Probabilistic engineering analysis using the NESSUS software

The ability to quantify the uncertainty of complex engineering structures subject to inherent randomness in loading, material properties, and geometric parameters is becoming increasingly important in the design and analysis of structures. Probabilistic analysis provides a means to quantify the reliability of complex systems in such areas as aerospace and automotive industries. Since structural analysis predictions are often based on the results of commercial finite element (FEM) programs (e.g., ABAQUS, ANSYS, and MSC/NASTRAN), probabilistic analysis methods must be linked to such programs to achieve useful reliability results. The NESSUS probabilistic analysis software combines state-of-the-art probabilistic analysis algorithms with general-purpose analysis packages to compute the probabilistic response and the reliability of engineering structures. In this paper, the NESSUS capabilities are presented and demonstrated for several application problems. Introduction and Background Numerical simulation is now routinely used to predict the behavior and response of complex systems. Computational simulation is being increasingly used as performance requirements for engineering structures increase and as a means of reducing testing. Since structural performance is directly affected by uncertainties associated with models or in physical parameters and loadings, the development and Senior Research Engineer, Member AIAA Principal Engineer, Senior Member AIAA Principal Engineer, Member AIAA Staff Engineer, Senior Member AIAA Senior Research Engineer ABAQUS is a registered trademark of Hibbitt, Karlsson, and Sorensen, Inc. ANSYS is a registered trademark of ANSYS, Inc. MSC is a registered trademark of the McNeal-Schwendler Corporation NESSUS is a registered trademark is SwRI. application of probabilistic analysis methods suitable for use with complex numerical models is needed. The traditional method of probabilistic analysis is Monte Carlo simulation. This approach generally requires a large number of simulations to calculate low or high probabilities, and is impractical when each simulation involves extensive finite element computations. Approximate fast probability integration (FPI) methods have been shown to be many times more efficient than Monte Carlo simulation and can often provide sufficient accuracy for engineering predictions. In many situations, the advanced mean value (AMV) procedure, based on FPI, can predict the probabilistic response of complex structures with relatively few response calculations. These methods also provide probabilistic sensitivity measures indicating the input parameters that influence the reliability the most. Beginning with the development of the NESSUS probabilistic analysis computer program, Southwest Research Institute (SwRI) has been addressing the need for efficient probabilistic analysis methods for over fifteen years. NESSUS can be used to simulate uncertainties in loads, geometry, material behavior, and other user-defined random variables to predict the probabilistic response, reliability and probabilistic sensitivity measures of systems. NESSUS provides a built-in finite element structural modeling capability as well as interfaces to many commercially available finite element programs. This paper discusses the current capabilities of the NESSUS software and presents several application problems to demonstrate its effectiveness.