  The Lagrangian approach is natural to study issues of turbulent dispersion
and mixing. We propose in this work a general Lagrangian stochastic model
including velocity and acceleration as dynamical variables for inhomogeneous
turbulent flows. The model takes the form of a diffusion process and the
coefficients of the model are determined via Kolmogorov theory and the
requirement of consistency with the velocity-based models. It is shown that the
present model generalises both the acceleration-based models for homogeneous
flows and the generalised Langevin models for the velocity. The resulting
closed model is applied to a channel flow at high Reynolds number and compared
to experiments as well as direct numerical simulations. A hybrid approach
coupling the stochastic model with a Reynolds-Averaged-Navier-Stokes (RANS) is
used to obtain a self-consistent model, as commonly used in probability density
function methods. Results highlight that most of the acceleration features are
well represented, notably the anisotropy and the strong intermittency. These
results are valuable, since the model allows to improve the modelling of
boundary layers yet remaining relatively simple. It sheds also some light on
the statistical mechanisms at play in the near-wall region.
