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Granular crystals present unique nonlinear properties that support standing waves. These depend on precompression and impurities. Thus, they can be used for different applications such as impact and shock dissipation.
There are different models that descriobe their behavior and experimental data agree with them. However, there are experimental errors that are not easily explained and are usually attributed to the approximations made and phenomena that are not accounted for. This tool provides a way to do uncertainty quantification to better understand how the uncertainty at the inputs propagate to the output and have a general understanding of how these affect the system.
This is done, by evaluating a surrogate function that is created from data gathered in 1000 simulations in which the radii and Young modulus of the particles are variable.
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Ilias Bilionis and Nicholas Zabaras. Bayesian uncertainty propagation.
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