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At least 289 records · Page 16

ISyCL technical report

The Air Force Integrated Information Systems Evolution Environment (IISEE) is a program focused on the development of technology for enabling the planning definition development and maintenance of evolutionary integrated information systems. This program has studied the representational needs of this knowledge base from the point of view of the needs of engineering, manufacturing, and logistics Evolutionary Information Systems (EIS). The definition of the concepts for a suite of automated tools and environments to support the pursuit of such engineering, manufacturing, and logistics EIS's has also required examination of languages and representation schemes for the knowledge base of these integrated systems. To accomplish this purpose, the language must be very rich, and must support object orientation, relational orientation, persistent storage, process transaction specification, and first order logic. The task of designing a unified language which supports these paradigms is a challenge. The Information Systems Constraint Language (ISyCL) is described. It was designed to meet the definitional and knowledge representation needs of three perspectives. It supports users from the area expert to the data base designer.

Decker, Louis P.↗

Formal specification and verification of Ada software

The use of formal methods in software development achieves levels of quality assurance unobtainable by other means. The Larch approach to specification is described, and the specification of avionics software designed to implement the logic of a flight control system is given as an example. Penelope is described which is an Ada-verification environment. The Penelope user inputs mathematical definitions, Larch-style specifications and Ada code and performs machine-assisted proofs that the code obeys its specifications. As an example, the verification of a binary search function is considered. Emphasis is given to techniques assisting the reuse of a verification effort on modified code.

Hird, Geoffrey R.↗

Roll-Out and Turn-Off Display Software for Integrated Display System

This report describes the software products, system architectures and operational procedures developed by Lockheed-Martin in support of the Roll-Out and Turn-Off (ROTO) sub-element of the Low Visibility Landing and Surface Operations (LVLASO) program at the NASA Langley Research Center. The ROTO portion of this program focuses on developing technologies that aid pilots in the task of managing the deceleration of an aircraft to a pre-selected exit taxiway. This report focuses on software that produces a system of redundant deceleration cues for a pilot during the landing roll-out, and presents these cues on a head up display (HUD). The software also produces symbology for aircraft operational phases involving cruise flight, approach, takeoff, and go-around. The algorithms and data sources used to compute the deceleration guidance and generate the displays are discussed. Examples of the display formats and symbology options are presented. Logic diagrams describing the design of the ROTO software module are also given.

Johnson, Edward J., Jr.↗

Monitoring the Microgravity Environment Quality On-Board the International Space Station Using Soft Computing Techniques

This paper presents an artificial intelligence monitoring system developed by the NASA Glenn Principal Investigator Microgravity Services project to help the principal investigator teams identify the primary vibratory disturbance sources that are active, at any moment in time, on-board the International Space Station, which might impact the microgravity environment their experiments are exposed to. From the Principal Investigator Microgravity Services' web site, the principal investigator teams can monitor via a graphical display, in near real time, which event(s) is/are on, such as crew activities, pumps, fans, centrifuges, compressor, crew exercise, platform structural modes, etc., and decide whether or not to run their experiments based on the acceleration environment associated with a specific event. This monitoring system is focused primarily on detecting the vibratory disturbance sources, but could be used as well to detect some of the transient disturbance sources, depending on the events duration. The system has built-in capability to detect both known and unknown vibratory disturbance sources. Several soft computing techniques such as Kohonen's Self-Organizing Feature Map, Learning Vector Quantization, Back-Propagation Neural Networks, and Fuzzy Logic were used to design the system.

Jules, Kenol↗

Monitoring the Microgravity Environment Quality On-board the International Space Station Using Soft Computing Techniques: Preliminary System Performance Results - Part 2

This paper presents the preliminary performance results of the artificial intelligence monitoring system in full operational mode using near real time acceleration data downlinked from the International Space Station. Preliminary microgravity environment characterization analysis result for the International Space Station (Increment-2), using the monitoring system is presented. Also, comparison between the system predicted performance based on ground test data for the US laboratory "Destiny" module and actual on-orbit performance, using measured acceleration data from the U.S. laboratory module of the International Space Station is presented. Finally, preliminary on-orbit disturbance magnitude levels are presented for the Experiment of Physics of Colloids in Space, which are compared with on ground test data. The ground test data for the Experiment of Physics of Colloids in Space were acquired from the Microgravity Emission Laboratory, located at the NASA Glenn Research Center, Cleveland, Ohio. The artificial intelligence was developed by the NASA Glenn Principal Investigator Microgravity Services Project to help the principal investigator teams identify the primary vibratory disturbance sources that are active, at any moment of time, on-board the International Space Station, which might impact the microgravity environment their experiments are exposed to. From the Principal Investigator Microgravity Services' web site, the principal investigator teams can monitor via a dynamic graphical display, implemented in Java, in near real time, which event(s) is/are on, such as crew activities, pumps, fans, centrifuges, compressor, crew exercise, structural modes, etc., and decide whether or not to run their experiments, whenever that is an option, based on the acceleration magnitude and frequency sensitivity associated with that experiment. This monitoring system detects primarily the vibratory disturbance sources. The system has built-in capability to detect both known and unknown vibratory disturbance sources. Several soft computing techniques such as Kohonen's Self-Organizing Feature Map, Learning Vector Quantization, Back-Propagation Neural Networks, and Fuzzy Logic were used to design the system.

Jules, Kenol↗

Error Free Software

A mathematical theory for development of "higher order" software to catch computer mistakes resulted from a Johnson Space Center contract for Apollo spacecraft navigation. Two women who were involved in the project formed Higher Order Software, Inc. to develop and market the system of error analysis and correction. They designed software which is logically error-free, which, in one instance, was found to increase productivity by 600%. USE.IT defines its objectives using AXES -- a user can write in English and the system converts to computer languages. It is employed by several large corporations.

Source record↗

The Development of Design Tools for Fault Tolerant Quantum Dot Cellular Automata Based Logic

We are developing software to explore the fault tolerance of quantum dot cellular automata gate architectures in the presence of manufacturing variations and device defects. The Topology Optimization Methodology using Applied Statistics (TOMAS) framework extends the capabilities of the A Quantum Interconnected Network Array Simulator (AQUINAS) by adding front-end and back-end software and creating an environment that integrates all of these components. The front-end tools establish all simulation parameters, configure the simulation system, automate the Monte Carlo generation of simulation files, and execute the simulation of these files. The back-end tools perform automated data parsing, statistical analysis and report generation.

Armstrong, Curtis D.↗

Real Time On-line Space Research Laboratory Environment Monitoring with Off-line Trend and Prediction Analysis

One of the responsibilities of the NASA Glenn Principal Investigator Microgravity Services is to support NASA sponsored investigators in the area of reduced-gravity acceleration data analysis, interpretation and the monitoring of the reduced-gravity environment on-board various carriers. With the International Space Station currently operational, a significant amount of acceleration data is being down-linked and processed on ground for both the space station onboard environment characterization (and verification) and scientific experiments. Therefore, to help principal investigator teams monitor the acceleration level on-board the International Space Station to avoid undesirable impact on their experiment, when possible, the NASA Glenn Principal Investigator Microgravity Services developed an artificial intelligence monitoring system, which detects in near real time any change in the environment susceptible to affect onboard experiments. The main objective of the monitoring system is to help research teams identify the vibratory disturbances that are active at any instant of time onboard the International Space Station that might impact the environment in which their experiment is being conducted. The monitoring system allows any space research scientist, at any location and at any time, to see the current acceleration level on-board the Space Station via the World Wide Web. From the NASA Glenn s Exploration Systems Division web site, research scientists can see in near real time the active disturbances, such as pumps, fans, compressor, crew exercise, re-boost, extra-vehicular activity, etc., and decide whether or not to continue operating or stopping (or making note of such activity for later correlation with science results) their experiments based on the g-level associated with that specific event. A dynamic graphical display accessible via the World Wide Web shows the status of all the vibratory disturbance activities with their degree of confidence as well as their g-level contribution to the environment. The system can detect both known and unknown vibratory disturbance activities. It can also perform trend analysis and prediction by analyzing past data over many Increments of the space station for selected disturbance activities. This feature can be used to monitor the health of onboard mechanical systems to detect and prevent potential system failure as well as for use by research scientists during their science results analysis. Examples of both real time on-line vibratory disturbance detection and off-line trend analysis are presented in this paper. Several soft computing techniques such as Kohonen s Self-Organizing Feature Map, Learning Vector Quantization, Back-Propagation Neural Networks, and Fuzzy Logic were used to design the system.

Jules, Kenol↗

Digital design using selection operations

A digital integrated circuit chip is designed by identifying a logical structure to be implemented. This logical structure is represented in terms of a logical operations, at least 5% of which include selection operations. A determination is made of logic cells that correspond to an implementation of these logical operations.

Whitaker, Sterling R.↗

The J-2X Fuel Turbopump - Turbine Nozzle Low Cycle Fatigue Acceptance Rationale

The J-2X Fuel Turbopump (FTP) turbine, which drives the pump that feeds hydrogen to the J-2X engine for main combustion, is based on the J-2S design developed in the early 1970 s. Updated materials and manufacturing processes have been incorporated to meet current requirements. This paper addresses an analytical concern that the J-2X Fuel Turbine Nozzle Low Cycle Fatigue (LCF) analysis did not meet safety factor requirements per program structural assessment criteria. High strains in the nozzle airfoil during engine transients were predicted to be caused by thermally induced stresses between the vane hub, vane shroud, and airfoil. The heritage J-2 nozzle was of a similar design and experienced cracks in the same area where analysis predicted cracks in the J-2X design. Redesign options that did not significantly impact the overall turbine configuration were unsuccessful. An approach using component tests and displacement controlled fracture mechanics analysis to evaluate LCF crack initiation and growth rate was developed. The results of this testing and analysis were used to define the level of inspection on development engine test units. The programmatic impact of developing crack initiation/growth rate/arrest data was significant for the J-2X program. Final Design Certification Review acceptance logic will ultimately be developed utilizing this test and analytical data.

Hawkins, Lakiesha V.↗

Design and Stability of an On-Orbit Attitude Control System Using Reaction Control Thrusters

Principles for the design and stability of a spacecraft on-orbit attitude control system employing on-off Reaction Control System (RCS) thrusters is presented. Both the vehicle dynamics and the control system actuators are inherently nonlinear, hence traditional linear control system design approaches are not directly applicable. This paper has three main aspects: It summarizes key RCS control System design principles from the Space Shuttle and Space Station programs, it demonstrates a new approach to develop a linear model of a phase plane control system using describing functions, and applies each of these to the initial development of the NASA's next generation of upper stage vehicles. Topics addressed include thruster hardware specifications, phase plane design and stability, jet selection approaches, filter design metrics, and automaneuver logic.

Hall, Robert A.↗

From Machine Learning to Machine Reasoning: A Model-based Approach to Analyze Equipment Reliability Data

In current nuclear power plants (NPPs) a large amount of condition-based data which can be used to assess and monitor component health and performance. Assessing component health from such data can be performed with a large variety of methods. While the analysis of numeric data can be performed with several methods, the extraction of information from textual data remains a challenge. Currently employed natural language processing (NLP) methods do not really provide quantitative information that might be contained in IRs. In addition, the integration of numeric and textual data to identify possible causal relationships between data elements is still an unresolved challenge. This paper presents an approach to extract information from textual (e.g., incident or maintenance reports) and numeric data that relies on model based system engineer (MBSE) models. MBSE are diagrams designed to represent system and component dependencies (from both a form and functional point of view). In our approach, MBSE models emulate system engineer knowledge about component/system architecture. NLP methods are employed to perform syntactic and semantic analyses. Syntactic analysis analyzes the grammatical structure of a sentence while semantic analysis is designed to analyze the logic structure of a sentence. An innovative element of our approach is that semantic analysis uses MBSE models to identify links between textual elements. Similarly, numeric data is directly linked to elements of the MBSE models in order to map which functions are being monitored.

97 - MATHEMATICS AND COMPUTING↗

Genetic Algorithm Tuned Fuzzy Logic for Gliding Return Trajectories

The problem of designing and flying a trajectory for successful recovery of a reusable launch vehicle is tackled using fuzzy logic control with genetic algorithm optimization. The plant is approximated by a simplified three degree of freedom non-linear model. A baseline trajectory design and guidance algorithm consisting of several Mamdani type fuzzy controllers is tuned using a simple genetic algorithm. Preliminary results show that the performance of the overall system is shown to improve with genetic algorithm tuning.

Burchett, Bradley T.↗

A microprogrammable radar controller

The Wave Propagation Lab. has completed the design and construction of a microprogrammable radar controller for atmospheric wind profiling. Unlike some radar controllers using state machines or hardwired logic for radar timing, this design is a high speed programmable sequencer with signal processing resources. A block diagram of the device is shown. The device is a single 8 1/2 inch by 10 1/2 inch printed circuit board and consists of three main subsections: (1) the host computer interface; (2) the microprogram sequencer; and (3) the signal processing circuitry. Each of these subsections are described in detail.

Law, D. C.↗

Development of ferrite logic devices for an arithmetic processor

A number of fundamentally ultra-reliable, all-magnetic logic circuits are developed using as a basis a single element ferrite structure wired as a logic delay element. By making minor additions or changes to the basic wiring pattern of the delay element other logic functions such as OR, AND, NEGATION, MAJORITY, EXCLUSIVE-OR, and FAN-OUT are developed. These logic functions are then used in the design of a full-adder, a set/reset flip-flop, and an edge detector. As a demonstration of the utility of all the developed devices, an 8-bit, all-magnetic, logic arithmetic unit capable of controlled addition, subtraction, and multiplication is designed. A new basic ferrite logic element and associated complementary logic scheme with the potential of improved performance is also described. Finally, an improved batch process for fabricating joint-free power drive and logic interconnect conductors for this basic class of all-magnetic logic is presented.

Heckler, C. H., Jr.↗

Intelligent control based on fuzzy logic and neural net theory

In the conception and design of intelligent systems, one promising direction involves the use of fuzzy logic and neural network theory to enhance such systems' capability to learn from experience and adapt to changes in an environment of uncertainty and imprecision. Here, an intelligent control scheme is explored by integrating these multidisciplinary techniques. A self-learning system is proposed as an intelligent controller for dynamical processes, employing a control policy which evolves and improves automatically. One key component of the intelligent system is a fuzzy logic-based system which emulates human decision making behavior. It is shown that the system can solve a fairly difficult control learning problem. Simulation results demonstrate that improved learning performance can be achieved in relation to previously described systems employing bang-bang control. The proposed system is relatively insensitive to variations in the parameters of the system environment.

Lee, Chuen-Chien↗