加速腐蚀当量加速关系研究方法综述

为了进一步研究当量加速关系,归纳了现有腐蚀损伤当量化的研究方法,详细介绍了基于电化学原理、物理参量和力学损伤的当量折算法,讨论了各种方法的优劣和所适用范围。基于电化学原理的当量加速关系研究方法适合用于制定飞机金属结构加速试验环境谱,以物理参量为基准的当量折算法适用于建立疲劳关键部位、腐蚀关键部位的涂层及金属基体等各种加速试验环境谱的当量加速关系,力学损伤对比法适合用于结构疲劳关键部位。最后得出针对不同材料、不同部位应该采用不同的当量加速关系的结论。     

基于相关性分析的PCBA热力学模型修正

目的精确且高效地对印制电路板组件热力学模型进行修正。方法采用基于拉丁超立方抽样试验设计和Speraman等级相关系数计算公式的相关性分析方法,找出电子产品热仿真试验中对元器件表面温度值影响较大的输入参数,然后进一步分析得出输入与输出之间的函数关系。在此基础上给出印制电路板组件(PCBA)热力学模型修正的一般方法流程。最后利用该方法对某航空电子产品中一块PCBA的热力学模型进行修正。结果修正结果较精确且只调用2次有限元软件。结论该热模型修正方法具有较高的精确性和高效性,可推广用于工程实践。     

郁江、黔江和浔江广西桂平段水质变化趋势分析

根据2003-2012年水质监测资料,采用秩相关系数法对郁江、黔江和浔江广西桂平段水质变化趋势进行分析。结果表明,黔江和浔江水质呈明显好转趋势;郁江水质呈好转趋势,但不明显。提出了继续加强水污染防治工作的建议。     

大连星海地区环境空气中挥发性有机物的臭氧生成潜势研究

以该实验的观测资料为基础,通过数据分析表明,对大连星海地区OH自由基消耗的主要环境VOCs组分是烯烃类物质,对O3生成潜势贡献最高的环境VOCs组分是芳香烃类物质;综合LiOH及OFP值评价,识别影响大连星海地区O3生成的关键环境VOCs反应活性物种为丙烯、甲苯、间对二甲苯等物质。     

基于距离相关系数和支持向量机回归的PM2.5浓度滚动统计预报方案

针对目前空气质量统计预报方法存在的主要缺陷,本文提出了距离相关系数和支持向量机回归相结合的统计预报方案DC-SVR.利用淮安市2013年1—12月PM_(2.5)观测资料和常规气象观测资料,首先在选入预报当日气象要素的基础上,增加选取前期污染物和气象要素作为预报因子,再采用距离相关系数分季节从预报因子中筛选出重要预报因子,最后采用支持向量机回归对PM_(2.5)浓度值进行逐日滚动统计预报.研究发现,淮安地区气温和气压对PM_(2.5)的距离相关性要高于其他气象要素,夏秋季PM_(2.5)与气象要素的距离相关性较春冬季好.基于距离相关系数和支持向量机回归建立DC-SVR模型,PM_(2.5)的试预报值和实测值的全年相关系数高达0.76,平均偏差仅为1.13μg·m~(-3),平均绝对误差为23.47μg·m~(-3).通过与支持向量机回归、人工神经网络的统计预报效果对比,DC-SVR模型有效降低预报因子维数且能自适应选取最佳参数,预报精度显著优于其他3种统计预报方案,可为业务化预报提供参考.     

2013-2015年上海市霾污染事件潜在源区贡献分析

统计分析2013-2015年上海市每个月不同空气质量等级天数比重,根据HYSPLIT（Hybrid Single Particle Lagrangian Integrated Trajectory）后向轨迹模型对3年内的12月份影响上海地区的污染气团进行了综合聚类分析和逐年聚类分析.在综合12次严重霾事件的后向轨迹基础上,结合上海实时公布的PM_2.5小时浓度资料,对潜在源贡献因子PSCF（Potential Source Contribution Function）和浓度权重轨迹CWT（Concentration-weighted Trajectory）进行分析与比较,研究重霾期间影响上海PM_2.5质量浓度的潜在源区及不同源区对PM_2.5质量浓度的贡献差异.结果显示,上海市3年期间12月份霾颗粒物外来源主要输送渠道为西北路径和北方路径,源自于西北方向的气团比重占总气团的50.4%,北方向的气团几乎都经过海洋后进入上海地区.影响上海地区PM_2.5质量浓度的潜在源区主要分布在安徽、江苏和山东地区,此外江西北部、浙江北部、河北南部及山西少部分地区也对重霾事件中的污染物颗粒有一定程度的贡献.     

水环境质量评价3种方法的应用对比

从众多水质评价方法中选取单项指数法、加权均值型指数法、模糊数学法进行介绍,并通过运用这3种方法对大汶河某年监测数据的平均值进行评价.经对比分析发现,加权均值型指数法是一种比较实用的水质评价方法,模糊数学法可以作为必要的补充.     

地下水环境中甲基叔丁基醚运移过程的动力学模型

建立了地下水环境中甲基叔丁基醚(MTBE)运移过程的变系数动力学模型,并对模型进行了验证和参数灵敏度分析.模拟结果表明,地下水流速和阻滞系数对于MTBE的运移过程影响最为显著,而水动力弥散系数的影响较小,忽略其变化不会对预测地下水环境中污染物运移的环境动力学行为造成太大误差.由此得到的结论可定量研究MTBE在地下水环境中的对流.扩散特征,还可为MTBE污染地下水的预测预报、修复治理等研究提供科学依据.     

RETRACTED ARTICLE: Environmental Impact Assessment of Industrial Structure Change in a Rural Region of China

As the embodiment of human activities, the change of regional industrial structure is an essential driving factor of global environmental change. Consequently, the research on the change of regional industrial structure and associated effects on the environment is one of the key issues of researches on sustainable development, human–environment relationship, and regional response to global environment change. However, compared to the flourish of researches on environmental impact assessment of industrial departments, few studies have been conducted to assess the environmental impact of regional industrial structure. In this study, based on a synthetic analysis of environmental disturbances of different industrial departments, the environmental impact coefficient of industrial department associated with the index of environmental impact of industrial structure was constructed, so as to make a quantitative assessment of environmental impact of the change of regional industrial structure. And the results of the case study in Lijiang City, a rural region of China, have showed that there are two obvious changes of industrial structure in the study area from 1992 to 2003, associated with a continuous decreasing of the index of environmental impact of industrial structure, which indicated a positive environmental effects of the change of regional industrial structure.     

Suitable error evaluation criteria selection in the wind energy assessment via the K-means clustering algorithm

In this paper, wind energy potential of four locations in Xinjiang region is assessed. The Weibull distribution as well as the Logistic and the Lognormal distributions are applied to describe the distributions of the wind speed at different heights. In determining the parameters in the Weibull distribution, four intelligent parameter optimization approaches including the differential evolutionary, the particle swarm optimization, and two other approaches derived from these two algorithms and combined advantages of these two approaches are employed. Then the optimal distribution is chosen through the Chi-square error (CSE), the Kolmogorov–Smirnov test error (KSE), and the root mean square error (RMSE) criteria. However, it is found that the variation range of some criteria is quite large, thus these criteria are analyzed and evaluated both from the anomalous values and by the K-means clustering method. Anomaly observation results have shown that the CSE is the first one should be considered to be eliminated from the consequent optimal distribution function selection. This idea is further confirmed by the K-means clustering algorithm, by which the CSE is clustered into a different group with KSE and RMSE. Therefore, only the reserved two error evaluation criteria are utilized to evaluate the wind power potential.