以位移为基础的钢筋混凝土连续梁桥抗震设计方法

利用等效线性化方法将钢筋混凝土(RC)连续梁桥结构简化为多自由度线弹性体系,采用振型反应谱的概念研究了结构在横向地震作用下考虑多阶模态效应的直接基于位移的抗震设计方法。探讨了连续梁桥的上部结构(主梁)及桥墩(台)刚度的变化对结构横向振动模态质量与模态周期的影响,给出了多阶模态设计方法的具体设计过程。对对称与非对称连续梁桥采用相同的设计步骤进行基于位移的抗震设计,并对设计算例用非线性时程分析验证了设计结果的合理性。     

Analysis of the effectiveness of control measures to mitigate road dust emissions in a regional network

The effectiveness of control measures to reduce road dust emissions is analyzed using a year’s data of road dust emissions collected with a mobile sampling platform and a survey of road maintenance practices in the Lake Tahoe Basin of Nevada and California US. Attributes such as sweeping practices, anti-icing, shoulder improvement, pavement condition, trackout, and abrasive material from road segments were analyzed with a feature subset selection algorithm. Street sweeping was found to be an effective means of controlling dust emissions from roads. Road dust from dirty tertiary roads served as a continuous source of suspendable material for adjacent high-speed roads in the winter time. To be most effective, emission control strategies require that not only primary roads, but all roads be swept after snow storms to recover applied abrasive material.     

Fast Ferry Smoothing Motion via Intelligent PD Controller

A novel type of control law was adopted to reduce the vertical acceleration of a fast ferry as well as the motion sickness incidence suffered by the passengers onboard by means of a submerged T-foil. Considering the system changing characteristics under high disturbances, a model-free approach was adopted. In addition, an upgraded proportional-derivative (PD) controller with correction terms resulting from a fast-online estimation of the system dynamics was designed. The overall controller, known as intelligent PD (i-PD) controller, was tested, and the obtained results were compared with those of a classic PD controller. The controllers were also tested in a changing environment and at different operating velocities. The results confirmed the effectiveness of the i-PD controller to smooth the motions with low computational cost control schemes. Furthermore, thanks to ability of the i-PD controller to continually update the estimated dynamics of the system, it showed a better reduction in both vertical motions and the seasickness level of the passengers with the needed robustness under external disturbances and system changing parameters.     

深圳地铁永磁同步牵引系统研究分析

牵引传动系统是轨道交通车辆装备实现机电能量转换的“心脏”单元,其性能在某种程度上决定轨道交通车辆的动力品质、能耗和控制特性,是轨道交通车辆节能升级的关键系统。而永磁同步牵引系统以其高效率、高可靠性和低能耗的优势特点,受到轨道交通行业的密切关注。文章阐述深圳地铁10号线永磁同步牵引系统批量装车概况,重点分析永磁同步牵引系统组成及优势,指出推广应用永磁同步牵引系统的经济和社会效益显著。     

Real-Time Fault Diagnosis for Gas Turbine Blade Based on Output-Hidden Feedback Elman Neural Network

In order to remotely monitor and maintain large-scale complex equipment in real time, China Telecom plans to create a total solution that integrates remote data collection, transmission, storage, analysis and prediction. This solution can provide manufacturers with proactive, systematic, integrated operation and maintenance service, and the data analysis and health forecasting are the most important part. This paper conducts health management for the turbine blades. Elman neural network, and improved Elman neural network, i.e., outputhidden feedback (OHF) Elman neural network are studied as the main research methods. The results verify the applicability of OHF Elman neural network.     

集装箱专用平车加装承载板实现滚装运输技术研究

为弥补应急情况下滚装运输所需平车数量缺口,同时为完善车辆自身应急保障能力,分析集装箱专用平车用于滚装运输需求,针对集装箱专用平车用于滚装运输存在的主要问题,提出在不改变车体结构前提下,通过加装承载板实现滚装运输的解决思路。结合集装箱专用平车结构特点,分析承载板的数量、尺寸、材质,设计承载板由承载面、横支撑架、渡板、斜支腿、受力面、绳拴构成,给出加装改造方法,并通过校核承载能力和研究适运范围,研究加装改造后的集装箱专用平车滚装运输能力,得出改造后的集装箱专用平车可以满足大部分滚装运输货物运输需要。     

铑催化剂用水合三氯化铑的制备

水合三氯化铑是制备铑催化剂的关键原材料之一。随着化工及汽车行业的发展,对铑催化剂有了更多的需求,由此对水合三氯化铑的需求量越来越大。本文综述了当前铑催化剂的应用,以及其原材料水合三氯化铑制备技术的研究进展,并且展望了未来水合三氯化铑的制备技术。     

CT reconstruction with priori MRI images through multi-group datasets expansion

Computed tomography (CT) reconstruction with a well-registered priori magnetic resonance imaging (MRI) image can improve reconstruction results with low-dose CT, because well-registered CT and MRI images have similar structures. However, in clinical settings, the CT image of patients does not always match the priori MRI image because of breathing and movement of patients during CT scanning. To improve the image quality in this case, multi-group datasets expansion is proposed in this paper. In our method, multi-group CT-MRI datasets are formed by expanding CT-MRI datasets. These expanded datasets can also be used by most existing CT-MRI algorithms and improve the reconstructed image quality when the CT image of a patient is not registered with the priori MRI image. In the experiments, we evaluate the performance of the algorithm by using multi-group CT-MRI datasets in several unregistered situations. Experiments show that when the CT and priori MRI images are not registered, the reconstruction results of using multi-group dataset expansion are better than those obtained without using the expansion.     

Travel time estimation oriented freeway sensor placement problem considering sensor failure

Optimal sensor placement on freeway corridor is of great interest to transportation authorities. However, current traffic sensors are easily subject to various failures. Therefore, it is necessary to incorporate sensor failure into the optimal sensor placement model. In this article, a two-stage stochastic model is proposed for the purpose of travel time estimation on freeway corridor. To balance the effectiveness and reliability, a stochastic conditional value at risk (CVaR) model is also proposed. Since both models are too complicated, a customized genetic algorithm is developed. Numerical experiments show that considering sensor failure makes a significant performance improvement in the sensor placement pattern. Sensitivity analysis is also applied to investigate the impact of a number of allowable sensors and different traffic sensor failure probability.