污水生物处理建模水质数据误差来源分析与影响评价

为进一步提高国内基础建模数据质量,降低建模实践中的数据清洗难度,本研究以北京龙庆再生水厂生物建模过程中的实际数据问题为例,基于数理统计理论及国内污水水质特征分别构建误差来源分析方法与误差影响评价方法.通过设计补充采样与实验排查方案,成功识别数据误差来源并实现不同类型误差对数据准确性的影响量化评价.研究结果表明,污水处理厂日常的取样与化验过程中产生的随机误差不可忽视,特别是当大量随机误差存在时,对数据总体造成的波动影响无法通过数据量的积累而消除;而不同的采样位置与不当的样品保存方式则会引起水质发生变化,由此产生的系统误差将导致测量结果长期偏高/偏低.因此,在依赖人工测量数据进行建模的国内实践中,应首先对历史数据进行误差检验,再进行必要的建模补充采样,以避免补充数据质量受相同误差影响,减少非必要的人力、物力浪费.     

Holocene dynamics of forest ecosystems on the upper plateau of the Volga Upland

Main stages in the development of forest ecosystems on the upper plateau of the Volga Upland in the Holocene have been reconstructed by analyzing palynological assemblages from peat deposits. Dominance of the forest landscape in the region began in the Boreal time. Pine and, to a lesser extent, birch were the main forest-forming species, whereas the role of spruce was never significant. Broad-leaved species appeared in forests in the early Atlantic time. The formation of floodplain and upland bogs began at the end of the Boreal time and in the first half of the Atlantic time, respectively. Significant anthropogenic changes in the vegetation began in the Subboreal time.     

Nutrient fluxes in a eutrophic coastal Louisiana freshwater lake

Nitrogen and phosphorus cycling in a eutrophic Louisiana freshwater lake system (Lac des Allemands) was studied. Nutrients from runoff entering the lake, as well as sediment-interstitial and lake water nitrogen and phosphorus fractions, were measured seasonally. Sedimentation rates in the lake were determined using¹³⁷Cs dating.Phosphorus levels in the lake were found to be largely dependent on concentrations in the incoming bayou water from upland drainage. Lake water concentrations appear to respond to fluctuations in incoming waters. Laboratory equilibrium studies showed bottom sediments in the lake are a major sink for the incoming dissolved orthophosphate phosphorus. Total nitrogen concentrations in the lake water generally exceeded incoming runoff concentrations, suggesting fixation by the large blue-green algae population in the lake as being the major source of nitrogen to the system.Sedimentation ranged from 0.44 cm/year to 0.81 cm/year, depending on the proximity to the inlet bayous. Even though the lake is eutrophic the sediment served as a buffer by removing large amounts of carbon, nitrogen, and phosphorus through sedimentation processes. Carbon, nitrogen, and phosphorus were accumulating in the sediment at rates of 60, 7.1, and 1.1 g/m²/year, respectively.The water quality of the lake is likely to continue to decline unless measures are taken to reduce municipal, industrial, and agricultural inputs of phosphorus into the lake.     

ASSESSMENT OF SAMPLING ERROR ASSOCIATED WITH SOIL MOISTURE ESTIMATION DESIGNS1

A spectral formalism was developed and applied to quantify the sampling errors due to spatial and/or temporal gaps in soil moisture measurements. A design filter was developed to compute the sampling errors for discrete measurements in space and time. This filter has as its advantage a general form applicable to various types of sampling design. The lack of temporal measurements of the two‐dimensional soil moisture field made it difficult to compute the spectra directly from observed records. Therefore, the wave number frequency spectra of soil moisture data derived from stochastic models of rainfall and soil moisture were used. Parameters for both models were estimated using data from the Southern Great Plains Hydrology Experiment (SGP97) and the Oklahoma Mesonet. The estimated sampling error of the spatial average soil moisture measurement by airborne L‐band microwave remote sensing during the SGP97 hydrology experiment is estimated to be 2.4 percent. Under the same climate conditions and soil properties as the SGP97 experiment, equally spaced ground probe networks at intervals of 25 and 50 km are expected to have about 16 percent and 27 percent sampling error, respectively. Satellite designs with temporal gaps of two and three days are expected to have about 6 percent and 9 percent sampling errors, respectively.     

CREAM方法中控制模式分类的模糊方法

认知可靠性与差错分析方法(CREAM)通过对任务环境进行分析从而直接确定人为差错发生概率。该方法提出控制模式的概念,认定不同的任务环境下可能对应不同的控制模式,而人为差错概率直接由控制模式确定。因此,确定控制模式是其中的关键环节。针对该问题,笔者提出了一种模糊方法。通过对性能影响因子进行打分对任务环境进行量化,利用专家打分的方式确定性能影响因子分值对于控制模式的隶属度;通过拟合分析确定性能影响因子的分值对控制模式的隶属函数,得到控制模式与分值之间的对应关系;将该方法应用到两个示例中,其结果与原有方法的结果基本一致。     

用层次分析法分析核电站中影响人误的组织因素

应用层次分析法的基本原理,构建核电站中影响人误的组织因素AHP(层次分析法)模型,确定影响人误的组织因素的指标体系,将成对比较矩阵的特征向量作为组织因素的权重,确定了相关因子的影响力排序。研究结果显示:培训与交流反馈是影响人误的主要组织因素;强化质量监督与控制以及加强交流协作与技能培训,是减少核电站人误发生的重要举措。     

数字水准仪DiNi11/12原理及应用中应注意的问题

本文介绍了数字水准仪的原理、特点,着重分析了对台站跨断层观测精度影响较大的几个因素,并结合台站工作实际提出了减弱这些影响的措施,实测结果表明:采取这些措施可以有效地提高测量精度.     

基于人类动力学的地震压埋人员先验在室率研究

破坏性地震发生后,科学、有效地评估地震压埋人员压埋情况,是有序地开展应急救援工作的基础。人员在室率作为压埋率评估模型的主要参数之一,目前主要以作息时间区为基础以省或市为基础单元进行计算,这难以体现基础单元之下的不同市或县人员在室率之间的差异性。为解决这一问题,采用人类动力学相关原理,运用极大似然法估算人员在室率,进而形成基于人类动力学的地震压埋人员压埋率预估模型。最后以汶川8.0级地震部分受灾学校为例,进行压埋率实际评估和模型误差分析。研究表明:提出的微观在室率能更准确地反映人员在室情况具有更好的适用性;在实际评估中模型精度达到±0.13,表明模型能达到较好的预估效果,能为震后应急救援工作提供一定的参考。     

基于实船结构监测数据的异常检测及处理方法

目的 获得高质量实船结构监测数据,减少数据因外界干扰造成的异常现象,现开发一套面向真实海况的实船结构监测数据的异常处理方法。方法 将统计学中的Z-score异常检测方法与数据处理中常用的平均值计算法相结合,实现对船舶结构应力数据的异常处理。基于正常信号创建含有异常现象的验证数据,对新的异常处理方法进行精度验证。结果 相比Hampel滤波法、Smooth平滑函数等传统的信号处理方法,Z-score异常检测及平均值计算方法的异常处理精度最高,且以此为基础计算的结构信号统计值准确度较好。结论 Z-score异常检测及平均值计算方法可实现真实海况下的实船结构监测数据的异常处理,并在结构应力数据的价值挖掘上可提供有力支撑。     

基于信息处理和事故链原理的结构化飞行员差错模型

为了对民航飞行员人为差错进行系统分析,研究民航业中常见人为差错的分析方法,指出其局限性。基于信息处理过程和事故链原理,从微观的认知过程和宏观的HFACS框架2个层面构建一种新的飞行员人为差错分析模型,并对模型中的情景分析、差错模式与分类、认知机理、差错恢复、差错成因、反馈机制和防御机制等几大核心模块进行阐述,重点介绍认知机理在差错形成中产生的关键影响因素,提出结构化差错分析方法的思路与步骤。该模型为民航飞行员人为差错的产生机理、差错分类和差错成因的分析提供一种新思路,但模型的进一步应用还有待于通过案例分析来验证。