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All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Influence of structural and aerodynamic modeling on optimization with flutter constraint

The influences of structural and aerodynamic modeling on multidisciplinary optimization in an aeroelastic environment are not well understood. Therefore, optimizations with flutter and frequency constraints were performed to investigate the effects these modeling factors have on various representative wings. To this end, the Automated Structural Optimization System (ASTROS) was used as a tool to minimize the weight of various fully built-up finite element wing models in subsonic and supersonic flow under given flutter and frequency constraints. First, the performance of the optimization module was tested against results from other codes on a straight and uniform wing widely used for optimization with flutter constraints. Then, fully built-up finite element models of various wings with different aspect ratios were investigated for the influence on the structural optimization for minimum weight of the following modeling factors: finite element selection, structural grid refinement; number of selected modes, retention of breathing modes; selection of reduced frequencies to be used in flutter analysis; aerodynamic panel size and placement; splining of the aerodynamic grid to the structural grid selection of extra points of the structural wing box for splining; and number of constraints to be retained. Knowledge of these influences as well as of the program behavior is important, since optimization can be made more efficient by the selection of reasonable initial models. Also, it was shown previously that modeling has an impact on the results of modal and aeroelastic analyses. Thus, if modeling errors can negatively affect the analyses, a minimum weight optimization can be jeopardized and result in an optimal design that is rather unreliable. In the following, selected results are presented and the influences of some modeling parameters on optimization are pointed out.

Striz, Alfred G.↗
NASA NTRS1992

A vision architecture for the extravehicular activity retriever

The Extravehicular Activity Retriever (EVAR) is a robotic device currently being developed by the Automation and Robotics Division at the NASA Johnson Space Center to support activities in the neighborhood of the Space Shuttle or Space Station Freedom. As the name implies, the Retriever's primary function will be to provide the capability to retrieve tools, equipment or other objects which have become detached from the spacecraft, but it will also be able to rescue a crew member who may have become inadvertently de-tethered. Later goals will include cooperative operations between a crew member and the Retriever such as fetching a tool that is required for servicing or maintenance operations. This report documents a preliminary design for a Vision System Planner (VSP) for the EVAR that is capable of achieving visual objectives provided to it by a high level task planner. Typical commands which the task planner might issue to the VSP relate to object recognition, object location determination, and obstacle detection. Upon receiving a command from the task planner, the VSP then plans a sequence of actions to achieve the specified objective using a model-based reasoning approach. This sequence may involve choosing an appropriate sensor, selecting an algorithm to process the data, reorienting the sensor, adjusting the effective resolution of the image using lens zooming capability, and/or requesting the task planner to reposition the EVAR to obtain a different view of the object. An initial version of the Vision System Planner which realizes the above capabilities using simulated images has been implemented and tested. The remaining sections describe the architecture and capabilities of the VSP and its relationship to the high level task planner. In addition, typical plans that are generated to achieve visual goals for various scenarios will be discussed. Specific topics to be addressed will include object search strategies, repositioning of the EVAR to improve the quality of information obtained from the sensors, complementary usage of the sensors and redundant capabilities.

Magee, Michael↗
NASA NTRS2005

INDUCTIVE SYSTEM HEALTH MONITORING WITH STATISTICAL METRICS

Model-based reasoning is a powerful method for performing system monitoring and diagnosis. Building models for model-based reasoning is often a difficult and time consuming process. The Inductive Monitoring System (IMS) software was developed to provide a technique to automatically produce health monitoring knowledge bases for systems that are either difficult to model (simulate) with a computer or which require computer models that are too complex to use for real time monitoring. IMS processes nominal data sets collected either directly from the system or from simulations to build a knowledge base that can be used to detect anomalous behavior in the system. Machine learning and data mining techniques are used to characterize typical system behavior by extracting general classes of nominal data from archived data sets. In particular, a clustering algorithm forms groups of nominal values for sets of related parameters. This establishes constraints on those parameter values that should hold during nominal operation. During monitoring, IMS provides a statistically weighted measure of the deviation of current system behavior from the established normal baseline. If the deviation increases beyond the expected level, an anomaly is suspected, prompting further investigation by an operator or automated system. IMS has shown potential to be an effective, low cost technique to produce system monitoring capability for a variety of applications. We describe the training and system health monitoring techniques of IMS. We also present the application of IMS to a data set from the Space Shuttle Columbia STS-107 flight. IMS was able to detect an anomaly in the launch telemetry shortly after a foam impact damaged Columbia's thermal protection system.

Iverson, David L.↗
NASA NTRS2020

Planetary Defence Activities Beyond NASA and ESA

The collision of a significant asteroid or comet with Earth represents a singular natural disaster for a myriad of reasons, including: its extraterrestrial origin; the fact that it is perhaps the only natural disaster that is preventable in many cases, given sufficient preparation and warning; its scope, which ranges from damaging a city to an extinction-level event; and the duality of asteroids and comets themselves---they are grave potential threats, but are also tantalising scientific clues to our ancient past and resources with which we may one day build a prosperous spacefaring future. Accordingly, the problems of developing the means to interact with asteroids and comets for purposes of defence, scientific study, exploration, and resource utilisation have grown in importance over the past several decades. Since the 1980s, more and more asteroids and comets (especially the former) have been discovered, radically changing our picture of the solar system. At the beginning of the year 1980, approximately 9,000 asteroids were known to exist. By the beginning of 2001, that number had risen to approximately 125,000 thanks to the Earth-based telescopic survey efforts of the era, particularly the emergence of modern automated telescopic search systems, pioneered by the Massachusetts Institute of Technology’s (MIT’s) LINEAR system in the mid-to-late 1990s. Today, in late 2019, about 840,000 asteroids have been discovered, with more and more being found every week, month, and year. Of those, approximately 21,400 are categorised as near-Earth asteroids (NEAs), 2,000 of which are categorised as Potentially Hazardous Asteroids (PHAs) and 2,749 of which are categorised as potentially accessible. The hazards posed to us by asteroids affect people everywhere around the world. As well, the opportunities presented by asteroids may benefit our entire species. Thus, with such a large number of currently known asteroids and so many yet to be discovered, it is not surprising that individuals, organisations, institutions, and governments all around the world have become interested in the study of asteroids. Indeed, a variety of government space agencies, private organisations, and individuals have worked on developing the means by which to observe, study, and even interact with asteroids and comets for purposes including science, exploration, pioneering, commerce, and planetary defence. This includes significant individual contributions by amateur asteroid astronomers all over the world. International cooperation in planetary defence within the contexts of the United Nations and the International Asteroid Warning Network (IAWN) are discussed in Chapter 2, and the activities undertaken by the world’s larger space agencies, ESA and NASA, are discussed in Chapters 3 and 4. But, what of the other agencies and institutions around the world who are also working on the problem of defence against hazardous asteroids and comets, or related topics? In this chapter we provide an overview, in alphabetical order, of some of the planetary defence related efforts that have been undertaken around the world beyond the activities at the United Nations, NASA, and ESA.

Barbee, Brent W.↗
NASA NTRS1993

A vision system planner for increasing the autonomy of the Extravehicular Activity Helper/Retriever

The Extravehicular Activity Retriever (EVAR) is a robotic device currently being developed by the Automation and Robotics Division at the NASA Johnson Space Center to support activities in the neighborhood of the Space Shuttle or Space Station Freedom. As the name implies, the Retriever's primary function will be to provide the capability to retrieve tools and equipment or other objects which have become detached from the spacecraft, but it will also be able to rescue a crew member who may have become inadvertently de-tethered. Later goals will include cooperative operations between a crew member and the Retriever such as fetching a tool that is required for servicing or maintenance operations. This paper documents a preliminary design for a Vision System Planner (VSP) for the EVAR that is capable of achieving visual objectives provided to it by a high level task planner. Typical commands which the task planner might issue to the VSP relate to object recognition, object location determination, and obstacle detection. Upon receiving a command from the task planner, the VSP then plans a sequence of actions to achieve the specified objective using a model-based reasoning approach. This sequence may involve choosing an appropriate sensor, selecting an algorithm to process the data, reorienting the sensor, adjusting the effective resolution of the image using lens zooming capability, and/or requesting the task planner to reposition the EVAR to obtain a different view of the object. An initial version of the Vision System Planner which realizes the above capabilities using simulated images has been implemented and tested. The remaining sections describe the architecture and capabilities of the VSP and its relationship to the high level task planner. In addition, typical plans that are generated to achieve visual goals for various scenarios are discussed. Specific topics to be addressed will include object search strategies, repositioning of the EVAR to improve the quality of information obtained from the sensors, and complementary usage of the sensors and redundant capabilities.

Magee, Michael↗
NASA NTRS2024

A Multi‐Probe Automated Classification of Ice Crystal Habits During the IMPACTS Campaign

Although all ice crystals are unique, many can be grouped together by shape or habit, with members of a habit class sharing similar representations of properties such as fall velocity and growth rate. A decision tree algorithm designed to be adaptable to any particle imaging probe, thus enabling the creation of habit size distributions over a size range larger than that of any probe on its own, is used to classify ice crystals imaged by three airborne cloud probes in mid-latitude winter cyclones during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign. Crystals are sorted into seven habit classes based on their morphological properties: sphere, column/needle, plate, graupel, dendrite, aggregate, and irregular. Although adaptability was its primary goal, the algorithm was found to be moderately skillful for identifying idealized habit images. Quantitative tests of the algorithm’s adaptability displayed mixed results, as Two-Dimensional Stereo Probe (2DS) classifications showed moderate correlation with Particle Habit Imaging and Polar Scattering Probe (PHIPS) classifications, but only weak correlation with High Volume Precipitation Spectrometer (HVPS) classifications. The algorithm was applied to random sets of images from each probe in a case study of a mesoscale snow band sampled on 7 February 2020. In the case study, qualitative analysis of particle images revealed general agreement on classifications among the probes, supporting the algorithm’s applicability to multiple cloud probes. Most classifications appeared correct upon manual inspection, suggesting that in practical use, the algorithm is reasonably able to classify non-idealized images.

Julian Schima↗
NASA NTRSDate not supplied

Recent Improvements and Verification of A Full Body Model in Opensim

BACKGROUND: The dynamic feasibility [1,2] criterion, that the subject’s Center of Pressure (COP) be located within the Base of Support (BOS) which outlines the feet, has aided in assessing the stability of human motion recorded on earth while performing the recorded tasks in lunar gravity or as countermeasures exercises on a vibration isolation and stabilization system in microgravity. The convex hull of the BOS on the platform under the subject’s feet was estimated using virtual markers on the feet of the scaled subject model. The COP was calculated using the ground reaction forces and moments determined from motion capture data with biomechanical modeling tools [3]. Occasionally, large-amplitude oscillatory spikes or “artifacts” were observed in the subject’s linear and angular momentum derivatives, affecting some COP data derived from motion capture. The purpose of this investigation was to assess and improve the accuracy of model scaling and BOS estimation as well as to determine the efficacy of model adjustments in mitigating artifacts influencing motion capture-derived ground reaction force and COP results. METHODS: To aid evaluation of proposed process and model updates, motion capture data were collected for two subjects during unit test and range of motion trials, lunar tasks, and countermeasures exercise motions. Markers were added to the full body Plug-in Gait marker set [4] during data collection. New markers were placed on the front, back, sides, and top of the head to improve scaling using distances between marker pairs. Medial elbow markers were added to stabilize the upper arm during OpenSim Inverse Kinematics (IK) [5]. Finally, markers were added on the outer edge of the heels and on the outside edges of the first and last toes on each foot. These additional foot markers were made available to test new automated foot scaling techniques and to calculate the error between the subject’s estimated and recorded BOS. The modified unscaled OpenSim Full Body Rajagopal Model [6,7] was adjusted using some previously investigated techniques [8] to mitigate rapid shifts in joint angles occurring during IK, as these were found to cause the spike artifacts observed in subsequent stages of analysis. Since OpenSim models use Euler angles and rotation sequences, the arm axes of rotation were adjusted, and the pelvis order of rotation was changed to minimize the likelihood of encountering “gimbal lock” during common human motion. The model clavicle, arm, elbow, wrist, pelvis, and ankle angle limits were adjusted to better accommodate the full human range of motion seen in exercise and lunar data. The shoulder joint center was calculated using a “pivoting” algorithm [9], and both shoulder joint center and upper arm markers were included during IK to provide additional shoulder stability on a case-by-case basis. The quality of IK results was assessed by three criteria: minimizing error between recorded motion capture markers and model markers, checking for reasonable rates of change in joint angles between fames (i.e., no IK artifacts), and ensuring the absence of spikes in the inertial forces and angular momentum derivatives calculated using a custom OpenSim plugin [10]. RESULTS: The additional markers placed on the subject during data collection allowed the head and feet to be scaled more accurately using distances between new marker pairs. Scaling with BOS markers placed on the subject and removing the limit on subtalar angle resulted in more accurate BOS determination. Unrealistically large changes in joint angles between frames could be reduced by including clavicle, sternum, and medial elbow markers during IK. In cases with large arm ranges of motion, results could be further improved by running IK using medial elbow and virtual shoulder joint center markers. Model adjustments significantly improved the IK results affecting COP calculation and increased the accuracy of BOS estimation.

C A Bell↗
NASA NTRS1995

Josephson frequency meter for millimeter and submillimeter wavelengths

Frequency measurements of electromagnetic oscillations of millimeter and submillimeter wavebands with frequency growth due to a number of reasons become more and more difficult. First, these frequencies are considered to be cutoffs for semiconductor converting devices and one has to use optical measurement methods instead of traditional ones with frequency transfer. Second, resonance measurement methods are characterized by using relatively narrow bands and optical ones are limited in frequency and time resolution due to the limited range and velocity of movement of their mechanical elements as well as the efficiency of these optical techniques decrease with the increase of wavelength due to diffraction losses. That requires a priori information on the radiation frequency band of the source involved. Method of measuring frequency of harmonic microwave signals in millimeter and submillimeter wavebands based on the ac Josephson effect in superconducting contacts is devoid of all the above drawbacks. This approach offers a number of major advantages over the more traditional measurement methods, that is one based on frequency conversion, resonance and interferometric techniques. It can be characterized by high potential accuracy, wide range of frequencies measured, prompt measurement and the opportunity to obtain a panoramic display of the results as well as full automation of the measuring process.

Anischenko, S. E.↗
NASA NTRS1991

A strongly goal-directed close-range vision system for spacecraft docking

In this presentation, we will propose a strongly goal-oriented stereo vision system to establish proper docking approach motions for automated rendezvous and capture (AR&C). From an input sequence of stereo video image pairs, the system produces a current best estimate of: contact position; contact vector; contact velocity; and contact orientation. The processing demands imposed by this particular problem and its environment dictate a special case solution; such a system should necessarily be, in some sense, minimalist. By this we mean the system should construct a scene description just sufficiently rich to solve the problem at hand and should do no more processing than is absolutely necessary. In addition, the imaging resolution should be just sufficient. Extracting additional information and constructing higher level scene representations wastes energy and computational resources and injects an unnecessary degree of complexity, increasing the likelihood of malfunction. We therefore take a departure from most prior stereopsis work, including our own, and propose a system based on associative memory. The purpose of the memory is to immediately associate a set of motor commands with a set of input visual patterns in the two cameras. That is, rather than explicitly computing point correspondences and object positions in world coordinates and trying to reason forward from this information to a plan of action, we are trying to capture the essence of reflex behavior through the action of associative memory. The explicit construction of point correspondences and 3D scene descriptions, followed by online velocity and point of impact calculations, is prohibitively expensive from a computational point of view for the problem at hand. Learned patterns on the four image planes, left and right at two discrete but closely spaced instants in time, will be bused directly to infer the spacecraft reaction. This will be a continuing online process as the docking collar approaches.

Boyer, Kim L.↗
DOE OSTI2023

Moving-horizon false data injection attack design against cyber–physical systems

Systematic attack design is essential to understanding the vulnerabilities of cyber–physical systems (CPSs), to better design for resiliency. In particular, false data injection attacks (FDIAs) are well-known and have been shown to be capable of bypassing bad data detection (BDD) while causing targeted biases in resulting state estimates. However, their effectiveness against moving horizon estimators (MHE) is not well understood. In fact, this paper shows that conventional FDIAs are generally ineffective against MHE. One of the main reasons is that the moving window renders the static FDIA recursively infeasible. Here, this paper proposes a new attack methodology, moving-horizon FDIA (MH-FDIA), by considering both the performance of historical attacks and the current system’s status. Theoretical guarantees for successful attack generation and recursive feasibility are given. Numerical simulations on the IEEE-14 bus system further validate the theoretical claims and show that the proposed MH-FDIA outperforms state-of-the-art counterparts in both stealthiness and effectiveness. In addition, an experiment on a path-tracking control system of an autonomous vehicle shows the feasibility of the MH-FDIA in real-world nonlinear systems.

42 ENGINEERING↗
NASA NTRS2014

Multi-Source Autonomous Response for Targeting and Monitoring of Volcanic Activity

The study of volcanoes is important for both purely scientific and human survival reasons. From a scientific standpoint, volcanic gas and ash emissions contribute significantly to the terrestrial atmosphere. Ash depositions and lava flows can also greatly affect local environments. From a human survival standpoint, many people live within the reach of active volcanoes, and therefore can be endangered by both atmospheric (ash, debris) toxicity and lava flow. There are many potential information sources that can be used to determine how to best monitor volcanic activity worldwide. These are of varying temporal frequency, spatial regard, method of access, and reliability. The problem is how to incorporate all of these inputs in a general framework to assign/task/reconfigure assets to monitor events in a timely fashion. In situ sensing can provide a valuable range of complementary information such as seismographic, discharge, acoustic, and other data. However, many volcanoes are not instrumented with in situ sensors, and those that have sensor networks are restricted to a relatively small numbers of point sensors. Consequently, ideal volcanic study synergistically combines space and in situ measurements. This work demonstrates an effort to integrate spaceborne sensing from MODIS (Terra and Aqua), ALI (EO-1), Worldview-2, and in situ sensing in an automated scheme to improve global volcano monitoring. Specifically, it is a "sensor web" concept in which a number of volcano monitoring systems are linked together to monitor volcanic activity more accurately, and this activity measurement automatically tasks space assets to acquire further satellite imagery of ongoing volcanic activity. A general framework was developed for evidence combination that accounts for multiple information sources in a scientist-directed fashion to weigh inputs and allocate observations based on the confidence of an events occurrence, rarity of the event at that location, and other scientists' inputs. The software framework uses multiple source languages and is a general framework for combining inputs and incrementally submitting observation requests/reconfigurations, accounting for prior requests. The autonomous aspect of operations is unique, especially in the context of the wide range of inputs that includes manually inputted electronic reports (such as the Air Force Weather Advisories), automated satellite-based detection methods (such as MODVOLC and GOESVOLC), and in situ sensor networks.

Davies, Ashley G.↗
DOE OSTI2025

Digital Safety Analysis for Small Modular Nuclear Reactors (SMRs)

A Documented Safety Analysis (DSA) is a Department of Energy (DOE) construct that defines the extent to which a nuclear facility can be operated safely. It includes a description of hazards, safe boundaries, and hazard controls. The authors assert that a Digital Safety Analysis (DgSA) is far superior to a legacy DSA for several reasons: • The underling database is structured such that it is possible to perform a comprehensive design review and safety analysis by iterating systematically across a hierarchy of linked objects versus a redundant and spotty review by entities of various abilities under unknown resource and schedule constraints. • The analysis of a new design can discover elements that are similar to elements in previous designs. The discovery of similarities is made possible by using the same structure for the underlying database for each new DgSA. The “prior learning” from previous designs is then applied automatically to new designs. • Outputs from the DgSA are from a single source to ensure consistency among various views of the same information. After the DgSA is released, the continued use of a single source implements a configuration management program to ensure consistency between the design basis, the design, the built system, and system procedures. • The development of the DgSA is agile in that any change in a linked object triggers an analysis of impacts on other linked objects and updates of linked objects are made accordingly. After the DgSA is released, the continued maintenance of these links and objects automates the “unreviewed safety question” process.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Advances in Resin Management Using 3R-Scan - 20154

The most important factor underlying optimal waste management is developing a clear picture of the radioactivity content of the waste and its impact on waste disposal cost. For over 35 years since the publishing of 10CFR61, waste characterization has relied on sampling the final waste product after formation. In the days following 10CFR61, the cost of final disposal was marginal with only a small impact on the overall costs. Constraints were added by provisions of the Low Level Waste Policy Act of 1985 leading to increasingly limited access to those disposal sites that remained available. In addition, Nuclear Regulatory Commission (NRC) pressure promoting waste volume reduction led to disposal costs inevitably rising. Despite this, characterization practices in monitoring of waste generation for activity content still center on the same dated processes. This results in a disposal classification on the basis of endpoint sampling without consideration of the homogeneity of the waste mixture. It can also disregard consideration of the representativeness of the single or small sample base. As a minimum effort, a formalized sampling program of a fixed grouping of waste streams can be implemented that could account for more than 95% of all of the activity carried in solid waste products. The sample results for each radionuclide could then be trended as time passes to develop reasonable scaling factors for difficult to measure radionuclides. This process, identified in NRC guidance, has been rigorously followed by a relatively small number of facilities. The trended scaling factors serve to improve accuracy by identifying anomalous results that could otherwise go undetected. Direct monitoring of the accumulation of activity in process streams generating solid radwaste, including demineralizers and filter streams, is a more precise approach. Nearly all of these streams are monitored by plant chemistry on a regular schedule to maintain water quality. This paper discusses viable options for developing the basis for characterization through process monitoring of the accumulation of activity at the point of generation. Special focus is on resin bed tracking and how process knowledge of these streams can be brought together to form a consistent and precise solid waste radioactivity inventory. Some of the specific points covered in this paper include the merger of the fission product release computer program, 3R-STAT, with the radwaste sample analysis computer program, SCAN4 to create 3R-SCAN, the importance of individual waste stream influences on the overall source term, and the use of historic sample data to develop scaling factors using an automated process. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRSDate not supplied

Increasing Data Discovery and Re-Use: The Space Life Sciences Ontology

Two of the most important goals of the adoption of the FAIR principles are increasing the ability of agents to find and re-use research data. Achieving these goals for space life sciences research is even more pressing, given the relatively expensive and scarce nature of these data. We have reported in the past on the progress made by exemplar life sciences data systems towards implementing FAIR, showing gaps particularly in the “interoperability area” of the principles; the lack of common conceptual models for space life science research is one reason for this gap. There were few available resources that define, annotate, categorize or otherwise relate various kinds of metadata describing the acquisition, nature, and intent of investigational space life sciences data. To address this gap, NASA is working with the Open Biological and Biomedical Ontology Foundry (https://obofoundry.org/) to develop the Space Life Science Ontology (SLSO) that is intended to support archival and other kinds of systems that operate using these data. The scope of the ontology includes concepts regarding those aspects of investigation design and execution specific or unique to space environments, such as types of specialized equipment, operating organizations, and documentation. The ontology is continually being developed and published to the life science community (https://github.com/nasa/LSDAO/); at the time of this publication, the SLSO newly and uniquely defines 30 types (classes), 90 properties, and 14 relations specific to space life sciences metadata. In addition, the SLSO reuses (imports) some 2,360 types (classes), 49 properties, and 393 relations from other ontologies that are relevant to these kinds of metadata. In addition to its role as a common conceptualization for space biomedical research activities, the SLSO can also be used to provide automated support for traditionally difficult and expensive activities such as data curation and cross-system data integration and analysis.

fair↗
NASA NTRS1991

Systematic methods for knowledge acquisition and expert system development

Nine cooperating rule-based systems, collectively called AUTOCREW, were designed to automate functions and decisions associated with a combat aircraft's subsystem. The organization of tasks within each system is described; performance metrics were developed to evaluate the workload of each rule base, and to assess the cooperation between the rule-bases. Each AUTOCREW subsystem is composed of several expert systems that perform specific tasks. AUTOCREW's NAVIGATOR was analyzed in detail to understand the difficulties involved in designing the system and to identify tools and methodologies that ease development. The NAVIGATOR determines optimal navigation strategies from a set of available sensors. A Navigation Sensor Management (NSM) expert system was systematically designed from Kalman filter covariance data; four ground-based, a satellite-based, and two on-board INS-aiding sensors were modeled and simulated to aid an INS. The NSM Expert was developed using the Analysis of Variance (ANOVA) and the ID3 algorithm. Navigation strategy selection is based on an RSS position error decision metric, which is computed from the covariance data. Results show that the NSM Expert predicts position error correctly between 45 and 100 percent of the time for a specified navaid configuration and aircraft trajectory. The NSM Expert adapts to new situations, and provides reasonable estimates of hybrid performance. The systematic nature of the ANOVA/ID3 method makes it broadly applicable to expert system design when experimental or simulation data is available.

Belkin, Brenda L.↗
NASA NTRS1998

Exploration of the Moon with Remote Sensing, Ground-Penetrating Radar, and the Regolith-Evolved Gas Analyzer (REGA)

There are two important reasons to explore the Moon. First, we would like to know more about the Moon itself: its history, its geology, its chemistry, and its diversity. Second, we would like to apply this knowledge to a useful purpose. namely finding and using lunar resources. As a result of the recent Clementine and Lunar Prospector missions, we now have global data on the regional surface mineralogy of the Moon, and we have good reason to believe that water exists in the lunar polar regions. However, there is still very little information about the subsurface. If we wish to go to the lunar polar regions to extract water, or if we wish to go anywhere else on the Moon and extract (or learn) anything at all, we need information in three dimensions an understanding of what lies below the surface, both shallow and deep. The terrestrial mining industry provides an example of the logical steps that lead to an understanding of where resources are located and their economic significance. Surface maps are examined to determine likely locations for detailed study. Geochemical soil sample surveys, using broad or narrow grid patterns, are then used to gather additional data. Next, a detailed surface map is developed for a selected area, along with an interpretation of the subsurface structure that would give rise to the observed features. After that, further sampling and geophysical exploration are used to validate and refine the original interpretation, as well as to make further exploration/ mining decisions. Integrating remotely sensed, geophysical, and sample datasets gives the maximum likelihood of a correct interpretation of the subsurface geology and surface morphology. Apollo-era geophysical and automated sampling experiments sought to look beyond the upper few microns of the lunar surface. These experiments, including ground-penetrating radar and spectrometry, proved the usefulness of these methods for determining the best sites for lunar bases and lunar mining operations.

Cooper, B. L.↗
NASA NTRS1993

Storage system architectures and their characteristics

Not all users storage requirements call for 20 MBS data transfer rates, multi-tier file or data migration schemes, or even automated retrieval of data. The number of available storage solutions reflects the broad range of user requirements. It is foolish to think that any one solution can address the complete range of requirements. For users with simple off-line storage requirements, the cost and complexity of high end solutions would provide no advantage over a more simple solution. The correct answer is to match the requirements of a particular storage need to the various attributes of the available solutions. The goal of this paper is to introduce basic concepts of archiving and storage management in combination with the most common architectures and to provide some insight into how these concepts and architectures address various storage problems. The intent is to provide potential consumers of storage technology with a framework within which to begin the hunt for a solution which meets their particular needs. This paper is not intended to be an exhaustive study or to address all possible solutions or new technologies, but is intended to be a more practical treatment of todays storage system alternatives. Since most commercial storage systems today are built on Open Systems concepts, the majority of these solutions are hosted on the UNIX operating system. For this reason, some of the architectural issues discussed focus around specific UNIX architectural concepts. However, most of the architectures are operating system independent and the conclusions are applicable to such architectures on any operating system.

Sarandrea, Bryan M.↗
NASA NTRS1993

Nonlinear rescaling of control values simplifies fuzzy control

Traditional control theory is well-developed mainly for linear control situations. In non-linear cases there is no general method of generating a good control, so we have to rely on the ability of the experts (operators) to control them. If we want to automate their control, we must acquire their knowledge and translate it into a precise control strategy. The experts' knowledge is usually represented in non-numeric terms, namely, in terms of uncertain statements of the type 'if the obstacle is straight ahead, the distance to it is small, and the velocity of the car is medium, press the brakes hard'. Fuzzy control is a methodology that translates such statements into precise formulas for control. The necessary first step of this strategy consists of assigning membership functions to all the terms that the expert uses in his rules (in our sample phrase these words are 'small', 'medium', and 'hard'). The appropriate choice of a membership function can drastically improve the quality of a fuzzy control. In the simplest cases, we can take the functions whose domains have equally spaced endpoints. Because of that, many software packages for fuzzy control are based on this choice of membership functions. This choice is not very efficient in more complicated cases. Therefore, methods have been developed that use neural networks or generic algorithms to 'tune' membership functions. But this tuning takes lots of time (for example, several thousands iterations are typical for neural networks). In some cases there are evident physical reasons why equally space domains do not work: e.g., if the control variable u is always positive (i.e., if we control temperature in a reactor), then negative values (that are generated by equal spacing) simply make no sense. In this case it sounds reasonable to choose another scale u' = f(u) to represent u, so that equal spacing will work fine for u'. In the present paper we formulate the problem of finding the best rescaling function, solve this problem, and show (on a real-life example) that after an optimal rescaling, the un-tuned fuzzy control can be as good as the best state-of-art traditional non-linear controls.

Vanlangingham, H.↗