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Effects of helical-shaped blades on the flow characteristics and power production of finite-length wind farms composed of vertical-axis wind turbines (VAWTs) are studied numerically using large-eddy simulation (LES). Two helical-bladed VAWTs (with opposite blade twist angles) are studied against one straight-bladed VAWT in different array configurations with coarse, intermediate, and tight spacings. Statistical analysis of the LES data shows that the helical-bladed VAWTs can improve the mean power production in the fully developed region of the array by about 4.94%–7.33% compared with the corresponding straight-bladed VAWT cases. The helical-bladed VAWTs also cover the azimuth angle more smoothly during the rotation, resulting in about 47.6%–60.1% reduction in the temporal fluctuation of the VAWT power output. Using the helical-bladed VAWTs also reduces the fatigue load on the structure by significantly reducing the spanwise bending moment (relative to the bottom base), which may improve the longevity of the VAWT system to reduce the long-term maintenance cost.

 

The Southeastern United States has high landscape heterogeneity, with heavily managed forestlands, developed agriculture, and multiple metropolitan areas. The spatial pattern of land use is dynamic. Expansion of urban areas convert forested and agricultural land, scrub forests are converted to citrus groves, and some croplands transition to pine plantations. Previous studies have recognized that forest management is the predominant factor in structural and functional changes forests, but little is known about how forest management practices interact with surrounding land uses at the regional scale. The first step in studying the spatial relationships of forest management with surrounding landscapes is to be able to map management practices and describe their proximity to various land uses. There are two major difficulties in generating land use and land management maps at the regional scale by any method: the necessity of large training data sets and expensive computation. The combination of crowdsourced, citizen-science mapping and cloud-based computing may help overcome those difficulties. In this study, OpenStreetMap is incorporated into mapping land use and shows great potential for justifying and monitoring land use at a regional scale. Google Earth Engine enables large-scale spatial analysis and imagery processing by providing a variety of Earth observation datasets and computational resources. By incorporating the OpenStreetMap dataset into Earth observation images to map forest land management practices and determine the distribution of other nearby land uses, we develop a robust regional land-use mapping approach and describe the patterns of how different land uses may affect forest management and vice versa . We find that cropland is more likely to be near ecological forest management patches; few close spatial relationships exist between land uses and preservation forest management, which fulfills the preservation management strategy of sustaining the forests, and production forests have the strongest spatial relationships with croplands. This approach leads to increased understanding of land-use patterns and management practices at local to regional scales. 

Turbulent wake flows behind helical- and straight-bladed vertical axis wind turbines (VAWTs) in boundary layer turbulence are numerically studied using the large-eddy simulation (LES) method combined with the actuator line model. Based on the LES data, systematic statistical analyses are performed to explore the effects of blade geometry on the characteristics of the turbine wake. The time-averaged velocity fields show that the helical-bladed VAWT generates a mean vertical velocity along the center of the turbine wake, which causes a vertical inclination of the turbine wake and alters the vertical gradient of the mean streamwise velocity. Consequently, the intensities of the turbulent fluctuations and Reynolds shear stresses are also affected by the helical-shaped blades when compared with those in the straight-bladed VAWT case. The LES results also show that reversing the twist direction of the helical-bladed VAWT causes the spatial patterns of the turbulent wake flow statistics to be reversed in the vertical direction. Moreover, the mass and kinetic energy transports in the turbine wakes are directly visualized using the transport tube method, and the comparison between the helical- and straight-bladed VAWT cases show significant differences in the downstream evolution of the transport tubes. 

Management practices are one of the most important factors affecting forest structure and function. Landowners in southern United States manage forests using appropriately sized areas, to meet management objectives that include economic return, sustainability, and esthetic enjoyment. Road networks spatially designate the socio-environmental elements for the forests, which represented and aggregated as forest management units. Road networks are widely used for managing forests by setting logging roads and firebreaks. We propose that common types of forest management are practiced in road-delineated units that can be determined by remote sensing satellite imagery coupled with crowd-sourced road network datasets. Satellite sensors do not always capture road-caused canopy openings, so it is difficult to delineate ecologically relevant units based only on satellite data. By integrating citizen-based road networks with the National Land Cover Database, we mapped road-delineated management units across the regional landscape and analyzed the size frequency distribution of management units. We found the road-delineated units smaller than 0.5 ha comprised 64% of the number of units, but only 0.98% of the total forest area. We also applied a statistical similarity test (Warren’s Index) to access the equivalency of road-delineated units with forest disturbances by simulating a serious of neutral landscapes. The outputs showed that the whole southeastern U.S. has the probability of road-delineated unit of 0.44 and production forests overlapped significantly with disturbance areas with an average probability of 0.50. 

We report a viable route to plasmonic nanoparticles with well-controlled sizes, shapes, and compositions. A series of monodisperse Ag and Au nanoparticles capped with polystyrene chains ( i.e. , “hairy” nanoparticles) are crafted by capitalizing on star-like diblock copolymers as nanoreactors. Such monodisperse nanoparticles render an accurate absorption spectrum, providing a strong basis for theoretical investigation into their optical properties. By combining the experimental study with the three-dimensional finite element calculation of electromagnetic field distributions, the contributions of both intra-band and inter-band transitions to plasmonic absorption are revealed. The calculated absorption spectra perfectly reproduce the experimental observations, including the peak positions, shapes, and trends of peak shifting or broadening as a function of nanoparticle sizes. The influences of nanoparticle dimensions and surface ligands on plasmonic absorption of metallic nanoparticles are also systematically explored. 

Macrosystem‐scale research is supported by many ecological networks of people, infrastructure, and data. However, no network is sufficient to address all macrosystems ecology research questions, and there is much to be gained by conducting research and sharing resources across multiple networks. Unfortunately, conducting macrosystem research across networks is challenging due to the diversity of expertise and skills required, as well as issues related to data discoverability, veracity, and interoperability. The ecological and environmental science community could substantially benefit from networking existing networks to leverage past research investments and spur new collaborations. Here, we describe the need for a “network of networks” (NoN) approach to macrosystems ecological research and articulate both the challenges and potential benefits associated with such an effort. We describe the challenges brought by rapid increases in the volume, velocity, and variety of “big data” ecology and highlight how a NoN could build on the successes and creativity within component networks, while also recognizing and improving upon past failures. We argue that a NoN approach requires careful planning to ensure that it is accessible and inclusive, incorporates multimodal communications and ways to interact, supports the creation, testing, and promulgation of community standards, and ensures individuals and groups receive appropriate credit for their contributions. Additionally, a NoN must recognize important trade‐offs in network architecture, including how the degree of centralization of people, infrastructure, and data influence network scalability and creativity. If implemented carefully and thoughtfully, a NoN has the potential to substantially advance our understanding of ecological processes, characteristics, and trajectories across broad spatial and temporal scales in an efficient, inclusive, and equitable manner.