An approach for reliability-based robust design optimisation of angle-ply composites

Curnis, Antonio; Hoffbauer, Luísa N.

doi:10.1016/j.compstruct.2009.01.008

Cited by 49 publications

(19 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Most of these publications attempted to reduce the variance of cost function, f ðd; x; pÞ, in Model (1) [23,4,21,10,24]. Accordingly, the objective function can be either formulated as multi-objective optimization or a single objective as a linear combination of both mean and variance of cost function.…”

Section: Impact Of Ignoring Robustness In Design Processmentioning

confidence: 99%

See 1 more Smart Citation

Enhancing product robustness in reliability-based design optimization

Zhuang¹,

Pan

2015

Reliability Engineering & System Safety

View full text Add to dashboard Cite

Section: Impact Of Ignoring Robustness In Design Processmentioning

confidence: 99%

“…Some other measures of robustness have been proposed in the literature. For example, a performance percentile difference method was used in [19]; a robust index derived from the acceptable performance variation was developed in [20]; a coefficient of variation measure was given in [21].…”

Section: Robust Product Designmentioning

confidence: 99%

Enhancing product robustness in reliability-based design optimization

Zhuang¹,

Pan

2015

Reliability Engineering & System Safety

View full text Add to dashboard Cite

“…(2) is referred to, in technical literature, as the design point or most probable failure point (MPP). The bisection method used to estimate the load factor, k, is iteratively used in the external loop [23]. After the minimization of the objective function given in Eq.…”

Section: Ann-mc Approachmentioning

confidence: 99%

Uncertainty assessment approach for composite structures based on global sensitivity indices

Curnis

Hoffbauer

2013

Composite Structures

View full text Add to dashboard Cite

The problem of uncertainty propagation in composite laminate structures is studied. An approach based on the optimal design of composite structures to achieve a target reliability level is proposed. Using the Uniform Design Method (UDM), a set of design points is generated over a design domain centred at mean values of random variables, aimed at studying the space variability. The most critical Tsai number, the structural reliability index and the sensitivities are obtained for each UDM design point, using the max-imum load obtained from optimal design search. Using the UDM design points as input/output patterns, an Artificial Neural Network (ANN) is developed based on supervised evolutionary learning. Finally, using the developed ANN a Monte Carlo simulation procedure is implemented and the variability of the struc-tural response based on global sensitivity analysis (GSA) is studied. The GSA is based on the first order Sobol indices and relative sensitivities. An appropriate GSA algorithm aiming to obtain Sobol indices is proposed. The most important sources of uncertainty are identified.

show abstract

“…The bisection method used to estimate the load factor, k, is iteratively used in the external loop (António and Hoffbauer 2009). After the minimization of the objective function given in Eq.…”

Section: Inverse Reliability Analysismentioning

confidence: 99%

Uncertainty propagation in inverse reliability-based design of composite structures

Curnis

Hoffbauer

2010

Int J Mech Mater Des

Self Cite

View full text Add to dashboard Cite

An approach for the analysis of uncertainty propagation in reliability-based design optimization of composite laminate structures is presented. Using the Uniform Design Method (UDM), a set of design points is generated over a domain centered on the mean reference values of the random variables. A methodology based on inverse optimal design of composite structures to achieve a specified reliability level is proposed, and the corresponding maximum load is outlined as a function of ply angle. Using the generated UDM design points as input/output patterns, an Artificial Neural Network (ANN) is developed based on an evolutionary learning process. Then, a Monte Carlo simulation using ANN development is performed to simulate the behavior of the critical Tsai number, structural reliability index, and their relative sensitivities as a function of the ply angle of laminates. The results are generated for uniformly distributed random variables on a domain centered on mean values. The statistical analysis of the results enables the study of the variability of the reliability index and its sensitivity relative to the ply angle. Numerical examples showing the utility of the approach for robust design of angle-ply laminates are presented.

show abstract

An approach for reliability-based robust design optimisation of angle-ply composites

Cited by 49 publications

References 13 publications

Enhancing product robustness in reliability-based design optimization

Enhancing product robustness in reliability-based design optimization

Uncertainty assessment approach for composite structures based on global sensitivity indices

Uncertainty propagation in inverse reliability-based design of composite structures

Contact Info

Product

Resources

About