload, inert mass, and total system mass being the primary comparison metrics. Analyses of several types of missions and spacecraft were conducted and it was found that the RFS offers a performance improvement, especially in terms of delivered payload, over conventional pressure fed systems. Furthermore, it is competitive with a turbopump system at low to moderate chamber pressures, up to approximately 1,500 psi. Various example cases estimating the system mass and deliverable payload of several types of spacecraft are presented that illustrate the potential system performance advantages of the RFS. In addition, a reliability assessment of the RFS was conducted, comparing it to simplified conventional pressure fed and turbopump systems, based on MIL-STD 756B; these results showed that the RFS offers higher reliability, and thus substantially longer periods between system refurbishment, than turbopump systems, and is competitive with conventional pressure fed systems. This is primarily the result of the intrinsic RFS fail-operational capability with three run tanks, since the system can operate with just two run tanks.

Eddleman, David E.↗
NASA NTRS2008

Proven and Robust Ground Support Systems - GSFC Success and Lessons Learned

Over the past fifteen years, Goddard Space Flight Center has developed several successful science missions in-house: the Wilkinson Microwave Anisotropy Probe (WMAP), the Imager for Magnetopause-to-Aurora Global Exploration (IMAGE), the Earth Observing 1 (EO-1) [1], and the Space Technology 5 (ST-5)[2] missions, several Small Explorers, and several balloon missions. Currently in development are the Solar Dynamics Observatory (SDO) [3] and the Lunar Reconnaissance Orbiter (LRO)[4]. What is not well known is that these missions have been supported during spacecraft and/or instrument integration and test, flight software development, and mission operations by two in house satellite Telemetry and Command (T & C) Systems, the Integrated Test and Operations System (ITOS) and the Advanced Spacecraft Integration and System Test (ASIST). The advantages of an in-house satellite Telemetry and Command system are primarily in the flexibility of management and maintenance - the developers are considered a part of the mission team, get involved early in the development process of the spacecraft and mission operations-control center, and provide on-site, on-call support that goes beyond Help Desk and simple software fixes. On the other hand, care must be taken to ensure that the system remains generic enough for cost effective re-use from one mission to the next. The software is designed such that many features are user-configurable. Where user-configurable options were impractical, features were designed so as to be easy for the development team to modify. Adding support for a new ground message header, for example, is a one-day effort because of the software framework on which that code rests. This paper will discuss the many features of the Goddard satellite Telemetry and Command systems that have contributed to the success of the missions listed above. These features include flexible user interfaces, distributed parallel commanding and telemetry decommutation, a procedure language, the interfaces and tools needed for a high degree of automation, and instantly accessible archives of spacecraft telemetry. It will discuss some of the problems overcome during development, including secure commanding over networks or the Internet, constellation support for the three satellites that comprise the ST-5 mission, and geographically distributed telemetry end users.

Pfarr, Barbara↗
NASA NTRS2018

NASA Pilot-Engaged Expert Response Using IBM Watson Technology: Prototype Evaluation of Knowledge Retrieval System

NASA Langley Research Center and IBM have been investigating the use of IBM Watson technology in aerospace research and development. One application of Watson technology is the Pilot-Engaged Expert Response (PEER) use case. The PEER system is envisioned as an in-cockpit advisor that will act as a source of situationally-relevant information for pilots and other flight crew members to assist in decision making about real-time events and situations that arise in the course of aircraft operations. PEER will make available vast stores of knowledge and information quickly and directly, putting important informational resources where they are needed most. IBM has worked with NASA to develop an architecture and articulate a roadmap for the development of the PEER system. That vision is built around Watson Discovery Advisor (WDA) software solution, derived from IBM's Jeopardy!-winning automatic question answering system. PEER makes use of WDA's sophisticated question-answering capabilities as its core, adding important User Interface components and other customizations for the cockpit environment, including communication with flight systems and other external data sources. The development plan for PEER includes four development stages, with the current project constituting the first phase. In this project, a prototype instance of PEER was successfully adapted to the aviation domain, enabling users to ask questions about aviation topics and receive useful and accurate answers to these questions. Major tasks accomplished include the development of procedures for domain adaptation through automatic lexicon extraction from domain glossaries; generation of question-answer training data which was used to train the system; and assessment of the effectiveness of domain adaptation, which showed a dramatic improvement in the ability of the PEER system to answer domain-relevant questions. In addition, the vision for the PEER system was pushed forward by the articulation of a plan for the automatic enhancement of question-answering with contextual information. This initial phase focused on two main goals: 1) the targeted domain adaptation of the underlying WDA system to the aviation domain; and, 2) the design of the software systems needed to leverage flight-contextual data. Domain adaptation of the WDA system proceeds via three main activities: Domain data ingestion, lexical customization and model training. A textual corpus consisting of 1,147 individual documents with more than 7.5 million words of text was ingested into the system and this served as the basis of all further development. A domain lexicon of over 3,500 aviation-domain terms was semi-automatically generated from domain documents and used to train the system. In addition, a set of over 500 question-answer (QA) pairs relevant to the PEER use case was developed; these were used to train and assess the system. These important first steps established the basis for the PEER system. In addition, steps were taken towards the integration of the PEER system into the cockpit environment with the development of a functional design for the Contextual Data Augmentation (CDA) subsystem. This subsystem brings to bear contextual data to improve system responses. It has three main submodules: the Contextual Data Collection module, the Contextual Data Selection module, and the Contextual QA Augmentation module. These modules form a processing pipeline that addresses the problems associated with automatically integrating information from external resources into the knowledge-retrieval mechanism.

Machine learning↗
NASA NTRS1990

Diverter Decision Aiding for In-Flight Diversions

It was determined that artificial intelligence technology can provide pilots with the help they need in making the complex decisions concerning en route changes in a flight plan. A diverter system should have the capability to take all of the available information and produce a recommendation to the pilot. Phase three illustrated that using Joshua to develop rules for an expert system and a Statice database provided additional flexibility by permitting the development of dynamic weighting of diversion relevant parameters. This increases the fidelity of the AI functions cited as useful in aiding the pilot to perform situational assessment, navigation rerouting, flight planning/replanning, and maneuver execution. Additionally, a prototype pilot-vehicle interface (PVI) was designed providing for the integration of both text and graphical based information. Advanced technologies were applied to PVI design, resulting in a hierarchical menu based architecture to increase the efficiency of information transfer while reducing expected workload. Additional efficiency was gained by integrating spatial and text displays into an integrated user interface.

Rudolph, Frederick M.↗