烟气扩散的CFD数值模拟

运用商业CFD软件Fluent模拟计算小尺寸下的简单烟气扩散规律.将结果用正态分布假设下的高斯烟羽模型验证.证明该软件模拟烟气扩散问题的可行性.     

The impact of global warming on winter tourism and skiing: a regionalised model for Austrian snow conditions

Possible climate change will modify snow-cover depth and change the characteristics of winter tourism and skiing districts. Our model describes seasonal snow-cover depth related to altitude in six Alpine climate regions as the best fit of all snow stations. Data cover 30 winter seasons (November to April values) from 1965 to 1995. We modified the data according to a scenario of temperature and precipitation change (2 °C warming, no precipitation change) and achieve a new simulated snow-cover depth. The indicators MARP (mean altitude of resident population) and MASPSL (mean altitude of starting point of ski lifts) serve as references for “critical altitudes” of Austrian districts. A warming implies a reduction of snow in all districts, but the loss is overproportional in lower altitudes. The direction of economic impacts is clear – income losses and adaptation costs – but magnitude and time frames remain uncertain. Received: 24 February 1999 · Accepted: 15 May 1999     

Dynamics of Ammonia Exchange in Response to Cutting and Fertilising in an Intensively-Managed Grassland

Continuous micrometorological measurements of ammonia (NH₃)exchange were made for a period of 19 months (May 1998–November 1999) over intensively managed grassland in southern Scotland. This study focused on the influence of management activities, such as cutting and fertilising, on vegetation-atmosphere exchange of NH₃. Measurements were conducted within the European project GRAMINAE (GRassland AMmonia INteractions Across Europe) within which the Scottish site forms one of 6 sites in an E–W transect across Europe. NH₃ emissions were enhanced (up to 300 ng m^-2 s^-1) after cutting followed by larger emissions after fertilising (up to 1400 ng m^-2 s^-1). Annual budget calculations show the intensive grassland acted as a net source (1.8 kg N ha^-1 yr¹) although fluxes were bi-directional with deposition dominating in the winter and emission in the summer. Initial modelling of the NH₃ exchange using a `canopy compensation point' model has been conducted for key periods. The dynamics of the fluxes during these key periods, such as before and after cutting and fertilising, may be reproduced by introducing different values of the apoplastic ratio, = [NH₄ ⁺]/[H⁺].     

Small cetacean bycatch as estimated from stranding schemes: The common dolphin case in the northeast Atlantic

Death in fishing gear of non-target species (called ‘bycatch’) is a major concern for marine wildlife, and mostly worrying for long-lived species like cetaceans, considering their demographic characteristics (slow population growth rates and low fecundity). In European waters, cetaceans are highly impacted by this phenomenon. Under the Common Fishery Policy, the EC 812/2004 regulation constitutes a legal frame for bycatch monitoring on 5–10% of fishing vessels >15 m. The aim of this work was to compare parameters and bycatch estimates of common dolphins (Delphinus delphis) provided by observer programmes in France and UK national reports and those inferred from stranding data, through two approaches. Bycatch was estimated from stranding data, first by correcting effectives from drift conditions (using a drift prediction model) and then by estimating the probability of being buoyant. Observer programmes on fishing vessels allowed us to identify the specificity of the interaction between common dolphins and fishing gear, and provided low estimates of annual bycaught animals (around 550 animals year⁻¹). However, observer programmes are hindered by logistical and administrative constraints, and the sampling scheme seems to be poorly designed for the detection of marine mammal bycatches. The analyses of strandings by considering drift conditions highlighted areas with high levels of interactions between common dolphins and fisheries. Since 1997, the highest densities of bycaught dolphins at sea were located in the southern part of the continental shelf and slope of the Bay of Biscay. Bycatch numbers inferred from strandings suggested very high levels, ranging from 3650 dolphins year⁻¹ [2250–7000] to 4700 [3850–5750] dolphins year⁻¹, depending on methodological choices. The main advantage of stranding data is its large spatial scale, cutting across administrative boundaries. Diverging estimates between observer programmes and stranding interpretation can set very different management consequences: observer programmes suggest a sustainable situation for common dolphins, whereas estimates based on strandings highlight a very worrying and unsustainable process.     

Use of hydrodynamic models for the management of the Danube Delta wetlands: The case study of Sontea-Fortuna ecosystem

Due to its high biodiversity the Danube Delta, in Romania, is recognized as a UNESCO World Heritage Natural Site and it is listed as a RAMSAR wetland. The Danube River variable discharges have a great impact on the habitats and the overall ecological status of the delta. One of its most vulnerable parts, from both hydrodynamic and morphological point of view is the Sontea-Fortuna wetland located in the upstream of the Danube Delta. Sontea-Fortuna wetland is susceptible to both floods and droughts. On a long term, decision makers in the area need to know which measures to implement and how these will impact/improve the environment.This article presents how a 3D hydrodynamic model can be used as support for making sound decisions regarding the management of deltaic ecosystems. In particular, the methodology is applied on the Sontea-Fortuna wetland. The case study is part of a wider research in the area, which was developed within the EnviroGRIDS EU FP7 research project. EnviroGRIDS aimed at building capacity for scientists, decision-makers and the general public in the Black Sea Catchment, through collection and sharing of environmental data and models at the basin scale.     

Description and evaluation of a model of deposition velocities for routine estimates of dry deposition over North America. Part II: review of past measurements and model results

Numerical sensitivity tests and four months of complete model runs have been conducted for the Routine Deposition Model (RDM). The influence of individual model inputs on dry deposition velocity as a function of land-use category (LUC) and pollutant (SO₂, O₃, SO²⁻₄ and HNO₃) were examined over a realistic range of values for solar radiation, stability and wind speed. Spatial and temporal variations in RDM deposition velocity (V_d) during June – September 1996 time period generated using meteorological input from a mesoscale model run at 35 km resolution over north-eastern North America were also examined. Comparison of RDM V_d values to a variety of measurements of dry deposition velocities of SO₂, O₃, SO²⁻₄ and NHO₃ that have been reported in the literature demonstrated that RDM produces realistic results. Over northeastern NA RDM monthly averaged dry deposition velocities for SO₂ vary from 0.2 to 3.0 cm s⁻¹ with the highest deposition velocities over water surfaces. For O₃, the monthly averaged dry deposition velocities are from 0.05 to 1.0 cm s⁻¹ with the lowest values over water surfaces and the highest over forested areas. For HNO₃, the monthly averaged dry deposition velocities have the range of 0.5 to 6 cm s⁻¹, with the highest values for forested areas. For SO²⁻₄, they range from 0.05–1.5 cm s⁻¹, with the lowest values over water and the highest over forest. The monthly averaged dry deposition velocities for SO₂ and O₃ are higher in the growing season compared to the fall, but this behaviour is not apparent for HNO₃ and sulphate. In the daytime, the hourly averaged dry deposition velocities for SO₂, O₃, SO²⁻₄ and HNO₃ are higher than that in the nighttime over most of the vegetated area. The diurnal variation is most evident for surfaces with large values for leaf area index (LAI), such as forests. Based on the results presented in this paper, it is concluded that RDM V_d values can be combined with measured air concentrations over hourly, daily or weekly periods to determine dry deposition amounts and with wet deposition measurements to provide seasonal estimates of total deposition and estimates of the relative importance of dry deposition.     

风对定日镜影响的计算流体动力学数值模拟

利用linux系统下软件平台Fluent 6.3的并行计算技术和实用的结构网格划分方法,基于Reynolds 时均方程,分别采用两种湍流封闭模型:标准k-ε和MMK修正的k-ε模型,模拟计算了定日镜结构的平均风压系数、阻力、升力以及力矩系数和平均风流场.分析了定日镜镜体平均风压、平均风流场的分布规律和特点;并将数值计算结果与风洞试验进行了比较.结果表明,基于Fluent 6.3的MMK修正的k-ε模型较之标准k-ε模型有更好的预测效果.     

Dynamic behaviour of direct spring loaded pressure relief valves in gas service: II reduced order modelling

A previous study of gas-service direct-spring pressure relief valves connected to a tank via a straight pipe is continued by deriving a reduced-order model for predicting oscillatory instabilities such as valve flutter and chatter. The reduction process uses collocation to take into account a finite number N of acoustic pressure waves within the pipe, resulting in a set of 2N+3 ordinary differential equations. Following a novel non-dimensionalization, it is shown analytically that the model can exhibit, at experimentally realistic parameter values, instabilities associated with coupling between the valve and acoustic waves in the pipe. The thresholds for each instability are such that for a given flow rate, the first mode to go unstable as the inlet pipe length increases is the quarter-wave mode, then a three-quarter wave, a 5/4-wave etc. Thus the primary mode of instability should always be due to the quarter wave. In the limit of low flow rates, a simple approximate expression is found for the quarter-wave instability threshold in the form of inlet pipe length against mass flow rate. This threshold curve is found to agree well with simulation of the full model. For higher flow rates there is a need to include fluid convection, inlet pressure loss and pipe friction in order to get good agreement. The reduced model enables the dependence of the stability curve on key dimensionless physical parameters to be readily computed.     

Development and Operational Testing of a Super‐Ensemble Artificial Intelligence Flood‐Forecast Model for a Pacific Northwest River

Coastal catchments in British Columbia, Canada, experience a complex mixture of rainfall‐ and snowmelt‐driven contributions to flood events. Few operational flood‐forecast models are available in the region. Here, we integrated a number of proven technologies in a novel way to produce a super‐ensemble forecast system for the Englishman River, a flood‐prone stream on Vancouver Island. This three‐day‐ahead modeling system utilizes up to 42 numerical weather prediction model outputs from the North American Ensemble Forecast System, combined with six artificial neural network‐based streamflow models representing various slightly different system conceptualizations, all of which were trained exclusively on historical high‐flow data. As such, the system combines relatively low model development times and costs with the generation of fully probabilistic forecasts reflecting uncertainty in the simulation of both atmospheric and terrestrial hydrologic dynamics. Results from operational testing by British Columbia's flood forecasting agency during the 2013‐2014 storm season suggest that the prediction system is operationally useful and robust.     

Modelling and Prediction of Diesel Engine Performance using Relevance Vector Machine

Diesel engines are being increasingly adopted by many car manufacturers today, yet no exact mathematical diesel engine model exists due to its highly nonlinear nature. In the current literature, black-box identification has been widely used for diesel engine modelling and many artificial neural network (ANN) based models have been developed. However, ANN has many drawbacks such as multiple local minima, user burden on selection of optimal network structure, large training data size, and over-fitting risk. To overcome these drawbacks, this article proposes to apply an emerging machine learning technique, relevance vector machine (RVM), to model and predict the diesel engine performance. The property of global optimal solution of RVM allows the model to be trained using only a few experimental data sets. In this study, the inputs of the model are engine speed, load, and cooling water temperature, while the output parameters are the brake-specific fuel consumption and the amount of exhaust emissions like nitrogen oxides and carbon dioxide. Experimental results show that the model accuracy is satisfactory even the training data is scarce. Moreover, the model accuracy is compared with that using typical ANN. Evaluation results also show that RVM is superior to typical ANN approach.