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A common metamodel based on all state variable trajectories can thereby be generated.
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We suggest to express and define metrics using a language-independent metamodel based on graphs.
Then, a multifidelity data metamodel based design optimization (MBDO) process is adopted based on the Ansys-DesignXplorer frameworks.
To increase the efficiency of metamodel based optimization method, the parallel architecture is implemented for BBNS due to its drawbacks.
A metamodel based multi-response objective-oriented sequential optimization was adopted, where Kriging models were updated with sequential training points.
A multi-step metamodel based optimization method is presented for the buckling design of a variable stiffness composite cylinder.
The crucial issue regarding influence of sampling techniques on the performance of metamodel based uncertainty quantification has been addressed as an integral part of this article.
In order to construct robust and accurate metamodel based LS-SVR, suitable quantity and intervals of samples are recommended.
For this purpose, a novel dual layer metamodel based approach is proposed where a limited number of simulations are used to train the first binary classifier, which predicts failure of tanks, upon which the second metamodel is trained; the final metamodel is used to derive parameterized fragility functions.
This work involved building a screen-printing quality metamodel, based upon fractional factorial experimental design data using a neural network approach that were then solved by genetic algorithms.
This study proposes a dual layer metamodel based approach to develop parameterized fragility functions for above ground storage tanks (ASTs) subjected to hurricane induced storm surge.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com