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At least 1,225 records · Page 68

Psychophysical Models for Signal Detection with Time Varying Uncertainty

Psychophysical models for the behavior of the human operator in detection tasks which include change in detectability, correlation between observations and deferred decisions are developed. Classical Signal Detection Theory (SDT) is discussed and its emphasis on the sensory processes is contrasted to decision strategies. The analysis of decision strategies utilizes detection tasks with time varying signal strength. The classical theory is modified to include such tasks and several optimal decision strategies are explored. Two methods of classifying strategies are suggested. The first method is similar to the analysis of ROC curves, while the second is based on the relation between the criterion level (CL) and the detectability. Experiments to verify the analysis of tasks with changes of signal strength are designed. The results show that subjects are aware of changes in detectability and tend to use strategies that involve changes in the CL's.

Gai, E.↗

An all-digital Manchester symbol synchronizer for Space Shuttle

The Shuttle S-Band relay communications links via TDRS are coded and may operate at symbol signal-to-noise ratios (Es/No) as low as -5dB. A brass-board all-digital bit synchronizer with very low (0.05dB) degradation relative to an idealized analog model has been designed to process the 216 KBPS Manchester data symbols. This all-digital bit synchronizer, which provides soft decision detected outputs to a convolutional decoder, may be operated at any rate below 216 KBPS by merely changing the master clock frequency.

Batson, B. H.↗

A study of course deviations during cross-country soaring

Several models are developed for studying the impact of deviations from course during cross country soaring flights. Analyses are performed at the microstrategy and macrostrategy levels. Two types of lift sources are considered: concentrated thermals and thermal streets. The sensitivity of the optimum speed solutions to various model, piloting and performance parameters is evaluated. Guides are presented to provide the pilot with criterions for making in-flight decisions. In general, course deviations are warranted during weak lift conditions, but are less justifiable with moderate to strong lift conditions.

Sliwa, S. M.↗

Advanced probabilistic method of development

Advanced structural reliability methods are utilized on the Probabilistic Structural Analysis Methods (PSAM) project to provide a tool for analysis and design of space propulsion system hardware. The role of the effort at the University of Arizona is to provide reliability technology support to this project. PSAM computer programs will provide a design tool for analyzing uncertainty associated with thermal and mechanical loading, material behavior, geometry, and the analysis methods used. Specifically, reliability methods are employed to perform sensitivity analyses, to establish the distribution of a critical response variable (e.g., stress, deflection), to perform reliability assessment, and ultimately to produce a design which will minimize cost and/or weight. Uncertainties in the design factors of space propulsion hardware are described by probability models constructed using statistical analysis of data. Statistical methods are employed to produce a probability model, i.e., a statistical synthesis or summary of each design variable in a format suitable for reliability analysis and ultimately, design decisions.

Wirsching, P. H.↗

DFVLR Roentgen satellite

The entire engineering model is being concluded in the shuttle configuration. The flight model components are extensively included in the shuttle configuration and will not be changed until after a binding Atlas/Centaur (A/C) booster decision for the A/C configuration. The urgent projects for the altering of the shuttle configuration on the A/C configuration must be carried out before a binding Atlas/Centaur booster decision is completed. All other modification projects are being delayed until the presentation of a binding booster decision.

Source record↗

Use of artificial intelligence in supervisory control

Viewgraphs describing the design and testing of an intelligent decision support system called OFMspert are presented. In this expert system, knowledge about the human operator is represented through an operator/system model referred to as the OFM (Operator Function Model). OFMspert uses the blackboard model of problem solving to maintain a dynamic representation of operator goals, plans, tasks, and actions given previous operator actions and current system state. Results of an experiment to assess OFMspert's intent inferencing capability are outlined. Finally, the overall design philosophy for an intelligent tutoring system (OFMTutor) for operators of complex dynamic systems is summarized.

Cohen, Aaron↗

An overview of the neuron ring model

The Neuron Ring model employs an avalanche structure with two important distinctions at the neuron level. Each neuron has two memory latches; one traps maximum neuronal activation during pattern presentation, and the other records the time of latch content change. The latches filter short term memory. In the process, they preserve length 1 snapshots of activation theory history. The model finds utility in pattern classification. Its synaptic weights are first conditioned with sample spectra. The model then receives a test or unknown signal. The objective is to identify the sample closest to the test signal. Class decision follows complete presentation of the test data. The decision maker relies exclusively on the latch contents. Presented here is an overview of the Neuron Ring at the seminar level.

Taber, Rod↗

A Petri-net coordination model for an intelligent mobile robot

The authors present a Petri net model of the coordination level of an intelligent mobile robot system (IMRS). The purpose of this model is to specify the integration of the individual efforts on path planning, supervisory motion control, and vision systems that are necessary for the autonomous operation of the mobile robot in a structured dynamic environment. This is achieved by analytically modeling the various units of the system as Petri net transducers and explicitly representing the task precedence and information dependence among them. The model can also be used to simulate the task processing and to evaluate the efficiency of operations and the responsibility of decisions in the coordination level of the IMRS. Some simulation results on the task processing and learning are presented.

Wang, F.-Y.↗

Recent experience with multidisciplinary analysis and optimization in advanced aircraft design

The task of modern aircraft design has always been complicated due to the number of intertwined technical factors from the various engineering disciplines. Furthermore, this complexity has been rapidly increasing by the development of such technologies as aeroelasticity tailored materials and structures, active control systems, integrated propulsion/airframe controls, thrust vectoring, and so on. Successful designs that achieve maximum advantage from these new technologies require a thorough understanding of the physical phenomena and the interactions among these phenomena. A study commissioned by the Aeronautical Sciences and Evaluation Board of the National Research Council has gone so far as to identify technology integration as a new discipline from which many future aeronautical advancements will arise. Regardless of whether one considers integration as a new discipline or not, it is clear to all engineers involved in aircraft design and analysis that better methods are required. In the past, designers conducted parametric studies in which a relatively small number of principal characteristics were varied to determine the effect on design requirements which were themselves often diverse and contradictory. Once a design was chosen, it then passed through the various engineers' disciplines whose principal task was to make the chosen design workable. Working in a limited design space, the discipline expert sometimes improved the concept, but more often than not, the result was in the form of a penalty to make the original concept workable. If an insurmountable problem was encountered, the process began over. Most design systems that attempt to account for disciplinary interactions have large empirical elements and reliance on past experience is a poor guide in obtaining maximum utilizations of new technologies. Further compounding the difficulty of design is that as the aeronautical sciences have matured, the discipline specialist's area of research has generally narrowed as more sophisticated methods are developed in the specialist's area of expertise. The results have been a decrease in the awareness of the impact of his decisions on other disciplines. This paper will outline the progress and problems encountered in the analysis, design, optimization sensitivity analysis, mathematical modeling, and configurations control and the means by which they are being solved. The breadth versus depth dilemma in analysis and design and the means for coping with that dilemma will be discussed. Finally, the all-important human aspects and the need for a new 'culture ' for doing business in an integrated, multidisciplinary design environment are discussed.

Dollyhigh, Samuel M.↗

Real-time robot deliberation by compilation and monitoring of anytime algorithms

Anytime algorithms are algorithms whose quality of results improves gradually as computation time increases. Certainty, accuracy, and specificity are metrics useful in anytime algorighm construction. It is widely accepted that a successful robotic system must trade off between decision quality and the computational resources used to produce it. Anytime algorithms were designed to offer such a trade off. A model of compilation and monitoring mechanisms needed to build robots that can efficiently control their deliberation time is presented. This approach simplifies the design and implementation of complex intelligent robots, mechanizes the composition and monitoring processes, and provides independent real time robotic systems that automatically adjust resource allocation to yield optimum performance.

Zilberstein, Shlomo↗

An Overview of Quantitative Risk Assessment of Space Shuttle Propulsion Elements

Since the Space Shuttle Challenger accident in 1986, NASA has been working to incorporate quantitative risk assessment (QRA) in decisions concerning the Space Shuttle and other NASA projects. One current major NASA QRA study is the creation of a risk model for the overall Space Shuttle system. The model is intended to provide a tool to estimate Space Shuttle risk and to perform sensitivity analyses/trade studies, including the evaluation of upgrades. Marshall Space Flight Center (MSFC) is a part of the NASA team conducting the QRA study; MSFC responsibility involves modeling the propulsion elements of the Space Shuttle, namely: the External Tank (ET), the Solid Rocket Booster (SRB), the Reusable Solid Rocket Motor (RSRM), and the Space Shuttle Main Engine (SSME). This paper discusses the approach that MSFC has used to model its Space Shuttle elements, including insights obtained from this experience in modeling large scale, highly complex systems with a varying availability of success/failure data. Insights, which are applicable to any QRA study, pertain to organizing the modeling effort, obtaining customer buy-in, preparing documentation, and using varied modeling methods and data sources. Also provided is an overall evaluation of the study results, including the strengths and the limitations of the MSFC QRA approach and of qRA technology in general.

Safie, Fayssal M.↗

Space Transportation Operations: Assessment of Methodologies and Models

The systems design process for future space transportation involves understanding multiple variables and their effect on lifecycle metrics. Variables such as technology readiness or potential environmental impact are qualitative, while variables such as reliability, operations costs or flight rates are quantitative. In deciding what new design concepts to fund, NASA needs a methodology that would assess the sum total of all relevant qualitative and quantitative lifecycle metrics resulting from each proposed concept. The objective of this research was to review the state of operations assessment methodologies and models used to evaluate proposed space transportation systems and to develop recommendations for improving them. It was found that, compared to the models available from other sources, the operations assessment methodology recently developed at Kennedy Space Center has the potential to produce a decision support tool that will serve as the industry standard. Towards that goal, a number of areas of improvement in the Kennedy Space Center's methodology are identified.

Joglekar, Prafulla↗

Space Transportation Operations: Assessment of Methodologies and Models

The systems design process for future space transportation involves understanding multiple variables and their effect on lifecycle metrics. Variables such as technology readiness or potential environmental impact are qualitative, while variables such as reliability, operations costs or flight rates are quantitative. In deciding what new design concepts to fund, NASA needs a methodology that would assess the sum total of all relevant qualitative and quantitative lifecycle metrics resulting from each proposed concept. The objective of this research was to review the state of operations assessment methodologies and models used to evaluate proposed space transportation systems and to develop recommendations for improving them. It was found that, compared to the models available from other sources, the operations assessment methodology recently developed at Kennedy Space Center has the potential to produce a decision support tool that will serve as the industry standard. Towards that goal, a number of areas of improvement in the Kennedy Space Center's methodology are identified.

Joglekar, Prafulla↗

Use of Remote Sensing Products for the SERVIR Project

The United Nations University (UNU) estimates that floods presently impacts greater than 520 million people per year worldwide, resulting in up to 25,000 annual deaths, extensive homelessness, disaster-induced disease, crop and livestock damage, famine, and other serious harm. Meanwhile, aid agencies such as the International Federation of Red Cross and Red Crescent Societies (IFRC) are increasingly seeking better information concerning flood hazards in order to plan for and help mitigate the effects of damaging floods. There is fertile ground to continue development of better remote sensing and modeling techniques to help manage flood related disasters. Disaster management and humanitarian aid organizations need accurate and timely information for making decisions regarding deployment of relief teams and emergency supplies during major floods. Flood maps based on the use of satellite data have proven extremely valuable to such organizations for identifying the location, extent, and severity of these events. However, despite extraordinary efforts on the part of remote sensing data providers to rapidly deliver such maps, there is typically a delay of several days or even weeks from the on-set of flooding until such maps are available to the disaster management community. This paper summarizes efforts at NASA to address this problem through development of an integrated and automated process of a) flood forecasting b) flood detection, c) satellite data acquisition, d) rapid flood mapping and distribution, and e) validation of flood forecasting and detection products.

Policelli, Frederick S.↗

Integrated Traffic Flow Management Decision Making

A generalized approach is proposed to support integrated traffic flow management decision making studies at both the U.S. national and regional levels. It can consider tradeoffs between alternative optimization and heuristic based models, strategic versus tactical flight controls, and system versus fleet preferences. Preliminary testing was accomplished by implementing thirteen unique traffic flow management models, which included all of the key components of the system and conducting 85, six-hour fast-time simulation experiments. These experiments considered variations in the strategic planning look-ahead times, the replanning intervals, and the types of traffic flow management control strategies. Initial testing indicates that longer strategic planning look-ahead times and re-planning intervals result in steadily decreasing levels of sector congestion for a fixed delay level. This applies when accurate estimates of the air traffic demand, airport capacities and airspace capacities are available. In general, the distribution of the delays amongst the users was found to be most equitable when scheduling flights using a heuristic scheduling algorithm, such as ration-by-distance. On the other hand, equity was the worst when using scheduling algorithms that took into account the number of seats aboard each flight. Though the scheduling algorithms were effective at alleviating sector congestion, the tactical rerouting algorithm was the primary control for avoiding en route weather hazards. Finally, the modeled levels of sector congestion, the number of weather incursions, and the total system delays, were found to be in fair agreement with the values that were operationally observed on both good and bad weather days.

Grabbe, Shon R.↗

Integration Process for the Habitat Demonstration Unit

The Habitat Demonstration Unit (HDU) is an experimental exploration habitat technology and architecture test platform designed for analog demonstration activities. The HDU previously served as a test bed for testing technologies and sub-systems in a terrestrial surface environment. in 2010 in the Pressurized Excursion Module (PEM) configuration. Due to the amount of work involved to make the HDU project successful, the HDU project has required a team to integrate a variety of contributions from NASA centers and outside collaborators The size of the team and number of systems involved With the HDU makes Integration a complicated process. However, because the HDU shell manufacturing is complete, the team has a head start on FY--11 integration activities and can focus on integrating upgrades to existing systems as well as integrating new additions. To complete the development of the FY-11 HDU from conception to rollout for operations in July 2011, a cohesive integration strategy has been developed to integrate the various systems of HDU and the payloads. The highlighted HDU work for FY-11 will focus on performing upgrades to the PEM configuration, adding the X-Hab as a second level, adding a new porch providing the astronauts a larger work area outside the HDU for EVA preparations, and adding a Hygiene module. Together these upgrades result in a prototype configuration of the Deep Space Habitat (DSH), an element under evaluation by NASA's Human Exploration Framework Team (HEFT) Scheduled activates include early fit-checks and the utilization of a Habitat avionics test bed prior to installation into HDU. A coordinated effort to utilize modeling and simulation systems has aided in design and integration concept development. Modeling tools have been effective in hardware systems layout, cable routing, sub-system interface length estimation and human factors analysis. Decision processes on integration and use of all new subsystems will be defined early in the project to maximize the efficiency of both integration and field operations. In addition a series of tailored design reviews are utilized to quickly define the systems and their integration into the DSH configuration. These processes are necessary to ensure activities, such as partially reversing integration of the X-Hab second story of the HDU and deploying and stowing the new work porch for transportation to the JSC Rock Yard and to the Arizona Black Point Lava Flow Site are performed with minimal or no complications. In addition, incremental test operations leading up to an Integrated systems test allows for an orderly systems test program. For FY-11 activities, the HDU DSH will act as a laboratory utilizing a new X-Hab inflatable second floor with crew habitation features. In addition to the day to day operations involving maintenance of the HDU and exploring the surrounding terrain, testing and optimizing the use of the new X-Hab, work porch, Hygiene Module, and other sub-system enhancements will be the focus of the FY-11 test objectives. The HDU team requires a successful integration strategy using a variety of tools and approaches to prepare the DSH for these test objectives. In a challenging environment where the prototyping influences the system design, as well as Vice versa, results of the HDU DSH field tests will influence future designs of habitat systems.

Gill, Tracy↗

Health Management Applications for International Space Station

Traditional mission and vehicle management involves teams of highly trained specialists monitoring vehicle status and crew activities, responding rapidly to any anomalies encountered during operations. These teams work from the Mission Control Center and have access to engineering support teams with specialized expertise in International Space Station (ISS) subsystems. Integrated System Health Management (ISHM) applications can significantly augment these capabilities by providing enhanced monitoring, prognostic and diagnostic tools for critical decision support and mission management. The Intelligent Systems Division of NASA Ames Research Center is developing many prototype applications using model-based reasoning, data mining and simulation, working with Mission Control through the ISHM Testbed and Prototypes Project. This paper will briefly describe information technology that supports current mission management practice, and will extend this to a vision for future mission control workflow incorporating new ISHM applications. It will describe ISHM applications currently under development at NASA and will define technical approaches for implementing our vision of future human exploration mission management incorporating artificial intelligence and distributed web service architectures using specific examples. Several prototypes are under development, each highlighting a different computational approach. The ISStrider application allows in-depth analysis of Caution and Warning (C&W) events by correlating real-time telemetry with the logical fault trees used to define off-nominal events. The application uses live telemetry data and the Livingstone diagnostic inference engine to display the specific parameters and fault trees that generated the C&W event, allowing a flight controller to identify the root cause of the event from thousands of possibilities by simply navigating animated fault tree models on their workstation. SimStation models the functional power flow for the ISS Electrical Power System and can predict power balance for nominal and off-nominal conditions. SimStation uses realtime telemetry data to keep detailed computational physics models synchronized with actual ISS power system state. In the event of failure, the application can then rapidly diagnose root cause, predict future resource levels and even correlate technical documents relevant to the specific failure. These advanced computational models will allow better insight and more precise control of ISS subsystems, increasing safety margins by speeding up anomaly resolution and reducing,engineering team effort and cost. This technology will make operating ISS more efficient and is directly applicable to next-generation exploration missions and Crew Exploration Vehicles.

Alena, Richard↗

Predicting Pilot Behavior in Medium Scale Scenarios Using Game Theory and Reinforcement Learning

Effective automation is critical in achieving the capacity and safety goals of the Next Generation Air Traffic System. Unfortunately creating integration and validation tools for such automation is difficult as the interactions between automation and their human counterparts is complex and unpredictable. This validation becomes even more difficult as we integrate wide-reaching technologies that affect the behavior of different decision makers in the system such as pilots, controllers and airlines. While overt short-term behavior changes can be explicitly modeled with traditional agent modeling systems, subtle behavior changes caused by the integration of new technologies may snowball into larger problems and be very hard to detect. To overcome these obstacles, we show how integration of new technologies can be validated by learning behavior models based on goals. In this framework, human participants are not modeled explicitly. Instead, their goals are modeled and through reinforcement learning their actions are predicted. The main advantage to this approach is that modeling is done within the context of the entire system allowing for accurate modeling of all participants as they interact as a whole. In addition such an approach allows for efficient trade studies and feasibility testing on a wide range of automation scenarios. The goal of this paper is to test that such an approach is feasible. To do this we implement this approach using a simple discrete-state learning system on a scenario where 50 aircraft need to self-navigate using Automatic Dependent Surveillance-Broadcast (ADS-B) information. In this scenario, we show how the approach can be used to predict the ability of pilots to adequately balance aircraft separation and fly efficient paths. We present results with several levels of complexity and airspace congestion.

Game Theory↗