协同商务环境中的主观信任模型研究

针对开放网络环境中协同商务的动态、多域、异构等特点,提出了适用于开放式协作环境的基于云模型的主观信任评价方法,给出了基于云模型的信任更新算法.通过源实体与恶意推荐实体交互的仿真实验证明,应用该算法不仅可以有效抑制恶意实体的推荐行为,还可以激发实体的积极推荐.     

海绵城市建设雨水基础设施优化配置研究进展

气候变化和快速城市化改变了城市生态水文循环过程,加剧了水资源短缺、水环境污染、水生态破坏、暴雨洪涝灾害等城市问题.为获取低影响开发措施(low impact development,LID)/绿色基础设施(green infrastructure,GI)与城市灰色基础设施耦合系统空间优化配置方案以及多目标成本-效益最优...     

电力市场与电力系统交互动态仿真设计

分析了电力交易市场、投资市场与电力系统的功能关系及其数学描述。借鉴实验经济学方法，将电力市场中能用数学模型表达的环节表达为数学模型，而将参与者的主观行为、市场规则、市场监管行为作为数学模型的输入，在实验环境中动态地交互。定义失稳风险，将输电动态阻塞对交易的物理制约转化为经济上各交易应承担的输电风险。在此基础上，建立电力市场动态过程的仿真器平台，实现电力市场与电力系统动态仿真，并采用市场调节的预交易阻塞管理模式实现电力系统技术问题与电力市场经济问题的协调。     

车辆运行风险贝叶斯网络量化分级方法

为评估自然驾驶过程中车辆运行存在的交通风险,采用贝叶斯网络对车辆运行风险进行量化研究. 首先开展自然驾驶试验,获取车辆距离控制指标、加速度、方向盘转向熵车辆控制数据及驾驶人视线转移时间、扫视速度、眨眼频率眼动数据. 然后,分析了各项指标的风险概率,确定各项指标阈值对应风险等级. 最后,构建了基于贝叶斯网络的车辆运行风险评估模型,给出了风险量化分级方法,确定了车辆运行风险等级,并对模型进行了敏感性分析. 结果表明:基于车辆控制和眼动表征的贝叶斯网络模型能够有效地对驾驶过程中车辆运行风险进行定量评估. 研究结果可评估自然驾驶过程中的车辆运行风险,并为运行风险进行量化分级.     

A practical polynomial chaos Kalman filter implementation using nonlinear error projection on a reduced polynomial chaos expansion

The polynomial chaos Kalman filter (PCKF) has been gaining popularity as a computationally efficient and robust alternative to sampling methods in sequential data assimilation settings. The PCKF's sampling free scheme and attractive structure to represent non‐Gaussian uncertainties makes it a promising approach for data filtering techniques in nonlinear and non‐Gaussian frameworks. However, the accuracy of PCKF is dependent on the dimension and order of the polynomial chaos expansion used to represent all sources of uncertainty in the system. Thus, when independent sources of errors, like process noise and time independent sensors' errors are incorporated in the system, the curse of dimensionality hinders the efficiency and the applicability of PCKF. This study sheds light on this issue and presents a practical framework to maintain an acceptable accuracy of PCKF without scarifying the computational efficiency of the filter. The robustness and efficiency of the presented implementation is demonstrated on 3 typical numerical examples to illustrate its ability to achieve considerable accuracy at a low computational tax.     

柴达木盆地西部南区第三系原油成熟度特征

原油成熟度特征是原油地球化学研究的重要组成部分。通过对柴达木盆地西部南区第三系原油的色谱-质谱分析,在饱和烃和芳烃成熟度参数、生物标志物绝对浓度和热不稳定化合物的定量与定性分析基础上,详细剖析了该区原油的成熟度特征。研究结果表明:柴达木盆地西部南区第三系原油主体为未熟-低熟油,不存在混源造成未熟-低熟假象的可能性。成熟原油仅出现在花土沟、狮子沟和砂西地区。柴达木盆地西部南区有效烃源岩的发育特征,佐证了大量未熟-低熟原油存在的可能性。     

用MicroBCA方法定量检测硅烷化表面固定的纤维连接蛋白

使用microBCA方法（micro-bicinchoninicacid protein assay）,定量研究了人纤维连接蛋白（fi-bronectin,Fn）在硅烷化石英玻璃表面实现共价固定的情况。首先对石英玻璃进行化学清洗,使表面的羟基得以充分暴露。再利用硅烷偶联剂（APTE）将氨基基团引入,并通过EDC/NHS催化体系把人纤维连接蛋白以酰胺键的形式共价固定于该表面。最后用Mi-croBCA方法对该表面固定化的生物分子（Fn）进行量化表征。应用水接触角、X射线光电子能谱（X-rayphotoelectron spectroscopy,XPS）、原子力显微镜（atomic force microscope,AFM）等方法对各步处理效果进行跟踪分析。结果表明Fn在硅烷化石英玻璃表面实现了固定,一定范围内,硅烷化表面的Fn固定量随所使用Fn孵化液浓度的增加而增大。为生物材料表面改性与修饰研究中生物大分子的量化表征提供了一种新方法。     

Monte Carlo uncertainty quantification of the effective delayed neutron fraction

The applicability of Monte Carlo techniques, namely the Monte Carlo sensitivity method and the random-sampling method, for uncertainty quantification of the effective delayed neutron fraction β_eff is investigated using the continuous-energy Monte Carlo transport code, MCNP, from the perspective of statistical convergence issues. This study focuses on the nuclear data as one of the major sources of β_eff uncertainty. For validation of the calculated β_eff, a critical configuration of the VENUS-F zero-power reactor was used. It is demonstrated that Chiba's modified k-ratio method is superior to Bretscher's prompt k-ratio method in terms of reducing the statistical uncertainty in calculating not only β_eff but also its sensitivities and the uncertainty due to nuclear data. From this result and a comparison of uncertainties obtained by the Monte Carlo sensitivity method and the random-sampling method, it is shown that the Monte Carlo sensitivity method using Chiba's modified k-ratio method is the most practical for uncertainty quantification of β_eff. Finally, total β_eff uncertainty due to nuclear data for the VENUS-F critical configuration is determined to be approximately 2.7% with JENDL-4.0u, which is dominated by the delayed neutron yield of ²³⁵U.     

Variability response functions for effective material properties

The variability response function (VRF) is a well-established concept for efficient evaluation of the variance and sensitivity of the response of stochastic systems where properties are modeled by random fields that circumvents the need for computationally expensive Monte Carlo (MC) simulations. Homogenization of material properties is an important procedure in the analysis of structural mechanics problems in which the material properties fluctuate randomly, yet no method other than MC simulation exists for evaluating the variability of the effective material properties. The concept of a VRF for effective material properties is introduced in this paper based on the equivalence of elastic strain energy in the heterogeneous and equivalent homogeneous bodies. It is shown that such a VRF exists for the effective material properties of statically determinate structures. The VRF for effective material properties can be calculated exactly or by Fast MC simulation and depends on extending the classical displacement VRF to consider the covariance of the response displacement at two points in a statically determinate beam with randomly fluctuating material properties modeled using random fields. Two numerical examples are presented that demonstrate the character of the VRF for effective material properties, the method of calculation, and results that can be obtained from it.