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At least 1,009 records · Page 56

Synthetic Butterfly Scale Surfaces with Compliance‐Tailored Anisotropic Drop Adhesion

Abstract Many natural surfaces such as butterfly wings, beetles' backs, and rice leaves exhibit anisotropic liquid adhesion; this is of fundamental interest and is important to applications including self‐cleaning surfaces, microfluidics, and phase change energy conversion. Researchers have sought to mimic the anisotropic adhesion of butterfly wings using rigid surface textures, though natural butterfly scales are sufficiently compliant to be deflected by capillary forces exerted by drops. Here, inspired by the flexible scales of the Morpho aega butterfly wing, synthetic surfaces coated with flexible carbon nanotube (CNT) microscales with anisotropic drop adhesion properties are fabricated. The curved CNT scales are fabricated by a strain‐engineered chemical vapor deposition technique, giving ≈5000 scales of ≈10 µm thickness in a 1 cm 2 area. Using various designed CNT scale arrays, it is demonstrated that the anisotropy of drop roll‐off angle is influenced by the geometry, compliance, and hydrophobicity of the scales; and a maximum roll‐off anisotropy of 6.2° is achieved. These findings are supported by a model that relates the adhesion anisotropy to the scale geometry, compliance, and wettability. The electrical conductivity and mechanical robustness of the CNTs, and the ability to fabricate complex multidirectional patterns, suggest further opportunities to create engineered synthetic scale surfaces.

Zhao, Hangbo↗

A study on the scale dependence of mixing indices for Eulerian multiphase models

Abstract Mixing can vary based on the scale at which the system is observed, and a mixing index that can capture the features at different length scales is desirable. In this article, we analyze the scale dependence of the mixing indices developed for Eulerian multiphase models. Relevant length scales are distinguished by filtering solid fraction fields. The scale‐dependence study is first done on manufactured fields of solid fraction to assess the performance of the mixing indices. The study is extended to a two‐dimensional CFD simulation of the segregation of a bidisperse gas–solid mixture. The local mixing index performs well in capturing the spatial variation of mixing at different scales. The scale dependence of two global mixing indices is considered in the study, where the state of mixing is defined based on statistical measures. We demonstrate that the choice of measures influences the sensitivity of mixing indices to mixing at different scales.

Nagawkar, Barlev R.↗

Scale-fixed predictions for γ + η c production in electron-positron collisions at NNLO in perturbative QCD

In the paper, we present QCD predictions for γ + η c production at an electron-positron collider up to next-to-next-to-leading order (NNLO) accuracy without renormalization scale ambiguities. The NNLO total cross-section for e + + e – → γ + η c using the conventional scale-setting approach has large renormalization scale ambiguities, usually estimated by choosing the renormalization scale to be the e + e – center-of-mass collision energy $\sqrt{s}$. The Principle of Maximum Conformality (PMC) provides a systematic way to eliminate such renormalization scale ambiguities by summing the nonconformal β contributions into the QCD coupling α s ( Q 2 ). The renormalization group equation then sets the value of α s for the process. The PMC renormalization scale reflects the virtuality of the underlying process, and the resulting predictions satisfy all of the requirements of renormalization group invariance, including renormalization scheme invariance. After applying the PMC, we obtain a renormalization scale-and-scheme independent prediction, σ | NNLO,PMC ≃ 41.18 fb for $\sqrt{s}$=10.6 GeV. The resulting pQCD series matches the series for conformal theory and thus has no divergent renormalon contributions. The large K factor which contributes to this process reinforces the importance of uncalculated NNNLO and higher-order terms. Using the PMC scale-and-scheme independent conformal series and the Padé approximation approach, we predict σ | NNNLO,PMC+Pade ≃ 18.99 fb, which is consistent with the recent BELLE measurement ${\sigma}^{\mathrm{obs}}={16.58}_{-9.93}^{+10.51}$ fb at $\sqrt{s}$ ≃ 10.6 GeV. This procedure also provides a first estimate of the NNNLO contribution.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Hourly water-carbon interactions modulate decadal water-use efficiency trends inferred from ecosystem-scale measurements

Plant stomatal conductance regulates photosynthesis and transpiration. This physiological link affects ecosystem responses to microclimate and harmonizes carbon, energy, and water exchanges between the biosphere and atmosphere. The relationship between water losses via transpiration and carbon gains via photosynthesis can be quantified by plant water-use efficiency (WUE). While leaf- and ecosystem-scale observations both suggest rising WUE in recent decades, WUE trends inferred from the ecosystem scale are much larger than those inferred from the leaf scale or implied by theory. The unexpectedly large ecosystem-scale WUE trends complicate interpretation of ecophysiological responses to changing environmental conditions. Here, we analyze ecosystem-scale WUE inferred from 40 FLUXNET sites, each with at least 10 years of measurements. Furthermore, our results demonstrate that observed ecosystem-scale WUE trends are more sensitive to hourly weather conditions than longer-term changes in atmospheric carbon dioxide or vapor pressure deficit. Our analysis shows that Earth System Models participating in CMIP6 did not capture the observed WUE sensitivity to inter-site variability and microclimatic conditions. Collectively, our findings suggest that ecosystem-scale WUE trends reflect water-carbon interactions across multiple temporal scales, and disentangling factors contributing to emergent ecosystem responses is needed to infer ecophysiological relationships and model structures from observations.

54 ENVIRONMENTAL SCIENCES↗

Sample-based synthesis of two-scale structures with anisotropy

A vast majority of natural or synthetic materials are characterized by their anisotropic properties, such as stiffness. Such anisotropy is effected by the spatial distribution of the fine-scale structure and/or anisotropy of the constituent phases at a finer scale. In design, proper control of the anisotropy may greatly enhance the efficiency and performance of synthesized structures. In this paper, we propose a sample-based two-scale structure synthesis approach that explicitly controls anisotropic effective material properties of the structure on the coarse scale by orienting sampled material neighborhoods at the fine scale. We first characterize the non-uniform orientations distribution of the sample structure by showing that the principal axes of an orthotropic material may be determined by the eigenvalue decomposition of its effective stiffness tensor. Such effective stiffness tensors can be efficiently estimated based on the two-point correlation functions of the fine-scale structures. Then we synthesize the two-scale structure by rotating fine-scale structures from the sample to follow a given target orientation field. Finally, the effectiveness of the proposed approach is demonstrated through examples in both 2D and 3D.

42 ENGINEERING↗

A multi-scale calibration approach for process-oriented aggregated building energy demand models

Long-term energy planning relies largely on projections of future energy demand and hourly load profiles. Aggregate building models are increasingly being utilized to characterize the sensitivity of current and future building stocks to changes in climate, population, and building technology on city-to-regional-to-national scales. Due to challenges in the availability of data, those analyses have been limited to projection of energy demand at a single scale, usually state or country, while long-term planning power system models and production cost models might operate at different spatial scales such as energy regions which are focused on ensuring adequate generation infrastructure. In this work, we propose and evaluate a novel method to calibrate an aggregate building energy demand model (PNNL’s BEND model) against the best available data at the spatial scale of balancing authorities. This approach extends previous work on aggregated building energy demand by facilitating analysis of building energy demand across scales, in particular policy and operational decision-making scales. We show that the bias-corrected model estimates building electric loads reasonably well compared with estimates from a statistical model, but has the additional feature of flexibility across spatial scales. While the calibration approach is presently U.S.-centric and associated with U.S. energy regions, it can be extrapolated to other worldwide regions with similar scale challenges between policy and operational implementation decision making. We discuss the significant challenges involved in formulating and calibrating a complex physical model based on simulations of roughly 100,000 individual buildings against available aggregate regional electric load data and highlight areas for potential future work and improved data collection.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Assessing pore network heterogeneity across multiple scales to inform CO2 injection models

Geologic heterogeneity is a key feature that must be considered when translations of scaled data are performed. This paper presents the assessment of geologic heterogeneity using a multiscale workflow that includes image analysis-based methods coupled with well log analysis to provide data in which fractals and machine learning methods estimate the carbon dioxide (CO 2 ) storage resource potential of a reservoir. The heterogeneity of rock properties of the complex Bell Creek reservoir in Montana, USA, was explored at the pore scale (~nm to mm), core scale (~mm to m), and well scale (~cm to m). The data used in this study included advanced image analysis of micro-CT (computed tomography) images (pore scale), thin sections (pore scale), plugs and core images (core scale) and well logs (well scale). The micro-CT images were segmented using a U-net segmentation approach into objects of pores and grains. Further, the segmented images were reconstructed into subvolumes of different sizes. Physical properties (porosity and permeability) and fractal dimensions were calculated for the various subvolumes, and Lorenz coefficient (Lc) values, a single parameter to describe the degree of heterogeneity within a pay zone section, were calculated from thin-section images and well logs. Porosity and fractal dimension values were used to estimate the 188-µm threshold of representative elementary volume (REV) in this study. Both the Lc and fractal dimension values were found to be negatively correlated. When these two parameters are combined, it is possible to discern differences in the complex porous networks of the samples analyzed in this study.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Scaling of two-phase water-steam relative permeability and thermal fluxes in porous media

Two-phase water-steam flow conditions are frequently encountered in many engineering applications, including geothermal reservoirs. Although routine calculations are based on the multiphase Darcy’s law, the role of the topology of the flowing phases at the pore-scale is usually neglected in the estimation of relative permeabilities. Instead, the latter are frequently computed using empirical models like the Corey correlation. In this work, we first apply the model for relative permeabilities based on pore-scale flow regimes developed by Picchi and Battiato (2019), Relative permeability scaling from pore-scale flow regimes, Water Resour. Res. 55, 3215–3233, to scenarios typical of geothermal reservoirs and then extend it by deriving the scaling laws for the transmissibilities and the thermal properties as a function of temperature. First, we discuss the scaling behavior of normalized relative permeabilities in terms of viscosity ratio and capillary number of water-steam systems and, then, we provide a validation of the model against experimental data available in the literature. The model captures well the data trends collected in real 3D porous media. These results suggest that water-steam relative permeabilities follow the same scaling behavior of gas-liquid systems where the non-wetting phase is much less viscous than the wetting phase. Finally, we investigate the impact that relative permeabilities have on heat transfer rates at two-phase flow conditions and the scaling of mass and energy transmissibility and thermal properties of the mixture. An estimation of the exergy carried by the two-phase water-steam mixture is also included.

42 ENGINEERING↗

Determination of the oxide scale growth mechanism using 18O-tracer experiments in combination with Transmission Electron Microscopy and nanoscale Secondary Ion Mass Spectrometry

Highlights: • {sup 18}O-tracer experiments to determine oxide scale growth mechanism on a Fe-Cr alloy. • Cr{sub 2}O{sub 3} scale growth primarily by means of metal outwards diffusion in air at 850 °C • nanoSIMS mapping on TEM lamella more accurate than SIMS sputter depth profiling • nanoSIMS mapping on TEM lamella reveal information about local oxide growth. • Strong local variation of oxide scale growth - Abstract: Two-stage {sup 18}O{sub 2}/{sup 16}O{sub 2} exposures can be used to investigate the effect that alloying elements, secondary phases, or surface treatments have on the high temperature oxidation behaviour of certain materials. During subsequent exposures to {sup 16}O{sub 2}- and {sup 18}O{sub 2}-rich atmospheres, {sup 16}O- and {sup 18}O-rich layers are formed. Analysis of the layers using Secondary Ion Mass Spectrometry (SIMS) depth profiling allows for conclusions to be drawn about the oxide scale growth mechanism. The conclusions are, however, not entirely unambiguous due to the limited lateral resolution of the technology. Rough surface topography and the thickness variation of the oxide scale over the analysed volume add to the ambiguity of the findings. In this study, an Fe-20%Cr alloy was exposed to both {sup 18}O- and {sup 16}O-rich environments at 850 °C. Two methods were used to analyse the thermally grown Cr{sub 2}O{sub 3} scale: (1) traditional SIMS depth profiling and (2) preparation of a cross-sectional lamellae for Transmission Electron Microscopy (TEM), which, subsequently, was analysed in a NanoSIMS. The NanoSIMS {sup 16}O and {sup 18}O elemental maps were then superimposed on the TEM image. In comparison with traditional SIMS depth profiling, the nanoSIMS elemental maps reveal detailed information about local oxide growth in different parts of an oxide scale. Moreover, a clear {sup 16}O/{sup 18}O interface can be seen in the nanoSIMS maps, which is not the case in the sputter depth profiles. The findings of this study show that the aforementioned issues associated with sputter depth profiling can be eliminated by mapping a cross-section of an oxide scale using high resolution nanoSIMS.

36 MATERIALS SCIENCE↗

Study of the scale formed on super 304H boiler tube steels after long-term steam oxidation at high temperatures

Highlights: • Steam oxidation tests were performed on the conventional and shot-peened Super304H boiler tube. • A continuous amorphous SiO{sub 2} layer separated the metal from the scale in shot-peened specimen. • The SiO{sub 2} layer enhanced the formation of dense Cr{sub 2}O{sub 3} and FeCr{sub 2}O{sub 4} layers. • The scale on shot-peened specimens is stable upon steam temperature and time increase. Steam oxidation of a Super 304H boiler tube was performed at steam temperatures of 650 °C and 700 °C for time durations up to 5000 h. The oxidation scale outcomes which formed on as-received untreated and shot-peened (SP) tubes were studied using X-ray diffraction (XRD), scanning electron microscopy (SEM), electron backscatter diffraction (EBSD), and transmission electron microscopy (TEM). γ-Grain nanocrystallization on the surface of the SP specimen generated an abundant fraction of grain boundary that guaranteed the formation of a continuous amorphous SiO{sub 2} layer at the metal-scale interface that enhanced the formation of dense Cr{sub 2}O{sub 3} and FeCr{sub 2}O{sub 4} in the scale. Scale breakaway along defects in the outer layer of the scale was accelerated by the steam temperature in the untreated specimens, whereas the scale that formed on the SP specimens appeared to be stable.

36 MATERIALS SCIENCE↗

Mechanisms of Dynamic Near-Wake Modulation of a Utility-Scale Wind Turbine

The current study uses large eddy simulations to investigate the transient response of a utility-scale wind turbine wake to dynamic changes in atmospheric and operational conditions, as observed in previous field-scale measurements. Most wind turbine wake investigations assume quasi-steady conditions, but real wind turbines operate in a highly stochastic atmosphere, and their operation (e.g. blade pitch, yaw angle) changes constantly in response. Furthermore, dynamic control strategies have been recently proposed to optimize wind farm power generation and longevity. Therefore, improved understanding of dynamic wake behaviours is essential. First, changes in blade pitch are investigated and the wake expansion response is found to display hysteresis as a result of flow inertia. The time scales of the wake response to different pitch rates are quantified. Next, changes in wind direction with different time scales are explored. Under short time scales, the wake deflection is in the opposite direction of that observed under quasi-steady conditions. Finally, yaw changes are implemented at different rates, and the maximum inverse wake deflection and time scale are quantified, showing a clear dependence on yaw rate. To gain further physical understanding of the mechanism behind the inverse wake deflection, the streamwise vorticity in different parts of the wake is quantified. The results of this study provide guidance for the design of advanced wake flow control algorithms. The lag in wake response observed for both blade pitch and yaw changes shows that proposed dynamic control strategies must implement turbine operational changes with a time scale of the order of the rotor time scale or slower.

flow-structure interactions↗

Analysis of scale-dependent kinetic and potential energy in sheared, stably stratified turbulence

Budgets of turbulent kinetic energy (TKE) and turbulent potential energy (TPE) at different scales $\ell$ in sheared, stably stratified turbulence are analysed using a filtering approach. Competing effects in the flow are considered, along with the physical mechanisms governing the energy fluxes between scales, and the budgets are used to analyse data from direct numerical simulation at buoyancy Reynolds number $Re_b=O(100)$ . The mean TKE exceeds the TPE by an order of magnitude at the large scales, with the difference reducing as $\ell$ is decreased. At larger scales, buoyancy is never observed to be positive, with buoyancy always converting TKE to TPE. As $\ell$ is decreased, the probability of locally convecting regions increases, though it remains small at scales down to the Ozmidov scale. The TKE and TPE fluxes between scales are both downscale on average, and their instantaneous values are correlated positively, but not strongly so, and this occurs due to the different physical mechanisms that govern these fluxes. Moreover, the contributions to these fluxes arising from the sub-grid fields are shown to be significant, in addition to the filtered scale contributions associated with the processes of strain self-amplification, vortex stretching and density gradient amplification. Probability density functions (PDFs) of the $Q,R$ invariants of the filtered velocity gradient are considered and show that as $\ell$ increases, the sheared-drop shape of the PDF becomes less pronounced and the PDF becomes more symmetric about $R=0$ .

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Numerical validation of scaling laws for stratified turbulence

Recent theoretical progress using multiscale asymptotic analysis has revealed various possible regimes of stratified turbulence. Notably, buoyancy transport can either be dominated by advection or diffusion, depending on the effective Péclet number of the flow. Two types of asymptotic models have been proposed, which yield measurably different predictions for the characteristic vertical velocity and length scale of the turbulent eddies in both diffusive and non-diffusive regimes. The first, termed a ‘single-scale model’, is designed to describe flow structures having large horizontal and small vertical scales, while the second, termed a ‘multiscale model’, additionally incorporates flow features with small horizontal scales, and reduces to the single-scale model in their absence. By comparing predicted vertical velocity scaling laws with direct numerical simulation data, we show that the multiscale model correctly captures the properties of strongly stratified turbulence within regions dominated by small-scale isotropic motions, whose volume fraction decreases as the stratification increases. Meanwhile its single-scale reduction accurately describes the more orderly, layer-like, quiescent flow outside those regions.

Mechanics↗

Influence of Charge Scaling on the Solvation Properties of Ionic Liquid Solutions

Scaled-charge force fields (FFs) are widely employed in the simulation of neat ionic liquids (ILs), where the charges on the ions are empirically scaled to approximately account for electronic polarization and/or charge transfer. Such charge scaling has been found to yield significant improvement in liquid-state thermodynamic and dynamic properties (when compared to experiment). However, the mean field approximation inherent in charge scaling becomes suspect when applied to IL mixtures or solutions. In this work, we simulate solutions of IL with various nonpolar and polar gas solutes and compare results of charge-scaled and polarizable FFs to experiment. Our results demonstrate that scaling of the Coulomb interaction inherent in scaled-charge FFs leads to an underestimation of the solute–solvent electrostatic interaction and thus also the enthalpy and free energy of solvation; this effect is particularly pronounced for polar solutes. In some cases, we find that this artificial reduction in the solute–solvent interaction can also alter the apparent phase behavior of the resulting solution. Altogether, the totality of our results suggests that explicit polarization (rather than charge scaling) is likely necessary to provide high transferability to both neat IL and IL mixtures and solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Soil microbiome predictability increases with spatial and taxonomic scale

Soil microorganisms shape ecosystem function, yet it remains an open question whether we can predict the composition of the soil microbiome in places before observing it. Furthermore, it is unclear whether the predictability of microbial life exhibits taxonomic- and spatial-scale dependence, as it does for macrobiological communities. Here, we leverage multiple large-scale soil microbiome surveys to develop predictive models of bacterial and fungal community composition in soil, then test these models against independent soil microbial community surveys from across the continental United States. We find remark- able scale dependence in community predictability. The predictability of bacterial and fungal communities increases with the spatial scale of observation, and fungal predictability increases with taxonomic scale. These patterns suggest that there is an increasing importance of deterministic versus stochastic processes with scale, consistent with findings in plant and animal communities, suggesting a general scaling relationship across biology. Biogeochemical functional groups and high-level taxonomic groups of microorganisms were equally predictable, indicating that traits and taxonomy are both powerful lenses for understanding soil communities. Here, by focusing on out-of-sample prediction, these findings suggest an emerging generality in our understanding of the soil microbiome, and that this understanding is fundamentally scale dependent

Biogeography↗

Biome-scale temperature sensitivity of ecosystem respiration revealed by atmospheric CO2 observations

Abstract The temperature sensitivity of ecosystem respiration regulates how the terrestrial carbon sink responds to a warming climate but has been difficult to constrain observationally beyond the plot scale. Here we use observations of atmospheric CO 2 concentrations from a network of towers together with carbon flux estimates from state-of-the-art terrestrial biosphere models to characterize the temperature sensitivity of ecosystem respiration, as represented by the Arrhenius activation energy, over various North American biomes. We infer activation energies of 0.43 eV for North America and 0.38 eV to 0.53 eV for major biomes therein, which are substantially below those reported for plot-scale studies (approximately 0.65 eV). This discrepancy suggests that sparse plot-scale observations do not capture the spatial-scale dependence and biome specificity of the temperature sensitivity. We further show that adjusting the apparent temperature sensitivity in model estimates markedly improves their ability to represent observed atmospheric CO 2 variability. This study provides observationally constrained estimates of the temperature sensitivity of ecosystem respiration directly at the biome scale and reveals that temperature sensitivities at this scale are lower than those based on earlier plot-scale studies. These findings call for additional work to assess the resilience of large-scale carbon sinks to warming.

54 ENVIRONMENTAL SCIENCES↗

Universal scaling laws and density slopes for dark matter haloes

Smalls scale challenges suggest some missing pieces in our current understanding of dark matter. In this work, a cascade theory for dark matter is proposed to provide extra insights, similar to the cascade phenomenon in hydrodynamic turbulence. The kinetic energy is cascaded in dark matter from small to large scales involves a constant rate $ε_u$ (≈–4.6×10 –7 m 2 / s 3 ). Confirmed by N-body simulations, the energy cascade leads to a two-thirds law for kinetic energy $v^2_r$ on scale $\textit{r}$ such that $v^2_r∝(ε_ur)^{2/3}$. Equivalently, a four-thirds law can be established for mean halo density $ρ_s$ enclosed in the scale radius $r_s$ such that $ρ_s ∝ε^{2/3}_uG^{–1}r^{–4/3}_s$, which was confirmed by galaxy rotation curves. Critical properties of dark matter might be obtained by identifying key constants on relevant scales. First, the largest halo scale $r_l$ can be determined by $–u^3_0/ε_u$, where u0 is the velocity dispersion. Second, the smallest scale rη is dependent on the nature of dark matter. For collisionless dark matter, $r_η∝(–Gℏ/ε_u)^{1/3}$ ≈ 10 –13 m , where ℏ is the Planck constant. An uncertainty principle for momentum and acceleration fluctuations is also postulated. For self-interacting dark matter, $r_η∝ε^2_uG^{–3}(σ/m)^3$, where σ/m is the cross-section of interaction. On halo scale, the energy cascade leads to an asymptotic density slope γ = –4/3 for fully virialized haloes with a vanishing radial flow, which might explain the nearly universal halo density. Based on the continuity equation, halo density is analytically shown to be closely dependent on the radial flow and mass accretion, such that simulated haloes can have different limiting slopes. A modified Einasto density profile is proposed accordingly.

79 ASTRONOMY AND ASTROPHYSICS↗

Global tropical cyclone precipitation scaling with sea surface temperature

Understanding the relationship between tropical cyclone (TC) precipitation and sea surface temperature (SST) is essential for both TC hazard forecasting and projecting how these hazards will change in the future due to climate change. This work untangles how global TC precipitation is impacted by present-day SST variability (known as apparent scaling) and by long-term changes in SST caused by climate change (known as climate scaling). A variety of datasets are used including precipitation and SST observations, realistic climate model simulations, and idealized climate model simulations. The apparent scaling rates depend on precipitation metric; examples shown here have ranges of 6.1 to 9.5% per K versus 5.9 to 9.8% per K for two different metrics. The climate scaling is estimated at about 5% per K, which is slightly less than the atmospheric moisture scaling based on thermodynamic principles of about 7% per K (i.e., the Clausius–Clapeyron scaling). The apparent scaling is greater than the climate scaling, which implies that the relationship between TC precipitation and present-day SST variability should not be used to project the long-term response of TC precipitation to climate change.

54 ENVIRONMENTAL SCIENCES↗