Failure of Apollo Saturn V liquid oxygen loading system.
Apollo Saturn 5 liquid oxygen loading system failure, discussing reasons for rupture of main transfer line, fluid velocities and liquid-vapor interfaces
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Apollo Saturn 5 liquid oxygen loading system failure, discussing reasons for rupture of main transfer line, fluid velocities and liquid-vapor interfaces
O-ring response and sealing in pressurized shell structures is examined. The study found that the key elements in the failure of the seal to be joint opening and rotation, assembly out of roundness, and O-ring seal response.
This investigative program examines leakage testing of elastomeric O-ring seals for a solid rocket casing and provides direction towards an improved nondestructive postassembly test. It also details test equipment for the Space Shuttle systems solid rocket boosters (SRB). The results are useful to designers of hardware for pressure containment vessels which use O-ring seals. Using several subscale seal and groove configuration test fixtures equipped with either two or three O-ring seals in series, seal integrity is investigated with both a pressure decay and flowmeter methods. Both types of test equipment adequately detect the practical range of expected seal leak rates of 1 to 0.0001 sccs. The flowmeter leak test equipment appears to reduce testing time substantially. Limited seal leakage testing is performed on full-sized rocket motor segment seals, a pre-Challenger short stack, providing comparison of bore seals to test specimen bore and face seals. The conclusions are that seal reliability, verified via a performance pressure test, can be affected by temperature, quantity of grease, test pressure, and seal pressure load direction. Potential seal failure scenarios including contamination, seal damage, and sealing surface damage are discussed. Recommendations are made for an improved test procedure.
An overview of technical and economic matters relating to the eventual success or failure of the SSPP concept is presented, with emphasis on the pollution and energy problems which the SSPP would serve to eliminate. Factors discussed include cost, mariculture possibilities, siting, legal limitations, design materials, mooring and anchoring, and the human element involved. Several alternative power systems are considered for incorporation into SSPP design, such as Nitinol power, Claude cycle, and closed cycle engine systems.
An improved methodology for quantitatively evaluating failure risk of spaceflight systems to assess flight readiness and identify risk control measures is presented. This methodology, called Probabilistic Failure Assessment (PFA), combines operating experience from tests and flights with analytical modeling of failure phenomena to estimate failure risk. The PFA methodology is of particular value when information on which to base an assessment of failure risk, including test experience and knowledge of parameters used in analytical modeling, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which analytical models that characterize failure phenomena are used conjointly with uncertainties about analysis parameters and/or modeling accuracy to estimate failure probability distributions for specific failure modes. These distributions can then be modified, by means of statistical procedures of the PFA methodology, to reflect any test or flight experience. State-of-the-art analytical models currently employed for designs failure prediction, or performance analysis are used in this methodology. The rationale for the statistical approach taken in the PFA methodology is discussed, the PFA methodology is described, and examples of its application to structural failure modes are presented. The engineering models and computer software used in fatigue crack growth and fatigue crack initiation applications are thoroughly documented.
An improved methodology for quantitatively evaluating failure risk of spaceflights systems to assess flight readiness and identify risk control measures is presented. This methodology, called Probabilistic Failure Assessment (PFA), combines operating experience from tests and flights with analytical modeling of failure phenomena to estimate failure risk. The PFA methodology is of particular value when information on which to base an assessment of failure risk, including test experience and knowledge of parameters used in analytical modeling, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which analytical models that characterize failure phenomena are used conjointly with uncertainties about analysis parameters and/or modeling accuracy to estimate failure probability distributions for specific failure modes. These distributions can then be modified, by means of statistical procedures of the PFA methodology, to reflect any test or flight experience. State-of-the-art analytical models currently employed for design, failure prediction, or performance analysis are used in this methodology. The rationale for the statistical approach taken in the PFA methodology is discussed, the PFA methodology is described, and examples of its application to structural failure modes are presented. The engineering models and computer software used in fatigue crack growth and fatigue crack initiation applications are thoroughly documented.
Information on probabilistic structural analysis methods for space propulsion systems is given in viewgraph form. Information is given on deterministic certification methods, probability of failure, component response analysis, stress responses for 2nd stage turbine blades, Space Shuttle Main Engine (SSME) structural durability, and program plans. .
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.
In 1972, when engineers at Hughes Aircraft Corporation discovered that errors in their satellite avionics were being caused by cosmic rays (so-called single-event effects, or SEE), Moore's Law was only 7 years old. Now, more than 45 years on, the scaling that drove Moore's Law for its first 35 years has reached its limits. However, electronics technology continues to evolve exponentially and SEE remain a formidable issue for use of electronics in space. SEE occur when a single ionizing particle passes through a sensitive volume in an active semiconductor device and generates sufficient charge to cause anomalous behavior or failure in the device. Because SEE can occur at any time during the mission, the emphasis of SEE risk management methodologies is ensuring that all SEE modes in a device under test are detected by the test. Because a particle's probability of causing an SEE generally increases as the particle becomes more ionizing, heavy-ion beams have been and remain the preferred tools for elucidating SEE vulnerabilities. In this talk we briefly discuss space radiation environments and SEE mechanisms, describe SEE test methodologies and discuss current and future challenges for use of heavy-ion beams for SEE testing in an era when the continued validity of Moore's law depends on innovation rather than CMOS scaling.
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.
Owing to the frequency of occurrence and high risk associated with bearings, identification and characterization of bearing faults in motors via nondestructive evaluation (NDE) methods have been studied extensively, amongst which vibration analysis has been found to be a promising technique for early diagnosis of anomalies. However, a majority of the existing techniques rely on vibration sensors attached onto or in close proximity to the motor in order to collect signals with a relatively high SNR. Due to weight and space restrictions, these techniques cannot be used in unmanned aerial vehicles (UAVs), especially during flight operations since accelerometers cannot be attached onto motors in small UAVs. Small UAVs are often subjected to vibrational disturbances caused by multiple factors such as weather turbulence, propeller imbalance or bearing faults. Such anomalies may not only pose risks to UAV's internal circuitry, components or payload, they may also generate undesirable noise level particularly for UAVs expected to fly in low-altitudes or urban canyon. This paper presents a detailed discussion of challenges in in-flight detection of bearing failure in UAVs using existing approaches and offers potential solutions to detect overall vibration anomalies in small UAV operations based on IMU data.
Two samples of the Murchinson C2 chondrite were analyzed for organic nitrogen compounds, using mass spectrometry in combination with paper and thin-layer chromatography. Under mild extraction conditions (water or formic acid), only alphatic amines and some alkylpyridines were seen. Drastic extraction conditions (hot 3-6 M HCL) a variety of nitrogen compounds appeared, including adenine (15 ppm), guanine (5ppm), melamine (20 ppm), cyanuric acid (20 to 30 ppm), guanylurea (30 to 45 ppm), and urea (25 ppm). It appears that these compounds are present mainly in macromolecular material. Failure of other investigators to identify these compounds in carboneceous chondrites is attributed to inadequate extraction conditions (water and formic acid rather than HCl).
A quantitative methodology for estimating the probability of occurrence of critical structural failure modes of launch vehicle propulsion systems during mission operation is presented. In this approach, engineering analysis models that characterize specific failure modes based on the physics and mechanics of the failure phenomenon are used in a prescribed probabalistic structure in which quantified uncertainty in the information used in the analysis and quantified uncertainty of the engineering analysis models themselves are both considered in estimating failure risk. The methodology is applicable to high cycle fatigue, low cycle fatigue, flaw propagation stress rupture, and other failure modes of launch vehicle propulsion systems and other space-flight systems. The probabalistic failure assessment presented provides the capability of performing quantitative analyses to rank options to improve reliability, thereby enabling limited financial resources of development and improvement programs to be more effectively allocated.
A probabilistic fracture mechanics approach for predicting the failure life distribution due to subcritical crack growth is presented. A state-of-the-art crack propagation method is used in a Monte Carlo simulation to generate a distribution of failure lives. The crack growth failure model expresses failure life as a function of stochastic parameters including environment, loads, material properties, geometry, and model specification errors. A stochastic crack growth rate model that considers the uncertainties due to scatter in the data and mode misspecification is proposed. The rationale for choosing a particular type of probability distribution for each stochastic input parameter and for specifying the distribution parameters is presented. The approach is demonstrated through a probabilistic crack growth failure analysis of a welded tube in the Space Shuttle Main Engine. A discussion of the results from this application of the methodology is given.
An investigation was conducted to determine the cause of the failure of a massive AISI Type 316 stainless steel valve which controlled combustion air to a jet engine test facility. Several through-the-wall cracks were present near welded joints in the valve skirt. The valve had been in outdoor service for 18 years. Samples were taken in the cracked regions for metallographic and chemical analyses. Insulating material and sources of water mist in the vicinity of the failed valve were analyzed for chlorides. A scanning electron microscope was used to determine whether foreign elements were present in a crack. On the basis of the information generated, the failure was characterized as external stress-corrosion cracking. The cracking resulted from a combination of residual tensile stress from welding and the presence of aqueous chlorides. Recommended countermeasures are included.
A probabilistic high cycle fatigue (HCF) failure analysis of a welded duct in a rocket engine of the Space Shuttle main engine class is described. A state-of-the-art HCF failure prediction method was used in a Monte Carlo simulation to generate a distribution of failure lives. A stochastic stress/life model is used for material characterization, and a composite stress history is generated for accurately deriving the stress cycles for the fatigue-damage calculations. The HCF failure model expresses fatigue life as a function of stochastic parameters including environment, loads, material properties, geometry, and model specification errors. A series of HCF failure life analyses were performed to study the impact of a fixed parameter and to assess the importance of each stochastic input parameter through marginal analyses.
The objectives of the last six months were: Continue analysis of Hawaii Ocean Time-series (HOT) bio-optical mooring data, Recover instrumentation from JGOFS cruises in the Southern Ocean and analyze data Maintain documentation of MOCEAN algorithms and software for use by MOCEAN and GLI teams Continue chemostat experiments on the relationship of fluorescence quantum yield to environmental factors. Continue to develop and expand browser-based information system for in situ bio-optical data Work Analysis of Field Data from Hawaii We are continuing to analyze bio-optical data collected at the Hawaii Ocean Time Series mooring. The HOT bio-optical mooring was recovered in May 1998. After retrieving the data, the sensor package was serviced and redeployed. We now have over 18 months of data. These are being analyzed as part of a larger study of mesoscale processes at this JGOFS time series site. We have had some failures in the data logger which have affected the fluorescence channels. These are being repaired. We also had an instrument housing failure, and minor modifications have been made to avoid subsequent problems. In addition, Ricardo Letelier is funded as part of the SeaWiFS calibrator/validation effort (through a subcontract from the University of Hawaii, Dr. John Porter), and he is collecting bio-optical and fluorescence data as part of the HOT activity.
The weldability of W-Cu composite sheet was investigated using simulated and welded joints. The welded joints were produced in a vacuum hot press. Tensile test results showed that simulated joints can provide strength and failure mode data which can be used in joint design for actual weldments. Although all of the welded joints had flaws, a number of these joints were as strong as the W-Cu composite base material.