An Efficient Re-Analysis Methodology for Probabilistic Vibration of Large-Scale Structures

2009 ◽  
Vol 131 (5) ◽  
Author(s):  
Geng Zhang ◽  
Efstratios Nikolaidis ◽  
Zissimos P. Mourelatos

Probabilistic analysis and design of large-scale structures 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. The deterministic re-analysis method can analyze efficiently large-scale finite-element models consisting of tens or hundreds of thousand degrees of freedom and design variables that vary in a wide range. The probabilistic re-analysis method calculates very efficiently the system reliability for different probability distributions of the random variables by performing a single Monte Carlo simulation of one design. The methodology is demonstrated on probabilistic vibration analysis and reliability-based design optimization of a realistic vehicle model. It is shown that the computational cost of the proposed re-analysis method for a single reliability analysis is about 1/20 of the cost of the same analysis using MSC/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.

Author(s):  
Geng Zhang ◽  
Efstratios Nikolaidis ◽  
Zissimos P. Mourelatos

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.


2018 ◽  
Vol 10 (9) ◽  
pp. 168781401879333 ◽  
Author(s):  
Zhiliang Huang ◽  
Tongguang Yang ◽  
Fangyi Li

Conventional decoupling approaches usually employ first-order reliability method to deal with probabilistic constraints in a reliability-based design optimization problem. In first-order reliability method, constraint functions are transformed into a standard normal space. Extra non-linearity introduced by the non-normal-to-normal transformation may increase the error in reliability analysis and then result in the reliability-based design optimization analysis with insufficient accuracy. In this article, a decoupling approach is proposed to provide an alternative tool for the reliability-based design optimization problems. To improve accuracy, the reliability analysis is performed by first-order asymptotic integration method without any extra non-linearity transformation. To achieve high efficiency, an approximate technique of reliability analysis is given to avoid calculating time-consuming performance function. Two numerical examples and an application of practical laptop structural design are presented to validate the effectiveness of the proposed approach.


2007 ◽  
Vol 34 (7) ◽  
pp. 856-869 ◽  
Author(s):  
Hong Liang ◽  
Terje Haukaas ◽  
Johannes O Royset

This paper describes a functional tool for engineers to make rational design decisions by balancing cost and safety. Focus is on seismic design, in which nonlinear structural response must be considered. For this purpose, we implement and apply a state-of-the-art algorithm for reliability-based design optimization. The work extends the OpenSees software, which is rapidly gaining users in the earthquake engineering community. Consequently, design optimization with sophisticated nonlinear finite element models of real structures is possible. An object-oriented software architecture is employed that focuses on maintainability and extensibility of the software. This approach also offers flexibility in the choice of optimization and reliability methods for each specific problem, supported by the decoupled nature of the optimization algorithm. Our work utilizes and extends the existing tools for structural reliability analysis in OpenSees. In particular, we employ response sensitivities that are computed within the finite element code by direct differentiation. The implementation is tested through case studies with nonlinear structural response. Discontinuous response gradients are overcome by use of fibre cross sections and smoothed material models. The numerical examples include the seismic design optimization of a six-storey, three-bay, reinforced concrete building. Key words: reliability-based design optimization, nonlinear finite elements, earthquake engineering, object-oriented software development, OpenSees.


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