地铁运营系统安全综合评价指标体系研究

分析地铁运营系统的特点、运营模式、系统故障模式,并运用系统工程的理论原则,从系统外部因素、系统指挥因素、设备设施因素、运营管理因素4个方面,确立地铁运营系统安全综合评价指标体系,利用模糊数学综合评价法,建立了地铁运营系统安全综合评价模型,并通过典型实例进行综合分析评价,进而证明将模糊数学理论应用于地铁安全综合评价的可行性。通过地铁运营系统安全指标体系和评价方法的研究和探索,对正确评价地铁系统运营安全现状,修正偏差,提高地铁系统安全总体水平具有十分重要的意义。     

高密度电法在地质灾害调查和安全评价中应用研究

本文介绍了高密度电法工作原理、设备和使用方法，并应用高密度电法对某矿区地下不明采空区进行了成功的探测，探测结果为采空区危害的定性和定量评价提供了准确的基础数据．该方法在地质灾害调查和评估等领域有广阔的应用前景。     

基于人工神经网络理论的船舶动力装置安全综合评价模型

为提高船舶动力装置安全综合评价水平，依据人工神经网络的基本原理，分析了BP神经网络模型的基本原理和优化策略，将其应用于船舶动力装置的安全评价之中。提出了基于神经网络理论的船舶动力装置综合安全评价模型及实现方法，并以实例论证了此方法的可行性。     

基于BP网络的建筑安装施工现场安全综合评价的研究

针对目前我国建筑安装施工现场安全评价技术的不成熟和欠科学性的现状 ,笔者分析和综合了目前安全评价技术 ,结合建筑业特点 ,提出了基于BP神经网络的建筑安装施工现场安全评价方法 ,并对该评价模型的原理、方法及算法进行了研究。首先 ,结合建筑安装施工现场安全生产的特点建立评价指标体系 ,随后 ,运用层次分析法确定指标及准则层的权重 ,并运用模糊综合评价法生成评价样本集 ,最后 ,利用样本集训练BP网络 ,待误差满足要求后 ,即可运用训练成功的BP神经网络进行安全评价。     

Environmental assessment of supercritical water oxidation of sewage sludge

Environmental aspects of using supercritical water oxidation (SCWO) to treat sewage sludge were studied using a life cycle assessment (LCA) methodology. The system studied is the first commercial scale SCWO plant for sewage sludge in the world, treating sludge from the municipal wastewater treatment facility in Harlingen, TX, USA. The environmental impacts were evaluated using three specific environmental attributes: global warming potential (GWP), photo-oxidant creation potential (POCP) and resource depletion; as well as two single point indicators: EPS2000 and EcoIndicator99. The LCA results show that for the described process, gas-fired preheating of the sludge is the major contributor to environmental impacts, and emissions from generating electricity for pumping and for oxygen production are also important. Overall, SCWO processing of undigested sewage sludge is an environmentally attractive technology, particularly when heat is recovered from the process. Energy-conserving measures and recovery of excess oxygen from the SCWO process should be considered for improving the sustainability potential.     

TEMPORAL CHANGES IN THE YADKIN RIVER FLOW VERSUS SUSPENDED SEDIMENT CONCENTRATION RELATIONSHIP1

ABSTRACT: Dynamic linear models (DLM) and seasonal trend decomposition (STL) using local regression, or LOESS, were used to analyze the 50‐year time series of suspended sediment concentrations for the Yadkin River, measured at the U.S. Geological Survey station at Yadkin College, North Carolina. A DLM with constant trend, seasonality, and a log₁₀ streamflow regressor provided the best model to predict monthly mean log₁₀ suspended sediment concentrations, based on the forecast log likelihood. Using DLM, there was evidence (odds approximately 69:1) that the log₁₀ streamflow versus log₁₀ suspended sediment concentration relationship has changed, with an approximate 20 percent increase in the log₁₀ streamflow coefficient over the period 1981 to 1996. However, sediment concentrations in the Yadkin River have decreased during the decade of the 1990s, which has been accompanied by a concomitant increase in streamflow variability. Although STL has been shown to be a versatile trend analysis technique, DLM is shown to be more suitable for discovery and inference of structural changes (trends) in the model coefficient describing the relationship between flow and sediment concentration.     

黄河积石峡水电站库区泥石流危险度评价

在选取一次(可能)最大冲出物方量、泥石流发生频率、流域面积、主沟长度、流域相对高差、流域切割密度、泥沙补给段长度比7个因子为泥石流沟谷危险度划分的主要因子的基础上,对评价因子隶属度的确定作了分析和阐述,并运用模糊综合评判法对黄河上游积石峡水电站库区16条泥石流沟进行了危险度划分.     

利用信息扩散模式对安徽及华东地区地震的风险分析

本文利用信息扩散模式,分别从年地震频次和年最大震级两个方面对安徽及华东地区的地震风险进行评估.结果显示:安徽地区ML≥3.0地震,年频次4次以上,约两年一遇;年发生ML≥3.9地震,则3年可能遇一次.而华东地区ML≥4.0地震,年频次4次以上,大约3年一遇;年发生ML≥4.9的地震,则可能2年遇一次.