Solving the gate assignment problem through the Fuzzy Bee Colony Optimization

In the field of Swarm Intelligence, the Bee Colony Optimization (BCO) has proven to be capable of solving high-level combinatorial problems, like the Flight-Gate Assignment Problem (FGAP), with fast convergence performances. However, given that the FGAP can be often affected by uncertainty or approximation in data, in this paper we develop a new metaheuristic algorithm, based on the Fuzzy Bee Colony Optimization (FBCO), which integrates the concepts of BCO with a Fuzzy Inference System. The proposed method assigns, through the multicriteria analysis, airport gates to scheduled flights based on both passengers’ total walking distance and use of remote gates, to find an optimal flight-to-gate assignment for a given schedule. Comparison of the results with the schedules of real airports has allowed us to show the characteristics of the proposed concepts and, at the same time, it stressed the effectiveness of the proposed method.     

Dynamic loading history and collapse analysis of the pipe during deepwater S-lay operation

In the deepwater S-lay operations depending on the required stinger radius and rollers configuration, relatively large plastic deformation is induced when the pipe passes over the stinger, under the combined loadings of bending, axial tension, roller reaction force and the pipelay vessel motion. The resulting plastic deformation does not vanish after the pipe leaves the stinger. It accumulates until the pipe reaches the seabed. The inherited residual deformation might reduce the collapse capacity of the pipe under the external pressure loading. The present paper investigates the dynamic loading history of the pipe during the S-lay operation based on a test-verified finite element model, and then calculates the residual plastic deformation of the pipe cross-section after the pipe reaches the seabed. Finally, the nonlinear collapse analysis is implemented based on the modified RIKS method to evaluate the capacity of the installation-induced deformed pipe. The results confirm that the deepwater S-lay operation will lead to obvious plastic deformation of the pipe, which decreases the pipe collapse capacity to some extent.     

Towards a model of hydrodynamic damping for a circular cylinder with helical strakes at low KC

This paper investigates the hydrodynamic damping of a circular cylinder with helical strakes at Keulegan-Carpenter (KC) number from 0.07 to 3 in the presence of steady currents. Experiments were performed with a straked cylinder oscillating in either in-line or cross currents over Reynolds number (based on the oscillating velocity amplitude) varying from 1260 to 54,000. With in-line current being present, the measured drag coefficients of the straked cylinder are found to depend on the ratio between the oscillating velocity amplitude and the steady current velocity. This phenomenon is further confirmed by computational fluid dynamics using large-eddy simulations. The drag coefficients obtained from the numerical simulations agree well with the experimentally determined values. Similar phenomenon is observed for the cases with cross background current. Based on the experimental data, empirical formulae are proposed to evaluate drag coefficients. These results are of importance in estimating the resonant motion and the fatigue life of risers, e.g. water intake risers, in the flow regime of low KC. Finally, recommendations are provided for fatigue analysis of risers with helical strakes from the perspective of engineering practice.     

Probabilistic fatigue analysis of marine structures using the univariate dimension-reduction method

Probabilistic fatigue analysis of offshore structures requires the numerical simulation of a huge number of loading cases to compute the long-term multi-dimensional integral associated to the fatigue damage assessment. This paper proposes the implementation of the univariate dimension-reduction method developed by Rahman and Xu [1] in order to compute the long-term fatigue damage more efficiently. This method is particularly attractive because it reduces significantly the number of simulations by decomposing the N-dimensional integral associated to expected long-term fatigue damage assessment into the sum of N one-dimensional integrals. In addition, this paper compares the univariate-dimension reduction method with the brute force direct integration methodology and other methods based on Taylor expansions, such as perturbation approach and asymptotic expansion method discussed by Low and Cheung [2]. Two comprehensive examples are included to show the effectiveness of the method. At first, the performance of the univariate dimension-reduction method is evaluated by assessing the fatigue damage of a theoretical structure represented by a single stress response amplitude operator (RAO). Then, in order to show a case of practical application, the fatigue damage is evaluated for a Steel Lazy Wave Riser (SLWR) connected to an FPSO in a water depth of 2200 m.     

R/S分析法在盾构下穿机场过程中的地表变形规律研究

为保证机场的正常运营,在盾构下穿机场的施工过程中,对地表沉降变形控制的要求较高,因此对穿越过程中的施工控制和变形规律研究具有重要意义。首先,基于盾构下穿机场的工程条件,分析盾构下穿过程中的风险,并提出相应的控制措施;同时,根据现场监测数据,分析盾构下穿机场过程中的地表沉降变形规律,并利用R/S分析法对地表沉降的发展趋势进行研究。结果表明:盾构施工引起的机场地表变形均在控制值范围以内,且各监测点在不同序列条件下的Hurst指数均大于0.5,具有沉降持续减弱的趋势,验证下穿过程中风险控制措施的有效性,为类似下穿机场的盾构施工提供一定的实践经验,也为盾构施工引起的地表沉降变形规律研究提供参考。     

桩基建模方法对自升式钻井平台动力响应的影响

随着海洋油气开采作业水深的不断增加,海洋平台固有频率随之降低,易与相同频率成分的波浪产生共振,因此对平台动力响应特性研究是非常有必要的,而桩基模型在平台动力响应分析中发挥着关键作用。以某400英尺自升式钻井平台研究对象,基于等效建模的思想,分别建立了固支桩基、铰接桩基、线性弹簧桩基及非线性弹簧桩基四种有限元模型,并对其进行静力分析、模态分析及瞬态动力学分析,通过对比得到的振动频率、动力放大因子及波流惯性力,得出弹簧桩基模型在平台动力响应分析中的有效性及合理性结论。     

辽宁农业劳动生产率变动及影响因素分析

按照时间序列分析辽宁农业劳动生产率的变动趋势，运用人均耕地面积、灌溉率、劳均化肥施用量、结构调整系数、机电提灌面积占有效灌溉面积比重等指标构建影响农业劳动生产率的模型，结果表明农业产业结构调整、劳均化肥施用量、灌溉率对劳动生产率的影响非常显著．因此，应该加快农业产业结构调整、推进科学技术在农业生产中的应用、加强农业基础设施建设、提高公共服务水平．     

上海松江区现代有轨电车规划研究

现代有轨电车因其环保、舒适、高效、低造价、高品质等特点,在国际上得到广泛应用,我国多个城市也在规划和建设之中。但是,由于其在国内尚为一种全新的交通方式,没有标准或规范予以指导,规划及设计体系不完善,有些已建项目已呈现问题。文章结合上海松江区规划背景及交通特征,阐述有轨电车示范线T1、T2线的布局规划、建设的必要性及适应性,为即将开展有轨电车规划及建设的城市提供借鉴与参考。     

Customizing driving cycles to support vehicle purchase and use decisions: Fuel economy estimation for alternative fuel vehicle users

Wider deployment of alternative fuel vehicles (AFVs) can help with increasing energy security and transitioning to clean vehicles. Ideally, adopters of AFVs are able to maintain the same level of mobility as users of conventional vehicles while reducing energy use and emissions. Greater knowledge of AFV benefits can support consumers’ vehicle purchase and use choices. The Environmental Protection Agency’s fuel economy ratings are a key source of potential benefits of using AFVs. However, the ratings are based on pre-designed and fixed driving cycles applied in laboratory conditions, neglecting the attributes of drivers and vehicle types. While the EPA ratings using pre-designed and fixed driving cycles may be unbiased they are not necessarily precise, owning to large variations in real-life driving. Thus, to better predict fuel economy for individual consumers targeting specific types of vehicles, it is important to find driving cycles that can better represent consumers’ real-world driving practices instead of using pre-designed standard driving cycles. This paper presents a methodology for customizing driving cycles to provide convincing fuel economy predictions that are based on drivers’ characteristics and contemporary real-world driving, along with validation efforts. The methodology takes into account current micro-driving practices in terms of maintaining speed, acceleration, braking, idling, etc., on trips. Specifically, using a large-scale driving data collected by in-vehicle Global Positioning System as part of a travel survey, a micro-trips (building block) library for California drivers is created using 54 million seconds of vehicle trajectories on more than 60,000 trips, made by 3000 drivers. To generate customized driving cycles, a new tool, known as Case Based System for Driving Cycle Design, is developed. These customized cycles can predict fuel economy more precisely for conventional vehicles vis-à-vis AFVs. This is based on a consumer’s similarity in terms of their own and geographical characteristics, with a sample of micro-trips from the case library. The AFV driving cycles, created from real-world driving data, show significant differences from conventional driving cycles currently in use. This further highlights the need to enhance current fuel economy estimations by using customized driving cycles, helping consumers make more informed vehicle purchase and use decisions.     

船舶低硫柴油系统设计的分析与优化

就新辟航线首制船“汉亚直达”集装箱船的低硫柴油系统,叙述了船舶低硫柴油系统的设计经验,从当前国内外对船用燃油硫含量的要求、应对方案到船舶低硫柴油冷却方式选择、低硫柴油冷却系统设计、高/低硫柴油转换、使用低硫柴油风险分析及处理等方面进行详细叙述,为业内同行提供参考。