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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

High-Reliability Pump Module for Non-Planar Ring Oscillator Laser

We propose and have demonstrated a prototype high-reliability pump module for pumping a Non-Planar Ring Oscillator (NPRO) laser suitable for space missions. The pump module consists of multiple fiber-coupled single-mode laser diodes and a fiber array micro-lens array based fiber combiner. The reported Single-Mode laser diode combiner laser pump module (LPM) provides a higher normalized brightness at the combined beam than multimode laser diode based LPMs. A higher brightness from the pump source is essential for efficient NPRO laser pumping and leads to higher reliability because higher efficiency requires a lower operating power for the laser diodes, which in turn increases the reliability and lifetime of the laser diodes. Single-mode laser diodes with Fiber Bragg Grating (FBG) stabilized wavelength permit the pump module to be operated without a thermal electric cooler (TEC) and this further improves the overall reliability of the pump module. The single-mode laser diode LPM is scalable in terms of the number of pump diodes and is capable of combining hundreds of fiber-coupled laser diodes. In the proof-of-concept demonstration, an e-beam written diffractive micro lens array, a custom fiber array, commercial 808nm single mode laser diodes, and a custom NPRO laser head are used. The reliability of the proposed LPM is discussed.

micro lens array↗
NASA NTRS2013

FY12 End of Year Report for NEPP DDR2 Reliability

This document reports the status of the NEPP Double Data Rate 2 (DDR2) Reliability effort for FY2012. The task expanded the focus of evaluating reliability effects targeted for device examination. FY11 work highlighted the need to test many more parts and to examine more operating conditions, in order to provide useful recommendations for NASA users of these devices. In order to develop these approaches, it is necessary to develop test capability that can identify reliability outliers. To do this we must test many devices to ensure outliers are in the sample, and we must develop characterization capability to measure many different parameters. For FY12 we increased capability for reliability characterization and sample size. We increased sample size by moving from loose devices to DIMMs with an approximate reduction of 20 to 50 times in terms of per DUT cost. By increasing sample size we have improved our ability to characterize devices that may be considered reliability outliers. This report provides an update on the effort to improve DDR2 testing capability. Although focused on DDR2, the methods being used can be extended to DDR and DDR3 with relative ease.

temperature stress↗
NASA NTRS2015

Diverse Redundant Systems for Reliable Space Life Support

Reliable life support systems are required for deep space missions. The probability of a fatal life support failure should be less than one in a thousand in a multi-year mission. It is far too expensive to develop a single system with such high reliability. Using three redundant units would require only that each have a failure probability of one in ten over the mission. Since the system development cost is inverse to the failure probability, this would cut cost by a factor of one hundred. Using replaceable subsystems instead of full systems would further cut cost. Using full sets of replaceable components improves reliability more than using complete systems as spares, since a set of components could repair many different failures instead of just one. Replaceable components would require more tools, space, and planning than full systems or replaceable subsystems. However, identical system redundancy cannot be relied on in practice. Common cause failures can disable all the identical redundant systems. Typical levels of common cause failures will defeat redundancy greater than two. Diverse redundant systems are required for reliable space life support. Three, four, or five diverse redundant systems could be needed for sufficient reliability. One system with lower level repair could be substituted for two diverse systems to save cost.

life support↗
NASA NTRS2014

Body of Knowledge (BOK) for Leadless Quad Flat No-Lead/bottom Termination Components (QFN/BTC) Package Trends and Reliability

Bottom terminated components and quad flat no-lead (BTC/QFN) packages have been extensively used by commercial industry for more than a decade. Cost and performance advantages and the closeness of the packages to the boards make them especially unique for radio frequency (RF) applications. A number of high-reliability parts are now available in this style of package configuration. This report presents a summary of literature surveyed and provides a body of knowledge (BOK) gathered on the status of BTC/QFN and their advanced versions of multi-row QFN (MRQFN) packaging technologies. The report provides a comprehensive review of packaging trends and specifications on design, assembly, and reliability. Emphasis is placed on assembly reliability and associated key design and process parameters because they show lower life than standard leaded package assembly under thermal cycling exposures. Inspection of hidden solder joints for assuring quality is challenging and is similar to ball grid arrays (BGAs). Understanding the key BTC/QFN technology trends, applications, processing parameters, workmanship defects, and reliability behavior is important when judicially selecting and narrowing the follow-on packages for evaluation and testing, as well as for the low risk insertion in high-reliability applications.

MLF↗
NASA NTRS2016

Evolving Reliability and Maintainability Allocations for NASA Ground Systems

This paper describes the methodology that was developed to allocate reliability and maintainability requirements for the NASA Ground Systems Development and Operations (GSDO) program's subsystems. As systems progressed through their design life cycle and hardware data became available, it became necessary to reexamine the previously derived allocations. Allocating is an iterative process; as systems moved beyond their conceptual and preliminary design phases this provided an opportunity for the reliability engineering team to reevaluate allocations based on updated designs and maintainability characteristics of the components. Trade-offs in reliability and maintainability were essential to ensuring the integrity of the reliability and maintainability analysis. This paper will discuss the value of modifying reliability and maintainability allocations made for the GSDO subsystems as the program nears the end of its design phase.

allocations↗
NASA NTRS2016

Evolving Reliability and Maintainability Allocations for NASA Ground Systems

This paper describes the methodology and value of modifying allocations to reliability and maintainability requirements for the NASA Ground Systems Development and Operations (GSDO) program’s subsystems. As systems progressed through their design life cycle and hardware data became available, it became necessary to reexamine the previously derived allocations. This iterative process provided an opportunity for the reliability engineering team to reevaluate allocations as systems moved beyond their conceptual and preliminary design phases. These new allocations are based on updated designs and maintainability characteristics of the components. It was found that trade-offs in reliability and maintainability were essential to ensuring the integrity of the reliability and maintainability analysis. This paper discusses the results of reliability and maintainability reallocations made for the GSDO subsystems as the program nears the end of its design phase.

allocations↗
NASA NTRS2016

Evolving Reliability and Maintainability Allocations for NASA Ground Systems

This paper describes the methodology and value of modifying allocations to reliability and maintainability requirements for the NASA Ground Systems Development and Operations (GSDO) programs subsystems. As systems progressed through their design life cycle and hardware data became available, it became necessary to reexamine the previously derived allocations. This iterative process provided an opportunity for the reliability engineering team to reevaluate allocations as systems moved beyond their conceptual and preliminary design phases. These new allocations are based on updated designs and maintainability characteristics of the components. It was found that trade-offs in reliability and maintainability were essential to ensuring the integrity of the reliability and maintainability analysis. This paper discusses the results of reliability and maintainability reallocations made for the GSDO subsystems as the program nears the end of its design phase.

reliability↗
NASA NTRS2017

Heroic Reliability Improvement in Manned Space Systems

System reliability can be significantly improved by a strong continued effort to identify and remove all the causes of actual failures. Newly designed systems often have unexpected high failure rates which can be reduced by successive design improvements until the final operational system has an acceptable failure rate. There are many causes of failures and many ways to remove them. New systems may have poor specifications, design errors, or mistaken operations concepts. Correcting unexpected problems as they occur can produce large early gains in reliability. Improved technology in materials, components, and design approaches can increase reliability. The reliability growth is achieved by repeatedly operating the system until it fails, identifying the failure cause, and fixing the problem. The failure rate reduction that can be obtained depends on the number and the failure rates of the correctable failures. Under the strong assumption that the failure causes can be removed, the decline in overall failure rate can be predicted. If a failure occurs at the rate of lambda per unit time, the expected time before the failure occurs and can be corrected is 1/lambda, the Mean Time Before Failure (MTBF). Finding and fixing a less frequent failure with the rate of lambda/2 per unit time requires twice as long, time of 1/(2 lambda). Cutting the failure rate in half requires doubling the test and redesign time and finding and eliminating the failure causes.Reducing the failure rate significantly requires a heroic reliability improvement effort.

life support↗
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 NTRSDate not supplied

NASA Physics of Failure (PoF) for Reliability

An item’s reliability or longevity is dependent not only on its design but also on how it is used, manufactured, tested, and the stresses it has or will experience. Stresses include operational and environmental exposures to thermal, voltage, current, age/exposure, mechanical, and radiation mechanisms. Therefore, in reliability analysis, it is important to consider the contributions of all these factors when predicting the failure rates of components. Historically, there has been a reliance on handbook data (e.g., MIL-HDBK-217), but experience has shown that these values and distributions are not representative of actual performance. Therefore, to make more credible reliability and risk assessments for its missions, NASA must transition to estimating likelihoods of failure based on an item’s reliability or longevity factors (or the physical susceptibilities and strengths impacting the design’s performance) has or will experience, whenever possible. To facilitate this transition, a Handbook on Methodology for Physics of Failure Based Reliability Assessments has been developed by NASA to assist in applying physics experiences or experimental physics for empirical analysis and conceptualized physics exposures or theoretical physics for deterministic analysis, to develop and aggregate realistic likelihoods of failure leading to more credible forecasts of item performance and longevity. In addition, since it is NASA’s intention that this document continues to evolve based on community lessons learned and the introduction of new assessment methodologies, NASA is encouraging and appreciates the contributions of current and future authors to maintain and enhance this handbook and its supporting case studies.

PoF↗
DOE OSTI2024

Explained: Maintaining a Reliable Future Grid with More Wind and Solar

Since the early 2000s, maintaining grid reliability has become more complex due to a variety of factors, including the changing generation mix, the creation of wholesale energy markets, and a growing number of extreme weather events. Parts of the U.S. grid are already operating with significant amounts of wind and solar generation - with 2022 annual wind and solar generation in the range of 25% to 40%. Even without considering the effects of extreme weather, maintaining reliability will require new capacity to address both growth in electric demand and retiring capacity. Based on the 2022 North American Electric Reliability Corporation (NERC) Long-Term Reliability Assessment, the combination of both growth in peak demand and retirements suggests a need for more than 100 gigawatts (GW) of new capacity by 2032. In general, there are a five categories of resources that are expected to be deployed and used to meet the challenge of maintaining an adequate source of supply in the coming decades: new wind and solar resources (accounting for their reliability contributions), energy storage, demand response resources, expanded transmission, and continued use of thermal generators.

power grid↗
DOE OSTI2023

Reliability Improvement and Effective Switching Layer Model of Thin-Film MoS 2 Memristors

2D memristors have demonstrated attractive resistive switching characteristics recently but also suffer from the reliability issue, which limits practical applications. Previous efforts on 2D memristors have primarily focused on exploring new material systems, while damage from the metallization step remains a practical concern for the reliability of 2D memristors. Here, the impact of metallization conditions and the thickness of MoS 2 films on the reliability and other device metrics of MoS 2 -based memristors is carefully studied. The statistical electrical measurements show that the reliability can be improved to 92% for yield and improved by ≈16× for average DC cycling endurance in the devices by reducing the top electrode (TE) deposition rate and increasing the thickness of MoS 2 films. Intriguing convergence of switching voltages and resistance ratio is revealed by the statistical analysis of experimental switching cycles. An “effective switching layer” model compatible with both monolayer and few-layer MoS 2 , is proposed to understand the reliability improvement related to the optimization of fabrication configuration and the convergence of switching metrics. In conclusion, the Monte Carlo simulations help illustrate the underlying physics of endurance failure associated with cluster formation and provide additional insight into endurance improvement with device fabrication optimization.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Reliability Analysis for Unreliable FSM Computations

Finite State Machines (FSMs) are fundamental in both hardware design and software development. However, the reliability of FSM computations remains poorly understood. This becomes increasingly critical as the technology scaling becomes more aggressive. Existing reliability analyses are mainly designed for generic computations and are unaware of the special error tolerance characteristics in FSM computations. In this work, we introduce RelyFSM – a state-level reliability analysis framework for FSM computations. By qualitatively reasoning about the transition structures in FSM computations, RelyFSM can precisely capture their inherent error tolerance. Basically, RelyFSM takes an FSM specification as input and analyzes its reliability for a specific execution. At the core of the analysis is a set of mathematical models that accurately define the behaviors of unreliable FSM executions. Our evaluation with a spectrum of FSM benchmarks confirms the accuracy and efficiency of RelyFSM in analyzing the reliability of real-world FSM computations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Spatiotemporal Variability of Electric System Reliability Metrics

As urbanization continues to grow, urban density also rises, placing significant stress on critical infrastructure. Cities often face challenges in investing in new infrastructure or upgrading existing ones. One area of infrastructure that has come under strain is the electric grid, leading to prolonged power outages. According to data from the U.S. Energy Information Administration, the average duration of power outages has steadily doubled from 2013 to 2021, primarily due to extreme weather events. The IEEE has developed a series of reliability metrics to assess the reliability of the electric system. However, these metrics are only applied at the utility level, making it challenging to comprehend the variations in these indices at finer spatial resolutions and, consequently, evaluate reliability at the non-utility level. In this study, we leveraged electric outage data collected at 15-minute intervals at the county level to estimate electric system reliability over a six-year period using a novel data analysis approach. Our findings reveal a gradual decline in reliability in the U.S. Southwest compared to national averages. Furthermore, the duration of outages per customer per event has significantly decreased in large portions of California and Florida. These discoveries can be valuable for utility companies as they seek to pinpoint regional anomalies and plan for prioritized remediation efforts.

Singh, Nagendra↗
DOE OSTI2020

Safety Risk Reliability Model Library

SR2ML is a software package which contains a set of safety and reliability models designed to be interfaced with the INL developed RAVEN code. These models can be employed to perform both static and dynamic system risk analysis and determine risk importance of specific elements of the considered system. Two classes of reliability models have been developed; the first class includes all classical reliability models (Fault-Trees, Event-Trees, Markov models and Reliability Block Diagrams) which have been extended to deal not only with Boolean logic values but also time dependent values. The second class includes several components aging models. Models of these two classes are designed to be included in a RAVEN ensemble model to perform time dependent system reliability analysis (dynamic analysis). Similarly, these models can be interfaced with system analysis codes to determine failure time of systems and evaluate accident progression (static analysis).

Wang, Congjian↗
DOE OSTI2021

Reliability Prediction using FMEA, FTA, and Related Techniques [Slides]

Summary: We presented a reliability analysis framework. We made point estimates of reliability using reliability block diagrams, fault trees, success trees and estimates with uncertainty using expert elicitation, Monte Carlo simulation, Bayesian analysis. Expert elicitation of failure modes and probabilities is labor-intensive, but critical. Bayesian analysis updates information from expert elicitation with data from reliability and aging tests (aging/compatibility data are needed to estimate lower-bound reliabilities at end of life). Estimation by more than one method helps insure consistency and accuracy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Bridging Equipment Reliability Data and Robust Decisions in a Plant Operation Context

In order to reduce operation and maintenance (O&M) costs, nuclear power plants (NPPs) are moving from corrective and periodic maintenance to predictive maintenance strategies. Such transition requires changes on the data that needs to be retrieved and on the type of decision processes to be employed. Advanced monitoring and data analysis technologies are essential to support predictive strategies. They can in fact provide precise information about health of a component, track its degradation trends, and provide information of its expected failure time. With such information, maintenance operations for a component can be performed right before its expected failure time. This dynamic context of O&M operations requires new methods to analyze data, propagate component health information from the component to the system level, and optimize plant resources. In this respect, the risk informed asset management (RIAM) project has been tasked to develop and test this new class of methods into a risk analytics toolset. This toolset consists of data analytics tools coupled with reliability methods designed to manage plant assets and performances in a predictive maintenance context. This report shows the latest improvements on such development and the initial testing of our methods on the three main research areas that the RIAM project is focusing on. These areas are the following: equipment reliability data analytics, system reliability modeling, and plant resources optimization methods. We show how the methods developed in these areas can support predictive maintenance strategies by: 1) analyzing equipment reliability data (either in numeric and textual form), 2) assessing component and system health through an innovative margin-based reliability approach, and 3) identifying the most critical components and set optimal maintenance schedule based on plant economic and operational constraints.

97 MATHEMATICS AND COMPUTING↗