Error quantification of a high-resolution coupled hydrodynamic-ecosystem coastal-ocean model: Part 2. Chlorophyll-a, nutrients and SPM

Marine systems models are becoming increasingly complex and sophisticated, but far too little attention has been paid to model errors and the extent to which model outputs actually relate to ecosystem processes. Here we describe the application of summary error statistics to a complex 3D model (POLCOMS-ERSEM) run for the period 1988–1989 in the southern North Sea utilising information from the North Sea Project, which collected a wealth of observational data. We demonstrate that to understand model data misfit and the mechanisms creating errors, we need to use a hierarchy of techniques, including simple correlations, model bias, model efficiency, binary discriminator analysis and the distribution of model errors to assess model errors spatially and temporally. We also demonstrate that a linear cost function is an inappropriate measure of misfit. This analysis indicates that the model has some skill for all variables analysed. A summary plot of model performance indicates that model performance deteriorates as we move through the ecosystem from the physics, to the nutrients and plankton.     

Quantifying uncertainty in high-resolution coupled hydrodynamic-ecosystem models

Marine ecosystem models are becoming increasingly complex and sophisticated, and are being used to estimate the effects of future changes in the earth system with a view to informing important policy decisions. Despite their potential importance, far too little attention has been, and is generally, paid to model errors and the extent to which model outputs actually relate to real-world processes. With the increasing complexity of the models themselves comes an increasing complexity among model results. If we are to develop useful modelling tools for the marine environment we need to be able to understand and quantify the uncertainties inherent in the simulations. Analysing errors within highly multivariate model outputs, and relating them to even more complex and multivariate observational data, are not trivial tasks. Here we describe the application of a series of techniques, including a 2-stage self-organising map (SOM), non-parametric multivariate analysis, and error statistics, to a complex spatio-temporal model run for the period 1988–1989 in the Southern North Sea, coinciding with the North Sea Project which collected a wealth of observational data. We use model output, large spatio-temporally resolved data sets and a combination of methodologies (SOM, MDS, uncertainty metrics) to simplify the problem and to provide tractable information on model performance. The use of a SOM as a clustering tool allows us to simplify the dimensions of the problem while the use of MDS on independent data grouped according to the SOM classification allows us to validate the SOM. The combination of classification and uncertainty metrics allows us to pinpoint the variables and associated processes which require attention in each region. We recommend the use of this combination of techniques for simplifying complex comparisons of model outputs with real data, and analysis of error distributions.     

金融危机下，导航企业怎样生存

虽然金融危机爆发已经好几个月了,但真正的危机将在2009年春节后到来,现在只不过是个“危机预热期”。在此情况下,我们的导航地图业如何保持业绩持续增长,在危机期间凸显新兴行业的潜力呢？     

Tests on ultimate strength of hull box girders made of high tensile steel

The experimental results of the collapse of three box girders subjected to pure bending moment are presented. The structures are made of high tensile steel of 690 MPa of nominal yield stress reinforced with bar stiffeners of the same material. The moment curvature curves are presented covering the pre- and post-collapse regions. The modes of collapse for each box girder are discussed considering the variation on the panel's slenderness. The concept of efficiency of high tensile steel structures is introduced. The concept is very useful to identify the governing parameters affecting the ultimate strength of 3D structures under predominant bending moment.     

Correcting injection pressure maladjustments to reduce NOX emissions by marine diesel engines

Emissions from the exhausts of marine diesel engines comprises several different gases including NO_X. These are currently regulated at the international level under Regulation 13 of ANNEX VI of MARPOL 73/78, but this regulation only applies to new engines and is based on bench tests, for only a single engine designated the “parent engine”. Here, the need to take measurements from across their whole range and once in operation on board a vessel is examined. This would not only improve assessment of new equipment against the current regulation, but would also detect defects in the functioning of the engine.     

A novel physiological index for Driver’s Activation State derived from simulated monotonous driving studies

Automobile driving in monotonous situations such as driving for long periods and/or travelling a familiar route may cause the lowering of the driver’s awareness level or what we term here as a Driver’s Activation State (DAS), resulting in an increased risk of an accident. We propose here to develop means with which to create an in-car environment so as to allow active driving, hopefully thus avoiding potentially dangerous situations. In order ultimately to develop a validated activation method, we firstly set out to examine physiological variables, including cardiovascular parameters, during simulated monotonous driving. Subsequently, we investigated the derivation of a suitable DAS index. During the experiment, a momentary electrical test stimulus of 0.5 s duration was applied at a rate of approximately once per 10 min to the subject’s shoulder to evoke a physiological responses. In 11 healthy male volunteers we successfully monitored physiological variables during the experiment and found particular patterns in the beat-by-beat changes of blood pressure in response to the electrical test stimulus. This finding, explained by autonomic activity balance, suggests that the patterns may be used as an appropriate and practicable index relevant to the Driver’s Activation State.     

Assessment of diesel combustion noise overall level in transient operation

Combustion noise in passenger cars powered with direct injection (DI) diesel engines is frequently the main reason why end-users are reluctant to drive this type of vehicle. Thus, the great potential of diesel engines for environment preservation — due to their lower CO₂ emissions — could be missed. This situation worsens with the current design trends (engine downsizing) and the emerging new diesel combustion concepts (Homogeneous Charge Compression Ignition-HCCI, Premixed Charge Compression Ignition-PCCI, etc.), which are intrinsically noisy. This negative feature can be even more critical in transient operation due to the contribution of the temporal changes of both source and transmission path on engine noise. Therefore, combustion noise must be considered as an additional essential factor in engine development, together with performance, emissions and driveability. Thus, suitable evaluation procedures that can be integrated into the global engine development process in a timely and cost-effective manner are imperative. Regarding the evaluation procedures, most of the work available in the literature addressed combustion noise at steady operation. To surpass this limitation, two possible approaches — adapted from the classical and multiple regression methods — for the overall level assessment of combustion noise in transient conditions are evaluated in this paper.     

Combustion development of a Bi-Fuel engine

Environmental improvement and energy issues are increasingly becoming more important as worldwide concerns. Natural gas is a good alternative fuel that can help to improve these issues because of its large quantity and clean burning characteristics. This paper provides the experimental performance results of a Bi-Fuel engine that uses Compressed Natural Gas as its Primary fuel and gasoline as its secondary fuel. This engine is a modification of the basic 1.4-liter gasoline engine. Generally, on the unmodified base engine, torque and power for CNG fuel are considerably lower than gasoline fuel. In this paper, the influence of fuels on wall temperature, performance and emissions are investigated.     

Modelling inter-urban transport flows in Italy: A comparison between neural network analysis and logit analysis

In the present paper a modal split problem is analysed by means of two competing statistical models, the traditional logit model and the new technique for information processing, viz. the feedforward neural network model. This study aims to explore the modal split between rail and road transport modes in Italy in relation to the introduction of a new technological innovation, the new High-Speed Train. The paper is sub-divided into two major parts. The first part offers some general considerations on the use of neural networks in the light of the increasing number of empirical applications in the specific area of transport economics. The second part describes the Italian case study by using the two above mentioned statistical models. The results highlights the fact that the two adopted models, although methodologically different, are both able to provide a reasonable spatial forecasting of the phenomenon studied. In particular, the neural network model turns out to have a slightly better performance, even though there are still critical problems inherent in its application.