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Granular Crystals
Allows the user to sample properties of granular chains under uncertainty propagation
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Abstract
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.
References
[1]Gonzalez M., Yang J., Daraio C. and Ortiz M., Mesoscopic approach to granular crystal dynamics, Physical Review E, 85, 016604, 2012.
[2]Yang J., Gonzalez M., Kim E., Agbasi C., and Sutton M., Attenuation of solitary waves and localization of breathers in 1D granular crystals visualized via high speed photography, Experimental Mechanics, 54, 1043–1057, 2014.
[3]Marcial Gonzalez and Alberto M. Cuitiño. A nonlocal contact formulation for confined granular systems. Journal of the Mechanics and Physics of Solids, 60(2):333–350, 2012
[4]Caishan Liu, Zhen Zhao, and Bernard Brogliato. Theoretical Analysis and Numerical Algorithm for Frictionless Multiple Impacts in Multibody Systems. Inria, 2008
[5]C. E. Rasmussen and C-K. Williams, Gaussian processes for machine learning, USA: MIT Press, 2006
[6]Ilias Bilionis and Nicholas Zabaras. Bayesian uncertainty propagation.
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