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On the Buoyancy Subrange in Stratified Turbulence
This study is motivated by the importance of the stratified turbulence in geophysical flows. We present a theoretical analysis of the buoyancy subrange based on the theory of strongly stratified turbulence. Some important turbulent scales and their relations are explored. Scaling constants of the buoyancy subrange scaling laws for both kinetic and potential energy spectra are derived and analyzed. It is found that these constants are functions of the horizontal Froude number Frh . For the potential energy spectrum, the scaling constant also depends on the turbulent flux coefficient of Γ .
Resonant terahertz light absorption by virtue of tunable hybrid interface phonon-plasmon modes in semiconductor nanoshells
Metallic nanoshells have proven to be particularly versatile, with applications in biomedical imaging and surface-enhanced Raman spectroscopy. Here, we theoretically demonstrate that hybrid phonon-plasmon modes in semiconductor nanoshells offer similar advantages in the terahertz regime. We show that, depending on tm,n,nhe doping of the semiconductor shells, terahertz light absorption in these nanostructures can be resonantly enhanced due to the strong coupling between interface plasmons and phonons. A threefold to fourfold increase in the absorption peak intensity was achieved at specific values of electron concentration. Doping, as well as adapting the nanoshell radius, allowed for fine-tuning of the absorption peak frequencies.
Effect of Fans’ Placement on the Indoor Thermal Environment of Typical Tunnel-Ventilated Multi-Floor Pig Buildings Using Numerical Simulation
An increasing number of large pig farms are being built in multi-floor pig buildings (MFPBs) in China. Currently, the ventilation system of MFPB varies greatly and lacks common standards. This work aims to compare the ventilation performance of three popular MFPB types with different placement of fans using the Computational Fluid Dynamics (CFD) technique. After being validated with field-measured data, the CFD models were extended to simulate the air velocity, air temperature, humidity, and effective temperature of the three MFPBs. The simulation results showed that the ventilation rate of the building with outflowing openings in the endwall and fans installed on the top of the shaft was approximately 25% less than the two buildings with fans installed on each floor. The ventilation rate of each floor increased from the first to the top floor for both buildings with a shaft, while no significant difference was observed in the building without a shaft. Increasing the shaft’s width could mitigate the variation in the ventilation rate of each floor. The effective temperature distribution at the animal level was consistent with the air velocity distribution. Therefore, in terms of the indoor environmental condition, the fans were recommended to be installed separately on each floor.
Using SPOT-7 for Nitrogen Fertilizer Management in Oil Palm
Environmental concerns are growing about excessive applying nitrogen (N) fertilizers, especially in oil palm. Some conventional methods which are used to assess the amount of nutrient in oil palm are time-consuming, expensive, and involve frond destruction. Remote sensing as a non-destructive, affordable, and efficient method is widely used to detect the concentration of chlorophyll (Chl) from canopy plants using several vegetation indices (VIs) because there is an influential relation between the concentration of N in the leaves and canopy Chl content. The objectives of this research are to (i) evaluate and compare the performance of various vegetation indices (VIs) for measuring N status in oil palm canopy using SPOT-7 imagery (AIRBUS Defence & Space, Ottobrunn, Germany) to (ii) develop a regression formula that can predict the N content using satellite data to (iii) assess the regression formula performance on testing datasets by testing the coefficient of determination between the predicted and measured N contents. SPOT-7 was acquired in a 6-ha oil palm planted area in Pahang, Malaysia. To predict N content, 28 VIs based on the spectral range of SPOT-7 satellite images were evaluated. Several regression models were applied to determine the highest coefficient of determination between VIs and actual N content from leaf sampling. The modified soil-adjusted vegetation index (MSAVI) generated the highest coefficient of determination (R2 = 0.93). MTVI1 and triangular VI had the highest second and third coefficient of determination with N content (R2 = 0.926 and 0.923, respectively). The classification accuracy assessment of the developed model was evaluated using several statistical parameters such as the independent t-test, and p-value. The accuracy assessment of the developed model was more than 77%.
Effectivity and Cost Efficiency of a Tax on Nitrogen Fertilizer to Reduce GHG Emissions from Agriculture
The use of nitrogen (N) fertilizer substantially contributes to greenhouse gas (GHG) emissions due to N2O emissions from agricultural soils and energy-intensive fertilizer manufacturing. Thus, a reduction of mineral N fertilizer use can contribute to reduced GHG emissions. Fertilizer tax is a potential instrument to provide incentives to apply less fertilizer and contribute to the mitigation of GHG emissions. This study provides model results based on a production function analysis from field experiments in Brandenburg and Schleswig-Holstein, with respect to risk aversion by calculating certainty equivalents for different levels of risk aversion. The model results were used to identify effective and cost-efficient options considering farmers’ risk aversion to reduce N fertilizer, and to compare the potential and cost of GHG mitigation with different N fertilizer tax schemes. The results show that moderate N tax levels are effective in reducing N fertilizer levels, and thus, in curbing GHG emissions at costs below 100 €/t CO2eq for rye, barley and canola. However, in wheat production, N tax has limited effects on economically optimal N use due to the effects of N fertilizer on crop quality, which affect the sale prices of wheat. The findings indicate that the level of risk aversion does not have a consistent impact on the reduction of N fertilizer with a tax, even though the level of N fertilizer use is generally lower for risk-averse agents. The differences in N fertilizer response might have an impact on the relative advantage of different crops, which should be taken into account for an effective implementation of a tax on N fertilizer.
Estimating Canopy Parameters Based on the Stem Position in Apple Trees Using a 2D LiDAR
Data of canopy morphology are crucial for cultivation tasks within orchards. In this study, a 2D light detection and range (LiDAR) laser scanner system was mounted on a tractor, tested on a box with known dimensions (1.81 m × 0.6 m × 0.6 m), and applied in an apple orchard to obtain the 3D structural parameters of the trees (n = 224). The analysis of a metal box which considered the height of four sides resulted in a mean absolute error (MAE) of 8.18 mm with a bias (MBE) of 2.75 mm, representing a root mean square error (RMSE) of 1.63% due to gaps in the point cloud and increased incident angle with enhanced distance between laser aperture and the object. A methodology based on a bivariate point density histogram is proposed to estimate the stem position of each tree. The cylindrical boundary was projected around the estimated stem positions to segment each individual tree. Subsequently, height, stem diameter, and volume of the segmented tree point clouds were estimated and compared with manual measurements. The estimated stem position of each tree was defined using a real time kinematic global navigation satellite system, (RTK-GNSS) resulting in an MAE and MBE of 33.7 mm and 36.5 mm, respectively. The coefficient of determination (R2) considering manual measurements and estimated data from the segmented point clouds appeared high with, respectively, R2 and RMSE of 0.87 and 5.71% for height, 0.88 and 2.23% for stem diameter, as well as 0.77 and 4.64% for canopy volume. Since a certain error for the height and volume measured manually can be assumed, the LiDAR approach provides an alternative to manual readings with the advantage of getting tree individual data of the entire orchard.
A Parametric Model for Local Air Exchange Rate of Naturally Ventilated Barns
With an increasing number of naturally ventilated dairy barns (NVDBs), the emission of ammonia and greenhouse gases into the surrounding environment is expected to increase as well. It is very challenging to accurately determine the amount of gases released from a NVDB on-farm. Moreover, control options for the micro-climate to increase animal welfare are limited in an NVDB at present. Both issues are due to the complexity of the NVDB micro-environment, which is subject to temporal (such as wind direction and temperature) and spatial (such as openings and animals acting as airflow obstacles) fluctuations. The air exchange rate (AER) is one of the most valuable evaluation entities, since it is directly related to the gas emission rate and animal welfare. In this context, our study determined the general and local AERs of NVDBs of different shapes under diverse airflow conditions. Previous works identified main influencing parameters for the general AER and mathematically linked them together to predict the AER of the barn as a whole. The present research study is a continuation and extension of previous studies about the determination of AER. It provides new insights into the influence of convection flow regimes. In addition, it goes further in precision by determining the local AERs, depending on the position of the considered volume inside the barn. After running several computational fluid dynamics (CFD) simulations, we used the statistical tool of general linear modeling in order to identify quantitative relationships between the AER and the following five influencing parameters, the length/width ratio of the barn, the side opening configuration, the airflow temperature, magnitude and incoming direction. The work succeeded in taking the temperature into account as a further influencing parameter in the model and, thus, for the first time, in analysing the effect of the different types of flow convection in this context. The resulting equations predict the barn AER with an R2 equals 0.98 and the local AER with a mean R2 equals around 0.87. The results go a step further in the precise determination of the AER of NVDB and, therefore, are of fundamental importance for a better and deeper understanding of the interaction between the driving forces of AER in NVDB.
The equivalent circuit approach for the electrical diagnostics of dielectric barrier discharges: The classical theory and recent developments
Measurements of current and voltage are the basic diagnostics for electrical discharges. However, in the case of dielectric barrier discharges (DBDs), the measured current and voltage waveforms are influenced by the discharge reactor geometry, and thus, interpretation of measured quantities is required to determine the discharge properties. This contribution presents the main stages of the development of electrical diagnostics of DBDs, which are based on lumped electrical elements. The compilation and revision of the contributions to the equivalent circuit approach are targeted to indicate: (1) the interconnection between the stage of development, (2) its applicability, and (3) the current state-of-the-art of this approach. © 2019 by the authors.
Influence of Tree Species, Harvesting Method and Storage on Energy Demand and Wood Chip Quality When Chipping Poplar, Willow and Black Locust
The cultivation of fast-growing wood (e.g., poplar, willow or black locust) in short rotation coppices and agroforestry systems presents an opportunity for producing biomass sustainably in the agricultural sector. Cost-efficient agricultural wood production requires the availability of high-performance machinery and methods with which high-quality wood chips can be produced at low cost. It is known from harvesting short rotation coppices in practice that both the wood chip quality and the performance of the harvesting machinery depend on a variety of factors (e.g., harvesting method, weather conditions, tree species). That is why this study examines in detail the influence of the tree species (different varieties of poplar, willow, black locust) and the wood condition (fresh, stored or dried, frozen) on the specific energy demand for comminution in a stationary drum chipper and on the particle size distribution of the wood chips produced. For all the tree species examined, the chipping of dried as well as frozen stems was connected with a significant increase in the specific energy demand for comminution. An increase of 31% has been measured if poplar stems are chipped in frozen conditions (max. 6.31 kWh t−1). Drying led to an increase of 59% for dried willow stems (max. 6.67 kWh t−1). Drying and frost had also an influence on the size and quality of the wood chips, but no globally significant connection could be established for the examined tree varieties.
Simulating Cotton Growth and Productivity Using AquaCrop Model under Deficit Irrigation in a Semi-Arid Climate
AquaCrop is a water-driven model that simulates the effect of environment and management on crop production under deficit irrigation. The model was calibrated and validated using three databases and four irrigation treatments (i.e., 100%ET, 80%ET, 70%ET, and 50%ET). Model performance was evaluated by simulating canopy cover (CC), biomass accumulation, and water productivity (WP). Statistics of root mean square error (RMSE) and Willmott’s index of agreement (d) showed that model predictions are suitable for non-stressed and moderate stressed conditions. The results showed that the simulated biomass and yield were consistent with the measured values with a coefficient of determination (R2) of 0.976 and 0.950, respectively. RMSE and d-index values for canopy cover (CC) were 2.67% to 4.47% and 0.991% to 0.998% and for biomass were 0.088 to 0.666 ton/ha and 0.991 to 0.999 ton/ha, respectively. Prediction of simulated and measured biomass and final yield was acceptable with deviation ˂10%. The overall value of R2 for WP in terms of yield was 0.943. Treatment with 80% ET consumed 20% less water than the treatment with 100%ET and resulted in high WP in terms of yield (0.6 kg/m3) and biomass (1.74 kg/m3), respectively. The deviations were in the range of −2% to 11% in yield and −2% to 4% in biomass. It was concluded that AquaCrop is a useful tool in predicting the productivity of cotton under different irrigation scenarios.