Syver Agdestein

Full Name

S.D. Agdestein

Email

Syver.Agdestein@cwi.nl

Phone

+31 20 5929 333

Room

M137

Department(s)

Scientific Computing

Function(s)

Researcher

Syver Agdestein

Agdestein, S. (2026). Data-driven discrete closure models for large-eddy simulation of incompressible turbulence.
Ivagnes, A., van Gastelen, T., Agdestein, S., Sanderse, B., Stabile, G.& Rozza, G. (2026). A new data-driven energy-stable evolve-filter-relax model for turbulent flow simulation. Computer Methods in Applied Mechanics and Engineering, 450.https://doi.org/10.1016/j.cma.2025.118654
Agdestein, S., Verstappen, R.& Sanderse, B. (2026). Exact expressions for the unresolved stress in a finite-volume based large-eddy simulation. Journal of Computational Physics, 556, 114810:1–114810:35.https://doi.org/10.1016/j.jcp.2026.114810
Agdestein, S.& Sanderse, B. (2025). Discretize first, filter next: Learning divergence-consistent closure models for large-eddy simulation. Journal of Computational Physics, 522, 113577:1–113577:34.https://doi.org/10.1016/j.jcp.2024.113577
Agdestein, S.& Sanderse, B. (2022, November 24). Discretize first, filter next – a new closure model approach. European Congress on Computational Methods in Applied Sciences and Engineering - ECCOMAS.https://doi.org/10.23967/eccomas.2022.094

Discovering neural stochatsitc differential equations to simulate probabilistic tubulence (None)