  In the work, we derive novel hydrodynamic force models to describe the
interaction of a flow with particles in an assembly when only an averaged
resolution of the flow is available. These force models are able to predict the
average drag on the particle assembly, as well as the deviations from the
average drag force and the lift force for each individual particle in the
assembly. To achieve this, PR-DNS of various particle assemblies and flow
regimes are carried out, varying the particle volume fraction up to 0.6, and
the mean particle flow Reynolds number up to 300. To characterize the structure
of the particles in the assembly, a Voronoi tessellation is carried out, and a
number of scalars, vectors and tensors are defined based upon this
tessellation. The microstructure informed hydrodynamic force models are based
on symbolic regressions of these quantities derived from the Voronoi
tessellation, the global particle volume fraction of the particle assembly and
the flow regime represented by the Reynolds number, and the forces on the
individual particles in the assembly.
  The resulting hydrodynamic force models are single expressions can be
directly employed in a Lagrangian particle tracking (LPT) or computational
fluid dynamics/discrete element model (CFD/DEM) framework. By comparing the
results of the newly proposed hydrodynamic force models with an averaged force
model, as is usually adopted in Lagrangian particle tracking simulations, we
show that a significant increase in accuracy can be achieved, without
significantly increasing the cost of the simulation.
