A nonintrusive data assimilation methodology is developed to improve the statistical
predictions of large-eddy simulations (LES). The ensemble-variational (EnVar) approach …

Estimation of the initial state of turbulent channel flow from limited data is investigated using
an adjoint-variational approach. The data are generated from a reference direct numerical …

Reynolds-averaged Navier–Stokes (RANS)-based data assimilation has proven to be
essential in many data-driven approaches, including the augmentation of experimental data …

Reconstruction of turbulent flow based on data assimilation methods is of significant
importance for improving the estimation of flow characteristics by incorporating limited …

This study establishes a continuous sliding window weak-constraint four-dimensional
variational approach for reproducing a complete instantaneous flow from sparse …

We introduce a physically relevant stochastic representation of the rotating shallow water
equations. The derivation relies mainly on a stochastic transport principle and on a …

We investigate the estimation of the turbulent flow around a canonical square cylinder at
based on temporally resolved but spatially sparse velocity data and solving the unsteady …

Particle tracking velocimetry (PTV) is widely used to measure time-resolved, three-
dimensional velocity and pressure fields in fluid dynamics research. Inaccurate localization …

The vortex-in-cell time-segment assimilation (VIC-TSA) method is introduced. A particle track
is obtained from a finite number of successive time samples of the tracer's position and …

An adjoint-based variational optimal mixed model (VOMM) is proposed for subgrid-scale
(SGS) closure in large-eddy simulation (LES) of turbulence. The stabilized adjoint LES …