Objective Momentum Barriers in Wall Turbulence

We use the recent frame-indifferent theory of diffusive momentum transport to identify internal barriers in wall-bounded turbulence. Formed by the invariant manifolds of the Laplacian of the velocity field, the barriers block the viscous part of the instantaneous momentum flux in the flow. We employ the level sets of single-trajectory Lagrangian diagnostic tools, the trajectory rotation average and trajectory stretching exponent, to approximate both vortical and internal wall-parallel momentum transport barrier (MTB) interfaces. These interfaces provide frame-indifferent alternatives to classic velocity-gradient-based vortices and boundaries between uniform momentum zones (UMZs). Indeed, we find that these elliptic manifold approximations and MTBs also significantly outperform standard vortices and UMZ interfaces in blocking diffusive momentum transport.Comment: 26 Pages, 14 Figur

Interplay between advective, diffusive and active barriers in (rotating) Rayleigh–Bénard flow

Our understanding of the material organization of complex fluid flows has benefited recently from mathematical developments in the theory of objective coherent structures. These methods have provided a wealth of approaches that identify transport barriers in three-dimensional (3-D) turbulent flows. Specifically, theoretical advances have been incorporated into numerical algorithms that extract the most influential advective, diffusive and active barriers to transport from data sets in a frame-indifferent fashion. To date, however, there has been very limited investigation into these objectively defined transport barriers in 3-D unsteady flows with complicated spatiotemporal dynamics. Similarly, no systematic comparison of advective, diffusive and active barriers has been carried out in a 3-D flow with both thermally driven and mechanically modified structures. In our study, we utilize simulations of turbulent rotating Rayleigh–Bénard convection to uncover the interplay between advective transport barriers (Lagrangian coherent structures), material barriers to diffusive heat transport, and objective Eulerian barriers to momentum transport. For a range of (inverse) Rossby numbers, we identify each type of barrier and find intriguing relationships between momentum and heat transport that can be related to changes in the relative influence of mechanical and thermal forces. Further connections between bulk behaviours and structure-specific behaviours are also developed

Quasi-Objective Eddy Visualization from Sparse Drifter Data

We employ a recently developed single-trajectory Lagrangian diagnostic tool, the trajectory rotation average $(\mathrm{\overline{TRA}})$, to visualize oceanic vortices (or eddies) from sparse drifter data. We apply the $\mathrm{\overline{TRA}}$ to two drifter data sets that cover various oceanographic scales: the Grand Lagrangian Deployment (GLAD) and the Global Drifter Program (GDP). Based on the $\mathrm{\overline{TRA}}$, we develop a general algorithm that extracts approximate eddy boundaries. We find that the $\mathrm{\overline{TRA}}$ outperforms other available single-trajectory-based eddy detection methodologies on sparse drifter data and identifies eddies on scales that are unresolved by satellite-altimetry

Search for new particles in events with energetic jets and large missing transverse momentum in proton-proton collisions at root s=13 TeV

A search is presented for new particles produced at the LHC in proton-proton collisions at root s = 13 TeV, using events with energetic jets and large missing transverse momentum. The analysis is based on a data sample corresponding to an integrated luminosity of 101 fb(-1), collected in 2017-2018 with the CMS detector. Machine learning techniques are used to define separate categories for events with narrow jets from initial-state radiation and events with large-radius jets consistent with a hadronic decay of a W or Z boson. A statistical combination is made with an earlier search based on a data sample of 36 fb(-1), collected in 2016. No significant excess of events is observed with respect to the standard model background expectation determined from control samples in data. The results are interpreted in terms of limits on the branching fraction of an invisible decay of the Higgs boson, as well as constraints on simplified models of dark matter, on first-generation scalar leptoquarks decaying to quarks and neutrinos, and on models with large extra dimensions. Several of the new limits, specifically for spin-1 dark matter mediators, pseudoscalar mediators, colored mediators, and leptoquarks, are the most restrictive to date.Peer reviewe

A new polygenic score for refractive error improves detection of children at risk of high myopia but not the prediction of those at risk of myopic macular degeneration

Background High myopia (HM), defined as a spherical equivalent refractive error (SER) ≤ −6.00 diopters (D), is a leading cause of sight impairment, through myopic macular degeneration (MMD). We aimed to derive an improved polygenic score (PGS) for predicting children at risk of HM and to test if a PGS is predictive of MMD after accounting for SER. Methods The PGS was derived from genome-wide association studies in participants of UK Biobank, CREAM Consortium, and Genetic Epidemiology Research on Adult Health and Aging. MMD severity was quantified by a deep learning algorithm. Prediction of HM was quantified as the area under the receiver operating curve (AUROC). Prediction of severe MMD was assessed by logistic regression. Findings In independent samples of European, African, South Asian and East Asian ancestry, the PGS explained 19% (95% confidence interval 17–21%), 2% (1–3%), 8% (7–10%) and 6% (3–9%) of the variation in SER, respectively. The AUROC for HM in these samples was 0.78 (0.75–0.81), 0.58 (0.53–0.64), 0.71 (0.69–0.74) and 0.67 (0.62–0.72), respectively. The PGS was not associated with the risk of MMD after accounting for SER: OR = 1.07 (0.92–1.24). Interpretation Performance of the PGS approached the level required for clinical utility in Europeans but not in other ancestries. A PGS for refractive error was not predictive of MMD risk once SER was accounted fo

Objective momentum barriers in wall turbulence

We use the recent frame-indifferent theory of diffusive momentum transport to identify internal barriers in wall-bounded turbulence. Formed by the invariant manifolds of the Laplacian of the velocity field, the barriers block the viscous part of the instantaneous momentum flux in the flow. We employ the level sets of single-trajectory Lagrangian diagnostic tools, the trajectory rotation average and trajectory stretching exponent, to approximate both vortical and internal wall-parallel momentum transport barrier (MTB) interfaces. These interfaces provide frame-indifferent alternatives to classic velocity-gradient-based vortices and high-shear boundaries between uniform momentum zones (UMZs). Indeed, we find that these elliptic manifold approximations and MTBs outperform standard vortices and UMZ interfaces in blocking diffusive momentum transport, which suggests our momentum barriers are physical features that may be the cause of coherence signatures in statistical and non-objective diagnostics. We also introduce normalized trajectory metrics that provide unprecedented visualizations of objective coherent structures by avoiding strong turbulence biases.ISSN:0022-1120ISSN:1469-764

Machine-learning mesoscale and submesoscale surface dynamics from lagrangian ocean drifter trajectories

Lagrangian ocean drifters provide highly accurate approximations of ocean surface currents but are sparsely located across the globe. As drifters passively follow ocean currents, there is minimal control on where they will be making measurements, providing limited temporal coverage for a given region. Complementary Eulerian velocity data are available with global coverage but are themselveslimited by the spatial and temporal resolution possible with satellite altimetry measurements. In addition, altimetry measurements approximate geostrophic components of ocean currents but neglect smaller submesoscale motions and require smoothing and interpolation from raw satellite track measurements. In an effort to harness the rich dynamics available in ocean drifter datasets, we have trained a recurrent neural network on the time history of drifter motion to minimize the error in a reduced-order Maxey–Riley drifter model. This approach relies on a slow-manifold approximation to determine the most mathematically relevant variables with which to train, subsequently improving the temporal and spatial resolution of the underlying velocity field. By adding this neural-network component, we also correct drifter trajectories near submesoscale features missed by deterministic models using only satellite and wind reanalysis data. The effect of varying similarity between training and testing trajectory datasets for the blended model was evaluated, as was the effect of seasonality in the Gulf of Mexico. ©2020 American Meteorological Society

Interplay between advective, diffusive and active barriers in (rotating) Rayleigh-Benard flow

Our understanding of the material organization of complex fluid flows has benefited recently from mathematical developments in the theory of objective coherent structures. These methods have provided a wealth of approaches that identify transport barriers in three-dimensional (3-D) turbulent flows. Specifically, theoretical advances have been incorporated into numerical algorithms that extract the most influential advective, diffusive and active barriers to transport from data sets in a frame-indifferent fashion. To date, however, there has been very limited investigation into these objectively defined transport barriers in 3-D unsteady flows with complicated spatiotemporal dynamics. Similarly, no systematic comparison of advective, diffusive and active barriers has been carried out in a 3-D flow with both thermally driven and mechanically modified structures. In our study, we utilize simulations of turbulent rotating Rayleigh-B & eacute;nard convection to uncover the interplay between advective transport barriers (Lagrangian coherent structures), material barriers to diffusive heat transport, and objective Eulerian barriers to momentum transport. For a range of (inverse) Rossby numbers, we identify each type of barrier and find intriguing relationships between momentum and heat transport that can be related to changes in the relative influence of mechanical and thermal forces. Further connections between bulk behaviours and structure-specific behaviours are also developed.ISSN:0022-1120ISSN:1469-764