Uncertainty quantification in a reacting electrochemical microchannel flow model

We describe a technique for modeling electrochemical microchannel flows including the propagation of uncertainty from model parameters and boundary conditions to the model predictions. The approach uses a pseudo-spectral stochastic construction with a polynomial chaos (PC) representation for parameters and field quantities. Using a Galerkin approach, the governing equations are reformulated into equations for the coefficients in the PC expansion. The implementation of the resulting uncertainty propagation schemes is illustrated in the context of microfluidic applications, including a homogeneous protein-labeling reaction as well as two-dimensional electrochemical flow.