DAFI: An Open-Source Framework for Ensemble-Based Data Assimilation and Field Inversion

DOI10.4208/cicp.OA-2020-0178WikidataQ114926738 ScholiaQ114926738MaRDI QIDQ5163237

Xin-Lei Zhang, Heng Xiao, Carlos A. Michelén Ströfer

Publication date: 3 November 2021

Published in: Communications in Computational Physics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2012.02651

zbMATH Keywords

random fieldsBayesian inferencedata assimilationensemble Kalman filterinverse modeling

Mathematics Subject Classification ID

Inverse problems for PDEs (35R30) Numerical analysis (65-XX) Software, source code, etc. for problems pertaining to probability theory (60-04) Inverse problems in fluid mechanics (76M21)

Related Items (5)

Ensemble Kalman method for learning turbulence models from indirect observation data ⋮ Ensemble Gradient for Learning Turbulence Models from Indirect Observations ⋮ Combining direct and indirect sparse data for learning generalizable turbulence models ⋮ Assimilation of disparate data for enhanced reconstruction of turbulent mean flows ⋮ DAFI

Uses Software

• EnKF
• OpenFOAM
• DATeS
• GitHub
• OpenDA

Cites Work

• Flow over periodic hills -- numerical and experimental study in a wide range of Reynolds numbers
• Quantifying and reducing model-form uncertainties in Reynolds-averaged Navier-Stokes simulations: a data-driven, physics-informed Bayesian approach
• Regularized ensemble Kalman methods for inverse problems
• Iterative regularization methods for nonlinear ill-posed problems
• Analysis of iterative ensemble smoothers for solving inverse problems
• Evaluation of ensemble methods for quantifying uncertainties in steady-state CFD applications with small ensemble sizes
• Enforcing boundary conditions on physical fields in Bayesian inversion
• Physics-informed covariance kernel for model-form uncertainty quantification with application to turbulent flows
• Ensemble Kalman methods for inverse problems
• Deterministic Nonperiodic Flow
• Convergence analysis of ensemble Kalman inversion: the linear, noisy case
• Data Assimilation
• The ensemble Kalman filter for combined state and parameter estimation
• Unnamed Item

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