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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Space Shuttle Main Engine (SSME) Reliability and Analysis Evolution

The Space Shuttle Main Engine (SSME) is a large thrust class, reusable, staged combustion cycle rocket engine employing liquid hydrogen and liquid oxygen propellants. A cluster of three SSMEs is used on every space shuttle mission to propel the space shuttle orbiter vehicle into low earth orbit. Development of the SSME began in the early 70 s and the first flight of the space shuttle occurred in 1981. Today, the SSME has accrued over one million seconds of ground test and flight operational time, launching 129 space shuttle missions. Given that the SSME is used to launch a manned vehicle, its reliability must be commensurate for the task. At the same time, the SSME is a high performance, high power density engine which traditionally does not lend itself towards high reliability. Furthermore, throughout its history, the SSME operational envelope has been explored and expanded leading to several major test failures. Hence, assessing the reliability of the SSME throughout its history has been a challenging undertaking. This paper provides a review and discussion of SSME reliability assessment techniques and results over its history. Basic reliability drivers such as engine design, test program, major failures, redesigns and upgrades will also be discussed.

Stephens, Walter E.↗
NASA NTRS2010

Reliability Quantification of Advanced Stirling Convertor (ASC) Components

The Advanced Stirling Convertor, is intended to provide power for an unmanned planetary spacecraft and has an operational life requirement of 17 years. Over this 17 year mission, the ASC must provide power with desired performance and efficiency and require no corrective maintenance. Reliability demonstration testing for the ASC was found to be very limited due to schedule and resource constraints. Reliability demonstration must involve the application of analysis, system and component level testing, and simulation models, taken collectively. Therefore, computer simulation with limited test data verification is a viable approach to assess the reliability of ASC components. This approach is based on physics-of-failure mechanisms and involves the relationship among the design variables based on physics, mechanics, material behavior models, interaction of different components and their respective disciplines such as structures, materials, fluid, thermal, mechanical, electrical, etc. In addition, these models are based on the available test data, which can be updated, and analysis refined as more data and information becomes available. The failure mechanisms and causes of failure are included in the analysis, especially in light of the new information, in order to develop guidelines to improve design reliability and better operating controls to reduce the probability of failure. Quantified reliability assessment based on fundamental physical behavior of components and their relationship with other components has demonstrated itself to be a superior technique to conventional reliability approaches based on utilizing failure rates derived from similar equipment or simply expert judgment.

Shah, Ashwin R.↗
NASA NTRS1989

Space Station Freedom power - A reliability, availability, and maintainability assessment of the proposed Space Station Freedom electric power system

A preliminary reliability, availability, and maintainability (RAM) analysis of the proposed Space Station Freedom electric power system (EPS) was performed using the unit reliability, availability, and maintainability (UNIRAM) analysis methodology. Orbital replacement units (ORUs) having the most significant impact on EPS availability measures were identified. Also, the sensitivity of the EPS to variations in ORU RAM data was evaluated for each ORU. Estimates were made of average EPS power output levels and availability of power to the core area of the space station. The results of assessments of the availability of EPS power and power to load distribution points in the space stations are given. Some highlights of continuing studies being performed to understand EPS availability considerations are presented.

Turnquist, S. R.↗
NASA NTRS2009

Isokinetic Strength and Endurance Tests used Pre- and Post-Spaceflight: Test-Retest Reliability

To assess changes in muscular strength and endurance after microgravity exposure, NASA measures isokinetic strength and endurance across multiple sessions before and after long-duration space flight. Accurate interpretation of pre- and post-flight measures depends upon the reliability of each measure. The purpose of this study was to evaluate the test-retest reliability of the NASA International Space Station (ISS) isokinetic protocol. Twenty-four healthy subjects (12 M/12 F, 32.0 +/- 5.6 years) volunteered to participate. Isokinetic knee, ankle, and trunk flexion and extension strength as well as endurance of the knee flexors and extensors were measured using a Cybex NORM isokinetic dynamometer. The first weekly session was considered a familiarization session. Data were collected and analyzed for weeks 2-4. Repeated measures analysis of variance (alpha=0.05) was used to identify weekly differences in isokinetic measures. Test-retest reliability was evaluated by intraclass correlation coefficients (ICC) (3,1). No significant differences were found between weeks in any of the strength measures and the reliability of the strength measures were all considered excellent (ICC greater than 0.9), except for concentric ankle dorsi-flexion (ICC=0.67). Although a significant difference was noted in weekly endurance measures of knee extension (p less than 0.01), the reliability of endurance measure by week were considered excellent for knee flexion (ICC=0.97) and knee extension (ICC=0.96). Except for concentric ankle dorsi-flexion, the isokinetic strength and endurance measures are highly reliable when following the NASA ISS protocol. This protocol should allow accurate interpretation isokinetic data even with a small number of crew members.

Laughlin, Mitzi S.↗
NASA NTRS2012

Reliability of High I/O High Density CCGA Interconnect Electronic Packages under Extreme Thermal Environment

This paper provides the experimental test results of advanced CCGA packages tested in extreme temperature thermal environments. Standard optical inspection and x-ray non-destructive inspection tools were used to assess the reliability of high density CCGA packages for deep space extreme temperature missions. Ceramic column grid array (CCGA) packages have been increasing in use based on their advantages such as high interconnect density, very good thermal and electrical performances, compatibility with standard surface-mount packaging assembly processes, and so on. CCGA packages are used in space applications such as in logic and microprocessor functions, telecommunications, payload electronics, and flight avionics. As these packages tend to have less solder joint strain relief than leaded packages or more strain relief over lead-less chip carrier packages, the reliability of CCGA packages is very important for short-term and long-term deep space missions. We have employed high density CCGA 1152 and 1272 daisy chained electronic packages in this preliminary reliability study. Each package is divided into several daisy-chained sections. The physical dimensions of CCGA1152 package is 35 mm x 35 mm with a 34 x 34 array of columns with a 1 mm pitch. The dimension of the CCGA1272 package is 37.5 mm x 37.5 mm with a 36 x 36 array with a 1 mm pitch. The columns are made up of 80% Pb/20%Sn material. CCGA interconnect electronic package printed wiring polyimide boards have been assembled and inspected using non-destructive x-ray imaging techniques. The assembled CCGA boards were subjected to extreme temperature thermal atmospheric cycling to assess their reliability for future deep space missions. The resistance of daisy-chained interconnect sections were monitored continuously during thermal cycling. This paper provides the experimental test results of advanced CCGA packages tested in extreme temperature thermal environments. Standard optical inspection and x-ray non-destructive inspection tools were used to assess the reliability of high density CCGA packages for deep space extreme temperature missions. Keywords: Extreme temperatures, High density CCGA qualification, CCGA reliability, solder joint failures, optical inspection, and x-ray inspection.

high density CCGA qualifications↗
NASA NTRS1986

Reliability of photovoltaic modules

In order to assess the reliability of photovoltaic modules, four categories of known array failure and degradation mechanisms are discussed, and target reliability allocations have been developed within each category based on the available technology and the life-cycle-cost requirements of future large-scale terrestrial applications. Cell-level failure mechanisms associated with open-circuiting or short-circuiting of individual solar cells generally arise from cell cracking or the fatigue of cell-to-cell interconnects. Power degradation mechanisms considered include gradual power loss in cells, light-induced effects, and module optical degradation. Module-level failure mechanisms and life-limiting wear-out mechanisms are also explored.

Ross, R. G., Jr.↗
NASA NTRS1987

An overview of the mathematical and statistical analysis component of RICIS

Mathematical and statistical analysis components of RICIS (Research Institute for Computing and Information Systems) can be used in the following problem areas: (1) quantification and measurement of software reliability; (2) assessment of changes in software reliability over time (reliability growth); (3) analysis of software-failure data; and (4) decision logic for whether to continue or stop testing software. Other areas of interest to NASA/JSC where mathematical and statistical analysis can be successfully employed include: math modeling of physical systems, simulation, statistical data reduction, evaluation methods, optimization, algorithm development, and mathematical methods in signal processing.

Hallum, Cecil R.↗
NASA NTRS1990

Probabilistic simulation of uncertainties in thermal structures

Development of probabilistic structural analysis methods for hot structures is a major activity at Lewis Research Center. It consists of five program elements: (1) probabilistic loads; (2) probabilistic finite element analysis; (3) probabilistic material behavior; (4) assessment of reliability and risk; and (5) probabilistic structural performance evaluation. Recent progress includes: (1) quantification of the effects of uncertainties for several variables on high pressure fuel turbopump (HPFT) blade temperature, pressure, and torque of the Space Shuttle Main Engine (SSME); (2) the evaluation of the cumulative distribution function for various structural response variables based on assumed uncertainties in primitive structural variables; (3) evaluation of the failure probability; (4) reliability and risk-cost assessment, and (5) an outline of an emerging approach for eventual hot structures certification. Collectively, the results demonstrate that the structural durability/reliability of hot structural components can be effectively evaluated in a formal probabilistic framework. In addition, the approach can be readily extended to computationally simulate certification of hot structures for aerospace environments.

Chamis, Christos C.↗
NASA NTRS1990

Probabilistic simulation of uncertainties in thermal structures

Development of probabilistic structural analysis methods for hot structures is a major activity at NASA-Lewis, and consists of five program elements: (1) probabilistic loads, (2) probabilistic finite element analysis, (3) probabilistic material behavior, (4) assessment of reliability and risk, and (5) probabilistic structural performance evaluation. Attention is given to quantification of the effects of uncertainties for several variables on High Pressure Fuel Turbopump blade temperature, pressure, and torque of the Space Shuttle Main Engine; the evaluation of the cumulative distribution function for various structural response variables based on assumed uncertainties in primitive structural variables; evaluation of the failure probability; reliability and risk-cost assessment; and an outline of an emerging approach for eventual hot structures certification. Collectively, the results demonstrate that the structural durability/reliability of hot structural components can be effectively evaluated in a formal probabilistic framework. In addition, the approach can be readily extended to computationally simulate certification of hot structures for aerospace environments.

Chamis, C. C.↗
NASA NTRS2024

Evaluation of CS-type Metallized Polymer Film Capacitors

In 2023 Quantic Paktron announced production of Capstick high reliability multilayer metallized polymer film capacitors based on a new type of dielectric films and proprietary technology of manufacturing. These parts might be used in power conversion systems, snubbing, and high-frequency applications effectively replacing currently used hermetic polymer capacitors manufactured per MIL-PRF-83421. The purpose of this work is to evaluate design and performance of the parts, address potential reliability issues and get preliminary assessments of reliability and the possibility of use in space projects.

Alexander Teverovsky↗
NASA NTRS2016

Constructing the 'Best' Reliability Data for the Job - Developing Generic Reliability Data from Alternative Sources Early in a Product's Development Phase

Reliability practitioners advocate getting reliability involved early in a product development process. However, when assigned to estimate or assess the (potential) reliability of a product or system early in the design and development phase, they are faced with lack of reasonable models or methods for useful reliability estimation. Developing specific data is costly and time consuming. Instead, analysts rely on available data to assess reliability. Finding data relevant to the specific use and environment for any project is difficult, if not impossible. Instead, analysts attempt to develop the "best" or composite analog data to support the assessments. Industries, consortia and vendors across many areas have spent decades collecting, analyzing and tabulating fielded item and component reliability performance in terms of observed failures and operational use. This data resource provides a huge compendium of information for potential use, but can also be compartmented by industry, difficult to find out about, access, or manipulate. One method used incorporates processes for reviewing these existing data sources and identifying the available information based on similar equipment, then using that generic data to derive an analog composite. Dissimilarities in equipment descriptions, environment of intended use, quality and even failure modes impact the "best" data incorporated in an analog composite. Once developed, this composite analog data provides a "better" representation of the reliability of the equipment or component. It can be used to support early risk or reliability trade studies, or analytical models to establish the predicted reliability data points. It also establishes a baseline prior that may updated based on test data or observed operational constraints and failures, i.e., using Bayesian techniques. This tutorial presents a descriptive compilation of historical data sources across numerous industries and disciplines, along with examples of contents and data characteristics. It then presents methods for combining failure information from different sources and mathematical use of this data in early reliability estimation and analyses.

Kleinhammer, Roger K.↗
NASA NTRSDate not supplied

Interval Predictor Models for Robust System Identification

This paper proposes a framework for the identification and uncertainty quantification of plant models according to multivariable data. The only restriction imposed upon such models is for their outputs to depend continuously on their parameters. An Interval Predictor Model (IPM) prescribes the parameters of a computational model as a path-connected set thereby making each predicted output an interval-valued function of its inputs. The formulation proposed seeks the parameter set for which the predicted outputs tightly enclose the data. This set, which is modeled as a semi-algebraic set of low-degree polynomials, enables the characterization of possibly strong parameter dependencies commonly found in practice. This uncertainty characterization makes the resulting plant model amenable to robust control approaches using polynomial optimization. Furthermore, we use non-convex scenario theory to assess the reliability of the resulting IPM. This assessment yields a distribution-free upper bound on the probability that future data will fall outside the predicted intervals.

interval↗
NASA NTRS2015

Reliability and Probabilistic Risk Assessment - How They Play Together

PRA methodology is one of the probabilistic analysis methods that NASA brought from the nuclear industry to assess the risk of LOM, LOV and LOC for launch vehicles. PRA is a system scenario based risk assessment that uses a combination of fault trees, event trees, event sequence diagrams, and probability and statistical data to analyze the risk of a system, a process, or an activity. It is a process designed to answer three basic questions: What can go wrong? How likely is it? What is the severity of the degradation? Since 1986, NASA, along with industry partners, has conducted a number of PRA studies to predict the overall launch vehicles risks. Planning Research Corporation conducted the first of these studies in 1988. In 1995, Science Applications International Corporation (SAIC) conducted a comprehensive PRA study. In July 1996, NASA conducted a two-year study (October 1996 - September 1998) to develop a model that provided the overall Space Shuttle risk and estimates of risk changes due to proposed Space Shuttle upgrades. After the Columbia accident, NASA conducted a PRA on the Shuttle External Tank (ET) foam. This study was the most focused and extensive risk assessment that NASA has conducted in recent years. It used a dynamic, physics-based, integrated system analysis approach to understand the integrated system risk due to ET foam loss in flight. Most recently, a PRA for Ares I launch vehicle has been performed in support of the Constellation program. Reliability, on the other hand, addresses the loss of functions. In a broader sense, reliability engineering is a discipline that involves the application of engineering principles to the design and processing of products, both hardware and software, for meeting product reliability requirements or goals. It is a very broad design-support discipline. It has important interfaces with many other engineering disciplines. Reliability as a figure of merit (i.e. the metric) is the probability that an item will perform its intended function(s) for a specified mission profile. In general, the reliability metric can be calculated through the analyses using reliability demonstration and reliability prediction methodologies. Reliability analysis is very critical for understanding component failure mechanisms and in identifying reliability critical design and process drivers. The following sections discuss the PRA process and reliability engineering in detail and provide an application where reliability analysis and PRA were jointly used in a complementary manner to support a Space Shuttle flight risk assessment.

Safie, Fayssal M.↗
NASA NTRS1987

Development of confidence limits by pivotal functions for estimating software reliability

The utility of pivotal functions is established for assessing software reliability. Based on the Moranda geometric de-eutrophication model of reliability growth, confidence limits for attained reliability and prediction limits for the time to the next failure are derived using a pivotal function approach. Asymptotic approximations to the confidence and prediction limits are considered and are shown to be inadequate in cases where only a few bugs are found in the software. Departures from the assumed exponentially distributed interfailure times in the model are also investigated. The effect of these departures is discussed relative to restricting the use of the Moranda model.

Dotson, Kelly J.↗
NASA NTRS2015

Reliability and Probabilistic Risk Assessment - How They Play Together

Since the Space Shuttle Challenger accident in 1986, NASA has extensively used probabilistic analysis methods to assess, understand, and communicate the risk of space launch vehicles. Probabilistic Risk Assessment (PRA), used in the nuclear industry, is one of the probabilistic analysis methods NASA utilizes to assess Loss of Mission (LOM) and Loss of Crew (LOC) risk for launch vehicles. PRA is a system scenario based risk assessment that uses a combination of fault trees, event trees, event sequence diagrams, and probability distributions to analyze the risk of a system, a process, or an activity. It is a process designed to answer three basic questions: 1) what can go wrong that would lead to loss or degraded performance (i.e., scenarios involving undesired consequences of interest), 2) how likely is it (probabilities), and 3) what is the severity of the degradation (consequences). Since the Challenger accident, PRA has been used in supporting decisions regarding safety upgrades for launch vehicles. Another area that was given a lot of emphasis at NASA after the Challenger accident is reliability engineering. Reliability engineering has been a critical design function at NASA since the early Apollo days. However, after the Challenger accident, quantitative reliability analysis and reliability predictions were given more scrutiny because of their importance in understanding failure mechanism and quantifying the probability of failure, which are key elements in resolving technical issues, performing design trades, and implementing design improvements. Although PRA and reliability are both probabilistic in nature and, in some cases, use the same tools, they are two different activities. Specifically, reliability engineering is a broad design discipline that deals with loss of function and helps understand failure mechanism and improve component and system design. PRA is a system scenario based risk assessment process intended to assess the risk scenarios that could lead to a major/top undesirable system event, and to identify those scenarios that are high-risk drivers. PRA output is critical to support risk informed decisions concerning system design. This paper describes the PRA process and the reliability engineering discipline in detail. It discusses their differences and similarities and how they work together as complementary analyses to support the design and risk assessment processes. Lessons learned, applications, and case studies in both areas are also discussed in the paper to demonstrate and explain these differences and similarities.

Safie, Fayssal↗
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↗