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At least 271 records · Page 15

An improved approach for flight readiness certification: Methodology for failure risk assessment and application examples, volume 1

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.

Moore, N. R.↗

An improved approach for flight readiness certification: Methodology for failure risk assessment and application examples. Volume 2: Software documentation

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.

Moore, N. R.↗

An improved approach for flight readiness certification: Methodology for failure risk assessment and application examples. Volume 3: Structure and listing of programs

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.

Moore, N. R.↗

Flight test technique for evaluation of gust load alleviation analysis methodology

A technique for gust load alleviation (GLA) flight testing that will approximate a turbulence-like excitation of the wing has been devised. An artificial excitation is produced by randomly deflecting inboard control surfaces on the wing, thereby producing incremental loads on the wing. This presentation covers the background and development of the flight test technique and analyses performed to date.

Perry, B., III↗

Performance evaluation in full-mission simulation - Methodological advances and research challenges

The crew-factors research program at NASA Ames has developed a methodology for studying the impact of a variety of variables on the effectiveness of crews flying realistic but high workload simulated trips. The validity of investigations using the methodology is enhanced by careful design of full-mission scenarios, performance assessment using converging sources of data, and recruitment of representative subjects. Recently, portions of this methodology have been adapted for use in assessing the effectiveness of crew coordination among participants in line-oriented flight training.

Chidester, Thomas R.↗

6th AIAA Biennial Flight Test Conference, Hilton Head Island, SC, Aug. 24-26, 1992, Selected Papers

Topics presented include training for avionics evaluation, flight testing in the '90s, methodology for the critical evaluation of flight test data, flight testing of an electric powered vehicle, and the flying qualities of a remotely piloted vehicle. Also presented are airspeed calibration using GPS, the design and conduct of a windshear detection flight experiment, the 757 fly-by-wire demonstrator flight test, and an update of the B-52 flight test program.

American Institute of Aeronautics and Astronautics↗

Evaluation of a Progressive Failure Analysis Methodology for Laminated Composite Structures

A progressive failure analysis methodology has been developed for predicting the nonlinear response and failure of laminated composite structures. The progressive failure analysis uses C plate and shell elements based on classical lamination theory to calculate the in-plane stresses. Several failure criteria, including the maximum strain criterion, Hashin's criterion, and Christensen's criterion, are used to predict the failure mechanisms. The progressive failure analysis model is implemented into a general purpose finite element code and can predict the damage and response of laminated composite structures from initial loading to final failure.

Sleight, David W.↗

The Evaluation of Cryogenic Force Balance Calibration Methodologies with Respect to Wind Tunnel Results

Independent tests of the NASA Common Research Model (CRM) at NASA's National Transonic Facility (NTF) and the European Transonic Windtunnel (ETW) revealed discrepancies at low operating temperatures and high Reynolds numbers that warranted further investigation. Since each facility used their own force balance for their tunnel entry, one suggestion for the discrepancy was the temperature compensation methodology developed and applied for each balance. This hypothesis is explored through simulation and experimentally. Independent calibrations of NASA's NTF-118A balance at NASA Langley and ETW reveal discrepancies in the thermal compensation of the normal force and pitching moment primary sensitivities with temperature, while the axial force primary sensitivities are in good agreement. The application of the force balance calibrations performed at NASA and ETW to the prior wind tunnel data suggests that the thermal compensation discrepancies are an order of magnitude less than the discrepancies observed between the wind tunnel aerodynamic coefficients.

Burns, Devin E.↗

Advancing Methodologies for Applying Machine Learning and Evaluating Spatiotemporal Models of Fine Particulate Matter (PM 2.5 ) Using Satellite Data Over Large Regions

Reconstructing the distribution of fine particulate matter (PM 2.5 ) in space and time, even far from ground monitoring sites, is an important exposure science contribution to epidemiologic analyses of PM 2.5 health impacts. Flexible statistical methods for prediction have demonstrated the integration of satellite observations with other predictors, yet these algorithms are susceptible to overfitting the spatiotemporal structure of the training datasets. We present a new approach for predicting PM 2.5 using machine-learning methods and evaluating prediction models for the goal of making predictions where they were not previously available. We apply extreme gradient boosting (XGBoost) modeling to predict daily PM 2.5 on a 1 x 1 km 2 resolution for a 13 state region in the Northeastern USA for the years 2000–2015 using satellite-derived aerosol optical depth and implement a recursive feature selection to develop a parsimonious model. We demonstrate excellent predictions of withheld observations but also contrast an RMSE of 3.11 μg/m 3 in our spatial cross-validation withholding nearby sites versus an overfit RMSE of 2.10 μg/m 3 using a more conventional random ten-fold splitting of the dataset. As the field of exposure science moves forward with the use of advanced machine-learning approaches for spatiotemporal modeling of air pollutants, our results show the importance of addressing data leakage in training, overfitting to spatiotemporal structure, and the impact of the predominance of ground monitoring sites in dense urban sub-networks on model evaluation. The strengths of our resultant modeling approach for exposure in epidemiologic studies of PM 2.5 include improved efficiency, parsimony, and interpretability with robust validation while still accommodating complex spatiotemporal relationships.

air pollution↗

NASA PC software evaluation project

The USL NASA PC software evaluation project is intended to provide a structured framework for facilitating the development of quality NASA PC software products. The project will assist NASA PC development staff to understand the characteristics and functions of NASA PC software products. Based on the results of the project teams' evaluations and recommendations, users can judge the reliability, usability, acceptability, maintainability and customizability of all the PC software products. The objective here is to provide initial, high-level specifications and guidelines for NASA PC software evaluation. The primary tasks to be addressed in this project are as follows: to gain a strong understanding of what software evaluation entails and how to organize a structured software evaluation process; to define a structured methodology for conducting the software evaluation process; to develop a set of PC software evaluation criteria and evaluation rating scales; and to conduct PC software evaluations in accordance with the identified methodology. Communication Packages, Network System Software, Graphics Support Software, Environment Management Software, General Utilities. This report represents one of the 72 attachment reports to the University of Southwestern Louisiana's Final Report on NASA Grant NGT-19-010-900. Accordingly, appropriate care should be taken in using this report out of context of the full Final Report.

Dominick, Wayne D.↗

Infrared Algorithm Development for Ocean Observations with EOS/MODIS

Efforts continue under this contract to develop algorithms for the computation of sea surface temperature (SST) from MODIS infrared measurements. This effort includes radiative transfer modeling, comparison of in situ and satellite observations, development and evaluation of processing and networking methodologies for algorithm computation and data accession, evaluation of surface validation approaches for IR radiances, development of experimental instrumentation, and participation in MODIS (project) related activities. Activities in this contract period have focused on radiative transfer modeling, evaluation of atmospheric correction methodologies, undertake field campaigns, analysis of field data, and participation in MODIS meetings.

Brown, Otis B.↗

Methodology issues concerning the accuracy of kinematic data collection and analysis using the ariel performance analysis system

Kinematics, the study of motion exclusive of the influences of mass and force, is one of the primary methods used for the analysis of human biomechanical systems as well as other types of mechanical systems. The Anthropometry and Biomechanics Laboratory (ABL) in the Crew Interface Analysis section of the Man-Systems Division performs both human body kinematics as well as mechanical system kinematics using the Ariel Performance Analysis System (APAS). The APAS supports both analysis of analog signals (e.g. force plate data collection) as well as digitization and analysis of video data. The current evaluations address several methodology issues concerning the accuracy of the kinematic data collection and analysis used in the ABL. This document describes a series of evaluations performed to gain quantitative data pertaining to position and constant angular velocity movements under several operating conditions. Two-dimensional as well as three-dimensional data collection and analyses were completed in a controlled laboratory environment using typical hardware setups. In addition, an evaluation was performed to evaluate the accuracy impact due to a single axis camera offset. Segment length and positional data exhibited errors within 3 percent when using three-dimensional analysis and yielded errors within 8 percent through two-dimensional analysis (Direct Linear Software). Peak angular velocities displayed errors within 6 percent through three-dimensional analyses and exhibited errors of 12 percent when using two-dimensional analysis (Direct Linear Software). The specific results from this series of evaluations and their impacts on the methodology issues of kinematic data collection and analyses are presented in detail. The accuracy levels observed in these evaluations are also presented.

Wilmington, R. P.↗

Probabilistic micromechanics for high-temperature composites

The three-year program of research had the following technical objectives: the development of probabilistic methods for micromechanics-based constitutive and failure models, application of the probabilistic methodology in the evaluation of various composite materials and simulation of expected uncertainties in unidirectional fiber composite properties, and influence of the uncertainties in composite properties on the structural response. The first year of research was devoted to the development of probabilistic methodology for micromechanics models. The second year of research focused on the evaluation of the Chamis-Hopkins constitutive model and Aboudi constitutive model using the methodology developed in the first year of research. The third year of research was devoted to the development of probabilistic finite element analysis procedures for laminated composite plate and shell structures.

Reddy, J. N.↗

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.↗

Pressure Flammability Thresholds in Oxygen of Selected Aerospace Materials

The experimental approach consisted of concentrating the testing in the flammability transition zone following the Bruceton Up-and-Down Method. For attribute data, the method has been shown to be very repeatable and most efficient. Other methods for characterization of critical levels (Karberand Probit) were also considered. The data yielded the upward limiting pressure index (ULPI), the pressure level where approx.50% of materials self-extinguish in a given environment.Parametric flammability thresholds other than oxygen concentration can be determined with the methodology proposed for evaluating the MOC when extinguishment occurs. In this case, a pressure threshold in 99.8% oxygen was determined with the methodology and found to be 0.4 to 0.9 psia for typical spacecraft materials. Correlation of flammability thresholds obtained with chemical, hot wire, and other ignition sources will be conducted to provide recommendations for using alternate ignition sources to evaluate flammability of aerospace materials.

Hirsch, David↗

An improved approach for flight readiness certification: Probabilistic models for flaw propagation and turbine blade failure. Volume 1: Methodology and applications

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.

Moore, N. R.↗

An improved approach for flight readiness certification: Probabilistic models for flaw propagation and turbine blade failure. Volume 2: Software documentation

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.

Moore, N. R.↗