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NASA NTRS2006

Overview of NASA Langley's Systems Analysis Capabilities

The Systems Analysis and Concepts Directorate (SACD) has been in the systems analysis business line supporting National Aeronautics and Space Administration (NASA) aeronautics, exploration, space operations and science since the 1960 s. Our current organization structure is shown in Figure 1. SACD mission can be summed up in the following statements: 1. We conduct advanced concepts for Agency decision makers and programs. 2. We provide aerospace systems analysis products such as mission architectures, advanced system concepts, system and technology trades, life cycle cost and risk analysis, system integration and pre-decisional sensitive information. 3. Our work enables informed technical, programmatic and budgetary decisions. SACD has a complement of 114 government employees and approximately 50 on-site contractors which is equally split between supporting aeronautics and exploration. SACD strives for technical excellence and creditability of the systems analysis products delivered to its customers. The Directorate office is continuously building market intelligence and working with other NASA centers and external partners to expand our business base. The Branches strive for technical excellence and credibility of our systems analysis products by seeking out existing and new partnerships that are critical for successful systems analysis. The Directorates long term goal is to grow the amount of science systems analysis business base.

Cavanaugh, Stephen↗

NASA NTRS1997

Computational Models of Human Performance: Validation of Memory and Procedural Representation in Advanced Air/Ground Simulation

The Man-Machine Interaction Design and Analysis System (MIDAS) under joint U.S. Army and NASA cooperative is intended to assist designers of complex human/automation systems in successfully incorporating human performance capabilities and limitations into decision and action support systems. MIDAS is a computational representation of multiple human operators, selected perceptual, cognitive, and physical functions of those operators, and the physical/functional representation of the equipment with which they operate. MIDAS has been used as an integrated predictive framework for the investigation of human/machine systems, particularly in situations with high demands on the operators. We have extended the human performance models to include representation of both human operators and intelligent aiding systems in flight management, and air traffic service. The focus of this development is to predict human performance in response to aiding system developed to identify aircraft conflict and to assist in the shared authority for resolution. The demands of this application requires representation of many intelligent agents sharing world-models, coordinating action/intention, and cooperative scheduling of goals and action in an somewhat unpredictable world of operations. In recent applications to airborne systems development, MIDAS has demonstrated an ability to predict flight crew decision-making and procedural behavior when interacting with automated flight management systems and Air Traffic Control. In this paper, we describe two enhancements to MIDAS. The first involves the addition of working memory in the form of an articulatory buffer for verbal communication protocols and a visuo-spatial buffer for communications via digital datalink. The second enhancement is a representation of multiple operators working as a team. This enhanced model was used to predict the performance of human flight crews and their level of compliance with commercial aviation communication procedures. We show how the data produced by MIDAS compares with flight crew performance data from full mission simulations. Finally, we discuss the use of these features to study communication issues connected with aircraft-based separation assurance.

Corker, Kevin M.↗

NASA NTRS1994

Dual-Use Space Technology Transfer Conference and Exhibition

This is the second volume of papers presented at the Dual-Use Space Technology Transfer Conference and Exhibition held at the Johnson Space Center February 1-3, 1994. Possible technology transfers covered during the conference were in the areas of information access; innovative microwave and optical applications; materials and structures; marketing and barriers; intelligent systems; human factors and habitation; communications and data systems; business process and technology transfer; software engineering; biotechnology and advanced bioinstrumentation; communications signal processing and analysis; medical care; applications derived from control center data systems; human performance evaluation; technology transfer methods; mathematics, modeling, and simulation; propulsion; software analysis and decision tools; systems/processes in human support technology; networks, control centers, and distributed systems; power; rapid development; perception and vision technologies; integrated vehicle health management; automation technologies; advanced avionics; and robotics technologies.

Krishen, Kumar↗

NASA NTRS1992

Advanced construction management for lunar base construction - Surface operations planner

The study proposes a conceptual solution and lays the framework for developing a new, sophisticated and intelligent tool for a lunar base construction crew to use. This concept integrates expert systems for critical decision making, virtual reality for training, logistics and laydown optimization, automated productivity measurements, and an advanced scheduling tool to form a unique new planning tool. The concept features extensive use of computers and expert systems software to support the actual work, while allowing the crew to control the project from the lunar surface. Consideration is given to a logistics data base, laydown area management, flexible critical progress scheduler, video simulation of assembly tasks, and assembly information and tracking documentation.

Kehoe, Robert P.↗

NASA NTRS2003

Effective Team Support: From Modeling to Software Agents

The purpose of this research contract was to perform multidisciplinary research between CMU psychologists, computer scientists and engineers and NASA researchers to design a next generation collaborative system to support a team of human experts and intelligent agents. To achieve robust performance enhancement of such a system, we had proposed to perform task and cognitive modeling to thoroughly understand the impact technology makes on the organization and on key individual personnel. Guided by cognitively-inspired requirements, we would then develop software agents that support the human team in decision making, information filtering, information distribution and integration to enhance team situational awareness. During the period covered by this final report, we made substantial progress in modeling infrastructure and task infrastructure. Work is continuing under a different contract to complete empirical data collection, cognitive modeling, and the building of software agents to support the teams task.

Remington, Roger W.↗

NASA NTRS2005

Effective Team Support: From Task and Cognitive Modeling to Software Agents for Time-Critical Complex Work Environments

The purpose of this research contract was to perform multidisciplinary research between CMU psychologists, computer scientists and NASA researchers to design a next generation collaborative system to support a team of human experts and intelligent agents. To achieve robust performance enhancement of such a system, we had proposed to perform task and cognitive modeling to thoroughly understand the impact technology makes on the organization and on key individual personnel. Guided by cognitively-inspired requirements, we would then develop software agents that support the human team in decision making, information filtering, information distribution and integration to enhance team situational awareness. During the period covered by this final report, we made substantial progress in completing a system for empirical data collection, cognitive modeling, and the building of software agents to support a team's tasks, and in running experiments for the collection of baseline data.

Remington, Roger W.↗

NASA NTRS2016

Exploration Clinical Decision Support System: Medical Data Architecture

The Exploration Clinical Decision Support (ECDS) System project is intended to enhance the Exploration Medical Capability (ExMC) Element for extended duration, deep-space mission planning in HRP. A major development guideline is the Risk of "Adverse Health Outcomes & Decrements in Performance due to Limitations of In-flight Medical Conditions". ECDS attempts to mitigate that Risk by providing crew-specific health information, actionable insight, crew guidance and advice based on computational algorithmic analysis. The availability of inflight health diagnostic computational methods has been identified as an essential capability for human exploration missions. Inflight electronic health data sources are often heterogeneous, and thus may be isolated or not examined as an aggregate whole. The ECDS System objective provides both a data architecture that collects and manages disparate health data, and an active knowledge system that analyzes health evidence to deliver case-specific advice. A single, cohesive space-ready decision support capability that considers all exploration clinical measurements is not commercially available at present. Hence, this Task is a newly coordinated development effort by which ECDS and its supporting data infrastructure will demonstrate the feasibility of intelligent data mining and predictive modeling as a biomedical diagnostic support mechanism on manned exploration missions. The initial step towards ground and flight demonstrations has been the research and development of both image and clinical text-based computer-aided patient diagnosis. Human anatomical images displaying abnormal/pathological features have been annotated using controlled terminology templates, marked-up, and then stored in compliance with the AIM standard. These images have been filtered and disease characterized based on machine learning of semantic and quantitative feature vectors. The next phase will evaluate disease treatment response via quantitative linear dimension biomarkers that enable image content-based retrieval and criteria assessment. In addition, a data mining engine (DME) is applied to cross-sectional adult surveys for predicting occurrence of renal calculi, ranked by statistical significance of demographics and specific food ingestion. In addition to this precursor space flight algorithm training, the DME will utilize a feature-engineering capability for unstructured clinical text classification health discovery. The ECDS backbone is a proposed multi-tier modular architecture providing data messaging protocols, storage, management and real-time patient data access. Technology demonstrations and success metrics will be finalized in FY16.

Biomedical support↗

NASA NTRS2017

Enabling Autonomous Space Mission Operations with Artificial Intelligence

For over 50 years, NASA's crewed missions have been confined to the Earth-Moon system, where speed-of-light communications delays between crew and ground are practically nonexistent. This ground-centered mode of operations, with a large, ground-based support team, is not sustainable for NASAs future human exploration missions to Mars. Future astronauts will need smarter tools employing Artificial Intelligence (AI) techniques make decisions without inefficient communication back and forth with ground-based mission control. In this talk we will describe several demonstrations of astronaut decision support tools using AI techniques as a foundation. These demonstrations show that astronauts tasks ranging from living and working to piloting can benefit from AI technology development.

Frank, Jeremy↗

NASA NTRS1989

Applications of graphics to support a testbed for autonomous space vehicle operations

Researchers describe their experience using graphics tools and utilities while building an application, AUTOPS, that uses a graphical Machintosh (TM)-like interface for the input and display of data, and animation graphics to enhance the presentation of results of autonomous space vehicle operations simulations. AUTOPS is a test bed for evaluating decisions for intelligent control systems for autonomous vehicles. Decisions made by an intelligent control system, e.g., a revised mission plan, might be displayed to the user in textual format or he can witness the effects of those decisions via out of window graphics animations. Although a textual description conveys essentials, a graphics animation conveys the replanning results in a more convincing way. Similarily, iconic and menu-driven screen interfaces provide the user with more meaningful options and displays. Presented here are experiences with the SunView and TAE Plus graphics tools used for interface design, and the Johnson Space Center Interactive Graphics Laboratory animation graphics tools used for generating out out of the window graphics.

Schmeckpeper, K. R.↗

NASA NTRS2005

A Framework for Integration of IVHM Technologies for Intelligent Integration for Vehicle Management

As a part of the overall goal of developing Integrated Vehicle Health Management (IVHM) systems for aerospace vehicles, the NASA Faculty Fellowship Program (NFFP) at Marshall Space Flight Center has performed a pilot study on IVHM principals which integrates researched IVHM technologies in support of Integrated Intelligent Vehicle Management (IIVM). IVHM is the process of assessing, preserving, and restoring system functionality across flight and ground systems (NASA NGLT 2004). The framework presented in this paper integrates advanced computational techniques with sensor and communication technologies for spacecraft that can generate responses through detection, diagnosis, reasoning, and adapt to system faults in support of IIVM. These real-time responses allow the IIVM to modify the effected vehicle subsystem(s) prior to a catastrophic event. Furthermore, the objective of this pilot program is to develop and integrate technologies which can provide a continuous, intelligent, and adaptive health state of a vehicle and use this information to improve safety and reduce costs of operations. Recent investments in avionics, health management, and controls have been directed towards IIVM. As this concept has matured, it has become clear the IIVM requires the same sensors and processing capabilities as the real-time avionics functions to support diagnosis of subsystem problems. New sensors have been proposed, in addition, to augment the avionics sensors to support better system monitoring and diagnostics. As the designs have been considered, a synergy has been realized where the real-time avionics can utilize sensors proposed for diagnostics and prognostics to make better real-time decisions in response to detected failures. IIVM provides for a single system allowing modularity of functions and hardware across the vehicle. The framework that supports IIVM consists of 11 major on-board functions necessary to fully manage a space vehicle maintaining crew safety and mission objectives: Guidance and Navigation; Communications and Tracking; Vehicle Monitoring; Information Transport and Integration; Vehicle Diagnostics; Vehicle Prognostics; Vehicle mission Planning; Automated Repair and Replacement; Vehicle Control; Human Computer Interface; and Onboard Verification and Validation. Furthermore, the presented framework provides complete vehicle management which not only allows for increased crew safety and mission success through new intelligence capabilities, but also yields a mechanism for more efficient vehicle operations. The representative IVHM technologies for IIVH includes: 1) robust controllers for use in re-usable launch vehicles, 2) scaleable/flexible computer platform using heterogeneous communication, 3) coupled electromagnetic oscillators for enhanced communications, 4) Linux-based real-time systems, 5) genetic algorithms, 6) Bayesian Networks, 7) evolutionary algorithms, 8) dynamic systems control modeling, and 9) advanced sensing capabilities. This paper presents IVHM technologies developed under NASA's NFFP pilot project. The integration of these IVHM technologies forms the framework for IIVM.

Paris, Deidre E.↗

NASA NTRS2005

Intelligent Vehicle Health Management

As a part of the overall goal of developing Integrated Vehicle Health Management systems for aerospace vehicles, the NASA Faculty Fellowship Program (NFFP) at Marshall Space Flight Center has performed a pilot study on IVHM principals which integrates researched IVHM technologies in support of Integrated Intelligent Vehicle Management (IIVM). IVHM is the process of assessing, preserving, and restoring system functionality across flight and ground systems (NASA NGLT 2004). The framework presented in this paper integrates advanced computational techniques with sensor and communication technologies for spacecraft that can generate responses through detection, diagnosis, reasoning, and adapt to system faults in support of INM. These real-time responses allow the IIVM to modify the affected vehicle subsystem(s) prior to a catastrophic event. Furthermore, the objective of this pilot program is to develop and integrate technologies which can provide a continuous, intelligent, and adaptive health state of a vehicle and use this information to improve safety and reduce costs of operations. Recent investments in avionics, health management, and controls have been directed towards IIVM. As this concept has matured, it has become clear the INM requires the same sensors and processing capabilities as the real-time avionics functions to support diagnosis of subsystem problems. New sensors have been proposed, in addition, to augment the avionics sensors to support better system monitoring and diagnostics. As the designs have been considered, a synergy has been realized where the real-time avionics can utilize sensors proposed for diagnostics and prognostics to make better real-time decisions in response to detected failures. IIVM provides for a single system allowing modularity of functions and hardware across the vehicle. The framework that supports IIVM consists of 11 major on-board functions necessary to fully manage a space vehicle maintaining crew safety and mission objectives: Guidance and Navigation; Communications and Tracking; Vehicle Monitoring; Information Transport and Integration; Vehicle Diagnostics; Vehicle Prognostics; Vehicle mission Planning; Automated Repair and Replacement; Vehicle Control; Human Computer Interface; and Onboard Verification and Validation. Furthermore, the presented framework provides complete vehicle management which not only allows for increased crew safety and mission success through new intelligence capabilities, but also yields a mechanism for more efficient vehicle operations. The representative IVHM technologies for computer platform using heterogeneous communication, 3) coupled electromagnetic oscillators for enhanced communications, 4) Linux-based real-time systems, 5) genetic algorithms, 6) Bayesian Networks, 7) evolutionary algorithms, 8) dynamic systems control modeling, and 9) advanced sensing capabilities. This paper presents IVHM technologies developed under NASA's NFFP pilot project and the integration of these technologies forms the framework for IIVM.

Paris, Deidre E.↗

NASA NTRSDate not supplied

Risks of Increased Earth Independence

As human space exploration begins to extend beyond the immediate vicinity of Earth, the ability of expertise on the ground to support operations will progressively decrease. Ground control expertise has been the primary countermeasure preventing loss of life and mission over the past sixty years and it will be gradually stripped away as expeditions reach further into space. The large, flexible and adaptive teams of experts on the ground, provide not only engineering analysis and problem-solving but also greatly increased work capacity. Monitoring of the large and fast moving stream of telemetry data is carried out around the clock by 20-30 flight controllers per shift. Analysis of that data and troubleshooting is carried out by an additional 50-100 engineers per shift. Artificial intelligence capabilities will need to be part of the solution but will not the entire solution. As progress continues to be made on intelligent systems, especially those for use in complex, dynamic environments where humans will remain a part of the activity, there is an ever increasing need to focus on how those systems will interact with the humans. Although capabilities such as natural language processing and facial recognition have become common place, even basic aspects of problem-solving, causal reasoning and generative decision-making remain well-beyond of our current capabilities. Advanced data visualization, procedure execution support, and new training approaches will be needed to close the gap between what is currently provided by experts on the ground and what the crew will need to do in increasingly autonomous ways with greater distance from Earth.

human-systems integration architecture↗

NASA NTRS2005

IVHM Framework for Intelligent Integration for Vehicle Health Management

Integrated Vehicle Health Management (IVHM) systems for aerospace vehicles, is the process of assessing, preserving, and restoring system functionality across flight and techniques with sensor and communication technologies for spacecraft that can generate responses through detection, diagnosis, reasoning, and adapt to system faults in support of Integrated Intelligent Vehicle Management (IIVM). These real-time responses allow the IIVM to modify the affected vehicle subsystem(s) prior to a catastrophic event. Furthermore, this framework integrates technologies which can provide a continuous, intelligent, and adaptive health state of a vehicle and use this information to improve safety and reduce costs of operations. Recent investments in avionics, health management, and controls have been directed towards IIVM. As this concept has matured, it has become clear that IIVM requires the same sensors and processing capabilities as the real-time avionics functions to support diagnosis of subsystem problems. New sensors have been proposed, in addition to augment the avionics sensors to support better system monitoring and diagnostics. As the designs have been considered, a synergy has been realized where the real-time avionics can utilize sensors proposed for diagnostics and prognostics to make better real-time decisions in response to detected failures. IIVM provides for a single system allowing modularity of functions and hardware across the vehicle. The framework that supports IIVM consists of 11 major on-board functions necessary to fully manage a space vehicle maintaining crew safety and mission objectives. These systems include the following: Guidance and Navigation; Communications and Tracking; Vehicle Monitoring; Information Transport and Integration; Vehicle Diagnostics; Vehicle Prognostics; Vehicle Mission Planning, Automated Repair and Replacement; Vehicle Control; Human Computer Interface; and Onboard Verification and Validation. Furthermore, the presented framework provides complete vehicle management which not only allows for increased crew safety and mission success through new intelligence capabilities, but also yields a mechanism for more efficient vehicle operations.

Paris, Deidre↗

NASA NTRS2014

Exploration Technologies for Operations

Although the International Space Station (ISS) assembly has been completed, the Operations support teams continue to seek more efficient and effective ways to prepare for and conduct the ISS operations and future exploration missions beyond low earth orbit. This search for improvement has led to a significant collaboration between the NASA research and advanced software development community at NASA Ames Research Center and the Mission Operations community at NASA Johnson Space Center. Since 2001, NASA Ames Research Center has been developing and applying its advanced intelligent systems and human systems integration research to mission operations tools for several of the unmanned Mars missions operations. Since 2006, NASA Ames Research Center has also been developing and applying its advanced intelligent systems and human systems integration research to mission operations tools for manned operations support with the Mission Operations Directorate at NASA Johnson Space Center. This paper discusses the completion of the development and deployment of a variety of intelligent and human systems technologies adopted for manned mission operations. The technologies associated with the projects include advanced software systems for operations and human-centered computing. Human-centered computing looks to the processes and procedures that people do to perform any given job, then attempts to identify opportunities to improve these processes and procedures. In particular, for mission operations, improvements are quantified by specifically identifying how a tool can increase a persons efficiency, enhance a persons functional capability, andor improve the assurance of a persons decisions. The Ames development team has collaborated with the Mission Operations team to identify areas of efficiencies through technology infusion applications in support of the Plan, Train, and Fly activities of human-spaceflight mission operations. The specific applications discussed in this paper are in the areas of mission planning systems, mission operations design modeling and workflow automation, advanced systems monitoring, mission control technologies, search tools, training management tools, spacecraft solar array management, spacecraft power management, and spacecraft attitude planning. We discuss these specific projects between the Ames Research Center and the Johnson Space Centers Mission Operations Directorate, and how these technologies and projects are enhancing the mission operations support for the International Space Station. We also discuss the challenges, problems, and successes associated with long-distance and multi-year development projects between the research team at Ames and the Mission Operations customers at Johnson Space center. Finally, we discuss how these technology infusion applications and underlying technologies might be used in the future to support on-board operations of the crew and spacecraft systems as human exploration expands beyond low earth orbit to destinations in the solar system where communications delays will require more on-board autonomy and planning by the crew. Longer communications delays will require that the ground mission operations support will be primarily strategic in nature, while the tactical level of planning, systems monitoring and control, and failure analysisisolationrecovery will be the responsibility of both the spacecraft autonomous systems and the crew. Our expectation is that the technologies

mission operations↗

NASA NTRS1994

Dual-Use Space Technology Transfer Conference and Exhibition, Volume 1

This document contains papers presented at the Dual-Use Space Technology Transfer Conference and Exhibition held at the Johnson Space Center February 1-3, 1994. Possible technology transfers covered during the conference were in the areas of information access; innovative microwave and optical applications; materials and structures; marketing and barriers; intelligent systems; human factors and habitation; communications and data systems; business process and technology transfer; software engineering; biotechnology and advanced bioinstrumentation; communications signal processing and analysis; new ways of doing business; medical care; applications derived from control center data systems; human performance evaluation; technology transfer methods; mathematics, modeling, and simulation; propulsion; software analysis and decision tools systems/processes in human support technology; networks, control centers, and distributed systems; power; rapid development perception and vision technologies; integrated vehicle health management; automation technologies; advanced avionics; ans robotics technologies. More than 77 papers, 20 presentations, and 20 exhibits covering various disciplines were presented b experts from NASA, universities, and industry.

Kumar Krishen↗

NASA NTRS1997

Integration of CELSS Simulation with Long-Term Crop Scheduling

This project presents guidelines for the integration of the Intelligent Crop Scheduler (ICS) developed by Leon (1995) with a version of the Biological Life Support System (BLSS) simulation based on the work by Volk and Rummel (1987). These guidelines will also aid in defining the appropriate model detail of simulation-based schedulers. ICS determines what, when and how much to plant of different crops. These decisions are made such that the critical reservoir levels are maintained close to their nominal or desired settings during the duration of the mission. Initial feasibility of the approach has been demonstrated using simplified implementations of the scheduling approach and CELSS 'world' model developed by the investigator at JSC in the Summer of 1995. The BLSS model incorporates more detail. The increased fidelity is in terms of added mass-regeneration formalism (biochemical stoichiometry), more plants, and more accurate modeling of the mechanical system. This report describes the main features of the Crop scheduler and CELSS simulator, discusses integration issues, and provides with detailed guidelines for the integration of these two applications.

Leon, V. Jorge↗

NASA NTRS2011

ISS Operations Cost Reductions Through Automation of Real-Time Planning Tasks

In 2007 the Johnson Space Center s Mission Operations Directorate (MOD) management team challenged their organizations to find ways to reduce the cost of operations for supporting the International Space Station (ISS) in the Mission Control Center (MCC). Each MOD organization was asked to define and execute projects that would help them attain cost reductions by 2012. The MOD Operations Division Flight Planning Branch responded to this challenge by launching several software automation projects that would allow them to greatly improve console operations and reduce ISS console staffing and intern reduce operating costs. These tasks ranged from improving the management and integration mission plan changes, to automating the uploading and downloading of information to and from the ISS and the associated ground complex tasks that required multiple decision points. The software solutions leveraged several different technologies including customized web applications and implementation of industry standard web services architecture; as well as engaging a previously TRL 4-5 technology developed by Ames Research Center (ARC) that utilized an intelligent agent-based system to manage and automate file traffic flow, archive data, and generate console logs. These projects to date have allowed the MOD Operations organization to remove one full time (7 x 24 x 365) ISS console position in 2010; with the goal of eliminating a second full time ISS console support position by 2012. The team will also reduce one long range planning console position by 2014. When complete, these Flight Planning Branch projects will account for the elimination of 3 console positions and a reduction in staffing of 11 engineering personnel (EP) for ISS.

Hall, Timothy A.↗

NASA NTRS1992

Automating software design system DESTA

'DESTA' is the acronym for the Dialogue Evolutionary Synthesizer of Turnkey Algorithms by means of a natural language (Russian or English) functional specification of algorithms or software being developed. DESTA represents the computer-aided and/or automatic artificial intelligence 'forgiving' system which provides users with software tools support for algorithm and/or structured program development. The DESTA system is intended to provide support for the higher levels and earlier stages of engineering design of software in contrast to conventional Computer Aided Design (CAD) systems which provide low level tools for use at a stage when the major planning and structuring decisions have already been taken. DESTA is a knowledge-intensive system. The main features of the knowledge are procedures, functions, modules, operating system commands, batch files, their natural language specifications, and their interlinks. The specific domain for the DESTA system is a high level programming language like Turbo Pascal 6.0. The DESTA system is operational and runs on an IBM PC computer.

Lovitsky, Vladimir A.↗