Friday, October 20
Robert Moser - University of Texas – Austin
Modeling and Numerical Discretization in Large Eddy Simulation of Turbulence
Large eddy simulation (LES) of turbulence is expected to to be a more accurate and robust modeling approach than Reynolds averaged Navier-Stokes (RANS) modeling, and indeed, provided sufficient resolution is used, LES can be very reliable. However, for LES to be a practical tool for engineering applications, it is important that it provide reliable model predictions with the coarsest possible resolution. Such coarse resolution in LES introduces a number of challenges in both subgrid modeling and numerical discretization that will be discussed in this talk. In this talk, we will discuss the the effects of numerical dispersion on the energy cascade, and the effects of inhomogeneous LES resolution. Also discussed will be modeling strategies to overcome some of these challenges and improve the reliability of coarsely resolved LES.
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Luca Biferale - University of Roma - Sapienza
Data-driven and equations-informed tools for Lagrangian turbulence
We present some recent advancements in data-driven and equation-informed tools for a few Lagrangian turbulent problems, concerning Optimal Control of active particles and synthetic data-generation of Lagrangian trajectories.
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Alberto Scotti - University of North Carolina
Convection unchained: Radiatively Driven Convection
In this talk, I will present some results (mostly numerical) of Radiatively Driven Convection. RDC occurs naturally in freshwater lakes in temperate regions at the beginning of summer, when solar radiation warms the surface layer and the water column is below the temperature of maximum density. Since available potential energy is deposited directly into the water column, convection is not throttled by boundary layers.
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Perry Johnson - University of California – Irvine
Vortices within vortices: multiscale velocity gradient interactions and the energy cascade
Prior to the availability of direct numerical simulation (DNS) or spatially-resolved 3D experimental measurements, multiscale vortex stretching was hypothesized as the main mechanism of the energy cascade by some of the field's most brilliant contributors, including G. I. Taylor, Lars Onsager, and John Lumley. Early DNS evidence confirmed the ubiquitous presence of worm-like vortex structures. With increasing access to higher Reynolds numbers, visualization of filtered velocity gradients revealed the hierarchical nature of vortex tubes in turbulence. Meanwhile, theoretical advances and emerging evidence demonstrated the importance of strain-rate self-amplification for the energy cascade in addition to vortex stretching. In this talk, I will summarize recent advances using a new tool called Stokes Flow Regularization (SFR), a physics-inspired coarsening technique related to spatial filtering. SFR provides a rigorous mathematical basis that quantifies the role of vortex stretching and strain-rate self-amplification in the energy cascade. In addition, SFR can be used to derive analytical pen-and-paper dynamic coefficients for large-eddy simulation (LES) residual stress models. This provides an alternative to dynamic procedures based on the Germano identity, which require the calculation of a test filter. The future potential of SFR to tackle challenges related to non-uniform LES resolution (commutator errors) and multiphase flows will be briefly discussed.
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William Anderson - University of Texas – Dallas
Evidence that uniform momentum zones originate from roughness sublayer structure interactions in fully rough channel turbulence
Fully rough wall-sheared turbulence is composed of an inner and outer layer, the former occupied by sinuous structures sustained by the well-known autonomous inner cycle, the latter occupied by inclined parcels of momentum deviations relative to the average. The outer-layer structures are also known as uniform momentum zones (UMZs), where the presence of successive UMZs manifests instantaneously with a distinct ‘staircase’ pattern in streamwise velocity. Direct numerical simulation (DNS) of fully rough channel turbulence was recently used to interpret UMZs as wakes originating from antecedent bluff-body-like interactions within the inner layer (Anderson & Salesky, J. Fluid Mech., vol. 906, 2020, A8). Wake-scaling arguments agreed precisely with instantaneous results from DNS. Foremost among these results was evidence that the instantaneous wall-normal gradient of streamwise velocity exhibited scaling of ∼z -1/2, where z is wall-normal location; this is in contrast to logarithmic scaling, which requires the wall-normal gradient of streamwise velocity to scale as ∼z -1. Herein, wake-scaling arguments have been advanced and compared against results from wall-modelled large-eddy simulation (LES). New results from the ‘bottom up’ wake-scaling arguments agree with LES results, such that the shear associated with the instantaneous staircase-like streamwise velocity follows a clear trend. We have leveraged conditional sampling during LES – predicated upon instantaneous low-frequency, high-magnitude surface stress values known to correspond to large-scale inertial-layer coherence – to further assess the predictive value of the wake-scaling arguments. Model results compare favorably.
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Luis Martínez - National Renewable Energy Laboratory
The story of the Filtered Lifting Line Theory and Charles Meneveau (2012-Present)
We present the history of the development of the filtered lifting line theory and my journey as part of the Turbulence Research Group at JHU. We start by developing the analytical solution for flow over a 2D Gaussian body force. The analytical solutions are used to find an optimal representation of a 2D airfoil using a Gaussian body force. The analysis is then extended to the 3D wing and the equations are introduced. We solve the equations for flow over a 3D wing and introduce the filtered lifting line theory. We will provide insights into the conversations and stories that happened during my time at JHU and the interactions with Charles Meneveau over the last 10 years.
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Patricio Clark Di Leoni - Universidad de San Andrés
Reconstructing turbulent velocity and pressure fields from under-resolved noisy particle tracks using physics-informed neural networks
Volume-resolving imaging techniques are rapidly advancing progress in experimental fluid mechanics. However, reconstructing the full and structured Eulerian velocity and pressure fields from under-resolved and noisy particle tracks obtained experimentally remains a significant challenge. We adopt and characterize a method based on Physics-Informed Neural Networks (PINNs). In this approach, the network is regularized by the Navier-Stokes equations to interpolate the velocity data and simultaneously determine the pressure field. We compare this approach to the state-of-the-art Constrained Cost Minimization method. Using data from direct numerical simulations and various types of synthetically generated particle tracks, we show that PINNs are able to accurately reconstruct both velocity and pressure even in regions with low particle density and small accelerations. We analyze both the root mean square error of the reconstructions as well their energy spectra. PINNs are also robust against increasing the distance between particles and the noise in the measurements, when studied under synthetic and experimental conditions. Both the synthetic and experimental datasets used correspond to moderate Reynolds number flows.
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Hussein Aluie - University of Rochester
A hommage to Charles's multiscale analysis of turbulence
Among his many great scientific achievements, Charles is a pioneer in the multiscale analysis of turbulence. He was the first to develop a wavelet analysis framework in turbulence, which gave us one of the earliest insights into the cascade process in physical space. He was also one of the earliest developers of coarse-graining ideas from LES to probe the fundamental physics of complex multiscale flows. I will describe recent work extending such ideas to the sphere and applying them to the global oceanic circulation.
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