A variational data assimilation approach for sparse velocity reference data in coarse RANS simulations through a corrective forcing term

DOI10.1016/j.cma.2024.117026MaRDI QIDQ6557788

P. Jenny, Oliver Brenner, Pasha Piroozmand, Justin Plogmann

Publication date: 18 June 2024

Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)

zbMATH Keywords

adjointcorrectiondata assimilationsparseRANS

Mathematics Subject Classification ID

Direct numerical and large eddy simulation of turbulence (76F65) Mathematical modeling or simulation for problems pertaining to fluid mechanics (76-10)

Cites Work

• Recent applications of CFD modelling in the power generation and combustion industries
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• Efficient assimilation of sparse data into RANS-based turbulent flow simulations using a discrete adjoint method
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• A discrete adjoint method for pressure-based algorithms
• A random matrix approach for quantifying model-form uncertainties in turbulence modeling
• Topology optimization of turbulent flows
• A data-assimilation method for Reynolds-averaged Navier–Stokes-driven mean flow reconstruction
• Optimal sensor placement for variational data assimilation of unsteady flows past a rotationally oscillating cylinder
• Direct numerical simulation of backward-facing step flow at and expansion ratio 2
• OPTIMAL SENSOR PLACEMENT FOR THE ESTIMATION OF TURBULENCE MODEL PARAMETERS IN CFD
• Rotorcraft simulations: a challenge for CFD
• Turbulence Modeling in the Age of Data
• Boundary control in computational haemodynamics
• Comparison of different data-assimilation approaches to augment RANS turbulence models
• Dimensionality reduction for regularization of sparse data-driven RANS simulations
• Hierarchical regularization of solution ambiguity in underdetermined inverse and optimization problems

Related Items (1)

Variational assimilation of sparse time-averaged data for efficient adjoint-based optimization of unsteady RANS simulations

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