高烈度地震区隧道软硬围岩交接段刚柔并济抗减震技术研究*

为提高高烈度地震区隧道抗震性能，以某铁路隧道为研究背景，分析3种抗减震措施下隧道不同监测点隧道拱顶沉降、边墙收敛、衬砌结构PGA及最小安全系数，通过对比分析得到最优抗减震措施。结果表明:相比于工况1，工况2隧道拱顶沉降减小10.54%~81.10%，边墙收敛减小13.92%~78.77%，衬砌结构PGA减小31.42%~72.02%，最小安全系数增加18.04%~66.13%；相比于工况1，工况3结构拱顶沉降减小3.04%~18.02%，边墙收敛减小4.70%~32.00%，PGA增加13.95%~27.48%，最小安全系数增加7.49%~30.99%；工况4即“减震层+SFRC衬砌”刚柔并济法，相比于工况1，隧道拱顶沉降减小18.46%~83.98%，结构边墙收敛减小17.54%~85.47%，PGA减小30.00%~69.98%，最小安全系数增加47.95%~83.56%；4种工况抗减震性能由高到低依次为:工况4＞工况2＞工况3＞工况1。研究结果可为隧道软硬围岩交接段抗震设防提供理论参考。     

中国土壤环境监测方法现状、问题及建议

综述了目前中国现行的土壤环境监测国家标准方法和环保、农业、林业等行业标准方法,指出国家标准和环保行业标准方法侧重于土壤污染物的检测,而农业和林业标准方法侧重于土壤营养元素及其有效态、理化指标的检测。针对现行标准方法存在的一些问题(如检测的土壤污染物种类少、部分方法先进性不足、土壤环境监测的基础研究薄弱以及方法的标准化尚待完善等),提出加强土壤监测标准方法的顶层设计、合理增加土壤污染物的控制种类,及时更新方法、发展多组分测定方法,加强标准方法研究的系统性、协调性,以及逐步增加原位监测标准方法等建议,为土壤监测技术的发展提供借鉴和参考。     

模糊综合评价法在钢铁企业安全投资合理性评价中的应用

为了对钢铁企业安全投资进行模糊综合评价,建立了钢铁企业安全投资的评价体系,确定各因素的权重。得出模糊综合评价矩阵,可对各因素进行评价分析;得出某钢铁企业安全投资现状分数为83.9分,等级为较好,需着重加强安全培训、劳保品、工业卫生等人因素方面的投资;在环境方面的投资较合理。     

多波长法用于减小浊度对水源水中甲醛测定结果的影响

比较了减小水样浊度对样品结果影响的各种方法,包括过滤法、双波长法、三波长法,3种方法均基于乙酰丙酮分光光度法,测定波长均为414 nm。结果表明,以480 nm为参比波长的双波长法所得方法检出限为0.027 mg/L,采用470 nm与360 nm、460 nm与370 nm、450 nm与380 nm 3对参比波长的三波长法测得方法检出限为0.025~0.028 mg/L,这些方法用于检测0.100 mg/L标准点样品时,检测结果 RSD介于8.0%~8.6%。双波长法适合低浊度样品的直接分析,而浊度较高或双波长法测得结果大于方法检出限时,应采用三波长法进行定量分析,他们的使用有助于提高方法的准确度及减少工作量。用于地表水样品分析时,0.200、0.400 mg/L加标样品的回收率介于90.3%~101%,对应RSD介于0.0%~4.2%。     

城市给水管网优化设计研究

研究了几种典型的城市给水管网优化设计数学模型,并给出了求解方法,指出在给水管网系统的优化设计中进一步完善广义简约(GRG)算法的必要性.     

企业安全管理体系标准模式的比较研究

采用对比分析法和实证分析法,对当前国内外流行的企业安全管理体系标准模式及其评价方法进行比较研究,旨在把握诸多标准模式的原则、路径、结构、方法和共性特征及其可以发挥的具体优点,将研究的标准模式的评价方法归纳为两大类即体系认证审核法和综合考评打分法,并对两类评价方法的优缺点进行剖析。体系认证审核法的优点是过程方法、符合性及抽样,考评打分法则提供了安全绩效准则。对吸收融合两类评价方法的优点形成综合性评价方法的途径和方式进行了探讨,为企业建立有效、适用的安全管理体系提供了依据。     

Analysis of the Trend and Seasonal Cycle of Carbon Monoxide Concentrations in an Urban Area (4 pp)

Background, Aim and Scope Air quality is an field of major concern in large cities. This problem has led administrations to introduce plans and regulations to reduce pollutant emissions. The analysis of variations in the concentration of pollutants is useful when evaluating the effectiveness of these plans. However, such an analysis cannot be undertaken using standard statistical techniques, due to the fact that concentrations of atmospheric pollutants often exhibit a lack of normality and are autocorrelated. On the other hand, if long-term trends of any pollutant’s emissions are to be detected, meteorological effects must be removed from the time series analysed, due to their strong masking effects. Materials and Methods The application of statistical methods to analyse temporal variations is illustrated using monthly carbon monoxide (CO) concentrations observed at an urban site. The sampling site is located at a street intersection in central Valencia (Spain) with a high traffic density. Valencia is the third largest city in Spain. It is a typical Mediterranean city in terms of its urban structure and climatology. The sampling site started operation in January 1994 and monitored CO ground level concentrations until February 2002. Its geographic coordinates are W0°22′52″ N39°28′05″ and its altitude is 11 m. Two nonparametric trend tests are applied. One of these is robust against serial correlation with regards to the false rejection rate, when observations have a strong persistence or when the sample size per month is small. A nonparametric analysis of the homogeneity of trends between seasons is also discussed. A multiple linear regression model is used with the transformed data, including the effect of meteorological variables. The method of generalized least squares is applied to estimate the model parameters to take into account the serial dependence of the residuals of this model. This study also assesses temporal changes using the Kolmogorov-Zurbenko (KZ) filter. The KZ filter has been shown to be an effective way to remove the influence of meteorological conditions on O₃ and PM to examine underlying trends. Results The nonparametric tests indicate a decreasing, significant trend in the sampled site. The application of the linear model yields a significant decrease every twelve months of 15.8% for the average monthly CO concentration. The 95% confidence interval for the trend ranges from 13.9% to 17.7%. The seasonal cycle also provides significant results. There are no differences in trends throughout the months. The percentage of CO variance explained by the linear model is 90.3%. The KZ filter separates out long, short-term and seasonal variations in the CO series. The estimated, significant, long-term trend every year results in 10.3% with this method. The 95% confidence interval ranges from 8.8% to 11.9%. This approach explains 89.9% of the CO temporal variations. Discussion The differences between the linear model and KZ filter trend estimations are due to the fact that the KZ filter performs the analysis on the smoothed data rather than the original data. In the KZ filter trend estimation, the effect of meteorological conditions has been removed. The CO short-term componentis attributable to weather and short-term fluctuations in emissions. There is a significant seasonal cycle. This component is a result of changes in the traffic, the yearly meteorological cycle and the interactions between these two factors. There are peaks during the autumn and winter months, which have more traffic density in the sampled site. There is a minimum during the month of August, reflecting the very low level of vehicle emissions which is a direct consequence of the holiday period. Conclusions The significant, decreasing trend implies to a certain extent that the urban environment in the area is improving. This trend results from changes in overall emissions, pollutant transport, climate, policy and economics. It is also due to the effect of introducing reformulated gasoline. The additives enable vehicles to burn fuel with a higher air/fuel ratio, thereby lowering the emission of CO. The KZ filter has been the most effective method to separate the CO series components and to obtain an estimate of the long-term trend due to changes in emissions, removing the effect of meteorological conditions. Recommendations and Perspectives Air quality managers and policy-makers must understand the link between climate and pollutants to select optimal pollutant reduction strategies and avoid exceeding emission directives. This paper analyses eight years of ambient CO data at a site with a high traffic density, and provides results that are useful for decision-making. The assessment of long-term changes in air pollutants to evaluate reduction strategies has to be done while taking into account meteorological variability     

基于蒙特卡罗法的煤巷锚杆支护结构可靠性分析

应用工程结构可靠性理论,建立煤巷锚杆支护结构可靠性模型,针对其结构稳定性的极限状态功能函数高度非线性的特征,采用蒙特卡罗法在Matlab环境下直接产生服从各相应概率分布函数的随机变量数组计算其结构可靠度,编程过程简化,计算速度快,精度高,且不受极限状态方程非线性、随机变量非正态的限制,开辟了煤巷锚杆支护结构可靠度计算的新途径。建立了支护参数与可靠度的关系,指出了提高煤巷锚杆支护结构可靠度的方法和措施,为煤巷锚杆支护参数设计和优化提供了科学依据。     

生态足迹影响因子的定量分析

人口的膨胀和人类工业化进程的加剧，使得人类向自然界获取越来越多的资源，同时向环境源源不断的输入废弃物，已经严重超过了自然生态系统的供给能力和环境容量，生态环境日益恶化，水土流失、草场退化、植被消亡、生物多样性锐减、全球变暖等情况已经严重到难以遏制的地步，危及到人类自身的生存。在和平与发展成为世界两大主题的今天，人们越来越关注可持续发展的问题。在现有资料的基础上，利用主成分分析方法，定量地讨论了中国各省（区市）1999年生态足迹大小与其影响因子间的关系。结果表明，生态足迹的大小是各省（区市）的大中型企业个数、全社会固定生产投资等众多因子共同作用的结果，其中总人口和GDP是生态足迹大小的主要影响因子，其因子载荷量分别达到了0.940和0.913。值得一提的是非农业人口与生态足迹的相关系数超过了农业人口，这说明由于消费模式和生活水平等的差异，非农业人口对生态足迹的影响大于农业人口对生态足迹的影响。在此基础上建立了生态足迹影响因子的多元线性回归模型，以期为生态足迹在进行区域可持续发展评价的方法上提供新的思路。