Results for “failure modes” — Page 21

NASA NTRS1988

Independent Orbiter Assessment (IOA): Assessment of the reaction control system, volume 1

The results of the Independent Orbiter Assessment (IOA) of the Failure Modes and Effects Analysis (FMEA) and Critical Items List (CIL) are presented. The IOA effort first completed an analysis of the aft and forward Reaction Control System (RCS) hardware, and Electrical Power Distribution and Control (EPD and C), generating draft failure modes and potential critical items. To preserve independence, this analysis was accomplished without reliance upon the results contained within the NASA FMEA/CIL documentation. The IOA results were then compared to the proposed Post 51-L NASA FMEA/CIL baseline. This report documents the results of that comparison for the Orbiter RCS hardware and EPD and C systems. The IOA product for the RCS analysis consisted of 208 hardware and 2064 EPD and C failure mode worksheets that resulted in 141 hardware and 449 EPD and C potential critical items (PCIs) being identified. A comparison was made of the IOA product to the NASA FMEA/CIL baseline. After comparison and discussions with the NASA subsystem manager, 96 hardware issues, 83 of which concern CIL items or PCIs, and 280 EPD and C issues, 158 of which concern CIL items or PCIs, and 280 EPD and C issues, 158 of which concern CIL items or PCIs, remain unresolved. Volume 1 contains the subsystem description, assessment results, and some of the IOA worksheets.

Prust, Chet D.↗

NASA NTRSDate not supplied

Reliability Growth Modeling and Testing

Reliability growth has been modelled as an exponential decline in the cumulative failure rate that continues indefinitely as long as testing continues. Contrary to this, most reliability growth data show a brief high initial failure rate due to infant mortality followed by a long period of constant low failure rate. A two part failure rate model with an initial exponential decline followed by a constant failure rate usually fits the data and provides a more realistic description of reliability growth. The reliability growth process consists of testing, experiencing failures, finding the failure causes, and redesigning the system to remove them. The cost of reliability growth increases with the number of inherent failure modes and the time needed for them to occur and be removed. The failure modes with the lower failure rates will tend to occur later, as their Mean Time Before Failure (MTBF) is the inverse of the failure rate. Reliability growth testing has diminishing returns, since it takes longer to find and remove the less probable failures.This paper first discusses the reliability bathtub curve and then explains that reliability growth is produced by testing, identifying failure causes, and designing to remove them. A simple model of reliability growth is introduced, with a brief group of early failures followed by a constant failure rate. The cumulative failure rate n(t)/t can decline as rapidly as1/t or t-1butdeclines more slowly if additiona lfailures occur. The 56-failure Crow data seti s used to demonstrate the two-phase model of reliability growth followed by a constant failure rate. 13 additional data sets are modeled, with 9 of the 14 data sets showing reliability growth approximately as n(t)/t =1/t or t-1and substantial final failure rates. The model fits most of the data sets, but 4of the 14 show no reliability growth. The reliability growth period typically includes six failures and extends one-quarter or half the total test time. As reliability growth testing continues, the cumulative failure rate should be tracked to estimate the reliability growth exponent and the final failure rate.

reliability growth modeling↗

NASA NTRSDate not supplied

Modeling Reliability Growth

Reliability growth has been modelled as an exponential decline in the cumulative failure rate that continues indefinitely as long as testing continues. Contrary to this, most reliability growth data show a brief high initial failure rate due to infant mortality followed by a long period of constant low failure rate. A two part failure rate model with an initial exponential decline followed by a constant failure rate usually fits the data and provides a more realistic description of reliability growth. The reliability growth process consists of testing, experiencing failures, finding the failure causes, and redesigning the system to remove them. The cost of reliability growth increases with the number of inherent failure modes and the time needed for them to occur and be removed. The failure modes with the lower failure rates will tend to occur later, as their Mean Time Before Failure (MTBF) is the inverse of the failure rate. Reliability growth testing has diminishing returns, since it takes longer to find and remove the less probable failures.This paper first discusses the reliability bathtub curve and then explains that reliability growth is produced by testing, identifying failure causes, and designing to remove them. A simple model of reliability growth is introduced, with a brief group of early failures followed by a constant failure rate. The cumulative failure rate n(t)/t can decline as rapidly as1/t or t-1butdeclines more slowly if additiona lfailures occur. The 56-failure Crow data seti s used to demonstrate the two-phase model of reliability growth followed by a constant failure rate. 13 additional data sets are modeled, with 9 of the 14 data sets showing reliability growth approximately as n(t)/t =1/t or t-1and substantial final failure rates. The model fits most of the data sets, but 4of the 14 show no reliability growth. The reliability growth period typically includes six failures and extends one-quarter or half the total test time. As reliability growth testing continues, the cumulative failure rate should be tracked to estimate the reliability growth exponent and the final failure rate.

reliability growth modeling↗

NASA NTRS1995

Static stability of the Space Station solar array FASTMast structure

The combined loads test of the 3-Bay FASTMast marks the end of the Lewis Research Center (LeRC) effort to characterize the behavior of the principal Space Station solar array support structure. The primary objective of this test and analysis effort was to develop a method to predict structural stability failure modes under flight-like applied loads. Included at the beginning of this report is a brief historical perspective of the hardware design development and FASTMast structural stability problem evolution. Once an understanding of the solution process has been established, test and analysis details are presented and related to the postulated failure theories. The combined load test series subjected the structure to a combination of transverse, moment, and torsion loads similar to that expected in the service environment. Nonlinear finite element (FE) models were developed and large displacement analyses were performed to support the test effort and failure mode predictions. Details of the test configuration as well as test and analysis results are presented. The results were then critiqued to establish valid and successful support of the failure mode assessments. Finally, study conclusions are drawn and recommendations for safe operation of the FASTMast structure are presented for consideration.

Shaker, John F.↗

NASA NTRS1991

Variational mechanics analysis of the stresses in microdrop debond specimens

A recently derived variational mechanics analysis of stresses in single-fiber model composites has been applied to the analysis of the stresses in the microdrop debond specimen. The new analysis is more accurate than the commonly applied shear-lag or elastic-plastic analyses. The results from a sample stress state calculation suggest that interfacial failure between the fiber and the microdrop is by mode I or opening mode failure at the beginning of the microdrop. The opening mode failure is caused by a large tensile radial stress at the fiber/matrix interface. Previous analyses of microdrop debond data have been in terms of a shear strength. It is suggested that these analyses misrepresent microdrop debond results and recommend instead a failure analysis based on energy release rate and interfacial fracture toughness. A procedure for calculating the energy release rate for the growth of an interfacial crack is described.

Scheer, Robert J.↗

NASA NTRSDate not supplied

A Misperception in Reliability Growth Modelling

The Duane reliability growth model is n(t)/t = k t^-alpha (1) The reliability growth rate is alpha, the downward slope of n(t)/t versus t. It usually varies from 0.2 to 0.6. k is a constant. Crow used a 56-failure data set to illustrate reliability growth.1 A graphical Duane model fit to this data gives n(t)/t = 0.640 t^-0.283 (2) A problem in using the Duane-Crow reliability growth model is that it assumes that reliability growth continues and the failure rate decreases throughout the test period. It is more usual that reliability growth stops when the failure rated is low enough. Growth testing is often followed by testing with a low constant failure rate due to rare or uncorrectable failure modes. As more and more low constant rate acceptable failures accumulate after the period of reliability growth, the reliability growth time exponent alpha decreases toward zero. This occurs if constant rate failures are treated as occurring during the reliability growth period. It is more accurate to model a period of initial reliability growth followed by testing without repair to more accurately determine the final constant failure rate. This is done in the abcd model. n(t)/t = a t^-b + c from t = 0 to td (3) = c + d after td, where d = a td^-b (4) The term a t^-b describes the continuous reliability growth that continues out to time td and c is the constant uncorrected failure rate. The parameter d represents an additional constant failure rate due to correctable but uncorrected failure modes. After the reliability growth process is terminated, the failure rate n(t)/t = c + d.

Harry W Jones↗

NASA NTRS2003

Effects Of Environmental And Operational Stresses On RF MEMS Switch Technologies For Space Applications

Micro Electro Mechanical Systems (MEMS) have been heralded for their ability to provide tremendous advantages in electronic systems through increased electrical performance, reduced power consumption, and higher levels of device integration with a reduction of board real estate. RF MEMS switch technology offers advantages such as low insertion loss (0.1- 0.5 dB), wide bandwidth (1 GHz-100 GHz), and compatibility with many different process technologies (quartz, high resistivity Si, GaAs) which can replace the use of traditional electronic switches, such as GaAs FETS and PIN Diodes, in microwave systems for low signal power (x < 500 mW) applications. Although the electrical characteristics of RF MEMS switches far surpass any existing technologies, the unknown reliability, due to the lack of information concerning failure modes and mechanisms inherent to MEMS devices, create an obstacle to insertion of MEMS technology into high reliability applications. All MEMS devices are sensitive to moisture and contaminants, issues easily resolved by hermetic or near-hermetic packaging. Two well-known failure modes of RF MEMS switches are charging in the dielectric layer of capacitive membrane switches and contact interface stiction of metal-metal switches. Determining the integrity of MEMS devices when subjected to the shock, vibration, temperature extremes, and radiation of the space environment is necessary to facilitate integration into space systems. This paper will explore the effects of different environmental stresses, operational life cycling, temperature, mechanical shock, and vibration on the first commercially available RF MEMS switches to identify relevant failure modes and mechanisms inherent to these device and packaging schemes for space applications. This paper will also describe RF MEMS Switch technology under development at NASA GSFC.

Jah, Muzar↗

DOE OSTI2023

PacWave South SeaRAY k2 Risk Registers

The SeaRAY is a deployable power system for maritime sensors, monitoring equipment, communications, unmanned underwater vehicles, and other similar payloads. This project is to design, deliver, and test a prototype low-power WEC that lowers the total cost of ownership and provides robust, new capabilities for customers in the maritime environment. Failure Modes, Effects, and Criticality Analysis (FMECA) is conducted to systematically identify all potential failure modes and their effects on the system, and to analyze the criticality of each risk based on the likelihood of the event and the severity of the impact. Actions may then be recommended to mitigate the criticality of a risk, either by reducing the likelihood of the risk or the severity of its impact. Risk assessment is executed iteratively as an integral part of the design process. By incorporating risk assessment early in the development cycle, mitigation of risk can be achieved cost effectively. The actions recommended to mitigate risk may be subsequently executed, and as the design progresses the risk assessment is reviewed and revised. Review of the risk assessment is integrated into structured design reviews, ensuring that critical risks are comprehended and that the Project will not progress to e.g. fabrication while intolerable risks remain. The risk assessment process results in the population and maintenance of Risk Registers (RRs). Each major system (and as needed, subsystem) will have a distinct RR. This allows each system or subsystem to be assessed individually, rendering the RRs to a manageable size for review.

16 TIDAL AND WAVE POWER↗

NASA NTRS1990

An improved approach for flight readiness assessment

An improved methodology for quantitatively evaluating failure risk for a spaceflight system in order to assess flight readiness is presented. This methodology is of particular value when information relevant to failure prediction, including test experience and knowledge of parameters used in engineering analyses of failure phenomena, is limited. In this approach, engineering analysis models that characterize specific failure modes based on the physics and mechanics of the failure phenomena are used in a prescribed probabilistic structure to generate a failure probability distribution that is modified by test and flight experience in a Bayesian statistical procedure. The probabilistic structure and statistical methodology are generally applicable to any failure mode for which quantitative engineering analysis can be employed to characterize the failure phenomenon and are particularly well suited for use under the constraints on information availability that are typical of such spaceflight systems as the Space Shuttle and planetary spacecraft.

Moore, N. R.↗

DOE OSTI2024

Holistic comparison of environmental barrier coating material candidates through design of a figure of merit

The first figure of merit for environmental barrier coating (EBC) materials was designed through a ranking system for material properties pertaining to established EBC failure modes in service. Seven past, present, and novel EBC candidate materials were used in the figure of merit design: SiO 2 , Ba 0.75 Sr 0.25 Al 2 Si 2 O 8 (BSAS), HfSiO 4 , Yb 2 Si 2 O 7 , Yb 2 SiO 5 , Yb 2 O 3 , and YbPO 4 . Utilizing compiled data from the literature, the presented figure of merit verified Yb 2 Si 2 O 7 as the state-of-the-art candidate with optimal EBC properties and inferred that YbPO 4 should be considered as a potentially viable EBC material candidate. Further, the figure of merit allows for a holistic comparison of EBC candidates and informs experimental and computational search efforts for next-generation complex EBCs. Clear knowledge gaps found through this work include CaO–MgO–Al 2 O 3 –SiO 2 (CMAS)-resistant coatings, EBC lifetimes before delamination, and oxidant diffusion rates in relevant EBC microstructures. It was shown that while some materials show promise for solving a single key failure mode for EBCs (i.e., CMAS reactivity), a community-wide goal should be placed on materials development to achieve acceptable resistance against all major failure modes, which are interconnected. Novel compositionally complex EBC materials, in addition to layered EBC architectures, show promise for the optimization of material properties for long-lifetime EBCs in combustion environments.

36 MATERIALS SCIENCE↗

NASA NTRS1997

Quality Issues in Propulsion

Propulsion system quality is defined in this paper as having high reliability, that is, quality is a high probability of within-tolerance performance or operation. Since failures are out-of-tolerance performance, the probability of failures and their occurrence is the difference between high and low quality systems. Failures can be described at 3 levels: the system failure (which is the detectable end of a failure), the failure mode (which is the failure process), and the failure cause (which is the start). Failure causes can be evaluated & classified by type. The results of typing flight history failures shows that most failures are in unrecognized modes and result from human error or noise, i.e. failures are when engineers learn how things really work. Although the study based on US launch vehicles, a sampling of failures from other countries indicates the finding has broad application. The parameters of the design of a propulsion system are not single valued, but have dispersions associated with the manufacturing of parts. Many tests are needed to find failures, if the dispersions are large relative to tolerances, which could contribute to the large number of failures in unrecognized modes.

McCarty, John P.↗

NASA NTRS2004

Space Shuttle Columbia Reconstruction Effort: An Analysis of the Thermal Protection System.

Upon the breakup of the Space Shuffle Columbia, which occurred during peak heating, at an altitude of 200,000 feet, and traveling at Mach 19, the daunting responsibility was placed upon National Aeronautics and Space Administration (NASA) to determine the root cause of the accident. One of the foremost tasks was to begin locating Columbia's debris, which was scattered acr ss a 2,000 square miles area of Texas and into western Louisiana. Each potential shuttle debris piece found was categorized and the longitude and latitude noted. This provided crucial data to the vehicle's breakup trajectory path and aided in locating key shuffle components. Since the airframe and tiles would be the primary focus during the reconstruction effort at the Kennedy Space center in Florida, packing and shipping was crucial to the preservation of the shape and condition of each recovered object. Over 83,000 pieces of Columbia, in a five-month timeframe, were located. The recovered tiles still bonded to structure indicated failures modes due to heating and aerodynamic loads. Also, different types of tile bond failure modes were observed, with adhesion failures at the Koropon layer or material failure at the tile's densification layer. Numerous tiles had the identification markings burned off, slumping of the Reaction-Cured Glass (RCG) coating, and of the Ll-900 silica base material. The conditions in which the tiles were found resulted in developing methods to aid in the identification of the tile. Correctly identifying each tile was critical to understanding the heating patterns of the tiles in relationship to the vehicle, since it was known that the lower left wing received the initial external tank foam impact. With the aid of multiple disciplines, the clues found in the TPS debris, lead to the root cause of the breakup of Columbia.

Micklos, Ann M.↗

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 NTRS1991

Postbuckling response and failure prediction of flat rectangular graphite-epoxy plates loaded in axial compression

The objectives of the study are to assess the capability of a first-order shear deformable degenerated shell finite element theory to predict the postbuckling response and failure modes of various graphite-epoxy panels loaded in axial compression. Two panels without holes and one with a hole are studied, and the resulting responses and failure modes correlated well with the experimental results. A progressive damage failure mechanism is applied in the nonlinear analysis, which proved successful in predictions of failure location, mode, and load.

Engelstad, S. P.↗

NASA NTRS1993

Evaluating Risk Of Failure With Limited Information

Report describes probabilistic failure assessment (PFA). Developed for application to spaceflight systems for sufficient testing of hardware to ensure reliability not feasible. However, must be ascertained that critical failure modes extremely unlikely to occur during service. PFA applied to any failure mode described by quantitative models of physics and mechanics of failure phenomena, such as fatigue crack in initiation or propagation in structures, leakage of seals, wear in bearings, and erosion of arcjet thrustor cathodes.

Moore, N. R.↗

NASA NTRS1985

Thermal barrier coating life prediction model development

A methodology was established to predict thermal barrier coating life in an environment simulative of that experienced by gas turbine airfoils. Specifically, work is being conducted to determine failure modes of thermal barrier coatings in the aircraft engine environment. Analytical studies coupled with appropriate physical and mechanical property determinations are being employed to derive coating life prediction model(s) on the important failure mode(s). An initial review of experimental and flight service components indicates that the predominant mode of TBC failure involves thermomechanical spallation of the ceramic coating layer. This ceramic spallation involves the formation of a dominant crack in the ceramic coating parallel to and closely adjacent to the metal-ceramic interface. Initial results from a laboratory test program designed to study the influence of various driving forces such as temperature, thermal cycle frequency, environment, and coating thickness, on ceramic coating spalling life suggest that bond coat oxidation damage at the metal-ceramic interface contributes significantly to thermomechanical cracking in the ceramic layer. Low cycle rate furnace testing in air and in argon clearly shows a dramatic increase of spalling life in the non-oxidizing environments.

Sheffler, K. D.↗

NASA NTRS2004

Failure of Non-Circular Composite Cylinders

In this study, a progressive failure analysis is used to investigate leakage in internally pressurized non-circular composite cylinders. This type of approach accounts for the localized loss of stiffness when material failure occurs at some location in a structure by degrading the local material elastic properties by a certain factor. The manner in which this degradation of material properties takes place depends on the failure modes, which are determined by the application of a failure criterion. The finite-element code STAGS, which has the capability to perform progressive failure analysis using different degradation schemes and failure criteria, is utilized to analyze laboratory scale, graphite-epoxy, elliptical cylinders with quasi-isotropic, circumferentially-stiff, and axially-stiff material orthotropies. The results are divided into two parts. The first part shows that leakage, which is assumed to develop if there is material failure in every layer at some axial and circumferential location within the cylinder, does not occur without failure of fibers. Moreover before fibers begin to fail, only matrix tensile failures, or matrix cracking, takes place, and at least one layer in all three cylinders studied remain uncracked, preventing the formation of a leakage path. That determination is corroborated by the use of different degradation schemes and various failure criteria. Among the degradation schemes investigated are the degradation of different engineering properties, the use of various degradation factors, the recursive or non-recursive degradation of the engineering properties, and the degradation of material properties using different computational approaches. The failure criteria used in the analysis include the noninteractive maximum stress criterion and the interactive Hashin and Tsai-Wu criteria. The second part of the results shows that leakage occurs due to a combination of matrix tensile and compressive, fiber tensile and compressive, and inplane shear failure modes in all three cylinders. Leakage develops after a relatively low amount of fiber damage, at about the same pressure for three material orthotropies, and at approximately the same location.

Hyer, M. W.↗