title: Péclet-dependent memory kernels for transport in heterogeneous media.
abstract: Transport in heterogeneous media can be described by partial differential equations, which exhibit convolutions with time and/or space memory kernels. In this work, we characterize the full time spectrum of time-memory kernels by applying a nonparametric inversion algorithm to macroscopic synthetic data for heterogeneous porous media, Our findings put into evidence the inherent nonuniqueness of the transport parameters for nonlocal transport models. Notably, we find that the Péclet number can be interpreted as an ancillary parameter of a family of probability distribution functions that characterizes the memory kernels of transport.
authors.affiliation: Earth Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA. acortis@lbl.gov
authors.forename: Andrea
authors.initials: A
authors.lastname: Cortis