Damage detection in offshore structures using neural networks

This paper discusses the damage detection in offshore jacket platforms subjected to random loads using a combined method of random decrement signature and neural networks. The random decrement technique is used to extract the free decay of the structure from its online response while the structure is in service. The free decay and its time derivative are used as input for a neural network. The output of the neural network is used as an index for damage detection. It has been shown that function N is effective in damage detection in the members of an offshore structure. Experimental studies conducted on a reduced model for a real jacket structure with geometrical scale of 1:30 are used. The applied loads were random loads. Two different load spectra were used: White noise, and Pierson-Moskowitz.     

Improving pollutant emissions in diesel engines for heavy-duty transportation using retarded intake valve closing strategies

A combined theoretical and experimental study has been carried out to determine the real potential of reducing pollutant emissions in a HD diesel engine by means of retarding the intake valve closing. The effects produced by this alteration of the basic operation cycle have been examined by a preliminary modelling study, and from the obtained results, a modified camshaft was manufactured with a delayed intake valve closing of 60 crank angle degrees. Single-cylinder engine tests were carried out with this modified camshaft, and the emissions and fuel consumption were recorded. The results showed that the retarded intake valve closing can enhance the premixed combustion phase, and thus simultaneously reduce soot and NOx emissions. Moreover, the combustion process attained is extremely tolerant to exhaust gas recirculation, and by adoption of this measure, Euro-5 emissions limits can be achieved at the tested conditions without after-treatment.     

我依然是局外人——宝马车手库比卡专访

踏入F1的第3年，23岁的Robert Kubica就拿下个人的首胜，而且他并非是待在传统强队之中，一度成为积分的暂时领先者，跃升为祖国波兰的超级明星人物，然而他依然保持低调的风格，凡事都有着超龄的成熟度，赛季迈入一半，让他来谈谈挤进Ferrari及Mclaren的争冠集团的感想。     

Condition monitoring of wooden railway sleepers

Wooden railway sleeper inspections in Sweden are currently performed manually by a human operator; such inspections are to large extent based on visual analysis. In this paper a machine vision based approach has been considered to emulate the visual abilities of the human operator to enable automation of the process. Digital images from either ends (left and right) of the sleepers have been acquired. A pattern recognition approach has been adopted to classify the condition of the sleeper into classes (good or bad) and thereby achieve automation. Appropriate image analysis techniques were applied and relevant features such as the number of cracks on a sleeper, average length and width of the crack and the condition of the metal plate were determined. Feature fusion has been proposed in order to integrate the features obtained from each end for the classification task which follows. The effect of using classifiers like multi-layer perceptron and support vector machines has been tested and compared. Results obtained from the experiments show that multi-layer perceptron and support vector machines have achieved encouraging results, with a classification accuracy of 90%; thereby exhibiting a competitive performance when compared to a human operator.     

Adapting the light · biomass (BZI) models of phytoplankton primary production to shallow marine ecosystems

Several authors have reported a strong linear relationship between daily phytoplankton production and the product of chlorophyll biomass, photic depth, and incident irradiance for a variety of estuaries. This “light · biomass” (BZ_pI_o) formulation has been proposed as an alternative to traditional mechanistic approaches for computing phytoplankton production in numerical estuarine models. One limitation to their application in shallow systems is that the BZ_pI_o models have been developed in relatively deep estuaries where light does not reach the bottom. We propose a nonlinear correction factor to adapt the BZ_pI_o relationship to shallow systems where light does reach the bottom. Our function takes into account variations in incident irradiance, attenuation coefficient for light, photosynthetic efficiency, and maximum rate of photosynthesis. A series of correction polynomials are proposed for various ranges of incident irradiance, and are integrated into a single multiple polynomial which applies across all irradiance levels. Our new correction factor was tested against a ¹⁴C-based productivity dataset from shallow stations in Narragansett Bay, RI and an O₂-based dataset from shallow (1.1 m) lagoon mesocosms at the University of Rhode Island. Results showed that our polynomials accurately correct BZ_pI_o-predicted rates of production in shallow water columns. Application of our correction factor to a series of shallow water productivity datasets from the literature together with theoretical calculations show how significant the shallow water correction can be, especially in very shallow water columns with low turbidity.     

A note on the use of correlation coefficients for assessing goodness-of-fit in spatial interaction models

The use of correlation coefficients to evaluate the accuracy of spatial interaction models is inappropriate unless such models have been fitted using least squares techniques. In other cases the correlation involves an implicit intercept value and a regression coefficient that may significantly modify the interaction model's estimates. Researchers have not acknowledged the role of these two parameters when the correlation is used. A generalized root mean square error is proposed as an alternative indicator of accuracy that may be used with any model.     

Conditional modelling of tanker market risk using route specific freight rates

This paper provides statistical evidence in support of the view, widely held in the tanker industry, that there are systematic differences in the degree of risk involved in investing in tankers of different sizes, and in operating tankers in spot and time charter markets. The industry view, broadly supported by the results of this paper, is that larger vessels are 'risker' assets than smaller vessels, and operating vessels in the time-charter market is less risky than employing them on a spot basis. The results are obtained by using a method derived from the financial economics literature, which models both the conditional mean and variance of a variable, known as GARCH modelling. Only one other paper has applied this method to the tanker market, and these results provide confirmatory support of those findings.     

Torque characteristics analysis for optimal design of a copper-layered eddy current brake system

An enhanced parametric model for a copper-layered eddy current electric machine (retarder) is introduced in this paper. The modeled torque characteristics of the copper-layered electromagnetic retarders are based on the results from a detailed electromagnetic finite element analysis (FEA) of these eddy current machines. The model uses a parameterized double-exponential function to model the steady state speed-torque characteristics of the retarder. The parameters are adjusted for optimal braking performance in conjunction with predicted speed-torque characteristics of a copper-layered retarder. A full vehicle model, along with the proposed retarder speed-torque model has been used to simulate a series braking events. The simulation results show that the peaks of the retarder speed-torque curves must be designed to occur within a specific range of speeds for optimal braking performance.     

Optimal scheduling of the flexray static segment based on two-dimensional bin-packing algorithm

FlexRay is a reliable and hard real-time in-vehicle communication protocol that is strongly promoted by car manufacturers as the de facto standard in the automotive domain. The protocol offers both a time-triggered and an eventtriggered architecture. This paper focuses on the optimal scheduling of the time-triggered component of FlexRay known as the static (ST) segment using a two-dimensional bin-packing technique. To maximize the bandwidth utilization in the ST segment, a fast heuristic as well as an efficient integer linear programming approach are proposed. Our methods directly schedule signals into slots including frame packing, according to signal-based data scheduling and the slot/ cycle multiplexing mechanisms presented by the latest version of the FlexRay protocol. The benefits of our proposed methods are demonstrated by extensive experiments on synthetic and an automotive X-by-wire system case study. An additional test case is examined to emphasize the superior performance of the proposed approach relative to that of existing optimal scheduling approaches.     

Valuation of improved railway rolling stock: A review of the literature and new evidence

The paper provides a comprehensive review of a large amount of previously unpublished British evidence about the valuation of new railway rolling stock and its effects on demand. An important conclusion is that incentives to bias Stated Preference responses and unfamiliarity with the rolling stock being considered have led to inflated values. This has broader implications for the use of Stated Preference techniques. Also provided is fresh empirical evidence for a range of different types of rolling stock and specific rolling stock attributes. A novel aspect of the research was the use of disaggregate Revealed Preference choice data. The estimated rolling stock values are much lower than those obtained from previous studies.