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At least 37 records · Page 2

Prognostic Launch Vehicle Probability of Failure Assessment Methodology for Conceptual Systems Predicated on Human Causal Factors

Lessons learned from past failures of launch vehicle developments and operations were used to create a new method to predict the probability of failure of conceptual systems. Existing methods such as Probabilistic Risk Assessments and Human Risk Assessments were considered but found to be too cumbersome for this type of system-wide application for yet-to-be-flown vehicles. The basis for this methodology were historic databases of past failures, where it was determined that various faulty human-interactions were the predominant root causes of failure rather than deficient component reliabilities evaluated through statistical analysis. This methodology contains an expert scoring part which can be used in either a qualitative or a quantitative mode. The method produces two products: a numerical score of the probability of failure or guidance to program management on critical areas in need of increased focus to improve the probability of success. In order to evaluate the effectiveness of this new method, data from a concluded vehicle program (USAF's Titan IV with the Centaur G-Prime upper stage) was used as a test case. Although the theoretical vs. actual probability of failure was found to be in reasonable agreement (4.46% vs. 6.67% respectively) the underlying sub-root cause scoring had significant disparities attributable to significant organizational changes and acquisitions. Recommendations are made for future applications of this method to ongoing launch vehicle development programs.

Craig H Williams↗

Statistical study of thermal fracture of ceramic materials in the water quench test

The Weibull statistical theory of fracture was applied to thermal shock of ceramics in the water quench test. Transient thermal stresses and probability of failure were calculated for a cylindrical specimen cooled by convection. The convective heat transfer coefficient was calibrated using the time to failure which was measured with an acoustic emission technique. Theoretical failure probability distributions as a function of time and quench temperature compare favorably with experimental results for three high-alumina ceramics and a glass.

Rogers, Wayne P.↗

Probabilistic Prediction of Lifetimes of Ceramic Parts

ANSYS/CARES/PDS is a software system that combines the ANSYS Probabilistic Design System (PDS) software with a modified version of the Ceramics Analysis and Reliability Evaluation of Structures Life (CARES/Life) Version 6.0 software. [A prior version of CARES/Life was reported in Program for Evaluation of Reliability of Ceramic Parts (LEW-16018), NASA Tech Briefs, Vol. 20, No. 3 (March 1996), page 28.] CARES/Life models effects of stochastic strength, slow crack growth, and stress distribution on the overall reliability of a ceramic component. The essence of the enhancement in CARES/Life 6.0 is the capability to predict the probability of failure using results from transient finite-element analysis. ANSYS PDS models the effects of uncertainty in material properties, dimensions, and loading on the stress distribution and deformation. ANSYS/CARES/PDS accounts for the effects of probabilistic strength, probabilistic loads, probabilistic material properties, and probabilistic tolerances on the lifetime and reliability of the component. Even failure probability becomes a stochastic quantity that can be tracked as a response variable. ANSYS/CARES/PDS enables tracking of all stochastic quantities in the design space, thereby enabling more precise probabilistic prediction of lifetimes of ceramic components.

Nemeth, Noel N.↗

Quantifying parameters for Bayesian prior assumptions when estimating the probability of failure of software

Software reliability has become increasingly important, especially in life-critical situations. The ability to measure the results of testing and to quantify software reliability is needed. If this is accomplished, a certain minimum amount of reliability for a piece of software can be specified, and testing and/or other analysis may be done until that minimum number has been attained. There are many models for estimating software reliability. The accuracy of these models has been challenged and many revisions for the models and recalibration techniques have been devised. Of particular interest is the method of estimating the probability of failure of software when no failures have yet occurred in its current version as described by Miller. This model uses black box testing with formulae based on Bayesian estimation. The focus is on three interrelated issues: estimating the probability of failure when testing has revealed no errors; modifying this estimation when the input use distribution does not match the test distribution; and combining the results from random testing with other relevant information to obtain a possibly more accurate estimate of the probability of failure. Obtaining relevant information about the software and combining the results for a better estimate for the Miller model are discussed.

Long, Jacquelyn E.↗

An experimental evaluation of software redundancy as a strategy for improving reliability

The strategy of using multiple versions of independently developed software as a means to tolerate residual software design faults is suggested by the success of hardware redundancy for tolerating hardware failures. Although, as generally accepted, the independence of hardware failures resulting from physical wearout can lead to substantial increases in reliability for redundant hardware structures, a similar conclusion is not immediate for software. The degree to which design faults are manifested as independent failures determines the effectiveness of redundancy as a method for improving software reliability. Interest in multi-version software centers on whether it provides an adequate measure of increased reliability to warrant its use in critical applications. The effectiveness of multi-version software is studied by comparing estimates of the failure probabilities of these systems with the failure probabilities of single versions. The estimates are obtained under a model of dependent failures and compared with estimates obtained when failures are assumed to be independent. The experimental results are based on twenty versions of an aerospace application developed and certified by sixty programmers from four universities. Descriptions of the application, development and certification processes, and operational evaluation are given together with an analysis of the twenty versions.

Eckhardt, Dave E., Jr.↗

An experimental evaluation of software redundancy as a strategy for improving reliability

The strategy of using multiple versions of independently developed software as a means to tolerate residual software design faults is suggested by the success of hardware redundancy for tolerating hardware failires. Although, as generally accepted, the independence of hardware failures resulting from physical wearout can lead to substantial increases in reliability for redundant hardware structures, a similar conclusion is not immediate for software. The degree to which design faults are manifested as independent failures determines the effectiveness of redundancy as a method for improving software reliability. Interest in multi-version software centers on whether it provides an adequate measure of increased reliability to warrant its use in critical applications. The effectiveness of multi-version software is studied by comparing estimates of the failure probabilities of these systems with the failure probabilities of single versions. The estimates are obtained under a model of dependent failures and compared with the estimates obtained when failures are assumed to be independent. The experimental results are based on twenty versions of an aerospace application developed and certified by sixty programmers from four universities. Descriptions of the application, development and certifications processes, and operational evaluation are given together with an analysis of the twenty versions.

Eckhardt, Dave E.↗

Probability of failure prediction for step-stress fatigue under sine or random stress

A previously proposed cumulative fatigue damage law is extended to predict the probability of failure or fatigue life for structural materials with S-N fatigue curves represented as a scatterband of failure points. The proposed law applies to structures subjected to sinusoidal or random stresses and includes the effect of initial crack (i.e., flaw) sizes. The corrected cycle ratio damage function is shown to have physical significance.

Lambert, R. G.↗

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↗

NESTEM-QRAS: A Tool for Estimating Probability of Failure

An interface between two NASA GRC specialty codes, NESTEM and QRAS has been developed. This interface enables users to estimate, in advance, the risk of failure of a component, a subsystem, and/or a system under given operating conditions. This capability would be able to provide a needed input for estimating the success rate for any mission. NESTEM code, under development for the last 15 years at NASA Glenn Research Center, has the capability of estimating probability of failure of components under varying loading and environmental conditions. This code performs sensitivity analysis of all the input variables and provides their influence on the response variables in the form of cumulative distribution functions. QRAS, also developed by NASA, assesses risk of failure of a system or a mission based on the quantitative information provided by NESTEM or other similar codes, and user provided fault tree and modes of failure. This paper will describe briefly, the capabilities of the NESTEM, QRAS and the interface. Also, in this presentation we will describe stepwise process the interface uses using an example.

Patel, Bhogilal M.↗

A Confidence-Based Approach to Including Survivors in a Probabilistic TID Failure Assessment

A probabilistic total ionizing dose (TID) failure assessment is extended to include survivor data, enabling the bounding of failure probability to a desired confidence level (CL) without failure data. The extension provides an avenue for analyzing microelectronics tested for TID without reaching a failure mode, a scenario often encountered by missions utilizing commercial-off-the-shelf (COTS) technologies. Using the type-I censored likelihood formulation and a realistic upper bound on expected device performance, the failure probability space is bounded by confidence contours within the context of a variable environment. The framework accommodates any type of distribution assumed for the part failure or the environment under consideration. Furthermore, the framework can be utilized pre-emptively to plan future device TID tests, minimizing costs while meeting survival requirements. Heritage data may also be used as survivors to further minimize testing costs when parts are from the same lot, but the amount of constraint derived from heritage is limited. Altogether, the framework enables a formal, mathematically rigorous analysis of radiation tolerant devices tested to a maximum dose, as well as flight heritage, in a hardness assurance methodology.

confidence↗

A Prognostic Launch Vehicle Probability of Failure Assessment Methodology for Conceptual Systems Predicated on Human Causal Factors

Create an improved method to calculate reliability of a conceptual launch vehicle system prior to fabrication by using historic data of actual root causes of failures. While failures have unique "proximate causes", there are typically a finite amount of common "root causes". Heretofore launch vehicle reliability evaluation typically hardware-centric statistical analyses, while most root causes of failures are been shown to be human-centric. A method based on human-centric root causes can be used to quantify reliability assessments and focus proposed actions to mitigate problems. Existing methods have been optimistic in their projections of launch vehicle reliability compared to actuals. Hypothesis: reliability of a conceptual launch vehicle can be more accurately evaluated based on a rational, probabilistic approach using past failure assessment teams' findings predicated on human-centric causes."Human Reliability Analysis Methods Selection Guidance for NASA"Chandler F.T., et al., NASA HQ/OSMA study group, July 2006. Outside HRA experts from academia, other federal labs, and the private sector. 50 system reliability methods considered, fourteen selected for further study, four finally selected as best suited for human spaceflight. Probabilistic Risk Analysis (PRA) + Human Reliability Analysis (HRA) enabled incorporating effects and probabilities of human errors. While four down-selected methods deemed appropriate for failure assessment, it did not appear that these methods could be concisely applied to perform major system-wide assessment of probability of failure of a conceptual design without becoming unwieldy."Engineering a Safer World", Detailed, comprehensive study external to NASA Leveson N. G., MIT, 2011.Systems-Theoretic Accident Model and Processes (STAMP). All-encompassing accident model based on systems theory analyzed accidents after they occurred and created approaches to prevent occurrence in developing systems not focused on failure prevention per se, but rather reducing hazards by influencing human behavior through use of constraints, hierarchical control structures, and process models to improve system safetySystem Theoretic Process Analysis (STPA) addresses predictive part of problem (a "hazard analysis"). Includes all causal factors identified in STAMP: "...design errors, software flaws, component interaction accidents, cognitively complex human decision-making errors, and social organizational and management factors contributing to accidents" can guide design process rather than require it to exist before-hand did not appear capable of concise application for system-wide assessment of probability of failure of a conceptual design without becoming unwieldy.

Williams, Craig H.↗

A Reliability Model to Assess Reliability of Shuttle Derived Launch Vehicle and Next Generation Vehicles

One important thrust in NASA s space exploration vision is to improve the safety and reliability of future launch vehicles. A quantitative reliability model is an essential technical tool to evaluate launch vehicle reliability and to enhance launch vehicle configuration down selection and detailed designs. A quantitative reliability model that supports NASA's thrust has been developed and implemented in an MS Excel spreadsheet. The model addresses key reliability parameters, and provides for sensitivity analysis of various vehicle designs. This paper presents the specific elements of the model and examples of selected sensitivity analysis results. Reliability input parameters in the model include the following: 1. Main propulsion element failure probability; 2. Propulsion element catastrophic failure fraction (Cf). This is defined as the ratio of probability of uncontained failures over sum of probability of uncontained failures and contained failures); 3. Engine-out design vs. no-engine-out design; 4. Engine with redlines vs. no redlines; 5. Different levels of health management system implementation; 6. Launch Escape System (LES) reliability; and 7. Power level correlation with reliability. The sensitivity results will illustrate the impact of each of the above parameters on several reliability metrics: Loss of Mission (LOM), LOV (Loss of Vehicle) and Loss of Crew (LOC).

Huang, Zhao↗

Ares I-X First Flight Loss of Vehicle Probability Analysis

As part of the Constellation (Cx) Program development effort, several test flights were planned to prove concepts and operational capabilities of the new vehicles being developed. The first test, involving the Eastern Test Range, is the Ares I-X launched in 2009. As part of this test, the risk to the general public was addressed to ensure it is within Air Force requirements. This paper describes the methodology used to develop first flight estimates of overall loss of vehicle (LOV) failure probability, specifically for the Ares I-X. The method described in this report starts with the Air Force s generic failure probability estimate for first flight and adjusts the value based on the complexity of the vehicle as compared to the complexity of a generic vehicle. The results estimate a 1 in 9 probability of failure. The paper also describes traditional PRA methods used in this assessment, which were then combined with the updated first flight risk methodology to generate inputs required by the malfunction turn analysis to support estimate of casualty (Ec) calculations as part of the Final Flight Data Package (FFDP) delivered to the Eastern Range for Final Flight Plan Approval.

Bigler, Mark A.↗

Stochastic damage evolution in textile laminates

A probabilistic model utilizing random material characteristics to predict damage evolution in textile laminates is presented. Model is based on a division of each ply into two sublaminas consisting of cells. The probability of cell failure is calculated using stochastic function theory and maximal strain failure criterion. Three modes of failure, i.e. fiber breakage, matrix failure in transverse direction, as well as matrix or interface shear cracking, are taken into account. Computed failure probabilities are utilized in reducing cell stiffness based on the mesovolume concept. A numerical algorithm is developed predicting the damage evolution and deformation history of textile laminates. Effect of scatter of fiber orientation on cell properties is discussed. Weave influence on damage accumulation is illustrated with the help of an example of a Kevlar/epoxy laminate.

Dzenis, Yuris A.↗

AXAF Hypervelocity Impact Test Results

Composite and honeycomb panels are commonly used for spacecraft structural components. The impact test results and analysis of six different composite and honeycomb combinations for use on the advanced X-ray astrophysics facility (AXAF) are reported. The AXAF consists of an X-ray telescope and the associated detecting devices attached to an octagonal spacecraft with an internal propulsion system. The spacecraft's structural panels and optical bench are made of two different graphite fiber reinforced polyimides or composite panels bonded to either side of an aluminum honeycomb. The instrument is required to have at least a 0.92 probability of no failure of any of the critical elements due to meteoroids and debris. In relation to the no-failure probability determination in its low earth orbit environment, hypervelocity impact testing was performed to determine the ballistic limit range and the extent of damage due to impact. The test results for a power and signal cable bundle located behind a panel are presented. Tests planned for a multilayer insulation (MLI) blanket and four types of cable bundles are discussed.

Cynthia L Frost↗

Fault Tree Based Diagnosis with Optimal Test Sequencing for Field Service Engineers

When field service engineers go to customer sites to service equipment, they want to diagnose and repair failures quickly and cost effectively. Symptoms exhibited by failed equipment frequently suggest several possible causes which require different approaches to diagnosis. This can lead the engineer to follow several fruitless paths in the diagnostic process before they find the actual failure. To assist in this situation, we have developed the Fault Tree Diagnosis and Optimal Test Sequence (FTDOTS) software system that performs automated diagnosis and ranks diagnostic hypotheses based on failure probability and the time or cost required to isolate and repair each failure. FTDOTS first finds a set of possible failures that explain exhibited symptoms by using a fault tree reliability model as a diagnostic knowledge to rank the hypothesized failures based on how likely they are and how long it would take or how much it would cost to isolate and repair them. This ordering suggests an optimal sequence for the field service engineer to investigate the hypothesized failures in order to minimize the time or cost required to accomplish the repair task. Previously, field service personnel would arrive at the customer site and choose which components to investigate based on past experience and service manuals. Using FTDOTS running on a portable computer, they can now enter a set of symptoms and get a list of possible failures ordered in an optimal test sequence to help them in their decisions. If facilities are available, the field engineer can connect the portable computer to the malfunctioning device for automated data gathering. FTDOTS is currently being applied to field service of medical test equipment. The techniques are flexible enough to use for many different types of devices. If a fault tree model of the equipment and information about component failure probabilities and isolation times or costs are available, a diagnostic knowledge base for that device can be developed easily.

Iverson, David L.↗

A theoretical basis for the analysis of redundant software subject to coincident errors

Fundamental to the development of redundant software techniques fault-tolerant software, is an understanding of the impact of multiple-joint occurrences of coincident errors. A theoretical basis for the study of redundant software is developed which provides a probabilistic framework for empirically evaluating the effectiveness of the general (N-Version) strategy when component versions are subject to coincident errors, and permits an analytical study of the effects of these errors. The basic assumptions of the model are: (1) independently designed software components are chosen in a random sample; and (2) in the user environment, the system is required to execute on a stationary input series. The intensity of coincident errors, has a central role in the model. This function describes the propensity to introduce design faults in such a way that software components fail together when executing in the user environment. The model is used to give conditions under which an N-Version system is a better strategy for reducing system failure probability than relying on a single version of software. A condition which limits the effectiveness of a fault-tolerant strategy is studied, and it is posted whether system failure probability varies monotonically with increasing N or whether an optimal choice of N exists.

Eckhardt, D. E., Jr.↗

A Probabilistic Design Method Applied to Smart Composite Structures

A probabilistic design method is described and demonstrated using a smart composite wing. Probabilistic structural design incorporates naturally occurring uncertainties including those in constituent (fiber/matrix) material properties, fabrication variables, structure geometry and control-related parameters. Probabilistic sensitivity factors are computed to identify those parameters that have a great influence on a specific structural reliability. Two performance criteria are used to demonstrate this design methodology. The first criterion requires that the actuated angle at the wing tip be bounded by upper and lower limits at a specified reliability. The second criterion requires that the probability of ply damage due to random impact load be smaller than an assigned value. When the relationship between reliability improvement and the sensitivity factors is assessed, the results show that a reduction in the scatter of the random variable with the largest sensitivity factor (absolute value) provides the lowest failure probability. An increase in the mean of the random variable with a negative sensitivity factor will reduce the failure probability. Therefore, the design can be improved by controlling or selecting distribution parameters associated with random variables. This can be implemented during the manufacturing process to obtain maximum benefit with minimum alterations.

Shiao, Michael C.↗