复杂载荷下裂纹SIF计算的子模型技术

对船舶与海洋工程结构物进行疲劳评估,首先要通过子模型技术解决复杂应力场中裂纹应力强度因子(SIF)的计算问题。针对子模型技术实现过程繁杂且效率较低的问题,分别提出"逐周分层法","转换矩阵法"及"映射划分法"并基于VBA及APDL语言编写插件MPCarrangerV1.0,FEMcoortransferV1.0及CrackmapperV1.0,解决从Patran整体有限元模型到Ansys子模型时壳体单元间MPC创建低效、不同坐标系间节点位置转换困难及裂纹自由划分的局限性问题。基于DNV及ABS相关规范,以某B型LNG燃料舱的疲劳热点为例,对改进的子模型技术进行验证,结果表明经改进的子模型技术可成功施加合理边界条件并实现SIF的求解,可为子模型技术快速实现复杂载荷下裂纹SIF的准确计算提供参考。     

The identification and empirical characterization of vehicular (Lagrangian) fundamental diagrams in multilane traffic flow

Traditional macroscopic traffic flow modeling framework adopts the spatial–temporal coordinate system to analyze traffic flow dynamics. With such modeling and analysis paradigm, complications arise for traffic flow data collected from mobile sensors such as probe vehicles equipped with mobile phones, Bluetooth, and Global Positioning System devices. The vehicle‐based measurement technologies call for new modeling thoughts that address the unique features of moving measurements and explore their full potential. In this paper, we look into the concept of vehicular fundamental diagram (VFD) and discuss its engineering implications. VFD corresponds to a conventional fundamental diagram (FD) in the kinematic wave (KW) theory that adopts space–time coordinates. Similar to the regular FD in the KW theory, VFD encapsulates all traffic flow dynamics. In this paper, to demonstrate the full potential of VFD in interpreting multilane traffic flow dynamics, we generalize the classical Edie's formula and propose a direct approach of reconstructing VFD from traffic measurements in the vehicular coordinates. A smoothing algorithm is proposed to effectively reduce the nonphysical fluctuation of traffic states calculated from multilane vehicle trajectories. As an example, we apply the proposed methodology to explore the next‐generation simulation datasets and identify the existence and forms of shock waves in different coordinate systems. Our findings provide empirical justifications and further insight for the Lagrangian traffic flow theory and models when applied in practice. Copyright © 2015 John Wiley & Sons, Ltd.     

Data dependent input control for origin–destination demand estimation using observability analysis

In this paper, we address the observability issue of static O–D estimation based on link counts. Unlike most classic observability analyses that relied only on network topological relationships, our analysis incorporates the actual values of input parameters, thus including network operational relations as well. We first analyze possible mathematical properties of an O–D estimation problem with different data input. We then propose a modeling approach based on mixed-integer program for selecting model input that ensures observability and estimation quality. Through establishing a stronger connection between observability analysis and the corresponding estimation problem, the proposed method aims to improve estimation quality while reducing reliance on erroneous data.     

Strain prediction for critical positions of FPSO under different loading of stored oil using GAIFOA-BP neural network

FPSO (floating, production, storage and offloading) units are widely used in the offshore oil and gas industry. Generally, FPSOs have excellent oil storage capacity owing to their huge oil cargo holds. The volume and distribution of stored oil in the cargo holds influence the strain level of hull girder, especially at critical positions of FPSO. However, strain prediction using structural analysis tools is computationally expensive and time consuming. In this study, a prediction tool based on back-propagation (BP) neural network called GAIFOA-BP is proposed to predict the strain values of concerned positions of an FPSO model under different oil storage conditions. The GAIFOA-BP combines BP model and GAIFOA which is a combination of genetic algorithm (GA) and an improved fruit fly optimization algorithm (IFOA). Results from three benchmark tests show that the GAIFOA-BP model has a remarkable performance. Subsequently, a total of 81 sets of training data and 25 sets of testing data are obtained from experiment using fiber Bragg grating (FBG) sensors installed on the surface of an FPSO model. The numerical results show that the GAIFOA-BP is capable of predicting the strain values with higher accuracy as compared with other BP models. Finally, the reserved GAIFOA-BP model is utilized to predict the strain values under the inputs of a 10-day time series of volume and distribution of stored oil. The predicted strain results are further used to calculate the fatigue consumption of measurement points.     

基于时延特性建模的多断面短时交通流预测

针对现有交通流预测方法未充分考虑多断面车流演变规律，提出基于时延特性建模的时空相关性计算方法. 该方法采用对不同断面、不同时刻交通流的分布相似性度量，对输入的车辆到达数据序列进行切割构建时空相似度矩阵，得到相邻断面之间的时延参数. 基于时延特性建模，将多断面之间的流量信息进行融合，使用长短时记忆(LSTM)网络进行流量预测. 通过对实际路段数据的预测和结果分析，验证所提方法的有效性和实用性.     

Path-constrained traffic assignment: A trip chain analysis under range anxiety

This paper proposes and analyzes a distance-constrained traffic assignment problem with trip chains embedded in equilibrium network flows. The purpose of studying this problem is to develop an appropriate modeling tool for characterizing traffic flow patterns in emerging transportation networks that serve a massive adoption of plug-in electric vehicles. This need arises from the facts that electric vehicles suffer from the “range anxiety” issue caused by the unavailability or insufficiency of public electricity-charging infrastructures and the far-below-expectation battery capacity. It is suggested that if range anxiety makes any impact on travel behaviors, it more likely occurs on the trip chain level rather than the trip level, where a trip chain here is defined as a series of trips between two possible charging opportunities (Tamor et al., 2013). The focus of this paper is thus given to the development of the modeling and solution methods for the proposed traffic assignment problem. In this modeling paradigm, given that trip chains are the basic modeling unit for individual decision making, any traveler’s combined travel route and activity location choices under the distance limit results in a distance-constrained, node-sequenced shortest path problem. A cascading labeling algorithm is developed for this shortest path problem and embedded into a linear approximation framework for equilibrium network solutions. The numerical result derived from an illustrative example clearly shows the mechanism and magnitude of the distance limit and trip chain settings in reshaping network flows from the simple case characterized merely by user equilibrium.     

Robust weekly aircraft maintenance routing problem and the extension to the tail assignment problem

In this paper, we study two closely related airline planning problems: the robust weekly aircraft maintenance routing problem (RWAMRP) and the tail assignment problem (TAP). In real life operations, the RWAMRP solution is used in tactical planning whereas the TAP solution is implemented in operational planning. The main objective of these two problems is to minimize the total expected propagated delay (EPD) of the aircraft routes. To formulate the RWAMRP, we propose a novel weekly line-of-flights (LOF) network model that can handle complex and nonlinear cost functions of EPD. Because the number of LOFs grows exponentially with the number of flights to be scheduled, we propose a two-stage column generation approach to efficiently solve large-scale real-life RWAMRPs. Because the EPD of an LOF is highly nonlinear and can be very time-consuming to accurately compute, we propose three lower bounds on the EPD to solve the pricing subproblem of the column generation. Our approach is tested on eight real-life test instances. The computational results show that the proposed approach provides very tight LP relaxation (within 0.6% of optimal solutions) and solves the test case with more than 6000 flights per week in less than three hours. We also investigate the solutions obtained by our approach over 500 simulated realizations. The simulation results demonstrate that, in all eight test instances, our solutions result in less EPDs than those obtained from traditional methods. We then extend our model and solution approach to solve realistically simulated TAP instances.     

土压平衡盾构施工中泡沫改良砾砂土的试验研究

为了解决土压平衡盾构在砾砂土地层掘进过程中,土体塑流性差、刀盘及螺旋输送机磨损严重和开挖面平衡不易保持等问题,通过自制泡沫发生器发泡,对砾砂土地层的泡沫改良技术进行室内试验研究,分析气液比、含水率和泡沫掺量对塑流性的影响和改良前后土样的渗透系数的变化规律,得出泡沫发生器气液比在30∶1~55∶1、含水率为5%~12.5%、泡沫掺量为20%~40%时,土体具有较好的塑流性,泡沫的"轴承效应"和泡沫剂中表面活性剂的亲水基团与水、砾砂土颗粒形成的氢键是塑流性提高的根本原因;使用泡沫剂改良砾砂土后,渗透系数大幅降低,掺泡沫后在280 min内渗透系数随时间变化较小,能达到10~(-5)cm/s,泡沫剂溶液中高分子化合物的联结和液桥力是土样具有堵水作用的原因。     

构建网络安全体系,保障电子政务畅通

构建安全的电子政务网络体系对于推动政府工作信息化、促进政务公开、提高政府办公效率、构建和谐社会是非常重要的.在详细介绍目前网络安全一些认识误区的基础上,结合实际工作经验,从技术实施、制度建设方面阐述了如何构建安全的网络体系的问题.