210m钢筋混凝土烟囱控制爆破拆除数值模拟研究

通过采用LS-DYNA动力学有限元程序,模拟210 m钢筋混凝土烟囱的控制爆破拆除倒塌过程。采用数值模拟方法,不仅可以对控制爆破拆除工程中构筑物倾倒、破坏的重要影响因素进行分析,对有关理论研究结果的正确性和有效性进行验证,还能优化爆破拆除方案、预测实际爆破拆除效果,提高爆破拆除设计与施工的经济性、可靠性和安全性。     

珠江口夏季海陆源有机碳的模拟研究——分布特征、贡献比重及其迁移转化过程

基于经过验证的三维水动力-水质模型,对珠江口夏季有机碳进行海陆源区分,并对海陆源有机碳的分布特征、贡献比重及其通量过程进行研究.结果表明,水平方向上,珠江口夏季陆源（海源）有机碳浓度从口门到外海逐渐降低（升高）,在表、底层海水中平均浓度分别为1.45和0.87mg/L（0.97和1.05mg/L）;垂直方向上,在层化水域陆源（海源）有机碳浓度从上到下逐渐递减（升高）,在非层化水域海陆源有机碳浓度垂向分布较为均匀.珠江口夏季海源有机碳贡献率表层海水低于底层海水,平均贡献率为48.26%,沿向海方向海源有机碳贡献率逐渐增加--从内伶仃洋水域的4.43%逐渐提升到外伶仃洋东侧水域的81.20%.珠江口水动力条件复杂,在径流、潮汐、季风等因素的作用下陆源有机碳向海输送且向海输送量逐渐递减;海源有机碳在不同水域动力输送特征不同,西南水域向海输送,向海输送量逐渐递增;东北水域向岸输送,向岸输送量逐渐递减.陆源有机碳生化反应活性较弱,只有小部分被生化过程消耗,其迁移转化主要由沉降过程控制,而海源有机碳的迁移转化,则由口门的动力输送过程主控向外海的生化耗碳过程主控过渡.此外,海源有机碳沉降作用明显低于陆源有机碳,生化作用明显高于陆源有机碳.     

双区静电除尘器的数值模拟研究

采用数模拟的方法研究了双区静电除尘器内流场分布、颗粒荷电及颗粒运动等难以直接测量的物理过程,构建了双区静电除尘过程完整的数值模型.采用泊松方程、电流连续性方程和匀强电场方程描述电场,采用N-S方程和雷诺应力标准湍流模型描述流场,采用拉格朗日法描述颗粒运动轨迹.通过截面风速与颗粒去除率的模拟值与实验值的对比,验证了数值模型在模拟内部流场和颗粒运动时的准确性.数值模拟结果表明：双区静电除尘器内部流场分布对入口风速的变化非常敏感;颗粒荷电方式占比由颗粒粒径决定;荷电区内颗粒向极板的趋近过程由流体曳力和电场力共同完成,收尘区内的趋近过程则由电场力主导;入口流速通过改变颗粒前进速度和内部流场形态来影响颗粒运动轨迹.     

考虑边界条件不确定性的地下水污染风险分析

为分析边界条件不确定性对地下水污染质运移数值模拟模型输出结果的影响,运用Monte Carlo方法对一算例进行阐明,并从污染风险预报方面对模拟结果进行分析.为减少重复调用模拟模型产生的大量计算负荷,将边界条件（第一类边界条件-水头值）作为随机变量,建立地下水污染质运移数值模拟模型的Kriging替代模型,在保证较高精度的同时,实现了Monte Carlo模拟.结果表明：边界条件的不确定性,对地下水污染质运移数值模拟模型预报的结果有很大影响,考虑与未考虑边界条件不确定性得到的研究区污染羽分布差别较大.对地下水污染质运移数值模拟模型的Monte Carlo模拟结果进行统计与分析,可以评估研究区观测井1,2,3污染物浓度预报结果的可靠程度,并且可以预报出研究区观测井1,2,3遭受不同程度污染的风险.     

Analysis of pollutant levels in central Hong Kong applying neural network method with particle swarm optimization

Air pollution has emerged as an imminent issue in modernsociety. Prediction of pollutant levels is an importantresearch topic in atmospheric environment today. For fulfillingsuch prediction, the use of neural network (NN), and inparticular the multi-layer perceptrons, has presented to be acost-effective technique superior to traditional statisticalmethods. But their training, usually with back-propagation (BP)algorithm or other gradient algorithms, is often with certaindrawbacks, such as: 1) very slow convergence, and 2) easilygetting stuck in a local minimum. In this paper, a newlydeveloped method, particle swarm optimization (PSO) model, isadopted to train perceptrons, to predict pollutant levels, andas a result, a PSO-based neural network approach is presented. The approach is demonstrated to be feasible and effective bypredicting some real air-quality problems.     

Trihalomethanes in Drinking Water of Greater Québec Region (Canada): Occurrence, Variations and Modelling

The levels of trihalomethanes (THMs) – the main species of by-product from water chlorination – were monitored in thedistribution systems of the five major drinking water utilitiesof the greater area of Québec City in order to investigate andmodel their occurrence on a spatial and seasonal basis. Data forTHMs and other water quality and operational parametersassociated with their formation were generated through a 16 monthsampling program involving several sites representing variablewater residence times, from the plant to the system extremity.The results demonstrate that the differences in measured THMlevels between the five utilities are mainly due to the variablequality of raw waters, the type of water treatment process beingused and the type and levels of applied disinfectant. Dependingon the utility, average THM levels were from 1.3 to 2.5 timeshigher in the system extremities than in the water leaving thetreatment plant. Also, average levels of THMs measured in summerat the distribution system extremities were, depending on theutility, from 2.5 to 5 times higher than the average levelsmeasured in winter. The seasonal differences were found to besignificantly greater than those observed by others in waterutilities in the United States and Europe and are explained inlarge part by the considerable changes, over the year, in thequality and temperature of surface waters in Southern Québec. Forthe five utilities under study, multivariate regression modelswere developed in order to predict spatial and seasonalvariations of THMs. Both residual chlorine demand and temperaturewere found to be better, statistically, as predictors for THMoccurrence. The usefulness of the developed models for routineand long term water quality management, as well as for assessmentof human exposure to THMs, are also discussed.     

Study on the effect of porous fence on air quality and traffic noise level around a double-decked road structure

Fence for traffic noise control sometimes causes adverse effect on air pollution. Thus in this study, performance of porous fence as a tool for control of both air pollution and noise pollution was evaluated. A two-dimensional numerical model for flow and pollutant concentration and an analytical model for traffic noise were utilized in the analysis of a double-decked road structure with fences only at ground (Case 1) and at both ground and upper deck (Case 2). Porous fences were assumed only at the ground level since the solid fences at the upper deck usually leads to desirable result on air pollution. Effects of the variable porosity on air quality and noise level near road were evaluated. Obtained results showed: (1) flow pattern in leeward of fence was drastically changed at 40–50% porosity in Case 1 and 50% in Case 2. The porosity larger than 40% excluded presence of a circulation behind the fence. (2) Effect of porous fence on air pollution was different in Cases 1 and 2. In Case 1, the porous fence generally resulted in the reduction of air pollution at the ground level; on the other hand, in Case 2, it rather led to increase of the concentration. (3) Traffic noise level was also largely changed by the porosity of the fence; an example of simultaneous evaluation of the effects of porous fence on both air and noise pollution in Case 1 showed that the fence of 60% porosity leads to reduction of air pollution by 20% compared with solid fence case, and reduction of noise pollution by 4–6% in dB compared with no fence case, at l m high and 10 m from the road.     

linking various aspects of atmospheric change through a systems analysis of food

Although interdisciplinary collaboration to address a singleenvironmental problem is more common than in the past, all toooften the significant atmospheric problems of our day such asstratospheric ozone depletion, acidic deposition or climaticchange are addressed on a single issue basis. Systems analysis isa way of looking at a problem in a holistic, integrated fashionthrough including as many as practicable of the importantcomponents, and the linkages among them. Systems analysisoften begins with a conceptual model which, even if lackingquantification, is a useful means of changing ones thinking to amulti-issue approach. If possible, conceptual models areoperationalized by quantification (using the best availablescientific knowledge) of the stocks and flows of the relevantcomponents of the problem, and the processes that are involved.In this paper, a systems approach to food production is used tolink various atmospheric issues such as regional acidification andclimatic change. A spreadsheet model of food demand andproduction in various world regions examined the possible effectof atmospheric change on how much food we can grow, andwhether or not we may be able to meet the increased demand inthe year 2025. Using relatively modest changes in factors ofagricultural production, the spreadsheet model calculated globalshortfalls by the year 2025 of the order of 10 to 20% in someimportant agricultural crops, despite the improvements in cropproduction factors that are envisaged by the Food andAgricultural Organization from now until the year 2010, and thatwere extrapolated in this paper to 2025. The model alsocalculated that climatic change in combination with eithertropospheric ozone or increased UV-B radiation caused bydepletion of the stratospheric ozone layer may in general makethe situation worse than in the case of climatic change alone.Given the large uncertainties in the input data, the results in thispaper should not be viewed as predictions but rather as anexample of taking a relatively simple systems approach to foodproduction using a spreadsheet model, and calculating the effectsthat various aspects of atmospheric change might have upon it.Therefore, it is extremely important to know the effects uponcrop production factors of climatic change, tropospheric ozoneand increased UV-B radiation not only as individual issues, butalso of their combined effect since it is probable that in manyregions they will occur in combination.     

Application of CFD Methods for Modelling in Air Pollution Problems: Possibilities and Gaps

Different urban air pollution problems deal with complex structure of air flows and turbulence. For such problems the Computer Fluid Dynamics (CFD) methods become widely used. However, this approach despite a number of advantages has some problems. Experience of use of CFD tools for development of models and suggestions of their applications for a local scale air pollution over a complex terrain and stable stratification are discussed in this paper, including: Topography and complex geometry: choose of the co-ordinate system and computer grid; Turbulence closure for air pollution modelling: modified k- model for stable stratified ABL; Boundary conditions for vertical profiles of velocity for stable-stratified atmosphere; Effects of the radiation and thermal budget of inclined surfaces to dispersion of pollutants; Artificial sources of air dynamics and circulation.Some examples of CFD applications for air pollution modelling for a flat terrain, mountainous area, mining open cast and indoor ventilation are discussed. Modified k- model for stably-stratified ABL is suggested. Due to the isotropic character of the k- model a combination of it in vertical with the sub-grid turbulence closure in horizontal can be more suitable for ABL. An effective scheme of boundary conditions for velocity profiles, based on the developed similarity theory for stable-stratified ABL, is suggested. Alongside with the common studies of atmospheric dispersion, the CFD methods have also demonstrated a good potential for studying anthropogenic and artificial-ventilation sources of air dynamic and circulation in local-scale processes of air pollution.     

Multipoint source method in air pollution modelling of cold start emission

The paper presents a new method of air pollution modelling on a micro scale. For estimation of concentration of car exhaust pollutants, each car is treated as an instantaneous moving emission source. This approach enables us to model time and spatial changes of emission, especially during cold and cool start of an engine. These stages of engine work are a source of significant pollution concentration in urban areas. In this work, two models are proposed: one for the estimation of emission after cold start of the engine and another for the prediction of pollutant concentration. The first model (defined for individual exhaust gas pollutants) enables us to calculate the emission as a function of time after the cold or cool start, ambient temperature and average speed of motion. This model uses the HBEFA database. The second mathematical model is developed in order to calculate the pollutant dispersion and concentrations. The finite volume method is applied to discretise the set of partial differential equations describing wind flow and pollutant dispersion in the domain considered. Models presented in this paper can be called short-term models on a small spatial scale. The results of numerical simulation of pollutant emission and dispersion are also presented.