Abstract
We explore the use of Equation-Free algorithms as Dynamic Data Driven experimental design protocols for the computational as well as laboratory study of the dynamics of engineered granular crystals and their models. The ability to prescribe de- sired initial conditions for computational -and, in this case, also possibly for laboratory- experiments provides an interesting link between traditional, matrix-free numerical analysis and the acceleration of dynamic studies. The framework is further enhanced through combination with data-mining algorithms that process detailed, fine-scale data to uncover underlying im- portant, coarse-grained variables (macroscopic system observables).
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