It is challenging to perform probabilistic analysis and design of large-scale structures because it requires repeated finite-element analyses of large models and each analysis is expensive. This paper presents a methodology for probabilistic analysis and reliability-based design optimization of large-scale structures that consists of two re-analysis methods; one for estimating the deterministic vibratory response and another for estimating the probability of the response exceeding a certain level. Deterministic re-analysis can analyze efficiently large-scale finite element models consisting of tens or hundreds of thousand degrees of freedom and large numbers of design variables that vary in a wide range. Probabilistic re-analysis calculates very efficiently the system reliability for different probability distributions of the design variables by performing a single Monte Carlo simulation. The methodology is demonstrated on probabilistic vibration analysis and a reliability-based design optimization of a realistic vehicle model. It is shown that computational cost of the proposed reanalysis method for a single reliability analysis is about 1/20th of the cost of the same analysis using NASTRAN. Moreover, the probabilistic re-analysis approach enables a designer to perform reliability-based design optimization of the vehicle at a cost almost equal to that of a single reliability analysis. Without using the probabilistic re-analysis approach, it would be impractical to perform reliability-based design optimization of the vehicle.
- Design Engineering Division and Computers in Engineering Division
An Efficient Re-Analysis Methodology for Probabilistic Vibration of Large-Scale Structures
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Zhang, G, Nikolaidis, E, & Mourelatos, ZP. "An Efficient Re-Analysis Methodology for Probabilistic Vibration of Large-Scale Structures." Proceedings of the ASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. Volume 1: 34th Design Automation Conference, Parts A and B. Brooklyn, New York, USA. August 3–6, 2008. pp. 1093-1107. ASME. https://doi.org/10.1115/DETC2008-49156
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