超长桩荷载－沉降曲线的拟合方法

本文提出一种超长桩Ｐ—ｓ曲线的拟合方程，并对该方程作了讨论。     

变电构架受损伤圆钢管杆件轴压极限承载力分析

以电力构架中常用的圆钢管杆件为研究对象,采用有限元计算和试验数据建立的回归模型方法,研究一般受损条件下杆件轴压极限承载力的变化情况。分析了凹陷深度、初弯曲、长细比和截面径厚比等参数对杆件极限承载力的影响,讨论了上述参数对荷载-轴向缩短关系的单独影响和综合影响。了解了多杆件极限承载力的特点,引入了受损杆件的折算刚度系数。所得结论为变电构架的可靠性分析和维修加固提供了依据。     

不排水强度的空间变异性及单桩承载力可靠性分析

对于土性随深度变化的情况,讨论了不排水剪切强度cu空间变异性的随机场概率统计模型.由于现有的土层随机场模型都是针对平稳随机场,即土性的随机分量的,所以首先要用回归的方法分离出趋势分量来,然后才能对随机分量进行模拟.认为在进行岩土工程可靠度分析时,不仅要考虑抽样所带来的误差,还要考虑土性本身的空间变异性.并用不排水剪强度cu的变异性来计算粘性土中单桩承载力的方差,旨在阐明随机场理论在岩土工程可靠性分析中的应用.最后用一个算例作了具体说明.     

钢纤维混凝土受压极限强度研究

根据试验结果,分析了钢纤维混凝土受压极限强度与钢纤维体积掺率、基体强度等级和纤维形状的关系。提出双因素、双参数计算模型,并通过对2 1 1组试验数据的回归分析,给出可以与《混凝土结构设计规范》相衔接、并适用于各等级基体强度的计算表达式。进一步分析了纤维形状对强度的影响,给出了表达式中纤维形状因子的简化取值建议。     

胜坨油田岩石三轴抗压强度的多元回归分析

针对胜坨油田高含水期出砂严重的实际情况，对该油田的储层砂岩进行了岩芯三轴抗压强度试验，获得了可靠的试验数据。通过对测井数据和岩芯试验数据分析比较，选择了几个与岩石三轴抗压强度密切相关的数据作变量，通过不断引入重要变量、检验旧变量和剔除不重要变量的方法，进行多元逐步回归分析，建立了岩石三轴抗压强度与井深、岩石密度、孔隙度、声波时差、杨氏模量等数据的回归关系式，用于现场计算地层岩石三轴抗压强度和指导防砂、压裂等油田开发措施的实施。     

Application of nonparametric regression methods to study the relationship between NO2 concentrations and local wind direction and speed at background sites

Background concentrations of nitrogen dioxide (NO₂) are not constant but vary temporally and spatially. The current paper presents a powerful tool for the quantification of the effects of wind direction and wind speed on background NO₂ concentrations, particularly in cases where monitoring data are limited. In contrast to previous studies which applied similar methods to sites directly affected by local pollution sources, the current study focuses on background sites with the aim of improving methods for predicting background concentrations adopted in air quality modelling studies. The relationship between measured NO₂ concentration in air at three such sites in Ireland and locally measured wind direction has been quantified using nonparametric regression methods. The major aim was to analyse a method for quantifying the effects of local wind direction on background levels of NO₂ in Ireland. The method was expanded to include wind speed as an added predictor variable. A Gaussian kernel function is used in the analysis and circular statistics employed for the wind direction variable. Wind direction and wind speed were both found to have a statistically significant effect on background levels of NO₂ at all three sites. Frequently environmental impact assessments are based on short term baseline monitoring producing a limited dataset. The presented non-parametric regression methods, in contrast to the frequently used methods such as binning of the data, allow concentrations for missing data pairs to be estimated and distinction between spurious and true peaks in concentrations to be made. The methods were found to provide a realistic estimation of long term concentration variation with wind direction and speed, even for cases where the data set is limited. Accurate identification of the actual variation at each location and causative factors could be made, thus supporting the improved definition of background concentrations for use in air quality modelling studies.     

照明工程中定性与定量之间的转换研究

为了建立照明工程中主观感觉量与客观物理量之间的关系，利用广义的韦伯一费昔勒定律把照明工程中的定性问题与定量问题联系起来，并对于照明工程实际应用问题，推导出了由客观物理量得到相应主观感觉量的近似计算式。对广告照明的实例验证表明，该近似计算式的计算精度较高，与实际情况更为吻合。利用该近似计算式，采用解方程的方法可以求得在给定满意度水平条件下对应的照明水平，即由指定的主观感觉量求出相应的客观物理量，从而可以更合理地指导照明工程设计。     

A parameterization of dust concentration (PM₁₀) of dust events observed at Erdene in Mongolia using the monitored tower data

Hourly mean time series of dust concentration (PM₁₀) measured at 3 m high and a sonic-anemometer measured momentum and kinematic heat fluxes at 8 m high above the surface have been obtained from a 20-m monitoring tower located at Erdene in the Asian dust source region of Mongolia for years of 2009 and 2010. These time series were used to identify dust events and to develop optimal regression equations for the dust concentration of dust events with the friction velocity (u_*) and the convective velocity scale (w_*). In total, 68 dust events were identified in 2009 (except for November) and 43 dust events for the period from March to August in 2010. The duration of each dust event ranged from 3-29 h in 2009 and 5-35 h in 2010. The maximum hourly mean dust concentration of the dust event was found to be 4,107 μg m^− 3 in May in 2009 and 4,708 μg m^− 3 in March in 2010 while a minimum of 251 μg m^− 3 in August in 2009 and 662 μg m^− 3 in June in 2010. The optimal regression equation for the dust concentration (C) of dust events was found to have the form of log C = a + b(u_* + cw_*)ⁿ, where a, b, c and n are constants that vary month to month. The convective velocity scale (w_*) that has not been taken into account in most dust modelings was found to enhance the dust concentration of dust events during the cold period from December to March when the soil temperature was below the freezing level for both the stable (w_* < 0) and unstable (w_* > 0) stratifications, whereas the convective velocity caused a reduction in the dust concentrations during the warm period from April to October, suggesting the importance of the convective velocity to estimate dust concentration of dust events.     

城市污水排放量预测模型研究

采用多元线性回归和BP人工神经网络两种方法分别建立城市污水排放量的预测模型，并进行实例计算验证。通过比较分析，发现BP神经网络的非线性映射能力能够更好地反映城市污水量与多个自变量间的复杂关系，具有较高的模拟精度且应用简便。