Confidence bounds on structural reliability estimations for offshore platforms

Second-order estimates to measure platform reliability are generated and used to provide an additional space to select safety margins appropriate to the owner's perception or for risk-averse managers. The aleatory and epistemic uncertainties in the parameters of an offshore platform are explicitly considered in the reliability analysis and the platform structural reliability becomes a random variable, assessing then the beneficial effects of a reduction on these uncertainties. One of these benefits is for risk-aversive managers who often demand additional room to make conservative decisions regarding reliability estimations. Proposed here is a procedure to generate the frequency diagram of platform reliability with the use of confidence bounds to support reliability and cost decisions based on percentiles instead of mean values. The concepts are illustrated through a typical offshore platform in Mexico. The frequency diagram of the platform reliability index is built for several alternative designs and three levels of epistemic uncertainty. The results may be applied for decision making on new designs and also on the assessment and optimal inspection, retrofit, and decommissioning of existing platforms.     

Data-driven State-of-Charge estimator for electric vehicles battery using robust extended Kalman filter

An accurate battery State-of-Charge (SoC) estimation method is one of the most significant and difficult techniques to promote the commercialization of electric vehicles. This paper tries to make two contributions to the existing literatures through a robust extended Kalman filter (REKF) algorithm. (1) An improved lumped parameter battery model has been proposed based on the Thevenin battery model and the global optimization-oriented genetic algorithm is used to get the optimal polarization time constant of the battery model. (2) A REKF algorithm is employed to build an accurate data-driven based robust SoC estimator for a LiFePO4 lithium-ion battery. The result with the Federal Urban Driving Schedules (FUDS) test shows that the improved lumped parameter battery model can simulate the dynamic performance of the battery accurately. More importantly, the REKF based SoC estimation approach makes the SoC estimation with high accuracy and reliability, it can efficiently eliminate the problem of accumulated calculation error and erroneous initial estimator state of the SoC.     

Experimental study of the flow characteristics in an automotive HVAC system using a PIV technique

Air flow inside an automotive HVAC module was visualized using a high-resolution PIV technique with varying temperature control modes. The PIV (particle image velocimetry) system used for the experiment consisted of a 2-head Nd:YAG laser (125 mJ), a high-resolution CCD camera (2 K × 2 K), optics and a synchronizer. A real automotive HVAC module was used as a test model, and some of its casing parts were replaced with transparent windows to capture the flow images of the laser-light-sheet illumination. In addition, instant velocity fields were measured for three different temperature control modes by adjusting the temperature baffle. Characteristics of the air flow inside the automotive HVAC were then evaluated based on the time-averaged PIV data. Results from the experiment showed that flow for the warm mode loses more momentum due to its complicated flow path. Thus, the present PIV data can be used to validate numerical prediction and to improve the performance of HVAC modules.     

Development of real-world driving cycle: Case study of Pune,India

The critical component of all emission models is a driving cycle representing the traffic behaviour. Although Indian driving cycles were developed to test the compliance of Indian vehicles to the relevant emission standards, they neglects higher speed and acceleration and assume all vehicle activities to be similar irrespective of heterogeneity in the traffic mix. Therefore, this study is an attempt to develop an urban driving cycle for estimating vehicular emissions and fuel consumption. The proposed methodology develops the driving cycle using micro-trips extracted from real-world data. The uniqueness of this methodology is that the driving cycle is constructed considering five important parameters of the time–space profile namely, the percentage acceleration, deceleration, idle, cruise, and the average speed. Therefore, this approach is expected to be a better representation of heterogeneous traffic behaviour. The driving cycle for the city of Pune in India is constructed using the proposed methodology and is compared with existing driving cycles.     

A study of the Alboran sea mesoscale system by means of empirical orthogonal function decomposition of satellite data

This paper presents the results of a combined empirical orthogonal function (EOF) analysis of Advanced Very High Resolution Radiometer (AVHRR) sea surface temperature (SST) data and sea-viewing wide field-of-view sensor (SeaWiFS) chlorophyll concentration data over the Alboran Sea (Western Mediterranean), covering a period of 1 year (November 1997–October 1998). The aim of this study is to go beyond the limited temporal extent of available in situ measurements by inferring the temporal and spatial variability of the Alboran Gyre system from long temporal series of satellite observations, in order to gain insight on the interactions between the circulation and the biological activity in the system. In this context, EOF decomposition permits concise and synoptic representation of the effects of physical and biological phenomena traced by SST and chlorophyll concentration. Thus, it is possible to focus the analysis on the most significant phenomena and to understand better the complex interactions between physics and biology at the mesoscale. The results of the EOF analysis of AVHRR-SST and SeaWiFS-chlorophyll concentration data are presented and discussed in detail. These improve and complement the knowledge acquired during the in situ observational campaigns of the MAST-III Observations and Modelling of Eddy scale Geostrophic and Ageostrophic motion (OMEGA) Project.     

Capitalization of BRT network expansions effects into prices of non-expansion areas

A before and after hedonic model is used to determine the property value impacts on properties already served by the transit system caused by extensions to Bogotá’s bus rapid transit system. Asking prices of residential properties belonging to an intervention area (N = 1407 before, 1570 after) or a control area (N = 267 before, 732 after) and offered for sale between 2001 and 2006 are used to determine capitalization of the enhanced regional access provided by the extension. Properties offered during the year the extension was inaugurated and in subsequent years have asking prices that are between 13% and 14% higher than prices for properties in the control area, after adjusting for structural, neighborhood and regional accessibility characteristics of each property. Furthermore, the appreciation is similar for properties within 500 m and properties between 500 m and 1 km of the BRT.     

可提高能量再生效率的锂离子充电电池

近30多年来,再生制动系统已为电动车组降低能耗做出了极大贡献.然而,这种系统还存在许多问题,如再生能被车轮滑行和拖车电压抵消,在高速范围电制动力降低,供电电路阻抗限定了再生功率.为了利用和循环利用制动能,确保稳定的再生荷载,我们选用锂离子电池来储能,开发出锂离子充电电池(600V系统),作为重要的替换方法之一用于电动车组.阐述了使用锂离子充电电池、能量再利用的无接触导线电车,展示了电车性能和电池特性.并表明,开发中的电池在能量和功率密度、效率、500A充电和放电电流、内部电阻和维护等各方面都有极好的性能.     

旅客信息系统的现状与未来

有轨运输的旅客信息系统广泛使用了信息和通信技术.这种系统既用于地面,例如站台上,又用于移动的列车中.技术的不断发展为显示、计算机和通信开辟了新的功能和应用场合.继续发展的这些技术,给旅客信息系统提供了有利于铁路运营部门和旅客的新功能.德国铁路公司的403/406/411和415/605型车辆使用了最现代化的旅客信息系统,文章以该系统为例介绍这种移动应用的技术现状以及由于技术进步提供的新应用情况.     

异步电机用随机定位空间矢量PWM降低开关噪声

任意脉宽调制(RPWM)是用来将电压、电流谐波扩展到宽频率范围的开关技术.通过任意改变逆变器开关频率,可以将电磁声频噪声的功率频谱扩展到宽带区.与窄带噪声相比,宽带噪声给人们带来的不适和干扰较小.因而,在逆变驱动系统中,RPWM作为一种能降低声频噪声的极好途径,正在引起研究人员的注意.文章提出并实现了一种新型的任意定位空间矢量PWM(RPPWM)技术.在每一个开关周期内,三相脉冲均可以任意定位.采用一个C167微控制器就能够实现PWM脉冲的任意定位和空间矢量调制.仿真和试验结果表明,通过应用一种新的RPPWM技术,可以将电压、电流谐波扩展到宽带区,从而降低开关声频噪声.