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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Model-based reasoning for system and software engineering: The Knowledge From Pictures (KFP) environment

This paper presents a discussion of current work in the area of graphical modeling and model-based reasoning being undertaken by the Automation Technology Section, Code 522.3, at Goddard. The work was initially motivated by the growing realization that the knowledge acquisition process was a major bottleneck in the generation of fault detection, isolation, and repair (FDIR) systems for application in automated Mission Operations. As with most research activities this work started out with a simple objective: to develop a proof-of-concept system demonstrating that a draft rule-base for a FDIR system could be automatically realized by reasoning from a graphical representation of the system to be monitored. This work was called Knowledge From Pictures (KFP) (Truszkowski et. al. 1992). As the work has successfully progressed the KFP tool has become an environment populated by a set of tools that support a more comprehensive approach to model-based reasoning. This paper continues by giving an overview of the graphical modeling objectives of the work, describing the three tools that now populate the KFP environment, briefly presenting a discussion of related work in the field, and by indicating future directions for the KFP environment.

Bailin, Sydney↗
NASA NTRS2009

Survey and Method for Determination of Trajectory Predictor Requirements

A survey of air-traffic-management researchers, representing a broad range of automation applications, was conducted to document trajectory-predictor requirements for future decision-support systems. Results indicated that the researchers were unable to articulate a basic set of trajectory-prediction requirements for their automation concepts. Survey responses showed the need to establish a process to help developers determine the trajectory-predictor-performance requirements for their concepts. Two methods for determining trajectory-predictor requirements are introduced. A fast-time simulation method is discussed that captures the sensitivity of a concept to the performance of its trajectory-prediction capability. A characterization method is proposed to provide quicker, yet less precise results, based on analysis and simulation to characterize the trajectory-prediction errors associated with key modeling options for a specific concept. Concept developers can then identify the relative sizes of errors associated with key modeling options, and qualitatively determine which options lead to significant errors. The characterization method is demonstrated for a case study involving future airport surface traffic management automation. Of the top four sources of error, results indicated that the error associated with accelerations to and from turn speeds was unacceptable, the error associated with the turn path model was acceptable, and the error associated with taxi-speed estimation was of concern and needed a higher fidelity concept simulation to obtain a more precise result

Rentas, Tamika L.↗
NASA NTRS1994

A modular approach for automated sample preparation and chemical analysis

Changes in international relations, especially within the past several years, have dramatically affected the programmatic thrusts of the U.S. Department of Energy (DOE). The DOE now is addressing the environmental cleanup required as a result of 50 years of nuclear arms research and production. One major obstacle in the remediation of these areas is the chemical determination of potentially contaminated material using currently acceptable practices. Process bottlenecks and exposure to hazardous conditions pose problems for the DOE. One proposed solution is the application of modular automated chemistry using Standard Laboratory Modules (SLM) to perform Standard Analysis Methods (SAM). The Contaminant Analysis Automation (CAA) Program has developed standards and prototype equipment that will accelerate the development of modular chemistry technology and is transferring this technology to private industry.

Clark, Michael L.↗
NASA NTRS2023

Pypromice: A Python Package for Processing Automated Weather Station Data

The pypromice Python package is for processing and handling observation datasets from automated weather stations (AWS). It is primarily aimed at users of AWS data from the Geological Survey of Denmark and Greenland (GEUS), which collects and distributes in situ weather station observations to the cryospheric science research community. Functionality in pypromice is primarily handled using two key open-source Python packages, xarray (Hoyer & Hamman, 2017) and pandas (The pandas development team, 2020). A defined processing workflow is included in pypromice for transforming original AWS observations (Level 0, L0) to a usable, CF-convention-compliant dataset (Level 3, L3) (Figure 1). Intermediary processing levels (L1,L2) refer to key stages in the workflow, namely the conversion of variables to physical measurements and variable filtering (L1), cross-variable corrections and user-defined data flagging and fixing (L2), and derived variables (L3). Information regarding the station configuration is needed to perform the processing, such as instrument calibration coefficients and station type (one-boom tripod or two-boom mast station design, for example), which are held in a toml configuration file. Two example configuration files are provided with pypromice , which are also used in the package’s unit tests. More detailed documentation of the AWS design, instrumentation, and processing steps are described in Fausto et al. (2021).

pypromice↗
NASA NTRS1990

i-SAIRAS '90; Proceedings of the International Symposium on Artificial Intelligence, Robotics and Automation in Space, Kobe, Japan, Nov. 18-20, 1990

The present conference on artificial intelligence (AI), robotics, and automation in space encompasses robot systems, lunar and planetary robots, advanced processing, expert systems, knowledge bases, issues of operation and management, manipulator control, and on-orbit service. Specific issues addressed include fundamental research in AI at NASA, the FTS dexterous telerobot, a target-capture experiment by a free-flying robot, the NASA Planetary Rover Program, the Katydid system for compiling KEE applications to Ada, and speech recognition for robots. Also addressed are a knowledge base for real-time diagnosis, a pilot-in-the-loop simulation of an orbital docking maneuver, intelligent perturbation algorithms for space scheduling optimization, a fuzzy control method for a space manipulator system, hyperredundant manipulator applications, robotic servicing of EOS instruments, and a summary of astronaut inputs on automation and robotics for the Space Station Freedom.

Source record↗
NASA NTRS1976

Space Processing Applications - Designing the initial space transportation system payloads capability

A review is presented of the broad objectives identified by the U.S. Space Processing Applications program. A description is given of the types of materials to be considered, taking into account aspects of crystal growth, questions of purification and separation, mixing, solidification, and processes in fluids. The program requirements are discussed, giving attention to time in space, energy, research and development payload equipment design efforts, design payloads, early mission automated payloads, and early mission manned payloads.

Hammel, R. L.↗
NASA NTRS1994

Planning applications in image analysis

We describe two interim results from an ongoing effort to automate the acquisition, analysis, archiving, and distribution of satellite earth science data. Both results are applications of Artificial Intelligence planning research to the automatic generation of processing steps for image analysis tasks. First, we have constructed a linear conditional planner (CPed), used to generate conditional processing plans. Second, we have extended an existing hierarchical planning system to make use of durations, resources, and deadlines, thus supporting the automatic generation of processing steps in time and resource-constrained environments.

Boddy, Mark↗
NASA NTRSDate not supplied

Artemis Flight Plan Evolution

Current capabilities and processes are insufficient to confidently meet mission objectives given the complexity of humans on the ground and on-orbit working with different automated vehicles. This research aims to reduce risk of human error by providing a consolidated, human-digestible, source of information that can be used in pre-mission through mission execution by all team members involved in spaceflight.

Mission Control↗
NASA NTRS2011

Materials Science Research Rack Onboard the International Space Station

The Materials Science Research Rack (MSRR) allows for the study of a variety of materials including metals, ceramics, semiconductor crystals, and glasses onboard the International Space Station (ISS). MSRR was launched on STS-128 in August 2009, and is currently installed in the U. S. Destiny Laboratory Module. Since that time, MSRR has performed virtually flawlessly logging more than 550 hours of operating time. Materials science is an integral part of development of new materials for everyday life here on Earth. The goal of studying materials processing in space is to develop a better understanding of the chemical and physical mechanisms involved. Materials science research benefits from the microgravity environment of space, where the researcher can better isolate chemical and thermal properties of materials from the effects of gravity. With this knowledge, reliable predictions can be made about the conditions required on Earth to achieve improved materials. MSRR is a highly automated facility containing two furnace inserts in which Sample Cartridge Assemblies (SCAs), each containing one material sample, can be processed up to temperatures of 1400C. Once an SCA is installed by a Crew Member, the experiment can be run by automatic command or science conducted via telemetry commands from the ground. Initially, 12 SCAs were processed in the first furnace insert for a team of European and US investigators. The processed samples have been returned to Earth for evaluation and comparison of their properties to samples similarly processed on the ground. A preliminary examination of the samples indicates that the majority of the desired science objectives have been successfully met leading to significant improvements in the understanding of alloy solidification processes. The second furnace insert will be installed in the facility in January 2011 for processing the remaining SCA currently on orbit. Six SCAs are planned for launch summer 2011, and additional batches are planned for future processing. This facility is available to support additional materials science investigations through programs such as the US National Laboratory, Technology Development, NASA Research Announcements, ESA application oriented research programs, and others. The development of the research rack was a cooperative effort between NASA's Marshall Space Flight Center and the European Space Agency (ESA).

Frazier, Natalie C.↗
NASA NTRS2019

Integrated Design and Manufacturing Analysis for Automated Fiber Placement Structures

Automated fiber placement provides many advancements beyond traditional hand layups in terms of efficiency and reliability. However, there are also a variety of unique challenges that arise with automated fiber placement technology. In particular, steering of tows over doubly-curved tool surfaces can result in material overlaps and gaps due to path convergence/divergence, fiber angle deviation, as well defects in the tows themselves such as puckers and wrinkles. Minimization of these defects is traditionally considered a task for the manufacturing discipline. Manufacturing specifications are often created for these defects based on laminate testing and can be inflexible to avoid more tests. Recent efforts have been made under the National Aeronautics and Space Administration (NASA) Advanced Composites Project (ACP) to develop software tools and processes that provide automated coupling between design and manufacturing disciplines. The objective of this coupling is to provide information to the design discipline on the manufacturability of a laminate while the laminate is being designed. A variety of software tools, both existing commercial tools and research tools under development, will be used to achieve this objective: HyperSizer for laminate optimization, the Computer Aided Process Planning module for selection of manufacturing process parameters, Vericut Composite Programming for tow path simulation, and COMPRO for deposition and cure defects. The newly developed “Central Optimizer” tool will be used to tie the modules together and drive the design for manufacturing process.

Noevere, August↗
NASA NTRS1994

The SCRAM tool-kit

This paper proposes a new series of on-orbit capabilities to support the near-term Hubble Space Telescope, Extended Duration Orbiter, Long Duration Orbiter, Space Station Freedom, other orbital platforms, and even the future manned Lunar/Mars missions. These proposed capabilities form a toolkit termed Space Construction, Repair, and Maintenance (SCRAM). SCRAM addresses both intra-Vehicular Activity (IVA) and Extra-Vehicular Activity (EVA) needs. SCRAM provides a variety of tools which enable welding, brazing, cutting, coating, heating, and cleaning, as well as corresponding nondestructive examination. Near-term IVA-SCRAM applications include repair and modification to fluid lines, structure, and laboratory equipment inside a shirt-sleeve environment (i.e. inside Spacelab or Space Station). Near-term EVA-SCRAM applications include construction of fluid lines and structural members, repair of punctures by orbital debris, refurbishment of surfaces eroded by contaminants. The SCRAM tool-kit also promises future EVA applications involving mass production tasks automated by robotics and artificial intelligence, for construction of large truss, aerobrake, and nuclear reactor shadow shields structures. The leading candidate tool processes for SCRAM, currently undergoing research and development, include Electron Beam, Gas Tungsten Arc, Plasma Arc, and Laser Beam. A series of strategic space flight experiments would make SCRAM available to help conquer the space frontier.

Tamir, David↗
NASA NTRS2018

Planetary Probe Entry Models for Concurrent and Integrated Interplanetary Mission Design

There are many prospective mission opportunities involving atmospheric entry probes. The Planetary Science Deep Space SmallSat Studies (PSDS3) re-cently selected probe missions to Venus, Mars, and the outer planets as part of the 10 selected studies. Two of the six themes in the most recent New Fron-tiers call were a Saturn probe and a Venus in situ explorer. The 2013-2022 Planetary Science Decadal Survey includes probe missions at Venus, Mars, Saturn, Titan, Uranus, and Neptune. Across mission destinations and mission classes there is growing interest in planetary probes. While interplanetary trajectory specialists may like to use a broad sweep of low-fidelity solutions to find a wide array of trajectory options, probe specialists typically start off with mid- to high-fidelity point designs for the entry probe since the equations of motion for atmospheric probes require numerical integration and are so directly linked with some of the probe's subsystem design. Cur-rently, there are no alternatives to this design ap-proach as there are no tools capable of automatical-ly and concurrently designing interplanetary and atmospheric trajectories. Unfortunately, this makes us reliant on point designs in the early stages of the mission design process. The reliance on point de-signs for atmospheric probes hinders the flexibility of the design, making the design process cumber-some and restricting decision-making down the road. The research presented here addresses this problem by providing low-fidelity models for the automated, rapid design of atmospheric trajectories and probe's models which may be solved concur-rently with the interplanetary trajectory.

atmospheric probes↗
NASA NTRS1990

Real-time piloted simulation of fully automatic guidance and control for rotorcraft nap-of-the-earth (NOE) flight following planned profiles

Developing a single-pilot all-weather NOE capability requires fully automatic NOE navigation and flight control. Innovative guidance and control concepts are being investigated to (1) organize the onboard computer-based storage and real-time updating of NOE terrain profiles and obstacles; (2) define a class of automatic anticipative pursuit guidance algorithms to follow the vertical, lateral, and longitudinal guidance commands; (3) automate a decision-making process for unexpected obstacle avoidance; and (4) provide several rapid response maneuvers. Acquired knowledge from the sensed environment is correlated with the recorded environment which is then used to determine an appropriate evasive maneuver if a nonconformity is observed. This research effort has been evaluated in both fixed-base and moving-base real-time piloted simulations thereby evaluating pilot acceptance of the automated concepts, supervisory override, manual operation, and reengagement of the automatic system.

Clement, Warren F.↗
NASA NTRSDate not supplied

The Human Research Program Grant Lifecycle & Data Integration Schedule: Infographic

The Human Research Program (HRP) Grant Lifecycle process can be described using information from several government authoritative sources with overlapping generalizations. It is the responsibility of the HRP Program Planning & Control (PP&C) Office and the Data Management Integration Office (DMIO)to interpret this information into a cohesive process that can be communicated to the human research organization. PP&C and DMIO have been exploring training opportunities to facilitate understanding through the form of infographics. This communication tool combines eye-catching visuals and text making complex information and data more digestible and shareable. The infographic poster tells a short story about a federally awarded grant and is intended to help both the new and experienced HRP workforce understand the timeline for a research procurement and where their specific tasks fall within the 4 phases of the grant lifecycle. The Pre-Award, Award, Post-Award, and Closeout phases are overlayed with business swimlanes so HRP stakeholders can see where they fit into the timeline rather than working in an isolated part. This includes the Chief Scientist Office (CSO), PP&C, the Data Management Integration Office (DMIO), the Principal Investigator (PI), the Element stakeholders, the LSDA Archivists, and the Research & Operations Integration (ROI) team along with the stakeholders in the Human Health and Performance Directorate. Additionally, the poster introduces (1) the HRP Data Integration Schedule identified in the HRP Data Management Plan HRP-48047, Table 8-2 and (2) a Smartsheet Solution to automate the grants tracking business process. Emphasis is given to the Data Integration Schedule which is the basis for the milestone tasks that are to be completed during the Post-Award phase in the grant lifecycle. The poster is also an opportunity to present the Smartsheet Solution, a software collaboration and work management tool used to assign tasks and track project progress. This PP&C FY24 effort will facilitate an end-to-end solution to track grants and provide insight to the health of HRP grant research procurements using metrics, reports, and dashboards.

J Peace↗
NASA NTRS1982

Analysis of in-trail following dynamics of CDTI-equipped aircraft

In connection with the necessity to provide greater terminal area capacity, attention is given to approaches in which the required increase in capacity will be obtained by making use of more automation and by involving the pilot to a larger degree in the air traffic control (ATC) process. It was recommended that NASA should make extensive use of its research aircraft and cockpit simulators to assist the FAA in examining the capabilities and limitations of cockpit displays of traffic information (CDTI). A program was organized which utilizes FAA ATC (ground-based) simulators and NASA aircraft and associated cockpit simulators in a research project which explores applications of the CDTI system. The present investigation is concerned with several questions related to the CDTI-based terminal area traffic tactical control concepts. Attention is given to longitudinal separation criteria, a longitudinal following model, longitudinal capture, combined longitudinal/vertical control, and lateral control.

Sorensen, J. A.↗
NASA NTRS1990

Technological advances for studying human behavior

Technological advances for studying human behavior are noted in viewgraph form. It is asserted that performance-aiding systems are proliferating without a fundamental understanding of how they would interact with the humans who must control them. Two views of automation research, the hardware view and the human-centered view, are listed. Other viewgraphs give information on vital elements for human-centered research, a continuum of the research process, available technologies, new technologies for persistent problems, a sample research infrastructure, the need for metrics, and examples of data-link technology.

Roske-Hofstrand, Renate J.↗
NASA NTRS2003

Supporting the Growing Needs of the GIS Industry

Visual Learning Systems, Inc. (VLS), of Missoula, Montana, has developed a commercial software application called Feature Analyst. Feature Analyst was conceived under a Small Business Innovation Research (SBIR) contract with NASA's Stennis Space Center, and through the Montana State University TechLink Center, an organization funded by NASA and the U.S. Department of Defense to link regional companies with Federal laboratories for joint research and technology transfer. The software provides a paradigm shift to automated feature extraction, as it utilizes spectral, spatial, temporal, and ancillary information to model the feature extraction process; presents the ability to remove clutter; incorporates advanced machine learning techniques to supply unparalleled levels of accuracy; and includes an exceedingly simple interface for feature extraction.

Source record↗
NASA NTRSDate not supplied

Manufacturing Trials of Integrally Stiffened Composite Panels Using Automated Fiber Placement

Commercial aircraft structures are frequently manufactured from carbon-epoxy materials because of their weight and stiffness advantages compared to metallic materials. Wing cover panels are regularly manufactured using an automated fiber placement (AFP) process, but current design and manufacturing methodologies do not fully take advantage of the opportunities afforded by AFP. Design and manufacturing studies were undertaken at the NASA Langley Research Center at the Integrated Structural Assembly of Advanced Composites (ISAAC) facility to quantify manufacturing benefits and limitations associated with AFP to create structurally efficient integral stiffeners as an alternative to bonded or mechanically fastened stiffeners. This methodology could save weight and remove failure mechanisms by reducing the need for rivets and bonding materials since the stiffener plies are interleaved within the skin plies. The use of AFP with integral stiffeners can open the design space, but a fundamental, systematic evaluation of manufacturing limitations is necessary. Manufacturing trials are described herein, where considered manufacturing variables included stiffener location, stiffener course staggering, stiffener widths, stiffener intersections, and material thicknesses for both the skin and stiffener plies. The manufacturing process and lessons learned from each trial are described, including the most successful current design which contains staggered stiffeners, non-traditional laminate angles, and a combination of multiple material thicknesses within the same laminate.

Automated Fiber Placement↗