丽香铁路黄山哨隧道下穿岩堆段设计施工关键技术

以下穿岩堆段的丽香铁路黄山哨隧道为工程依托,对岩堆段地表开裂及洞内初期支护边墙严重变形的问题进行研究。地表埋设6根测斜管监测地表位移情况,洞内布置3个断面进行围岩压力、钢架内力、二次衬砌内力、初期支护与二次衬砌间的接触压力、锚杆轴力量测。在分析现场岩堆段洞内外受力机制及原因的基础上,根据数值计算结果优化二次衬砌断面型式及进一步加大二次衬砌厚度及配筋。采取以下措施控制隧道岩堆段变形： 1）地表岩堆土石接触面开裂处增设截排水措施; 2）加大隧道初期支护钢架型号及加长岩堆侧边墙径向系统锚杆; 3）加大隧道边墙轮廓曲率并优化隧道二次衬砌型式为圆顺型; 4）隧道预留变形量加大至30 cm; 5）隧道二次衬砌内净空预留50 cm补强空间; 6）隧道拱部设置42小导管超前支护。现场岩堆段采取以上措施后已顺利施工通过,根据洞内外监测结果显示,结构在安全可控范围内。     

The value of options for time charterparty extension: an artificial neural networks (ANN) approach

The most frequently associated options in the physical shipping market are options to extend the charter period on time charters and additional shipment options on contracts of affreightment. The value of freight options, in practice, is estimated mostly by referring to forward curves. An option on freight has different properties from its financial counterparts, and the straightforward adoption of theoretical models does not produce promising results. In this paper, extension options, which have the property of options on futures, were transformed into regular European options before the application of the Black-Scholes model (BSM). The efficient market hypothesis, which justifies the parity of the performance of a long-term charter to that of repetitive short-term charters, worked as the basis for the transformation. The option values determined by the BSM were compared with actual realized values. Additionally, the artificial neural networks (ANN) was employed to derive the option values. This study is meaningful as the first-time application of both the closed-form solution and the ANN to the valuation of physical freight options. The research results can contribute to the quality of chartering decisions. The results could also be used in quantifying credit risk, as extension options tend to be granted to charterers with more creditability.     

基于HMM-SVR的船舶动力设备故障模式识别与状态预测研究

船舶动力设备因故障监测信号样本少、变化缓慢且数据特征呈非线性,使得设备故障模式的准确识别和状态预测比较难。鉴于此,文章研究了基于隐马尔科夫模型的故障模式识别方法,利用该模型将微弱变化的信号特征转换为变化较大的对数似然概率对故障模式实现有效识别。在此基础上进一步提出基于HMM-SVR的设备状态预测模型,将遗传算法用于支持向量回归模型参数寻优,并结合隐马尔科夫模型,实现对设备状态的预测。对船用柴油机进行仿真,结果表明上述模型具有较高的识别率,能准确预测船舶动力设备的当前状态。     

面向智能船舶的容错卡尔曼融合估计方法

针对智能船舶多传感器系统因未知海洋环境干扰和设备间干扰等因素导致的一个或数个传感器产生随机间歇性故障从而导致融合估计结果出现偏差甚至失真的问题,设计1种基于四分位滤波的容错方法,并针对该方法导致的观测时滞问题设计1种预报方法,提前预报观测值,进而抵消容错方法导致的时滞问题。此外,针对多传感器之间的互协方差难以准确估计的问题,采用CI融合估计方法进行融合估计。为验证算法的有效性和融合估计的精度,对带有间歇性故障的两传感器系统进行仿真试验,并与按矩阵、按对角阵和按标量3种分布式融合估计方法得到的结果进行对比。4种方法的均方误差系数大小对比结果显示,对于带间歇性故障的多传感器系统,设计的融合滤波不仅具有鲁棒性,而且具有较高的融合精度。     

全回转起重船多系统耦合运动响应仿真分析

根据运动学基本原理,计入船-吊物、船-锚链耦合影响以及起重船自身受到的外环境载荷,建立船舶多系统运动模型。利用MATLAB/Simulink软件进行仿真,对多系统耦合作用下的船舶运动进行数值分析。分别在不同的遭遇浪向角和不同的吊臂回转角下,对船舶在各自由度上的位移进行比较,得到其对船舶运动参数的影响规律。结果表明:起重船运动过程中因计入多系统耦合影响,自身运动也表现出更为符合实际的运动特性,为准确预报全回转起重船多系统的运动响应提供了更为科学的理论依据。     

可变截面涡轮增压瞬态性能仿真研究

为研究可变截面涡轮喷嘴开度对发动机的性能影响,建立GT-power和MATLB/Simulink联合仿真模型。采用GT-power软件建立的TBD234V12可变截面涡轮增压柴油机仿真模型研究发动机稳态性能,联合MATLB/Simulink软件建立的可变截面涡轮增压柴油机控制模型,对发动机瞬态性能进行仿真计算。结果表明:在发动机瞬态工况下,可变截面涡轮增压系统可以明显改善常规增压柴油机的动力性、经济性和动态响应特性,并且有效降低增压柴油机的时滞性,涡轮迟滞时间的降幅约为30%。     

考虑螺旋桨体积力的水下机器人水动力特性仿真

为在初步设计时预测ROV的水动力性能,使用CFD技术进行分析,以ROV模型为例,最大程度地保留ROV内部的构件,使模型更加接近真实状况。分别计算ROV在不同工况下的阻力、不同漂角下的横向力和转艏力矩以及添加体积力模型之后的螺旋桨流场状况,很好地模拟出ROV周围的流场,并与已有的试验数据进行对比。结果验证了CFD水动力仿真的可行性和准确性,并还可预测ROV在螺旋桨作用下的进速等,对ROV设计具有实际的参考价值和指导意义。     

里海远洋渔船无人机舱系统研究

针对我国远洋渔船装备落后、操纵性差、机舱环境恶劣、电站管理水平低、劳动强度大以及渔船机舱自动化水平低等问题,介绍里海远洋渔船无人机舱系统的设计与组成。通过采用主机遥控系统、电站功率管理系统、机舱监测报警系统以及网络通信等技术,将自动化、电气化、信息化和智能化控制技术等船舶前沿科技应用于实船,构建一个满足法国船级社(BV)机舱自动化最高等级AUT-UMS要求的无人机舱系统,以提高远洋渔船的操控性、安全性和可靠性,提升供电系统自动化管理水平,改善作业人员工作环境。对该自动化系统的效果和特点进行分析,结果可为我国远洋渔船自动化系统的研究提供策略和思路。     

Locating rental stations and bikeways in a public bike system

To determine the spatial distribution of rental stations and bikeways in a public bike system, this paper proposes a facility location and network design model. The model is developed as a multi-objective programing problem that considers four objectives (minimizing cyclist risk, maximizing cyclist comfort, minimizing adverse impacts on traffic and maximizing service coverage) and multiple constraints (monetary budget, network connectivity, station spacing, bikeway types, station number and value ranges of decision variables). The ε-constraint method solves the programing problem for the public bike system in Daan District, Taipei City, Taiwan. The nine non-dominated alternatives generated are all markedly better than existing locations of rental stations and bikeways. Scenario analysis results indicate that increasing the construction budget for bikeways significantly improves cyclist safety and comfort whilst increasing the adverse impact on traffic. Planners can use this model to develop public bike systems that spatially integrate rental stations and bikeway networks.