Annual Production Research Articles

Changes in phycospheric and environmental microbes in Neoporphyra haitanensis during the cultivation cycle

Neoporphyra haitanensis is an economic seaweed widely cultivated along the coast of China, allowing 4–5 times harvests during a cultivation season. The composition and functions of algal-microbial communities are intricate, dynamic, and closely linked to the health of algae. This study utilized metagenomic and 16S ribosomal RNA (rRNA) sequencing to investigate the dynamic changes in the phycospheric microbial communities of Neoporphyra haitanensis (PMC-Nh) and bacterial communities of surrounding seawater (BC-SW) during the cultivation cycle, providing valuable reference data for monitoring and preventing diseases of cultivated seaweed. The results indicated that N. haitanensis might possess the ability to “recruit” and “select” surrounding microbial communities. Beneficial bacteria contributing to carbon, nitrogen, sulfur or phosphorus cycles, such as Proteobacteria, Firmicutes, Cyanobacteria at the class level, and Rhodobacteraceae, Saprospiraceae, Flavobacteriaceae at the family level, exhibited increased abundance. A symbiotic relationship based on resource supply formed between algae and PMC-Nh. However, potential pathogenic bacteria capable of degrading algae, such as Aquimana, Nonlabens, Alteromonas, Loktanella, also successfully colonized. The yield and quality of N. haitanensis in the 2nd and 3rd harvests are crucial for annual production and income. However, potential pathogenic bacteria and factors peaked in abundance during the 2nd harvest. At this point, the symbiotic body formed by Neoporphyra and the PMC-Nh was in a state of equilibrium on the “tip of the needle”. Biomarkers in the 2nd harvest, such as Nonlabens and Alteromonas, have been reported as algal pathogens. Moreover, pathways or factors associated with bacterial pathogenesis were significantly enriched in the algal-associated microbial community in the 2nd harvest, such as biofilm formation, flagellar assembly, bacterial secretion system pathways, and virulence factors of the Virulence Factors of Pathogenic Bacteria (VFDB) database. This may be attributed to the variable and frequently intense temperature increases in the coastal areas of the East China Sea during the 2nd harvest period in mid to late October, leading to significant shifts in microbial balance. The PMC-Nh remained relatively stable during the 3rd harvest. Until the end of cultivation, pathways related to glycometabolism and the content of glycoside hydrolases in the PMC-Nh increased, possibly due to heightened polysaccharide content and the maturation or senescence of the final stage of N. haitanensis, favoring polysaccharide exudation. Our results suggest that the 2nd harvest stage is a high-risk period for N. haitanensis cultivation, and effective cultivation management should be conducted to prevent widespread algal decay and reduce production losses.

Numerical Study on the Performance of an OWC under Breaking and Non-Breaking Waves

A numerical model for the simulation of the performance of an oscillating water column (OWC) subjected to non-breaking and breaking waves is proposed in this paper. The numerical model consists of a hydrodynamic model specifically designed to simulate breaking waves and a pneumatic model that takes into account the air compressibility. The proposed numerical model was applied to evaluate the potential mean annual energy production from the waves of two coastal sites characterized by different hydrodynamic conditions: a deep-water condition, where the OWC interacts with non-breaking waves, and a shallow-water condition, where the OWC is subjected to breaking waves. The numerical results show that the effects of the air compressibility can be considered negligible only in numerical simulations of the performances of reduced-scale OWC devices, such as those used in laboratory experiments. We demonstrated that in real-scale simulations, the effect of the air compressibility within the OWC chamber significantly reduces its ability to extract energy from waves. The numerical results show that the effect of the air compressibility is even more significant in the case of a real-scale OWC located in the surf zone, where it interacts with breaking waves.

Determination of annual energy production loss due to erosion on wind turbine blades

Increasing size of the modern wind turbines amplifies the issues of leading-edge erosion, especially on the outboard sections of the blades, impacting both their structural integrity and aerodynamic efficiency. Predicting and detection of the aerodynamic losses which occurs before a noticeable structural degradation on the blade can be crucial for operational predictive maintenance strategies to avoid significant loss production. This paper presents the results from the collaborative study between DTU and CENER in order to investigate the influence of leading-edge erosion on wind turbine aerodynamic performance. For this purpose, three distinct erosion scenarios are analyzed by means of computational fluid dynamics (CFD), both 2D and 3D, blade-element momentum theory (BEM) based solver (OpenFAST) and a Simplified Aerodynamic Loss Tool (SALT). The results from previous studies are used as an input for these tools, with outputs from each tool complementing and reinforcing one another. Furthermore, annual energy production (AEP) reductions due to leading-edge erosion across these tools are compared and validation of the SALT tool is presented. It is observed that the thrust and power losses from both CFD and OpenFAST exhibit comparable results and for a severe erosion case, spanning the last third of the blade, results in a 4.3 % reduction in the annual energy production.

Integrated floating wind farm layout design and mooring system optimization to increase annual energy production

As we cluster wind turbines in wind farms to gain energy from sites with high wind speeds, wake losses occur within the wind farm. Wake loss is a term used to describe the lower energy production of a downwind turbine that is totally or partially in the wake of an upwind turbine. To decrease wake losses inside the wind farm, the wind farm’s layout is optimized. However, a variety of factors constrain the wind farm layout optimization, such as the size of the lease area relative to the number of turbines to be placed, or the shape of the lease area. Therefore, many wind farms end up with a regular grid layout, such as the Horns Rev 1 wind farm in the North Sea. The ability of a floating offshore wind turbine (FOWT) to change its position based on the wind direction and its mooring system design presents an opportunity to further decrease wake losses in floating wind farms. In this work, we integrate the design of the FOWT mooring systems with the floating wind farm layout design with the goal of increasing the farm’s annual energy production. We use the Horns Rev 1 wind farm as a case study to demonstrate our method. The results show that allowing the FOWT to relocate can decrease wake losses up to 18%. Moreover, the newly developed mooring systems are less stiff and therefore allow larger motion of the FOWT; hence, the material cost of the mooring system decreases by an estimated 17%.

The impact of spongy moth (Lymantria dispar dispar) defoliation on carbon balance of a temperate deciduous forest in North America

Temperate deciduous forests are an important contributor to the global carbon (C) sink. However, changes in environmental conditions and natural disturbances such as insect infestations can impact carbon sequestration capabilities of these forests. While, insect infestations are expected to increase in warmer future climates, there is a lack of knowledge on the quantitative impact of these natural disturbances on the carbon balance of temperate deciduous forests. In 2021, a record-breaking defoliation, caused by the spongy moth (Lymantria dispar dispar (LDD), formerly knows as the gypsy moth) occurred in eastern North America. In this study, we assess the impact of this spongy moth defoliation on carbon uptake in a mature oak-dominated temperate forest in the Great Lakes region in Canada, using eddy covariance flux data from 2012 to 2022. Study results showed that the forest was a large C sink with mean annual net ecosystem productivity (NEP) of 207 ± 77 g C m–2 yr−1 from 2012 to 2022, excluding 2021, which experienced the infestation. Over this period mean annual gross ecosystem productivity (GEP) was 1,398 ± 137 g C m–2 yr−1, while ecosystem respiration (RE) was 1,209 ± 139 g C m–2 yr−1. However, in 2021 due to defoliation in the early growing season, annual GEP of the forest declined to 959 g C m–2 yr−1, while annual RE increased to 1,345 g C m–2 yr−1 causing the forest to become a large source of C with annual NEP of -351 g C m–2 yr−1. The forest showed a rapid recovery from this major disturbance event, with annual GEP, RE, and NEP values of 1,671, 1,287, and 298 g C m–2 yr−1, respectively in 2022 indicating that the forest was once again a large C sink. This study demonstrates that major transient natural disturbances under changing climate can have a significant impact on forest C dynamics. The extent to which North American temperate forests will remain a major C sink will depend on the severity and intensity of these disturbance events and the rate of recovery of forests following disturbances. Lay abstractTemperate deciduous forests play an important role in carbon sequestration from the atmosphere. However, the impact of climate change, extreme weather, and disturbance events can alter the extent to which these forests sequester carbon, in some cases shifting their role from being a carbon sink to becoming a carbon source to the atmosphere. In 2021, a spongy moth infestation severely defoliated a mature oak-dominated temperate forest north of Lake Erie, Ontario, Canada, turning the forest from a 10-year mean carbon sink of about 2 tons of carbon per hectare to a carbon source of about 3.5 tons of carbon per hectare. Our analysis indicates that meteorological conditions during the early growing season might have influenced the severity of this infestation. Specifically, the prevalence of dry and warm weather conditions enabled the moth to survive and thrive longer. This study shows the significant influence of natural disturbances on forest carbon dynamics as temperatures continue to rise due to climate change. The future role forests play in carbon sequestration will be determined by the severity of disturbance events and the effectiveness of forests to recover in the aftermath of these events.

Multidisciplinary Wind Farm Electrical Infrastructure Optimization

During the construction stage of a wind farm, it is paramount to consider which layouts are the most efficient. Recent literature has found that optimization of the annual energy production is not necessarily driven by the same factors as other economic metrics, such as the internal rate of return. One parameter that makes this particularly true is the electrical cable length and layout, which affect both the cash flow of the project and the investments. While placing turbines far from each other is beneficial to mitigate the wake effect, the capital expenditures associated with the longer cables affects economic metrics. On the other hand, even though placing turbines close to each other reduces cable expenses, wind turbine mechanical loads are challenging to determine from wake effects. This work investigates trends between annual energy production, internal rate of return, electrical cable layout, and turbine components degradation due to mechanical loads. Results point towards corroborating recent literature, finding financial opportunities to explore tighter layouts with shorter electrical cables.

Techno-economic assessment of concentrated solar power technologies integrated with thermal energy storage system for green hydrogen production

The present study investigates the viability of employing Solar parabolic trough collectors (PTC) and parabolic dish collectors (PDC) integrated with thermal energy storage (TES) as the primary heat source for a steam-powered Rankine cycle, aimed to produce 5500 kW power for green hydrogen generation. A techno-economic analysis finds the system's overall efficiency (solar input to generator output) as 15.06% with PTC and 18.80% with PDC. Besides, incorporating PTC with binary and ternary salts in the proposed system yields approximately 22.7 % lower capital costs and a 7.8 % shorter payback period than solar PDC. Likewise, the levelized hydrogen cost with these options is around 12.3 % lower than those of PDC across all zones. However, to sustain a maximum annual hydrogen production of 238.38 tonne, equivalent to an annual electricity generation of 11180.07 MWh in each zone, the required PTC area is approximately 24.85% larger than PDC area.

Navigating the Web of Influence: A Bibliometric Analysis of Social Media Addiction.

Social media addiction is a behavioral dependency characterized by excessive and compulsive use of social media platforms, leading to negative impacts on various aspects of an individual's life. Bibliometric analysis is a research method used to quantitatively analyze academic literature, such as articles, books, and conference papers. It involves the application of statistical and mathematical tools to study the patterns and trends in scientific publications. This bibliometric study provides a comprehensive analysis of the literature on social media addiction, revealing patterns and dynamics within the field. Utilizing Web of Science for bibliographic data, the study employs advanced bibliometric tools like Biblioshiny and CiteSpace to map the scientific landscape. Annual scientific production, top contributing authors, key sources, trending topics, and thematic maps were identified using Biblioshiny. Additionally, network visualizations, such as co-citation networks of authors, time zone network visualizations of keyword co-occurrence, and timeline network visualizations of country collaborations, were created using CiteSpace. Our findings present an increasing trend in publications over the years, highlighting a growing recognition of social media addiction's significance. We detail the most relevant authors and sources, pinpointing key contributors and influential journals that shape the discourse. Trend topics analysis uncovers the prevalent themes, with "internet addiction" and "adolescents" at the forefront, reflecting the field's concentration on the younger population. The thematic map categorizes the research into motor themes (driving research areas), basic themes (fundamental and well-established areas), and niche themes (specialized and emerging topics), providing insight into the central and evolving topics. The study also delves into the co-occurrence of all keywords and the co-citation of authors, illustrating the interconnected nature of the research community. A timeline network visualization of country collaborations underscores the global scope of research efforts. Importantly, the study identifies critical research gaps such as underexplored demographics and emerging digital concerns and discusses practical implications, including the need for targeted intervention programs and informed policy-making. Collectively, this study charts the trajectory of social media addiction research and lays a foundation for future explorations to address identified lacunae.

Robustness of LiDAR-assisted controller towards measurement uncertainty

Many studies have concluded that LiDAR-assisted control can be used to increase annual energy production (AEP) as well as reduce extreme loads and fatigue damage on blades, tower, and main bearing components. However, most studies assume perfect LiDAR measurements and do not consider large measurement uncertainties on LiDAR measurements. In this study we evaluate the potential benefits in terms of fatigue load reduction from using a simple robust feedforward controller. In addition, we evaluate the impact of measurement uncertainties exemplified by a time shift between the expected time the wind hits the rotor and the actual time it hits the rotor as well as a mean wind speed measurement bias. Results shows that fatigue loads can be reduced up to 7% on the tower sections and up to 4% on other main components. However, these results only applies when the LiDAR is assumed to give perfect information about what is hitting the rotor plane. The load reduction degrades with the magnitude of a time shift of the arriving LiDAR wind measurements. A delay up to 2.5 seconds still gives reasonable load reductions. Furthermore, a positive wind speed bias does not affect the performance of the LiDAR-assisted controller, whereas a negative bias significantly deteriorates performance.

CFD investigation of flatback airfoils and swallow tail for wind turbine blades

Modern wind turbines use longer blades to improve annual energy production. Longer blades require thicker airfoils for structural integrity. Thicker airfoils are susceptible to issues like erosion, abrupt stalls, and early boundary layer transition, leading to increased drag and decreased lift, affecting overall performance. Flatback airfoils offer structural and aerodynamic advantages, being stiffer, less sensitive to surface roughness. However, this comes with a drag penalty, mainly due to the increase in base drag. Swallow tail add-on has been proposed to overcome these challenges. URANS simulations are used to analyze the aerodynamic performance of the different airfoils and hybrid RANS/LES simulations are used to study the flow features in more detail. The swallow tail airfoil was found to maintain many of the advantages of the flatback airfoils while reducing the drag penalty.

Robust wind farm layout optimization

Wake interactions in wind farms cause losses in annual energy production (AEP) on the order of 10%. Wind farm designers optimize the layout of the farm to mitigate wake losses, especially in the dominant site-specific wind directions. As wind turbines and wind farms grow in scale, optimization becomes more complex. Offshore wind farms regularly comprise more than 100 wind turbines and are characterized by complex boundaries due to shipping lanes, neighboring wind farms, and other constraints.Layout optimization methods are broadly split between gradient-based and gradient-free approaches. Gradient-based approaches can converge quickly and perform well for smaller, academic problems but are often sensitive to initial conditions and tuning parameters and require expert knowledge to use. On the other hand, gradient-free approaches can be more robust to problem complexities. We present a robust layout optimization approach based on a random search algorithm. The algorithm is intended for those who are not optimization experts and has few tuning parameters that need specification to achieve satisfactory results. Unlike off-the-shelf methods, which use generally available, non-domain-specific optimization routines that accept as inputs an optimization function and constraint definitions, this approach takes advantage of the relative computational costs of the different evaluations by evaluating cheaper computations first (boundary and minimum distance constraints) and running expensive AEP evaluations only if all other checks pass. Moreover, an outer genetic algorithm allows multiple solutions to evolve in parallel, enabling rapid solution development on high-performance computers. We discuss the relative ease of selecting necessary tuning parameters and demonstrate the efficacy of the genetic random search on a complex layout problem consisting of placing 70 turbines in a nonconvex and unconnected boundary region.

Exploring the Interdependence of Vertical Extrapolation Uncertainties in Repowering Wind Farms

Assessing a wind farm’s annual energy production (AEP) involves modelling the wind resource and the wind-to-power conversion at the site. The greenfield pre-construction phase generally comprises the installation of wind measurement devices. For repowering projects, the wind data from the pre-construction phase of the existing farm can be used as wind input to assess the energy yield of the repowered wind farm. Indeed, one study demonstrates that when the modelling error correlations are known, the AEP prediction uncertainty of the repowered farm can be reduced by combining the energy production records of the existing farm with the AEP assessment for both farms. Previous studies have successfully identified the correlation structure for certain errors, especially for horizontal flow modelling, but not for vertical flow modelling. However, vertical extrapolation is essential, as the wind measurement heights are generally lower than the hub height on the repowered farm. This paper bridges this research gap and demonstrates that the correlation structure of errors in vertical profile modelling is Gaussian, with parameters dependent on shear values and heights. The distribution is validated against site data from simple to moderately complex sites in France.

A two-step topology and layout wind farm optimization approach

A novel two-step approach is presented to optimize the placement of wind turbines within a wind farm. The goal is to maximize the annual energy production, while the topology and layout of the wind turbines are optimized in sequence with a two-step procedure using gradient-based algorithms. In particular, in the first step the topology of the wind farm is optimized. A grid of potential wind turbine locations is defined, and continuous density variables ranging from zero to one are assigned to each location. The variables indicate the presence or absence of a wind turbine. Throughout the topology optimization process, we penalize the intermediate values of these variables, implicitly pushing the algorithm towards crisp 0-1 final layouts. Constraints are imposed on the minimum and maximum number of wind turbines and the spacing between them. Subsequently, in the second step, we refine the wind farm layout by optimizing the coordinates (x, y) of the wind turbines, which are initialized based on the optimal topology obtained in the first step. Numerical findings demonstrate the capability of the proposed approach to identify non-intuitive optimized wind farm layouts, with reasonable computational resources and time.

The Use of Disposable Supplies: Measuring Suburethral Sling Surgical Waste by Cost and Weight

(Abstracted from Urogynecology 2024;30:132–137) Throughout the past decade, approximately 10% of total greenhouse gas emissions produced nationally in the United States have originated from the US health care system. Additionally, the carbon footprint of the health care system includes around 5 million tons of annual waste production (around 29 lb per hospital bed per day).

An improved wind farm parametrization for inhomogeneous inflow

Energy losses due to wind farm clustering and wind farm interaction are rarely well represented in the wind farm design process because of the lack of fast models that can accurately account for neighboring wind farm wakes. A recently developed solution is the actuator wind farm (AWF) model, which is a Reynolds-averaged Navier-stokes (RANS) based wind farm parametrization that models a wind farm as a distributed thrust force and applies a global wind farm thrust coefficient controller. We propose an improved version of the AWF model, where each turbine employs a local thrust force controller and uses turbine thrust and power coefficients as input to better handle inhomogeneous inflow conditions. The proposed AWF model shows improved performance compared to the original AWF model in terms of predicted wind turbine power of a downstream wind farm that operates in a partial wake of an upstream wind farm, without significantly increasing the computational effort. However, the annual energy production (AEP) wake losses of a large wind farm cluster are nearly unaffected by using local or global control and input because the largest impact is found near the cut-in wind speed, which does not contribute much to the AEP wake losses.

Agri-voltaics near airport facilities. Reconciling the risk of solar glare with power generation

The installation of photovoltaic systems on cultivated land enables both agricultural and green energy production simultaneously. The result is an efficient and inclusive use of land that promotes the rural economy, enables the recovery and maintenance of land and prevents its abandonment when it is considered not profitable. This intent is facilitated in semi-rural areas where there is already the presence of infrastructure connected to the national power grid, but at the same time is limited by other human activities. Runway approach and air traffic control operations impose very stringent constraints on the possibility that photovoltaic panels, reflecting solar radiation, may glare airport operators.This article provides a methodology for verifying such phenomena (control function) and mitigating them by maximizing solar power generation (objective function). Through a case study located in central Italy, positioned near an airport, it was possible to investigate the design variables to protect the landing air routes and the airport control tower.In this case study, with an azimuth angle of 47° and tilt angle of 25°, and thanks to a 5 m high tree screen placed on the edge of the land on which the agri-voltaic installation stands, it is possible to secure airport operations by eliminating all forms of solar glare. At the same time, 21.9 GWh of photovoltaic energy is produced annually, while avoiding the release of 8,773 tons of CO2 into the atmosphere. Compared with the optimal, unconstrained case, photovoltaic panels arranged in this way decrease their annual energy production by only 6.8 %.

Opensource machine learning metamodels for assessing blade performance impairment due to general leading edge degradation

Blades leading edge erosion can significantly reduce annual energy production of wind turbines. Accurate estimates of the resulting blade performance impairment are paramount to predict the resulting energy losses and enable cost-informed decisions on optimal maintenance and operational strategies, maximizing energy production and reducing maintenance costs. Computational Fluid Dynamics (CFD) is a robust approach for predicting the performance losses due to LEE. However, the impact of the damage on blade aerodynamics varies depending on damage pattern, extent and location. Therefore, direct CFD simulation of a sufficiently general set of damaged blades is computationally not viable in industrial applications, since the energy loss assessment needs to be performed for hundreds of turbines at many times of the wind farm operation. To address this issue, previous studies showed how CFD can be used to train machine learning metamodels of the perfomance of damaged blade sections, enabling the definition of multi-fidelity energy loss prediction systems. This study presents improved metamodels, using validated CFD to generate training datasets that cover a more general and wider range of erosion patterns, from low-amplitude roughness to severe grooves. In order to provide the industry with additional erosion geometry-linked tools for estimating energy yield losses, and foster further research and development in this area, the developed meta-models have been made available online with unrestricted access.

Difference in the production and elemental composition of litter in Kandelia obovata mangrove forests due to site elevation

Site elevation is a crucial driver for mangrove restoration, and litter production restoration is a significantly important target of mangrove restoration, but little attention has been paid to impact of site elevation on the production and elemental composition of litter in the restored mangrove forests. This study compared the production and elemental composition of mangrove litter at the three intertidal elevations, to explore impacts of site elevation on the production and elemental composition of mangrove litter. Compared with the upper elevation site, significantly lower annual litter production was found at the lower elevation site. Leaf litter was the main component of litter, up to 60.49% of total litter production at the upper elevation site, while reproductive materials (flower and fruit) were the key part of litter and accounted for 50.80% (the lower elevation site) and 57.02% (the middle elevation site) of total litter production. As site elevation decreased, element stocks within total litter decreased by approximately 65.39% (organic carbon), 65.17% (total nitrogen) and 63.66% (total phosphorus), respectively, which was attributed more to element stocks within leaf litter instead of element stocks within the other litter. Results showed that site elevation decreases resulted in decreased litter production, altered composition percentages of litter production, and reduced element stocks within total litter. In the future mangrove restoration projects, it is advisable to prioritize upper elevation (above local mean level) for promoting litter production.

Should Small Wind Pursue Traditional Region 3 Control?

A strategy to eliminate Region 3 control for small, fixed pitch turbines and utilize an extension of Region 2 is presented. Variations in wind probability distribution, capacity factor, and percent overshoot were examined. The relative performance of different control objectives was compared based on projected annual energy production. The results indicated that the Region 2 only control objective can produce energy equivalent to that of the currently employed Region 3 control objective over a range of wind regime-turbine combinations and capacity factors. It is suggested that the additional complexity required to provide Region 3 control for small turbines may not be warranted by the energy extraction benefits, particularly when factoring in additional equipment costs.

Dissecting the Characteristics and Driver Factors on Global Water Use Efficiency Using GLASS Data Sets

AbstractEcosystem water use efficiency (WUE) is a crucial parameter for understanding the interaction between carbon and water cycles. However, the spatio–temporal evolution and drivers of WUE remain unclear. This study utilized global annual scale global land surface satellite gross primary productivity and evapotranspiration data from 1982 to 2018 to estimate WUE and analyze its spatio–temporal characteristics. Additionally, the study investigated the response of WUE changes to five environmental factors (precipitation [PRE], soil moisture, temperature [TEM], palmer drought severity index, and vapor pressure deficit [VPD]) on WUE changes using partial correlation and structural equation modeling. The results suggested that the global annual WUE increased markedly over the study period, at an average rate of 0.0016 gC m−2 mm−1 H2O year−1. In contrast to the existing knowledge on the drivers of WUE change, climate change was found to have a larger contribution to WUE changes at the global and regional scales, especially in terms of TEM and VPD. A positive correlation between TEM and WUE was observed, but extreme TEM could lead to a decrease in WUE. VPD had the most significant direct effect on WUE, and its negative effect offset the positive influence of TEM especially in hyper‐arid, semi‐arid, and arid regions. These findings offer new insights into the impact of VPD and global warming on WUE.