17 citations · 17 across the 6 of their papers we have counts for
6 papers
A differentiable software suite for accelerated simulation of turbulent flows
Syver Døving Agdestein, Benjamin Sanderse
We present IncompressibleNavierStokes.jl, an open-source Julia package for solving the incompressible Navier--Stokes equations on staggered Cartesian grids. The package features ma…
Approaching the optimal closure: equivariance, inductive bias, and Reynolds-number generalization in data-driven LES
Syver Døving Agdestein, Benjamin Sanderse
Data-driven closures for large-eddy simulation (LES) are commonly built to respect the symmetries of the Navier--Stokes equations, on the premise that this improves accuracy and ge…
A new data-driven energy-stable Evolve-Filter-Relax model for turbulent flow simulation
Anna Ivagnes, Toby van Gastelen, Syver Døving Agdestein +3
We present a novel approach to define the filter and relax steps in the evolve-filter-relax (EFR) framework for simulating turbulent flows. The EFR main advantages are its ease of…
Exact expressions for the unresolved stress in a finite-volume based large-eddy simulation
Syver Døving Agdestein, Roel Verstappen, Benjamin Sanderse
In this article we propose new discretization-informed expressions for the residual stress tensor (RST) in a finite-volume based large-eddy simulation (LES-FVM). In addition to the…
Discretize first, filter next: learning divergence-consistent closure models for large-eddy simulation
Syver Døving Agdestein, Benjamin Sanderse
We propose a new neural network based large eddy simulation framework for the incompressible Navier-Stokes equations based on the paradigm "discretize first, filter and close next"…
Learning filtered discretization operators: non-intrusive versus intrusive approaches
Syver Døving Agdestein, Benjamin Sanderse
Simulating multi-scale phenomena such as turbulent fluid flows is typically computationally very expensive. Filtering the smaller scales allows for using coarse discretizations, ho…