提升汇流环湿热环境适应性方法研究

目的提高汇流环在湿热环境下的适应能力。方法实物解剖,观察汇流环绝缘材料损坏情况、碳粉堆积情况,在不同温度、湿度下测试绝缘材料绝缘度、抗电强度,碳粉堆积和导电情况,比对不同绝缘材料性能,并找出最适合的绝缘材料,比对滚动汇流环、碳刷组件、刷丝组件,找到解决碳粉堆积的方法。结果汇流环受湿热影响会从接缝处和电缆连接处进入湿气,温度、湿度的上升会使得原绝缘材料性能下降,长时间使用汇流环,碳粉会在汇流环内堆积并受到湿热的影响而导电,局部密封汇流环可以减少湿气进入。PPO材料性能优异,可以替换原绝缘材料从而减少湿热的影响,使用刷丝组件替代碳刷可以避免碳粉的产生。结论综合运用局部密封、绝缘材料改进、碳刷组件改进三种措施,可以有效提高汇流环在湿热环境下的适应能力。     

一种模拟动力学边界条件的环境振动试验方法研究

目的提高环境振动试验的可靠性。方法以某典型钛合金蜂窝夹芯壁板试验件为例,提出一种模拟试验件动力学边界条件的试验方法,在试验件周围引入弹性连接件,再通过刚性转接工装与振动台台面连接,以试验件在试验安装状态下的共振频率及振型节线位置为优化目标,以弹性连接件的外形尺寸及厚度为优化变量,对弹性连接件进行优化设计,从而模拟试验件真实的动力学边界条件。结果弹性连接件的优化设计使得试验件在试验安装状态下前两阶共振频率与试验要求相差小于8%,而且振型节线位置与试验要求基本重合,达到了模拟试验件真实动力学边界条件的设计目标。结论对于壁板类试验件,在传统刚性夹具的基础上引入弹性连接件的试验方法,可以较好地模拟试验件真实动力学边界条件,提高环境振动试验的可靠性,并且这种方法对试验费用及试验周期影响较小,具有良好的工程应用前景。     

环境升温过程对常温固化环氧树脂热力学性能的影响

目的提高常温固化环氧树脂体系的高温使用性能。方法采用常温固化剂T31、中温固化剂IPDA以及高温固化剂DDM作为混合固化剂,对E-44型和AG-80型混合环氧树脂体系进行常温固化反应,并分析环境升温过程对固化物热力学性能的影响。通过DMA分析、热变形测量、固化度测试,分别评价室温固化环氧树脂在环境升温过程前后的玻璃化转变温度、热变形量及体系内部的固化反应程度变化,并通过吸水率测试和弯曲强度测试对玻璃纤维布增强常温固化环氧树脂基复合材料的耐湿热性能以及高温条件下的力学性能进行分析。结果环氧树脂常温固化物的tg为85.21℃,经1.5℃/min的平均升温速率加热至90℃之后,该环境升温过程使固化物的固化度增大至92%以上,tg增长为132.06℃的同时热变形温度增大。其复合材料耐湿热性能提高,且100℃时弯曲强度的保持率为65%,对于加热至120℃的环境升温过程,固化物的固化度接近96%,tg增长为144.45℃的同时热变形温度进一步提高,其复合材料耐湿热性能改善程度更加明显,且130℃时弯曲强度保持率仍接近60%。结论常温、中温、高温混合固化剂的合理复配有助于环氧树脂体系在环境升温变化的诱导条件下发生梯度式固化反应,使体系内部的交联固化程度迅速升至较高水平,可以有效提高其玻璃化转变温度,显著改善常温固化环氧树脂体系在高温条件下的热力学性能。     

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.     

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.     

Factors influencing Aerosol Characteristics over Urban Environment

Atmospheric aerosols are an important contributing factor to turbidity in urban areas besides having impact on health. Aerosol characteristics show a high degree of variability in space and time as anthropogenic share of total aerosol loading is quite substantial and is essential to monitor the aerosol features over long time scales. In the present study extensive observations of columnar aerosol optical depth (AOD), total columnar ozone (TCO) and precipitable water content (PWC) have been carried over a tropical urban city of Hyderabad, India. Significant variations of AOD have been observed during course of the day with low values of AOD during morning and evening hours and high values during afternoon hours. Spectral variation of AOD exhibits high AOD at smaller wavelengths and vice versa except a slight enhancement in AOD at 500 nm. Anomalies in AOD, particulate matter and black carbon concentrations have been observed during May, 2003. Back trajectory analysis of air mass during these episodes suggested variation in air mass trajectories. Analysis of the results suggests that air trajectories from land region north of study area cause high loading of atmospheric aerosols. The results are discussed in the paper.     

Higher Plants As Bioindicators Of Sulphur Dioxide Emissions In Urban Environments

The evaluation of certain vascular plants that grow in the city of Madrid as biomonitors of SO₂ air pollution in urban environments has been carried out. Total concentration of sulphur in leaves of the chosen higher plants as well as other parameters in close relation to this contaminant (visible injury symptoms, chlorophyll a- and b-content and peroxidase activity) have been determined in order to study the spatial distribution and temporal changes in SO₂ deposition. Results obtained show that coniferous species such as Pinus pinea, were more sensitive to SO₂ atmospheric concentration than leafy species as Quercux ilex subspecies ballota and, in the same way, bush species, such asPyracantha coccinea and Nerium oleander, were more sensitive than wooded species, such as Cedrus deodaraandPinus pinea, respectively. There is a higher accumulation of sulphur in vegetable species located near highways and dense traffic incidence roads and near areas with high density of population. The minimum values for accumulation of SO₂ were registered in winter and spring seasons (from January to April) due to the vegetative stop; while maximum values are obtained during the summer season (from June to September), due to the stoma opening. The highest increments in sulphur concentration, calculated as the difference between two consecutive months, are obtained in May and June for all considered species except forCedrus deodara and Pyracantha coccinea, both species have few seasonal changes during the whole year. Some species are more sensitive to natural washing than others, showing a decrease in sulphur concentration after rainfall periods.     

土壤重金属污染的灰色模糊评价

以灰色聚类为基础，提出了灰色模糊聚类分析法，并将其应用于土壤环境质量评价中，经实例分析表明，这是一种较为简便，合理、有效的评价方法。     

昌吉州生态环境现状调查

通过对昌吉州近年生态环境保护工作及建设的概述,并对“八五”末期和“九五”末期生态环境现状的对比,说明昌吉州生态环境存在的问题,为生态环境保护规划和生态建设决策提供可靠的依据。     

A Study on Transfer Factors of 60Co and 65Zn from Soil to Plants in the Tropical Environment of Bangladesh

Soil to plant transfer factor (TF) of⁶⁰Co and ⁶⁵Zn was determined fromradioisotope experiments on plants grown in pots underoutdoor ambient tropical conditions for three growingseasons (1995–1998). The TFs were obtained fordifferent plants/crops such as, rice, bean, peanutspineapple, cabbage, tomato, spinach and grass. Theaverage TF values of ⁶⁰Co are found to be 0.087,0.15, 0.12, 0.67, 0.28, 0.79, 1.03 and 0.34respectively for the above mentioned plants/crops. Incase of ⁶⁵Zn, the average TF values are found tobe 2.24, 1.17, 0.89, 1.09, 0.78, 1.34, 2.92 and 1.78,respectively, for the above mentioned plants/crops. Thedata will be useful to assess the radiation exposureto man associated with the releases of radionuclidesfrom nuclear facilities by means of radiologicalassessment models that require transfer factors asinput parameters to predict the contamination ofradionuclides in foodchain.