Guidelines for certification of existing sensitive systems
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An averaging total pressure wake rake used by the Cessna Aircraft Company in flight tests of a modified 210 airplane with a laminar flow wing was calibrated in wind tunnel tests against a five-tube pressure probe. The model generating the wake was a full-scale model of the Cessna airplane wing. Indications of drag trends were the same for both instruments.
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This report outlines: (1) thesis; (2) ground clutter challenge; (3) moving scatters (birds, bugs); (4) range ambiguities; and rain attenuation.
Thermal tests of Orbiter thermal protection system (TPS) tiles, which were coated with borosilicate glass slurries fabricated at Kennedy Space Center (KSC), were performed in the Radiant Heat Test Facility and the Atmospheric Reentry Materials & Structures Evaluation Facility at Johnson Space Center to verify tile coating integrity after exposure to multiple entry simulation cycles in both radiant and convective heating environments. Eight high temperature reusable surface insulation (HRSI) tiles and six low temperature reusable surface insulation (LRSI) tiles were subjected to 25 cycles of radiant heat at peaked surface temperatures of 2300 F and 1200 F, respectively. For the LRSI tiles, an additional cycle at peaked surface temperature of 2100 F was performed. There was no coating crack on any of the HRSI specimens. However, there were eight small coating cracks (less than 2 inches long) on two of the six LRSI tiles on the 26th cycle. There was practically no change on the surface reflectivity, physical dimensions, or weight of any of the test specimens. There was no observable thermal-chemical degradation of the coating either. For the convective heat test, eight HRSI tiles were tested for five cycles at a surface temperature of 2300 F. There was no thermal-induced coating crack on any of the test specimens, almost no change on the surface reflectivity, and no observable thermal-chemical degradation with an exception of minor slumping of the coating under painted TPS identification numbers. The tests demonstrated that KSC's TPS slurries and coating processes meet the Orbiter's thermal specification requirements.
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 engineering analysis 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 engineering analyses of failure phenomena, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which engineering analysis 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. Conventional engineering analysis models currently employed for design of failure prediction are used in this methodology. The PFA methodology is described and examples of its application are presented. Conventional approaches to failure risk evaluation for spaceflight systems are discussed, and the rationale for the approach taken in the PFA methodology is presented. The statistical methods, engineering models, and computer software used in fatigue failure mode applications are thoroughly documented.
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 engineering analysis 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 engineering analyses of failure phenomena, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which engineering analysis 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. Conventional engineering analysis models currently employed for design of failure prediction are used in this methodology. The PFA methodology is described and examples of its application are presented. Conventional approaches to failure risk evaluation for spaceflight systems are discussed, and the rationale for the approach taken in the PFA methodology is presented. The statistical methods, engineering models, and computer software used in fatigue failure mode applications are thoroughly documented.
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 engineering analysis 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 engineering analyses of failure phenomena, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which engineering analysis 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. Conventional engineering analysis models currently employed for design of failure prediction are used in this methodology. The PFA methodology is described and examples of its application are presented. Conventional approaches to failure risk evaluation for spaceflight systems are discussed, and the rationale for the approach taken in the PFA methodology is presented. The statistical methods, engineering models, and computer software used in fatigue failure mode applications are thoroughly documented.
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.
This video tape shows the Shuttle hatch jettison test at Rockwell facilities. The video also shows a Shuttle escape pole deployment test from a NASA aircraft, and an emergency egress test performed by a volunteer Navy parachutist using the pole and a parachute escape system.
The effects of atomic oxygen on boron nitride (BN), silicon nitride (Si3N4), Intelsat 6 solar cell interconnects, organic polymers, and MoS2 and WS2 dry lubricant, were studied in Low Earth Orbit (LEO) flight experiments and in a ground based simulation facility. Both the inflight and ground based experiments employed in situ electrical resistance measurements to detect penetration of atomic oxygen through materials and Electron Spectroscopy for Chemical Analysis (ESCA) analysis to measure chemical composition changes. Results are given. The ground based results on the materials studied to date show good qualitative correlation with the LEO flight results, thus validating the simulation fidelity of the ground based facility in terms of reproducing LEO flight results. In addition it was demonstrated that ground based simulation is capable of performing more detailed experiments than orbital exposures can presently perform. This allows the development of a fundamental understanding of the mechanisms involved in the LEO environment degradation of materials.
Superposition testing of detection range performance forms a digital signal for input into a simulation of signal and data processing equipment and algorithms to be employed in a sensor system for advanced warning of hazardous windshear. For suitable pulse-Doppler radar, recording of the digital data at the input to the digital signal processor furnishes a realistic operational scenario and environmentally responsive clutter signal including all sidelobe clutter, ground moving target indications (GMTI), and large signal spurious due to mainbeam clutter and/or RFI respective of the urban airport clutter and aircraft scenarios (approach and landing antenna pointing). For linear radar system processes, a signal at the same point in the process from a hazard phenomena may be calculated from models of the scattering phenomena, for example, as represented in fine 3 dimensional reflectivity and velocity grid structures. Superposition testing furnishes a competing signal environment for detection and warning time performance confirmation of phenomena uncontrollable in a natural environment.
The development of high fidelity models of mechanical systems with flexible components is in flux. Many working models of these devices assume the elastic motion is small and can be superimposed on the overall rigid body motion. A drawback associated with this type of modeling technique is that it is required to regenerate the linear modal model of the device if the elastic motion is sufficiently far from the base rigid motion. An advantage to this type of modeling is that it uses NASTRAN modal data which is the NASA standard means of modal information exchange. A disadvantage to the linear modeling is that it fails to accurately represent large motion of the system, unless constant modal updates are performed. In this study, which is a continuation of a project started last year, the drawback of the currently used modal snapshot modeling technique is addressed in a rigorous fashion by novel and easily applied means.
Software development for NASA missions is a particularly challenging task. Missions are extremely ambitious scientifically, have very strict time frames, and must be accomplished with a maximum degree of reliability. Verification technologies must therefore be pushed far beyond their current capabilities. Moreover, reuse and adaptation of software architectures and components must be incorporated in software development within and across missions. This paper discusses NASA applications that we are currently investigating from these perspectives.
The method planned for the surface figure error measurement of the AMSDs at the XRCF will be discussed. Alignment, surface figure measurement, gravity effects, vibration & temperature environment effects, total error analysis, and data output will be discussed.
AUTOFILTER is a tool for automatically deriving Kalman filter code from high-level declarative specifications of state estimation problems. It can generate code with a range of algorithmic characteristics and for several target platforms. The tool has been designed with reliability of the generated code in mind and is able to automatically certify that the code it generates is free from various error classes. Since documentation is an important part of software assurance, AUTOFILTER can also automatically generate various human-readable documents, containing both design and safety related information. We discuss how these features address software assurance standards such as DO-178B.
Spacecraft such as the Mars Exploration Rovers (MER) must meet acceptable microbial population levels prior to launch. Sensitive parts and materials prevent any single sterilization method from being used as a final step on the assembled spacecraft.