Bare Regions Research Articles

Exploration of improved, roller-based spreading strategies for cohesive powders in additive manufacturing via coupled DEM-FEM simulations

Spreading of fine (D50 ≤20μm) powders into thin layers, such as required by layer-wise additive manufacturing (AM) processes, typically requires a mechanism such as a roller that provides adequate shear and compression to overcome the cohesive forces between particles. We explore improved, roller-based spreading strategies for highly cohesive powders using an integrated discrete element-finite element (DEM-FEM) framework. We find that optimal roller-based spreading, quantified by maximum packing density and uniformity of layer thickness, relies on a combination of surface friction of the roller and roller kinematics, e.g., counter-rotation or angular oscillation, that impart sufficient kinetic energy to break cohesive bonds between powder particles. However, excess rotation speed (or shear stress) can impart excessive kinetic energy to the powder causing ejection of particles and a non-uniform layer, suggesting the existence of a process window of optimal spreading parameters. Interestingly, the identified optimal parameters for both investigated roller kinematics, i.e., angular velocity for counter-rotation as well as angular frequency and amplitude for rotational oscillation, result in a very similar range of roller surface velocities, suggesting roller surface velocity as the critical kinematic parameter. When these conditions are chosen appropriately, layers with packing fractions beyond 50% are predicted for layer thicknesses as small as ∼2 times D90 of the exemplary cohesive powder, and the layer quality is robust with respect to substrate adhesion over a 10-fold range. The latter is an important consideration given the spatially varying substrate conditions in AM due to the combination of fused/bound and bare powder regions. As compared to counter-rotation, the proposed rotational oscillation kinematics are particularly attractive because they can overcome practical issues with mechanical runout of roller mechanisms (which limit their precision).

An encoder–decoder network for land cover classification using a fusion of aerial images and photogrammetric point clouds

Land cover information is becoming more important in urban planning, change detection, and management. The fusion of point clouds and images increases the accuracy of land use classification by utilising the advantages of both modalities. Similar structures such as buildings and roads, low and high vegetation, and impervious and bare regions are not too much discriminative. Models fail to discriminate these classes leading to misclassifications, false detections, and unreliable land cover maps. Therefore, this research proposes the fusion of dense point clouds and multi-spectral images based on a dual-stream deep convolutional model by adding vegetation and elevation information to spectral information. To fuse both modalities' features, a dual-stream deep neural network based on Deeplabv3+ architecture is implemented. In addition, the Xception (Extreme Inception) model is considered as a backbone and feature extractor. The model performance is evaluated with F1-Score and Overall Accuracy. 93.4% Overall Accuracy and F1-Score are achieved after adding height and vegetation information to the model. Results indicate improvements in all indexes, meaning that data fusion with the proposed model outperforms the existing state-of-the-art models.

Assessing the occurrence of soil improvement and its relationship to the dominant life form in the high mountains of Central Spain

Soil in mountainous regions is vital to the health and preservation of these unique and diverse ecosystems. In dry and semi-arid regions, vegetation patches play a crucial role in soil nutrient heterogeneity through continuous feedback with soils, acting as barriers to collect runoff water, sediments, and nutrients from bare soil regions. Soil amelioration, an enhancement of soil biogeochemical processes, results in the formation of “fertility islands,” the extent of which is contingent on the plant species in question, as well as nutrient dynamics and water availability. Here, we collected soil from across a two-peak altitudinal gradient in the Sierra de Guadarrama high-mountains, each peak featuring a different dominant vegetation type (herbs vs. cushion-like) to compare soil nutrients and properties between bare soil and vegetation-covered patches (microhabitats). Soil improvement was assessed in the microhabitats using the Relative Interaction Index (RII). Fertility islands were shown to be prevalent in high-mountain ecosystems, as soil quality and properties were higher beneath vegetation-covered regions than bare soils. There was a difference in RIIs between the transects, with greater soil improvement in the cushion-dominated transect than the herb-dominated one. Changes in nutrient levels were unrelated to patch successional stage, indicaing that plant generations may not shape the spatial variability of soil attributes. Instead, species variety or the presence of dominant clonal species increased soil nutrients and aggregate stability, highlighting the importance of root shape and high biomass in nutrient retention and soil reinforcement. Finally, our findings imply that the poor, shallow soils in the examined peaks, in comparison to other mountains, may account for the poor facilitative interactions. Competition for the scarce resources at these peaks may intensify as climate warms. Thus, while these plants may grow with minimum assistance under current climate circumstances, their associations may be especially vulnerable to climate change.

A New Method for Bare Permafrost Extraction on the Tibetan Plateau by Integrating Machine Learning and Multi-Source Information

Bare permafrost refers to permafrost with almost no vegetation on the surface, which is an essential part of the ecosystem of the Tibetan Plateau. An accurate extraction of the boundaries of bare permafrost is vital for studying how it is being impacted by climate change. The accuracy of permafrost and bare land distribution maps is inadequate, and the spatial and temporal resolution is low. This is due to the challenges associated with obtaining significant amounts of data in high-altitude and alpine regions and the limitations of current mapping techniques in effectively integrating multiple factors. This study introduces a novel approach to extracting information about the distribution of bare permafrost. The approach introduced here involves amalgamating a sample extraction method, the fusion of multi-source remote sensing information, and a hierarchical classification strategy. Initially, the available multi-source permafrost data, expert knowledge, and refinement rules for training samples are integrated to produce extensive and consistent permafrost training samples. Using the random forest method, these samples are then utilized to create features and classify permafrost. Subsequently, a methodology utilizing a hierarchical classification approach in conjunction with machine learning techniques is implemented to identify an appropriate threshold for fractional vegetation cover, thereby facilitating the extraction of bare land. The bare permafrost boundary is ultimately derived through layer overlay analysis. The permafrost classification exhibits an overall accuracy of 90.79% and a Kappa coefficient of 0.806. The overall accuracies of the two stratified extractions in bare land were 97.47% and 96.99%, with Kappa coefficients of 0.954 and 0.911. The proposed approach exhibits superiority over the extant bare land and permafrost distribution maps. It is well-suited for retrieving vast bare permafrost regions and is valuable for acquiring bare permafrost distribution data across a vast expanse. It offers technical assistance in acquiring extended-term data on the distribution of exposed permafrost on the Tibetan Plateau. Furthermore, it facilitates the elucidation of the impact of climate change on exposed permafrost.

Vegetation Cover Change Analysis during 1989-2020 of Coastal Barguna District, Bangladesh Using Remote Sensing and GIS Technology

This paper represents an advanced assessment of a satellite imagery-based vegetation transition detection method for Bangladesh's southern district of Barguna. Bangladesh has been identified as the most vulnerable country to the effects of climate change due to deteriorating vegetative cover and urbanization pushing forces. This paper aims to use GIS and remote sensing techniques to estimate vegetation change and determine the conversion pattern in the coastal district of Barguna, Bangladesh, from 1989 to 2020. The major methodology used in this research is NDVI differencing and supervised image classification to validate the conversion over time. With a combination of satellite imagery bands, NDVI uses multi-spectral remote sensing techniques to discover vegetation index, water, empty spaces, and forests. To categorize the canopy into distinct kinds, we use NDVI threshold values of 0, 0.1, 0.15, and 0.2. Our findings reveal significant geographical variations in bare regions, sparse, moderate, and thick vegetation types. We discovered that over the last 31 years, a total of 412.90 km2 (49.25 percent) of land has been deforested, with the transition rate being particularly high in dense vegetation. This research of vegetation cover change can help predict the recurrence of natural disasters, give humanitarian assistance, and enable innovative protection tactics.

Quantifying wind-induced undercatch in the precipitation measurements at Ukrainian weather stations

Literature overview. Precipitation measurements include random and systematic errors. Systematic errors increase in the following order: evaporation loss, wetting loss, and wind-induced undercatch (World Meteorological Organization, 2008). The last one occurs because of the aerodynamic blockage under the precipitation gauge collector (Baghapour et al. 2017; Sevruk & Nespor, 1994). Field experiments have shown that wind-induced undercatch reaches 14% for rain and 40% for snow for the Tretyakov wind-shielded gauge (Goodison et al., 1998). In Ukraine, precipitation records omit wind-induced undercatch correction. This study aims to calculate true precipitation values at Ukrainian weather stations, evaluate existing methodologies for precipitation measurements correction, and create the digital archive of corrected precipitation values based on sub-daily observations. Material and methods. We used four methods to quantify wind-related errors for the Tretyakov gauge with wind shield proposed by Golubev (Konovalov et al., 2000), Bryazgin (Aleksandrov et al., 2005), Norway meteorological institute (Forland et al., 1996), and Yang (Yang et al., 1995). Sub-daily records were requested from Central Geophysical Observatory named after Boris Sreznevsky covering 207 stations between 1976 and 2019; 187 stations had more than 20 years’ period. Results. For the Tretyakov gauge, annual wind-induced undercatch ranges from 5 to 9.5%, depending on correction methodology. The highest bias is observed for the solid precipitation – from 17.7 to 27.4%. The precipitation loss increases along with annual wind speed at the weather station (correlation coefficient r = 0.89). Conclusions. We suggest that Golubev’s and Yang’s methodologies estimate precipitation wind-induced undercatch more accurately at stations where blizzards are often observed, we recommended using the Golubev’s methodology because it takes into account “false” precipitations. The precipitation loss equals 0.2–4% according to the Golubev’s method at covered weather stations and reaches 13–19% at the bare mountain regions or seashore. Solid precipitation is more sensitive to the influence of wind – snow loss averages 17.3% according to the Golubev methodology or 21% according to the Yang methodology, while rain loss – 2.6% or 6.7%, respectively. The obtained database with corrected precipitation comprises sub-daily and daily records from 207 Ukrainian stations between 1976 and 2019. It could be used for hydrological and climatological research.

The stability of Cl-, Br-, and I-passivated Si(100)-(2 × 1) in ambient environments for atomically-precise pattern preservation

Atomic precision advanced manufacturing (APAM) leverages the highly reactive nature of Si dangling bonds relative to H- or Cl-passivated Si to selectively adsorb precursor molecules into lithographically defined areas with sub-nanometer resolution. Due to the high reactivity of dangling bonds, this process is confined to ultra-high vacuum (UHV) environments, which currently limits its commercialization and broad-based appeal. In this work, we explore the use of halogen adatoms to preserve APAM-derived lithographic patterns outside of UHV to enable facile transfer into real-world commercial processes. Specifically, we examine the stability of H-, Cl-, Br-, and I-passivated Si(100) in inert N2 and ambient environments. Characterization with scanning tunneling microscopy and x-ray photoelectron spectroscopy (XPS) confirmed that each of the fully passivated surfaces were resistant to oxidation in 1 atm of N2 for up to 44 h. Varying levels of surface degradation and contamination were observed upon exposure to the laboratory ambient environment. Characterization by ex situ XPS after ambient exposures ranging from 15 min to 8 h indicated the Br– and I–passivated Si surfaces were highly resistant to degradation, while Cl–passivated Si showed signs of oxidation within minutes of ambient exposure. As a proof-of-principle demonstration of pattern preservation, a H–passivated Si sample patterned and passivated with independent Cl, Br, I, and bare Si regions was shown to maintain its integrity in all but the bare Si region post-exposure to an N2 environment. The successful demonstration of the preservation of APAM patterns outside of UHV environments opens new possibilities for transporting atomically-precise devices outside of UHV for integrating with non-UHV processes, such as other chemistries and commercial semiconductor device processes.

The Wet-Oxidation of a Cu(111) Foil Coated by Single Crystal Graphene.

The wet-oxidation of a single crystal Cu(111) foil is studied by growing single crystal graphene islands on it followed by soaking it in water. 18 O-labeled water is also used; the oxygen atoms in the formed copper oxides in both the bare and graphene-coated Cu regions come from water. The oxidation of the graphene-coated Cu regions is enabled by water diffusing from the edges of graphene along the bunched Cu steps, and along some graphene ripples where such are present. This interfacial diffusion of water can occur because of the separation between the graphene and the "step corner" of bunched Cu steps. Density functional theory simulations suggest that adsorption of water in this gap is thermodynamically stable; the "step-induced-diffusion model" also applies to graphene-coated Cu surfaces of various other crystal orientations. Since bunched Cu steps and graphene ripples are diffusion pathways for water, ripple-free graphene is prepared on ultrasmooth Cu(111) surfaces and it is found that the graphene completely shields the underlying Cu from wet-oxidation. This study greatly deepens the understanding of how a graphene-coated copper surface is oxidized, and shows that graphene completely prevents the oxidation when that surface is ultrasmooth and when the graphene has no ripples or wrinkles.

Assessing urban sprawl by remote sensing and GIS techniques

In the context of mega sustainable urban development projects, this research was commenced with the impartial of assessing urban sprawl (i.e., land use versus land cover variations) during 2000-2016 by remote sensing and GIS techniques, where GCR “Greater Cairo Region” was taken as a case study. Primarily, literature in the field of remote sensing and GIS technologies were assembled and scrutinized. In addition, data regarding build zones, agricultural areas and bare soil regions so as water were assembled from different resources (i.e., Ministry of Agriculture). Remote sensing and GIS techniques were implemented. Results were obtained and analyzed. Finally, conclusions were deduced and recommendations were suggested. The research flagged-out that the GCR designated a drastic agriculture land loss of 10%. In addition, the research confirmed that built-up areas increased by 10% during 2000-2016. On the other hand, the results indicated that Giza and Qalyubia Governorates recorded the largest agriculture land loss by 8.72 and 7.88%, respectively, which is equivalent to 47 and 77 km2, respectively. The research prioritized the importance of defining the most affected zones within Giza and Qalyubia Governorates by correlating GIS data versus governmental files, where a difference of 50% was designated. The research portrayed the priority of modifying the government assessment approach in order to control urban sprawl.

Customized piezoresistive microprobes for combined imaging of topography and mechanical properties

Customized piezoresistive cantilever microprobes with a deflection range of 120 ​μm and silicon tips of 100 ​μm height were operated in a Cypher AFM showing their functionality for measuring topography together with viscoelastic properties of thin films. For drop-in mounting in the AFM a holder was developed comprising the piezoresistive microprobe and its voltage-supply and signal-conditioning electronics. With the probe tip in contact to a glass sample we found a vertical resolution of 2.8 ​nm in a bandwidth of 1 ​kHz, which is close to the theoretical limit of 3.0 ​nm ​at a deflection of 2.5 ​μm. This resolution could be verified in topographic images of a scratch of approximately 300 ​nm in depth. Force-volume images with lithographically patterned photoresist (AZ 5214E) of approximately 300 ​nm thickness on silicon revealed contrast of the resist-covered and bare regions in topography, stiffness and adhesion. With contact-resonance imaging using the Dual AC Resonance Tracking (DART) method, patterned AZ 5214E photoresist of approximately 50 ​nm thickness could be distinguished from the bare silicon in topography, contact stiffness (indicated by contact resonance frequency shift) and adhesion (indicated by phase shift). Finally, a droplet of lubricant (Lupranol VP 9209) on glass could be detected by force volume imaging revealing a thickness of approximately 90 ​nm of the liquid layer with a sharp lateral limitation, which was clearly detected. We conclude that the piezoresistive silicon microprobe is a promising tool for emerging tasks of industrial surface metrology on manufacturing machines, including micro-finish of work pieces and elasticity, thickness, adhesion, etc. of thin solid or liquid deposits on top.

The role of metal powder properties on the tribology of cold sprayed Ti6Al4V-TiC metal matrix composites

Ti6Al4V-TiC metal matrix composite (MMC) coatings were cold sprayed using spherical and irregular Ti6Al4V powders manufactured with plasma gas atomization and the Armstrong process, respectively. Composite coatings deposited using irregular powders showed higher ceramic retentions and lower porosity compared to spherical powder (SP) coatings. Sliding wear tests were performed at two different normal loads using a spherical WC-Co ball as counterface. Wear test results showed that at similar ceramic contents, spherical powder composites exhibited abrasive wear mechanisms with high coefficients of friction (CoF) and wear rates. In irregular powder (IP) composites, islands of tribolayers, comprised of fragmented TiC and TiO2 particles, resisted the localized shear deformation leading to low wear, and with free carbon from the TiC particles also lowered the CoF. Increase in ceramic content in the IP MMCs to 23% led to higher coverage of wear track area with tribolayers and further lowered the wear rate. At higher load, 23% TiC composite coatings showed a more continuous tribolayer, whereas lower ceramic content MMCs showed no significant formation of tribolayers. The formation of a highly continuous tribolayer at higher load (in 23% TiC MMC), led to extremely low CoF (~ 0.25) compared to other coatings along with low wear rate. Electron channel contrast imaging and transmission electron microscopy analysis of the worn subsurface under the tribolayers showed coarse-grain microstructures compared to the bare regions of the wear track (i.e. without tribolayer coverage). The formation of coarser grain microstructures indicated less stress transfer to the subsurface both due to the high hardness and lubricating nature of the tribolayers.

Soil arthropods indicate the range of plant facilitation on the soil of Mediterranean drylands

Drylands are ecosystems, where lack of rains imposes harsh conditions for the survival of organisms. These ecosystems are also susceptible to degradation and desertification. Their conservation depends on the understanding of the ecological functioning of vegetation and soil. In drylands, the vegetation is spatially structured as a mosaic of patches (vegetation) and interpatches (bare soil). This structure is a consequence of plant-plant interactions (facilitation and competition). Empirical data and modeling approaches reinforce the role of ecological facilitation for the maintenance of all organisms in drylands. However, the true range of facilitation is still poorly known. Here, we explored data of meso- and microarthropods living in soil, as bioindicators, to infer the range of facilitation provided by plants to soil. As dependent variables, we regard data of abundances and species richness collected in random patches (independent samples) and bare soil places. Data from patch size and distances between bare soil and patches were arranged in a single chute. Thus, one may consider a one-dimensional coordinate system, where zero is the border; negative coordinates are distances between bare soil and the border, while positive coordinates represent patch sizes. Discrete portions of this system are taken to calculate averages and variances of abundance and species richness. With these statistics, we investigate how soil communities vary across the patch border. Techniques of data transformation and signal analysis allowed us to reduce the data noise, reveal a continuous mean behavior, and fit a logistic function. Our findings indicate that soil communities change suddenly from simple patterns to numerous and diverse communities in bare soil regions. This abrupt change of fauna quantities, around 0.35 and 0.5 m outside the patch border, means that the facilitation of vegetation on soil goes beyond the patch border. However, the abundance and richness of soil communities in bare soil are small in comparison to overall quantities of soil arthropods. Consequently, variations in quantities of arthropods on bare soil do not necessarily reflect the main role of these soil arthropods for soil functions, which mainly occurs under the patches. Also, we found a minimum patch size (radius ≈ 0.5 m) able to maintain high diverse communities in soil. Accordingly, our results reveal information that can be interpreted in terms of soil amelioration, and, therefore, it indicates the range of plant facilitation, and the minimum patch size able to produce soil amelioration. These findings provide objective values that can be employed to update the general understanding of the ecological dynamics of drylands,as well as to better plan restoration and conservation actions.

Hydrodynamics and sediment deposition in turbidity currents: Comparing continuous and patchy vegetation canopies, and the effects of water depth

A flume experiment was carried out to improve understanding of interactions between turbidity currents and aquatic vegetation canopies and their landscape-scale consequences. It focussed on comparing hydrodynamics and sediment deposition in continuous canopies with those in vegetation patches, and on the effects of varying water depth – both of which are previously unreported. The currents’ particulate load was characterised as a mix of fine and coarse fractions. Varying canopy frontal densities, a, and water depths, H, were used. Fifteen runs were carried out with the flume fully vegetated, and a further ten with shorter vegetation patches. In all runs, the currents evolved as expected through inertial, drag-dominated and viscous regimes. The positions at which transitions between the regimes occurred were measured and analysed. In the fully-vegetated runs, both transition positions varied linearly with aH for aH < 0.8, and were constant when aH > 0.8. We argue that the variation at lower values of aH is caused by non-canopy drag forces becoming non-negligible compared to the canopy drag. An equation is derived that models, as a function of a and H, the size a vegetation patch needs to be for its effect on turbidity currents to be the same as that of a continuous canopy. The sediment depositional flux rate for fine particles from the currents within the vegetation was greater than that for coarse particles, by a factor of 1.57. This suggests that bed sediment deposited within canopy patches by turbidity currents will be on average finer than that in gaps between patches, as has been found previously for currents and waves. Thus, this effect will contribute to the development of inter-tidal and shallow sub-tidal landscapes characterized by patches of dense vegetation and fine sediments, surrounded by bare regions with coarser sediments. Our results imply that the distances over which the phenomena we document occur in typical inter-tidal and shallow sub-tidal contexts are of the same order of magnitude as sizes of patches of saltmarsh plants and seagrasses. This indicates that the reported patch length effects are highly relevant to understanding eco-hydrological interactions in these contexts.

Lithology, topography, and spatial variability of vegetation moderate fluvial erosion in the south-central Andes

Understanding how tectonics, climate and lithology interact to control fluvial erosion is complicated because these factors are spatially-variable and they may not be well-represented by mean values. We address these complications using eight new and 54 published 10Be catchment-wide fluvial erosion rates from the south-central Andes. We assess how tectonics, climate, lithology, and topography control erosion through bivariate and multivariate Bayesian regression analysis. We first compare catchment-wide mean values of independent variables compared to other summary statistics and find that metrics that capture extreme values (e.g., 90th percentile) and spatial variability (e.g., 90th minus 10th percentile) produce stronger correlations. This suggests that catchment-wide means may oversimplify the roles of tectonics, climate, and lithology in influencing erosion rates. We find that the overall variability of erosion rates in the south-central Andes is best explained by a combination of lithologic resistance and spatial variability in both vegetation (using the normalized difference vegetation index, NDVI) and topography (using specific stream power). Despite poor bivariate correlations, both lithologic resistance and spatial variability of specific stream power are significant regressors in our multivariate modeling. Lithology influences the relationship (i.e., linearity) between topography and erosion rates. Spatial variability of NDVI produces the strongest correlation with erosion rates of any of the variables we consider. Hence, spatial variability of NDVI both accounts for potential non-uniform vegetation responses to climate and also incorporates the role of both humid climates (high 90th percentile) and large bare regions (low 10th percentile) within a single catchment.

The Effect of Melt Pond Geometry on the Distribution of Solar Energy Under First‐Year Sea Ice

AbstractSea ice plays a critical role in the climate system through its albedo, which constrains light transmission into the upper ocean. In spring and summer, light transmission through sea ice is influenced by its iconic blue melt ponds, which significantly reduce surface albedo. We show that the geometry of surface melt ponds plays an important role in the partitioning of instantaneous solar radiation under sea ice by modeling the three‐dimensional light field under ponded sea ice. We find that aggregate properties of the instantaneous sub‐ice light field, such as the enhancement of available solar energy under bare ice regions, can be described using a new parameter closely related to pond fractal geometry. We then explore the influence of pond geometry on the ecological and thermodynamic sea ice processes that depend on solar radiation.

Evaluating soil nitrate dynamics in an intercropping dripped ecosystem using HYDRUS-2D

The competition mechanisms between crop species for water and nutrients, especially nitrate (NO3-N), in intercropping ecosystems are still poorly understood. Therefore, an experiment involving high (300 kg ha−1 for corn and 250 kg ha−1 for tomato), medium (210 kg ha−1 for corn and 175 kg ha−1 for tomato), and low (150 kg ha−1 for corn and 125 kg ha−1 for tomato) N-fertilizer applications (HF, MF, LF, respectively) was conducted in the corn and tomato intercropping ecosystem during 2014 (a calibration period for modeling) and 2015 (a validation period for modeling). The modified HYDRUS-2D code was used to analyze soil NO3-N concentrations (SNC) in the middle between corn rows (Pc), between corn and tomato rows (Pb), and between tomato rows (Pt), NO3-N exchange in the horizontal direction between different regions, NO3-N leaching from the corn, the bare, and the tomato region, and N uptake by crops. Simulated SNCs were in good agreement with measurements, with RMSE, NSE, and MRE of 0.01–0.06 mg cm−3, 0.75–0.98, and 8.7–19.1%, respectively, during the validation period (2015). Average SNCs in the 0–40 cm soil layer were different between Pc, Pt, and Pb. Intensive NO3-N exchange in the horizontal direction occurred during the second stage (Day After Sowing [DAS] 37-113 in 2014; DAS 29-120 in 2015). NO3-N exchange between the corn and bare regions was lower than between the tomato and bare regions due to smaller concentration gradients. However, in the vertical direction, NO3-N leaching from the corn region in both years was 4.1 and 8.8 times larger, respectively, than from the tomato region under HF since NO3-N mainly moved from the tomato region to the corn region. Our results reveal the competition between corn and tomato for N and provide a rationale for formulating and optimizing different fertilizer regimes for different crops in the intercropping ecosystem.

Enhancement of pool boiling heat transfer using 3D-printed polymer fixtures

Surface modification is a key technique which significantly enhances pool boiling heat transfer rates. There are several methods and manufacturing technologies that are used to alter surface morphologies, such as machining, surface coating, metal powder sintering, photolithography, and chemical processing, which create varied topologies at various length scales. However, some of these techniques are expensive, difficult to manufacture, limited to simple structures, or degrade over time.In the present study, additive manufacturing (AM) is utilized to produce low-cost, porous polymer fixtures that are designed to alter bubble dynamics and improve the pool boiling heat transfer characteristics from flat copper surfaces. The fixtures examined here consist of a uniform pattern of square cells. An open-source fused filament fabrication 3D printer was used to manufacture the fixtures from PLA, and they were attached mechanically to the boiling surface. The wickability of the printed porous samples was investigated using the rate-of-rise method, which showed that printing build orientation can affect their capillary pressure. The boiling experiments were performed under saturated conditions using deionized water as the working fluid at a pressure of 1 atm.Using fixtures with a small unit cell size, we were able to control the nucleation locations and increase the boiling heat transfer coefficient at low heat fluxes by approximately 80%. However, this did not have a significant effect on critical heat flux (CHF). This was attributed to the presence of a low-conductivity structure covering part of the boiling surface which caused the heat to preferentially flow to the bare regions of the surface and initiated nucleation earlier, even at low heat fluxes. It was also found that increasing the unit cell size was not beneficial at the low heat fluxes; however, it did enhance the CHF by approximately 28% compared with the bare surface.

Investigating the heavy metals’ removal capacity of some native plant species from the wetland groundwater of Maharlu Lake in Fars province, Iran

Saline Maharlu Lake in southern Iran is the outlet of Shiraz-Sarvestan basin, an inland flat lake, which its surroundings appear as wetland environment. The groundwater of the wetland area is polluted with heavy metals from the lake, and the wetland native plants grown in this area potentially have the tendency of uptaking the heavy metals from their rhizosphere environments. The lake is in hydraulic connection with its wetland groundwater and reverse hydraulic gradient results in movement of pollutants into the aquifers. This study aims to realize the wetland native plants efficiency in phytoremediation of the heavy metal. Groundwater samples were collected for analysis from rhizosphere of Jancus sp., Tamarix sp., and Suaeda sp. and compared with those of wetland regions without plants. Depletion and bio-concentration factors were calculated to evaluate the plants capability in removing metals from the wetland and determining the more suitable plant for phytoremediation. Results showed depletion of metals in the plant areas in compare with the bare land regions. Among the plants, the most depletion is for Jancus sp. followed by Tamarix sp. and Suaeda sp. The results also highlighted the potential of Jancus sp. for enhancing phytoremediation of heavy metal contaminated wetland, especially for Pb.

Spatio-temporal variation indicators for landscape structure dynamics monitoring using dense normalized difference vegetation index time series

Abstract Terrestrial ecosystems are constantly changing at various spatial and temporal scales due to natural and/or anthropogenic factors. It is therefore of great interest to develop effective indicators based on spatio-temporal variations to detect, map, and monitor ecosystem changes on the continental and global scales. In this study, spatio-temporal variation indicators were established to characterize landscape structure changes based on temporal analysis combined with spatial information obtained using dense Landsat time series in Changting County, Fujian, Province, China. All available Landsat images from 1987 to 2017 were collected. The fractal dimension (FD) of the spatial neighbor normalized difference vegetation index (NDVI) derived from the Landsat images was calculated. Four change patterns (stable, increasing, decreasing, and wave) were explored using the ordinary least-squares method between abrupt change points performed by a Mann–Kendall test on the FD time series to characterize the spatio-temporal dynamics. The results showed that 49.98% of the landscape structure in the study area decreased over the 31-year study period. The forest and water were dominated by decreasing patterns (67.00% and 56.27%); the urban land and cropland were dominated by wave patterns (50.07% and 50.95%); bare land regions were dominated by wave patterns and increasing patterns (50.52% and 31.38%). Wide and discontinuous landscape structures with high heterogeneity were replaced by landscape patches. The regional landscape structure heterogeneity increased in the bare land regions and other homogeneous landscape structures, while the decreases may be coupled with internal landscape structure changes. It was concluded that the spatial and temporal variations of the change patterns and change processes determined based on the FD of the NDVI in the spatial neighbor region are systematic indicators and can be used to detect landscape structure changes successfully and provide insights into dynamic trends.

Underwater acoustic radiation by structures arbitrarily covered with acoustic coatings

The shell structures of underwater vehicles are often covered with various acoustic coatings for the purpose of reducing the acoustic target strength or suppressing the structural vibration and underwater acoustic radiation. In engineering practice, there may be distinctions between acoustic coatings laid on different regions of the shell surface, and some bare regions may exist. For the complexity of the layout of acoustic coatings, a relevant calculation method needs to be developed to quantitively evaluate the effect of acoustic coatings on the reduction of underwater acoustic radiation. Further, the layout of acoustic coatings can be optimized on that basis. In this paper, the theory and relevant calculation method of three-dimensional sono-elasticity for ships arbitrarily covered by acoustic coatings are developed. By introducing an impedance matrix that describes the vibro-acoustic transfer between the inner and outer surfaces of the acoustic coating, boundary conditions on the interfaces of the acoustic coatings and the ambient water are derived. Expressions of the modal generalized hydrodynamic coefficients are given for the structure arbitrarily covered by acoustic coatings. Thus, the solution of vibro-acoustic and underwater acoustic radiation is obtained for the system of “ship structure-acoustic coating-water”. As an example, the acoustic radiation of a flat plate covered by acoustic coatings is numerically calculated and compared with analytical results, which verifies the correctness of the proposed method. Moreover, a series of results for the cylindrical shell structure with partial acoustic coatings are presented, which shows the interest of this method in engineering practice.