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The Cultural Impact of Rupaul's Drag Race
Insightful and provocative, and new in paperback. Examines the social, cultural, political and commercial implications of RuPaul's Drag Race, from its groundbreaking, subversive entry into the reality television arena, to a now mainstream, increasingly non-LGBTQ+, audience reach and relationship with fans. International contributors. 40 b/w illus. New Books Network (New Books in Popular Culture) interview with Cameron Crookston.
eBook
Using Machine Learning to Predict Urban Canopy Flows for Land Surface Modeling
Developing urban land surface models for modeling cities at high resolutions needs to better account for the city‐specific multi‐scale land surface heterogeneities at a reasonable computational cost. We propose using an encoder‐decoder convolutional neural network to develop a computationally efficient model for predicting the mean velocity field directly from urban geometries. The network is trained using the geometry‐resolving large eddy simulation results. Systematic testing on urban structures with increasing deviations from the training geometries shows the prediction error plateaus at 15%, compared to errors sharply increasing up to 35% in the null models. This is explained by the trained model successfully capturing the effects of pressure drag, especially for tall buildings. The prediction error of the aerodynamic drag coefficient is reduced by 32% compared with the default parameterization implemented in mesoscale modeling. This study highlights the potential of combining computational fluid dynamics modeling and machine learning to develop city‐specific parameterizations. Plain Language Summary Predicting the velocity field in the urban area with fine resolution at the meter scale is computationally expensive. Yet a detailed velocity field is necessary for improving the accuracy of urban land surface representation in weather and climate models. We propose using a convolutional neural network to predict the velocity field from the three‐dimensional (3D) building distribution. The similarity between the predicted velocity fields and LES simulations in the testing geometries illustrates the prediction capability of the trained model. We also investigate the aerodynamic drag coefficient, a key parameter for quantifying the land‐atmosphere momentum exchange. The results indicate that the trained model prediction is much closer to values derived from large‐eddy simulation models than those from the default parameterization scheme, showing the promise of using machine learning to improve urban land surface modeling. Key Points Machine learning (ML) can help develop city‐specific parameterization that fully utilizes urban form data It is a first attempt to develop an ML model for high‐Reynolds number urban canopy flow with multiple bluff‐body obstacles Limitation of the geometry to flow field approach is quantified by accessing the extrapolative capability of the trained model
Journal Article
The Effect of Surface Drag Strength on Mesocyclone Intensification and Tornadogenesis in Idealized Supercell Simulations
A suite of six idealized supercell simulations is performed in which the surface drag coefficient C d is varied over a range of values from 0 to 0.05 to represent a variety of water and land surfaces. The experiments employ a new technique for enforcing a three-force balance among the pressure gradient, Coriolis, and frictional forces so that the environmental wind profile can remain unchanged throughout the simulation. The initial low-level mesocyclone lowers toward the ground, intensifies, and produces a tornado in all experiments with C d ≥ 0.002, with the intensification occurring earlier for larger C d . In the experiment with C d = 0, the low-level mesocyclone remains comparatively weak throughout the simulation and does not produce a tornado. Vertical cross sections through the simulated tornadoes reveal an axial downdraft that reaches the ground only in experiments with smaller C d , as well as stronger corner flow in experiments with larger C d . Material circuits are initialized enclosing the low-level mesocyclone in each experiment and traced backward in time. Circulation budgets for these circuits implicate surface drag acting in the inflow sector of the supercell as having generated important positive circulation, and its relative contribution increases with C d . However, the circulation generation is similar in magnitude for the experiments with C d = 0.02 and 0.05, and the tornado in the latter experiment is weaker. This suggests the possible existence of an optimal range of C d values for promoting intense tornadoes within our experimental configuration.
Journal Article
Turbulent drag reduction over curved walls
This work studies the effects of skin-friction drag reduction in a turbulent flow over a curved wall, with a view to understanding the relationship between the reduction of friction and changes to the total aerodynamic drag. Direct numerical simulations are carried out for an incompressible turbulent flow in a channel where one wall has a small bump; two bump geometries are considered, that produce mildly separated and attached flows. Friction drag reduction is achieved by applying streamwise-travelling waves of spanwise velocity (StTW). The local friction reduction produced by the StTW is found to vary along the curved wall, leading to a global friction reduction that, for the cases studied, is up to 10 % larger than that obtained in the plane wall case. Moreover, the modified skin friction induces non-negligible changes of pressure drag, which is favourably affected by StTW and globally reduces by up to 10 %. The net power saving, accounting for the power required to create the StTW, is positive and, for the cases studied, is one half larger than the net saving of the planar case. The study suggests that reducing friction at the surface of a body of complex shape induces further effects, a simplistic evaluation of which might lead to underestimating the total drag reduction.
Journal Article
Impact of Variable Atmospheric and Oceanic Form Drag on Simulations of Arctic Sea Ice
Over Arctic sea ice, pressure ridges and floe and melt pond edges all introduce discrete obstructions to the flow of air or water past the ice and are a source of form drag. In current climate models form drag is only accounted for by tuning the air–ice and ice–ocean drag coefficients, that is, by effectively altering the roughness length in a surface drag parameterization. The existing approach of the skin drag parameter tuning is poorly constrained by observations and fails to describe correctly the physics associated with the air–ice and ocean–ice drag. Here, the authors combine recent theoretical developments to deduce the total neutral form drag coefficients from properties of the ice cover such as ice concentration, vertical extent and area of the ridges, freeboard and floe draft, and the size of floes and melt ponds. The drag coefficients are incorporated into the Los Alamos Sea Ice Model (CICE) and show the influence of the new drag parameterization on the motion and state of the ice cover, with the most noticeable being a depletion of sea ice over the west boundary of the Arctic Ocean and over the Beaufort Sea. The new parameterization allows the drag coefficients to be coupled to the sea ice state and therefore to evolve spatially and temporally. It is found that the range of values predicted for the drag coefficients agree with the range of values measured in several regions of the Arctic. Finally, the implications of the new form drag formulation for the spinup or spindown of the Arctic Ocean are discussed.
Journal Article
Numerical study on the aerodynamics of the Ahmed body and drag reduction analysis
At present, the vehicle is still an important means of transportation for human beings. Appropriate reduction of vehicle aerodynamic drag can effectively reduce fuel consumption. In this report, the aerodynamics analysis of the Ahmed body for the slant angles of 25º and 35º was presented numerically, and the average lift/drag was compared with the previous result. The average lift and drag were carried out, and the streamlines and volume vorticity structures were presented to reveal the relationship between aerodynamics and the flow field structure. In addition, two configurations of cylinder vortex generations were added to the Ahmed body for which the slant angle is 35º. It was found that, by applying the cylinder vortex generations, the results show a 10% reduction in drag coefficients compared to the baseline structure. The presented results provide an effective way for the drag reduction design of vehicles with the Ahmed body.
Journal Article
Wind–Wave Interaction for Strong Winds
In this paper, we revisit the problem of wind–wave interaction with emphasis on strong winds. For these events, it is assumed that nonlinearity is so large that the slope of the wind waves has reached a limiting steepness. Recent observations suggest that the drag decreases with wind in the strong wind speed regime. In this paper, we try to explain this. In the first step, we introduce a model for surface gravity waves and calculate explicitly the background roughness length from the original approach of Janssen. It is found that for young, steep wind sea, the background roughness length almost vanishes, giving a reduced drag. In addition, it is shown that for steep waves, the slowing down of the wind by waves is a nonlinear process; hence, the growth rate of the waves by wind depends in a nonlinear fashion on the wave spectrum. For strong winds, it is found that, as waves are typically steep, this nonlinear effect gives a further reduction of the wind input. As a consequence, in these extreme circumstances, the drag coefficient decreases with wind.
Journal Article
A Numerical Investigation of Cumulus Thermals
Although the steady, entraining, updraft plume is widely taken as the foundational concept of cumulus convection, past studies show that convection is typically dominated by thermals that are transient, more isotropic in shape, and possess interior vortical circulations. Here, several thousand such thermals are tracked in cloud-resolving simulations of transient growing convective events. Most tracked thermals are small (with radius R < 300 m), ascend at moderate rates (~ 2–4 m s−1), maintain an approximately constant size as they rise, and have brief (4–5 min) lifetimes, although a few are much larger, faster, and/or longer lived. They show slight vertical elongation, but few, if any, would be described as plumes. As convection deepens, thermals originate higher up, are larger, and rise faster, although radius and ascent rate are only weakly correlated among individual thermals. The main force opposing buoyancy is a nonhydrostatic pressure drag, not mixing of momentum. This drag can be expressed in terms of a drag coefficient cd that decreases as convection intensifies: deep convective thermals are less damped, with cd ~ 0.2, while shallow convective thermals are more damped, with cd ~ 0.6. The expected dependence of cd based on theoretical form and wave drag coefficients for a solid sphere is inconsistent with these results, since it predicts the opposite dependence on the Froude number. Thus, a theory for drag on cumulus thermals is not straightforward. Overall, it is argued that thermals are a more realistic prototype for atmospheric deep convection than plumes, at least for the less organized convection types simulated here.
Journal Article