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Adrian Lozano-Durán

Publications and source records attributed to Adrian Lozano-Durán.

2 recordsLinked to original sources

Informative and non-informative decomposition of turbulent flow fields

Not all the information in a turbulent field is relevant for understanding particular regions or variables in the flow. Here, we present a method for decomposing a source field into its informative $\boldsymbolΦ_I(\boldsymbol{x},t)$ and residual $\boldsymbolΦ_R(\boldsymbol{x},t)$ components relative to another target field. The method is referred to as informative and non-informative decomposition (IND). All the necessary information for physical understanding, reduced-order modelling, and control of the target variable is contained in $\boldsymbolΦ_I(\boldsymbol{x},t)$, whereas $\boldsymbolΦ_R(\boldsymbol{x},t)$ offers no substantial utility in these contexts. The decomposition is formulated as an optimisation problem that seeks to maximise the time-lagged mutual information of the informative component with the target variable while minimising the mutual information with the residual component. The method is applied to extract the informative and residual components of the velocity field in a turbulent channel flow, using the wall-shear stress as the target variable. We demonstrate the utility of IND in three scenarios: (i) physical insight of the effect of the velocity fluctuations on the wall-shear stress, (ii) prediction of the wall-shear stress using velocities far from the wall, and (iii) development of control strategies for drag reduction in a turbulent channel flow using opposition control.

physics.flu-dyn↗

Turbulence in the highly restricted dynamics of a closure at second order: comparison with DNS

S3T (Stochastic Structural Stability Theory) employs a closure at second order to obtain the dynamics of the statistical mean turbulent state. When S3T is implemented as a coupled set of equations for the streamwise mean and perturbation states, nonlinearity in the dynamics is restricted to interaction between the mean and perturbations. The S3T statistical mean state dynamics can be approximately implemented by similarly restricting the dynamics used in a direct numerical simulation (DNS) of the full Navier-Stokes equations (referred to as the NS system). Although this restricted nonlinear system (referred to as the RNL system) is greatly simplified in its dynamics in comparison to the associated NS, it nevertheless self-sustains a turbulent state in wall-bounded shear flow with structures and dynamics comparable to that in observed turbulence. Moreover, RNL turbulence can be analyzed effectively using theoretical methods developed to study the closely related S3T system. In order to better understand RNL turbulence and its relation to NS turbulence, an extensive comparison is made of diagnostics of structure and dynamics in these systems. Although quantitative differences are found, the results show that turbulence in the RNL system closely parallels that in NS and suggest that the S3T/RNL system provides a promising reduced complexity model for studying turbulence in wall-bounded shear flows.

physics.flu-dyn↗