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NASA NTRS2004

Virtual Sensors: Using Data Mining to Efficiently Estimate Spectra

Detecting clouds within a satellite image is essential for retrieving surface geophysical parameters, such as albedo and temperature, from optical and thermal imagery because the retrieval methods tend to be valid for clear skies only. Thus, routine satellite data processing requires reliable automated cloud detection algorithms that are applicable to many surface types. Unfortunately, cloud detection over snow and ice is difficult due to the lack of spectral contrast between clouds and snow. Snow and clouds are both highly reflective in the visible wavelen,ats and often show little contrast in the thermal Infrared. However, at 1.6 microns, the spectral signatures of snow and clouds differ enough to allow improved snow/ice/cloud discrimination. The recent Terra and Aqua Moderate Resolution Imaging Spectro-Radiometer (MODIS) sensors have a channel (channel 6) at 1.6 microns. Presently the most comprehensive, long-term information on surface albedo and temperature over snow- and ice-covered surfaces comes from the Advanced Very High Resolution Radiometer ( AVHRR) sensor that has been providing imagery since July 1981. The earlier AVHRR sensors (e.g. AVHRR/2) did not however have a channel designed for discriminating clouds from snow, such as the 1.6 micron channel available on the more recent AVHRR/3 or the MODIS sensors. In the absence of the 1.6 micron channel, the AVHRR Polar Pathfinder (APP) product performs cloud detection using a combination of time-series analysis and multispectral threshold tests based on the satellite's measuring channels to produce a cloud mask. The method has been found to work reasonably well over sea ice, but not so well over the ice sheets. Thus, improving the cloud mask in the APP dataset would be extremely helpful toward increasing the accuracy of the albedo and temperature retrievals, as well as extending the time-series of albedo and temperature retrievals from the more recent sensors to the historical ones. In this work, we use data mining methods to construct a model of MODIS channel 6 as a function of other channels that are common to both MODIS and AVHRR. The idea is to use the model to generate the equivalent of MODIS channel 6 for AVHRR as a function of the AVHRR equivalents to MODIS channels. We call this a Virtual Sensor because it predicts unmeasured spectra. The goal is to use this virtual channel 6. to yield a cloud mask superior to what is currently used in APP . Our results show that several data mining methods such as multilayer perceptrons (MLPs), ensemble methods (e.g., bagging), and kernel methods (e.g., support vector machines) generate channel 6 for unseen MODIS images with high accuracy. Because the true channel 6 is not available for AVHRR images, we qualitatively assess the virtual channel 6 for several AVHRR images.

Srivastava, Ashok↗
NASA NTRS1999

Development of Fuzzy Logic and Soft Computing Methodologies

Our earlier research on computing with words (CW) has led to a new direction in fuzzy logic which points to a major enlargement of the role of natural languages in information processing, decision analysis and control. This direction is based on the methodology of computing with words and embodies a new theory which is referred to as the computational theory of perceptions (CTP). An important feature of this theory is that it can be added to any existing theory - especially to probability theory, decision analysis, and control - and enhance the ability of the theory to deal with real-world problems in which the decision-relevant information is a mixture of measurements and perceptions. The new direction is centered on an old concept - the concept of a perception - a concept which plays a central role in human cognition. The ability to reason with perceptions perceptions of time, distance, force, direction, shape, intent, likelihood, truth and other attributes of physical and mental objects - underlies the remarkable human capability to perform a wide variety of physical and mental tasks without any measurements and any computations. Everyday examples of such tasks are parking a car, driving in city traffic, cooking a meal, playing golf and summarizing a story. Perceptions are intrinsically imprecise. Imprecision of perceptions reflects the finite ability of sensory organs and ultimately, the brain, to resolve detail and store information. More concretely, perceptions are both fuzzy and granular, or, for short, f-granular. Perceptions are f-granular in the sense that: (a) the boundaries of perceived classes are not sharply defined; and (b) the elements of classes are grouped into granules, with a granule being a clump of elements drawn together by indistinguishability, similarity. proximity or functionality. F-granularity of perceptions may be viewed as a human way of achieving data compression. In large measure, scientific progress has been, and continues to be, driven by a quest to progress from perceptions to measurements. Pursuit of this aim has led to brilliant successes. But alongside the successes stand problems whose solutions are not in sight. Representative of such problems is the problem of automation of driving in city traffic. In this case, as in many others, what can be done with ease by humans - without any measurements and a computations - is an intractable task for machines.

Zadeh, L. A.↗
NASA NTRS1990

Real-time data system: Incorporating new technology in mission critical environments

If the Space Station Freedom is to remain viable over its 30-year life span, it must be able to incorporate new information systems technologies. These technologies are necessary to enhance mission effectiveness and to enable new NASA missions, such as supporting the Lunar-Mars Initiative. Hi-definition television (HDTV), neural nets, model-based reasoning, advanced languages, CPU designs, and computer networking standards are areas which have been forecasted to make major strides in the next 30 years. A major challenge to NASA is to bring these technologies online without compromising mission safety. In past programs, NASA managers have been understandably reluctant to rely on new technologies for mission critical activities until they are proven in noncritical areas. NASA must develop strategies to allow inflight confidence building and migration of technologies into the trusted tool base. NASA has successfully met this challenge and developed a winning strategy in the Space Shuttle Mission Control Center. This facility, which is clearly among NASA's most critical, is based on 1970's mainframe architecture. Changes to the mainframe are very expensive due to the extensive testing required to prove that changes do not have unanticipated impact on critical processes. Systematic improvement efforts in this facility have been delayed due to this 'risk to change.' In the real-time data system (RTDS) we have introduced a network of engineering computer workstations which run in parallel to the mainframe system. These workstations are located next to flight controller operating positions in mission control and, in some cases, the display units are mounted in the traditional mainframe consoles. This system incorporates several major improvements over the mainframe consoles including automated fault detection by real-time expert systems and color graphic animated schematics of subsystems driven by real-time telemetry. The workstations have the capability of recording telemetry data and providing 'instant replay' for flight controllers. RTDS also provides unique graphics animated by real-time telemetry such as workstation emulation of the shuttle's flight instruments and displays of the remote manipulator system (RMS) position. These systems have been used successfully as prime operational tools since STS-26 and have supported seven shuttle missions.

Muratore, John F.↗
NASA NTRS1991

Systematic methods for knowledge acquisition and expert system development

Nine cooperating rule-based systems, collectively called AUTOCREW which were designed to automate functions and decisions associated with a combat aircraft's subsystems, are discussed. 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. Simulation and comparative workload results for two mission scenarios are given. The scenarios are inbound surface-to-air-missile attack on the aircraft and pilot incapacitation. The methodology used to develop the AUTOCREW knowledge bases is summarized. Issues involved in designing the navigation sensor selection expert in AUTOCREW's NAVIGATOR knowledge base are discussed in detail. The performance of seven navigation systems aiding a medium-accuracy INS was investigated using Kalman filter covariance analyses. A navigation sensor management (NSM) expert system was formulated from covariance simulation data using the analysis of variance (ANOVA) method and the ID3 algorithm. ANOVA results show that statistically different position accuracies are obtained when different navaids are used, the number of navaids aiding the INS is varied, the aircraft's trajectory is varied, and the performance history is varied. The ID3 algorithm determines the NSM expert's classification rules in the form of decision trees. The performance of these decision trees was assessed on two arbitrary trajectories, and the results demonstrate that the NSM expert adapts to new situations and provides reasonable estimates of the expected hybrid performance.

Belkin, Brenda L.↗
NASA NTRS2005

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

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

Paris, Deidre E.↗
NASA NTRS2005

Intelligent Vehicle Health Management

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

Paris, Deidre E.↗
NASA NTRS2005

IVHM Framework for Intelligent Integration for Vehicle Health Management

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

Paris, Deidre↗
NASA NTRS2004

Automated Classification of ROSAT Sources Using Heterogeneous Multiwavelength Source Catalogs

We describe an on-line system for automated classification of X-ray sources, ClassX, and present preliminary results of classification of the three major catalogs of ROSAT sources, RASS BSC, RASS FSC, and WGACAT, into six class categories: stars, white dwarfs, X-ray binaries, galaxies, AGNs, and clusters of galaxies. ClassX is based on a machine learning technology. It represents a system of classifiers, each classifier consisting of a considerable number of oblique decision trees. These trees are built as the classifier is 'trained' to recognize various classes of objects using a training sample of sources of known object types. Each source is characterized by a preselected set of parameters, or attributes; the same set is then used as the classifier conducts classification of sources of unknown identity. The ClassX pipeline features an automatic search for X-ray source counterparts among heterogeneous data sets in on-line data archives using Virtual Observatory protocols; it retrieves from those archives all the attributes required by the selected classifier and inputs them to the classifier. The user input to ClassX is typically a file with target coordinates, optionally complemented with target IDs. The output contains the class name, attributes, and class probabilities for all classified targets. We discuss ways to characterize and assess the classifier quality and performance and present the respective validation procedures. Based on both internal and external validation, we conclude that the ClassX classifiers yield reasonable and reliable classifications for ROSAT sources and have the potential to broaden class representation significantly for rare object types.

McGlynn, Thomas↗
NASA NTRS2003

High-Performance Acousto-Ultrasonic Scan System Being Developed

Acousto-ultrasonic (AU) interrogation is a single-sided nondestructive evaluation (NDE) technique employing separated sending and receiving transducers. It is used for assessing the microstructural condition and distributed damage state of the material between the transducers. AU is complementary to more traditional NDE methods, such as ultrasonic cscan, x-ray radiography, and thermographic inspection, which tend to be used primarily for discrete flaw detection. Throughout its history, AU has been used to inspect polymer matrix composites, metal matrix composites, ceramic matrix composites, and even monolithic metallic materials. The development of a high-performance automated AU scan system for characterizing within-sample microstructural and property homogeneity is currently in a prototype stage at NASA. This year, essential AU technology was reviewed. In addition, the basic hardware and software configuration for the scanner was developed, and preliminary results with the system were described. Mechanical and environmental loads applied to composite materials can cause distributed damage (as well as discrete defects) that plays a significant role in the degradation of physical properties. Such damage includes fiber/matrix debonding (interface failure), matrix microcracking, and fiber fracture and buckling. Investigations at the NASA Glenn Research Center have shown that traditional NDE scan inspection methods such as ultrasonic c-scan, x-ray imaging, and thermographic imaging tend to be more suited to discrete defect detection rather than the characterization of accumulated distributed microdamage in composites. Since AU is focused on assessing the distributed microdamage state of the material in between the sending and receiving transducers, it has proven to be quite suitable for assessing the relative composite material state. One major success story at Glenn with AU measurements has been the correlation between the ultrasonic decay rate obtained during AU inspection and the mechanical modulus (stiffness) seen during fatigue experiments with silicon carbide/silicon carbide (SiC/SiC) ceramic matrix composite samples. As shown in the figure, ultrasonic decay increased as the modulus decreased for the ceramic matrix composite tensile fatigue samples. The likely microstructural reason for the decrease in modulus (and increase in ultrasonic decay) is the matrix microcracking that commonly occurs during fatigue testing of these materials. Ultrasonic decay has shown the capability to track the pattern of transverse cracking and fiber breakage in these composites.

Roth, Don J.↗
NASA NTRSDate not supplied

In-Space Inspection Needs: Opportunities for advanced NDE tools such as x-ray CT for additively manufactured parts, in-situ resource utilization, geological applications, and more

It is now 50 years since the first human presence on the surface of the Moon and as we strive to return with women and men in the next few years, we embrace new technical challenges, goals, and innovative solutions to address 21st century objectives. These new ambitions carry fresh challenges and risks, with the field of NDE playing an increasingly more relevant role towards meeting these essential goals. In recent years, more advanced NDE tools have triggered a rapid expansion of applications for the space industry. In particular, x-ray Computed Tomography (CT) has proven to be a trusted and powerful asset for spaceflight hardware inspection, as well as applied geotechnical analysis for natural materials (e.g., rocks, soils) for NASA and across industry. However, such methods have yet to be extended to “deep space” applications such as those that are now part of the US National Space Policy Directive (SPD-1) and the accelerated push to return humans to the Moon (i.e., Artemis). For this reason, advancing these powerful Earth-based laboratory methods via new technologies, integrated computational solutions, and creative engineering approaches is directly aligned with national space policies, as well as with multiple NASA Strategic Plan priorities. The use of x-ray CT at scales as fine as a few microns or smaller can identify spacecraft part failure modes relevant to quality assurance for flight hardware and AM parts such as those recently developed for ISS. This technology could also identify valuable metallic phases within geological materials (i.e., rocks or drill cores), enabling resource-relevant triage of samples for In-Situ Resource Utilization (ISRU) and high science value sample return to Earth laboratories. There is also significant application for 3D imaging tools for medical use such as inspecting protective gear as well as bone density degradation studies which are critical in establishing a sustained presence in space. Timing for development of these tools for space use is advantageous as we prepare for new opportunities in the next few years and recognize recent commercial technology advancements which make it feasible. Moreover, as NASA strives to take full advantage of developments in AM technologies, including In-Space Manufacturing (ISM), it is widely recognized that NDE tools such as CT will play an essential role in acceptance of these parts for widespread use. New in-space 3D inspection tools with complimentary technology such as AI-based automated feature recognition (accelerated by machine learning), rapid compositional analysis, and advanced sample manipulation, would be a game-changing step toward a new class of crew-based laboratory sensors once human outposts on the Moon are established.

In-Space Non-Destructive Evaluation↗
NASA NTRS2003

High-Performance Acousto-Ultrasonic Scan System Being Developed

Acousto-ultrasonic (AU) interrogation is a single-sided nondestructive evaluation (NDE) technique employing separated sending and receiving transducers. It is used for assessing the microstructural condition and distributed damage state of the material between the transducers. AU is complementary to more traditional NDE methods, such as ultrasonic cscan, x-ray radiography, and thermographic inspection, which tend to be used primarily for discrete flaw detection. Throughout its history, AU has been used to inspect polymer matrix composites, metal matrix composites, ceramic matrix composites, and even monolithic metallic materials. The development of a high-performance automated AU scan system for characterizing within-sample microstructural and property homogeneity is currently in a prototype stage at NASA. This year, essential AU technology was reviewed. In addition, the basic hardware and software configuration for the scanner was developed, and preliminary results with the system were described. Mechanical and environmental loads applied to composite materials can cause distributed damage (as well as discrete defects) that plays a significant role in the degradation of physical properties. Such damage includes fiber/matrix debonding (interface failure), matrix microcracking, and fiber fracture and buckling. Investigations at the NASA Glenn Research Center have shown that traditional NDE scan inspection methods such as ultrasonic c-scan, x-ray imaging, and thermographic imaging tend to be more suited to discrete defect detection rather than the characterization of accumulated distributed micro-damage in composites. Since AU is focused on assessing the distributed micro-damage state of the material in between the sending and receiving transducers, it has proven to be quite suitable for assessing the relative composite material state. One major success story at Glenn with AU measurements has been the correlation between the ultrasonic decay rate obtained during AU inspection and the mechanical modulus (stiffness) seen during fatigue experiments with silicon carbide/silicon carbide (SiC/SiC) ceramic matrix composite samples. As shown in the figure, ultrasonic decay increased as the modulus decreased for the ceramic matrix composite tensile fatigue samples. The likely microstructural reason for the decrease in modulus (and increase in ultrasonic decay) is the matrix microcracking that commonly occurs during fatigue testing of these materials. Ultrasonic decay has shown the capability to track the pattern of transverse cracking and fiber breakage in these composites.

Roth, Don J.↗
NASA NTRS2010

Efficient Web Services Policy Combination

Large-scale Web security systems usually involve cooperation between domains with non-identical policies. The network management and Web communication software used by the different organizations presents a stumbling block. Many of the tools used by the various divisions do not have the ability to communicate network management data with each other. At best, this means that manual human intervention into the communication protocols used at various network routers and endpoints is required. Developing practical, sound, and automated ways to compose policies to bridge these differences is a long-standing problem. One of the key subtleties is the need to deal with inconsistencies and defaults where one organization proposes a rule on a particular feature, and another has a different rule or expresses no rule. A general approach is to assign priorities to rules and observe the rules with the highest priorities when there are conflicts. The present methods have inherent inefficiency, which heavily restrict their practical applications. A new, efficient algorithm combines policies utilized for Web services. The method is based on an algorithm that allows an automatic and scalable composition of security policies between multiple organizations. It is based on defeasible policy composition, a promising approach for finding conflicts and resolving priorities between rules. In the general case, policy negotiation is an intractable problem. A promising method, suggested in the literature, is when policies are represented in defeasible logic, and composition is based on rules for non-monotonic inference. In this system, policy writers construct metapolicies describing both the policy that they wish to enforce and annotations describing their composition preferences. These annotations can indicate whether certain policy assertions are required by the policy writer or, if not, under what circumstances the policy writer is willing to compromise and allow other assertions to take precedence. Meta-policies are specified in defeasible logic, a computationally efficient non-monotonic logic developed to model human reasoning. One drawback of this method is that at one point the algorithm starts an exhaustive search of all subsets of the set of conclusions of a defeasible theory. Although the propositional defeasible logic has linear complexity, the set of conclusions here may be large, especially in real-life practical cases. This phenomenon leads to an inefficient exponential explosion of complexity. The current process of getting a Web security policy from combination of two meta-policies consists of two steps. The first is generating a new meta-policy that is a composition of the input meta-policies, and the second is mapping the meta-policy onto a security policy. The new algorithm avoids the exhaustive search in the current algorithm, and provides a security policy that matches all requirements of the involved metapolicies.

Vatan, Farrokh↗
DOE OSTI2020

Design and Development of a Robotic Exoskeleton Device for use in Glove Boxes - 20374

Glovebox operators in nuclear facilities often operate under radioactive environment and typically perform monotonous, dull and repetitive work. This can result in muscle fatigue leading to increased levels of accidents. Current research work aims in assisting the glovebox operators by designing a novel upper limb exoskeleton device to reduce injuries and increase worker efficiency. Almost none of the commercially available hand and upper body exoskeletons are directly suitable for use in gloveboxes. This explains the novelty of the present work in developing a wearable powered robotic exoskeleton device. The device consists of electronics, motors and spring systems mounted on adjustable plates and is supported by a stationary frame behind the worker. The device is intended to be portable and adjustable according to the operator height. The elbow has a flexion movement assisted with motor control by way of a Bowden cable system. The system is floated on a spring and pulley combination that allows for extra safety and smoothness of operation. The end points are fixed near the pivot points to help minimize unwanted movement/torque. The extension movement of the upper and lower arm are assisted by gravity and a counter spring. The shoulder and upper arm movement are held in a neutral position with a spring system for counter balance allowing small movements within the glovebox. This initial concept considers only the vertical movement of the arm. The abduction and adduction movement will not be assisted or impeded by the over shoulder plate or at the forearm plate allowing for full range of motion. Several glovebox aspects such as the level of task assistance, ergonomic design, minimum hindrance in dexterity/operator movements and tear resistance for hazardous safety reasons will be considered in the design of the exoskeleton. Computer models will be simulated to test the load levels and stress conditions on the exoskeleton to enhance the designs. The exoskeleton focusses on major muscular involvement reduction through weight offset and active assistance with minimal parts and hence the device is derived with several joint links and contains both passive and active joints. The paper details the various stages in the design development and prototype testing of the exoskeleton device. Upon successful prototype device development, human testing will be conducted in a replica of the SRS-235F hot cell facility constructed at FIU-ARC. The final stage of the project will be potential testing/deployment of the exoskeleton device in one of the glovebox facilities in Savannah River Nuclear Waste site. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1992

Cognition and procedure representational requirements for predictive human performance models

Models and modeling environments for human performance are becoming significant contributors to early system design and analysis procedures. Issues of levels of automation, physical environment, informational environment, and manning requirements are being addressed by such man/machine analysis systems. The research reported here investigates the close interaction between models of human cognition and models that described procedural performance. We describe a methodology for the decomposition of aircrew procedures that supports interaction with models of cognition on the basis of procedures observed; that serves to identify cockpit/avionics information sources and crew information requirements; and that provides the structure to support methods for function allocation among crew and aiding systems. Our approach is to develop an object-oriented, modular, executable software representation of the aircrew, the aircraft, and the procedures necessary to satisfy flight-phase goals. We then encode in a time-based language, taxonomies of the conceptual, relational, and procedural constraints among the cockpit avionics and control system and the aircrew. We have designed and implemented a goals/procedures hierarchic representation sufficient to describe procedural flow in the cockpit. We then execute the procedural representation in simulation software and calculate the values of the flight instruments, aircraft state variables and crew resources using the constraints available from the relationship taxonomies. The system provides a flexible, extensible, manipulative and executable representation of aircrew and procedures that is generally applicable to crew/procedure task-analysis. The representation supports developed methods of intent inference, and is extensible to include issues of information requirements and functional allocation. We are attempting to link the procedural representation to models of cognitive functions to establish several intent inference methods including procedural backtracking with concurrent search, temporal reasoning, and constraint checking for partial ordering of procedures. Finally, the representation is being linked to models of human decision making processes that include heuristic, propositional and prescriptive judgement models that are sensitive to the procedural content in which the valuative functions are being performed.

Corker, K.↗
DOE OSTI2024

Accelerating polyketide synthase engineering for high TRY production of biofuels and bioproducts (Final Technical Report)

Polyketide synthase (PKS) enzymes have a modular, deterministic logic that holds the potential to act as a flexible chemical factory for the biological production of a huge diversity of valuable small molecule compounds. However, engineering a custom PKS to produce a specific desired product currently requires years of trial and error, for reasons that remain poorly understood. In this project, we have developed a rapid, high throughput, Design-Build-Test-Learn (DBTL) cycle for polyketide synthases (PKSs) and demonstrate its utility for production of materials precursors. The objectives are 1) to develop a rapid, high-throughput (HT) DBTL cycle for PKSs that will enable production of a large number of unnatural, organic molecules on demand at high titer, rate, and yield (TRY); 2) to demonstrate the utility of the PKS DBTL cycle to produce three molecules: one commodity chemical (caprolactam or valerolactam) and two novel materials precursors (caprolactam or valerolactam derivatives); and 3) to demonstrate the utility of the PKS DBTL cycle to increase the TRY of one molecule (caprolactam or valerolactam). In this project, we have successfully demonstrated our high throughput PKS DBTL pipeline, and have biologically produced valerolactam and several other novel nylon monomers.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2007

Hybrid Automated Diagnosis of Discrete/Continuous Systems

A recently conceived method of automated diagnosis of a complex electromechanical system affords a complete set of capabilities for hybrid diagnosis in the case in which the state of the electromechanical system is characterized by both continuous and discrete values (as represented by analog and digital signals, respectively). The method is an integration of two complementary diagnostic systems: (1) beacon-based exception analysis for multi-missions (BEAM), which is primarily useful in the continuous domain and easily performs diagnoses in the presence of transients; and (2) Livingstone, which is primarily useful in the discrete domain and is typically restricted to quasi-steady conditions. BEAM has been described in several prior NASA Tech Briefs articles: "Software for Autonomous Diagnosis of Complex Systems" (NPO-20803), Vol. 26, No. 3 (March 2002), page 33; "Beacon-Based Exception Analysis for Multimissions" (NPO-20827), Vol. 26, No. 9 (September 2002), page 32; "Wavelet-Based Real-Time Diagnosis of Complex Systems" (NPO-20830), Vol. 27, No. 1 (January 2003), page 67; and "Integrated Formulation of Beacon-Based Exception Analysis for Multimissions" (NPO-21126), Vol. 27, No. 3 (March 2003), page 74. Briefly, BEAM is a complete data-analysis method, implemented in software, for real-time or off-line detection and characterization of faults. The basic premise of BEAM is to characterize a system from all available observations and train the characterization with respect to normal phases of operation. The observations are primarily continuous in nature. BEAM isolates anomalies by analyzing the deviations from nominal for each phase of operation. Livingstone is a model-based reasoner that uses a model of a system, controller commands, and sensor observations to track the system s state, and detect and diagnose faults. Livingstone models a system within the discrete domain. Therefore, continuous sensor readings, as well as time, must be discretized. To reason about continuous systems, Livingstone uses monitors that discretize the sensor readings using trending and thresholding techniques. In development of the a hybrid method, BEAM results were sent to Livingstone to serve as an independent source of evidence that is in addition to the evidence gathered by Livingstone standard monitors. The figure depicts the flow of data in an early version of a hybrid system dedicated to diagnosing a simulated electromechanical system. In effect, BEAM served as a "smart" monitor for Livingstone. BEAM read the simulation data, processed the data to form observations, and stored the observations in a file. A monitor stub synchronized the events recorded by BEAM with the output of the Livingstone standard monitors according to time tags. This information was fed to a real-time interface, which buffered and fed the information to Livingstone, and requested diagnoses at the appropriate times. In a test, the hybrid system was found to correctly identify a failed component in an electromechanical system for which neither BEAM nor Livingstone alone yielded the correct diagnosis.

Park, Han↗
NASA NTRS2012

Leveraging Data Intensive Computing to Support Automated Event Services

A large portion of Earth Science investigations is phenomenon- or event-based, such as the studies of Rossby waves, mesoscale convective systems, and tropical cyclones. However, except for a few high-impact phenomena, e.g. tropical cyclones, comprehensive records are absent for the occurrences or events of these phenomena. Phenomenon-based studies therefore often focus on a few prominent cases while the lesser ones are overlooked. Without an automated means to gather the events, comprehensive investigation of a phenomenon is at least time-consuming if not impossible. An Earth Science event (ES event) is defined here as an episode of an Earth Science phenomenon. A cumulus cloud, a thunderstorm shower, a rogue wave, a tornado, an earthquake, a tsunami, a hurricane, or an EI Nino, is each an episode of a named ES phenomenon," and, from the small and insignificant to the large and potent, all are examples of ES events. An ES event has a finite duration and an associated geolocation as a function of time; its therefore an entity in four-dimensional . (4D) spatiotemporal space. The interests of Earth scientists typically rivet on Earth Science phenomena with potential to cause massive economic disruption or loss of life, but broader scientific curiosity also drives the study of phenomena that pose no immediate danger. We generally gain understanding of a given phenomenon by observing and studying individual events - usually beginning by identifying the occurrences of these events. Once representative events are identified or found, we must locate associated observed or simulated data prior to commencing analysis and concerted studies of the phenomenon. Knowledge concerning the phenomenon can accumulate only after analysis has started. However, except for a few high-impact phenomena. such as tropical cyclones and tornadoes, finding events and locating associated data currently may take a prohibitive amount of time and effort on the part of an individual investigator. And even for these high-impact phenomena, the availability of comprehensive records is still only a recent development. A major reason for the lack of comprehensive ,records for the majority of the ES phenomena is the perception that they do not pose immediate and/or severe threat to life and property and are thus not consistently tracked. monitored, and catalogued. Many phenomena even lack commonly accepted criteria for definitions. However. the lack of comprehensive records is also due to the increasingly prohibitive volume of observations and model data that must be examined. NASA Earth Observing System Data Information System (EOSDIS) alone archives several petabytes (PB) of satellite remote sensing data and steadily increases. All of these factors contribute to the difficulty of methodically identifying events corresponding to a given phenomenon and significantly impede systematic investigations. In the following we present a couple motivating scenarios, demonstrating the issues faced by Earth scientists studying ES phenomena.

Clune, Thomas L.↗
NASA NTRS1997

An Approach to Building a Traceability Tool for Software Development

It is difficult in a large, complex computer program to ensure that it meets the specified requirements. As the program evolves over time, a11 program constraints originally elicited during the requirements phase must be maintained. In addition, during the life cycle of the program, requirements typically change and the program must consistently reflect those changes. Imagine the following scenario. Company X wants to develop a system to automate its assembly line. With such a large system, there are many different stakeholders, e.g., managers, experts such as industrial and mechanical engineers, and end-users. Requirements would be elicited from all of the stake holders involved in the system with each stakeholder contributing their point of view to the requirements. For example, some of the requirements provided by an industrial engineer may concern the movement of parts through the assembly line. A point of view provided by the electrical engineer may be reflected in constraints concerning maximum power usage. End-users may be concerned with comfort and safety issues, whereas managers are concerned with the efficiency of the operation. With so many points of view affecting the requirements, it is difficult to manage them, communicate information to relevant stakeholders. and it is likely that conflicts in the requirements will arise. In the coding process, the implementors will make additional assumptions and interpretations on the design and the requirements of the system. During any stage of development, stakeholders may request that a requirement be added or changed. In such a dynamic environment, it is difficult to guarantee that the system will preserve the current set of requirements. Tracing, the mapping between objects in the artifacts of the system being developed, addresses this issue. Artifacts encompass documents such as the system definition, interview transcripts, memoranda, the software requirements specification, user's manuals, the functional specifications, design reports, and system code. Tracing helps 1) validate system features against, the requirement specification, 2) identify error sources and, most importantly, 3) manage change. With so many people involved in the development of the system, it becomes necessary to identify the reasons behind the design requirements or the implementation decisions. This paper is concerned with an approach that maps documents to constraints that capture properties of and relationships between the objects being modeled by the program. Section 2 provides the reader with a background on traceability tools. Section 3 gives a brief description of the context monitoring system on which the approach suggested in this paper is based. Section 4 presents an overview of our approach to providing traceability. The last section presents our future direction of research.

Delgado, Nelly↗