Hydrus-1D软件在地下水污染风险评价中的应用

以北京市东南郊再生水灌区为研究区域,应用Hydrus-1D软件构建水流、溶质运移模型,模拟再生水连续灌溉入渗过程中水流在包气带中的运动,并以再生水中的典型有机污染物多环芳烃萘、菲为研究对象,模拟其随灌溉水在包气带中的迁移衰减反应过程,结合MapGIS 6.7,将Hydrus-1D的点模拟结果应用于大面积、区域性的污染评价,通过与研究区地下水萘、菲的背景值进行对比,分级评估地下水污染风险.结果表明,经过50年连续灌溉后,再生水灌区整体地下水萘、菲污染风险较低,萘的污染风险高于菲,灌区内高污染风险区域主要位于凤港减河、红旗干渠与凤官沟交汇处以及东风干渠、永乐河与通大边沟之间.     

油田储油罐非甲烷总挥发实验及仿真模拟

针对油田单井拉油罐非密封生产带来的油气泄漏问题,建立小型原油储油罐挥发损耗实验模拟平台,通过气相色谱法探究各因素对其损耗的影响,利用Fluent仿真软件模拟储油罐的泄漏扩散。结果表明:储液温度和有无风环境对储油罐非甲烷总烃(NMHC)挥发影响较大,储液高度和环境温度对其影响较小;仿真模拟无风环境下,储油罐泄漏口短时间内存在油气积聚现象;有风环境下,当风速为1 m/s,油气积聚不明显;随风速增大,扩散浓度场面积不断增大,油品损耗量增大,在风速为5 m/s的环境下,扩散300 s时的浓度场面积相比扩散200 s时较小,但泄漏口处的油气积聚面积增大。     

基于机会约束规划的航班应急调度问题研究

为应对民航突发情况,保障民航运行安全,提出应急调度这一概念。阐述常规情况下航班调度基本模型,分析其在应急情况下的弊端。引入机会约束,构建应对突发状况的应急调度模型。研究兼顾航空公司成本、航班运行安全及旅客随机需求的机型分配问题(FAP)模型和机组排班问题(CSP)模型。比较混合智能算法、隐枚举法、等价转化法的优缺点及适用度。根据案例数据,使用Matlab软件编程,并采用随机模拟与粒子群(PSO)算法相结合的智能算法对模型求解。结果表明,机会约束规划模型在考虑随机因素的情况下,比基本模型更符合实际动态环境。     

空区探测方法优选的ANP模型及其应用

目前矿山空区探测方法众多,但缺乏对其进行优化选择的分析模型。为了提高特定条件下空区探测方法选择的科学性、合理性,采用网络分析法(ANP)将决策问题分解成控制层和网络层。就这些层中的元素而言,用一种标度对人的主观判断进行客观量化后,对其实施定性、定量分析。综合考虑空区探测方法的技术、经济、人机设计及环境指标,构建空区探测方法综合评价体系,确定各判断准则间的相互影响关系,建立空区探测方法优选决策问题的ANP结构,借助Super Deci-sions软件计算参选方法基于各影响因素的综合优先权,从而确定适用于特定条件下的空区探测方法。结果表明,该模型能够随着工作环境的改变而计算影响因素优先权,使空区探测方法根据工作环境的改变而调整。     

工艺变更管理在长北项目应用探讨

针对长北项目工艺变更管理的情况,阐述了长北项目工艺变更管理在程序控制、技术支持和审核保证等方面的优势,分析了目前长北项目工艺变更管理存在的问题,提出了解决建议。并通过实例讲解工艺变更管理在长北项目的应用,对于提高合作项目工艺变更管理水平,提升HSE业绩有一定借鉴意义。     

KR法铁水脱硫自动控制系统软件的编制及调试

根据KR搅拌式铁水脱硫的工艺流程、设备及操作特点,对铁水脱硫自动控制系统软件进行编制,并对软件调试中出现的问题加以解决,确保系统安全、可靠、高效运行。     

导管架式浅海石油平台的结构评估

介绍了应用挪威DNV船级社SESAM软件进行海上平台导管架结构的评估方法和程序,并得出评估结论.     

气溶胶采样头在无人机上安装位置的模拟

利用流体力学软件CFD对固定翼无人机在海拔1000m高处以30m/s速度飞行时采样头的最佳安装位置进行了模拟.首先利用ICEM CFD前处理软件对无人机模型进行了网格划分;然后利用FLUENT软件及其中的DPM模型先后对气相(连续相)和颗粒相(离散相)分别进行了数值模拟,最后用DPM模型模拟了从速度入口方向以30m/s速度释放粒径为1,2.5,10μm的颗粒物,由颗粒物的轨迹图得到了颗粒物在机身周围的阴影区和密集区厚度.得到主要结论如下:对于本研究中的无人机,在海拔1000m高处,采集PM1,PM2.5,PM10时的气溶胶采样头的最佳安装位置为机身下部距机头距离约42~75cm,采样头探头距机身下部壁面的距离分别应大于4,4,4.3cm,但不超过26cm(机身下部距地面距离).     

Priority areas for conservation of Old World vultures

The prosperity and well-being of human societies relies on healthy ecosystems and the services they provide. However, the biodiversity crisis is undermining ecosystems services and functions. Vultures are among the most imperiled taxonomic groups on Earth, yet they have a fundamental ecosystem function. These obligate scavengers rapidly consume large amounts of carrion and human waste, a service that may aid in both disease prevention and control of mammalian scavengers, including feral dogs, which in turn threaten humans. We combined information about the distribution of all 15 vulture species found in Europe, Asia, and Africa with their threats and used detailed expert knowledge on threat intensity to prioritize critical areas for conserving vultures in Africa and Eurasia. Threats we identified included poisoning, mortality due to collision with wind energy infrastructures, and other anthropogenic activities related to human land use and influence. Areas important for vulture conservation were concentrated in southern and eastern Africa, South Asia, and the Iberian Peninsula, and over 80% of these areas were unprotected. Some vulture species required larger areas for protection than others. Finally, countries that had the largest share of all identified important priority areas for vulture conservation were those with the largest expenditures related to rabies burden (e.g., India, China, and Myanmar). Vulture populations have declined markedly in most of these countries. Restoring healthy vulture populations through targeted actions in the priority areas we identified may help restore the ecosystem services vultures provide, including sanitation and potentially prevention of diseases, such as rabies, a heavy burden afflicting fragile societies. Our findings may guide stakeholders to prioritize actions where they are needed most in order to achieve international goals for biodiversity conservation and sustainable development.     

Effects of connectivity and spatial resolution of analyses on conservation prioritization across large extents

The outcome of analyses that prioritize locations for conservation on the basis of distributions of species, land cover, or other elements is influenced by the spatial resolution of data used in the analyses. We explored the influence of data resolution on prioritization of Finnish forests with Zonation, a software program that ranks the priority of cells in a landscape for conservation. We used data on the distribution of different forest types that were aggregated to nine different resolutions ranging from 0.1 × 0.1 km to 25.6 × 25.6 km. We analyzed data at each resolution with two variants of Zonation that had different criteria for prioritization, with and without accounting for connectivity and with and without adjustment for the effect on the analysis of edges between areas at the project boundary and adjacent areas for which data do not exist. Spatial overlap of the 10% of cells ranked most highly when data were analyzed at different resolutions varied approximately from 15% to 60% and was greatest among analyses with similar resolutions. Inclusion of connectivity or edge adjustment changed the location of areas that were prioritized for conservation. Even though different locations received high priority for conservation in analyses with and without accounting for connectivity, accounting for connectivity did not reduce the representation of different forest types. Inclusion of connectivity influenced most the outcome of fine-resolution analyses because the connectivity extents that we based on dispersal distances of typical forest species were small. When we kept the area set aside for conservation constant, representation of the forest types increased as resolution increased. We do not think it is necessary to avoid use of high-resolution data in spatial conservation prioritization. Our results show that large extent, fine-resolution analyses are computationally feasible, and we suggest they can give more flexibility to implementation of well-connected reserve networks.