Subgrid-Scale Modeling of Reacting Scalar Fluxes in Large-Eddy Simulations of Atmospheric Boundary Layers

In large-eddy simulations of atmospheric boundary layer turbulence, the lumped coefficient in the eddy-diffusion subgrid-scale (SGS) model is known to depend on scale for the case of inert scalars. This scale dependence is predominant near the surface. In this paper, a scale-dependent dynamic SGS model for the turbulent transport of reacting scalars is implemented in large-eddy simulations of a neutral boundary layer. Since the model coefficient is computed dynamically from the dynamics of the resolved scales, the simulations are free from any parameter tuning. A set of chemical cases representative of various turbulent reacting flow regimes is examined. The reactants are involved in a first-order reaction and are injected in the atmospheric boundary layer with a constant and uniform surface flux. Emphasis is placed on studying the combined effects of resolution and chemical regime on the performance of the SGS model. Simulations with the scale-dependent dynamic model yield the expected trends of the coefficients as function of resolution, position in the flow and chemical regime, leading to resolution-independent turbulent reactant fluxes.     

Automatic construction of concept hierarchies: The case of foliage-dwelling spiders

In this paper, we present the hierarchical variable dependencies that were obtained from raw data with the use of two machine learning techniques on an ecological data set. The data set contains features of field margins and the corresponding number of spider species inhabiting them. This data set was used before by domain experts to construct a fuzzy qualitative model with hierarchical variable dependencies, which we use for comparison with our results. One of the machine learning methods constructs a hierarchical structure similar to the one in the experts’ model, while revealing some additional interesting relations of environmental features with respect to the number of spider species. The other method constructs a different hierarchy from the one proposed by the experts, which, according to our classification performance experiments, might be even more appropriate.     

Integrating models to predict regional haze from wildland fire

Visibility impairment from regional haze is a significant problem throughout the continental United States. A substantial portion of regional haze is produced by smoke from prescribed and wildland fires. Here we describe the integration of four simulation models, an array of GIS raster layers, and a set of algorithms for fire-danger calculations into a modeling framework for simulating regional-scale smoke dispersion. We focus on a representative fire season (2003) in the northwestern USA, on a 12 km domain, and track the simulated dispersion and concentration of PM_2.5 over the course of the season. Simulated visibility reductions over national parks and wilderness areas are within the ranges of measured values at selected monitoring sites, although the magnitudes of peak events are underestimated because these include inputs other than fire. By linking the spatial and temporal patterns of haze-producing emissions to climatic variability, particularly synoptic weather patterns, and the stochastic nature of fire occurrence across the region, we can provide a robust method for estimating the quantity and distribution of fire-caused regional haze under climate-warming scenarios.     

Integrated landscape planning and remuneration of agri-environmental services. Results of a case study in the Fuhrberg region of Germany

Until now, existing remuneration of environmental services has not sufficiently supported the goals of spending money more effectively on the environment and of motivating farmers. Only a small share of the budgets for agriculture in the EU, as well as in US and other countries, is available for buying environmental goods and services beyond the level of good farming practice (GFP). This combined with the insufficient targeting of compensation payments to areas where special measures are needed leads to an unsatisfactorily low impact of agri-environment measures compared to other driving forces that stimulate the intensification of farming. The goal of this paper is to propose a management concept that enhances the ecological and cost efficiency of agri-environment measures. Components of the concept are a comprehensive environmental information base with prioritised goals and targets (available in Germany from landscape planning) and new remuneration models, which complement conventional compensation payments that are based upon predetermined measures and cost. Comprehensive landscape planning locates and prioritises areas which require environmental action. It contains the information that authorities need to prioritise funding for environmental services and direct measures to sites which need environmental services beyond the level of GFP.Also appropriate remuneration models, which can enhance the cost efficiency of public spending and the motivation of the farmers, can be applied on the base of landscape planning.Testing of the planning methodology and of one of the remuneration models (success-oriented remuneration) in a case study area (“Fuhrberger Feld” north of Hanover, Germany) demonstrated the usability of the concept and led to proposals for future development of the methodology and its application in combination with other approaches.     

Modeling Streams and Hydrogeomorphic Attributes in Oregon From Digital and Field Data1

Abstract: Managers, regulators, and researchers of aquatic ecosystems are increasingly pressed to consider large areas. However, accurate stream maps with geo‐referenced attributes are uncommon over relevant spatial extents. Field inventories provide high‐quality data, particularly for habitat characteristics at fine spatial resolutions (e.g., large wood), but are costly and so cover relatively small areas. Recent availability of regional digital data and Geographic Information Systems software has advanced capabilities to delineate stream networks and estimate coarse‐resolution hydrogeomorphic attributes (e.g., gradient). A spatially comprehensive coverage results, but types of modeled outputs may be limited and their accuracy is typically unknown. Capitalizing on strengths in both field and regional digital data, we modeled a synthetic stream network and a variety of hydrogeomorphic attributes for the Oregon Coastal Province. The synthetic network, encompassing 96,000 km of stream, was derived from digital elevation data. We used high‐resolution but spatially restricted data from field inventories and streamflow gauges to evaluate, calibrate, and interpret hydrogeomorphic attributes modeled from digital elevation and precipitation data. The attributes we chose to model (drainage area, mean annual precipitation, mean annual flow, probability of perennial flow, channel gradient, active‐channel width and depth, valley‐floor width, valley‐width index, and valley constraint) have demonstrated value for stream research and management. For most of these attributes, field‐measured, and modeled values were highly correlated, yielding confidence in the modeled outputs. The modeled stream network and attributes have been used for a variety of purposes, including mapping riparian areas, identifying headwater streams likely to transport debris flows, and characterizing the potential of streams to provide high‐quality habitat for salmonids. Our framework and models can be adapted and applied to areas where the necessary field and digital data exist or can be obtained.     

Mathematical modelling and experimental validation of solar drying of mushrooms

This article presents two mathematical models for drying mushrooms considering the shrinkage effect. Both the models consider the physical changes of mushrooms during drying using the diffusion equation. A convective term is presented in the first model while, in the second model, the effective diffusion co-efficient is employed. Although the diffusion co-efficient is mainly dependent on the water content of the mushrooms, both models are suitable for analyzing the drying process. Moreover, in this study it has been demonstrated that both models are equivalent. The Genetic Algorithmic process was used to estimate the parameter values in different conditions. The information regarding the moisture content and the thickness evaluation taken from the models shows the best fit with the experimental data. The mathematical models developed to simulate the drying curve of mushroom have been evaluated and compared.     

Computational Fluid Dynamics (CFD) Simulations on the Effect of Rough Surface on Atmospheric Turbulence Flow Above Hilly Terrain Shapes

The behavioral distribution of the atmospheric turbulence flow over the terrain with changes in a rough surface has become one of the most important topics of air pollution research, among such other topics as transportation and dispersion pollutants. In this study, a computational model on atmospheric turbulence flow over a terrain hill shaped with rough surface was investigated under neutral atmospheric conditions. The flow was assumed to be 2D and modeled using computational fluid dynamics (CFD) models, which were numerically solved using Reynolds-averaged Navier-Stokes equations. Rough surface conditions were modeled using a number of windbreak fences regularly spaced on the hill. The mean velocity and turbulent structures such as turbulence intensity and turbulent kinetic energy were investigated in the upwind and downwind regions over the hill, and the numerical models were validated against the wind-tunnel results to optimize the turbulence model. The computational results agreed well with the results obtained from the wind tunnel experiments. The computational results indicate that the mean velocity was observed to increase dramatically around the crest of the upwind slope of the hill. A thick internal boundary layer was observed with a fence on the crest and downwind region of the hill. The reversed flow and recirculation zone were formed in the wake region behind the hill. It was thus determined that turbulent kinetic energy decreases as the mean velocity increases.     

Analyzing the Effects of Groundwater Pumping on an Urban Stream‐Aquifer System

When the cone of influence of a pumping well reaches a nearby river, the resulting hydraulic gradient can induce enhanced seepage of streamflow into the aquifer. The rate of seepage is often modeled using analytical solutions that are simple to apply but may not reproduce field data due to mathematical assumptions not being met in the field. Furthermore, the appropriateness of such models has not been investigated in detail due to difficulty in measuring streamflow loss in the field. In this study, a field experiment was conducted on a reach of the South Platte River near Denver, Colorado to estimate pumping‐induced streamflow loss. A network of stream gauges, monitoring wells, and in situ measurements was used to observe streamflow rates, groundwater levels, and temperature to assess if pumping wells have a significant impact on streamflow, and to compare observed streamflow depletion against analytical solutions. Data collected suggest that pumping wells have a noticeable impact on streamflow. The analytical solutions proved accurate if streamflow was low and constant but performed poorly if streamflow was high and variable. Therefore, for this reach, the use of analytical solutions to predict streamflow may only be appropriate under low‐flow, constant‐flow conditions. Methods and results can be used to guide other streamflow depletion studies and to inform cases of pumping‐induced streamflow depletion, particularly in regard to water rights.     

核电厂运行人员可靠性研究中若干问题的分析

对已有人因可靠性分析模型进行归纳总结,结合核电厂运行人员可靠性研究实际,对人因分类、人因建模、数据采样及人因数据库完善等方面存在的问题进行分析,并提出可能的解决办法或研究方向:在人因分类方式上,要加强因素之间的细化程度,以降低评价的模糊性;在人因量化方面,要重点考虑其所依赖的HRA模型、数学依据、结果精确度等3个方面的影响;对待数据采集的问题,规范性数据采集平台的构建是确保数据一致性的关键措施,并有利于不同HRA模型之间接口相容性问题的解决;人因数据库管理系统的智能决策功能是研发设计的趋势。     

基于蝴蝶型突变理论的安全生产保障系统分析和探讨

利用突变理论探讨事故致因模型,揭示事故致因的基本要素及其内在联系,对构成的要素进行抽象化,将对众多复杂企业的不安全因素进一步归纳为"人-机-环境-管理"安全生产保障系统,分析建立该系统的必要性,在突变理论的蝴蝶型与该系统结合性的基础上,探讨和建立安全决策和安全对策模型,将企业的安全生产危险程度分为理想的安全区域、危险区域、相对的安全区域。提出了危险程度和安全状况改进的数学模型,蝴蝶型突变理论能够揭示企业的安全状况。