Towards real-time reconstruction of velocity fluctuations in turbulent channel flow
arXiv:2301.06734 · doi:10.1103/PhysRevFluids.8.064612
Abstract
We develop a framework for efficient streaming reconstructions of turbulent velocity fluctuations from limited sensor measurements with the goal of enabling real-time applications. The reconstruction process is simplified by computing linear estimators using flow statistics from an initial training period and evaluating their performance during a subsequent testing period with data obtained from direct numerical simulation. We address cases where (i) no, (ii) limited, and (iii) full-field training data are available using estimators based on (i) resolvent modes, (ii) resolvent-based estimation, and (iii) spectral proper orthogonal decomposition modes. During training, we introduce blockwise inversion to accurately and efficiently compute the resolvent operator in an interpretable manner. During testing, we enable efficient streaming reconstructions by using a temporal sliding discrete Fourier transform to recursively update Fourier coefficients using incoming measurements. We use this framework to reconstruct with minimal time delay the turbulent velocity fluctuations in a minimal channel at from sparse planar measurements. We evaluate reconstruction accuracy in the context of the extent of data required and thereby identify potential use cases for each estimator. The reconstructions capture large portions of the dynamics from relatively few measurement planes when the linear estimators are computed with sufficient fidelity. We also evaluate the efficiency of our reconstructions and show that the present framework has the potential to help enable real-time reconstructions of turbulent velocity fluctuations in an analogous experimental setting.
36 pages, 22 figures, accepted by Physical Review Fluids
References in corpus (12)
- Machine learning based spatio-temporal super resolution reconstruction of turbulent flows
- Frequency-time analysis, low-rank reconstruction and denoising of turbulent flows using SPOD
- The colour of forcing statistics in resolvent analyses of turbulent channel flows
- Forcing statistics in resolvent analysis: application in minimal turbulent Couette flow
- Resolvent-based estimation of turbulent channel flow using wall measurements
- Efficient computation of global resolvent modes
- Resolvent-based tools for optimal estimation and control via the Wiener-Hopf formalism
- Proof-of-concept Study of Sparse Processing Particle Image Velocimetry for Real Time Flow Observation
- Reconstructing the time evolution of wall-bounded turbulent flows from non-time resolved PIV measurements
- Optimal sensor and actuator placement for feedback control of vortex shedding
- Resolvent-based approach for H2-optimal estimation and control: an application to the cylinder flow
- Model-based multi-sensor fusion for reconstructing wall-bounded turbulence