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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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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

A provisional regulatory gene network for specification of endomesoderm in the sea urchin embryo

We present the current form of a provisional DNA sequence-based regulatory gene network that explains in outline how endomesodermal specification in the sea urchin embryo is controlled. The model of the network is in a continuous process of revision and growth as new genes are added and new experimental results become available; see http://www.its.caltech.edu/~mirsky/endomeso.htm (End-mes Gene Network Update) for the latest version. The network contains over 40 genes at present, many newly uncovered in the course of this work, and most encoding DNA-binding transcriptional regulatory factors. The architecture of the network was approached initially by construction of a logic model that integrated the extensive experimental evidence now available on endomesoderm specification. The internal linkages between genes in the network have been determined functionally, by measurement of the effects of regulatory perturbations on the expression of all relevant genes in the network. Five kinds of perturbation have been applied: (1) use of morpholino antisense oligonucleotides targeted to many of the key regulatory genes in the network; (2) transformation of other regulatory factors into dominant repressors by construction of Engrailed repressor domain fusions; (3) ectopic expression of given regulatory factors, from genetic expression constructs and from injected mRNAs; (4) blockade of the beta-catenin/Tcf pathway by introduction of mRNA encoding the intracellular domain of cadherin; and (5) blockade of the Notch signaling pathway by introduction of mRNA encoding the extracellular domain of the Notch receptor. The network model predicts the cis-regulatory inputs that link each gene into the network. Therefore, its architecture is testable by cis-regulatory analysis. Strongylocentrotus purpuratus and Lytechinus variegatus genomic BAC recombinants that include a large number of the genes in the network have been sequenced and annotated. Tests of the cis-regulatory predictions of the model are greatly facilitated by interspecific computational sequence comparison, which affords a rapid identification of likely cis-regulatory elements in advance of experimental analysis. The network specifies genomically encoded regulatory processes between early cleavage and gastrula stages. These control the specification of the micromere lineage and of the initial veg(2) endomesodermal domain; the blastula-stage separation of the central veg(2) mesodermal domain (i.e., the secondary mesenchyme progenitor field) from the peripheral veg(2) endodermal domain; the stabilization of specification state within these domains; and activation of some downstream differentiation genes. Each of the temporal-spatial phases of specification is represented in a subelement of the network model, that treats regulatory events within the relevant embryonic nuclei at particular stages. (c) 2002 Elsevier Science (USA).

Non-NASA Center↗
NASA NTRS2003

The Logical Extension

The same software controlling autonomous and crew-assisted operations for the International Space Station (ISS) is enabling commercial enterprises to integrate and automate manual operations, also known as decision logic, in real time across complex and disparate networked applications, databases, servers, and other devices, all with quantifiable business benefits. Auspice Corporation, of Framingham, Massachusetts, developed the Auspice TLX (The Logical Extension) software platform to effectively mimic the human decision-making process. Auspice TLX automates operations across extended enterprise systems, where any given infrastructure can include thousands of computers, servers, switches, and modems that are connected, and therefore, dependent upon each other. The concept behind the Auspice software spawned from a computer program originally developed in 1981 by Cambridge, Massachusetts-based Draper Laboratory for simulating tasks performed by astronauts aboard the Space Shuttle. At the time, the Space Shuttle Program was dependent upon paper-based procedures for its manned space missions, which typically averaged 2 weeks in duration. As the Shuttle Program progressed, NASA began increasing the length of manned missions in preparation for a more permanent space habitat. Acknowledging the need to relinquish paper-based procedures in favor of an electronic processing format to properly monitor and manage the complexities of these longer missions, NASA realized that Draper's task simulation software could be applied to its vision of year-round space occupancy. In 1992, Draper was awarded a NASA contract to build User Interface Language software to enable autonomous operations of a multitude of functions on Space Station Freedom (the station was redesigned in 1993 and converted into the international venture known today as the ISS)

Source record↗
NASA NTRS1990

Neural networks as a control methodology

While conventional computers must be programmed in a logical fashion by a person who thoroughly understands the task to be performed, the motivation behind neural networks is to develop machines which can train themselves to perform tasks, using available information about desired system behavior and learning from experience. There are three goals of this fellowship program: (1) to evaluate various neural net methods and generate computer software to implement those deemed most promising on a personal computer equipped with Matlab; (2) to evaluate methods currently in the professional literature for system control using neural nets to choose those most applicable to control of flexible structures; and (3) to apply the control strategies chosen in (2) to a computer simulation of a test article, the Control Structures Interaction Suitcase Demonstrator, which is a portable system consisting of a small flexible beam driven by a torque motor and mounted on springs tuned to the first flexible mode of the beam. Results of each are discussed.

Mccullough, Claire L.↗
NASA NTRS1977

Numerical aerodynamic simulation facility preliminary study, volume 2 and appendices

Data to support results obtained in technology assessment studies are presented. Objectives, starting points, and future study tasks are outlined. Key design issues discussed in appendices include: data allocation, transposition network design, fault tolerance and trustworthiness, logic design, processing element of existing components, number of processors, the host system, alternate data base memory designs, number representation, fast div 521 instruction, architectures, and lockstep array versus synchronizable array machine comparison.

Source record↗
NASA NTRS1993

Improvement on fuzzy controller design techniques

This paper addresses three main issues, which are somewhat interrelated. The first issue deals with the classification or types of fuzzy controllers. Careful examination of the fuzzy controllers designed by various engineers reveals distinctive classes of fuzzy controllers. Classification is believed to be helpful from different perspectives. The second issue deals with the design according to specifications, experiments related to the tuning of fuzzy controllers, according to the specification, will be discussed. General design procedure, hopefully, can be outlined in order to ease the burden of a design engineer. The third issue deals with the simplicity and limitation of the rule-based IF-THEN logical statements. The methodology of fuzzy-constraint network is proposed here as an alternative to the design practice at present. It is our belief that predicate calculus and the first order logic possess much more expressive power.

Wang, Paul P.↗
NASA NTRS1998

Software Development Technologies for Reactive, Real-Time, and Hybrid Systems: Summary of Research

This research is directed towards the implementation of a comprehensive deductive-algorithmic environment (toolkit) for the development and verification of high assurance reactive systems, especially concurrent, real-time, and hybrid systems. For this, we have designed and implemented the STCP (Stanford Temporal Prover) verification system. Reactive systems have an ongoing interaction with their environment, and their computations are infinite sequences of states. A large number of systems can be seen as reactive systems, including hardware, concurrent programs, network protocols, and embedded systems. Temporal logic provides a convenient language for expressing properties of reactive systems. A temporal verification methodology provides procedures for proving that a given system satisfies a given temporal property. The research covered necessary theoretical foundations as well as implementation and application issues.

Manna, Zohar↗
NASA NTRS2004

Automatic Generation of Algorithms for the Statistical Analysis of Planetary Nebulae Images

Analyzing data sets collected in experiments or by observations is a Core scientific activity. Typically, experimentd and observational data are &aught with uncertainty, and the analysis is based on a statistical model of the conjectured underlying processes, The large data volumes collected by modern instruments make computer support indispensible for this. Consequently, scientists spend significant amounts of their time with the development and refinement of the data analysis programs. AutoBayes [GF+02, FS03] is a fully automatic synthesis system for generating statistical data analysis programs. Externally, it looks like a compiler: it takes an abstract problem specification and translates it into executable code. Its input is a concise description of a data analysis problem in the form of a statistical model as shown in Figure 1; its output is optimized and fully documented C/C++ code which can be linked dynamically into the Matlab and Octave environments. Internally, however, it is quite different: AutoBayes derives a customized algorithm implementing the given model using a schema-based process, and then further refines and optimizes the algorithm into code. A schema is a parameterized code template with associated semantic constraints which define and restrict the template s applicability. The schema parameters are instantiated in a problem-specific way during synthesis as AutoBayes checks the constraints against the original model or, recursively, against emerging sub-problems. AutoBayes schema library contains problem decomposition operators (which are justified by theorems in a formal logic in the domain of Bayesian networks) as well as machine learning algorithms (e.g., EM, k-Means) and nu- meric optimization methods (e.g., Nelder-Mead simplex, conjugate gradient). AutoBayes augments this schema-based approach by symbolic computation to derive closed-form solutions whenever possible. This is a major advantage over other statistical data analysis systems which use numerical approximations even in cases where closed-form solutions exist. AutoBayes is implemented in Prolog and comprises approximately 75.000 lines of code. In this paper, we take one typical scientific data analysis problem-analyzing planetary nebulae images taken by the Hubble Space Telescope-and show how AutoBayes can be used to automate the implementation of the necessary anal- ysis programs. We initially follow the analysis described by Knuth and Hajian [KHO2] and use AutoBayes to derive code for the published models. We show the details of the code derivation process, including the symbolic computations and automatic integration of library procedures, and compare the results of the automatically generated and manually implemented code. We then go beyond the original analysis and use AutoBayes to derive code for a simple image segmentation procedure based on a mixture model which can be used to automate a manual preproceesing step. Finally, we combine the original approach with the simple segmentation which yields a more detailed analysis. This also demonstrates that AutoBayes makes it easy to combine different aspects of data analysis.

Fischer, Bernd↗
NASA NTRS2015

R2U2: Monitoring and Diagnosis of Security Threats for Unmanned Aerial Systems

We present R2U2, a novel framework for runtime monitoring of security properties and diagnosing of security threats on-board Unmanned Aerial Systems (UAS). R2U2, implemented in FPGA hardware, is a real-time, REALIZABLE, RESPONSIVE, UNOBTRUSIVE Unit for security threat detection. R2U2 is designed to continuously monitor inputs from the GPS and the ground control station, sensor readings, actuator outputs, and flight software status. By simultaneously monitoring and performing statistical reasoning, attack patterns and post-attack discrepancies in the UAS behavior can be detected. R2U2 uses runtime observer pairs for linear and metric temporal logics for property monitoring and Bayesian networks for diagnosis of security threats. We discuss the design and implementation that now enables R2U2 to handle security threats and present simulation results of several attack scenarios on the NASA DragonEye UAS.

Formal Methods↗
NASA NTRS1985

A synchronous fiber optic ring local area network for multigigabit/s mixed-traffic communication

A synchronous-ring fiber optic local area network is reported that facilitates the simultaneous transmission of packet and real-time traffic at gigabit/s rates, minimizes the amount of high-speed logic, and simplifies the user interface to the network. The novelty of the technique is based on (1) suspending in transit around the ring's circumference an integral number of data frames and (2) achieving this condition by skewing the frame clock rate a small amount. Rather than use the whole data frame as one packet destined to a specific user, many individual channels are instead time-multiplexed into the data frame. This technique only becomes feasible for local networks as data rates approach the Gbit/s range. This departure from other synchronous rings results in several advantages both in terms of system performance and hardware simplicity.

Bergman, L. A.↗
NASA NTRS1991

Method and apparatus for eliminating unsuccessful tries in a search tree

A circuit switching system in an M-ary, n-cube connected network completes a best-first path from an originating node to a destination node by latching valid legs of the path as the path is being sought out. Each network node is provided with a routing hyperswitch sub-network, (HSN) connected between that node and bidirectional high capacity communication channels of the n-cube network. The sub-networks are all controlled by routing algorithms which respond to message identification headings (headers) on messages to be routed along one or more routing legs. The header includes information embedded therein which is interpreted by each sub-network to route and historically update the header. A logic circuit, available at every node, implements the algorithm and automatically forwards or back-tracks the header in the network legs of various paths until a completed path is latched.

Peterson, John C.↗
NASA NTRS2005

Fuzzy/Neural Software Estimates Costs of Rocket-Engine Tests

The Highly Accurate Cost Estimating Model (HACEM) is a software system for estimating the costs of testing rocket engines and components at Stennis Space Center. HACEM is built on a foundation of adaptive-network-based fuzzy inference systems (ANFIS) a hybrid software concept that combines the adaptive capabilities of neural networks with the ease of development and additional benefits of fuzzy-logic-based systems. In ANFIS, fuzzy inference systems are trained by use of neural networks. HACEM includes selectable subsystems that utilize various numbers and types of inputs, various numbers of fuzzy membership functions, and various input-preprocessing techniques. The inputs to HACEM are parameters of specific tests or series of tests. These parameters include test type (component or engine test), number and duration of tests, and thrust level(s) (in the case of engine tests). The ANFIS in HACEM are trained by use of sets of these parameters, along with costs of past tests. Thereafter, the user feeds HACEM a simple input text file that contains the parameters of a planned test or series of tests, the user selects the desired HACEM subsystem, and the subsystem processes the parameters into an estimate of cost(s).

Douglas, Freddie↗
NASA NTRS1988

Heat exchanger expert system logic

The reduction is described of the operation and fault diagnostics of a Deep Space Network heat exchanger to a rule base by the application of propositional calculus to a set of logic statements. The value of this approach lies in the ease of converting the logic and subsequently implementing it on a computer as an expert system. The rule base was written in Process Intelligent Control software.

Cormier, R.↗
NASA NTRS1998

A Self-Tuning Kalman Filter for Autonomous Spacecraft Navigation

Most navigation systems currently operated by NASA are ground-based, and require extensive support to produce accurate results. Recently developed systems that use Kalman Filter and Global Positioning System (GPS) data for orbit determination greatly reduce dependency on ground support, and have potential to provide significant economies for NASA spacecraft navigation. Current techniques of Kalman filtering, however, still rely on manual tuning from analysts, and cannot help in optimizing autonomy without compromising accuracy and performance. This paper presents an approach to produce a high accuracy autonomous navigation system fully integrated with the flight system. The resulting system performs real-time state estimation by using an Extended Kalman Filter (EKF) implemented with high-fidelity state dynamics model, as does the GPS Enhanced Orbit Determination Experiment (GEODE) system developed by the NASA Goddard Space Flight Center. Augmented to the EKF is a sophisticated neural-fuzzy system, which combines the explicit knowledge representation of fuzzy logic with the learning power of neural networks. The fuzzy-neural system performs most of the self-tuning capability and helps the navigation system recover from estimation errors. The core requirement is a method of state estimation that handles uncertainties robustly, capable of identifying estimation problems, flexible enough to make decisions and adjustments to recover from these problems, and compact enough to run on flight hardware. The resulting system can be extended to support geosynchronous spacecraft and high-eccentricity orbits. Mathematical methodology, systems and operations concepts, and implementation of a system prototype are presented in this paper. Results from the use of the prototype to evaluate optimal control algorithms implemented are discussed. Test data and major control issues (e.g., how to define specific roles for fuzzy logic to support the self-learning capability) are also discussed. In addition, architecture of a complete end-to-end candidate flight system that provides navigation with highly autonomous control using data from GPS is presented.

Truong, Son H.↗
NASA NTRS1973

On-line diagnosis of sequential systems

A model for on-line diagnosis was investigated for discrete-time systems, and resettable sequential systems. Generalized notions of a realization are discussed along with fault tolerance and errors. Further investigation into the theory of on-line diagnosis is recommended for three levels: binary state-assigned level, logical circuit level, and the subsystem-network level.

Sundstrom, R. J.↗
NASA NTRS1981

CADAT network translator

Program converts cell-net data into logic-gate models for use in test and simulation programs. Input consists of either Place, Route, and Fold (PRF) or Place-and-Route-in-Two-Dimensions (PR2D) layout data deck. Output consists of either Test Pattern Generator (TPG) or Logic-Simulation (LOGSIM) logic circuitry data deck. Designer needs to build only logic-gate-model circuit description since program acts as translator. Language is FORTRAN IV.

Pitts, E. R.↗
NASA NTRS1991

Autonomous rendezvous and capture system design

Marshall Space Flight Center has a long history of involvement in the design of Autonomous Rendezvous and Capture (AR&C) systems. The first extensive studies were begun in the late seventies, incrementally leading to the development of an assortment of Guidance, Navigation, and Control (GN&C) concepts and algorithms suitable for a variety of mission requirements and spacecraft capabilities, with a strong emphasis placed upon flexible system-level design. These efforts have led to the development of sophisticated algorithms for docking with tumbling targets, and simple but efficient algorithms for stabilized spacecraft; each has been tested and validated using dynamic system simulation, with hardware in the loop when practical. Recent investigations include the use of neural networks for video image interpretation, and fuzzy logic for control system implementation.

Dabney, Richard W.↗
NASA NTRS1990

Optimized testing of meshes

Efficient testing techniques for two-dimensional mesh interconnection networks are presented. The tests cover faults in the arbitration logic of the switches; this includes an examination of fault detection in the data paths, routing, and control circuitry, including the conflict resolution capabilities of mesh interconnection networks using topological test methods. The proposed methods are not implementation specific and can be applied to any design with a mesh topology. The topology and behavior of the network are described and definitions are presented. The fault model is defined and parallel testing methods for the entire network are given.

Malek, Miroslaw↗