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NASA NTRS1986

KBGIS-2: A knowledge-based geographic information system

The architecture and working of a recently implemented knowledge-based geographic information system (KBGIS-2) that was designed to satisfy several general criteria for the geographic information system are described. The system has four major functions that include query-answering, learning, and editing. The main query finds constrained locations for spatial objects that are describable in a predicate-calculus based spatial objects language. The main search procedures include a family of constraint-satisfaction procedures that use a spatial object knowledge base to search efficiently for complex spatial objects in large, multilayered spatial data bases. These data bases are represented in quadtree form. The search strategy is designed to reduce the computational cost of search in the average case. The learning capabilities of the system include the addition of new locations of complex spatial objects to the knowledge base as queries are answered, and the ability to learn inductively definitions of new spatial objects from examples. The new definitions are added to the knowledge base by the system. The system is currently performing all its designated tasks successfully, although currently implemented on inadequate hardware. Future reports will detail the performance characteristics of the system, and various new extensions are planned in order to enhance the power of KBGIS-2.

Smith, T.↗

NASA NTRS1987

Flow visualization of CFD using graphics workstations

High performance graphics workstations are used to visualize the fluid flow dynamics obtained from supercomputer solutions of computational fluid dynamic programs. The visualizations can be done independently on the workstation or while the workstation is connected to the supercomputer in a distributed computing mode. In the distributed mode, the supercomputer interactively performs the computationally intensive graphics rendering tasks while the workstation performs the viewing tasks. A major advantage of the workstations is that the viewers can interactively change their viewing position while watching the dynamics of the flow fields. An overview of the computer hardware and software required to create these displays is presented. For complex scenes the workstation cannot create the displays fast enough for good motion analysis. For these cases, the animation sequences are recorded on video tape or 16 mm film a frame at a time and played back at the desired speed. The additional software and hardware required to create these video tapes or 16 mm movies are also described. Photographs illustrating current visualization techniques are discussed. Examples of the use of the workstations for flow visualization through animation are available on video tape.

Lasinski, Thomas↗

NASA NTRS1993

Recent advances in computational structural reliability analysis methods

The goal of structural reliability analysis is to determine the probability that the structure will adequately perform its intended function when operating under the given environmental conditions. Thus, the notion of reliability admits the possibility of failure. Given the fact that many different modes of failure are usually possible, achievement of this goal is a formidable task, especially for large, complex structural systems. The traditional (deterministic) design methodology attempts to assure reliability by the application of safety factors and conservative assumptions. However, the safety factor approach lacks a quantitative basis in that the level of reliability is never known and usually results in overly conservative designs because of compounding conservatisms. Furthermore, problem parameters that control the reliability are not identified, nor their importance evaluated. A summary of recent advances in computational structural reliability assessment is presented. A significant level of activity in the research and development community was seen recently, much of which was directed towards the prediction of failure probabilities for single mode failures. The focus is to present some early results and demonstrations of advanced reliability methods applied to structural system problems. This includes structures that can fail as a result of multiple component failures (e.g., a redundant truss), or structural components that may fail due to multiple interacting failure modes (e.g., excessive deflection, resonate vibration, or creep rupture). From these results, some observations and recommendations are made with regard to future research needs.

Thacker, Ben H.↗

NASA NTRSDate not supplied

Systems Health Management and Prognostics Approaches for Electric Aircrafts

As more and more electric vehicles emerge in our daily operation progressively, a very critical challenge lies in the prediction of remaining driving flying time/distance for the flying vehicles. This information is important, particularly in the case of auto vehicles, because such vehicles can become self-aware, autonomously compute its own capabilities, and identify how to best plan and successfully complete vehicular missions safely. In case of electric aircrafts, computing the remaining flying time is also safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Latest achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision-making. A systematic prediction framework is implemented to identify all possible sources of uncertainty, quantify each of them individually, and mathematically estimate their combined effect on the system-level quantity of interest, in this case, the remaining flying time/distance of the unmanned aircraft. Note - This presentation contains all previously published information.

Systems Health Managent↗

NASA NTRSDate not supplied

Health Monitoring and Prognostics for Electric Aircrafts

Systems Health Managent↗

NASA NTRS1996

Cloud Classification in Polar and Desert Regions and Smoke Classification from Biomass Burning Using a Hierarchical Neural Network

This research focuses on a new neural network scene classification technique. The task is to identify scene elements in Advanced Very High Resolution Radiometry (AVHRR) data from three scene types: polar, desert and smoke from biomass burning in South America (smoke). The ultimate goal of this research is to design and implement a computer system which will identify the clouds present on a whole-Earth satellite view as a means of tracking global climate changes. Previous research has reported results for rule-based systems (Tovinkere et at 1992, 1993) for standard back propagation (Watters et at. 1993) and for a hierarchical approach (Corwin et al 1994) for polar data. This research uses a hierarchical neural network with don't care conditions and applies this technique to complex scenes. A hierarchical neural network consists of a switching network and a collection of leaf networks. The idea of the hierarchical neural network is that it is a simpler task to classify a certain pattern from a subset of patterns than it is to classify a pattern from the entire set. Therefore, the first task is to cluster the classes into groups. The switching, or decision network, performs an initial classification by selecting a leaf network. The leaf networks contain a reduced set of similar classes, and it is in the various leaf networks that the actual classification takes place. The grouping of classes in the various leaf networks is determined by applying an iterative clustering algorithm. Several clustering algorithms were investigated, but due to the size of the data sets, the exhaustive search algorithms were eliminated. A heuristic approach using a confusion matrix from a lightly trained neural network provided the basis for the clustering algorithm. Once the clusters have been identified, the hierarchical network can be trained. The approach of using don't care nodes results from the difficulty in generating extremely complex surfaces in order to separate one class from all of the others. This approach finds pairwise separating surfaces and forms the more complex separating surface from combinations of simpler surfaces. This technique both reduces training time and improves accuracy over the previously reported results. Accuracies of 97.47%, 95.70%, and 99.05% were achieved for the polar, desert and smoke data sets.

Alexander, June↗

NASA NTRS1988

Design guidelines for remotely maintainable equipment

The quantity and complexity of on-orbit assets will increase significantly over the next decade. Maintaining and servicing these costly assets represent a difficult challenge. Three general methods are proposed to maintain equipment while it is still in orbit: an extravehicular activity (EVA) crew can perform the task in an unpressurized maintenance area outside any space vehicle; an intravehicular activity (IVA) crew can perform the maintenance in a shirt sleeve environment, perhaps at a special maintenance work station in a space vehicle; or a telerobotic manipulator can perform the maintenance in an unpressurized maintenance area at a distance from the crew (who may be EVA, IVA, or on the ground). However, crew EVA may not always be possible; the crew may have other demands on their time that take precedence. In addition, the orbit of the tasks themselves may be impossible for crew entry. Also crew IVA may not always be possible as option for equipment maintenance. For example, the equipment may be too large to fit through the vehicle airlock. Therefore, in some circumstances, the third option, telerobotic manipulation, may be the only feasible option. Telerobotic manipulation has, therefore, an important role for on-orbit maintenance. It is not only used for the reasons outlined above, but also used in some cases as backup to the EVA crew in an orbit that they can reach.

Clarke, Margaret M.↗

NASA NTRS1991

Electronic map interpretation in a dual-task context

The present experiment was designed to assess the extent to which spatial and verbal-analytic (VA) information processing resources are used in performing a simulated aircraft navigation task. Subjects were required to decide whether a 'match' or a mismatch' existed between a schematic 3D perspective forward field of view and a 2D top-down map. On dual-task trials, this navigation task was concurrently performed with either a VA side-task or with one of two tracking tasks. The data suggest that a VA strategy was most likely to be used when stimuli were simple or were mismatches, whereas a spatial mental rotation strategy was apparently used to confirm complex match stimuli. These results indicate that it may be possible to specify conditions wherein navigation is likely to compete for resources critical to other cockpit activities, such as aircraft control and communication.

Williams, Henry P.↗

NASA NTRS1998

MoSi2-Base Hybrid Composite Passed Engine Test

The intermetallics compound molybdenum disilicide (MoSi2) is an attractive high-temperature structural material for advanced engine applications. It has excellent oxidation resistance, a high melting point, relatively low density, and high thermal conductivity, and it is easily machined. Past research'at the NASA Lewis Research Center has resulted in the development of a hybrid composite consisting of a MoSi2 matrix reinforced with silicon nitride (Si3N4) Particulate and silicon carbide (SiC) fibers. This composite has demonstrated attractive strength, toughness, thermal fatigue, and oxidation resistance, including resistance to "pest" oxidation. These properties attracted the interest of the Office of Naval Research and Pratt & Whitney, and a joint NASA/Navy/Pratt & Whitney effort was developed to continue to mature the MoSi2 Composite technology. A turbine blade outer air seal, which was part of the Integrated High Performance Turbine Engine Technology (IHPTET) program, was chosen as a first component on which to focus. The first tasks of the materials development effort were to develop improved processing methods to reduce costs and to use fine-diameter fibers that enable the manufacturing of complex shapes. Tape-casting methods were developed to fully infiltrate the fine SiC fibers with matrix powders. The resulting composites were hot pressed to 100-percent density. Composites with cross-plied fiber architectures with 30 vol. % hi-nicalon SiC fibers and 30 vol. % nitride particles are now made routinely and demonstrate a good balance of properties. The next task entailed the measurement of a wide variety of mechanical properties to confirm the suitability of this composite in engines. In particular, participants in this effort demonstrated that composites made with Hi-Nicalon fibers had strength and toughness properties equal to or better than those of the composites made with the large-diameter fibers that had been used previously. Another critically important property measured was impact resistance. Aircraft engine components require sufficient toughness to resist manufacturing defects, assembly damage, stress concentrations at notches, and foreign object damage. Engine company designers indicated that impact resistance would have to be measured before they would seriously consider these types of composites. The Charpy V-notch test was chosen to assess impact resistance, and both monolithic and composite versions Of MOSi2 were tested from -300 to 1400 C. The results (see the following graphs) show that nitride-particulate-reinforced MoSi2 exhibited impact resistance higher than that of many monolithic ceramics and intermetallics, and that the fiber-reinforced composites had even higher values, approaching that of cast superalloys.

Keith, Theo G., Jr.↗

NASA NTRS1998

Variable-Complexity Multidisciplinary Optimization on Parallel Computers

This report covers work conducted under grant NAG1-1562 for the NASA High Performance Computing and Communications Program (HPCCP) from December 7, 1993, to December 31, 1997. The objective of the research was to develop new multidisciplinary design optimization (MDO) techniques which exploit parallel computing to reduce the computational burden of aircraft MDO. The design of the High-Speed Civil Transport (HSCT) air-craft was selected as a test case to demonstrate the utility of our MDO methods. The three major tasks of this research grant included: development of parallel multipoint approximation methods for the aerodynamic design of the HSCT, use of parallel multipoint approximation methods for structural optimization of the HSCT, mathematical and algorithmic development including support in the integration of parallel computation for items (1) and (2). These tasks have been accomplished with the development of a response surface methodology that incorporates multi-fidelity models. For the aerodynamic design we were able to optimize with up to 20 design variables using hundreds of expensive Euler analyses together with thousands of inexpensive linear theory simulations. We have thereby demonstrated the application of CFD to a large aerodynamic design problem. For the predicting structural weight we were able to combine hundreds of structural optimizations of refined finite element models with thousands of optimizations based on coarse models. Computations have been carried out on the Intel Paragon with up to 128 nodes. The parallel computation allowed us to perform combined aerodynamic-structural optimization using state of the art models of a complex aircraft configurations.

Grossman, Bernard↗

NASA NTRS2014

Extravehicular Activity Asteroid Exploration and Sample Collection Capability

NASA's Asteroid Redirect Crewed Mission (ARCM) is challenged with primary mission objectives of demonstrating deep space Extravehicular Activity (EVA) and tools, and obtaining asteroid samples to return to Earth for further study. Although the Modified Advanced Crew Escape Suit (MACES) is used for the EVAs, it has limited mobility which increases fatigue and decreases the crews' capability to perform EVA tasks. Furthermore, previous Shuttle and International Space Station (ISS) spacewalks have benefited from EVA interfaces which have been designed and manufactured on Earth. Rigid structurally mounted handrails, and tools with customized interfaces and restraints optimize EVA performance. For ARCM, some vehicle interfaces and tools can leverage heritage designs and experience. However, when the crew ventures onto an asteroid capture bag to explore the asteroid and collect rock samples, EVA complexity increases due to the uncertainty of the asteroid properties. The variability of rock size, shape and composition, as well as bunching of the fabric bag will complicate EVA translation, tool restraint and body stabilization. The unknown asteroid hardness and brittleness will complicate tool use. The rock surface will introduce added safety concerns for cut gloves and debris control. Feasible solutions to meet ARCM EVA objectives were identified using experience gained during Apollo, Shuttle, and ISS EVAs, terrestrial mountaineering practices, NASA Extreme Environment Mission Operations (NEEMO) 16 mission, and during Neutral Buoyancy Laboratory testing in the MACES suit. The proposed concept utilizes expandable booms and integrated features of the asteroid capture bag to position and restrain the crew at the asteroid worksite. These methods enable the capability to perform both finesse, and high load tasks necessary to collect samples for scientific characterization of the asteroid. This paper will explore the design trade space and options that were examined for EVA, the overall concept for the EVAs including translation paths and body restraint methods, potential tools used to extract the samples, design implications for the Asteroid Redirect Vehicle (ARV) for EVA, the results of early development testing of potential EVA tasks, and extensibility of the EVA architecture to NASA's exploration missions.

Scoville, Zebulon↗

NASA NTRS1993

Computationally efficient algorithms for real-time attitude estimation

For many practical spacecraft applications, algorithms for determining spacecraft attitude must combine inputs from diverse sensors and provide redundancy in the event of sensor failure. A Kalman filter is suitable for this task, however, it may impose a computational burden which may be avoided by sub optimal methods. A suboptimal estimator is presented which was implemented successfully on the Delta Star spacecraft which performed a 9 month SDI flight experiment in 1989. This design sought to minimize algorithm complexity to accommodate the limitations of an 8K guidance computer. The algorithm used is interpreted in the framework of Kalman filtering and a derivation is given for the computation.

Pringle, Steven R.↗

NASA NTRS2005

Autonomic Cluster Management System (ACMS): A Demonstration of Autonomic Principles at Work

Cluster computing, whereby a large number of simple processors or nodes are combined together to apparently function as a single powerful computer, has emerged as a research area in its own right. The approach offers a relatively inexpensive means of achieving significant computational capabilities for high-performance computing applications, while simultaneously affording the ability to. increase that capability simply by adding more (inexpensive) processors. However, the task of manually managing and con.guring a cluster quickly becomes impossible as the cluster grows in size. Autonomic computing is a relatively new approach to managing complex systems that can potentially solve many of the problems inherent in cluster management. We describe the development of a prototype Automatic Cluster Management System (ACMS) that exploits autonomic properties in automating cluster management.

Baldassari, James D.↗

NASA NTRS1993

Rover imaging system for the Mars rover/sample return mission

In the past year, the conceptual design of a panoramic imager for the Mars Environmental Survey (MESUR) Pathfinder was finished. A prototype camera was built and its performace in the laboratory was tested. The performance of this camera was excellent. Based on this work, we have recently proposed a small, lightweight, rugged, and highly capable Mars Surface Imager (MSI) instrument for the MESUR Pathfinder mission. A key aspect of our approach to optimization of the MSI design is that we treat image gathering, coding, and restoration as a whole, rather than as separate and independent tasks. Our approach leads to higher image quality, especially in the representation of fine detail with good contrast and clarity, without increasing either the complexity of the camera or the amount of data transmission. We have made significant progress over the past year in both the overall MSI system design and in the detailed design of the MSI optics. We have taken a simple panoramic camera and have upgraded it substantially to become a prototype of the MSI flight instrument. The most recent version of the camera utilizes miniature wide-angle optics that image directly onto a 3-color, 2096-element CCD line array. There are several data-taking modes, providing resolution as high as 0.3 mrad/pixel. Analysis tasks that were performed or that are underway with the test data from the prototype camera include the following: construction of 3-D models of imaged scenes from stereo data, first for controlled scenes and later for field scenes; and checks on geometric fidelity, including alignment errors, mast vibration, and oscillation in the drive system. We have outlined a number of tasks planned for Fiscal Year '93 in order to prepare us for submission of a flight instrument proposal for MESUR Pathfinder.

Source record↗

NASA NTRS1997

Using Common Graphics Paradigms Implemented in a Java Applet to Represent Complex Scheduling Requirements

The experiments planned for the International Space Station promise to be complex, lengthy and diverse. The scarcity of the space station resources will cause significant competition for resources between experiments. The scheduling job facing the Space Station mission planning software requires a concise and comprehensive description of the experiments' requirements (to ensure a valid schedule) and a good description of the experiments' flexibility (to effectively utilize available resources). In addition, the continuous operation of the station, the wide geographic dispersion of station users, and the budgetary pressure to reduce operations manpower make a low-cost solution mandatory. A graphical representation of the scheduling requirements for station payloads implemented via an Internet-based application promises to be an elegant solution that addresses all of these issues. The graphical representation of experiment requirements permits a station user to describe his experiment by defining "activities" and "sequences of activities". Activities define the resource requirements (with alternatives) and other quantitative constraints of tasks to be performed. Activities definitions use an "outline" graphics paradigm. Sequences define the time relationships between activities. Sequences may also define time relationships with activities of other payloads or space station systems. Sequences of activities are described by a "network" graphics paradigm. The bulk of this paper will describe the graphical approach to representing requirements and provide examples that show the ease and clarity with which complex requirements can be represented. A Java applet, to run in a web browser, is being developed to support the graphical representation of payload scheduling requirements. Implementing the entry and editing of requirements via the web solves the problems introduced by the geographic dispersion of users. Reducing manpower is accomplished by developing a concise representation which eliminates the misunderstanding possible with verbose representations and which captures the complete requirements and flexibility of the experiments.

Jaap, John↗

NASA NTRS2020

Characterization of How CO2 Level May Impact Crew Performance Related to the HSIA Risk

Safety and mission critical anomalies are inevitable on NASA exploration missions. Delays and interruptions in communication with Earth-experts drives the requirement that crew resolve these anomalies on their own. The Human Factors and Behavioral Performance (HFBP) element of the NASA Human Research Program (HRP) recently stood-up the Human-System Integration Architecture (HSIA) risk. The specific risk statement is: “Given decreasing real-time ground support for execution of complex operations during future exploration missions, there is a possibility of adverse performance outcomes including that crew are unable to adequately respond to unanticipated critical malfunctions or detect safety critical procedural errors.” Reliable, on-board capabilities will need to support the crew - not only to resolve anomalies, but also to promote situation awareness (SA) and to reduce workload. Unfortunately, the present level of technological advancement limits the range of achievable intelligent support (Wu & Vera, 2019). The Human Capabilities Assessment for Autonomous Missions (HCAAM) projects were devised to identify how technology may benefit crew situation awareness and enhance crew trust in the intelligent systems. A suite of time-critical and complex exploration tasks have been identified (Holden et al., 2019) that may advance human-integration Concept of Operations (ConOps) development. This ConOps (a future HFBP directed task) along with standards and guidelines (Holden et al., 2019) may be used as the foundation for human-system requirements for a self-reliant crew. Spaceflight CO2 levels are elevated relative to terrestrial levels. Above 2.5 mmHg there is an increase in the incidence of crew headaches (Law et al., 2014) and Mission Control reports of mood and performance changes in the crew. The concern is that elevated CO2 effects may exacerbate the HSIA risk. Unfortunately, effects of higher concentrations of CO2 on performance decrements are not well established. The main goal of the current report is to identify how elevated CO2 impacts the HSIA risk. The approach taken is to trace the relationship between cognitive and motor abilities required for anomaly response with critical mission tasks and the level of technological advancement to support anomaly resolution to identify how elevated CO2 may impact the HSIA risk. The conclusion is that elevated CO2 could exacerbate the HSIA risk. Several research gaps are identified.

cognition↗

NASA NTRS1991

Evaluating robot procedures and tasks for the flight telerobotic servicer

NASA is developing space telerobotic systems to construct, service and maintain complex space hardware. These systems will be controlled by an astronaut operator in space. Preliminary mission procedures have been developed and typical task elements have been selected. The present study simulates some of these procedures, tasks and devices in the laboratory in order to obtain initial operator/robot system performance data.

Sauerwein, Timothy A.↗

NASA NTRS2005

BEAM Technology Flight Demonstration

As technologies advance, their growing complexity makes them harder to maintain. Detection methods for isolating and identifying impending problems are needed to balance this complexity. Through comparison of signal pairs from onboard sensors, the Beacon-based Exception Analysis For Multimissions (BEAM) algorithm can identify and help classify deviations in system operation from a data-trained statistical model. The goal of this task is to mature BEAM and validate its performance on a flying test bed. A series of F-18 flight demonstrations with BEAM monitoring engine parameters in real time was used to demonstrate in-the-field readiness. Captured F-18 and simulated F-18 engine data were used in model creation and training. The algorithm was then ported to the embedded system with a data buffering, file writing, and data-time-stamp monitoring shell to reduce the impact of embedded system faults on BEAM'S ability to correctly identify engine faults. Embedded system testing identified hardware related restrictions and contributed to iterative improvements in the code's runtime performance. The system was flown with forced engine flameouts and other pilot induced faults to simulate operation out of the norm. Successful detection of these faults, confirmed through post-flight data analysis, helped BEAM achieve TRL6.

Wang, David↗