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Results for “COMPONENT RELIABILITY”

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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1975

Emotional-volitional components of operator reliability

Sensorimotor function testing in a tracking task under stressfull working conditions established a psychological characterization for a successful aviation pilot: Motivation significantly increased the reliability and effectiveness of their work. Their acitivities were aimed at suppressing weariness and the feeling of fear caused by the stress factors; they showed patience, endurance, persistence, and a capacity for lengthy volitional efforts.

Mileryan, Y. A.↗
NASA NTRSDate not supplied

Design for Reliability (DfR) in Space Life Support

The engineering process of Design for Reliability (DfR) is well established in the automotive and aerospace industries. DfR should be useful in the future development of space life support systems. DfR is a sequence of tasks that develop system requirements and plan reliability analysis and testing. First and fundamentally, the reliability requirement is defined. Next the system reliability model is developed, often using a reliability block diagram. The overall system reliability requirement is allocated to the subsystems and an estimate of the attainable reliability is made. This expected reliability can be improved by simplifying the design by removing components or by replacing less reliable components. Improving reliability can require difficult compromises, such as reducing performance requirements, increasing budget, or extending testing. The actual system reliability can be determined only by testing, which should continue long enough to provide the required confidence in the measured value. New systems often have unexpected design errors that cause failures in early testing. The usual reliability improvement process of testing, finding the failure modes, and redesigning to remove them reduces the failure rate and is referred to as “reliability growth.” After redesign has been completed, the system should be further tested to determine the actual achieved reliability more accurately. If the final system failure rate is too high, redundant systems can be used to improve overall operational reliability. Adding redundancy simply to increase the one- or two-fault tolerance metric may sometimes reduce reliability. Reliability can be improved in three ways: redesigning the system to include more reliable subsystems and components, reliability growth testing and failure mode removal, and by using parallel redundant systems. DfR should combine these approaches to achieve the required reliability while managing performance, cost, and schedule.

Reliability↗
NASA NTRSDate not supplied

Design for Reliability (DfR) in Space Life Support

The engineering process of Design for Reliability (DfR) is well established in the automotive and aerospace industries. DfR should be useful in the future development of space life support systems. DfR is a sequence of tasks that develop system requirements and plan reliability analysis and testing. First and fundamentally, the reliability requirement is defined. Next the system reliability model is developed, often using a reliability block diagram. The overall system reliability requirement is allocated to the subsystems and an estimate of the attainable reliability is made. This expected reliability can be improved by simplifying the design by removing components or by replacing less reliable components. Improving reliability can require difficult compromises, such as reducing performance requirements, increasing budget, or extending testing. The actual system reliability can be determined only by testing, which should continue long enough to provide the required confidence in the measured value. New systems often have unexpected design errors that cause failures in early testing. The usual reliability improvement process of testing, finding the failure modes, and redesigning to remove them reduces the failure rate and is referred to as “reliability growth.” After redesign has been completed, the system should be further tested to determine the actual achieved reliability more accurately. If the final system failure rate is too high, redundant systems can be used to improve overall operational reliability. Adding redundancy simply to increase the one- or two-fault tolerance metric may sometimes reduce reliability. Reliability can be improved in three ways: redesigning the system to include more reliable subsystems and components, reliability growth testing and failure mode removal, and by using parallel redundant systems. DfR should combine these approaches to achieve the required reliability while managing performance, cost, and schedule.

Reliability↗
NASA NTRS2012

Scaled CMOS Reliability and Considerations for Spacecraft Systems : Bottom-Up and Top-Down Perspectives

The recently launched Mars Science Laboratory (MSL) flagship mission, named Curiosity, is the most complex rover ever built by NASA and is scheduled to touch down on the red planet in August, 2012 in Gale Crater. The rover and its instruments will have to endure the harsh environments of the surface of Mars to fulfill its main science objectives. Such complex systems require reliable microelectronic components coupled with adequate component and system-level design margins. Reliability aspects of these elements of the spacecraft system are presented from bottom- up and top-down perspectives.

derating thermal margin↗
NASA NTRS1998

Damage Tolerance and Reliability of Turbine Engine Components

A formal method is described to quantify structural damage tolerance and reliability in the presence of multitude of uncertainties in turbine engine components. The method is based at the materials behavior level where primitive variables with their respective scatters are used to describe that behavior. Computational simulation is then used to propagate those uncertainties to the structural scale where damage tolerance and reliability are usually specified. Several sample cases are described to illustrate the effectiveness, versatility, and maturity of the method. Typical results from these methods demonstrate that the methods are mature and that they can be used for future strategic projections and planning to assure better, cheaper, faster products for competitive advantages in world markets. These results also indicate that the methods are suitable for predicting remaining life in aging or deteriorating structures.

Chamis, Christos C.↗
NASA NTRS1999

Damage Tolerance and Reliability of Turbine Engine Components

A formal method is described to quantify structural damage tolerance and reliability in the presence of multitude of uncertainties in turbine engine components. The method is based at the materials behaviour level where primitive variables with their respective scatters are used to describe the behavior. Computational simulation is then used to propagate those uncertainties to the structural scale where damage tolerance and reliability are usually specified. Several sample cases are described to illustrate the effectiveness, versatility, and maturity of the method. Typical results from these methods demonstrate that the methods are mature and that they can be used for future strategic projections and planning to assure better, cheaper, faster, products for competitive advantages in world markets. These results also indicate that the methods are suitable for predicting remaining life in aging or deteriorating structures.

Chamis, Christos C.↗
NASA NTRS1999

Damage Tolerance and Reliability of Turbine Engine Components

This report describes a formal method to quantify structural damage tolerance and reliability in the presence of a multitude of uncertainties in turbine engine components. The method is based at the material behavior level where primitive variables with their respective scatter ranges are used to describe behavior. Computational simulation is then used to propagate the uncertainties to the structural scale where damage tolerance and reliability are usually specified. Several sample cases are described to illustrate the effectiveness, versatility, and maturity of the method. Typical results from this method demonstrate that it is mature and that it can be used to probabilistically evaluate turbine engine structural components. It may be inferred from the results that the method is suitable for probabilistically predicting the remaining life in aging or deteriorating structures, for making strategic projections and plans, and for achieving better, cheaper, faster products that give competitive advantages in world markets.

Chamis, Christos C.↗
NASA NTRS1973

Modern methodology of designing target reliability into rotating mechanical components

Experimentally determined distributional cycles-to-failure versus maximum alternating nominal strength (S-N) diagrams, and distributional mean nominal strength versus maximum alternating nominal strength (Goodman) diagrams are presented. These distributional S-N and Goodman diagrams are for AISI 4340 steel, R sub c 35/40 hardness, round, cylindrical specimens 0.735 in. in diameter and 6 in. long with a circumferential groove 0.145 in. radius for a theoretical stress concentration = 1.42 and 0.034 in. radius for a stress concentration = 2.34. The specimens are subjected to reversed bending and steady torque in specially built, three complex-fatigue research machines. Based on these results, the effects on the distributional S-N and Goodman diagrams and on service life of superimposing steady torque on reversed bending are established, as well as the effect of various stress concentrations. In addition a computer program for determining the three-parameter Weibull distribution representing the cycles-to-failure data, and two methods for calculating the reliability of components subjected to cumulative fatigue loads are given.

Kececioglu, D. B.↗
NASA NTRS2020

A Method and Model to Predict Initial Failure Rates

It has long been well known that actual system reliability typically falls well short of early estimates. Failure rates are often ten or more times higher than anticipated. Many reasons have been given for this, but over-optimism is the fundamental cause of too-favorable reliability predictions. Most forecasts of reliability are essentially best-case scenarios, as are predictions of budget and schedule. Confident engineers assemble estimates bottom-up, including the known factors and ignoring problems that they hope won’t happen. Traditional reliability estimation is based on simply summing up the component failure rates. This ignores most actual failure causes. The way to reduce over-optimism is to use the historical system level failure rate from similar projects. Adjustments should not be made based purely on engineering judgment, but only if there is so logical quantitative justification. The traditional component-based reliability estimate is useful as a lower bound on the system failure rate. The difference between this lower bound component-based reliability and the historical system level reliability indicates how much of the total failure rate is due to system level problems rather than component failures.

Jones, Harry W.↗
NASA NTRS2020

A Method and Model to Predict Initial Failure Rates

It has long been well known that actual system reliability typically falls well short of early estimates. Failure rates are often ten or more times higher than anticipated. Many reasons have been given for this, but over-optimism is the fundamental cause of too-favorable reliability predictions. Most forecasts of reliability are essentially best-case scenarios, as are predictions of budget and schedule. Confident engineers assemble estimates bottom-up, including the known factors and ignoring problems that they hope won't happen. Traditional reliability estimation is based on simply summing up the component failure rates. This ignores most actual failure causes. The way to reduce over-optimism is to use the historical system level failure rate from similar projects. Adjustments should not be made based purely on engineering judgment, but only if there is so logical quantitative justification. The traditional component-based reliability estimate is useful as a lower bound on the system failure rate. The difference between this lower bound component-based reliability and the historical system level reliability indicates how much of the total failure rate is due to system level problems rather than component failures

Jones, Harry W.↗