注采比对“二三结合”开发模式渗流特征的影响

大庆油田的开发逐渐进入高含水阶段,厚油层动用程度低,"二三结合"开发模式是有效的提高厚油层动用程度,改善水驱开发效果,提高油田采收率的有效手段。在"二三结合"开发模式注聚阶段中注采比对井间压力、含水饱和度等变化有重要影响。为了探究注采比对开发层位的井间压力及饱和度的影响,利用油藏数值模拟方法,模拟了相同的开发模式不同注采比的生产情况,绘制了不同注采比情况下,不同层位的井间压力及含水饱和度变化情况,为维持地层压力平衡,保持油田稳定生产提供有力的依据。     

Models for solar radiation prediction based on different measurement sites

The modeling of solar radiation for forecasting its availability is a key tool for managing photovoltaic (PV) plants and, hence, is of primary importance for energy production in a smart grid scenario. However, the variability of the weather phenomena is an unavoidable obstacle in the prediction of the energy produced by the solar radiation conversion. The use of the data collected in the past can be useful to capture the daily and seasonal variability, while measurement of the recent past can be exploited to provide a short term prediction. It is well known that a good measurement of the solar radiation requires not only a high class radiometer, but also a correct management of the instrument. In order to reduce the cost related to the management of the monitoring apparatus, a solution could be to evaluate the PV plant performance using data collected by public weather station installed near the plant. In this paper, two experiments are conducted. In the first, the plausibility of the short term prediction of the solar radiation, based on data collected in the near past on the same site is investigated. In the second experiment, the same prediction is operated using data collected by a public weather station located at ten kilometers from the solar plant. Several prediction techniques belonging from both computational intelligence and statistical fields have been challenged in this task. In particular, Support Vector Machine for Regression, Extreme Learning Machine and Autoregressive models have been used and compared with the persistence and the k-NN predictors. The prediction accuracy achieved in the two experimental conditions are then compared and the results are discussed.     

托盘式湿法烟气脱硫塔阻力特性研究

采用冷态物理模型结合商用CFD(Computational Fluid Dynamics)软件,对山东某火电厂300 MW机组配套托盘塔的流场和阻力特性进行了研究,取得了孔板阻力损失与液气比之间的二次函数关系。研究结果表明,塔内两相流场分布合理,入口处液滴受烟气的拖拽作用形成明显的干湿界面,负荷和液气比是影响脱硫塔阻力的重要因素。当液气比一定时,托盘上方能够维持相对稳定的持液层及鼓泡过程;满负荷运行时,脱硫塔阻力损失约为1600 Pa,其中孔板占1/4,持液层占3/4。拟合获得了托盘区阻力损失同液气比之间的关系,为托盘塔的应用、运行及优化提供了理论指导。     

高落差粉尘扩散规律和分布特征

高溜井放矿过程中会形成强大的冲击气流引起粉尘扩散，造成严重的井下环境污染，对其进行有效治理一直是井下通风除尘的工作重心，本工作利用相似实验和数值模拟相结合的方式探究溜井放矿过程中粉尘的扩散规律和分布特征。通过改变放矿质量、矿石粒径、溜井密闭程度、含水率等因素测试不同条件下气流大小和粉尘浓度分布，并利用CFD-DPM耦合方法模拟卸矿过程中的气?固两相流，研究气流和粉尘浓度时空分布特征。结果表明，最大粉尘浓度和风速随放矿质量增加而上升，随颗粒粒径和溜井密闭程度增大而降低，且含水率越大，粉尘浓度越小，风速无明显变化，在放矿过程中矿石颗粒之间碰撞占主导作用，颗粒流呈横向分布。     

古建筑木结构透榫节点力学模型研究

为研究古建筑木结构透榫节点的M-θ力学模型，在分析透榫节点构造特征与受力机理的基础上，建立其数值模型，用透榫节点的试验数据验证了该数值模型的正确性，并分析了节点缝隙、木材横纹弹性模量和大榫头长度对透榫节点受弯承载力的影响。根据受力分析结果，建立以弹性点、屈服点与极限点为特征点的三折线多参数M-θ力学模型，其结果与多数的试验结果基本吻合，并将该力学模型应用于木构架的受力分析。研究结果表明：透榫节点的滞回耗能能力强，节点的变形主要集中在榫头处。当榫头与卯口之间的缝隙增大时，节点的受弯承载力降低。随木材横纹弹性模量的提高和大榫头长度的增加，节点的受弯承载力有一定提高。文章建立的M-θ力学模型能较好反映透榫节点的受力过程，适用于木构架的受力分析，其荷载 位移骨架曲线与试验结果基本吻合。研究成果可为古建筑木结构的维修与保护提供参考。     

潮流能水平轴水轮机在剪切来流下的水动力分析

采用基于计算流体力学方法的全尺度数值模拟计算,建立了适用于潮流能水轮机模拟的剪切来流环境,通过数值计算结果,对潮流能水轮机随时间变化的宏观力和流场特征进行了系统分析,探索水轮机在复杂工况下的水动力特性规律。结果表明,水轮机整个叶轮的总体平均受力在剪切流工况中未受到明显影响; 单个叶片的瞬态轴向力系数和瞬态轴向扭矩系数在旋转周期内出现了明显的周期性变化,且周期性变化幅值随转速增大而增大; 非定常的瞬时轴向扭矩和力的周期性振荡容易引起单个叶片的结构性振动,可能对水轮机的机械结构造成影响。     

基于射流冲击作用的舰机适配性数值分析与优化

准确分析和控制射流冲击对航母甲板环境的影响是新型喷气偏流板设计和布局的关键所在。为了确定射流冲击影响最小的偏流板布局，运用有限体积法，采用分区混合网格方案，结合雷诺时均纳维斯托克斯（RANS）方程和SST k-ω湍流模型对喷气偏流板在不同布局下的射流冲击效应进行三维数值模拟。选取舰载机双发动机全加力状态时喷气偏流板与发动机距离不同、喷气偏流板倾角不同共12种布局组合进行射流冲击效应的对比计算,计算结果显示了喷气偏流板各布局下的流场参数、传热特性、尾喷口温升、冲击力和力矩等分布规律。定性和定量分析了燃气射流冲击下温度场和速度场的危险区域，结果表明，偏流板与发动机距离5 m、偏流板倾角45°时的布局更有利于将燃气射流向上引导。在此基础上，基于倾角最小化原则及二次导流原理优化设计了一种导流隔热性能好、工作稳定性高的被动隔热式喷气偏流板装置。     

Multicellular Tumor Spheroids (MCTS) as a 3D In Vitro Evaluation Tool of Nanoparticles

Multicellular tumor spheroid models (MCTS) are often coined as 3D in vitro models that can mimic the microenvironment of tissues. MCTS have gained increasing interest in the nano‐biotechnology field as they can provide easily accessible information on the performance of nanoparticles without using animal models. Considering that many countries have put restrictions on animals testing, which will only tighten in the future as seen by the recent developments in the Netherlands, 3D models will become an even more valuable tool. Here, an overview on MCTS is provided, focusing on their use in cancer research as most nanoparticles are tested in MCTS for treatment of primary tumors. Thereafter, various types of nanoparticles—from self‐assembled block copolymers to inorganic nanoparticles, are discussed. A range of physicochemical parameters including the size, shape, surface chemistry, ligands attachment, stability, and stiffness are found to influence nanoparticles in MCTS. Some of these studies are complemented by animal studies confirming that lessons from MCTS can in part predict the behaviour in vivo. In summary, MCTS are suitable models to gain additional information on nanoparticles. While not being able to replace in vivo studies, they can bridge the gap between traditional 2D in vitro studies and in vivo models.     

基于云概率密度分布估计的大坝监测数据分析

大坝运行监测易受自然环境和监测条件影响，存在时间和空间上的变异性，监测数据具有不确定性。以云理论的随机性和不确定性分析方法为基础，并与空间数据辐射思想相结合，建立了云滴概率密度分布估计模型，然后导出云概率密度分布函数，依据样本监测数据推求母体空间数据的分布特征，并设计了基于逆向云算法云变换的计算程序。分析陆浑水库1979~1999年测压管监测数据和位移变形数据的云概率密度分布特征和云数字特征，得出了20 a来大坝的数据分布特征和运行状态。监测数据分析结果表明，云概率密度分布估计不仅能有效合理地分析大坝的运行状态，而且能够依据云数字特征来判断监测状态和监测环境的异常变化。 