BIM技术在钢结构建筑抗震减灾管理中的应用

为提高钢结构建筑抗震减灾性能,降低建筑坍塌风险,研究BIM技术在钢结构建筑抗震减灾管理中的应用方法是非常必要的.利用BIM技术在钢结构建筑整体建造中的动态建模、可视化、信息共享管理以及抗震减灾性能检测等优势,在建筑抗震减灾管理决策阶段,选出最优方案,针对方案中影响建筑抗震减灾性能风险制定管理策略;在设计阶段,创建三维建...     

Dams in the Amazon: Belo Monte and Brazil’s Hydroelectric Development of the Xingu River Basin

Hydroelectric dams represent major investments and major sources of environmental and social impacts. Powerful forces surround the decision-making process on public investments in the various options for the generation and conservation of electricity. Brazil’s proposed Belo Monte Dam (formerly Kararaô) and its upstream counterpart, the Altamira Dam (better known by its former name of Babaquara) are at the center of controversies on the decision-making process for major infrastructure projects in Amazonia. The Belo Monte Dam by itself would have a small reservoir area (440 km²) and large installed capacity (11, 181.3 MW), but the Altamira/Babaquara Dam that would regulate the flow of the Xingu River (thereby increasing power generation at Belo Monte) would flood a vast area (6140 km²). The great impact of dams provides a powerful reason for Brazil to reassess its current policies that allocate large amounts of energy in the country’s national grid to subsidized aluminum smelting for export. The case of Belo Monte and the five additional dams planned upstream (including the Altamira/Babaquara Dam) indicate the need for Brazil to reform its environmental assessment and licensing system to include the impacts of multiple interdependent projects.     

环境影响后评价的最新进展与建议

结合《中华人民共和国环境影响评价法》的有关条款,探讨了环境影响后评价的概念、分类、适用对象、意义和内容,提出了环境影响后评价的管理和实施程序.结合多年的实践,分析了目前环境影响后评价工作在理论、方法和管理上存在的问题,提出了改进和完善的建议.案例实践表明,开展环境影响后评价有助于提高环境影响评价制度的有效性.     

电磁兼容测量结果可追溯性技术探讨

无线电波因其具有较强的方向性和反射性等传播特点,往往会引起电磁兼容测量结果的不稳定甚至有较大的偏差,如果不对测量过程中的测量和试验布置、试品的工况、记录报告等要素进行可追溯性分析和控制,势必会造成测量结果的随意和不确定性.因此在电磁兼容测量实验室,非常有必要对测量过程和测量结果进行可追溯性研究、分析和控制,一是提供准确可再现的测量数据,对客户负责,二是通过可追溯性控制,再现试验和测量过程,验证测量结果,对实验室的风险进行预见和预防.本文主要立求通过实际案例的分析,畅述和分析在电磁兼容测量实验室如何建立可追溯性的控制体系.     

Non-UV based germicidal activity of metal-doped TiO2 coating on solid surfaces

A stain-based screening method was developed to screen different catalyst coatings for their germicidal activity. A Baclight dead/live bacteria viability kit （invitrogen, molecular probes） was used for staining the cell. The screening was carried out following a standard procedure. This included loading cell suspension to solid surface and maintaining contact for 30 min, then staining with a mixture containing dyes. The stained cells were observed using an epifluorescent microscope and photographed with a CCD camera under UV. Metal-doped TiO2 coatings on AI plates were prepared and tested for non-UV germicidal activity without using UV. It was tested using model microorganisms such as Bakers Yeast （Saccharomyces cerevisiae）, Bacillus subtilis, Pseudomonas putida, and Escherichia coli. On the basis of the germicidal activity of catalyst and the degree of damage caused to the cells, the stained cells may appear green （viable）, green with red or yellow nuclei and yellow （compromised） or red （nonviable）. According to their stained color, cells were counted to calculate the percentage of dead, live, and compromised cells. Compromised cells are cells that grow very slowly after reculturing indicating a degree of reversible cell damage. Screening the germicidal activity using this staining method is accurate and efficient, and requires less time than the culture-based method. A modification to the procedure for measuring germicidal activity of rough surfaces or fibrous coatings was developed. Both TiO2 and metal-doped TiO2 （Ag, Pt, Au, Cu） possess non-UV based germicidal activity. The germicidal activity of TiO2 was found to be related with its wetting property and can be improved by UV irradiation before testing. It is not greatly affected by contact time, indicating a fast acting germicidal activity.     

Evaluating the impact of uncertainty and variability on the value chain optimization of a forest biomass power plant using Monte Carlo Simulation

Mathematical programming models have been used to optimize the design and management of forest bioenergy supply chains. A deterministic mathematical model is beneficial for making optimum decisions; however, its applicability to real-world problems may be limited because it does not capture all the complexities, including uncertainties in the parameters, in the supply chain. In this paper, a combination of Monte Carlo Simulation and optimization model is used to evaluate the impact of uncertainty in biomass quality, availability and cost, and electricity prices on the supply chain of a forest biomass power plant. The optimization model is a deterministic mixed integer non-linear model with monthly time steps over a 1-year planning horizon. Variability in biomass quality, i.e. moisture content (MC) and higher heating value (HHV), based on the historical data of a real case study is studied in detail and fitted probability distributions are used in the model, while for electricity prices different scenarios are considered. The results show that the impact of variability in the MC on profit is higher than that of uncertainty in HHV. It is observed that the annual profit ranges between $13.3 million and $17.9 million in the presence of all possible uncertainties while its average is $15.5 million. Uncertainty in biomass availability and cost and electricity price results in the risks of having annual profit of less than $14 million and low monthly storage levels.     

Monte Carlo analysis of field water flow comparing uni- and bimodal effective hydraulic parameters for structured soil

Soil structure critically affects the hydrological behaviour of soils. In this paper, we examined the impact of areal heterogeneity of hydraulic properties of a structured soil on soil ensemble behaviour for various soil water flow processes with different top boundary conditions (redistribution and drainage plus evaporation and infiltration). Using a numerical solution of the Richards' equation in a stochastic framework, the ensemble characteristics and flow dynamics were studied for drying and wetting processes observed during a time interval of ten days when a series of relatively intense rainfall events occurred. The effects of using unimodal and bimodal interpretative models of hydraulic properties on the ensemble hydrological behaviour of the soil were illustrated by comparing predictions to mean water contents measured over time in several sites at field scale. Although the differences between unimodal and bimodal fitting are not significant in terms of goodness of fit, the differences in process predictions are considerable with the bimodal soil simulating water content measurements much better than unimodal soil. We also investigated the relative contribution of the soil variability of each parameter on the variance of the water contents obtained as the main output of the stochastic simulations. The variability of the structural parameter, weighting the two pore space fractions in the bimodal interpretative model, has the largest contribution to water content variance. The contribution of each parameter depends only partly on the coefficient of variation, much more on the sensitivity of the model to the parameters and on the flow process being observed. We observed that the contribution of the retention parameters to uncertainty increases during drainage processes; the opposite occurs with the hydraulic conductivity parameters.     

苏里格气田试气队伍节能减排工作现状及改进建议

苏里格气田试气队伍因涉及数家企业单位,节能减排工作有其特殊性和复杂性。通过调查试气过程中的排污状况,分析了其节能减排工作中出现的几个问题,如计量粗放、管理薄弱、措施简单等,提出了健全管理制度,完善计量系统,鼓励技术研究,加强自主创新,创建统一平台,依靠丙方监管等措施,以促进其节能减排工作健康有序地发展。     

Heavy metal contamination from mining sites in South Morocco: Monitoring metal content and toxicity of soil runoff and groundwater

The aim of the present work is the assessment of metal toxicity in runoff, in their contaminated soils and in the groundwater sampled from two mining areas in the region of Marrakech using a microbial bioassay MetPLATE™. This bioassay is based on the specific inhibition of the β-galactosidase enzyme of a mutant strain of Escherichia coli, by the metallic pollutants. The stream waters from all sampling stations in the two mines were all very toxic and displayed percent enzyme inhibition exceeding 87% except SWA₄ and SWB₁ stations in mine C. Their high concentrations of copper (Cu) and zinc (Zn) confirm the acute toxicity shown by MetPLATE. The pH of stream waters from mine B and C varied between 2.1 and 6.2 and was probably responsible for metal mobilization, suggesting a problem of acid mine drainage in these mining areas. The bioassay MetPLATE™ was also applied to mine tailings and to soils contaminated by the acidic waters. The results show that the high toxicity of these soils and tailings was mainly due to the relatively concentration of soluble Zn and Cu. The use of MetPLATE™ in groundwater toxicity testing shows that, most of the samples exhibited low metal toxicity (2.7–45.5% inhibition) except GW3 of the mine B (95.3% inhibition during the wet season and 82.9% inhibition during the dry season). This high toxicity is attributed to the higher than usual concentrations of Cu (189 μg Cu l⁻¹) and Zn (1505 μg Zn l⁻¹). These results show the potential risk of the contamination of different ecosystems situated to the vicinity of these two metalliferous sites. The general trend observed was an increase in metal toxicity measured by the MetPLATE with increasing total and mobile metal concentrations in the studied matrices. Therefore, the MetPLATE bioassay is a reliable and fast bioassay to estimate the metals toxicity in the aquatic and solids samples.     

Spatial modelling of the probability of obtaining a detectable concentration of ammonia in Moreton Bay, Australia

Ammonia is an important water quality variable, which in excess, can be detrimental to waterways and their ecosystems. In the Ecosystem Health Monitoring Program in South-east Queensland ammonia is monitored monthly, however, often more than 50% of the ammonia observations in Moreton Bay are below detection limit, making it difficult to draw useful inferences. In this paper a clipped Gaussian random field is used to spatially model and map the probability of detectable concentration of ammonia. The methodology is applied to the Moreton Bay samples collected in February 2005. The results suggest that for this month the oceanic impacted areas have higher probability of detectable ammonia concentration than the areas closer to the main sources of anthropogenic inputs.