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NASA NTRS1977

Redundant integrated flight control/navigation inertial sensor complex

A redundant strapdown inertial navigation system for integrated flight control/navigation use is described. Design of the system, which consists of four tuned-gimbal gyros, eight accelerometers, and four processors, is discussed, with emphasis on its compact configuration (13 by 13 by 14 in.), based on symmetry properties of an octahedron. A matrix operator for least-squares combination of data from an arbitrary number of two-degree-of-freedom gyros is derived, and general parity equations for error analysis are given. Self-contained detection and isolation of a two-axis gyro failure is considered; system failure probability, which depends on component failure rates and self-correction capacities, is analyzed. Test data, including typical parity equation responses during motion and simulated gyro and accelerometer failures, are also presented.

Ebner, R. E.↗

NASA NTRS2010

Probabilistic Design Analysis (PDA) Approach to Determine the Probability of Cross-System Failures for a Space Launch Vehicle

Quantifying the probability of significant launch vehicle failure scenarios for a given design, while still in the design process, is critical to mission success and to the safety of the astronauts. Probabilistic risk assessment (PRA) is chosen from many system safety and reliability tools to verify the loss of mission (LOM) and loss of crew (LOC) requirements set by the NASA Program Office. To support the integrated vehicle PRA, probabilistic design analysis (PDA) models are developed by using vehicle design and operation data to better quantify failure probabilities and to better understand the characteristics of a failure and its outcome. This PDA approach uses a physics-based model to describe the system behavior and response for a given failure scenario. Each driving parameter in the model is treated as a random variable with a distribution function. Monte Carlo simulation is used to perform probabilistic calculations to statistically obtain the failure probability. Sensitivity analyses are performed to show how input parameters affect the predicted failure probability, providing insight for potential design improvements to mitigate the risk. The paper discusses the application of the PDA approach in determining the probability of failure for two scenarios from the NASA Ares I project

Shih, Ann T.↗

NASA NTRS1976

Preliminary system design study for a digital fly-by-wire flight control system for an F-8C aircraft

The design of a fly-by-wire control system having a mission failure probability of less than one millionth failures per flight hour is examined. Emphasis was placed on developing actuator configurations that would improve the system performance, and consideration of the practical aspects of sensor/computer and computer/actuator interface implementation. Five basic configurations were defined as appropriate candidates for the F-8C research aircraft. Options on the basic configurations were included to cover variations in flight sensors, redundancy levels, data transmission techniques, processor input/output methods, and servo actuator arrangements. The study results can be applied to fly by wire systems for transport aircraft in general and the space shuttle.

Seacord, C. L.↗

NASA NTRS2007

Design for Reliability and Safety Approach for the NASA New Launch Vehicle

The United States National Aeronautics and Space Administration (NASA) is in the midst of a space exploration program intended for sending crew and cargo to the international Space Station (ISS), to the moon, and beyond. This program is called Constellation. As part of the Constellation program, NASA is developing new launch vehicles aimed at significantly increase safety and reliability, reduce the cost of accessing space, and provide a growth path for manned space exploration. Achieving these goals requires a rigorous process that addresses reliability, safety, and cost upfront and throughout all the phases of the life cycle of the program. This paper discusses the "Design for Reliability and Safety" approach for the NASA new crew launch vehicle called ARES I. The ARES I is being developed by NASA Marshall Space Flight Center (MSFC) in support of the Constellation program. The ARES I consists of three major Elements: A solid First Stage (FS), an Upper Stage (US), and liquid Upper Stage Engine (USE). Stacked on top of the ARES I is the Crew exploration vehicle (CEV). The CEV consists of a Launch Abort System (LAS), Crew Module (CM), Service Module (SM), and a Spacecraft Adapter (SA). The CEV development is being led by NASA Johnson Space Center (JSC). Designing for high reliability and safety require a good integrated working environment and a sound technical design approach. The "Design for Reliability and Safety" approach addressed in this paper discusses both the environment and the technical process put in place to support the ARES I design. To address the integrated working environment, the ARES I project office has established a risk based design group called "Operability Design and Analysis" (OD&A) group. This group is an integrated group intended to bring together the engineering, design, and safety organizations together to optimize the system design for safety, reliability, and cost. On the technical side, the ARES I project has, through the OD&A environment, implemented a probabilistic approach to analyze and evaluate design uncertainties and understand their impact on safety, reliability, and cost. This paper focuses on the use of the various probabilistic approaches that have been pursued by the ARES I project. Specifically, the paper discusses an integrated functional probabilistic analysis approach that addresses upffont some key areas to support the ARES I Design Analysis Cycle (DAC) pre Preliminary Design (PD) Phase. This functional approach is a probabilistic physics based approach that combines failure probabilities with system dynamics and engineering failure impact models to identify key system risk drivers and potential system design requirements. The paper also discusses other probabilistic risk assessment approaches planned by the ARES I project to support the PD phase and beyond.

Safie, Fayssal, M.↗

NASA NTRS2018

Aeroservoelastic Optimization under Stochastic Gust Constraints

This work considers the aeroservoelastic optimization of a highly flexible transport aircraft wingbox with several control surfaces distributed along the trailing edge. The steady deflections of the control surfaces are designed to alleviate static maneuver loads, while the unsteady deflections are designed to alleviate stochastic continuous gust disturbances. Spatially-detailed unsteady stochastic stress and panel buckling constraints are formulated via modal acceleration, and by methods to locate the most-probable failure point along an equal-probability hypersurface. For the case considered here, it is found that the inclusion of such gust constraints during optimization presents a sizable structural mass penalty. In some cases, this mass penalty can be completely recovered with controlled gust load alleviation.

Stanford, Bret K.↗

NASA NTRS1988

Probabilistic model for fracture mechanics service life analysis

The service longevity of complex propulsion systems, such as the Space Shuttle Main Engine (SSME), can be at risk from several competing failure modes. Conventional life assessment practice focuses upon the most severely life-limited feature of a given component, even though there may be other, less severe, potential failure locations. Primary, secondary, tertiary failure modes, as well as their associated probabilities, must also be considered. Futhermore, these probabilities are functions of accumulated service time. Thus a component may not always succumb to the most severe, or even the most probable failure mode. Propulsion system longevity must be assessed by considering simultaneously the actions of, and interactions among, life-limiting influences. These include, but are not limited to, high frequency fatigue (HFF), low cycle fatigue (LCF), and subsequent crack propagation, thermal and acoustic loadings, and the influence of less-than-ideal nondestructive evaluation (NDE). An outline is provided for a probabilistic model for service life analysis, and the progress towards its implementation is reported.

Annis, Charles↗

NASA NTRS2004

Designing to Mitigate Food Growing Failures in Space

Future space life support systems may use crop plants to grow most of the crew s food. A harvest failure can reduce the food available for future consumption. If the previously stored food is insufficient to reach the next harvest, the crew may go hungry. This paper considers how the overall food supply system should be modified to cope with food production failures. The food supply concept for a mission will use grown food, or stored food, cIr both. The optimum food supply mix depends on the costs and failure probabilities of stored and grown food. A simple food system model assumes that either we obtain the nominal harvest or a failure occurs and no food is harvested. Given the probability that any particular harvest fails, it is easy to compute the expected number of failures and the total food shortfall over a mission. If some food is grown and the probability of harvest failure is high, a non-redundant system has an unacceptable likelihood that the crew will have no food for a full harvest period. Food supply reliability must be increased either by supplying more food initially or by increasing food production capacity. We can obtain a very reliable food supply even when the harvest failure rate is high. If the cost of growing food is much less than the cost of providing stored food, it is better to provide redundant food growing capacity than to increase initial storage. A more realistic biomass production failure model allows the harvest amount or time to vary around the nominal values, using stochastic modeling with repeated Monte Carlo simulation, but such failures have minor impact compared to a complete harvest failure.

Jones, Harry↗

NASA NTRS2013

Unit-Sphere Anisotropic Multiaxial Stochastic-Strength Model Probability Density Distribution for the Orientation of Critical Flaws

Models that predict the failure probability of monolithic glass and ceramic components under multiaxial loading have been developed by authors such as Batdorf, Evans, and Matsuo. These "unit-sphere" failure models assume that the strength-controlling flaws are randomly oriented, noninteracting planar microcracks of specified geometry but of variable size. This report develops a formulation to describe the probability density distribution of the orientation of critical strength-controlling flaws that results from an applied load. This distribution is a function of the multiaxial stress state, the shear sensitivity of the flaws, the Weibull modulus, and the strength anisotropy. Examples are provided showing the predicted response on the unit sphere for various stress states for isotropic and transversely isotropic (anisotropic) materials--including the most probable orientation of critical flaws for offset uniaxial loads with strength anisotropy. The author anticipates that this information could be used to determine anisotropic stiffness degradation or anisotropic damage evolution for individual brittle (or quasi-brittle) composite material constituents within finite element or micromechanics-based software

Nemeth, Noel↗

NASA NTRS1974

Determination of failure limits for sterilizable solid rocket motor

A structural evaluation to establish probable failure limits and a series of environmental tests involving temperature cycling, sustained acceleration, and vibration were conducted on an 18-inch diameter solid rocket motor. Despite the fact that thermal, acceleration and vibration loads representing a severe overtest of conventional environmental requirements were imposed on the sterilizable motor, no structural failure of the grain or flexible support system was detected. The following significant conclusions are considered justified. It is concluded that: (1) the flexible grain retention system, which permitted heat sterilization at 275 F on the test motor, can readily be adopted to meet the environmental requirements of an operational motor design, and (2) if further substantiation of structural integrity is desired, the motor used is considered acceptable for static firing.

Lambert, W. L.↗

NASA NTRS1978

Effect of filtration on rolling-element-bearing life in contaminated lubricant environment

Fatigue tests were conducted on groups of 65 millimeter-bore ball bearings under four levels of filtration with and without a contaminated MIL-L-23699 lubricant. The baseline series used noncontaminated oil with 49 micron absolute filtration. In the remaining tests contaminants of the composition found in aircraft engine filters were injected into the filter's supply line at a constant rate of 125 milligrams per bearing-hour. The test filters had absolute particle removal ratings of 3, 30, 49, and 105 microns (0.45, 10, 30, and 70 microns nominal), respectively. Bearings were tested at 15,000 rpm under 4580 newtons radial load. Bearing life and running tract condition generally improved with finer filtration. The 3 and 30 micron filter bearings in a contaminated lubricant had statistically equivalent lives, approaching those from the baseline tests. The experimental lives of 49 micron bearings were approximately half the baseline bearing's lives. Bearings tested with the 105 micron filter experienced wear failures. The degree of surface distress, weight loss, and probable failure mode were found to be dependent on filtration level, with finer filtration being clearly beneficial.

Loewenthal, S. H.↗

NASA NTRS2006

Hard and Soft Constraints in Reliability-Based Design Optimization

This paper proposes a framework for the analysis and design optimization of models subject to parametric uncertainty where design requirements in the form of inequality constraints are present. Emphasis is given to uncertainty models prescribed by norm bounded perturbations from a nominal parameter value and by sets of componentwise bounded uncertain variables. These models, which often arise in engineering problems, allow for a sharp mathematical manipulation. Constraints can be implemented in the hard sense, i.e., constraints must be satisfied for all parameter realizations in the uncertainty model, and in the soft sense, i.e., constraints can be violated by some realizations of the uncertain parameter. In regard to hard constraints, this methodology allows (i) to determine if a hard constraint can be satisfied for a given uncertainty model and constraint structure, (ii) to generate conclusive, formally verifiable reliability assessments that allow for unprejudiced comparisons of competing design alternatives and (iii) to identify the critical combination of uncertain parameters leading to constraint violations. In regard to soft constraints, the methodology allows the designer (i) to use probabilistic uncertainty models, (ii) to calculate upper bounds to the probability of constraint violation, and (iii) to efficiently estimate failure probabilities via a hybrid method. This method integrates the upper bounds, for which closed form expressions are derived, along with conditional sampling. In addition, an l(sub infinity) formulation for the efficient manipulation of hyper-rectangular sets is also proposed.

Crespo, L.uis G.↗

NASA NTRS1993

Recent advances in computational structural reliability analysis methods

The goal of structural reliability analysis is to determine the probability that the structure will adequately perform its intended function when operating under the given environmental conditions. Thus, the notion of reliability admits the possibility of failure. Given the fact that many different modes of failure are usually possible, achievement of this goal is a formidable task, especially for large, complex structural systems. The traditional (deterministic) design methodology attempts to assure reliability by the application of safety factors and conservative assumptions. However, the safety factor approach lacks a quantitative basis in that the level of reliability is never known and usually results in overly conservative designs because of compounding conservatisms. Furthermore, problem parameters that control the reliability are not identified, nor their importance evaluated. A summary of recent advances in computational structural reliability assessment is presented. A significant level of activity in the research and development community was seen recently, much of which was directed towards the prediction of failure probabilities for single mode failures. The focus is to present some early results and demonstrations of advanced reliability methods applied to structural system problems. This includes structures that can fail as a result of multiple component failures (e.g., a redundant truss), or structural components that may fail due to multiple interacting failure modes (e.g., excessive deflection, resonate vibration, or creep rupture). From these results, some observations and recommendations are made with regard to future research needs.

Thacker, Ben H.↗

NASA NTRS1992

Probabilistic evaluation of uncertainties and risks in aerospace components

This paper summarizes a methodology developed at NASA Lewis Research Center which computationally simulates the structural, material, and load uncertainties associated with Space Shuttle Main Engine (SSME) components. The methodology was applied to evaluate the scatter in static, buckling, dynamic, fatigue, and damage behavior of the SSME turbo pump blade. Also calculated are the probability densities of typical critical blade responses, such as effective stress, natural frequency, damage initiation, most probable damage path, etc. Risk assessments were performed for different failure modes, and the effect of material degradation on the fatigue and damage behaviors of a blade were calculated using a multi-factor interaction equation. Failure probabilities for different fatigue cycles were computed and the uncertainties associated with damage initiation and damage propagation due to different load cycle were quantified. Evaluations on the effects of mistuned blades on a rotor were made; uncertainties in the excitation frequency were found to significantly amplify the blade responses of a mistuned rotor. The effects of the number of blades on a rotor were studied. The autocorrelation function of displacements and the probability density function of the first passage time for deterministic and random barriers for structures subjected to random processes also were computed. A brief discussion was included on the future direction of probabilistic structural analysis.

Shah, A. R.↗

NASA NTRS1982

Interconnect fatigue design for terrestrial photovoltaic modules

The results of comprehensive investigation of interconnect fatigue that has led to the definition of useful reliability-design and life-prediction algorithms are presented. Experimental data indicate that the classical strain-cycle (fatigue) curve for the interconnect material is a good model of mean interconnect fatigue performance, but it fails to account for the broad statistical scatter, which is critical to reliability prediction. To fill this shortcoming the classical fatigue curve is combined with experimental cumulative interconnect failure rate data to yield statistical fatigue curves (having failure probability as a parameter) which enable (1) the prediction of cumulative interconnect failures during the design life of an array field, and (2) the unambiguous--ie., quantitative--interpretation of data from field-service qualification (accelerated thermal cycling) tests. Optimal interconnect cost-reliability design algorithms are derived based on minimizing the cost of energy over the design life of the array field.

Mon, G. R.↗

NASA NTRS2024

Redundancy: How Many Unreliable Spares are Needed for High Reliability and Confidence?

This paper investigates the number of redundant units needed to achieve high reliability with high confidence. The approach is developed for the case when the system failure rate is too high for a single unit to provide the required reliability over the mission duration. To achieve high reliability, N redundant units can be used, one operating unit and N – 1 spares. If the unit failure rate is f, the mission length is L, and f * L is small (not the case assumed here), the unit failure probability over the mission duration is F1 = f * L << 1. In this case, the probability that all N units will fail is Ffail = F1 N , and the needed redundancy N = LN(F)/LN(F1). For the case of large f * L assumed here, F1 = f * L > 1, and F1 is the expected number of failures during the mission. (When F1 = f * L << 1, F1 is the probability that a unit will fail during the mission. When F1 = f * L > 1, F1 is the expected number of failures during the mission.) The needed redundancy, N, to achieve the required N redundant unit reliability, FN, can be computed using the cumulative Poisson distribution with mean equal to F1. The number of spares, N - 1, is increased until the probability - that the total number of failures will be less than N -1 - is equal to the required reliability. The confidence that this reliability can be achieved can be computed using the cumulative Poisson distribution or the chi-square distribution. Since the measured unit failure rate, f, has some probabilistic uncertainty, the actual failure rate will be randomly higher or lower. This means that the reliability of the N redundant systems will be overestimated about half the time. Adding more redundant units increases the confidence that the required reliability will be achieved. For a fixed number of redundant units, the expected reliability and confidence can be traded off, since lower reliability goals will be achieved with higher confidence. Both the desired reliability and confidence can be specified as initial requirements and the needed number of redundant units estimated using the measured failure rate.

Redundancy↗

NASA NTRS1973

Space shuttle solid rocket booster recovery system definition, volume 1

The performance requirements, preliminary designs, and development program plans for an airborne recovery system for the space shuttle solid rocket booster are discussed. The analyses performed during the study phase of the program are presented. The basic considerations which established the system configuration are defined. A Monte Carlo statistical technique using random sampling of the probability distribution for the critical water impact parameters was used to determine the failure probability of each solid rocket booster component as functions of impact velocity and component strength capability.

Source record↗

NASA NTRSDate not supplied

Redundancy: How Many Unreliable Spares are Needed for High Reliability and Confidence on a Time Limited Mission?

This paper investigates the number of redundant units needed to achieve high reliability with high confidence. The approach applies to the case where the unit failure rate is too high for a single unit to provide the required reliability over the mission duration. To achieve high reliability, the design then uses N redundant units, one operating unit and N – 1 spares. If the unit failure rate is f, the mission length is L, and f * L is small (not the case assumed here), the unit failure probability over the mission duration is F1 = f * L << 1. In this case, the probability that all N units will fail is FN = F1N, and the needed N = LN(FN)/LN(F1). For the case of large f * L assumed here, F1 = f * L > 1, and F1 is the expected number of failures during the mission. The needed redundancy, N, to achieve the specified N unit reliability, FN, can be computed using the cumulative Poisson distribution with mean equal to F1. The number of spares, N - 1, is increased until the probability - that the total number of failures will be less than N -1 - achieves the required reliability. The confidence that this reliability can be achieved can be computed using the cumulative Poisson distribution or the chi-square distribution. Since the measured unit failure rate, f, has some uncertainty, the confidence that the rate is not lower than the actual failure rate and the required reliability is not overestimated is about 50%. Adding more redundant units increases the confidence that the required reliability, FN, will be achieved. For a fixed number of redundant units, the expected reliability and confidence can be traded off, since lower reliability goals have higher confidence in being achieved. Both the required reliability and confidence can be specified initially and the needed number of redundant units computed using the measured failure rate. The unit failure rate is determined by initial reliability growth testing to remove design errors and to better estimate the final constant failure rate. Reducing the failure rate and reducing its variance both reduce the number of redundant units needed for the required reliability and confidence. Since the total cost is the sum of the costs of the units and of the testing, there is an optimum test time that produces minimum cost.

Harry W. Jones↗

NASA NTRS1995

Alternative Computational Approaches for Probalistic Fatigue Analysis

The feasibility is discussed for alternative methods of direct Monte Carlo simulation for failure probability computations. First and second order reliability methods are used for fatigue crack growth and low cycle fatigue structural failure modes to illustrate typical problems.

fatigue analysis failure models simulation↗