A multigrid/ensemble Kalman filter strategy for assimilation of unsteady flows
From MaRDI portal
Publication:2132567
DOI10.1016/j.jcp.2021.110481OpenAlexW3117062191MaRDI QIDQ2132567
Publication date: 28 April 2022
Published in: Journal of Computational Physics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2012.10091
Related Items (5)
Nudging-based data assimilation of the turbulent flow around a square cylinder ⋮ A novel estimation method for microstructural evolution based on data assimilation and phase field crystal model ⋮ Sequential multilevel assimilation of inverted seismic data ⋮ Multi-index ensemble Kalman filtering ⋮ Optimized parametric inference for the inner loop of the multigrid ensemble Kalman filter
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Quantifying and reducing model-form uncertainties in Reynolds-averaged Navier-Stokes simulations: a data-driven, physics-informed Bayesian approach
- A reduced order model based on Kalman filtering for sequential data assimilation of turbulent flows
- 4D large scale variational data assimilation of a turbulent flow with a dynamics error model
- Regularized ensemble Kalman methods for inverse problems
- A family of low dispersive and low dissipative explicit schemes for flow and noise computations.
- Optimal control of a transitional jet using a continuous adjoint method
- Multilevel ensemble Kalman filtering for spatio-temporal processes
- Combining ensemble Kalman filter and multiresolution analysis for efficient assimilation into adaptive mesh models
- Assessment of multilevel ensemble-based data assimilation for reservoir history matching
- Kriging-enhanced ensemble variational data assimilation for scalar-source identification in turbulent environments
- Reconstruction of unsteady viscous flows using data assimilation schemes
- Computational Methods for Fluid Dynamics
- Multilevel ensemble Kalman filtering
- Reduced-order Kalman-filtered hybrid simulation combining particle tracking velocimetry and direct numerical simulation
- A data-assimilation method for Reynolds-averaged Navier–Stokes-driven mean flow reconstruction
- The Shannon sampling theorem—Its various extensions and applications: A tutorial review
- Multi-Level Adaptive Solutions to Boundary-Value Problems
- Turbulent Flows
- Sensitivity of two-dimensional spatially developing mixing layers with respect to uncertain inflow conditions
- Data Assimilation
- The ensemble Kalman filter for combined state and parameter estimation
- A comparative study of inflow conditions for two‐ and three‐dimensional spatially developing mixing layers using large eddy simulation
- A Reduced-Order Kalman Filter for Data Assimilation in Physical Oceanography
- Geometric multigrid with applications to computational fluid dynamics
This page was built for publication: A multigrid/ensemble Kalman filter strategy for assimilation of unsteady flows