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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Intelligent tutoring systems research in the training systems division: Space applications

Computer-Aided Instruction (CAI) is a mature technology used to teach students in a wide variety of domains. The introduction of Artificial Intelligence (AI) technology of the field of CAI has prompted research and development efforts in an area known as Intelligent Computer-Aided Instruction (ICAI). In some cases, ICAI has been touted as a revolutionary alternative to traditional CAI. With the advent of powerful, inexpensive school computers, ICAI is emerging as a potential rival to CAI. In contrast to this, one may conceive of Computer-Based Training (CBT) systems as lying along a continuum which runs from CAI to ICAI. Although the key difference between the two is intelligence, there is not commonly accepted definition of what constitutes an intelligent instructional system.

Regian, J. Wesley↗
NASA NTRS2008

Intelligent Propulsion System Foundation Technology: Summary of Research

The purpose of this cooperative agreement was to develop a foundation of intelligent propulsion technologies for NASA and industry that will have an impact on safety, noise, emissions, and cost. These intelligent engine technologies included sensors, electronics, communications, control logic, actuators, smart materials and structures, and system studies. Furthermore, this cooperative agreement helped prepare future graduates to develop the revolutionary intelligent propulsion technologies that will be needed to ensure pre-eminence of the U.S. aerospace industry. This Propulsion 21 - Phase 11 program consisted of four primary research areas and associated work elements at Ohio universities: 1.0 Turbine Engine Prognostics, 2.0 Active Controls for Emissions and Noise Reduction, 3.0 Active Structural Controls and Performance, and 4.0 System Studies and Integration. Phase l, which was conducted during the period August 1, 2003, through September 30, 2004, has been reported separately.

Source record↗
NASA NTRS1990

Cooperating systems: Layered MAS

Distributed intelligent systems can be distinguished by the models that they use. The model developed focuses on layered multiagent system conceived of as a bureaucracy in which a distributed data base serves as a central means of communication. The various generic bureaus of such a system is described and a basic vocabulary for such systems is presented. In presenting the bureaus and vocabularies, special attention is given to the sorts of reasonings that are appropriate. A bureaucratic model has a hierarchy of master system and work group that organizes E agents and B agents. The master system provides the administrative services and support facilities for the work groups.

Rochowiak, Daniel↗
NASA NTRS1991

Knowledge-based decision support for Space Station assembly sequence planning

A complete Personal Analysis Assistant (PAA) for Space Station Freedom (SSF) assembly sequence planning consists of three software components: the system infrastructure, intra-flight value added, and inter-flight value added. The system infrastructure is the substrate on which software elements providing inter-flight and intra-flight value-added functionality are built. It provides the capability for building representations of assembly sequence plans and specification of constraints and analysis options. Intra-flight value-added provides functionality that will, given the manifest for each flight, define cargo elements, place them in the National Space Transportation System (NSTS) cargo bay, compute performance measure values, and identify violated constraints. Inter-flight value-added provides functionality that will, given major milestone dates and capability requirements, determine the number and dates of required flights and develop a manifest for each flight. The current project is Phase 1 of a projected two phase program and delivers the system infrastructure. Intra- and inter-flight value-added were to be developed in Phase 2, which has not been funded. Based on experience derived from hundreds of projects conducted over the past seven years, ISX developed an Intelligent Systems Engineering (ISE) methodology that combines the methods of systems engineering and knowledge engineering to meet the special systems development requirements posed by intelligent systems, systems that blend artificial intelligence and other advanced technologies with more conventional computing technologies. The ISE methodology defines a phased program process that begins with an application assessment designed to provide a preliminary determination of the relative technical risks and payoffs associated with a potential application, and then moves through requirements analysis, system design, and development.

Source record↗
NASA NTRS2008

Intelligent Engine Systems: Thermal Management and Advanced Cooling

The objective of the Advanced Turbine Cooling and Thermal Management program is to develop intelligent control and distribution methods for turbine cooling, while achieving a reduction in total cooling flow and assuring acceptable turbine component safety and reliability. The program also will develop embedded sensor technologies and cooling system models for real-time engine diagnostics and health management. Both active and passive control strategies will be investigated that include the capability of intelligent modulation of flow quantities, pressures, and temperatures both within the supply system and at the turbine component level. Thermal management system concepts were studied, with a goal of reducing HPT blade cooling air supply temperature. An assessment will be made of the use of this air by the active clearance control system as well. Turbine component cooling designs incorporating advanced, high-effectiveness cooling features, will be evaluated. Turbine cooling flow control concepts will be studied at the cooling system level and the component level. Specific cooling features or sub-elements of an advanced HPT blade cooling design will be downselected for core fabrication and casting demonstrations.

Bergholz, Robert↗
NASA NTRS2003

Rethinking Human-Centered Computing: Finding the Customer and Negotiated Interactions at the Airport

The breakdown in the air transportation system over the past several years raises an interesting question for researchers: How can we help improve the reliability of airline operations? In offering some answers to this question, we make a statement about Huuman-Centered Computing (HCC). First we offer the definition that HCC is a multi-disciplinary research and design methodology focused on supporting humans as they use technology by including cognitive and social systems, computational tools and the physical environment in the analysis of organizational systems. We suggest that a key element in understanding organizational systems is that there are external cognitive and social systems (customers) as well as internal cognitive and social systems (employees) and that they interact dynamically to impact the organization and its work. The design of human-centered intelligent systems must take this outside-inside dynamic into account. In the past, the design of intelligent systems has focused on supporting the work and improvisation requirements of employees but has often assumed that customer requirements are implicitly satisfied by employee requirements. Taking a customer-centric perspective provides a different lens for understanding this outside-inside dynamic, the work of the organization and the requirements of both customers and employees In this article we will: 1) Demonstrate how the use of ethnographic methods revealed the important outside-inside dynamic in an airline, specifically the consequential relationship between external customer requirements and perspectives and internal organizational processes and perspectives as they came together in a changing environment; 2) Describe how taking a customer centric perspective identifies places where the impact of the outside-inside dynamic is most critical and requires technology that can be adaptive; 3) Define and discuss the place of negotiated interactions in airline operations, identifying how these interactions between customers and airline employees provided new insights into design problems in the airline system; 4) Show how taking a customer-centric perspective influences the HCC design of an airline system and make recommendations for new architectures and intelligent devices that will enable airline systems to adapt flexibly to delay situations, supporting both customers and airline employees.

Wales, Roxana↗
NASA NTRS1988

Systems autonomy

Information on systems autonomy is given in viewgraph form. Information is given on space systems integration, intelligent autonomous systems, automated systems for in-flight mission operations, the Systems Autonomy Demonstration Project on the Space Station Thermal Control System, the architecture of an autonomous intelligent system, artificial intelligence research issues, machine learning, and real-time image processing.

Lum, Henry, Jr.↗
NASA NTRS1990

The role of artificial intelligence techniques in scheduling systems

Artificial Intelligence (AI) techniques provide good solutions for many of the problems which are characteristic of scheduling applications. However, scheduling is a large, complex heterogeneous problem. Different applications will require different solutions. Any individual application will require the use of a variety of techniques, including both AI and conventional software methods. The operational context of the scheduling system will also play a large role in design considerations. The key is to identify those places where a specific AI technique is in fact the preferable solution, and to integrate that technique into the overall architecture.

Geoffroy, Amy L.↗
NASA NTRS2002

Measuring the Performance and Intelligence of Systems: Proceedings of the 2002 PerMIS Workshop

Contents include the following: Performance Metrics; Performance of Multiple Agents; Performance of Mobility Systems; Performance of Planning Systems; General Discussion Panel 1; Uncertainty of Representation I; Performance of Robots in Hazardous Domains; Modeling Intelligence; Modeling of Mind; Measuring Intelligence; Grouping: A Core Procedure of Intelligence; Uncertainty in Representation II; Towards Universal Planning/Control Systems.

Messina, E. R.↗
NASA NTRS1992

Needs for supervised space robots in space exploration

The areas of application for space robots in the Space Exploration Initiative (SEI) are examined by reviewing the roles of SEI supervised robots particularly with planet-surface systems (PSSs). Treatment is given to both teleoperated conventional robot systems and autonomous intelligent systems for comparison in terms of safety, reliability, and productivity. Two development stages are proposed including one with a robotic actor, human observer, and a human supervisor and a second in which a closed-loop control and monitoring system is established. The use of remote control is shown to require robustness, self-calibration and -diagnosis, adjustable autonomy, and multitask capability. The requirements of intelligent control are also listed so that the PSSs of the SEI can be used to enable surface exploration, local-resource utilization potential, and reductions of human tasks.

Erickson, Jon D.↗
NASA NTRS1987

A flexible telerobotic system for space operations

This paper describes the objective and design of a proposed goal-oriented knowledge-based telerobotic system for space operations. This design effort encompasses the elements of the system executive and user interface and the distribution and general structure of the knowledge base, the displays, and the task sequencing. The objective of the design effort is to provide an expandable structure for a telerobotic system that provides cooperative interaction between the human operator and computer control. The initial phase of the implementation provides a rule-based, goal-oriented script generator to interface to the existing control modes of a telerobotic research system, in the Intelligent Systems Research Lab at NASA Research Center.

Sliwa, Nancy Orlando↗
NASA NTRS1987

A flexible telerobotic system for space operations

The objective and design of a proposed goal-oriented knowledge-based telerobotic system for space operations is described. This design effort encompasses the elements of the system executive and user interface and the distribution and general structure of the knowledge base, the displays, and the task sequencing. The objective of the design effort is to provide an expandable structure for a telerobotic system that provides cooperative interaction between the human operator and computer control. The initial phase of the implementation provides a rule-based, goal-oriented script generator to interface to the existing control modes of a telerobotic research system, in the Intelligent Systems Research Lab at NASA Research Center.

Sliwa, N. O.↗
NASA NTRS2002

Computing, Information and Communications Technology (CICT) Website

The Computing, Information and Communications Technology Program (CICT) was established in 2001 to ensure NASA's Continuing leadership in emerging technologies. It is a coordinated, Agency-wide effort to develop and deploy key enabling technologies for a broad range of mission-critical tasks. The NASA CICT program is designed to address Agency-specific computing, information, and communications technology requirements beyond the projected capabilities of commercially available solutions. The areas of technical focus have been chosen for their impact on NASA's missions, their national importance, and the technical challenge they provide to the Program. In order to meet its objectives, the CICT Program is organized into the following four technology focused projects: 1) Computing, Networking and Information Systems (CNIS); 2) Intelligent Systems (IS); 3) Space Communications (SC); 4) Information Technology Strategic Research (ITSR).

Hardman, John↗
NASA NTRSDate not supplied

ILEOS: A Novel Intelligent Observing System Enabled by High Altitude Long Endurance Uncrewed Aerial Systems

Most major global satellite surveyors of climate-relevant trace gases have relatively coarse spatial resolution or temporal sampling. While these data can be supplemented by fine-pointing satellites and aircraft, the spatial and temporal resolutions available from crewed aircraft is not sufficient to observe stochastic, ephemeral events that take place between observations. Emerging High Altitude Long Endurance (HALE) Uncrewed Aerial Systems (UAS) can operate for months at a time and loiter over targets to provide continuous daylight geostationary-like observations, allowing these new platforms to be integrated with existing satellites as part of a New Observing Strategy (NOS).To aid in the planning of future NOS missions, NASA is developing the Intelligent Long Endurance Observing System (ILEOS), a science activity planning system. ILEOS will help scientists build plans to improve spatio-temporal resolution of climate-relevant gases by fusing coarse-grained sensor data from satellites and other sources(e.g., terrain, forecasts), and plan HALE UAS flights to obtain finer-grain (high spatio-temporal) data. ILEOS will also enable observations for longer periods and of environments not accessible through in-situ observations and crewed aircraft field campaigns.

science planning pipeline↗
NASA NTRS1990

Knowledge base rule partitioning design for CLIPS

This describes a knowledge base (KB) partitioning approach to solve the problem of real-time performance using the CLIPS AI shell when containing large numbers of rules and facts. This work is funded under the joint USAF/NASA Advanced Launch System (ALS) Program as applied research in expert systems to perform vehicle checkout for real-time controller and diagnostic monitoring tasks. The Expert System advanced development project (ADP-2302) main objective is to provide robust systems responding to new data frames of 0.1 to 1.0 second intervals. The intelligent system control must be performed within the specified real-time window, in order to meet the demands of the given application. Partitioning the KB reduces the complexity of the inferencing Rete net at any given time. This reduced complexity improves performance but without undo impacts during load and unload cycles. The second objective is to produce highly reliable intelligent systems. This requires simple and automated approaches to the KB verification & validation task. Partitioning the KB reduces rule interaction complexity overall. Reduced interaction simplifies the V&V testing necessary by focusing attention only on individual areas of interest. Many systems require a robustness that involves a large number of rules, most of which are mutually exclusive under different phases or conditions. The ideal solution is to control the knowledge base by loading rules that directly apply for that condition, while stripping out all rules and facts that are not used during that cycle. The practical approach is to cluster rules and facts into associated 'blocks'. A simple approach has been designed to control the addition and deletion of 'blocks' of rules and facts, while allowing real-time operations to run freely. Timing tests for real-time performance for specific machines under R/T operating systems have not been completed but are planned as part of the analysis process to validate the design.

Mainardi, Joseph D.↗
NASA NTRS2004

Intelligent Propulsion System Foundation Technology: Summary of Research

The purpose of this cooperative agreement was to develop a foundation of intelligent propulsion technologies for NASA and industry that will have an impact on safety, noise, emissions and cost. These intelligent engine technologies included sensors, electronics, communications, control logic, actuators, and smart materials and structures. Furthermore this cooperative agreement helped prepare future graduates to develop the revolutionary intelligent propulsion technologies that will be needed to ensure pre-eminence of the U.S. aerospace industry. The program consisted of three primary research areas (and associated work elements at Ohio universities): 1.0 Turbine Engine Prognostics, 2.0 Active Controls for Emissions and Noise Reduction, and 3.0 Active Structural Controls.

Williams, James C.↗
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 NTRS1987

A conceptual framework for intelligent real-time information processing

By combining artificial intelligence concepts with the human information processing model of Rasmussen, a conceptual framework was developed for real time artificial intelligence systems which provides a foundation for system organization, control and validation. The approach is based on the description of system processing terms of an abstraction hierarchy of states of knowledge. The states of knowledge are organized along one dimension which corresponds to the extent to which the concepts are expressed in terms of the system inouts or in terms of the system response. Thus organized, the useful states form a generally triangular shape with the sensors and effectors forming the lower two vertices and the full evaluated set of courses of action the apex. Within the triangle boundaries are numerous processing paths which shortcut the detailed processing, by connecting incomplete levels of analysis to partially defined responses. Shortcuts at different levels of abstraction include reflexes, sensory motor control, rule based behavior, and satisficing. This approach was used in the design of a real time tactical decision aiding system, and in defining an intelligent aiding system for transport pilots.

Schudy, Robert↗