油田地面注水系统节能降耗对策

针对国内现有油田地面注水系统的现状,分析在役地面注水系统的能量损失,提出油田地面注水系统节能降耗的对策。主要从提高效率、节约能源的两个角度,对地面注水系统能量损失进行阐述。从选择高效率的电动机和注水泵、提高注水水质、降低管网沿程磨损等方面降低整个地面注水系统能量损耗,达到节约能源的目的。     

西福河大桥T梁架设工艺

文章以广东省道S119线西福河大桥工程施工为例,介绍采用军用六四式轻便杆件现场设计和组装双导梁架桥机跨河架设35～40mT梁的工艺技术,此技术不仅可降低架梁费用;取得较好的经济效益,而且能克服设备进场难和交通干扰等问题。     

基于Matlab／Simulink汽车驾驶员电动座椅控制系统的仿真设计

以汽车驾驶员电动座椅的水平调节为例,利用Matlab／Simuulink对具有自动调节功能的直流伺服位置控制系统的动态特性进行计算和仿真,从而确定该系统控制器的最佳控制参数的匹配。     

基于遗传支持向量机的综合管廊土建工程造价估算方法研究

综合管廊工程造价估算具有影响因素多、小样本及非线性的特点,传统的造价估算方法对于这类问题无法得到准确结果。针对这一问题,提出一种基于遗传支持向量机的综合管廊造价估算模型。分析综合管廊工程的具体特征,运用支持向量机建立工程造价与影响因子之间的非线性映射关系,利用遗传算法对支持向量机进行参数优化并对综合管廊的工程造价进行估算。以16条已建综合管廊工程作为数据库样本,对该模型进行分析验证。样本测试结果显示,利用该模型可将估算误差控制在10%以内,验证了模型估算的可行性。     

最小二乘支持向量机-粒子群算法在地下厂房围岩参数反分析中的应用

为准确确定地下厂房围岩的弹性模量、泊松比、黏聚力、内摩擦角、侧压力系数等参数,以正交设计、最小二乘支持向量机和粒子群算法等现代数学方法为基本手段,建立基于位移增量的围岩参数反分析方法。以CCS水电站大型地下厂房为研究背景,通过工程地质条件研究选取8#机组剖面作为分析对象,采用二维弹塑性有限元方法建立地质结构分析模型。以地下厂房洞室群分层开挖多点位移计实测位移增量为依据,对CCS水电站地下厂房区域围岩力学特性及地应力场特征进行反分析。研究结果表明： 主厂房第Ⅵ层与第Ⅰ层开挖和主变室第4层与第1层开挖所产生的位移增量计算值与多点位移计实测值吻合较好,最大相对误差小于10%,说明采用最小二乘支持向量机和粒子群算法相结合的反分析方法在工程上是可行的,且效果较为显著。     

Measurements of car-body lateral vibration induced by high-speed trains negotiating complex terrain sections under strong wind conditions

Assessment of the vibration of high-speed trains negotiating complex sections of terrain under strong wind conditions is very important for research into the operation safety and comfort of passengers on high-speed trains. To assess the vibration of high-speed trains negotiating complex sections of terrain under strong wind conditions, we performed a field measurement when the train passes through typical sections of complex terrain along the Lanzhou–Xinjiang high-speed railway in China. We selected the lateral vibration conditions, including the roll angle and lateral displacement of car-body gravity centre through two typical representative sections (embankment–tunnel–embankment and embankment–rectangular transition–cutting) for analysis. The results show that the severe car-swaying phenomenon occurs when the high-speed train moves through the test section, and the car-body lateral vibration characteristic is related significantly to the state of the terrain and topography along the railway. The main causes for this car-swaying phenomenon may be the transitions between different windproof structures, and the greater the scale of the transition region between different windproof structures or landform changes, the more obvious the car-swaying phenomenon becomes. The lateral vibration of the car-body is relatively steady when the train is running through terrain with minor changes in topography, such as the windbreak installed on the bridge and embankment, but the tail car sways more violently than the head car. When the vehicle runs from the windbreak installed on the embankment into the tunnel (or in the opposite direction), the tail car sways more intensely than the head car, and the head car runs relatively stable in the tunnel.     

Effect of handling characteristics on minimum time cornering with torque vectoring

In this paper, the effect of both passive and actively-modified vehicle handling characteristics on minimum time manoeuvring for vehicles with 4-wheel torque vectoring (TV) capability is studied. First, a baseline optimal TV strategy is sought, independent of any causal control law. An optimal control problem (OCP) is initially formulated considering 4 independent wheel torque inputs, together with the steering angle rate, as the control variables. Using this formulation, the performance benefit using TV against an electric drive train with a fixed torque distribution, is demonstrated. The sensitivity of TV-controlled manoeuvre time to the passive understeer gradient of the vehicle is then studied. A second formulation of the OCP is introduced where a closed-loop TV controller is incorporated into the system dynamics of the OCP. This formulation allows the effect of actively modifying a vehicle's handling characteristic via TV on its minimum time cornering performance of the vehicle to be assessed. In particular, the effect of the target understeer gradient as the key tuning parameter of the literature-standard steady-state linear single-track model yaw rate reference is analysed.     

岩石掘进机关键技术展望

经过5个阶段的发展,TBM在我国的应用正在不断推广,应用前景十分光明,挑战也十分严峻。简要总结我国TBM研究与应用的5个发展阶段和应用前景,分析TBM施工面临的6大挑战： 地质多样化带来更多的地质风险; 应用领域亟待拓展; 设备技术发展赶不上施工需求的变化; 施工进度不均衡; 施工环境越来越严苛; 存在不合理的施工合同。从TBM设计制造及施工应用的9个方面提出展望： 核心部件国产化; 提升各种地质条件下的破岩能力; 提高出渣能力及可靠性; 提升初期支护及超前加固性能; 研发异形断面TBM; 圆形断面TBM开挖隧道的空间合理利用; 大力推动TBM周转使用和再制造TBM应用; 研究极端恶劣地质条件下TBM施工技术; 促进国产配套施工设备研发应用。只有不断深入研究TBM设备与施工的关键技术及前沿技术,有效解决设备设计制造和施工过程中遇到的难题,才能不断提升我国TBM设备与施工技术水平,避免陷入关键技术受制于人的窘境,促进我国TBM事业持续健康发展。     

软土刀具的磨损预测——一种研究刀具磨损系统中主要影响因素的新方法

硬岩隧道掘进机的性能很大程度上取决于其切削刀具的磨损情况。刀具的磨损会降低掘进速度,进而导致掘进时间延长、项目成本增加。通常在隧道项目的规划阶段使用预测模型来进行磨损预测,而常规的磨损试验对磨损系统的考虑还不够准确,并没有考虑到刀具/土体的相互作用、周围介质（水、膨润土）以及掘进过程中的荷载等因素。针对该问题,专门设计了一个水平放置的磨损试验设备。本文介绍了该试验方法,研究并讨论了磨损系统相关因素对磨损率的影响。结果表明,该设备可模拟真实的掘进过程,很好地解决了上述问题,达到了高效、准确预测磨损的效果。     

基于遗传算法和极限学习机的智能算法在基坑变形预测中的应用

为解决传统智能算法网络结构参数复杂、运算速度慢等问题,基于遗传算法和极限学习机构建基坑变形的新型优化智能预测模型。先利用皮尔逊相关系数评价不同影响因素与基坑沉降变形之间的相关性,以确定极限学习机的输入层; 再采用试算法确定最优激励函数和隐层节点数,并将遗传算法和极限学习机耦合,利用遗传算法优化极限学习机的初始权值和阈值,以提高预测精度。经实例检验表明： 1)开挖时间、开挖深度、土体抗剪参数及重度均与基坑沉降变形显著相关,为构建极限学习机输入层提供了依据; 2)在预测过程中,激励函数和隐层节点数对极限学习机的预测效果具有一定的影响,以Sigmiod型激励函数和13个隐层节点数的预测效果为最优; 3)通过遗传算法的优化,能进一步提高预测精度,验证了遗传算法的优化能力和有效性。预测模型在不同工况下的预测结果均较优,说明该模型具有较高的稳定性和可靠性。