Macro-scale Effects Research Articles

Collagen bundling and alignment in equibiaxially stretched human amnion

We study irreversible collagen arrangement processes in ex-vivo human amnions subjected to inflation tests, which simulate the mechanical conditions prior to and during the initiation of labor uterine contractions. The investigation is focused on the center of the membrane where the stresses are maximal and equibiaxial. Second harmonic generation reveals an unexpected collagen rearrangement in the compact layer that is responsible for the structural integrity of the fetal membrane. The observed bundling and alignment of the collagen fibers indicate a deviation from the expected equibiaxial stress state. The statistical analysis of the fiber orientations provides information on two driving forces for collagen alignment: microscale flaws and macroscale deviation from the equibiaxial strain. As the pressure increases, the macroscale effect becomes dominant, and a high density of fibers that are aligned along a specific direction is observed. A model that explains these observations and relates them to the material properties is presented. The results of this study indicate that a temporal increase in intrauterine pressure or uterine cervix dilatation causes irreversible changes in collagen molecular connections that may lead to biological changes, such as the initiation of term and preterm labor.

Nanoscale and Macroscale Effects of Mineral Deposition During Water Evaporation on Nanoporous Surfaces

Recent studies have indicated that droplet evaporation heat transfer can be substantially enhanced by fabricating a thin nanoporous superhydrophilic layer on a metal substrate. Such surfaces have immense potential to improve spray cooling processes, however, little durability testing of the surface has been performed. In spray cooling applications, as water evaporates any impurities in the water will be deposited onto the surface. Primarily, this investigation serves to demonstrate how minerals in hard water deposit on the surface and interact with the ZnO nanopillars of the superhydrophilic surface. Quantifying the effects of mineral scale on droplet spreading and vaporization heat transfer on the surface is important in determining implementation requirements to advance the surface into industry applications. Micrographs of the surface demonstrate minerals deposit nonuniformly and quickly fill the nanostructure. Despite a reduction in the extent of droplet spreading due to the mineral deposition, scaled surfaces still demonstrated improved thermal performance compared to an uncoated, smooth copper surface. Scale tended to build up on previously deposited scale, leaving largely uncoated areas where droplets chose to preferentially spread and resulting in a continued low contact angle. Maintaining these uncoated areas and reducing the contaminants present in the water will extend the life and performance of the nanostructured surface.

Using Process Based Snow Modeling and Lidar to Predict the Effects of Forest Thinning on the Northern Sierra Nevada Snowpack

Reductions in snow accumulation and melt in headwater basins are increasing the water stress on forest ecosystems across the western US. Forest thinning has the potential to reduce water stress by decreasing sublimation losses from canopy interception; however, it can also increase snowpack exposure to sun and wind. We used the high-resolution (1 m) energy and mass balance Snow Physics and Lidar Mapping (SnowPALM) model to investigate the effect of two virtual forest thinning scenarios on the snowpack of two adjacent watersheds (54 km2 total) in the Lake Tahoe Basin, California, where forest thinning is being planned. SnowPALM realistically represents small-scale snow-forest interactions to simulate the impact of virtual thinning experiments in which trees 3 m2/m2 and 5 to 15-m tall show the largest increases in snow accumulation (up to 450 mm) and melt volume (up to 650 mm). Despite the role of tree- and stand-scale thinning on snowmelt, macroscale effects were limited to slightly larger increases in melt volumes at mid to low elevation slopes (<2,300 masl) and south facing areas per unit of LAI removed. A decision support tool using machine learning (random forest) was developed to synthesize SnowPALM results, and was applied to neighboring watersheds. These results will inform ongoing forest management practices in California, and improve our understanding of the effects of snow-forest interactions at scales relevant to water management.

Experimental and numerical simulation of supercritical CO2 microbubble injection into a brine-saturated porous medium

Microbubbles are one solution to the channeling problem in the displacement process through porous media. However, applications of microbubbles to geological carbon sequestration (GCS) is scarcely reported. In this work, we injected supercritical CO2 (scCO2) into brine-saturated sandstone and mapped the displacement process by medical computed tomography (CT). The injections were performed by two methods: an analog of a regular drainage process and a special injection module incorporating microbubble injection. The microbubble injection increased the scCO2 saturation, which corresponds to the sweep efficiency, by alleviating the channeling effect. We then investigated the microbubble injection in numerical simulations and gained insights into the injection mechanism. Both injection processes were reasonably produced by assigning the sub-core permeability approximation with the porosity−capillary pressure approach (ϕ-Pc). Based on these results, we attributed the macroscale effects of microbubble injection to the lowered entry capillary pressure.

Multiscale proper generalized decomposition based on the partition of unity

SummarySolutions of partial differential equations could exhibit a multiscale behavior. Standard discretization techniques are constraints to mesh up to the finest scale to predict accurately the response of the system. The proposed methodology is based on the standard proper generalized decomposition rationale; thus, the PDE is transformed into a nonlinear system that iterates between microscale and macroscale states, where the time coordinate could be viewed as a 2D time, representing the microtime and macrotime scales. The macroscale effects are taken into account because of an FEM‐based macrodiscretization, whereas the microscale effects are handled with unidimensional parent spaces that are replicated throughout the domain. The proposed methodology can be seen as an alternative route to circumvent prohibitive meshes arising from the necessity of capturing fine‐scale behaviors.

Multiscale Homogenization Analysis of Alkali–Silica Reaction (ASR) Effect in Concrete

Abstract The alkali–silica reaction (ASR) is one of the major long-term deterioration mechanisms occurring in concrete structures subjected to high humidity levels, such as bridges and dams. ASR is a chemical reaction between the silica existing inside the aggregate pieces and the alkali ions from the cement paste. This chemical reaction produces ASR gel, which imbibes additional water, leading to gel swelling. Damage and cracking are subsequently generated in concrete, resulting in degradation of its mechanical properties. In this study, ASR damage in concrete is considered within the lattice discrete particle model (LDPM), a mesoscale mechanical model that simulates concrete at the scale of the coarse aggregate pieces. The authors have already modeled successfully ASR within the LDPM framework and they have calibrated and validated the resulting model, entitled ASR-LDPM, against several experimental data sets. In the present work, a recently developed multiscale homogenization framework is employed to simulate the macroscale effects of ASR, while ASR-LDPM is utilized as the mesoscale model. First, the homogenized behavior of the representative volume element (RVE) of concrete simulated by ASR-LDPM is studied under both tension and compression, and the degradation of effective mechanical properties due to ASR over time is investigated. Next, the developed homogenization framework is utilized to reproduce experimental data reported on the free volumetric expansion of concrete prisms. Finally, the strength degradation of prisms in compression and four-point bending beams is evaluated by both the mesoscale model and the proposed multiscale approach in order to analyze the accuracy and computational efficiency of the latter. In all the numerical analyses, different RVE sizes with different inner particle realizations are considered in order to explore their effects on the homogenized response.

Nano, micro, and macro-scale effects on cochlear tuning

Reconciling the highly tuned and nonlinear basilar membrane (BM) response at the base with the nearly low-pass and weakly nonlinear response at the apex has presented a longstanding challenge to cochlear mechanics modelers. Recent experiments have shown that the BM centric view of cochlear mechanics is incomplete and have highlighted the importance of modeling and measuring the dynamics of the organ of Corti (OoC). Here, we describe a new computational model of the guinea pig cochlea that can correctly simulate the response at all frequencies. The model shows that the electromotile force from the outer hair cells modulate the differential motion between the reticular lamina and the BM. Model calculations at the apex show that the geometric taper of the scalae duct as well as the cytoarchitecture of the OoC breaks the scaling symmetry observed at the base. Further, the model predicts that the neural tuning at the base is primarily governed by the macroscopic dynamics of the cochlear partition, while the micro-scale fluid dynamics and the nano-scale channel dynamics dominate the neural tuning at the apex. Overall, the model provides a physiological explanation for the differences between high and low frequency hearing observed in psychophysical experiments. [Work supported by NIH-R01-04084.]

Prey biomass dynamics in gray whale feeding areas adjacent to northeastern Sakhalin (the Sea of Okhotsk), Russia, 2001–2015

Changing climate patterns strongly influence marine ecosystems across the Pacific Arctic region creating significant ecosystem transitions and change. Macrobenthic species are essential prey for numerous marine mammals and seabirds but the influence of climatic drivers that control macrobenthic community population dynamics are poorly known in critical prey habitats. We investigated associations of environmental, temporal, and climatic covariates with the biomass concentrations of six prey groups (Actinopterygii, Amphipoda, Bivalvia, Cumacea, Isopoda, and Polychaeta) in essential habitats for Korean-Okhotsk (western) gray whales adjacent to northeastern Sakhalin Island in the Sea of Okhotsk. Prey community biomass concentrations were correlated with water depth, year, and climate indices reflecting oceanographic and climatic patterns associated with macro-scale climatological effects. The correlation of prey biomass with water depth and year accounted for ∼90% of total variation in canonical correlation analyses (CCor). Climate indices accounted for ∼10% of total variation in CCor. Water circulation in winter may be particularly important for maintaining populations through the advection of particulate organic carbon entrained in winter currents. Overall, temporal trends in the biomass concentrations of gray whale prey resources appear to reflect climatic and oceanographic factors that are driving ecosystem changes across the Sea of Okhotsk and the Pacific Arctic region.

Macro-scale effects over filtered and residual stresses in gas-solid riser flows

Sub-grid models for filtered and residual stresses are required as closures in filtered two-fluid modeling of gas-solid fluidized flows. An approach for deriving such models consists of filtering over results from highly resolved simulations with microscopic two-fluid modeling, which are mostly performed under suspension like conditions as separation of scales is assumed. This means that no macro-scale effects are accounted for. In this work effects of flow macro-scale are evaluated by practicing conditions from suspensions up to pneumatic transport, under solid concentrations typical of risers, applying highly resolved simulations with microscopic two-fluid modeling in periodic domains. Results show that the domain average gas Reynolds number and the domain average solid volume fraction both considerably affect filtered and residual stresses of both phases. It becomes evident that accurate sub-grid models require macro-scale effects to be accounted for.

Defects of Porous Self-Structured Anodic Alumina Oxide on Industrial Aluminum Grades

In this paper, an experimental examination of defects in anodization of aluminum of the industrial grade A7E is presented. A two-step method of anodizing was used in an electrolyte containing 20% wt. % sulfuric acid at 0 ° C at constant voltage. Micro-video recording was carried out in both anodizing stages to examine anodizing process on a micrometer scale, and to determine the corresponding macro-scale effects indicating incorrect anodization process. Macro-scale effects in the form of gas evolution were detected. Subsequently confirmed on the surface of the coating from which it occurred, using scanning electron microscopy. Methods for preparing samples subject to anodization are proposed to reduce the number of defects. The results should lead to industrial implementation of inexpensive and high-quality nanoporous anode materials with a variety of applications.

Theory for acoustic streaming in soft porous matter and its applications to ultrasound-enhanced convective delivery

This paper develops theory for bulk acoustic streaming in soft porous materials, with applications to biological tissue. The principal results of this paper are: (i) streaming equations for such porous media, which show interestingly significant differences from those that describe streaming in pure fluids; (ii) the Green functions obtained for these equations in isotropic, infinite media; and (iii) approximate evaluation of the sources in the streaming equations from acoustic wave forms often used, and the streaming velocities and particle trajectories resulting therefrom. People are now investigating acoustic enhancement of delivery of therapeutics such as drug molecules or other particulates, introduced directly into cellular tissue. A comparison of the predictions of the theory in this paper to available data is made and shown to be surprisingly good. Some macroscale effects of the ultrastructure of the tissue that are not contained in the current paper are pointed out for future studies.

On the effects of the flow macro-scale over meso-scale filtered parameters in gas-solid riser flows

Filtered two-fluid formulations of gas–solid fluidized flows require closure models to deal with sub-grid filtered parameters, which have been derived from filtering over results of meso-scale highly resolved simulations with two-fluid modeling. Trusting on scale separation, the correlation of filtered parameters has been performed to meso-scale filtered data only, disregarding any macro-scale effects. In this work, the correctness of such practice is tested, and it fails. Two macro-scale parameters associated to flow topology, namely the average solid volume fraction and the average gas Reynolds number, are both considered as for their effects over relevant filtered parameters. This is done by filtering over results of highly resolved simulations, where the concerning macro-scale parameters are held constant at various levels. The current interest is directed towards dilute conditions typical of riser flows. Results show that both the concerning macro-scale parameters should be accounted for in sub-grid correlation if higher accuracy is pursued.

The Agricultural Water Rebound Effect in China

Although the water productivity of the agricultural sector in China continuously increased over the last twenty years, by improvements in irrigation technology, the total agricultural water use did not decline as expected, mainly due to continuous increases in agricultural output partially derived from technological progress. Thus, agricultural water use in China may experience a rebound effect. This study defines the water rebound effect (WRE) using macro-scale indicators of water use and water productivity, establishes a simplified direct comparison method using the contribution rate of technological progress, and evaluates the magnitude of the macro-scale water rebound effect in the Chinese agricultural sector using provincial panel data from 1997 to 2014. The magnitude of the agricultural WRE in China (1998–2014) is 61.49%. The northern and western regions of China experience a greater WRE than the southern and eastern regions, and the changes in the inter-annual WRE are distinct. These observations indicate that much of the expected water savings from efficiency improvement could be offset by increased water use for increased agricultural production due to technology enhancement. The control of water use growth is effective for reducing the water rebound effect. The study confirmed the existence of the agricultural WRE in China.

Simulation of droplet impact onto a deep pool for large Froude numbers in different open-source codes

A droplet impact on a deep pool can induce macro-scale or micro-scale effects like a crown splash, a high-speed jet, formation of secondary droplets or thin liquid films, etc. It depends on the diameter and velocity of the droplet, liquid properties, effects of external forces and other factors that a ratio of dimensionless criteria can account for. In the present research, we considered the droplet and the pool consist of the same viscous incompressible liquid. We took surface tension into account but neglected gravity forces. We used two open-source codes (OpenFOAM and Gerris) for our computations. We review the possibility of using these codes for simulation of processes in free-surface flows that may take place after a droplet impact on the pool. Both codes simulated several modes of droplet impact. We estimated the effect of liquid properties with respect to the Reynolds number and Weber number. Numerical simulation enabled us to find boundaries between different modes of droplet impact on a deep pool and to plot corresponding mode maps. The ratio of liquid density to that of the surrounding gas induces several changes in mode maps. Increasing this density ratio suppresses the crown splash.

Photo-thermal study of a layer of randomly distributed gold nanoparticles: from nano-localization to macro-scale effects

We present an experimental characterization and a comprehensive theoretical modeling of macroscopic plasmonic heat production that takes place in a single layer of small gold nanoparticles (GNPs), randomly distributed on a glass substrate, covered with different host media and acted on by a resonant radiation. We have performed a detailed experimental study of the temperature variations of three different systems, obtained by varying the density of nanoparticles. Due to the macroscopic dimension of the spot size, the used laser irradiates a huge number of nanoparticles, inducing a broad thermo-plasmonic effect that modifies the thermal conductivity of the entire system; starting from the state of art, we have implemented a simple model that enables to evaluate the resulting new thermal conductivity. We have also extended our theoretical approach to the macroscale, including an analysis of the effects predicted for different NP densities and laser spot size values, as well as for different values of the laser intensity, which can be as low as 0.05 W . Theoretically predicted temperature variations are in excellent agreement with experimental results.

A multi-scale approach for the analysis of the mechanical effects of salt crystallisation in porous media

In this paper, a multi-scale approach for the analysis of mechanical effects induced by salt crystallisation in porous media is presented. The approach is based on numerical homogenisation and allows to predict the effects of salt crystallisation occurring at the scale of the structure, based on the real 3D micro geometry of the porous material coming from X-ray Micro Computed Tomography images. The micro-mechanical model is obtained by automatically converting the images into a finite element mesh. The macro-scale distribution of the crystallized salt is assumed as an input datum coming from Hygro Thermal Chemical models available in the literature. Then, some hypotheses on the loading condition of the micro-mechanical model, accounting for different crystallisation physics, are introduced and their effects in terms of mechanical response at the macro-scale are compared. As case study, the proposed approach is applied to the Prague sandstone. Results show that the macro-scale mechanical effects are influenced by the loading scheme and that some approaches commonly used in the literature for their evaluation can lead to their underestimation. The proposed approach can be incorporated in a structural computation with environmental-mechanical loadings to forecast the most probable damage scenarios.

Lattice Boltzmann Simulations of Macro/Microscale Effects on Saturated Pool Boiling Curves for Heated Horizontal Surfaces

Results of lattice Boltzmann (LB) simulations of macroscale effects (heating modes, heater size, and saturation temperature) as well as microscale effects (wettability and roughness) on saturated pool boiling from superheated horizontal surfaces are summarized in this paper. These effects on pool boiling curves from natural convection through nucleate boiling to critical heat flux (CHF) and from transition boiling to film boiling are illustrated. It is found that macroscale effects have negligible influence on nucleate boiling heat transfer, and Rohsenow's correlation equation fits well with the simulated nucleate boiling heat transfer on smooth hydrophilic and hydrophobic horizontal surfaces. Both macroscale and microscale effects have important influence on critical heat flux and transition boiling heat transfer.

Soil erosion assessment—Mind the gap

AbstractAccurate assessment of erosion rates remains an elusive problem because soil loss is strongly nonunique with respect to the main drivers. In addressing the mechanistic causes of erosion responses, we discriminate between macroscale effects of external factors—long studied and referred to as “geomorphic external variability”, and microscale effects, introduced as “geomorphic internal variability.” The latter source of erosion variations represents the knowledge gap, an overlooked but vital element of geomorphic response, significantly impacting the low predictability skill of deterministic models at field‐catchment scales. This is corroborated with experiments using a comprehensive physical model that dynamically updates the soil mass and particle composition. As complete knowledge of microscale conditions for arbitrary location and time is infeasible, we propose that new predictive frameworks of soil erosion should embed stochastic components in deterministic assessments of external and internal types of geomorphic variability.

Direct Numerical Simulations in Solid Mechanics for Quantifying the Macroscale Effects of Microstructure and Material Model-Form Error

Two fundamental approximations in macroscale solid-mechanics modeling are (1) the assumption of scale separation in homogenization theory and (2) the use of a macroscopic plasticity material model that represents, in a mean sense, the multitude of inelastic processes occurring at the microscale. With the goal of quantifying the errors induced by these approximations on engineering quantities of interest, we perform a set of direct numerical simulations (DNS) in which polycrystalline microstructures are embedded throughout a macroscale structure. The largest simulations model over 50,000 grains. The microstructure is idealized using a randomly close-packed Voronoi tessellation in which each polyhedral Voronoi cell represents a grain. An face centered cubic crystal-plasticity model is used to model the mechanical response of each grain. The overall grain structure is equiaxed, and each grain is randomly oriented with no overall texture. The detailed results from the DNS simulations are compared to results obtained from conventional macroscale simulations that use homogeneous isotropic plasticity models. The macroscale plasticity models are calibrated using a representative volume element of the idealized microstructure. Ultimately, we envision that DNS modeling will be used to gain new insights into the mechanics of material deformation and failure.

Attention Modulates Spatial Precision in Multiple-Object Tracking.

We present a computational model of multiple-object tracking that makes trial-level predictions about the allocation of visual attention and the effect of this allocation on observers' ability to track multiple objects simultaneously. This model follows the intuition that increased attention to a location increases the spatial resolution of its internal representation. Using a combination of empirical and computational experiments, we demonstrate the existence of a tight coupling between cognitive and perceptual resources in this task: Low-level tracking of objects generates bottom-up predictions of error likelihood, and high-level attention allocation selectively reduces error probabilities in attended locations while increasing it at non-attended locations. Whereas earlier models of multiple-object tracking have predicted the big picture relationship between stimulus complexity and response accuracy, our approach makes accurate predictions of both the macro-scale effect of target number and velocity on tracking difficulty and micro-scale variations in difficulty across individual trials and targets arising from the idiosyncratic within-trial interactions of targets and distractors.