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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Structural Probability Concepts Adapted to Electrical Engineering

Through the use of equivalent variable analogies, the authors demonstrate how an electrical subsystem can be modeled by an equivalent structural subsystem. This allows the electrical subsystem to be probabilistically analyzed by using available structural reliability computer codes such as NESSUS. With the ability to analyze the electrical subsystem probabilistically, we can evaluate the reliability of systems that include both structural and electrical subsystems. Common examples of such systems are a structural subsystem integrated with a health-monitoring subsystem, and smart structures. Since these systems have electrical subsystems that directly affect the operation of the overall system, probabilistically analyzing them could lead to improved reliability and reduced costs. The direct effect of the electrical subsystem on the structural subsystem is of secondary order and is not considered in the scope of this work.

Steinberg, Eric P.↗
NASA NTRS2004

Reliable and Affordable Control Systems Active Combustor Pattern Factor Control

Active, closed-loop control of combustor pattern factor is a cooperative effort between Honeywell (formerly AlliedSignal) Engines and Systems and the NASA Glenn Research Center to reduce emissions and turbine-stator vane temperature variations, thereby enhancing engine performance and life, and reducing direct operating costs. Total fuel flow supplied to the engine is established by the speed/power control, but the distribution to individual atomizers will be controlled by the Active Combustor Pattern Factor Control (ACPFC). This system consist of three major components: multiple, thin-film sensors located on the turbine-stator vanes; fuel-flow modulators for individual atomizers; and control logic and algorithms within the electronic control.

McCarty, Bob↗
NASA NTRS2012

Hardware for Accelerating N-Modular Redundant Systems for High-Reliability Computing

A hardware unit has been designed that reduces the cost, in terms of performance and power consumption, for implementing N-modular redundancy (NMR) in a multiprocessor device. The innovation monitors transactions to memory, and calculates a form of sumcheck on-the-fly, thereby relieving the processors of calculating the sumcheck in software

Dobbs, Carl, Sr.↗
NASA NTRS1989

Three approaches to reliability analysis

It is noted that current reliability analysis tools differ not only in their solution techniques, but also in their approach to model abstraction. The analyst must be satisfied with the constraints that are intrinsic to any combination of solution technique and model abstraction. To get a better idea of the nature of these constraints, three reliability analysis tools (HARP, ASSIST/SURE, and CAME) were used to model portions of the Integrated Airframe/Propulsion Control System architecture. When presented with the example problem, all three tools failed to produce correct results. In all cases, either the tool or the model had to be modified. It is suggested that most of the difficulty is rooted in the large model size and long computational times which are characteristic of Markov model solutions.

Mesh networks↗
DOE OSTI2016

Software Dependability

The purpose of this paper is to provide a brief introduction of Software Dependability and a summary of lessons learned. The components of Software Dependability vary among standards, however there is agreement among the standards that reliability, availability and maintainability are some the main components of dependability. Safety is also a main component is safety systems. Although reliability and safety are similar there is an additional difference, safety can withstand some level of fault tolerance. For the purposes of this discussion Software Dependability includes reliability, availability, maintainability and safety. Software Dependability: Trustworthiness of a computer system such that reliance can be justifiably placed on the service it delivers. Reliability, availability, and maintainability are aspects of dependability. Reliability: The ability of a system or component to perform its required functions under stated conditions for a specified period of time. Availability: The degree to which a system or component is operational and accessible when required for use. Often expressed as a probability. Maintainability: Speed and ease with which a program can be corrected or changed. Safety: a measure of the length of time the software system can be expected to run before failing in such a way as to cause a system hazard. (author)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1985

The use of automatic programming techniques for fault tolerant computing systems

It is conjectured that the production of software for ultra-reliable computing systems such as required by Space Station, aircraft, nuclear power plants and the like will require a high degree of automation as well as fault tolerance. In this paper, the relationship between automatic programming techniques and fault tolerant computing systems is explored. Initial efforts in the automatic synthesis of code from assertions to be used for error detection as well as the automatic generation of assertions and test cases from abstract data type specifications is outlined. Speculation on the ability to generate truly diverse designs capable of recovery from errors by exploring alternate paths in the program synthesis tree is discussed. Some initial thoughts on the use of knowledge based systems for the global detection of abnormal behavior using expectations and the goal-directed reconfiguration of resources to meet critical mission objectives are given. One of the sources of information for these systems would be the knowledge captured during the automatic programming process.

Wild, C.↗
NASA NTRS1983

The reliability analysis of a separated, dual fail operational redundant strapdown IMU

A methodology for quantitatively analyzing the reliability of redundant avionics systems, in general, and the dual, separated Redundant Strapdown Inertial Measurement Unit (RSDIMU), in particular, is presented. The RSDIMU is described and a candidate failure detection and isolation system presented. A Markov reliability model is employed. The operational states of the system are defined and the single-step state transition diagrams discussed. Graphical results, showing the impact of major system parameters on the reliability of the RSDIMU system, are presented and discussed.

Motyka, P.↗