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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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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

Correlation study between vibrational environmental and failure rates of civil helicopter components

An investigation of two selected helicopter types, namely, the Models 206A/B and 212, is reported. An analysis of the available vibration and reliability data for these two helicopter types resulted in the selection of ten components located in five different areas of the helicopter and consisting primarily of instruments, electrical components, and other noncritical flight hardware. The potential for advanced technology in suppressing vibration in helicopters was assessed. The are still several unknowns concerning both the vibration environment and the reliability of helicopter noncritical flight components. Vibration data for the selected components were either insufficient or inappropriate. The maintenance data examined for the selected components were inappropriate due to variations in failure mode identification, inconsistent reporting, or inaccurate informaton.

Alaniz, O.↗
NASA NTRS1976

Voltage stress effects on microcircuit accelerated life test failure rates

The applicability of Arrhenius and Eyring reaction rate models for describing microcircuit aging characteristics as a function of junction temperature and applied voltage was evaluated. The results of a matrix of accelerated life tests with a single metal oxide semiconductor microcircuit operated at six different combinations of temperature and voltage were used to evaluate the models. A total of 450 devices from two different lots were tested at ambient temperatures between 200 C and 250 C and applied voltages between 5 Vdc and 15 Vdc. A statistical analysis of the surface related failure data resulted in bimodal failure distributions comprising two lognormal distributions; a 'freak' distribution observed early in time, and a 'main' distribution observed later in time. The Arrhenius model was shown to provide a good description of device aging as a function of temperature at a fixed voltage. The Eyring model also appeared to provide a reasonable description of main distribution device aging as a function of temperature and voltage. Circuit diagrams are shown.

Johnson, G. M.↗
NASA NTRSDate not supplied

The System Complexity Metric (SCM) Explains Systems Design and is Correlated with Cost and Failure Rate

The human short term memory span and working capacity is limited to three to five items, especially if they are organized complex “chunks” of information. The impression of complexity occurs when a system is simply difficult to understand, where there is no apparent pattern to predict its behavior. Hierarchical systems design can reduce perceived complexity and increase the amount of information that can be managed. The SCM was developed to measure complexity and help compare proposed overall system architectures before detailed design information is available. The SCM is defined as the sum of the number of major nodes, N, in the system block diagram plus the number of one-way interactions, I, between the nodes. SCM = N + I. SCM’s are easily determined by direct inspection of high-level block diagrams of life support systems. Axiomatic design develops a hierarchy of subsystem requirements and designs together in a top-down, back-and-forth process. A coupling matrix is used to control the relationships between the subsystem functions and design concepts. Axiomatic design can improve system design by decoupling requirements and designs. Axiomatic design was applied to the planning of a closed life support system, similar to that used on the International Space Station. A materially open as opposed to a closed system design was created by removing the interconnections required to close the system. The open system had the same number of designed subsystems as the closed system, but it had many fewer interconnections and its SCM was lower by about half. The costs were estimated and the MTBF (Mean Time Before Failure) tabulated for open and closed space life support systems. The estimated costs were linearly proportional to SCM for the wide variations of SCM in life support, but small differences may not be significant. The flight and preflight MTBF’s both declined exponentially with increasing MTBF, faster than MTBF-2, even though the preflight estimated MTBF’s were about ten times higher than the flight MTBF’s.

System Complexity Metric (SCM)↗
NASA NTRS1972

Development of KSC program for investigating and generating field failure rates. Volume 1: Summary and overview

A summary of the KSC program for investigating the reliability aspects of the ground support activities is presented. An analysis of unsatisfactory condition reports (RC), and the generation of reliability assessment of components based on the URC are discussed along with the design considerations for attaining reliable real time hardware/software configurations.

Bean, E. E.↗
NASA NTRS2017

Lognormal Uncertainty Estimation for Failure Rates

"Uncertainty analysis itself is uncertain, therefore, you cannot evaluate it exactly," Source Uncertain. Quantitative results for aerospace engineering problems are influenced by many sources of uncertainty. Uncertainty analysis aims to make a technical contribution to decision-making through the quantification of uncertainties in the relevant variables as well as through the propagation of these uncertainties up to the result. Uncertainty can be thought of as a measure of the 'goodness' of a result and is typically represented as statistical dispersion. This presentation will explain common measures of centrality and dispersion; and-with examples-will provide guidelines for how they may be estimated to ensure effective technical contributions to decision-making.

Britton, Paul T.↗
NASA NTRS1980

JANTX1N5554 switching diode

Micro Semiconductor and Semtech diodes were tested. In group 1 tests Micro Semiconductor and Semtech lot testing was stopped because of excess failure rate. Failure analysis was performed on group 1 and 3 because of apparent failure mode.

Source record↗
NASA NTRS1986

Reliability Research for Photovoltaic Modules

Report describes research approach used to improve reliability of photovoltaic modules. Aimed at raising useful module lifetime to 20 to 30 years. Development of cost-effective solutions to module-lifetime problem requires compromises between degradation rates, failure rates, and lifetimes, on one hand, and costs of initial manufacture, maintenance, and lost energy, on other hand. Life-cycle costing integrates disparate economic terms, allowing cost effectiveness to be quantified, allowing comparison of different design alternatives.

Ross, Ronald J., Jr.↗
NASA NTRSDate not supplied

Analysis and Optimization of Test Plans for Advanced Exploration Systems Reliability and Supportability

Future crewed exploration missions beyond Low Earth Orbit (LEO) will operate farther from Earth and be logistically isolated for longer than any previous human spaceflight mission. Under these conditions, supportability and reliability willbestronger drivers of mission mass and risk than they have been in the past. Items with high failure rates, or uncertain failure rates, can result in high spares mass requirements and/or high risk on deep space missions. Testing is a critical element of system development which provides the opportunity to identify and resolve design issues, defects, or other failure modes before they cause problems during a mission. Reliability growth programs can reduce failure rates by identifying and remove failure modes via design changes, and long-duration life testing can provide valuable data to reduce failure rate estimate uncertainty and verify (to some level of confidence) that components are as reliable as expected. Testing activities take time and resources, however, and must be incorporated into program plans in order to be fully effective. This paper presents an integrated reliability test plan analysis and optimization methodology, which has been used to inform Advanced Exploration Systems (AES) Life Support Systems (LSS) ground test planning for future missions. The methodology determines the optimal number of test units to purchase and allocation of test time –split between reliability growth and uncertainty reduction testing –across a given set of items in order to minimize spares mass for a given mission under constraints on total test cost and schedule. Model outputs also include expected spares mass after testing and the expected number of modifications or refurbishments during testing, both of which can inform program planning. Discussion of the model, conclusions, and future work are also presented.

Testing↗
NASA NTRSDate not supplied

Analysis and Optimization of Test Plans for Advanced Exploration Systems Reliability and Supportability

Future crewed exploration missions beyond Low Earth Orbit (LEO) will operate farther from Earth and be logistically isolated for longer than any previous human spaceflight mission. Under these conditions, supportability and reliability willbestronger drivers of mission mass and risk than they have been in the past. Items with high failure rates, or uncertain failure rates, can result in high spares mass requirements and/or high risk on deep space missions. Testing is a critical element of system development which provides the opportunity to identify and resolve design issues, defects, or other failure modes before they cause problems during a mission. Reliability growth programs can reduce failure rates by identifying and remove failure modes via design changes, and long-duration life testing can provide valuable data to reduce failure rate estimate uncertainty and verify (to some level of confidence) that components are as reliable as expected. Testing activities take time and resources, however, and must be incorporated into program plans in order to be fully effective. This paper presents an integrated reliability test plan analysis and optimization methodology, which has been used to inform Advanced Exploration Systems (AES) Life Support Systems (LSS) ground test planning for future missions. The methodology determines the optimal number of test units to purchase and allocation of test time –split between reliability growth and uncertainty reduction testing –across a given set of items in order to minimize spares mass for a given mission under constraints on total test cost and schedule. Model outputs also include expected spares mass after testing and the expected number of modifications or refurbishments during testing, both of which can inform program planning. Discussion of the model, conclusions, and future work are also presented.

Testing↗
NASA NTRS1993

Tutorial: Performance and reliability in redundant disk arrays

A disk array is a collection of physically small magnetic disks that is packaged as a single unit but operates in parallel. Disk arrays capitalize on the availability of small-diameter disks from a price-competitive market to provide the cost, volume, and capacity of current disk systems but many times their performance. Unfortunately, relative to current disk systems, the larger number of components in disk arrays leads to higher rates of failure. To tolerate failures, redundant disk arrays devote a fraction of their capacity to an encoding of their information. This redundant information enables the contents of a failed disk to be recovered from the contents of non-failed disks. The simplest and least expensive encoding for this redundancy, known as N+1 parity is highlighted. In addition to compensating for the higher failure rates of disk arrays, redundancy allows highly reliable secondary storage systems to be built much more cost-effectively than is now achieved in conventional duplicated disks. Disk arrays that combine redundancy with the parallelism of many small-diameter disks are often called Redundant Arrays of Inexpensive Disks (RAID). This combination promises improvements to both the performance and the reliability of secondary storage. For example, IBM's premier disk product, the IBM 3390, is compared to a redundant disk array constructed of 84 IBM 0661 3 1/2-inch disks. The redundant disk array has comparable or superior values for each of the metrics given and appears likely to cost less. In the first section of this tutorial, I explain how disk arrays exploit the emergence of high performance, small magnetic disks to provide cost-effective disk parallelism that combats the access and transfer gap problems. The flexibility of disk-array configurations benefits manufacturer and consumer alike. In contrast, I describe in this tutorial's second half how parallelism, achieved through increasing numbers of components, causes overall failure rates to rise. Redundant disk arrays overcome this threat to data reliability by ensuring that data remains available during and after component failures.

Gibson, Garth A.↗
NASA NTRSDate not supplied

The optimum cost-effective test time for redundant systems with specified reliability and confidence

This paper investigates the optimum test time to determine the number of redundant units needed to achieve high reliability with high confidence. Newly designed systems often have high initial failure rates which can be reduced by testing to find failure modes and remove them by redesign. To accurately estimate the required number of redundant units, the test time must be extended to accurately determine the failure rate. If the measured failure rate is used, there is a 50% chance that the actual hardware failure rate is higher. Using the measured failure rate gives only a 50% confidence that the failure rate and number of spares are not too low. After the test, given the measured failure rate and the desired reliability, the number of spares can be determined and the confidence in the reliability computed. Instead of accepting the reliability results of a fixed duration test, it is possible to set the requirements for both the redundant reliability and the confidence level and then compute the test time needed to minimize the total cost required to achieve these requirements. The confidence that the redundant reliability is not too low is increased by using a higher than measured failure rate to increase the number of spares. The higher number of spares increases cost. Longer test time reduces the variance in the failure rate and the increase in the number of spares, so that test cost increases and spares cost decreases. The total cost is the sum of the cost of the test time and the spares. The optimum test time produces the minimum total cost for the system failure rate, mission length, and required reliability and confidence level. Longer testing is justified by reduced cost. Some examples are given.

Harry W Jones↗