Spatial Length Scales Research Articles

CNN for scalar-source distance estimation in grid-generated turbulence

Countermeasures against material leakage in industrial plants call for rapid leak source estimation techniques based on limited downstream information. Assuming that such scalar diffusion occurs in a turbulent environment, it is necessary to extract features from its instantaneous local concentration distribution and estimate the distance from the observation point to the source. To this end, we proposed an estimation method using a supervised deep learning of a convolutional neural network (CNN) and investigated its estimation performance in grid-generated turbulence fields. The grid turbulence fields were reproduced by direct numerical simulations at three Reynolds numbers (Re), and the CNN was trained using two-dimensional distribution images of passive scalars downstream. We confirmed that the images large enough to cover the spatial integral length scales of the scalar resulted in high estimation accuracy. For images with a coarsened brightness gradation, the small-scale feature of scalar fluctuations was lost, and the CNN attained a low estimation accuracy. By training the CNN with high-Re images, a high estimation accuracy was obtained, even for low-Re images. The opposite case (low-Re training and high-Re estimation) yielded low accuracy, where the CNN significantly underestimated the distance against the source. Based on these results, we discussed the generalizability and essential features to be learned by the CNN.

Superposition‐based concurrent multiscale approaches for porodynamics

AbstractThe current study presents superposition‐based concurrent multiscale approaches for porodynamics, capable of capturing related physical phenomena, such as soil liquefaction and dynamic hydraulic fracture branching, across different spatial length scales. Two scenarios are considered: superposition of finite element discretizations with varying mesh densities, and superposition of peridynamics (PD) and finite element method (FEM) to handle discontinuities like strain localization and cracks. The approach decomposes the acceleration and the rate of change in pore water pressure into subdomain solutions approximated by different models, allowing high‐fidelity models to be used locally in regions of interest, such as crack tips or shear bands, without neglecting the far‐field influence represented by low‐fidelity models. The coupled stiffness, mass, compressibility, permeability, and damping matrices were derived based on the superposition‐based current multiscale framework. The proposed FEM‐FEM porodynamic coupling approach was validated against analytical or numerical solutions for one‐ and two‐dimensional dynamic consolidation problems. The PD‐FEM porodynamic coupling model was applied to scenarios like soil liquefaction‐induced shear strain accumulation near a low‐permeability interlayer in a layered deposit and dynamic hydraulic fracturing branching. It has been shown that the coupled porodynamic model offers modeling flexibility and efficiency by taking advantage of FEM in modeling complex domains and the PD ability to resolve discontinuities.

Accessing versatile tensile ductility of amorphous materials by fractal nanoarchitecture design

Amorphous materials have been known to be intrinsically brittle under tensile stress. This is especially true in silicon-based and metallic-based glasses. In particular, for the latter, they quite often show promising mechanical properties superior to their crystalline counterparts. However, lacking tensile ductility strongly prohibits them from servicing the societies. Although with decades of immense research efforts, we are still waiting for a sophisticated solution. To march in this direction, in this work, we are dedicated to finding a practical method by smart fractal nano-architecture design through advanced computational modeling. This mainly aims to circumvent the intrinsic strain localization at the nano-scale to avoid catastrophic failure. By distributing the external strain to numerous self-confined nano-branches, we successfully achieve astonishing and tunable tensile ductility. This strategy proves to be very effective for different classes of amorphous materials. We found that the tensile properties of the nano-architectured glasses depend on both the constituent elements and the nanostructure. This demonstrates our flexible capability to design desired mechanical properties for a specific material at any spatial length scale. The current findings will inspire experimental realization by cutting-edge 3D-printing techniques and call for optimal design by top-notch graph neural network deep learning algorithms. This work also proposes a new ’structure’-property relationship to efficiently bridge experimental fabrication and computational design.

Quantification of melt pool dynamics and microstructure during simulated additive manufacturing

The dynamics of laser spot melting and metallic alloy solidification are investigated through synchrotron x-ray radiography, 3D electron backscatter diffraction data, and computational fluid dynamics (CFD) simulations on a model NiMoAl alloy. Solidification velocities are measured from in-situ images to validate a CFD model of the spot melt. TriBeam tomography is used to reconstruct the melt pool in 3D, characterize the microstructure, and validate the CFD model melt pool dimensions. 3D geometrically necessary dislocation (GND) density calculations reveal extensive deformation at the sample surface. GND calculations integrated with the CFD model reveal that the halo of small, equiaxed grains adjacent to the fusion line is a result of recrystallization that occurred in the heat affected zone. By combining in-situ and ex-situ data modalities across a variety of temporal and spatial length scales, the microstructure formation mechanisms and their relationship to melt pool solidification are quantified.

Profiling the molecular destruction rates of temperature and humidity as well as the turbulent kinetic energy dissipation in the convective boundary layer

Abstract. A simultaneous deployment of Doppler, temperature, and water-vapor lidars is able to provide profiles of molecular destruction rates and turbulent kinetic energy (TKE) dissipation in the convective boundary layer (CBL). Horizontal wind profiles and profiles of vertical wind, temperature, and moisture fluctuations are combined, and transversal temporal autocovariance functions (ACFs) are determined for deriving the dissipation and molecular destruction rates. These are fundamental loss terms in the TKE as well as the potential temperature and mixing ratio variance equations. These ACFs are fitted to their theoretical shapes and coefficients in the inertial subrange. Error bars are estimated by a propagation of noise errors. Sophisticated analyses of the ACFs are performed in order to choose the correct range of lags of the fits for fitting their theoretical shapes in the inertial subrange as well as for minimizing systematic errors due to temporal and spatial averaging and micro- and mesoscale circulations. We demonstrate that we achieve very consistent results of the derived profiles of turbulent variables regardless of whether 1 or 10 s time resolutions are used. We also show that the temporal and spatial length scales of the fluctuations in vertical wind, moisture, and potential temperature are similar with a spatial integral scale of ≈160 m at least in the mixed layer (ML). The profiles of the molecular destruction rates show a maximum in the interfacial layer (IL) and reach values of ϵm≃7×10-4 g2 kg−2 s−1 for mixing ratio and ϵθ≃1.6×10-3 K2 s−1 for potential temperature. In contrast, the maximum of the TKE dissipation is reached in the ML and amounts to ≃10-2 m2 s−3. We also demonstrate that the vertical wind ACF coefficient kw∝w′2‾ and the TKE dissipation ϵ∝w′2‾3/2. For the molecular destruction rates, we show that ϵm∝m′2‾w′2‾1/2 and ϵθ∝θ′2‾w′2‾1/2. These equations can be used for parameterizations of ϵ, ϵm, and ϵθ. All noise error bars are derived by error propagation and are small enough to compare the results with previous observations and large-eddy simulations. The results agree well with previous observations but show more detailed structures in the IL. Consequently, the synergy resulting from this new combination of active remote sensors enables the profiling of turbulent variables such as integral scales, variances, TKE dissipation, and the molecular destruction rates as well as deriving relationships between them. The results can be used for the parameterization of turbulent variables, TKE budget analyses, and the verification of large-eddy simulations.

Experimental study on passive plate pitching and coherent structures in a square channel by TR-PIV

The interaction of plate pitching and vortex may damage the accumulator isolation passive valve in nuclear power plant. The plate pitching and turbulent flow in a square channel were studied by high-speed camera (HSC) and time-resolved particle image velocimetry (TR-PIV) at Reynolds numbers (Re) from 1474 to 58952.The plate angle captured by HSC were analyzed by edge detection algorithm. The plate is inclined in hydraulic equilibrium without oscillation when Re is less than 14738. The plate pitching start to be periodic at Re = 22107, and then the periodicity weakens with Re increasing from 22,107 to 51583. The time-averaged pitching angle increases from 0.08467 rad to 1.454 rad with Re increasing from Re = 1474 to Re = 51583. The standard deviation of pitching angle increases from zero with Re less than 14,738 to 0.1294 rad at Re = 22107, and then it decreases to 0.006536 rad at Re = 51583. The peak frequency of plate pitching is the same as that of turbulent flow extracted from the power spectral density of instantaneous velocity downstream of the pitching plate, indicating the passive plate pitching is determined by turbulence. The plate pitching is driven by lift force torque due to the leading-edge-vortex shedding from the pitching plate.The interaction between passive plate pitching and fluid generates complicated turbulence. The time-averaged flow structures are typical shear-flow due to small plate inclination angle without oscillation when Re is less than 14738. The Reynolds stresses are highly enhanced in the shear flow. At Re = 22107, the time-averaged flow structures behave as vortex bubble over the plate and shear flow surrounding the plate, and the Reynolds stresses downstream of the plate are obviously enhanced by shedding vortices from the plate. With Re increasing from 22,107 to 58952, the time-averaged vortex bubble becomes smaller and shifts downwards to the plate trailing end, while the Reynolds stresses with similar distribution patterns decrease fast. The peak frequency of vortex shedding increases with Re increasing. The large spatial and temporal length scales are induced by shear flow at low Re less than 14738. The large length scales are dominated by von Kármán street shedding from the plate at Re from 22,107 to 58952, which are identified by proper orthogonal decomposition (POD) analysis, because the first two modes are the same mode of von Kármán street with a phase difference.The experimental work improves understandings of plate-fluid-interaction of the isolation passive valve and supports validations of numerical simulations.

Global analysis of the controls on seawater dimethylsulfide spatial variability

Abstract. Dimethylsulfide (DMS) emitted from the ocean makes a significant global contribution to natural marine aerosol and cloud condensation nuclei and, therefore, our planet's climate. Oceanic DMS concentrations show large spatiotemporal variability, but observations are sparse, so products describing global DMS distribution rely on interpolation or modelling. Understanding the mechanisms driving DMS variability, especially at local scales, is required to reduce uncertainty in large-scale DMS estimates. We present a study of mesoscale and submesoscale (< 100 km) seawater DMS variability that takes advantage of the recent expansion in high-frequency seawater DMS observations and uses all available data to investigate the typical distances over which DMS varies in all major ocean basins. These DMS spatial variability length scales (VLSs) are uncorrelated with DMS concentrations. The DMS concentrations and VLSs can therefore be used separately to help identify mechanisms underpinning DMS variability. When data are grouped by sampling campaigns, almost 80 % of the DMS VLS can be explained using the VLSs of sea surface height anomalies, density, and chlorophyll a. Our global analysis suggests that both physical and biogeochemical processes play an equally important role in controlling DMS variability, which is in contrast with previous results based on data from the low to mid-latitudes. The explanatory power of sea surface height anomalies indicates the importance of mesoscale eddies in driving DMS variability, previously unrecognised at a global scale and in agreement with recent regional studies. DMS VLS differs regionally, including surprisingly high-frequency variability in low-latitude waters. Our results independently confirm that relationships used in the literature to parameterise DMS at large scales appear to be considering the right variables. However, regional DMS VLS contrasts highlight that important driving mechanisms remain elusive. The role of submesoscale features should be resolved or accounted for in DMS process models and parameterisations. Future attempts to map DMS distributions should consider the length scale of variability.

Two‐scale conjugate heat transfer solution for micro‐structured surface

AbstractThe primary challenges for simulating a turbulent flow over a micro‐structured surface arise from the two hugely disparate spatial length scales. For fluid–solid coupled conjugate heat transfer (CHT), there is also a time‐scale disparity. The present work addresses the scale disparities based on a two‐scale framework. For the spatial scale disparity, a dual meshing is employed to couple a global coarse‐mesh domain with local fine‐mesh blocks around micro‐structures through source terms generated from the local fine‐mesh and propagated to the global coarse‐mesh domain. The convergence and robustness of the source terms driven coarse‐mesh solution is enhanced by a balanced eddy‐viscosity damping. In this work, the two‐scale method previously developed only for a fluid‐domain is extended to a solid domain so that thermal conduction around micro‐elements can now be resolved accurately and efficiently. The fluid–solid timescale disparity is dealt with by a frequency domain approach. The time‐averaged (zeroth harmonic) is effectively obtained in the same way as steady CHT. And remarkably, wall temperature unsteadiness can be simply obtained from the fluid temperature harmonics through a wall fluid–solid temperature harmonic transfer‐function at minimal computational cost. The developed CHT capability is validated for an experimental internal cooling channel with multiple surface rib‐elements. For a test configuration with 100 micro‐structures, the fluid domain‐only, the solid domain‐only and the fluid–solid coupled CHT solutions are analyzed respectively to examine and demonstrate the validity of the present framework and implementation methods. Some of the results also serve to illustrate the primary underlying working of the methodology.

Smoothing tool design and performance during subaperture glass polishing.

During subaperture tool grinding and polishing, overlaps of the tool influence function can result in undesirable mid-spatial frequency (MSF) errors in the form of surface ripples, which are often corrected using a smoothing polishing step. In this study, flat multi-layer smoothing polishing tools are designed and tested to simultaneously (1)reduce or remove MSF errors, (2)minimize surface figure degradation, and (3)maximize the material removal rate. A time-dependent convergence model in which spatial material removal varies with a workpiece-tool height mismatch, combined with a finite element mechanical analysis to determine the interface contact pressure distribution, was developed to evaluate various smoothing tool designs as a function of tool material properties, thicknesses, pad textures, and displacements. An improvement in smoothing tool performance is achieved when the gap pressure constant, h¯ (which describes the inverse rate at which the pressure drops with a workpiece-tool height mismatch), is minimized for smaller spatial scale length surface features (namely, MSF errors) and maximized for large spatial scale length features (i.e.,surface figure). Five specific smoothing tool designs were experimentally evaluated. A two-layer smoothing tool using a thin, grooved IC1000 polyurethane pad (with a high elastic modulus, E p a d =360M P a), thicker blue foam (with an intermediate modulus, E f o a m =5.3M P a) underlayer, and an optimized displacement (d t=1m m) provided the best overall performance (namely, high MSF error convergence, minimal surface figure degradation, and high material removal rate).

Sea ice and snow characteristics from year-long transects at the MOSAiC Central Observatory

Repeated transects have become the backbone of spatially distributed ice and snow thickness measurements crucial for understanding of ice mass balance. Here we detail the transects at the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) 2019–2020, which represent the first such measurements collected across an entire season. Compared with similar historical transects, the snow at MOSAiC was thin (mean depths of approximately 0.1–0.3 m), while the sea ice was relatively thick first-year ice (FYI) and second-year ice (SYI). SYI was of two distinct types: relatively thin level ice formed from surfaces with extensive melt pond cover, and relatively thick deformed ice. On level SYI, spatial signatures of refrozen melt ponds remained detectable in January. At the beginning of winter the thinnest ice also had the thinnest snow, with winter growth rates of thin ice (0.33 m month−1 for FYI, 0.24 m month−1 for previously ponded SYI) exceeding that of thick ice (0.2 m month−1). By January, FYI already had a greater modal ice thickness (1.1 m) than previously ponded SYI (0.9 m). By February, modal thickness of all SYI and FYI became indistinguishable at about 1.4 m. The largest modal thicknesses were measured in May at 1.7 m. Transects included deformed ice, where largest volumes of snow accumulated by April. The remaining snow on level ice exhibited typical spatial heterogeneity in the form of snow dunes. Spatial correlation length scales for snow and sea ice ranged from 20 to 40 m or 60 to 90 m, depending on the sampling direction, which suggests that the known anisotropy of snow dunes also manifests in spatial patterns in sea ice thickness. The diverse snow and ice thickness data obtained from the MOSAiC transects represent an invaluable resource for model and remote sensing product development.

In situ particle sampling relationships to surface and turbulent fluxes using large eddy simulations with Lagrangian particles

Abstract. Source functions for mechanically driven coarse-mode sea spray and dust aerosol particles span orders of magnitude owing to a combination of physical sensitivity in the system and large measurement uncertainty. Outside special idealized settings (such as wind tunnels), aerosol particle fluxes are largely inferred from a host of methods, including local eddy correlation, gradient methods, and dry deposition methods. In all of these methods, it is difficult to relate point measurements from towers, ships, or aircraft to a general representative flux of aerosol particles. This difficulty is from the particles' inhomogeneous distribution due to multiple spatiotemporal scales of an evolving marine environment. We hypothesize that the current representation of a point in situ measurement of sea spray or dust particles is a likely contributor to the unrealistic range of flux and concentration outcomes in the literature. This paper aims to help the interpretation of field data: we conduct a series of high-resolution, cloud-free large eddy simulations (LESs) with Lagrangian particles to better understand the temporal evolution and volumetric variability of coarse- to giant-mode marine aerosol particles and their relationship to turbulent transport. The study begins by describing the Lagrangian LES model framework and simulates flux measurements that were made using numerical analogs to field practices such as the eddy covariance method. Using these methods, turbulent flux sampling is quantified based on key features such as coherent structures within the marine atmospheric boundary layer (MABL) and aerosol particle size. We show that for an unstable atmospheric stability, the MABL exhibits large coherent eddy structures, and as a consequence, the flux measurement outcome becomes strongly tied to spatial length scales and relative sampling of crosswise and streamwise sampling. For example, through the use of ogive curves, a given sampling duration of a fixed numerical sampling instrument is found to capture 80 % of the aerosol flux given a sampling rate of zf/w∗∼ 0.2, whereas a spanwise moving instrument results in a 95 % capture. These coherent structures and other canonical features contribute to the lack of convergence to the true aerosol vertical flux at any height. As expected, sampling all of the flow features results in a statistically robust flux signal. Analysis of a neutral boundary layer configuration results in a lower predictive range due to weak or no vertical roll structures compared to the unstable boundary layer setting. Finally, we take the results of each approach and compare their surface flux variability: a baseline metric used in regional and global aerosol models.

Experimental study of coherent structures downstream mixing vaned spacer grid of different inclination angles in a 5 × 5 rod bundle by TR-PIV

Experimental study of coherent structures downstream of a spacer grid with different inclination angles (20°, 25°, 30°) of split-type mixing vanes in a 5 × 5 rod bundle was conducted by time-resolved particle image velocimetry (TR-PIV) under Reynolds number from 6.6 × 103 to 3.96 × 104. The fluorinated ethylene propylene (FEP) tubes and water are used as the matched index of refraction (MIR) materials. The maximum standard uncertainty of time-averaged velocity is less than 2 % of bulk flow velocity (Wb), and that of Reynolds stress is less than 2 % Wb2.The secondary flow structures downstream spacer grid with mixing vanes of different inclination angles change with several similar patterns, including vortices shedding from mixing vanes and fast dissipation near spacer grid, counter-current shear-flow development and shear-flow induced vortices formation, shear-flow induced vortices decaying and dissipation. The development trends of spanwise time-averaged velocity, Reynolds stress, integral spatial length scales and integral temporal length scales are determined by coherent structures. With Reynolds number increasing, smaller coherent structures are generated and the time-averaged velocity, Reynolds stress, spatial and temporal length scales decrease. Larger inclination angle generates larger coherent structures, and spatial and temporal length scales increase with inclination angle increasing.The experimental findings provide valuable information for understanding sub-channel mixing phenomena caused by mixing vaned spacer grids. The experimental data can be used for sub-channel mixing model developments and validations of turbulent models.

Evaluation of Independent Stochastically Perturbed Parameterization Tendency (iSPPT) Scheme on HWRF-Based Ensemble Tropical Cyclone Intensity Forecasts

Abstract Tropical cyclone (TC) intensity has been shown to have limited predictability in numerical weather prediction models; therefore, ensemble forecasting may be critical. An ensemble prediction system (EPS) should ideally cover all sources of uncertainty; however, most meso- and convective-scale EPSs typically consider initial-condition uncertainty alone, with limited treatment of model uncertainty, even though the evolution of mesoscale features is highly dependent on uncertain parameterization schemes. The role of stochastic treatment of model error in the Hurricane Weather Research and Forecasting (HWRF) EPS is evaluated by applying independent stochastically perturbed parameterization (iSPPT) scheme to individual parameterization schemes for four TCs from 2017 to 2018. Experiments with Hurricane Irma (2017) indicate that TC intensity ensemble standard deviation is most sensitive to the amplitude of the stochastic perturbation field, with smaller impact from adjusting the decorrelation time scale and spatial length scale. Results from all four TC cases show that stochastic perturbations to the turbulent mixing scheme can increase the ensemble standard deviation in intensity metrics over a 72-h simulation without introducing significant differences in mean error or bias. By contrast, stochastic perturbations to the microphysics, radiation, and cumulus tendencies have negligible effects on intensity standard deviation.

An improved consistent inflow turbulence generator for LES evaluation of wind effects on buildings

This paper proposes an improved consistent inflow turbulence generator for reproducing spatially correlated turbulence fields with specified wind profiles and spectra for large eddy simulation (LES). The inflow turbulence is developed based on the widely used Random Flow Generation (RFG) technique, and improvements include obtaining more consistent wind spectra, direct control of spatial integral length scales, mitigation of fictitious pressure fluctuations caused by nonsatisfaction of divergence-free conditions, and iteration-based adaption of velocity profiles within the future building area. These improvements are obtained from strictly theoretical derivation, and the correctness of the proposed algorithm is verified by comparing the velocity profiles and the wind spectra of the simulated turbulence atmospheric boundary layer (ABL) with target values. The proposed turbulence generator is adopted to generate inflow turbulence for analyzing wind-induced pressure distributions on isolated low-rise buildings immersed in the turbulent ABL, and the comparison between simulated results and wind tunnel experimental results obtained by Tokyo Polytechnic University (TPU) is presented. Good agreement between the numerical and experimental results verifies the applicability of the proposed generator technique to LES of wind effects on low-rise buildings.

A nonlinear wave-based model to study the magnetic turbulence generation associated with the nonlinear evolution of Kinetic Alfven Wave in laser-produced plasma relevant to laboratory and astrophysical plasmas

A nonlinear wave-based model is introduced to understand the behaviour of the ion-scaled magnetic turbulence in the laser-produced plasmas generated during the high-intensity laser-plasma interaction. The coupled model equations are developed for the pump Kinetic Alfven Wave and the low-frequency Magnetosonic Wave by taking into account the ponderomotive nonlinearity. Numerical simulation is performed using the pseudo-spectral and the finite difference method to solve the model equations. The simulation results illustrate the nonlinear evolution of the pump wave at the early stage, which subsequently becomes turbulent. From the simulation results, the time-averaged turbulent power spectrum has been studied. The observed MHD type and KAW type plasma turbulence in different spatial scale lengths are nearly close to the magnetic turbulence reported in Chatterjee et al.12 experimental results. A semi-analytical method is also given to better understand the nonlinear evolution of the pump wave inside the plasma medium. Such studies of nonlinear wave-based models could be crucial in imitating the astrophysical phenomena by laboratory simulations and understanding the inherent essential physics of magnetic turbulence.

A data science approach for analysis and reconstruction of spinodal-like composition fields in irradiated FeCrAl alloys

A statistical method for the analysis of continuously distributed data representative of composition fluctuations in irradiated FeCrAl alloys acquired using Energy Dispersive X-ray Spectroscopy (EDS) method is presented. Using probability distribution functions, direct and cross-covariances between the elemental compositions, the effects of alloy composition and irradiation dose were investigated on the spatial distribution and length scale of composition fluctuations at the nanoscale. It was observed that, for neutron-irradiated FeCrAl alloys, the distribution of Fe and Cr followed a left-skewed and right-skewed distribution, respectively for all (average) alloy compositions and irradiation doses. The analysis also revealed enhanced spatial gradients in the elemental compositions at higher irradiation dose. Direct and cross-covariance estimates of the experimental data were also utilized for reconstruction of composition data through fitting it to a parametric form of the covariance functions. Linear Model of Coregionalization was used to determine the parameters of the covariance functions. Subsequently, a spectral method was utilized for simulating a realization of the alloy compositions. Close correspondence was observed between the experimental and the reconstructed data which was analyzed using probability distribution functions and covariance functions. Composition space of the experimental and reconstructed data and dislocation velocities as a function of applied stress and line directions over the entire composition maps were also examined.

Multiscale modelling framework for elasticity of ultra high strength concrete using nano/microscale characterization and finite element representative volume element analysis

Ultra-High Strength Concrete (UHSC) (greater than 100 MPa) is a mechanically superior material compared with the Normal Strength Concrete (NSC) due to its inherent performance characteristics. Improved modulus of elasticity is one of the key target characteristics in the development of UHSC. Macroscopic response of UHSC is a result of a multitude of phases in different spatial length scales such as mesoscale, microscale, nanoscale etc. and investigating these spatial scales can yield a better understanding about contribution of each heterogenous phases to the macroscopic behaviour of UHSC. In this paper, a new multiscale modelling method including procedures to obtain micro/nano scale properties is proposed to predict the macroscopic elastic modulus using nanoindentation experiments, hydration simulations, Scanning Electron Microscopy (SEM) and Finite Element Representative Volume Element (FE-RVE) modelling.Characterization of nanomechanical properties of the cementitious composite was carried out using nanoindentation, microstructural characterization was performed using scanning electron microscopy, and hydration simulation of the cementitious paste was carried out using Virtual Cement and Concrete Testing Laboratory (VCCTL) software. A five-level multiscale framework is proposed for UHSC and results from these experimental testing and simulations were used as inputs in the proposed framework.A novel algorithm which can model any volume fraction of different phases was developed to generate geometries for RVEs to be used in FE-RVE simulations. Upscaling of elastic modulus using FE-RVE was found to be very accurate, and this method can generate detailed variation of microfields inside the RVE. A parametric study was carried out on how varying inhomogeneities in the RVE, boundary conditions, and the shape of the inhomogeneities would affect the homogenized elastic modulus.Continuum micromechanics models such as Mori-Tanaka method and Self Consistent Scheme were used for the analytical homogenization at each scale for comparison with FE-RVE method. The results of the proposed FE-RVE analysis, the Mean Field Homogenization (MFH) method, and experiment were compared and found to be a very good fit.

Spatial Correlation Length Scales of Sea-Ice Concentration Errors for High-Concentration Pack Ice

The European Organisation for the Exploitation of Meteorological Satellites-Ocean and Sea Ice Satellite Application Facility–European Space Agency-Climate Change Initiative (EUMETSAT-OSISAF–ESA-CCI) Level-4 sea-ice concentration (SIC) climate data records (CDRs), named SICCI-25km, SICCI-50km and OSI-450, provide gridded SIC error estimates in addition to SIC. These error estimates, called total error henceforth, comprise a random, uncorrelated error contribution from retrieval and sensor noise, aka the algorithm standard error, and a locally-to-regionally correlated contribution from gridding and averaging Level-2 SIC into the Level-4 SIC CDRs, aka the representativity error. However, these CDRs do not yet provide an error covariance matrix. Therefore, correlation scales of these error contributions and the total error in particular are unknown. In addition, larger-scale SIC errors due to, e.g., unaccounted weather influence or mismatch between the actual ice type and the algorithm setup are neither well represented by the total error, nor are their correlation scales known for these CDRs. In this study, I attempt to contribute to filling this knowledge gap by deriving spatial correlation length scales for the total error and the large-scale SIC error for high-concentration pack ice. For every grid cell with >90% SIC, I derive circular one-point correlation maps of 1000 km radius by computing the cross-correlation between the central 31-day time series of the errors and all other 31-day error time series within that circular area (disc) with 1000 km radius. I approximate the observed decrease in the correlation away from the disc’s center with an exponential function that best fits this decrease and thereby obtain the correlation length scale L sought. With this approach, I derive L separately for the total error and the large-scale SIC error for every high-concentration grid cell, and map, present and discuss these for the Arctic and the Southern Ocean for the year 2010 for the above-mentioned products. I find correlation length scales are substantially smaller for the total error, mostly below ~200 km, than the SIC error, ~200 km to ~700 km, in both hemispheres. I observe considerable spatiotemporal variability of the SIC error correlation length scales in both hemispheres and provide first directions to explain these. For SICCI-50km, I present the first evidence of the method’s robustness for other years and time series of L for 2003–2010.

Velocimetry in rapidly rotating convection: Spatial correlations, flow structures and length scales (a) (a)Contribution to the Focus Issue Turbulent Thermal Convection edited by Mahendra Verma and Jörg Schumacher.

Rotating Rayleigh-Bénard convection is an oft-employed model system to evaluate the interplay of buoyant forcing and Coriolis forces due to rotation, an eminently relevant interaction of dynamical effects found in many geophysical and astrophysical flows. These flows display extreme values of the governing parameters: large Rayleigh numbers Ra, quantifying the strength of thermal forcing, and small Ekman numbers E, a parameter inversely proportional to the rotation rate. This leads to the dominant geostrophic balance of forces in the flow between pressure gradient and Coriolis force. The so-called geostrophic regime of rotating convection is difficult to study with laboratory experiments and numerical simulations given the requirements to attain simultaneously large Ra values and small values of E. Here, we use flow measurements using stereoscopic particle image velocimetry in a large-scale rotating convection apparatus in a horizontal plane at mid-height to study the rich flow phenomenology of the geostrophic regime of rotating convection. We quantify the horizontal length scales of the flow using spatial correlations of vertical velocity and vertical vorticity, reproducing features of the convective Taylor columns and plumes flow states both part of the geostrophic regime. Additionally, we find in this horizontal plane an organisation into a quadrupolar vortex at higher Rayleigh numbers starting from the plumes state.

Does mesoscopic elasticity control viscous slowing down in glassforming liquids?

The dramatic slowing down of relaxation dynamics of liquids approaching the glass transition remains a highly debated problem, where the crux of the puzzle resides in the elusive increase in the activation barrier ΔE(T) with decreasing temperature T. A class of theoretical frameworks-known as elastic models-attribute this temperature dependence to the variations of the liquid's macroscopic elasticity, quantified by the high-frequency shear modulus G∞(T). While elastic models find some support in a number of experimental studies, these models do not take into account the spatial structures, length scales, and heterogeneity associated with structural relaxation in supercooled liquids. Here, we propose and test the possibility that viscous slowing down is controlled by a mesoscopic elastic stiffness κ(T), defined as the characteristic stiffness of response fields to local dipole forces in the liquid's underlying inherent structures. First, we show that κ(T)-which is intimately related to the energy and length scales characterizing quasilocalized, nonphononic excitations in glasses-increases more strongly with decreasing T than the macroscopic inherent structure shear modulus G(T) [the glass counterpart of liquids' G∞(T)] in several computer liquids. Second, we show that the simple relation ΔE(T) ∝ κ(T) holds remarkably well for some computer liquids, suggesting a direct connection between the liquid's underlying mesoscopic elasticity and enthalpic energy barriers. On the other hand, we show that for other computer liquids, the above relation fails. Finally, we provide strong evidence that what distinguishes computer liquids in which the ΔE(T) ∝ κ(T) relation holds from those in which it does not is that the latter feature highly fragmented/granular potential energy landscapes, where many sub-basins separated by low activation barriers exist. Under such conditions, it appears that the sub-basins do not properly represent the landscape properties relevant for structural relaxation.