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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS1989

DEVS representation of dynamical systems - Event-based intelligent control

It is shown how systems can be advantageously represented as discrete-event models by using DEVS (discrete-event system specification), a set-theoretic formalism. Such DEVS models provide a basis for the design of event-based logic control. In this control paradigm, the controller expects to receive confirming sensor responses to its control commands within definite time windows determined by its DEVS model of the system under control. The event-based contral paradigm is applied in advanced robotic and intelligent automation, showing how classical process control can be readily interfaced with rule-based symbolic reasoning systems.

Zeigler, Bernard P.↗

NASA NTRS2008

Orbital Express AVGS Validation and Calibration for Automated Rendezvous

From March to July of 2007, the DARPA Orbital Express mission achieved a number of firsts in autonomous spacecraft operations. The NASA Advanced Video Guidance Sensor (AVGS) was the primary docking sensor during the first two dockings and was used in a blended mode three other automated captures. The AVGS performance exceeded its specification by approximately an order of magnitude. One reason that the AVGS functioned so well during the mission was that the validation and calibration of the sensor prior to the mission advanced the state-of-the-art for proximity sensors. Some factors in this success were improvements in ground test equipment and truth data, the capability for ILOAD corrections for optical and other effects, and the development of a bias correction procedure. Several valuable lessons learned have applications to future proximity sensors.

Heaton, Andrew F.↗

NASA NTRS2015

A Description of the Development, Capabilities, and Operational Status of the Test SLATE Data Acquisition System at the National Transonic Facility

The paper will present a brief background of the previous data acquisition system at the National Transonic Facility (NTF) and the reasoning and goals behind the upgrade to the current Test SLATE (Test Software Laboratory and Automated Testing Environments) data acquisition system. The components, performance characteristics, and layout of the Test SLATE system within the NTF control room will be discussed. The development, testing, and integration of Test SLATE within NTF operations will be detailed. The operational capabilities of the system will be outlined including: test setup, instrumentation calibration, automatic test sequencer setup, data recording, communication between data and facility control systems, real time display monitoring, and data reduction. The current operational status of the Test SLATE system and its performance during recent NTF testing will be highlighted including high-speed, frame-by-frame data acquisition with conditional sampling post-processing applied. The paper concludes with current development work on the system including the capability for real-time conditional sampling during data acquisition and further efficiency enhancements to the wind tunnel testing process.

Cramer, Christopher J.↗

NASA NTRS1991

Data simulation for the Lightning Imaging Sensor (LIS)

This project aims to build a data analysis system that will utilize existing video tape scenes of lightning as viewed from space. The resultant data will be used for the design and development of the Lightning Imaging Sensor (LIS) software and algorithm analysis. The desire for statistically significant metrics implies that a large data set needs to be analyzed. Before 1990 the quality and quantity of video was insufficient to build a usable data set. At this point in time, there is usable data from missions STS-34, STS-32, STS-31, STS-41, STS-37, and STS-39. During the summer of 1990, a manual analysis system was developed to demonstrate that the video analysis is feasible and to identify techniques to deduce information that was not directly available. Because the closed circuit television system used on the space shuttle was intended for documentary TV, the current value of the camera focal length and pointing orientation, which are needed for photoanalysis, are not included in the system data. A large effort was needed to discover ancillary data sources as well as develop indirect methods to estimate the necessary parameters. Any data system coping with full motion video faces an enormous bottleneck produced by the large data production rate and the need to move and store the digitized images. The manual system bypassed the video digitizing bottleneck by using a genlock to superimpose pixel coordinates on full motion video. Because the data set had to be obtained point by point by a human operating a computer mouse, the data output rate was small. The loan and subsequent acquisition of a Abekas digital frame store with a real time digitizer moved the bottleneck from data acquisition to a problem of data transfer and storage. The semi-automated analysis procedure was developed using existing equipment and is described. A fully automated system is described in the hope that the components may come on the market at reasonable prices in the next few years.

Boeck, William L.↗

NASA NTRS2006

Developing Formal Correctness Properties from Natural Language Requirements

This viewgraph presentation reviews the rationale of the program to transform natural language specifications into formal notation.Specifically, automate generation of Linear Temporal Logic (LTL)correctness properties from natural language temporal specifications. There are several reasons for this approach (1) Model-based techniques becoming more widely accepted, (2) Analytical verification techniques (e.g., model checking, theorem proving) significantly more effective at detecting types of specification design errors (e.g., race conditions, deadlock) than manual inspection, (3) Many requirements still written in natural language, which results in a high learning curve for specification languages, associated tools and increased schedule and budget pressure on projects reduce training opportunities for engineers, and (4) Formulation of correctness properties for system models can be a difficult problem. This has relevance to NASA in that it would simplify development of formal correctness properties, lead to more widespread use of model-based specification, design techniques, assist in earlier identification of defects and reduce residual defect content for space mission software systems. The presentation also discusses: potential applications, accomplishments and/or technological transfer potential and the next steps.

requirements engineering↗

NASA NTRS2003

NASA Tech Briefs, August 2003

Topics covered include: Stable, Thermally Conductive Fillers for Bolted Joints; Connecting to Thermocouples with Fewer Lead Wires; Zipper Connectors for Flexible Electronic Circuits; Safety Interlock for Angularly Misdirected Power Tool; Modular, Parallel Pulse-Shaping Filter Architectures; High-Fidelity Piezoelectric Audio Device; Photovoltaic Power Station with Ultracapacitors for Storage; Time Analyzer for Time Synchronization and Monitor of the Deep Space Network; Program for Computing Albedo; Integrated Software for Analyzing Designs of Launch Vehicles; Abstract-Reasoning Software for Coordinating Multiple Agents; Software Searches for Better Spacecraft-Navigation Models; Software for Partly Automated Recognition of Targets; Antistatic Polycarbonate/Copper Oxide Composite; Better VPS Fabrication of Crucibles and Furnace Cartridges; Burn-Resistant, Strong Metal-Matrix Composites; Self-Deployable Spring-Strip Booms; Explosion Welding for Hermetic Containerization; Improved Process for Fabricating Carbon Nanotube Probes; Automated Serial Sectioning for 3D Reconstruction; and Parallel Subconvolution Filtering Architectures.

Source record↗

NASA NTRS2003

Proof Rules for Automated Compositional Verification through Learning

Compositional proof systems not only enable the stepwise development of concurrent processes but also provide a basis to alleviate the state explosion problem associated with model checking. An assume-guarantee style of specification and reasoning has long been advocated to achieve compositionality. However, this style of reasoning is often non-trivial, typically requiring human input to determine appropriate assumptions. In this paper, we present novel assume- guarantee rules in the setting of finite labelled transition systems with blocking communication. We show how these rules can be applied in an iterative and fully automated fashion within a framework based on learning.

Barringer, Howard↗

NASA NTRSDate not supplied

Combining Disparate Measures of Metabolic Rate During Simulated Spacewalks

Scientists from NASA's Extravehicular Activities (EVA) Physiology Systems and Performance Project help design space suits for future missions, during which astronauts are expected to perform EVA activities on the Lunar or Martian surface. During an EVA, an astronaut's integrated metabolic rate is used to predict how much longer the activity can continue and still provide a safe margin of remaining consumables. For EVAs in the Apollo era, NASA physicians monitored live data feeds of heart rate, O 2 consumption, and liquid cooled garment (LCG) temperatures, which were subjectively combined or compared to produce an estimate of metabolic rate. But these multiple data feeds sometimes provided conflicting estimates of metabolic rate, making real-time calculations of remaining time difficult for physician/monitors. Currently, designs planned for the Constellation Program EVAs utilize an automated, but largely heuristic methodology for incorporating the above three measurements, plus an additional one - CO 2 production, ignoring data that appears in conflict; however a more rigorous model-based approach is desirable. In this study, we show how principal axis factor analysis, in combination with OLS regression and LOWESS smoothing can be used to estimate metabolic rate as a data-driven weighted average of heart rate, O 2 consumption, LCG temperature data, and CO 2 production. Preliminary results suggest less sensitivity to occasional spikes in observed data feeds, and reasonable within-subject reproducibility when applied to subsequent tasks. These methods do not require physician monitoring and as such can be automated in the electronic components of future space suits. With additional validation, our models show promise for increasing astronaut safety, while reducing the need for and potential errors associated with human monitoring of multiple systems.

Alan H Feiveson↗

NASA NTRS1993

A pattern recognition system for locating small volvanoes in Magellan SAR images of Venus

The Magellan data set constitutes an example of the large volumes of data that today's instruments can collect, providing more detail of Venus than was previously available from Pioneer Venus, Venera 15/16, or ground-based radar observations put together. However, data analysis technology has not kept pace with data collection and storage technology. Due to the sheer size of the data, complete and comprehensive scientific analysis of such large volumes of image data is no longer feasible without the use of computational aids. Our progress towards developing a pattern recognition system for aiding in the detection and cataloging of small-scale natural features in large collections of images is reported. Combining classical image processing, machine learning, and a graphical user interface, the detection of the 'small-shield' volcanoes (less than 15km in diameter) that constitute the most abundant visible geologic feature in the more that 30,000 synthetic aperture radar (SAR) images of the surface of Venus are initially targeted. Our eventual goal is to provide a general, trainable tool for locating small-scale features where scientists specify what to look for simply by providing examples and attributes of interest to measure. This contrasts with the traditional approach of developing problem specific programs for detecting Specific patterns. The approach and initial results in the specific context of locating small volcanoes is reported. It is estimated, based on extrapolating from previous studies and knowledge of the underlying geologic processes, that there should be on the order of 10(exp 5) to 10(exp 6) of these volcanoes visible in the Magellan data. Identifying and studying these volcanoes is fundamental to a proper understanding of the geologic evolution of Venus. However, locating and parameterizing them in a manual manner is forbiddingly time-consuming. Hence, the development of techniques to partially automate this task were undertaken. The primary constraints for this particular problem are that the method must be reasonably robust and fast. Unlike most geological features, the small volcanoes of Venus can be ascribed to a basic process that produces features with a short list of readily defined characteristics differing significantly from other surface features on Venus. For pattern recognition purposes the relevant criteria include (1) a circular planimetric outline, (2) known diameter frequency distribution from preliminary studies, (3) a limited number of basic morphological shapes, and (4) the common occurrence of a single, circular summit pit at the center of the edifice.

Burl, M. C.↗

NASA NTRS2001

The 3D Recognition, Generation, Fusion, Update and Refinement (RG4) Concept

This paper describes an active (real time) recognition strategy whereby information is inferred iteratively across several viewpoints in descent imagery. We will show how we use inverse theory within the context of parametric model generation, namely height and spectral reflection functions, to generate model assertions. Using this strategy in an active context implies that, from every viewpoint, the proposed system must refine its hypotheses taking into account the image and the effect of uncertainties as well. The proposed system employs probabilistic solutions to the problem of iteratively merging information (images) from several viewpoints. This involves feeding the posterior distribution from all previous images as a prior for the next view. Novel approaches will be developed to accelerate the inversion search using novel statistic implementations and reducing the model complexity using foveated vision. Foveated vision refers to imagery where the resolution varies across the image. In this paper, we allow the model to be foveated where the highest resolution region is called the foveation region. Typically, the images will have dynamic control of the location of the foveation region. For descent imagery in the Entry, Descent, and Landing (EDL) process, it is possible to have more than one foveation region. This research initiative is directed towards descent imagery in connection with NASA's EDL applications. Three-Dimensional Model Recognition, Generation, Fusion, Update, and Refinement (RGFUR or RG4) for height and the spectral reflection characteristics are in focus for various reasons, one of which is the prospect that their interpretation will provide for real time active vision for automated EDL.

Maluf, David A.↗

NASA NTRS2018

Contingency Management with Human Autonomy Teaming

Automation is playing an increasingly important role in many operations. It is often cheaper faster and more precise than human operators. However, automation is not perfect. There are many situations in which a human operator must step in. We refer to these instances as contingencies and the act of stepping in contingency management. Here we propose coupling Human Autonomy Teaming (HAT) with contingency management. We describe two aspects to HAT, bi-directional communication, and working agreements (or plays). Bi-directional communication like Crew Resource Management in traditional aviation, allows all parties to contribute to a decision. Working agreements specify roles and responsibilities. Importantly working agreements allow for the possibility of roles and responsibilities changing depending on environmental factors (e.g., situations the automation was not designed for, workload, risk, or trust). This allows for the automation to "automatically" become more autonomous as it becomes more trusted and/or it is updated to deal with a more complete set of possible situations. We present a concrete example using a prototype contingency management station one might find in a future airline operations center. Automation proposes reroutes for aircraft that encounter bad weather or are forced to divert for environmental or systems reasons. If specific conditions are met, these recommendations may be autonomously datalinked to the affected aircraft.

dispatch↗

NASA NTRS1993

Model-based reasoning for power system management using KATE and the SSM/PMAD

The overall goal of this research effort has been the development of a software system which automates tasks related to monitoring and controlling electrical power distribution in spacecraft electrical power systems. The resulting software system is called the Intelligent Power Controller (IPC). The specific tasks performed by the IPC include continuous monitoring of the flow of power from a source to a set of loads, fast detection of anomalous behavior indicating a fault to one of the components of the distribution systems, generation of diagnosis (explanation) of anomalous behavior, isolation of faulty object from remainder of system, and maintenance of flow of power to critical loads and systems (e.g. life-support) despite fault conditions being present (recovery). The IPC system has evolved out of KATE (Knowledge-based Autonomous Test Engineer), developed at NASA-KSC. KATE consists of a set of software tools for developing and applying structure and behavior models to monitoring, diagnostic, and control applications.

Morris, Robert A.↗

NASA NTRS1996

A Model-based Approach to Reactive Self-Configuring Systems

This paper describes Livingstone, an implemented kernel for a self-reconfiguring autonomous system, that is reactive and uses component-based declarative models. The paper presents a formal characterization of the representation formalism used in Livingstone, and reports on our experience with the implementation in a variety of domains. Livingstone's representation formalism achieves broad coverage of hybrid software/hardware systems by coupling the concurrent transition system models underlying concurrent reactive languages with the discrete qualitative representations developed in model-based reasoning. We achieve a reactive system that performs significant deductions in the sense/response loop by drawing on our past experience at building fast prepositional conflict-based algorithms for model-based diagnosis, and by framing a model-based configuration manager as a prepositional, conflict-based feedback controller that generates focused, optimal responses. Livingstone automates all these tasks using a single model and a single core deductive engine, thus making significant progress towards achieving a central goal of model-based reasoning. Livingstone, together with the HSTS planning and scheduling engine and the RAPS executive, has been selected as the core autonomy architecture for Deep Space One, the first spacecraft for NASA's New Millennium program.

Williams, Brian C.↗

NASA NTRS2006

Dynamic Aperture-based Solar Loop Segmentation

A new method to automatically segment arc-like loop structures from intensity images of the Sun's corona is introduced. The method constructively segments credible loop structures by exploiting the Gaussian-like shape of loop cross-sectional intensity profiles. The experimental results show that the method reasonably segments most of the well-defined loops in coronal images. The method is only the second published automated solar loop segmentation method. Its advantage over the other published method is that it operates independently of supplemental time specific data.

Lee, Jon Kwan↗

NASA NTRS1993

An autonomous satellite architecture integrating deliberative reasoning and behavioural intelligence

This paper describes a method for the design of autonomous spacecraft, based upon behavioral approaches to intelligent robotics. First, a number of previous spacecraft automation projects are reviewed. A methodology for the design of autonomous spacecraft is then presented, drawing upon both the European Space Agency technological center (ESTEC) automation and robotics methodology and the subsumption architecture for autonomous robots. A layered competency model for autonomous orbital spacecraft is proposed. A simple example of low level competencies and their interaction is presented in order to illustrate the methodology. Finally, the general principles adopted for the control hardware design of the AUSTRALIS-1 spacecraft are described. This system will provide an orbital experimental platform for spacecraft autonomy studies, supporting the exploration of different logical control models, different computational metaphors within the behavioral control framework, and different mappings from the logical control model to its physical implementation.

Lindley, Craig A.↗

NASA NTRS2018

Automated Scenario Generation for Human-in-the-Loop Simulations

Automated Multi-Aircraft Control System scenario generation for Human-in-the-Loop evaluations of air traffic management concepts is described. Methods for analyzing and comparing the seed-scenario generated using the automated process and the Human-in-the-Loop-scenario designed to meet the experiment objectives are discussed. The main findings are: (1) many of the characteristics of the seed-scenario used for constructing the Human-in-the-Loop-scenario are preserved in the Human-in-the-Loop Scenario, (2) landing characteristics of the traffic generated by the Multi-Aircraft Control System using the input scenario compare reasonably well with that intended in the input scenario, and (3) many of desired characteristics of the Human-in-the-Loop-scenario can be achieved by further automation.

SMART-NAS Testbed↗

NASA NTRS2004

Autonomous Multi-Sensor Coordination: The Science Goal Monitor

Many dramatic earth phenomena are dynamic and coupled. In order to fully understand them, we need to obtain timely coordinated multi-sensor observations from widely dispersed instruments. Such a dynamic observing system must include the ability to Schedule flexibly and react autonomously to sciencehser driven events; Understand higher-level goals of a sciencehser defined campaign; Coordinate various space-based and ground-based resources/sensors effectively and efficiently to achieve goals. In order to capture transient events, such a 'sensor web' system must have an automated reactive capability built into its scientific operations. To do this, we must overcome a number of challenges inherent in infusing autonomy. The Science Goal Monitor (SGM) is a prototype software tool being developed to explore the nature of automation necessary to enable dynamic observing. The tools being developed in SGM improve our ability to autonomously monitor multiple independent sensors and coordinate reactions to better observe dynamic phenomena. The SGM system enables users to specify what to look for and how to react in descriptive rather than technical terms. The system monitors streams of data to identify occurrences of the key events previously specified by the scientisther. When an event occurs, the system autonomously coordinates the execution of the users' desired reactions between different sensors. The information can be used to rapidly respond to a variety of fast temporal events. Investigators will no longer have to rely on after-the-fact data analysis to determine what happened. Our paper describes a series of prototype demonstrations that we have developed using SGM and NASA's Earth Observing-1 (EO-1) satellite and Earth Observing Systems' Aqua/Terra spacecrafts' MODIS instrument. Our demonstrations show the promise of coordinating data from different sources, analyzing the data for a relevant event, autonomously updating and rapidly obtaining a follow-on relevant image. SGM was used to investigate forest fires, floods and volcanic eruptions. We are now identifying new Earth science scenarios that will have more complex SGM reasoning. By developing and testing a prototype in an operational environment, we are also establishing and gathering metrics to gauge the success of automating science campaigns.

Koratkar, Anuradha↗

NASA NTRS2004

Autonomous Multi-sensor Coordination: The Science Goal Monitor

Next-generation science and exploration systems will employ new observation strategies that will use multiple sensors in a dynamic environment to provide high quality monitoring, self-consistent analyses and informed decision making. The Science Goal Monitor (SGM) is a prototype software tool being developed to explore the nature of automation necessary to enable dynamic observing of earth phenomenon. The tools being developed in SGM improve our ability to autonomously monitor multiple independent sensors and coordinate reactions to better observe the dynamic phenomena. The SGM system enables users to specify events of interest and how to react when an event is detected. The system monitors streams of data to identify occurrences of the key events previously specified by the scientist/user. When an event occurs, the system autonomously coordinates the execution of the users desired reactions between different sensors. The information can be used to rapidly respond to a variety of fast temporal events. Investigators will no longer have to rely on after-the-fact data analysis to determine what happened. Our paper describes a series of prototype demonstrations that we have developed using SGM and NASA's Earth Observing-1 (EO-1) satellite and Earth Observing Systems Aqua/Terra spacecrafts MODIS instrument. Our demonstrations show the promise of coordinating data from different sources, analyzing the data for a relevant event, autonomously updating and rapidly obtaining a follow-on relevant image. SGM is being used to investigate forest fires, floods and volcanic eruptions. We are now identifying new earth science scenarios that will have more complex SGM reasoning. By developing and testing a prototype in an operational environment, we are also establishing and gathering metrics to gauge the success of automating science campaigns.

Koratkar, Anuradha↗