Probabilistic Analysis Using NESSUS (Numerical Evaluation of Stochastic Structures Under Stress)

John M. McFarland () and David S. Riha ()
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John M. McFarland: Southwest Research Institute, Mechanical Engineering Division
David S. Riha: Southwest Research Institute, Mechanical Engineering Division

Chapter 51 in Handbook of Uncertainty Quantification, 2017, pp 1733-1764 from Springer

Abstract: Abstract NESSUS is a general-purpose software program for probabilistic analysis with original development beginning in the 1980s as part of a 10-year NASA project focused on predicting risk and reliability of space shuttle main engine components. NESSUS now includes a streamlined graphical interface, 16 different reliability methods, interfaces to many third-party commercial analysis codes, and the ability to define custom interfaces to computational models. Recent developments have added powerful tools for global sensitivity analysis and have expanded the response surface methods to include Gaussian process modeling. This chapter highlights NESSUS’s core capabilities and gives an overview of setting up and solving a probabilistic analysis problem using the software. A detailed tutorial is used to illustrate how to use NESSUS to perform a probabilistic analysis on a finite element model. A turbine blade case study is then presented to illustrate a practical solution strategy for assessing model uncertainties for computationally intensive models. The strategy demonstrates the use of response surface models and efficient probabilistic methods to make the best use of model evaluations to iteratively improve the uncertainty assessments.

Keywords: Probabilistic analysis; NESSUS; Software; Graphical user interface; AMV; EGRA; Finite element analysis; Response surface; Surrogate model; Gaussian process (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/978-3-319-12385-1_54

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