Options-Based Multi-Objective Evaluation of Product Platforms

A platform is the set of elements and interfaces that are common to a family of products. Design teams must choose among feasible platform concepts upon which a product family could be based, often involving new technologies. Multiple performance objectives need to be considered. A standard approach is to convert the performance outcomes into financial figures, which can then be weighed against the required investments. However, it is not always possible to transform performance outcomes (benefits) into monetary terms, such as in defense or highly technical projects. A multi-objective form of real-options-based platform selection is developed. Systems are compared based on multiple technical and economic goals, incorporating uncertainty by representing the unknown factors during the subsequent development process with probability distributions. The range of uncertain outcomes is integrated into single expected measures of effectiveness, which can then be applied to select the most appropriate platform and set of support product variants. An application to the design of platform-based families of naval high-speed ships is shown.     

The role of cities in achieving the EU targets on biofuels for transportation: The cases of Berlin,London, Milan and Helsinki

Road transportation is a strongly growing source of CO₂, and use of biofuels represents one option to reduce end-of-pipe emissions of the existing car fleet. In this contribution, the implementation of the EU Biofuels Directive (2003/30/EC) and related voluntary measures at the local level are examined in Germany, UK, Italy and Finland and the cities of Berlin, London, Milan and Helsinki. Even though they are not directly involved in the implementation of the biofuel directive, all four cities studied have played an important role in emissions reduction by voluntarily participating in research and demonstration projects and by using biofuels in their own fleet. An analysis of the numerous causes and driving forces leading to different local level measures is provided. The environmental sensitivity, usually examined at national level, and the national level implementation of the EU Biofuels Directive (2003/30/EC) were not directly correlated with the city-level activities Instead, support from local businesses and acquisition of EU funds were considered to be valid explanatory factors for the city-level activities. In addition, through horizontal networking cities are starting to exchange know-how gained in their projects, contributing in this way to the accumulation of experience for future policies and technologies.     

A return period based plastic design approach for ice loaded side-shell/bow structures

Based on the design ice load that corresponds to a certain return period, a practical approach for designing the frames behind the side-shell or the bow of a ship subject to ice loading is proposed. Four typical types of section profiles have been selected for modelling and numerical analysis. Non-linear finite element analyses that involve both the geometric and material non-linearity were performed. From the analyses, the relationships between the loads and the beam's cross-section properties were obtained for different permanent set requirements. These relationships were then used for finding the section modulus from which the cross-section of the beam can be decided. Finally, a design example is presented for illustration.     

Lane change algorithm for autonomous vehicles via virtual curvature method

This paper addresses the lane changing problem of autonomous vehicles when there is no road infrastructure support. The autonomous vehicle should drive from the current lane to the adjacent lane in the absence of a reference path to guide the vehicle to the new lane. We suggest an algorithm that incorporates a virtual road curvature with bicycle model for lane change guidance. As the name suggests, the virtual road curvature does not physically exist. It is a user assigned radius of a curved path which connects the current lane to the adjacent lane. Since the lateral sensor readings during lane changing maneuver are erroneous, the steering angle along with the virtual curvature is fed into a bicycle model to estimate the lateral position during the transition to the next lane. Details of the algorithm and the virtual road curvature determination are presented in the paper. In contrast to other lane changing methods, controller switching is not required and the same controller is for both lane keeping and lane changing. The algorithm is verified experimentally and the results are comparable with lane changing with physical transition lane.     

美国铁路客车的发展动向与水平

文章阐述了美国地铁、高速列车等轨道车辆的发展水平、动态,以及铁道车辆市场现状。介绍了美国针对铁路事故而开展提高车辆强度、抗碰撞能力的研究及取得的成果。     

Estimation of air–sea CO2 fluxes in the Bay of Biscay based on empirical relationships and remotely sensed observations

An empirical algorithm has been developed to compute the sea surface CO₂ fugacity (fCO₂^sw) in the Bay of Biscay from remotely sensed sea surface temperature (SST_RS) and chlorophyll a (chl a_RS) retrieved from AVHRR and SeaWiFS sensors, respectively. Underway fCO₂^sw measurements recorded during 2003 were correlated with SST_RS and chl a_RS data yielding a regression error of 0.1 ± 7.5 µatm (mean ± standard deviation). The spatial and temporal variability of air–sea fCO₂ gradient (ΔfCO₂) and air–sea CO₂ flux (FCO₂) was analyzed using remotely sensed images from September 1997 to December 2004. An average FCO₂ of ? 1.9 ± 0.1 mol m^? 2 yr^? 1 characterized the Bay of Biscay as a CO₂ sink that is suffering a significant long-term decrease of 0.08 ± 0.05 mol m^? 2 yr^? 2 in its capacity to store atmospheric CO₂. The main parameter controlling the long-term variability of the CO₂ uptake from the atmosphere was the air–sea CO₂ transfer velocity (57%), followed by the SST_RS (10%) and the chl a_RS (2%).     

Improving assimilation of SeaWiFS data by the application of bias correction with a local SEIK filter

Ocean-biogeochemical models show typically significant errors in the representation of chlorophyll concentrations. The model state can be improved by the assimilation of satellite chlorophyll data with algorithms based on the Kalman filter. However, these algorithms do usually not account for the possibility that the model prediction contains systematic errors in the form of model bias. Accounting explicitly for model biases can improve the assimilation performance. To study the effect of bias estimation on the estimation of surface chlorophyll concentrations, chlorophyll data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) are assimilated on a daily basis into the NASA Ocean Biogeochemical Model (NOBM). The assimilation is performed by the ensemble-based SEIK filter combined with an online bias correction scheme. The SEIK filter is simplified here by the use of a static error covariance matrix. The performance of the filter algorithm is assessed by comparison with independent in situ data over the 7-year period 1998–2004. The bias correction results in significant improvements of the surface chlorophyll concentrations compared to the assimilation without bias estimation. With bias estimation, the daily surface chlorophyll estimates from the assimilation show about 3.3% lower error than SeaWiFS data. In contrast, the error in the global surface chlorophyll estimate without bias estimation is 10.9% larger than the error of SeaWiFS data.     

Propagation and origin of warm anomalies in the Angola Benguela upwelling system in 2001

Warmer than average sea surface temperatures were observed by the Tropical Rainfall Mission Microwave Imager in the Angola Benguela Current system in late austral summer 2001 and persisted for about three months. These coastal anomalies extended offshore by 1 to 4° longitude and were not due to local ocean atmosphere interaction or relaxation of the upwelling favorable southerly winds. Instead, they were remotely forced by ocean atmosphere interaction in the Tropical Atlantic. Satellite remote sensing and a linear ocean model suggest that relaxation of trade winds along the equator triggered Kelvin waves that crossed the basin within a month in early 2001. Westerly wind anomalies were also observed in December 2000 and January 2001 over most of the Tropical Atlantic contributing to a warm preconditioning due to an enhancement of the oceanic annual cycle. This led to abnormal sea level heights near equatorial Africa that propagated southwards along the coast towards the Angola Benguela Frontal zone. This process increased the seasonal penetration of warm and salty water of tropical origin into the Angola Benguela upwelling system.     

A Mean Dynamic Topography of the Mediterranean Sea computed from altimetric data, in-situ measurements and a general circulation model

In the Mediterranean Sea, where the mean circulation is largely unknown and characterized by smaller scales and less intensity than in the open ocean, the interpretation of altimetric Sea Level Anomalies (SLA) is rather difficult. In the context of operational systems such as MFS (Mediterranean Forecasting System) or MERCATOR, that assimilate the altimetric information, the estimation of a realistic Mean Dynamic Topography (MDT) consistent with altimetric SLA to be used to reconstruct absolute sea level is a crucial issue. A method is developed here to estimate the required MDT combining oceanic observations as altimetric and in-situ measurements and outputs from an ocean general circulation model (OGCM).In a first step, the average over the 1993–1999 period of dynamic topography outputs from MFS OGCM provides a first guess for the computation of the MDT. Then, in a second step, drifting buoy velocities and altimetric data are combined using a synthetic method to obtain local estimates of the mean geostrophic circulation which are then used to improve the first guess through an inverse technique and map the MDT field (hereafter the Synthetic Mean Dynamic Topography or SMDT) on a 1/8° resolution grid.Many interesting current patterns and cyclonic/anticyclonic structures are visible on the SMDT obtained. The main Mediterranean coastal currents are well marked (as the Algerian Current or the Liguro–Provenço–Catalan Current). East of the Sicily channel, the Atlantic Ionian Stream divides into several main branches crossing the Ionian Sea at various latitudes before joining at 19°E into a unique Mid-Mediterranean Jet. Also, strong signatures of the main Mediterranean eddies are obtained (as for instance the Alboran gyre, the Pelops, Ierapetra, Mersa-Matruh or Shikmona anticyclones and the Cretan, Rhodes or West Cyprius cyclones). Independent in-situ measurements from Sea Campaigns NORBAL in the North Balearic Sea and the North Tyrrhenian Sea and SYMPLEX in the Sicily channel are used to validate locally the SMDT: deduced absolute altimetric dynamic topography compares well with in-situ observations. Finally, the SMDT is used to compute absolute altimetric maps in the Alboran Sea and the Algerian Current. The use of absolute altimetric signal allows to accurately follow the formation and propagation of cyclonic and anticyclonic eddies in both areas.     

Effective arterial road incident detection: A Bayesian network based algorithm

Timely and accurate incident detection is an essential part of any successful advanced traffic management system. The complex nature of arterial road traffic makes automated incident detection a real challenge. Stable performance and strong transferability remain major issues concerning the existing incident detection algorithms. A new arterial road incident detection algorithm TSC_ar is presented in this paper. In this algorithm, Bayesian networks are used to quantitatively model the causal dependencies between traffic events (e.g. incident) and traffic parameters. Using real time traffic data as evidence, the Bayesian networks update the incident probability at each detection interval through two-way inference. An incident alarm is issued when the estimated incident probability exceeds the predefined decision threshold. The Bayesian networks allow us to subjectively build existing traffic knowledge into their conditional probability tables, which makes the knowledge base for incident detection robust and dynamic. Meanwhile, we incorporate intersection traffic signals into traffic data processing. A total of 40 different types of arterial road incidents are simulated to test the performance of the algorithm. The high detection rate of 88% is obtained while the false alarm rate of the algorithm is maintained as low as 0.62%. Most importantly, it is found that both the detection rate and false alarm rate are not sensitive to the incident decision thresholds. This is the unique feature of the TSC_ar algorithm, which suggests that the Bayesian network approach is advanced in enabling effective arterial road incident detection.