Four-dimensional variational data assimilation of a turbulent jet for super-temporal-resolution reconstruction

DOI10.1017/jfm.2023.972MaRDI QIDQ6145701

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Publication date: 9 January 2024

Published in: Journal of Fluid Mechanics (Search for Journal in Brave)

zbMATH Keywords

large eddy simulationNyquist limitsegregated assimilation procedureweak-constraint four-dimensional variation

Mathematics Subject Classification ID

Shear flows and turbulence (76F10) Variational methods applied to problems in fluid mechanics (76M30) Direct numerical and large eddy simulation of turbulence (76F65) Basic methods in fluid mechanics (76M99) Inverse problems in fluid mechanics (76M21)

Cites Work

• Unnamed Item
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• Continuous adjoint methods for turbulent flows, applied to shape and topology optimization: industrial applications
• POD/DEIM reduced-order strategies for efficient four dimensional variational data assimilation
• Inflow and initial conditions for direct numerical simulation based on adjoint data assimilation
• Strong and weak constraint variational assimilations for reduced order fluid flow modeling
• 4D large scale variational data assimilation of a turbulent flow with a dynamics error model
• Design principles for bounded higher-order convection schemes -- a unified approach
• Internal motion of a small element of fluid in an inviscid flow
• Large-eddy simulation of circular jet mixing: lip- and inner-ribbed nozzles
• Scale interactions in a mixing layer – the role of the large-scale gradients
• Amplitude and frequency modulation in wall turbulence
• Machine Learning for Fluid Mechanics
• A data-assimilation method for Reynolds-averaged Navier–Stokes-driven mean flow reconstruction
• A continuous adjoint formulation for the computation of topological and surface sensitivities of ducted flows
• Stochastic estimation of a separated-flow field using wall-pressure-array measurements
• Amplification of enstrophy in the far field of an axisymmetric turbulent jet
• Low-dimensional characteristics of a transonic jet. Part 2. Estimate and far-field prediction
• Stochastic estimation of organized turbulent structure: homogeneous shear flow
• Turbulence and the dynamics of coherent structures. I. Coherent structures
• Turbulent Flows
• Linear and nonlinear sensor placement strategies for mean-flow reconstruction via data assimilation
• Prediction of turbulent heat transfer using convolutional neural networks
• Phase-resolved ocean wave forecast with ensemble-based data assimilation
• Nudging-based data assimilation of the turbulent flow around a square cylinder
• The effect of large-scale forcing on small-scale dynamics of incompressible turbulence
• What is observable from wall data in turbulent channel flow?
• Real-time thermoacoustic data assimilation
• Numerische Strömungsmechanik
• Machine-learning-based spatio-temporal super resolution reconstruction of turbulent flows
• Unsupervised deep learning for super-resolution reconstruction of turbulence
• Large-scale amplitude modulation of the small-scale structures in turbulent boundary layers
• Small-scale reconstruction in three-dimensional Kolmogorov flows using four-dimensional variational data assimilation
• Data assimilation method to de-noise and de-filter particle image velocimetry data
• Data-driven prediction of unsteady flow over a circular cylinder using deep learning
• Turbulence Modeling in the Age of Data
• Comparative analysis of machine learning methods for active flow control
• 4D variational data analysis with imperfect model
• Deep learning closure models for large-eddy simulation of flows around bluff bodies

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