A model for the prediction of laminar-turbulent transition processes was formulated. It is based on the LCTM (‘Local Correlation-based Transition Modelling’) concept, where experimental correlations ...are being integrated into standard convection-diffusion transport equations using local variables. The starting point for the model was the
γ
-Re
θ
model already widely used in aerodynamics and turbomachinery CFD applications. Some of the deficiencies of the
γ
-Re
θ
model, like the lack of Galilean invariance were removed. Furthermore, the Re
θ
equation was avoided and the correlations for transition onset prediction have been significantly simplified. The model has been calibrated against a wide range of Falkner-Skan flows and has been applied to a variety of test cases.
The purpose of this work is to improve the k-ω-γ transition model for separation-induced transition prediction. The fundamental cause of the excessively small separation bubble predicted by k-ω-γ ...model is scrutinized from the perspective of model construction. On the basis, three rectifications are conducted to improve the k-ω-γ model for separation-induced transition. Firstly, a damping function is established via comparing the molecular diffusion timescale with the rapid pressure-strain timescale. The damping function is applied to prevent the effective length scale from incorrect distribution near the leading edge of the separation bubble. Secondly, the pressure gradient parameter λζ, is proposed as an indicator for local susceptibility to the separation instability. Additionally, λζ,-based separation intermittency γsep is constructed to accelerate the substantial growth of turbulent kinetic energy after flow separation. The improved model appropriate for both low- and high-speed flow has been calibrated against a variety of diverse and challenging experiments, including the subsonic T3L plate, Aerospatial A airfoil, transonic NLR-7301 airfoil and deformed hypersonic inflatable aerodynamic decelerator aeroshell. The improved model is strictly based on local variables and Galilean invariance. Besides, the proposed improvement for k-ω-γ model can be fairly convenient to incorporate into other existing intermittency-based transition models.
Display omitted
•Alfalfa surface in the landscape enhances the abundance of predators and herbivores.•Orchard surface in the landscape may lead to suppression of potential predators.•Non-crop ...habitats and forest proportions and landscape Shannon diversity had minor effects.•At local scale, the maize growth stages had higher effects on the abundance of insect.
The traditional agricultural landscape of Ebro Basin (NE Spain), which is mainly composed of alfalfa and cereal crops, has undergone changes in recent years, mainly consisting of an increase in the area occupied by intensively managed irrigated orchards. Recently, it has been reported that the presence of a higher proportion of orchards in the landscape and their management negatively affect the abundance and diversity of natural enemies. Two hypotheses are tested in this study: (1) the increased orchard surface has led to a reduction in natural enemies in neighbouring maize crops, and (2) the higher alfalfa proportion of agricultural land enhances the predatory fauna on maize. Maize fields were selected across a landscape gradient created by orchards and field crops (alfalfa and maize) in a buffer of 500 m. The abundance of 17 insect taxa in each maize field was estimated by means of 3 yellow sticky traps per season over three years. The insect abundance was related to the landscape structure (proportions of landscape elements and landscape diversity) and local variables (maize phenology, perimeter/area, weed diversity of the maize edges and abundance of the potential predators or potential prey). Our results show that the proportion of orchards in the landscape had negative effects on the main predators, and alfalfa had positive effects on herbivores and their predators. Semi-natural habitats (non-crop habitats and forest) and landscape diversity had low effects on insect abundance. However, variables at the local level included more significant effects than landscape structure; maize growth stages and abundance of potential prey or predators on the crop were the most influential variables at a local level. Here we show the interplay between different land uses types and local management and their impact on natural enemies and herbivores in maize crops in the Mediterranean area.
Monitoring and control of West Nile virus (WNV) presents a challenge to state and local vector control managers. Models of mosquito presence and viral incidence have revealed that variations in ...mosquito autecology and land use patterns introduce unique dynamics of disease at the scale of a county or city, and that effective prediction requires locally parameterized models. We applied Bayesian spatiotemporal modeling to West Nile surveillance data from 49 mosquito trap sites in Nassau County, New York, from 2001 to 2015 and evaluated environmental and sociological predictors of West Nile virus incidence in Culex pipiens-restuans. A Bayesian spike-and-slab variable selection algorithm was used to help select influential independent variables. This method can be used to identify locally-important predictors.
The best model predicted West Nile positives well, with an Area Under Curve (AUC) of 0.83 on holdout data. The temporal trend was nonlinear and increased throughout the year. The spatial component identified increased West Nile incidence odds in the northwestern portion of the county, with lower odds in wetlands on the south shore of Long Island. High Normalized Difference Vegetation Index (NDVI) areas, wetlands, and areas of high urban development had negative associations with WNV incidence.
In this study we demonstrate a method for improving spatiotemporal models of West Nile virus incidence for decision making at the county and community scale, which empowers disease and vector control organizations to prioritize and evaluate prevention efforts.
Display omitted
•49 mosquito trap locations tested for West Nile virus over a 15-year span•Bayesian zero-inflated binomial model with spatial and temporal correlated random effects developed using R-INLA•Model predicted 75% of all WNV outcomes correctly on holdout data, with 72% of positives correctly classified.•Spatial and temporal trends mapped across the study area highlighted areas and times of concern for WNV incidence.•Areas with lower vegetation and less-dense development, such as suburbs, were at highest risk.
The Static Single Assignment (SSA) form is an intermediate representation used for the analysis and optimization of programs in modern compilers. The ϕ-function placement is the most computationally ...expensive part of converting any program into its SSA form. The most widely-used ϕ-function placement algorithms are based on computing dominance frontiers (DF). However, this kind of algorithms works under the limiting assumption that all variables are defined at the beginning of the program, which is not the case for local variables. In this paper, we introduce an innovative ϕ-placement algorithm based on computing reaching definitions (RD), which generates a precise number of ϕ-functions. We provided theorems and proofs showing the correctness and the theoretical computational complexity of our algorithms. We implemented our approach and a well-known DF-based algorithm in the Clang/LLVM compiler framework, and performed experiments on a number of benchmarks. The results show that the limiting assumption of the DF-based algorithm when compared with the more accurate results of our RD-based approach leads to generating up to 87% (69% on average) superfluous ϕ-functions on all benchmarks, and thus brings about a significant precision loss. Moreover, even though our approach computes more information to generate precise results, it is able to analyze up to 92.96% procedures (65.63% on average) of all benchmarks with execution time within twice the execution time of the reference DF-based approach.
In this study, we investigated the influence of environmental variables (predictor variables) on the species richness, species diversity, functional diversity, and functional redundancy (response ...variables) of stream fish assemblages in an agroecosystem that harbor a gradient of degradation. We hypothesized that, despite presenting high richness or diversity in some occasions, fish communities will be more functionally redundant with stream degradation. Species richness, species diversity, and functional redundancy were predicted by the percentage of grass on the banks, which is a characteristic that indicates degraded conditions, whereas the percentage of coarse substrate in the stream bottom was an important predictor of all response variables and indicates more preserved conditions. Despite being more numerous and diverse, the groups of species living in streams with an abundance of grass on the banks perform similar functions in the ecosystem. We found that riparian and watershed land use had low predictive power in comparison to the instream habitat. If there is any interest in promoting ecosystem functions and fish diversity, conservation strategies should seek to restore forests in watersheds and riparian buffers, protect instream habitats from siltation, provide wood debris, and mitigate the proliferation of grass on stream banks. Such actions will work better if they are planned together with good farming practices because these basins will continue to be used for agriculture and livestock in the future.
On the surface of a rotating projectile flying with a supersonic speed, due to the rotational motion, an asymmetric boundary layer transition will occur. This boundary layer distortion caused by the ...rotation has a significant contribution to the Magnus effect, which will produce a large instability moment and cause flight instability. Therefore, it is of great significance to conduct in-depth research and flow mechanism analysis on the asymmetric boundary layer transition phenomenon on the surface of high-speed rotating projectiles. On the one hand, in supersonic boundary layers, the steamwise flow instability modes are mainly the first mode and the laminar flow separation mode; on the other hand, strong crossflow velocity shear will be generated in the self-rotating state of the projectile and the compressible crossflow instability plays an extremely important role. This paper proposes a physics-informed transition-turbulence model suitable for supersonic/hypersonic boundary layers, which contains physical instability mechanisms and all variables can be solved locally. New time scales for the first mode and crossflow mode are developed. Furthermore, compressibility corrections and cooled wall modifications are performed on the model. Based on this model, we conducted the unsteady simulations of the high-speed rotating straight cone, and carefully compared the mesh sensitivity. In detail, the boundary layer transition characteristics under different Mach numbers, angles of attack, Reynolds numbers and rotational speeds are analyzed through the present transition-turbulence model. Decent agreement with the experiment data verifies that the transition-turbulence model developed by the authors can be applied to predict the asymmetric transition phenomenon on the supersonic flying rotating projectiles with high accuracy.
•An improved physics-informed transition-turbulence model for supersonic/hypersonic boundary layers is proposed based on local variables in this paper.•New time scales for the first mode, second mode and crossflow mode are developed and the cooled wall correction is formulated.•When the asymmetric transition phenomenon is considered using the present transition turbulence model, the accuracy of the prediction results has been greatly improved.
Species distribution models have been used to assist decision-making in many different aspects of conservation, restoration, and environmental management. However, to apply species distribution ...models effectively, we need to discriminate between suitable and unsuitable environments and the models need to be developed at fine scales (i.e. covering small areas at a fine resolution). These characteristics allow more precise decision-making for heterogeneous environments in smaller areas, such as biomes. We also need to understand the potential limiting factors in relation to these models better, including the effects of sample bias in species occurrence records and the potential mismatch between the scale at which the models were built and the scale at which the predictor variables interact with species occurrence. Here we evaluate the effects of two methods used to reduce bias (geographic vs. environmental filters) and three predictor variable types (climactic, local and biotic) on model predictions. We explore these issues for the hyacinth macaw (
Anodorhynchus hyacinthinus
), a globally vulnerable species in the Pantanal biome of central South America. We consider broad-scale variables, local-scale habitat associations, and the interactions of the macaw with two plant species that provide its food and nesting location. Our results show that using broad-scale climate variables for local-scale models (i.e., models with a fine resolution with a small extent) can generate predictive distribution models that underpredict suitability. Using local and biotic variables generates more accurate models with predictions consistent with the known distribution of the bird species. Although not commonly used, local-scale variables strongly affect model performance by increasing accuracy, reducing omission error, and leading to more conservative predictions. On the other hand, these methods lead to variable results in relation to bias reduction, with their efficiency depending on the amount of sampling bias in the occurrence records. In conclusion, local variables and the method of bias reduction play an important role in species distribution models. Fine resolution models constructed at the local scale for small areas show the greatest skill in predicting species distribution.
We assess the effects of changing land use and crop management on alfalfa insect abundance by comparing it in 50 alfalfa fields when they were inserted in landscapes with different proportions of ...arable crops and orchards. Land use in a buffer of 500 m was assessed, and alfalfa insect abundance was estimated with sticky yellow traps. The number of catches of several herbivores and predators was related to the proportion of landscape components and several field variables. Results indicated that the proportion of orchards in the buffer negatively affected the abundance of predators on alfalfa, likely because orchards treated with pesticides are a sink for predators moving in the landscape, among other possible causes. Other landscape variables such as noncrop habitats, winter cereals, and landscape diversity analysed by the Shannon index had a minor influence. Among field variables, field size influenced positively the abundance of insects on alfalfa, whereas alfalfa growth stage and age affected positively or negatively the different herbivores and predators. Of course, abundance of predators and prey was affected by the abundance of prey and predators, respectively. These findings suggest that a high proportion of intensively managed crops (orchards) in the landscape interferes with the role of alfalfa as a reservoir of predatory insects for adjacent crops and that the responses to local and landscape structures are temporal and species-specific as previously concluded for maize. Consequently, landscape and field management strategies to improve pest control must consider both types of variables as well as their changing influence when we modify them.
PDF
