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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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Rigorous analysis applied early in design effort. Method of identifying potential inadequacies and modes and effects of failures caused by inadequacies (failure-modes-and-effects analysis or "FMEA" for short) devised for application to software logic.
The goal of this work was to analyze the potential of neural networks and fuzzy logic methods to develop approximate response surfaces as process modeling, that is for mapping of input into output. Structural response was chosen as an example. Each of the many methods surveyed are explained and the results are presented. Future research directions are also discussed.
This paper presents a fuzzy-logic approach to the synthesis of synchronization control for magnetically suspended rotor system. The synchronization control enables a whirling rotor to undergo synchronous motion along the magnetic bearing axes; thereby avoiding the gyroscopic effect that degrade the stability of rotor systems when spinning at high speed. The control system features a fuzzy controller acting on the magnetic bearing device, in which the fuzzy inference system trained through fuzzy rules to minimize the differential errors between four bearing axes so that an error along one bearing axis can affect the overall control loop for the motion synchronization. Numerical simulations of synchronization control for the magnetically suspended rotor system are presented to show the effectiveness of the present approach.
Through the evolutionary development of the Simulation by Logical Modeling System (SIBYL) we have re-engineered the expensive and complex IBM mainframe based Long-term Hardware Projection Model (LHPM) to a robust cost-effective computer based mode that is easy to use. We achieved significant cost reductions and improved productivity in preparing long-term forecasts of Space Shuttle Main Engine (SSME) hardware. The LHPM for the SSME is a stochastic simulation model that projects the hardware requirements over 10 years. SIBYL is now the primary modeling tool for developing SSME logistics proposals and Program Operating Plan (POP) for NASA and divisional marketing studies.
Research conducted with the support of NASA Grant NCC2-275 has been focused in the main on the development of fuzzy logic and soft computing methodologies and their applications to systems analysis and control. with emphasis 011 problem areas which are of relevance to NASA's missions. One of the principal results of our research has been the development of a new methodology called Computing with Words (CW). Basically, in CW words drawn from a natural language are employed in place of numbers for computing and reasoning. There are two major imperatives for computing with words. First, computing with words is a necessity when the available information is too imprecise to justify the use of numbers, and second, when there is a tolerance for imprecision which can be exploited to achieve tractability, robustness, low solution cost, and better rapport with reality. Exploitation of the tolerance for imprecision is an issue of central importance in CW.
This paper discusses the development of a prototype alerting system for a conceptual Free Flight environment. The concept assumes that datalink between aircraft is available and that conflicts are primarily resolved on the flight deck. Four alert stages are generated depending on the likelihood of a conflict. If the conflict is not resolved by the flight crews, Air Traffic Control is notified to take over separation authority. The alerting logic is based on probabilistic analysis through modeling of aircraft sensor and trajectory uncertainties. Monte Carlo simulations were used over a range of encounter situations to determine conflict probability. The four alert stages were then defined based on probability of conflict and on the number of avoidance maneuvers available to the flight crew. Preliminary results from numerical evaluations and from a piloted simulator study at NASA Ames Research Center are summarized.
This column will be provided each quarter as a source for reliability, radiation results, NASA capabilities, and other information on programmable logic devices and related applications. This quarter's column will include some announcements and some recent radiation test results and evaluations of interest. Specifically, the following topics will be covered: the Military and Aerospace Applications of Programmable Devices and Technologies Conference to be held at GSFC in September, 1998, proton test results, heavy ion test results, and some total dose results.
Digital Particle Image Velocimetry (DPIV) is an instantaneous, planar velocity measurement technique that is ideally suited for studying transient flow phenomena in high speed turbomachinery. DPIV is being actively used at the NASA Glenn Research Center to study both stable and unstable operating conditions in a high speed centrifugal compressor. Commercial PIV systems are readily available which provide near real time feedback of the PIV image data quality. These commercial systems are well designed to facilitate the expedient acquisition of PIV image data. However, as with any general purpose system, these commercial PIV systems do not meet all of the data processing needs required for PIV image data reduction in our compressor research program. An in-house PIV PROCessing (PIVPROC) code has been developed for reducing PIV data. The PIVPROC software incorporates fuzzy logic data validation for maximum information recovery from PIV image data. PIVPROC enables combined cross-correlation/particle tracking wherein the highest possible spatial resolution velocity measurements are obtained.
This column will be provided each quarter as a source for reliability, radiation results, NASA capabilities, and other information on programmable logic devices and related applications. This quarter the focus is on some experimental data on low voltage drop out regulators to support mixed 5 and 3.3 volt systems. A discussion of the Small Explorer WIRE spacecraft will also be given. Lastly, we show take a first look at robust state machines in Hardware Description Languages (VHDL) and their use in critical systems. If you have information that you would like to submit or an area you would like discussed or researched, please give me a call or e-mail.
This column will be provided each quarter as a source for reliability, radiation results, NASA capabilities, and other information on programmable logic devices and related applications. This quarter's column will include some announcements and some recent radiation test results and evaluations of interest. Specifically, the following topics will be covered: the Military and Aerospace Applications of Programmable Devices and Technologies Conference to be held at GSFC in September, 1998, proton test results, and some total dose results.
Our earlier research on computing with words (CW) has led to a new direction in fuzzy logic which points to a major enlargement of the role of natural languages in information processing, decision analysis and control. This direction is based on the methodology of computing with words and embodies a new theory which is referred to as the computational theory of perceptions (CTP). An important feature of this theory is that it can be added to any existing theory - especially to probability theory, decision analysis, and control - and enhance the ability of the theory to deal with real-world problems in which the decision-relevant information is a mixture of measurements and perceptions. The new direction is centered on an old concept - the concept of a perception - a concept which plays a central role in human cognition. The ability to reason with perceptions perceptions of time, distance, force, direction, shape, intent, likelihood, truth and other attributes of physical and mental objects - underlies the remarkable human capability to perform a wide variety of physical and mental tasks without any measurements and any computations. Everyday examples of such tasks are parking a car, driving in city traffic, cooking a meal, playing golf and summarizing a story. Perceptions are intrinsically imprecise. Imprecision of perceptions reflects the finite ability of sensory organs and ultimately, the brain, to resolve detail and store information. More concretely, perceptions are both fuzzy and granular, or, for short, f-granular. Perceptions are f-granular in the sense that: (a) the boundaries of perceived classes are not sharply defined; and (b) the elements of classes are grouped into granules, with a granule being a clump of elements drawn together by indistinguishability, similarity. proximity or functionality. F-granularity of perceptions may be viewed as a human way of achieving data compression. In large measure, scientific progress has been, and continues to be, driven by a quest to progress from perceptions to measurements. Pursuit of this aim has led to brilliant successes. But alongside the successes stand problems whose solutions are not in sight. Representative of such problems is the problem of automation of driving in city traffic. In this case, as in many others, what can be done with ease by humans - without any measurements and a computations - is an intractable task for machines.
Complex electronics and sensors are increasingly being relied on to enhance the capabilities and efficiency of modernjet aircraft. Some of these electronics and sensors monitor and control vital engine components and aerosurfaces that operate at high temperatures above 300 C. However, since today's silicon-based electronics technology cannot function at such high temperatures, these electronics must reside in environmentally controlled areas. This necessitates either the use of long wire runs between sheltered electronics and hot-area sensors and controls, or the fuel cooling of electronics and sensors located in high-temperature areas. Both of these low-temperature-electronics approaches suffer from serious drawbacks in terms of increased weight, decreased fuel efficiency, and reduction of aircraft reliability. A family of high-temperature electronics and sensors that could function in hot areas would enable substantial aircraft performance gains. Especially since, in the future, some turbine-engine electronics may need to function at temperatures as high as 600 C. This paper reports the fabrication and demonstration of the first semiconductor digital logic gates ever to function at 600 C. Key obstacles blocking the realization of useful 600 C turbine engine integrated sensor and control electronics are outlined.
This column will be provided each quarter as a source for reliability, radiation results, NASA capabilities, and other information on programmable logic devices and related applications. This quarter will start a series of notes concentrating on analysis techniques with this issues section discussing worst-case analysis requirements.
Bridge faults, especially in CMOS circuits, have unique characteristics which make them difficult to detect during testing. This paper presents a technique for detecting bridge faults which have an effect on the output of CMOS Domino logic circuits. The faults are modeled at the transistor level and this technique is based on analyzing the off-set of the function during off-line testing.
The purpose of fault detection is to identify when a fault or failure has occurred in a system such as an aircraft or expendable launch vehicle. The faults may occur in sensors, actuators, structural components, etc. One of the primary approaches to model-based fault detection relies on analytical redundancy. That is the output of a computer-based model (actually a state estimator) is compared with the sensor measurements of the actual system to determine when a fault has occurred. Unfortunately, the state estimator is based on an idealized mathematical description of the underlying plant that is never totally accurate. As a result of these modeling errors, false alarms can occur. This research uses mixed structured singular value theory, a relatively recent and powerful robustness analysis tool, to develop robust estimators and demonstrates the use of these estimators in fault detection. To allow qualitative human experience to be effectively incorporated into the detection process fuzzy logic is used to predict the seriousness of the fault that has occurred.
This report will be provided each quarter as a source for reliability, radiation results, NASA capabilities, and other information on programmable logic devices and related applications. This quarter will continue a series of notes concentrating on analysis techniques with this issue's section discussing the use of Root-Sum-Square calculations for digital delays.
We present an algorithm for efficiently testing Linear Temporal Logic (LTL) formulae on finite execution traces. The standard models of LTL are infinite traces, reflecting the behavior of reactive and concurrent systems which conceptually may be continuously alive. In most past applications of LTL. theorem provers and model checkers have been used to formally prove that down-scaled models satisfy such LTL specifications. Our goal is instead to use LTL for up-scaled testing of real software applications. Such tests correspond to analyzing the conformance of finite traces against LTL formulae. We first describe what it means for a finite trace to satisfy an LTL property. We then suggest an optimized algorithm based on transforming LTL formulae. The work is done using the Maude rewriting system. which turns out to provide a perfect notation and an efficient rewriting engine for performing these experiments.
The problem of testing a linear temporal logic (LTL) formula on a finite execution trace of events, generated by an executing program, occurs naturally in runtime analysis of software. We present an algorithm which takes an LTL formula and generates an efficient dynamic programming algorithm. The generated algorithm tests whether the LTL formula is satisfied by a finite trace of events given as input. The generated algorithm runs in linear time, its constant depending on the size of the LTL formula. The memory needed is constant, also depending on the size of the formula.