A stochastic inverse solution for functionally graded acoustic layered metamaterial validation
| Autor: | Heather Reed, Patrick Murray, Jeffrey Cipolla |
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| Rok vydání: | 2015 |
| Předmět: |
Materials science
Acoustics and Ultrasonics Mathematical analysis Metamaterial Markov chain Monte Carlo Functionally graded material symbols.namesake Arts and Humanities (miscellaneous) Reflection (physics) symbols Waveguide (acoustics) Probability distribution Uncertainty quantification Material properties |
| Zdroj: | The Journal of the Acoustical Society of America. 138:1910-1910 |
| ISSN: | 0001-4966 |
| Popis: | Functionally graded acoustic metamaterials (FGAMs) can be designed to have specific waveguide properties. In sonar applications, FGAMs can be tailored to resist incident wave reflection. As these materials do not exist naturally, they must be fabricated by gradually layering manufactured, resulting in a (usually smooth) variation of properties. Validating material properties of FGAMs is difficult with conventional tests, as the distribution of material properties over the layered structure results in a non-unique solution if typical data (e.g., compressive strain) is measured. This talk will demonstrate an approach to characterize the functionally graded material properties by parameterizing how the functionally graded material changes throughout the specimen. Experiments designed to minimize the uncertainty surrounding the FGM model parameters are formulated and evaluated numerically. The FGM model parameters are estimated by Markov chain Monte Carlo so that a probability distribution surrounding each parameter is recovered. Probability distributions enable uncertainty quantification (UQ) surround the validated material parameters. UQ is important as uncertainty surrounding the parameter results directly translates into uncertainty surround the FGM performance. The approach is verified by bootstrap analyses of known FGAM distributions. |
| Databáze: | OpenAIRE |
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