SYSTEM RELIABILITY EVALUATION FROM SUCCESS AND FAILURE DATA
Use of success and failure data in reliability engineering
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Use of success and failure data in reliability engineering
System for switching circuits between on line and off line switching computers at NASA communications network /NASCOM/ primary and remote switching centers
A grouping into four classes is proposed for all reliability computations that are related to electronic equipment. Examples are presented of reliability computations in three of these four classes. Each of the three specific reliability tasks described was originally undertaken to satisfy an engineering need for reliability data. The form and interpretation of the print-out of the specific reliability computations is presented. The justification for the costs of these computations is indicated. The skills of the personnel used to conduct the analysis, the interfaces between the personnel, and the timing of the projects is discussed.
Goddard activities are reported for 1973. An eight-year flight schedule for projected space missions is presented. Data acquired by spacecraft in the following disciplines are described: stellar ultraviolet, stellar X-rays, stellar gamma rays, solar radiation, radio astronomy, particles/fields, magnetosphere, aurora, and the upper atmosphere.
The reliability of adaptive controls for future aircraft are discussed. The research, formulation, and experimentation for improved aircraft performance are considered.
The major short life, unreliable, and high maintenance engine and power components and subsystems in current civil helicopters were identified. Categories included both reciprocating and turbine engines, single and multiple engine configurations, single and tandem trotor vehicles, and light, medium, and heavy helicopters. The major focus was on the following parameters: accident rate data; maintenance rate data; and direct operator input.
Reliability and availability characteristics of the DSN traveling wave maser (TWM) Assemblies are reported for the years 1981 through 1983, the charcteristics determined are: mean time between failures (MTBF) - 1200 hours; mean time to restore service (MTTRS) - 2.5 hours; and availability - 99.83%. The TWM MTBF is very good as compared to other DSN subsystems and assemblies. The TWM MTTRS is currently about three times as long as the average of other DSN subsystems. The dominant cause of TWM failures is contamination of the helium gas in the closed cycle refrigerators. Station configurations that do not provide TWM redundancy are subject to reception outages for long periods of time. Recommendations are made to improve the TWM Assembly availability characteristics for future mission support operations.
A real-time Sensor Failure Simulator (SFS) was designed and assembled for the Advanced Detection, Isolation, and Accommodation (ADIA) program. Various designs were considered. The design chosen features an IBM-PC/XT. The PC is used to drive analog circuitry for simulating sensor failures in real-time. A user defined scenario describes the failure simulation for each of the five incoming sensor signals. Capabilities exist for editing, saving, and retrieving the failure scenarios. The SFS has been tested closed-loop with the Controls Interface and Monitoring (CIM) unit, the ADIA control, and a real-time F100 hybrid simulation. From a productivity viewpoint, the menu driven user interface has proven to be efficient and easy to use. From a real-time viewpoint, the software controlling the simulation loop executes at greater than 100 cycles/sec.
Consideration is given to the intuitively appealing notion of discarding sensor values which are strongly suspected of being erroneous in a modified approximate agreement protocol. Approximate agreement with editing imposes a time bound upon the convergence of the protocol - no such bound was possible for the original approximate agreement protocol. This new approach is potentially useful in the construction of asynchronous fault tolerant systems. The main result is that a wild-point replacement technique called t-worst editing can be shown to guarantee convergence of the approximate agreement protocol to a valid agreement value. Results are presented for a four-processor synchronous system in which a single processor may be faulty.
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Microsemi (Microchip) RTG4 embedded triple modular redundant (TMR) phase-locked-loop (PLL) SEU data is presented. SEU data analysis includes: 1) Evaluation of heavy-ion beam angular effects (rectangular parallel pipe (RPP) or no RPP), 2) Importance of finding linear energy transfer (LET) onset (L0), 3) Comparison of prediction rate techniques.
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Harnessing the power of waves requires more than just putting devices in the ocean - it takes tools that can refine and accelerate innovation before the first deployment. That's where NLR's largeamplitude motion platform, or LAMP, comes in. LAMP is a six-degree-of-freedom motion system designed to replicate the response of a wave energy converter (WEC) device in realistic ocean conditions. By letting researchers evaluate WEC performance in a safe, controlled lab environment before moving offshore, LAMP helps accelerate innovation while reducing risk. An NLR report, titled Initial Characterization of the NLR LargeAmplitude Motion Platform (https://www.nrel.gov/docs/fy26osti/93733.pdf), provides a deeper understanding of LAMP's capabilities and also lays the groundwork for future advancements in WEC testing methodologies. Researchers studied LAMP's amplitude and frequency limits across different payloads and collected data from 16 test profiles. Testing demonstrated that platform accuracy remained consistent across all payloads evaluated; researchers expect similar accuracy up to LAMP's 10,000-kilogram capacity limit. The measured position limits for single degrees of freedom experienced by WECs, including surge, sway, heave, roll, pitch, and yaw, also exceeded the original manufacturer specifications, providing new insight into the true boundaries of the system.
Reliable VTOL flight control system
Reliable systems health management is an important research area of NASA. A health management system that can accurately and quickly diagnose faults in various on-board systems of a vehicle will play a key role in the success of current and future NASA missions. We introduce in this paper the ProDiagnose algorithm, a diagnostic algorithm that uses a probabilistic approach, accomplished with Bayesian Network models compiled to Arithmetic Circuits, to diagnose these systems. We describe the ProDiagnose algorithm, how it works, and the probabilistic models involved. We show by experimentation on two Electrical Power Systems based on the ADAPT testbed, used in the Diagnostic Challenge Competition (DX 09), that ProDiagnose can produce results with over 96% accuracy and less than 1 second mean diagnostic time.