印度孟买采用双电流制电动车组

介绍了印度盂买双电流制电动车组的结构特点及主要的技术参数。     

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.     

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%).     

Evolving the subspace of the three-dimensional multiscale ocean variability: Massachusetts Bay

A data and dynamics driven approach to estimate, decompose, organize and analyze the evolving three-dimensional variability of ocean fields is outlined. Variability refers here to the statistics of the differences between ocean states and a reference state. In general, these statistics evolve in time and space. For a first endeavor, the variability subspace defined by the dominant eigendecomposition of a normalized form of the variability covariance is evolved. A multiscale methodology for its initialization and forecast is outlined. It combines data and primitive equation dynamics within a Monte-Carlo approach.The methodology is applied to part of a multidisciplinary experiment that occurred in Massachusetts Bay in late summer and early fall of 1998. For a 4-day time period, the three-dimensional and multivariate properties of the variability standard deviations and dominant eigenvectors are studied. Two variability patterns are discussed in detail. One relates to a displacement of the Gulf of Maine coastal current offshore from Cape Ann, with the creation of adjacent mesoscale recirculation cells. The other relates to a Bay-wide coastal upwelling mode from Barnstable Harbor to Gloucester in response to strong southerly winds. Snapshots and tendencies of physical fields and trajectories of simulated Lagrangian drifters are employed to diagnose and illustrate the use of the dominant variability covariance. The variability subspace is shown to guide the dynamical analysis of the physical fields. For the stratified conditions, it is found that strong wind events can alter the structures of the buoyancy flow and that circulation features are more variable than previously described, on multiple scales. In several locations, the factors estimated to be important include some or all of the atmospheric and surface pressure forcings, and associated Ekman transports and downwelling/upwelling processes, the Coriolis force, the pressure force, inertia and mixing.     

Fatigue features extraction of road load time data using the S-transform

This paper presents the algorithm development of a new fatigue data editing technique using S-T approach. In general, the S-transform (S-T) is a time-frequency spectral localization method which performs a multi-resolution analysis on signal. This method represents a better time-frequency resolution especially for non-stationary signal analysis. This technique was developed to produce shortened fatigue data for fatigue durability testing. The S-T method was applied to detect the damaging events contained in the fatigue signals due to high S-T spectrum location. The damaging events were extracted from an original fatigue signal to produce the shortened edited signal which has equivalent fatigue damage. Three types of road load fatigue data were used for simulation purpose, pave track, highway and country road. In this study, an algorithm was developed, to detect the damaging events in the original fatigue signal. The algorithm can be used to extract the fatigue damaging events and these events were combined in order to produce a new edited signal which neglect the low amplitude cycles. The edited signal consists of the majority of the original fatigue damage in the shortened signal with 15–25% time reduction. Thus, it has been suggested that this shortened signal can then be used in the laboratory fatigue testing for the purpose of accelerated fatigue testing.     

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.     

Determinants of the damage cost and injury severity of ferry vessel accidents

This study investigates determinants of the property damage cost and injury severity of ferry vessel accidents. Detailed data of individual ferry vessel accidents for the 11-year timeperiod 1991–2001 that were investigated by the U.S. Coast Guard are used to estimate ferry-vessel accident property damage cost and injury severity equations. Tobit regression is used to estimate the former equation and the ordered probit model is used to estimate the latter. Property damage costs include damage costs to the vessel itself, its cargo and contents, and other-property damage (e.g., damage to pier structures and waterfront facilities). Injury severity for a ferry vessel accident is measured as an ordinal variable — no injuries, non-fatal injuries and fatal injuries. Damage cost and injury severity of individual ferry vessel accidents are expressed as functions of the type of vessel accident, vessel characteristics, vessel operation phase, weather/visibility conditions, type of waterway, type of vessel propulsion, type of vessel hull construction and cause of vessel accident. The property damage estimation results suggest that allision, collision and fire ferry vessel accidents incur more vessel property damage cost per vessel gross ton than other types of accidents. The injury severity estimation results suggest that injury severity is greater when the ferry vessel accident is caused by human error as opposed to vessel and environmental factors.     

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.     

Large-scale physical controls on phytoplankton growth in the Irminger Sea Part I: Hydrographic zones, mixing and stratification

Hydrographic surveys in three consecutive seasons in the Irminger Sea in 2001/2002 have revealed six physical regimes (zones) in which different surface mixing and spring re-stratification processes dominate. They are the South Irminger Current, the North Irminger Current, the Central Irminger Sea, the Polar-origin East Greenland Current, the Atlantic-origin East Greenland Current and the Reykjanes Ridge. The variations in restratification processes in particular have significant implications for the timing of shallow spring mixed layer development and therefore the timing and strength of the spring bloom. The relative roles of heat and freshwater in controlling re-stratification are examined for each hydrographic zone, and it is shown that the simplest concept of solar warming generating spring stratification is appropriate for the Irminger Current and the central Irminger Sea. However in the East Greenland Current and the Reykjanes Ridge zones, the springtime arrival of fresh or saline water at the surface dominates re-stratification and generates the earliest and strongest spring blooms of the region. In the cool fresh centre of the Irminger Sea the relatively low chlorophyll-a throughout the year cannot be wholly explained by stratification or nutrient concentrations. Details of the annual cycle in temperature, salinity, chlorophyll-a and nutrients are presented for each hydrographic zone.