Motivated by convection in the context of geological carbon-dioxide (CO2) storage, we present an experimental study of dissolution-driven convection in a Hele–Shaw cell for Rayleigh numbers \documentclass[12pt]{minimal}\begin{document}$\mathcal {R}$\end{document}R in the range \documentclass[12pt]{minimal}\begin{document}$100 < \mathcal {R}< 1700$\end{document}100<R<1700. We use potassium permanganate (KMnO4) in water as an analog for CO2 in brine and infer concentration profiles at high spatial and temporal resolution and accuracy from transmitted light intensity. We describe behavior from first contact up to 65% average saturation and measure several global quantities including dissolution flux, average concentration, amplitude of perturbations away from pure one-dimensional diffusion, and horizontally averaged concentration profiles. We show that the flow evolves successively through distinct regimes starting with a simple one-dimensional diffusional profile. This is followed by linear growth in which fingers are initiated and grow quasi-exponentially, independently of one-another. Once the fingers are well-established, a flux-growth regime begins as fresh fluid is brought to the interface and contaminated fluid removed, with the flux growing to a local maximum. During this regime, fingers still propagate independently. However, beyond the flux maximum, fingers begin to interact and zip together from the root down in a merging regime. Several generations of merging occur before only persistent primary fingers remain. Beyond this, the reinitiation regime begins with new fingers created between primary existing ones before merging into them. Through appropriate scaling, we show that the regimes are universal and independent of layer thickness (equivalently \documentclass[12pt]{minimal}\begin{document}$\mathcal {R}$\end{document}R) until the fingers hit the bottom. At this time, progression through these regimes is interrupted and the flow transitions to a saturating regime. In this final regime, the flux gradually decays in a manner well described by a Howard-style phenomenological model.

Foot stiffness underlies its mechanical function, and is central to the evolution of human bipedal locomotion. [1][2][3][4][5] The stiff and propulsive human foot has two distinct arches, the longitudinal and transverse. [3][4][5] By contrast, the feet of non-human primates are flat and softer. 6-8 Current understanding of foot stiffness is based on studies that focus solely on the longitudinal arch, [9][10][11][12][13][14] and little is known about the mechanical function of the transverse arch. However, common experience suggests that transverse curvature dominates the stiffness; a drooping dollar bill stiffens significantly upon curling it along the transverse direction, not the longitudinal. We derive a normalized curvature parameter that encapsulates the geometric principle 15 underlying the transverse curvature-induced stiffness. We show that the transverse arch accounts for almost all the difference in stiffness between human and monkey feet (vervet monkeys and pig-tailed macaques) by comparing transverse curvature-based predictions against published data on foot stiffness. 6,7 Using this functional interpretation of the transverse arch, we trace the evolution of hominin feet [16][17][18][19][20] and show that a human-like stiff foot likely predates Homo by ∼ 1.5 million years, and appears in the ∼ 3.4 million year old fossil from Burtele. 19 A distinctly human-like transverse arch is also present in early members of Homo, including Homo naledi, 20 Homo habilis, 16 and Homo erectus. 17 However, the ∼ 3.2 million year old Australopithecus afarensis 18 is estimated to have possessed a transitional foot, softer than humans and stiffer than other extant primates. A foot with human-like stiffness probably evolved around the same time as other lower limb adaptations for regular bipedality, 3,18,21,22 and well before the emergence of Homo, the longitudinal arch, and other adaptations for endurance running. 2 *

The onset of monami -the synchronous waving of seagrass beds driven by a steady flow -is modelled as a linear instability of the flow. Unlike previous works, our model considers the drag exerted by the grass in establishing the steady flow profile, and in damping out perturbations to it. We find two distinct modes of instability, which we label modes 1 and 2. Mode 1 is closely related to Kelvin-Helmholtz instability modified by vegetation drag, whereas mode 2 is unrelated to Kelvin-Helmholtz instability and arises from an interaction between the flow in the vegetated and unvegetated layers. The vegetation damping, according to our model, leads to a finite threshold flow for both of these modes. Experimental observations for the onset and frequency of waving compare well with model predictions for the instability onset criteria and the imaginary part of the complex growth rate respectively, but experiments lie in a parameter regime where the two modes can not be distinguished.

Particles floating on the surface of a turbulent incompressible fluid accumulate along string-like structures, while leaving large regions of the flow domain empty. This is reflected experimentally by a very peaked probability distribution function of c(r), the coarse-grained particle concentration at scale r, around c(r)=0, with a power-law decay over two decades of c(r), Pi(c(r)) proportional, variant c(r)(-beta(r)). The positive exponent beta(r) decreases with scale in the inertial range and stays approximately constant in the dissipative range, thus, indicating a qualitative difference between the dissipative and the inertial ranges of scales, also visible in the first moment of c(r).

Wind power fluctuations for an individual turbine and plant have been widely reported to follow the Kolmogorov spectrum of atmospheric turbulence; both vary with a fluctuation time scale τ as τ^{2/3}. Yet, this scaling has not been explained through turbulence theory. Using turbines as probes of turbulence, we show the τ^{2/3} scaling results from a large scale influence of atmospheric turbulence. Owing to this long-range influence spanning 100s of kilometers, when power from geographically distributed wind plants is summed into aggregate power at the grid, fluctuations average (geographic smoothing) and their scaling steepens from τ^{2/3}→τ^{4/3}, beyond which further smoothing is not possible. Our analysis demonstrates grids have already reached this τ^{4/3} spectral limit to geographic smoothing.