Probabilistic structural analysis methods for space propulsion system components
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Probabilistic structural analysis methods for space propulsion system components

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Published by National Aeronautics and Space Administration, For sale by the National Technical Information Service in [Washington, DC], [Springfield, Va .
Written in English


  • Space shuttles.,
  • Structural analysis (Engineering)

Book details:

Edition Notes

StatementChristos C. Chamis.
SeriesNASA technical memorandum -- 88861.
ContributionsUnited States. National Aeronautics and Space Administration.
The Physical Object
Pagination1 v.
ID Numbers
Open LibraryOL14662362M

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The main objective of this effort is the development of advanced probabilistic structural analysis methods, which combine the versatility of modernfinite element methodswith the latest developments in the areas of probabilistic modeling and structural reliability. PROBABILISTIC STRUCTURAL ANALYSIS METHODS (PSAM) The focus of the PSAM contractual effort4,5, is to develop analysis methods and computer programs for predicting the probabilistic response of critical structural components for current and future space propulsions by: The NESSUS code will be verified by Its application to four selected space propulsion system hardware items. These will include the turbine blade, transfer duct, LOX post, and the high pressure oxidizer duct. Experimental data to support the analyses will be compiled and statistically modeled.   Probabilistic structural analysis methods for select space propulsion system structural components (PSAM) Probabilistic structural analysis methods for improving Space Shuttle engine reliability. L. Boyce ; Journal of Propulsion and Power Vol. 5, No. 4 July

perform probabilistic analysis of structures. These components include: an expert system, a probabilistic finite element code, a probabilistic boundary element code and a fast probability integrator. The NESSUS software system is shown in figure 1. An expert system is included to capture and utilize PSAM knowledge and experience. PROBABILISTIC STRUCTURAL ANALYSIS METHODS (PSAM) Overview of PSAM algorithm NESSUS has three functional modules: PRE, FEM and FPI. The PRE (pre-processor) module is responsible for generating independent random variables based on the information of marginal distributions and correlation coefficients[l].Cited by: Burnsick, O.H., "Probabilistic Structural Analysis for Space Propulsion System Components," Advances in Aerospace Structural Analysis, AD (Proceedings of Symposium on Probabilistic . The structural analysis packages include stochastic modeling of loads, material properties, geometry (e.g. tolerances), and boundary conditions. The structural analysis solution is in terms of the cumulative distribution function (CDF) and confidence bounds. Two methods of probability modeling are included in the analysis by:

Probabilistic structural analysis methodology and applications to advanced space propulsion system components. The development of reliability-based design methods requires the development and use of general purpose structural analysis tools that predict the uncertainty of structural response due to uncertainties in a full range of design Cited by: 5. Probabilistic Structural Analysis Methods (PSAM) for select space propulsion system components, part 2. By. A library of structural resistance models is implemented in the Numerical Evaluations of Stochastic Structures Under Stress (NESSUS) code that included fatigue, fracture, creep, multi-factor interaction, and other important effects. Probabilistic Structural Analysis Methods (PSAM) for select space propulsion system structural components. The purpose in doing probabilistic structural analysis is to provide the designer with a more realistic ability to assess the importance of uncertainty in the response of a high performance structure. Probabilistic Structural Analysis Author: T. A. Cruse. Abstract. Development of reliability and risk methods for structural components and structures is a major activity at Lewis Research Center. It consists of six program elements: (1) probabilistic loads, (2) probabilistic finite element analysis, (3) probabilistic material behavior, (4) assessment of reliability and risk, (5) probabilistic structural performance evaluation, and (6) extension to Author: C. C. Chamis.